climate vulnerability and resilience in the blue river
TRANSCRIPT
Climate vulnerability and resilience in the Blue River watershed in metro Kansas City
Prepared for:
Mid-America Regional Council
Federal Highway Administration
Date:
Prepared by:
Tom Jacobs, Mid-America Regional Council
Notice: This report was developed by the Mid-America Regional Council in accordance with a grant from the Federal Highway Administration (FHWA). The statements, findings, conclusions, and recommendations are those of the authors and do not necessarily reflect the views of FHWA or the U.S. Department of Transportation.
Technical Report Documentation Page 1. Report No. 2. Government Accession No. 3. Recipient’s Catalog No. 4. Title and Subtitle Blue River Watershed Modeling Report
5. Report Date 08/31/2020 6. Performing Organization Code:
7. Author(s) Stacy Hutchinson, Kansas State University Kelsey McDonough, University of Newcastle Jessica Stanton, Kansas State University Victoria Thomas, Kansas State University
8. Performing Organization Report No.
9. Performing Organization Name and Address Tom Jacobs, Alecia Kates, and Joe Gauer Mid-America Regional Council 600 Broadway Boulevard, Suite 200 Kansas City, MO 64105
10. Work Unit No. 11. Contract or Grant No.
12. Sponsoring Agency Name and Address Federal Highway Administration 1200 New Jersey Avenue, SE Washington, DC 20590
13. Type of Report and Period Pilot Final Report 14. Sponsoring Agency Code
15. Supplementary Notes 16. Abstract
The Mid-America Regional Council (MARC), in partnership with Kansas State University (KSU), Johnson County, Kansas (JOCO) and Kansas City, Missouri (KCMO), used FHWA's Vulnerability Assessment Framework (Framework) to assess how potential changes in extreme precipitation may affect the transportation system in the Blue River Watershed.
Three key goals defined this effort:
1. Apply the Framework to the Blue River Key watershed, using modeling techniques to evaluate risks, vulnerabilities and potential mitigation strategies associated with flooding and stream stability and their effects on transportation infrastructure.
2. Incorporate a resilience lens into the emerging “one water” Blue River watershed plan and the Metropolitan Transportation Plan (MTP), and inform the intersection of regional transportation and water resource management plans and policies through integrated, cross-sector, multi-benefit approaches to mitigation.
3. Create a replicable pilot project that will support resilience planning throughout the Kansas City region, and in other inland riverine environments across the country.
17. Key Words Watershed planning, climate adaptation and mitigation, resilience, green infrastructure, Kansas City
18. Distribution Statement No restrictions.
19. Security Classif. (of this report) Unclassified
20. Security Classif. (of this page) Unclassified
21. No. of Pages 94
22. Price
Form DOT F 1700.7 (8-72) Reproduction of completed page authorized.
Overview
I. Description of the Proposed Effort Purpose, description and goals:
The Mid-America Regional Council (MARC), in partnership with Kansas State University (KSU), Johnson County, Kansas (JOCO) and Kansas City, Missouri (KCMO), used FHWA's Vulnerability Assessment Framework (Framework) to assess how potential changes in extreme precipitation may affect the transportation system in the Blue River Watershed.
Three key goals defined this effort:
1. Apply the Framework to the Blue River Key watershed, using modeling techniques to evaluate risks, vulnerabilities and potential mitigation strategies associated with flooding and stream stability and their effects on transportation infrastructure. 2. Incorporate a resilience lens into the emerging “one water” Blue River watershed plan and the Metropolitan Transportation Plan (MTP), and inform the intersection of regional transportation and water resource management plans and policies through integrated, cross-sector, multi-benefit approaches to mitigation. 3. Create a replicable pilot project that will support resilience planning throughout the Kansas City region, and in other inland riverine environments across the country.
II. Project background and partnerships Mid-America Regional Council (MARC, Kansas City’s regional and metropolitan planning organization) and Kansas State University collaborated on the implementation of this initiation. MARC led the project team, facilitated partner and stakeholder engagement, lead planning and policy development efforts, and conducted community outreach and education. Kansas State University (KSU) led technical analysis and modeling for quantitative vulnerability assessment. Key community partners and stakeholders included Johnson County, Kansas; the city of Kansas City, Missouri; and multiple area nonprofit organizations.
III. Project process Project analysis and findings were interwoven through four separate but interrelated planning processes. These included the regional transportation plan, the regional hazard mitigation plan, the regional climate action plan, and the Integrated Blue River Watershed Feasibility Study. At the outset, the latter study was projected to be a key lever for advancing study outcomes. However, project partners determined that it was not necessary to advance the watershed study at this time.
During the entire course of the project, stakeholders were involved in project scoping, analysis, review of findings, and consideration of applications and next steps. These discussions were held at the watershed feasibility overview committee, the Water Resources Committee of the American Public Works (APWA) – Kansas City Chapter, and the MARC Total Transportation Policy Committee, Sustainable Places Policy Committee, and Green Infrastructure Advisory Committee.
After KSU analysis was completed, MARC had intended to convene a four-hour community workshop to present project findings and evaluate implications, applications and potential next steps. Because of the pandemic, however, MARC convened two one-hour online presentations and discussions to accomplish that goal. Approximately 90 participants participated in these two events. More importantly, interest in continuing the conversation resulted in four additional online Zoom discussions about issues of climate adaptation, resilience and environmental justice.
IV. Project outcomes A range of notable process and substantive outcomes resulted from the project.
Analytical methods
From a methodological perspective, KSU analysis demonstrated how common hydrological modeling procedures may be modified to account for climate change. Common assumptions about the frequency, intensity and duration of storm events are likely to shift. While downscaled climate data reflects the probability of shorter duration and higher intensity storms, changes in the frequency of in future precipitation events, and storm “stacking” over multi-day periods, the lack of temporal resolution in future predicted climate data (e.g. daily data) may result in missing the true impact of higher intensity storms.
In addition to shifts in hydrological modeling assumptions, future watershed analysis will require a shift from a wholly empirical basis to one that incorporates projected precipitation regimes using evolving downscaled modeling approaches. Further, the discipline will benefit from shifting from a focus on discrete design storms to an approach guided by risk assessment and mitigation.
Watershed management and green infrastructure
Analysis of alternative land use and development scenarios demonstrated two key findings, which reiterate conclusions from multiple studies in Kansas City and nationally over an extended time frame. The study found the connected riparian corridors and the disconnection of impervious areas throughout the watershed create meaningful reductions in peak flows. While the study did not address water quality or geomorphological analysis, it can be reasonably projected that these measures would create substantial benefits in those regards as well.
Stakeholder conversations highlighted the need for riparian conservation and restoration measures, especially in upper watershed areas. Further, ongoing discussions with the American Public Works Association (APWA) and local government partners reflect a strong interest in revising area stormwater engineering standards and best management practice design to address these issues. The APWA committee recently completed a vision and principles document to guide this process. The document reflects a commitment to resilience and watershed-based approaches, highlight issues of risk, community value and natural resource stewardship. MARC/APWA work will facilitate new site-level planning and design recommendations embedded in a watershed-based understanding that complements this study’s findings related to riparian system connectivity and impervious disconnections.
Embedding climate adaptation in regional planning
The regional transportation and hazard mitigation plans were each completed during the process of completing this study. Multiple conversations with planning stakeholders enabled preliminary project findings to be shared as those plans were advanced. Given that this project had not yet completed its analysis when the other plans were being finalized, the integration of adaptation and resilience into other planning efforts andwill continue in future plans.
The newly adopted Connected KC 2050 metropolitan transportation plan highlights climate protection and resilience as one of five overarching strategies. The plan specifically highlights nature-based solutions and green infrastructure strategies as notable resilience strategies. Further, from a transportation programming perspective, a green infrastructure criterion is applied for transportation project review and selection. Projects address this issue through variable strategies including green and complete streets, multi-purpose greenways, right-of-way management, native landscaping, riparian restoration and other stormwater best management practices.
The Regional Hazard Mitigation Plan addressed key natural hazards, including key climate risks associated with flooding, drought and extreme heat. The plan recognizes the evolving nature of these threats due to climate change, recommending, for instance, that communities consider management of the 500-year floodplain. New collaborations among emergency managers and infrastructure planners and designers reflect a growing understanding of how proactive adaptation and mitigation measures increase both emergency preparedness and community resilience.
The Regional Climate Action Plan, which is anticipated to be completed in December 2020, recognized threats from extreme weather in its climate risk and vulnerability assessment. Green infrastructure is widely recognized by community stakeholders as the “low-hanging fruit” of climate adaptation and resilience. As such, stakeholder feedback has reiterated community support for robust green infrastructure implementation strategies such as urban forestry, stream and riparian restoration, and native landscaping. Importantly, many of these measures have been linked to strategies for food security, public health and environmental justice.
Each of these plans takes an increasingly holistic and integrated approach. The pandemic has highlighted the interrelated nature of water resource management concerns with issues of health and social equity. Future efforts will clearly focus on the intersection of these issues in pursuit of regional sustainability and resilience goals.
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Table of Contents
Executive Summary ..................................................................................................................................... 11
Key Findings ........................................................................................................................................... 11 General Trends .................................................................................................................................. 11 Riparian Buffer Importance ............................................................................................................... 11 Impact of Land Development ............................................................................................................ 12 Green Infrastructure Assessment ...................................................................................................... 13 Summary of Scenario Findings .......................................................................................................... 14
Study Motivation ........................................................................................................................................ 14 Study Area ................................................................................................................................................... 15 Model Development ................................................................................................................................... 23
Input Datasets ........................................................................................................................................ 23
Calibration and Validation ..................................................................................................................... 29
Calibration and Validation Results ......................................................................................................... 31 Scenario Modeling ...................................................................................................................................... 34
Precipitation ........................................................................................................................................... 37
Analysis Locations .................................................................................................................................. 47
Scenario BRW1 ....................................................................................................................................... 49 Scenario BRW1A................................................................................................................................ 49 Scenario BRW1B ................................................................................................................................ 50 Scenario BRW1C ................................................................................................................................ 51 Scenario BRW1D ............................................................................................................................... 53 Scenario BRW1E ................................................................................................................................ 54
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Scenario BRW2: Conversion of the Riparian Buffer to Managed Green Space ..................................... 56
Scenario BRW3: Restoration of Riparian Buffer of All Streams
(Including Ephemeral) .................................................................................................................... 58
Scenario BRW5: Restoration of the Riparian Buffer of Main Channels ................................................. 60
Scenario BRW6: Transportation Outlook (TO) 2040- Forecasted Fully Developed ............................... 63
Scenario BRW7: TO 2040 with Adapted Land Use Recommendation ................................................... 66
Scenario BRW 8A: TO 2040 with Adapted Land Use Recommendation and Restoration of the Riparian Corridor ...................................................................................... 69
Scenario BRW8B: TO 2040 with Forecasted Land Use and Restoration
of the Riparian Corridor ................................................................................................................. 69
Scenario BRW9A: TO 2040 with Adapted Land Use Recommendation and Restoration of the Riparian Corridor and Conservation Development .................................. 69
Scenario BRW9B: TO 2040 with Forecasted Land Use and Restoration
of the Riparian Corridor and Development Max in Outer Buffers................................................. 70
Tomahawk Creek Scenarios ................................................................................................................... 70
Summary of Scenarios............................................................................................................................ 71 Discussion.................................................................................................................................................... 73
General Trends ....................................................................................................................................... 73
Hydrologic Trends .................................................................................................................................. 73
Geographic Trends ................................................................................................................................. 74
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Scenario Trends ...................................................................................................................................... 75
Scenario BRW2: Conversion of Riparian Buffer to Managed Green Space ....................................... 75
Scenario BRW3: Riparian Buffer Restoration of All Streams
(Including Ephemeral) .................................................................................................................... 76
Scenario BRW5: Riparian Buffer Restoration of Main Channels ....................................................... 77
Scenarios Defined by MARC’s Transportation Outlook 2040: BRW- 1E, 6, 7, 8A, 8B, 9A, 9B ......................................................................................................... 78
Land Development Trends ..................................................................................................................... 83
Riparian Buffers ................................................................................................................................. 83
MARC Adapted Land Use Recommendation..................................................................................... 85
Conclusions ................................................................................................................................................. 91
General Scenario Review ....................................................................................................................... 91
Development .......................................................................................................................................... 91
Policy.. .................................................................................................................................................... 91
References .................................................................................................................................................. 93
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List of Figures
Figure 1. The Blue River Watershed is a tributary to the Missouri River with parts in both Kansas and Missouri. The main stream channel is shown in blue (Thomas, 2020). ........................................................................................................................ 15
Figure 2. The Blue River Watershed has area in five counties, overlapping
twenty cities (MARC, 2010). ..................................................................................................... 16 Figure 3. The BRW intersects four U.S. EPA Level IV ecoregions
(U.S. EPA, 2013). ....................................................................................................................... 17 Figure 4. Land use/land cover in the Blue River Watershed from the 2011 National Land
Cover Dataset (Homer et al., 2011). ......................................................................................... 18 Figure 5. Tomahawk creek watershed is located in the center of the BRW. ........................................... 19 Figure 6. Tomahawk Creek Watershed landcover is largely suburban development with
golf courses and light industrial mix. ........................................................................................ 20 Figure 7. Average percent imperviousness in Tomahawk Watershed along with
assessment locations ................................................................................................................ 21 Figure 8. Location of the USGS stream gauges in the Blue River Watershed. ......................................... 28 Figure 9. Continuous calibration/validation results throughout the Blue River Watershed
at a) J06893080, b) J06893100, c) J06893350, d) J06893300, e) J06893500, f) J06893578. ............................................................................................................................. 31
Figure 10. Peak and total inflow are monitored at three locations (J17, J06893350,
and J27) in the Tomahawk Creek Watershed. .......................................................................... 37 Figure 11. The correlation (ρ) between the monthly total GCM precipitation and historical,
observed precipitation from NOAA on a location basis. .......................................................... 40 Figure 12. The correlation (ρ) between the monthly maximum GCM precipitation and
historical, observed precipitation from NOAA on a location basis. .......................................... 40 Figure 13. The correlation (ρ) between the monthly total GCM precipitation and historical,
observed precipitation from NOAA for each of the 7 significant GCMs.. ................................. 41
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Figure 14. The correlation (ρ) between the monthly maximum GCM precipitation and historical, observed precipitation from NOAA for each of the 7 significant GCMs.. ................................. 42
Figure 15. Taylor diagram illustrating the overall validation performance by location of the
NOAA precipitation station. All GCMs were comparable across locations, with the exception of the Merriam OP location which showed poorer validation performance. ......... 43
Figure 16. Taylor diagram illustrating the overall validation performance of each of the seven
selected models. Model performance was comparable, though GDO_CCSM4, GDO_MRI.CGCM3, and GDO_NorESM1.M demonstrate better validation performance overall.................................................................................................................. 44
Figure 17. NCEI (NOAA) observed monthly precipitation for the year 1950 at the Downtown
Airport Location and the projected precipitation by the 7 selected GCMs. ............................. 45 Figure 18. NCEI (NOAA) observed monthly precipitation for the year 2001 at the Downtown
Airport Location and the projected precipitation by the 7 selected GCMs. ............................. 46 Figure 19. Peak and total inflow are monitored at three locations (J17, J06893350, and J27)
in the Tomahawk Creek Watershed. ........................................................................................ 48 Figure 20. Scenario BRW1B required the integration of a 300-foot buffer around
main channels, which are represented by the model conduit network. ................................. 49 Figure 21. The updated subcatchment layer includes the new, 300-foot riparian
buffer surrounding the stream corridor (yellow). The dashed, blue line shows the updated flow path of the subcatchment through the riparian corridor subcatchment to the outlet. ...................................................................................... 50
Figure 22. Scenario BRW1C required the addition of a 300-foot buffer around the
National Hydrography Dataset, representing all streams in the Watershed. Approximately 36,825 acres of land were included in this buffer system. ............................. 51
Figure 23. Scenario BRW1D required the addition of a 150-foot buffer around the conduit
system, which represents the main channel system in the Watershed. Approximately 6,000 acres of land was included in this buffer system. .......................................................................................................................... 52
Figure 24. Existing land use in the Blue River Watershed as defined by the Mid-America
Regional Council (2012). .......................................................................................................... 53 Figure 25. Conversion of riparian corridors from wooded cover, grasslands, and wetlands
(left) to turf grass (right). ....................................................................................................... 576
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Figure 26. Restoration of the riparian buffer required conversion of all agricultural and developed land (left) to deciduous forest (right). ................................................................. 598
Figure 27. The conversion of developed, agricultural, and barren land cover (left) within
the 150-foot riparian buffer to deciduous forest (right). ........................................................ 60 Figure 28. Forecasted land use scenario from the Transportation Outlook 2040
“LU_FORE” provided by the Mid-America Regional Council. .................................................. 62 Figure 29. Percent impervious (IMPERV) across the watershed as defined by MARC’s
forecasted fully developed land use dataset. ......................................................................... 63 Figure 30. The change in percent impervious from the current scenario, Scenario BRW1E,
to the forecasted scenario, Scenario BRW6 (top figure) and percent change in impervious, calculated by dividing the change in impervious between Scenario BRW1E and Scenario BRW6 by the percent impervious of BRW1E (bottom figure) of each subcatchment as defined by MARC’s Transportation Outlook 2040 dataset. ........................................................................................................................... 64
Figure 31. Adapted land use scenario as part of the Transportation Outlook 2040 project
provided by the Mid-America Regional Council. ..................................................................... 65 Figure 32. The percent impervious of the adapted land use recommendation “LU_ADAP”
as defined by MARC (Scenario BRW7). ................................................................................... 66 Figure 33. (top) The change in percent impervious for each subcatchment from forecasted to
recommend land use as defined by MARC’s TO 2040 demonstrates land preservation efforts in most of the upper Watershed and continued development in the lower Watershed. (bottom) The percent change in impervious cover between these scenarios with respect to the forecasted land use is presented, allowing changes in imperviousness to be put into perspective. ............................................................................ 67
Figure 34. Total inflow during a 4.63-in storm at various locations in the Watershed
(Stations 2 (a), 6 (b), and 10 (c), respectively) under current conditions (Scenario 1C) and riparian buffer restoration within 300-feet of all streams (Scenario 3). Restoration of the riparian buffer provided substantial reductions in total inflow across the watershed. ...................................................................................... 75
Figure 35. Examining the total inflow at various locations in the Watershed, Stations 2 (a),
6 (b), and 10 (c), from a 4.63-in storm under current conditions (Scenario 1D) and riparian buffer restoration (Scenario 5) indicates restoration of the buffer improved the storage capacity of the system, reducing total inflow. Stations in in more developed tributaries, Station 6 included, saw the largest percent reductions in total inflow. ....................................................................................................... 76
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Figure 36. Changes in inflow between MARC scenarios for a 3.08-in storm. Values are reported as a percent change in inflow based on the difference between the scenarios listed. Scenario 6 and 7 represent forecasted and recommend land use respectively. ...................................................................................................................... 77
Figure 37. Changes in inflow from MARC Scenario 6 (forecasted land use) to 7
(recommended land use). ....................................................................................................... 78 Figure 38. Examination of the percent change in flooding between (a) 1E to 6,
(b) 1E to 7, and (c) 6 to 7 where land use of each scenario, 1E, 6, and 7, can be described as baseline, forecasted, and recommended respectively, demonstrated the forecasted land use (Scenario 6) is preferred to the recommended (Scenario 7). .................................................................................................... 81
Figure 39. Total inflow observed at various locations throughout the watershed under
land use scenarios as defined by MARC’s TO 2040 under the 5.48-in, 24-hour storm. Scenario 1E represents land use under current conditions. Scenario 6 represents the forecasted land use. Scenario 7 represents the adapted land use recommendation. Scenarios 8A and 8B represent Scenarios 7 and 6 respectively with the addition of a fully restored riparian buffer. Scenarios 9A and 9B build off of 8A and 8B respectively with the addition of conservation development within an outer buffer of the riparian area, limited to 29% or less for Scenario 9A and maximum development of 29% in the outer buffer for Scenario 9B. ...................................................... 85
Figure 40. There was a 9.9% flood extent reduction for the 5-year, 24-hour storm in the
Tomahawk Creek Watershed with maximum green infrstructure measures (Scenario TCW100R) implemented. ........................................................................................ 87
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List of Tables
Table 1. Land use-derived model properties (James et al., 2010). ......................................................... 23 Table 2. Soil hydraulic properties by soil type used in the development of the model (James
et al., 2010). .............................................................................................................................. 24 Table 3. Manning’s N values for each stream segment (James et al., 2010; Huffman
et al., 2011). .............................................................................................................................. 24 Table 4. Precipitation stations from NOAA LCD in the Blue River Watershed. ...................................... 25 Table 5. Average monthly evaporation for Kansas City, Missouri. ......................................................... 26 Table 6. USGS stream gauge stations in the Blue River Watershed. ...................................................... 27 Table 7. Model parameter calibration uncertainty as recommended by James (2003). ....................... 29 Table 8. Recommended statistical ratings for model calibration/validation. Adapted from
Shamsi and Konan (2017). ........................................................................................................ 30 Table 9. Continuous streamflow (cfs) calibration and validation results for the Blue River
Watershed model. .................................................................................................................... 30 Table 10. Event-based total streamflow calibration and validation results for the Blue River
Watershed model. .................................................................................................................... 32 Table 11. Event-based mean streamflow calibration and validation results for the Blue River
Watershed model. .................................................................................................................... 32 Table 12. Event-based maximum streamflow calibration and validation results for the Blue
River Watershed model. ........................................................................................................... 33 Table 13. Summary of modeling scenarios applied within the PCSWMM Blue River Watershed
model. ....................................................................................................................................... 34 Table 14. Summary of detailed green infrastructure modeling scenarios applied within the
PCSWMM Tomahawk Creek Watershed model. The percent routed subcatchment parameter was adjusted to simulate changing percentages of green infrastructure. ............. 35
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Table 15. NOAA Atlas 14 event-based precipitation depths for the Shawnee 2 S station (NOAA, 2017). ............................................................................................................... 36
Table 16. The selected NOAA stations, locations, and availability. .......................................................... 37 Table 17. The 18 selected GCMs name and model agency. ..................................................................... 38
Table 18. The 7 selected GCMs models names and agency. .................................................................... 39
Table 19. Locations of analysis for each scenario across the Blue River Watershed. .............................. 47
Table 20. Land use classes within the Transportation Outlook 2040 dataset and associated subcatchment parameters. .............................................................................. 54
Table 21. Adjusted subcatchment parameters for select land use classes, representing
the land cover conversion to turf grass within the 300-foot riparian buffer, in Scenario 2. ................................................................................................................................. 57
Table 22. Adjusted subcatchment parameters for select land use classes, representing
the land cover conversion to forested land cover within the 300-foot riparian buffer, in Scenario 3. ............................................................................................................................. 59
Table 23. Adjusted subcatchment parameters for selected land use classes, representing the
land cover conversion to forested cover within the 150-foot riparian buffer, in Scenario 5. ................................................................................................................................. 61
Table 24. Summary of modeling scenarios with description of scenario and the amount of
contributing impervious cover (%, with acres below) to each analysis location. A brief description of each of the analysis locations is provided. ................................................ 70
Table 25. Percent change in inflow from one MARC scenario to another. Scenarios BRW- 1E, 6
and 7 represent current, forecasted, and adapted recommendation land use, respectively. Values are reported as a percent. Cells highlighted in green indicate a decrease in inflow volume. ............................................. 79
Table 26. Summary of percent changes in flooding from one MARC scenario to another.
Scenarios BRW-1E, 6 and 7 represent current, forecasted, and adapted recommendation land use, respectively. Values are reported as a percent. Cells in green indicate a reduction in flooding was observed. ................................................. 80
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Table 27. Change in total inflow and flooding volumes for a 4.63-inch storm event. Acres converted is based on the amount of impervious land located in the buffers prior to restoration of riparian vegetation. ........................................................................................... 83
Table 28. Percent reduction in peak inflow and total volume of inflow from current conditions
for the 1.37-inch, 24-hour precipitation event. Shading indicates statistically significant results. ..................................................................................................................... 86
Table 29. Results of the Tukey Honest Significant Difference test comparing the baseline
TCW5 scenario to all other scenarios. Comparisons with a p-value of less than 0.05 indicate a significant difference between the results, and are shaded in gray. .................................................................................................................... 86
Table 30. Percent reduction in peak inflow and total volume with addition of 150 ft. riparian
buffer and 25% “disconnectedness”. Shading indicates statistically significant results. ....................................................................................................................................... 88
Table 31. Percent reduction in peak inflow and total volume with addition of 150 ft. riparian
buffer and 100% “disconnectedness”. Shading indicates statistically significant results. ....................................................................................................................................... 89
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Executive Summary
The Earth’s climate is currently changing faster than at any point in the history of modern civilization, primarily as a result of human activities (Reidmiller et al., 2018). In addition to increases in very hot days and heat waves, more frequent and intense extreme weather events are expected (Herring et al., 2019; Reidmiller et al., 2018; Transportation Research Board, 2008) Trenberth, 2011). The increased flooding caused by the intensification of the hydrologic cycle heightens the risk to America’s aging transportation infrastructure. The Blue River Watershed, located in Kansas City, Kansas and Missouri houses many important highways including US-69, I-35, and I-435. The intent of this study was to understand the impact of land development patterns, conservation strategies, and green infrastructure implementation on the climate change resiliency of transportation infrastructure across a watershed.
The Blue River Watershed is an urbanizing watershed on the southern edge of Kansas City, which crosses the Kansas-Missouri border from its headwaters in Johnson County, Kansas towards its outlet on the Missouri River in Kansas City, Missouri. Kansas State University developed a comprehensive water quantity model using PCSWMM software to assess future scenarios of conservation and urban development and climate change (McDonough, 2018; Stanton, 2020; Thomas, 2020). Utilization of the PCSWMM model enabled geospatial, exploratory analysis of integrated watershed management scenarios across the Blue River Watershed. Scenarios that combined varying degrees of land development and conservation and different precipitation events were applied within the model and compared in order to understand the most effective means for improved hydrologic function throughout the watershed, with a particular focus on flood reduction. A more detailed PCSWMM model was developed for Tomahawk Creek, a tributary of the Blue River, to better assess implementation of green infrastructure in a developed watershed and provide a more detailed analysis of flooding reductions and transportation resiliency (Thomas, 2020).
Key Findings
Key findings and trends from this study are reported below. A more in-depth discussion of model outputs and scenario results can be found in the Discussion section of this report.
General Trends
The impacts of land development on runoff and flooding varies spatially across the Blue River Watershed due to the existing land use gradient (e.g., largely rural, undeveloped land in the headwaters compared to predominantly urban land toward the outlet of the Watershed) and the corresponding anthropogenic activities. The amount of impervious land cover, including its spatial distribution and connectivity, play a substantial role in runoff generation and associated increases in flooding. The preservation of natural land cover such as forests and grasslands, particularly within the riparian corridor, would reduce flooding throughout the Watershed. Future development scenarios that account for both increases and connectivity in natural/pervious landcover will be beneficial for flood mitigation.
Riparian Buffer Importance
Disturbance of the riparian buffer, to include conversion of the area to a managed green space (Scenario BRW2) represented by turf grass, reduces the infiltration capacity of the system. Ultimately, this resulted in increased flood potential in the lower watershed where reduced flooding is most needed.
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Although alteration from natural cover to a managed green space does not increase impervious area, the roughness of the landscape is reduced, which results in water flowing more quickly over the land reducing the peak time to flood (peak inflow). In many cases, the total inflow decreased while the total flooding increased across the watershed due to the reduced time of concentration. This trend was most consistent in the lower watershed. Depending on the storm, the headwaters saw occasional increases in inflow due to the amount of natural cover that was converted. Natural vegetation should be preserved in this area as opposed to managed green space or impervious cover.
Restoration of the riparian buffer of all streams, including ephemeral streams, provided great benefits in both runoff inflow and flooding reduction. These benefits varied across the watershed and were dependent on the contribution area. For a 4.63-in storm (5-yr, 24-hr storm), riparian buffer restoration provided an inflow reduction of 50% in the headwaters, but only realized an 18% reduction near the outlet of the watershed. Effectiveness of the buffers depends on precipitation depth and location in the watershed (Scenario BRW3: Restoration of Riparian Buffer of All Streams (Including Ephemeral)).
Restoration of the riparian buffer of the main channel is a beneficial practice. Buffer conservation reduced the total inflow and flooding volumes, resulting in reduced maximum depth observed (Scenario BRW5: Restoration of the Riparian Buffer of Main Channels).
Restoration of the riparian buffer around all streams, including ephemeral streams, provided greater inflow and flood volume reduction benefits than that of riparian buffer restoration only on the main channel (Riparian Buffers). However, the efficiency of benefits, meaning inflow and/or flooding reduction divided by acres converted from impervious to pervious cover in the buffer, was more often lower than the efficiency of riparian restoration of main channels (Scenario BRW3 vs Scenario BRW5). Restoration of the riparian buffer around all streams, including ephemeral streams, would likely supply additional ecosystem services and benefits that were not accounted for in this study. Likewise, more ecosystem services and benefits would be experienced when a wider buffer is protected. Evaluation of these benefits would provide insight into the true value of riparian buffer restoration.
Impact of Land Development
The Blue River Watershed is expected to be further developed in the coming years. Informed land development decisions must be made in order to reduce the stress of this development on man-made and natural waterways.
Due to the increase in impervious cover, an increase in flooding and inflow was observed under the forecasted (Scenario BRW6) and adapted recommended (Scenario BRW7) land use scenarios compared to current conditions (Scenario BRW1E) as defined by the Mid-America Regional Council’s (MARC) Transportation Outlook (TO) 2040. The adapted land use recommendation included roughly 3,200 less acres of impervious surface than the forecasted land use. With this, little preservation was seen in the lower watershed, an area already characterized by its development. Most preservation of natural land cover was seen in the headwaters (Scenario BRW7: TO 2040 with Adapted Land Use Recommendation).
Despite the decrease in overall impervious surface, the adapted land use recommendation was not beneficial across the watershed compared to the forecasted land use. When inflow and flooding benefits were observed, this was typically in the headwaters instead of the lower watershed where flooding is a greater concern. The amount of flow accumulation and contributing area in the lower watershed make it difficult for changes in the headwaters to benefit the watershed near the outlet. Land use alterations need to be made throughout the watershed in order to experience inflow and
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flooding reduction benefits closer to the outlet (Scenario Trends: Scenarios Defined by MARC’s Transportation Outlook 2040: BRW- 1E, 6, 7, 8A, 8B, 9A, 9B).
Inclusion of riparian buffer restoration provided benefits under all potential land development scenarios defined by MARC’s TO 2040 (Land Development Trends: MARC Adapted Land Use Recommendation).
Conservation development policies which aim to restrict the amount of impervious cover in an area are of benefit. These policies should take the amount of development in other parts of the watershed into consideration to ensure limitations are set appropriately (Land Development Trends: MARC Adapted Land Use Recommendation).
Green Infrastructure Assessment
Green infrastructure impacts depend on climate change and precipitation distribution. The average annual precipitation in Kansas City is projected to increase. If 90% of the stormwater runoff volume of all 24-hour storms on an annual basis continues to be generated by the current water quality event (1.37-inch, 24-hour storm, e.g. smaller, but more frequent events), then green infrastructure will do a good job reducing peak inflow, total inflow, and providing other ecosystem services. However, if the increase in annual precipitation is seen in larger events (e.g. 100-year storm event) as expected, then green infrastructure will not have a significant impact on flood reduction, but will provide other ecosystem services year round. Adding riparian buffers and increasing percent of impervious surface runoff routed to pervious landcover (e.g. increased green infrastructure) to at least 25% achieved significant peak inflow and total volume reductions across all storm events, and coupling the riparian buffer with increased disconnectedness (e.g. additional green infrastructure throughout the watershed including practices that reduce direct runoff from impervious surfaces to surface streams) is more effective than either of the practices individually.
Increasing green infrastructure increases the climate resiliency of stormwater management and transportation infrastructure, however additional structural flood control is needed to reduce flood impacts of large storms.
Climate Change
The Kansas City region is expected to see an increase in average annual rainfall with more intense rainfall events separated by longer dry periods (Revi et al., 2014; Anderson and Walker, 2015). As discussed above, changes in precipitation intensity, duration, and frequency will have a significant impact on the watershed hydrologic function and nature-based solutions (e.g. green infrastructure).
In order to develop a better understanding of the watershed response to future climate, the model was run for a range of single events (BRW 1-yr, 24-hr to 25-yr, 24-hr (Table 15) and TCW 1-yr, 6-hr to 100-yr, 24-hr (Table 27)) and a series of global climate models (GCMs) (Mauer et a., 2007; USDOI, 2013; USDOI 2014; Pierce et al., 2015). The series of single event model runs allow for detailed analysis of the more intense individual storms expected in the future, while the continuous runs allow for a better understanding of watershed water storage and green infrastructure function.
While the single event model precipitation amounts were based on current rainfall data, current literature and models suggest that future storms will be less frequent and more intense. Thus, future water management plans should consider using results from more intense events and the higher end of the current ninety-percent confidence intervals reported by the NOAA National Weather Service. Effectively, the current 10-yr, 24-hr event may be the future 5-yr, 24-hr event. For example, station
14
Shawnee 2 S 10-yr, 24-hr is estimated to be 5.48 inches with a 90% confidence interval of 4.45 to 6.76 inches and the 5-yr, 24-hr estimate is 4.63 inches with a 90% confidence interval of 3.78 to 5.69 inches. With storms being more intense, designing for the higher end of the 90% confidence interval, 5.69 inches for the 5-yr, 24-hr return period, which is slightly higher than the current 10-yr, 24-hr event.
A series of GCMs from the Coupled Model Intercomparison Project Phase 5 (CMIP5) were analyzed for use. Through the validation and visualization of the 1950-2005 datasets with the observed NOAA precipitation data, it was determined that the seven models could be used for the Blue River Watershed research area. However, subsequent watershed model runs produced questionable results. While the single event models provided the ability to assess the impact of a range of event sizes, watershed analysis with continuous runs using future climate model data generated results conflicting with expected increases in extreme events. We hypothesize the coarse temporal resolution (e.g. daily precipitation values) did not capture the intensity of Midwest storms and reduced the modeled severity of runoff and flooding. This is supported by the improved model calibration and validation when using 15-minute precipitation data, 1,440 data points per day. Given the variation in modeled results from the downscaled future climate models and disagreement with other climate change projections, we suggest additional analysis on downscaled precipitation for the Kansas City area be completed and caution in using these data.
Summary of Scenario Findings
Overall, it was found that scenarios which restore the riparian buffer (especially Scenarios BRW3 and BRW5) and increase impervious disconnectedness (TCW scenarios) offer benefits in terms of improved hydrologic function compared to their respective baseline scenarios—decreased total inflow volume, flood volume, and depth. Restoration of natural land cover increased the surface roughness and storage of the system, thus providing more opportunities for infiltration to occur.
Alternatively, scenarios which involve the disturbance of the buffer (Scenario BRW2) or increase the amount of impervious cover throughout the Watershed were not beneficial (Scenarios BRW6 and BRW7 compared to Scenario BRW1E). However, some of the negative impacts of scenarios involving potential future conditions in the Watershed could be combated by integration of riparian buffer restoration, as observed in Scenarios BRW8A, BRW8B, BRW9A, and BRW9B compared to scenarios BRW1E, BRW6, and BRW7, which do not involve riparian buffer restoration.
Study Motivation
The Kansas City Region has suffered fourteen deaths, $49 million in crop damages, and $111.6 million in property damage due to flooding since 1993 (Mid-America Regional Council, 2015). Substantial rainfall increases for seasonal spring and fall rain in addition to extreme events are projected (Anderson and Walker, 2015). Annual precipitation is predicted to increase roughly 1.5” by midcentury (2021-2060) even if emissions are curbed to the A1B lower emission scenario described in the National Climate Assessment (2014). If greenhouse gas emissions continue at their current rate, scenario A1F1, annual average precipitation is projected to increase 5.8 inches to 44.6 inches for 2061-2100 (Anderson and Walker, 2015). This rainfall will be seen in more extreme, concentrated events, as the number of consecutive dry days is also expected to increase from 30.9 days/year to 39.5 days/ year (Anderson and Walker, 2015). This amplification of existing climate-related risks is of grave concern to managers and citizens of an already flood-prone Kansas City metro region.
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In 2017, the Mid-America Regional Council (MARC), a nonprofit association of city and county governments and the metropolitan planning organization for all nine counties of the bistate Kansas City Region, released a Climate Resilience Strategy which included an action goal of increasing trees and green infrastructure. Their report also notes a lack of analysis of risks and vulnerabilities associated with climate change effects on transportation. This study helps inform their goal of creating and implementing a Regional Transportation Climate Resiliency Action Plan and aligns with the goal of utilizing increased green infrastructure. The Tomahawk Watershed is of particular significance because it contains the most congested four-lane highway in the state: U.S. Highway 69 (Ritter, 2020). Around 80,000 vehicles travel on US-69 in Johnson County each day, and the Kansas Department of Transportation (KDOT) estimates traffic will double by 2045 (KDOT, 2018). Vulnerability of stormwater systems to climate change varies according to regional climate patterns and natural and engineered site-specific factors (Heidrich et al., 2013). A site-specific study is required to better estimate the climate change effects on stormwater under varying development scenarios.
Study Area
The Blue River Watershed (HUC #1030010101) is located south of the Kansas City metropolitan area and is part of the Lower Missouri-Crooked watershed (HUC #10300101). As such, it serves as a tributary to the Missouri River. The Blue River Watershed has areas in both Kansas and Missouri. The headwaters of the watershed are in Kansas, moving northeast towards the outlet. The Blue River is a fifth order stream with its major tributaries being Brush, Indian, Tomahawk, Wolf, and Coffee Creeks (Missouri, n.d.).
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Figure 1 The Blue River Watershed is a tributary to the Missouri River with parts in both Kansas and
Missouri. The main stream channel is shown in blue (Thomas, 2020).
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The entire watershed is roughly 75,000 hectares (185,000 acres) with multiple cities in its boundary including Olathe, Overland Park, Leawood, Prairie Village, and Kansas City (MARC, 2019). The watershed spans five counties with notable area in Johnson, Jackson, and Cass counties.
Figure 2 The Blue River Watershed has area in five counties, overlapping twenty cities (MARC, 2010).
The Blue River Watershed is mainly located in the physiographic region of the Osage Cuestas (Wingfield, 2007). The word “cuesta” means hill or cliff in Spanish. Thus, series of ridges are found in this area along with other landforms such as rolling hills and flat plains. Limestone and shale compose most of the rock near the surface in the region (Kansas, 1963). The rocks in the Blue River Watershed are part of the Carboniferous system, most specifically the Pennsylvanian subsystem which occurred 318 million years ago (Kansas, 1998). As such, streams in the region typically have sand, silt, and rock fragments in them (Kansas, 1963).
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The Blue River Watershed intersects four U.S. EPA Level IV ecoregions: the Osage Cuestas, Wooded Osage Plains, Rolling Loess Plains, and Missouri Alluvial Plain (U.S. EPA, 2013). The physiography of the Osage Cuestas and Wooded Osage Plains are defined by gentle undulating plains and perennial streams, while the Missouri Alluvial Plain is glaciated level floodplain alluvium with riparian wetlands that have been largely drained (Kansas Native Plant Society, 2019). The Rolling Loess Prairie topography is dominated by irregular plains to low open hills (Iowa Department of Natural Resources, n.d.). Limestone and shale rocks that compose the bedrock geology were formed in sediments deposited in the shallow seas that covered the watershed during the Pennsylvanian subperiod that occurred between 323 to 299 million years ago (Kansas Geological Survey, 1963; O’Connor, 1971). Once the sea levels fell far enough to expose the land, freshwater streams cut deep channels into the limestone and shale that were then filled with sand, silt, and rock fragments from the channel walls (Kansas Geological Survey, 1963). The most prominent soil types in the watershed are Chillicothe silt loam, Oska-Martin silky clay loams, Sharpsburg silt loam, Snead-Urban land complex, and Sibley-Urban land complex, at approximately 19%, 12%, 8%, 6%, and 6% respectively (Soil Survey Staff, 2019).
Figure 3 The BRW intersects four U.S. EPA Level IV ecoregions (U.S. EPA, 2013).
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A land use/land cover gradient exists within the watershed, with urbanization dominating the northern area and rural land uses (e.g. grazing land, cropland) in the headwaters in the southern portion of the watershed (Figure 4 Land use/land cover in the Blue River Watershed from the 2011 National Land Cover Dataset). The amount of urban area in the watershed is predicted to increase, with some areas of the headwaters estimated to urbanize at a rate of 8.89% per year (Ji et al., 2016). Notable areas of deciduous forest are still present along the main channel and in parts of the headwaters of the Blue River. However, wide-spread disturbance of the riparian buffer, resulting from urbanization, has clearly occurred in the Tomahawk and Indian Creek tributaries.
Figure 4 Land use/land cover in the Blue River Watershed from
the 2011 National Land Cover Dataset (Homer et al., 2011).
The smaller Tomahawk Creek subwatershed of the Blue River Watershed was selected for a more in-depth analysis. The Tomahawk Creek Watershed (TCW) is 59.8 km2 (14,790 acres). It comprises 8.5% of the Blue River Watershed (Figure 5), and is almost fully developed suburban area (Figure 6) with an average of 35% imperviousness across the watershed (Figure 7). The highest average impervious areas are concentrated around the U.S. Highway 69 corridor in the center of the watershed.
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Figure 5. Tomahawk creek watershed is located in the center of the BRW.
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Figure 6. Tomahawk Creek Watershed landcover is largely suburban development
with golf courses and light industrial mix.
Tomahawk Creek Watershed contains one USGS gage, 06893350, located on the bridge where Tomahawk Creek flows under Roe Avenue. Tomahawk Creek was determined to have a bankfull discharge of 31.15 cms (1,100 cfs) at this location and a bankfull stage of approximately 3 m (9.8 ft) (Peters and Studley, 2014).
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Figure 7. Average percent imperviousness in Tomahawk Watershed along with assessment locations
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Model Development
PCSWMM, a physically based hydrologic modeling software (McDonough et al., 2017), was used to develop a model of Blue River Watershed. PCSWMM is a physically based, semi-lumped, and deterministic model (Zeckoski et al., 2015) that can simulate environmental conditions across a range of spatial scales. The PCSWMM software (version 7.1.2480) enables watershed modeling in both urban and rural areas through the full integration of the United States Environmental Protection Agency’s (U.S. EPA) Storm Water Management Model (SWMM, version 5.0.013-5.1.012) coupled with Geographic Information Systems (GIS; Rossman, 2008; James et al., 2010; Ahiablame and Shakya, 2016). PCSWMM “contains a wide variety of hydrologic and hydraulic capabilities such as flow routing, snow accumulation and melting, evaporation of standing surface water, rainfall interception in depression storage, flow routing through closed and open conduit networks of unlimited size, two-dimensional flood routing, and modeling of backwater, surcharging, reverse flow, and surface ponding,” (Ahiablame and Shakya, 2016). The PCSWMM software also has the capability to estimate pollutant loading for water quality applications, simulate low-impact development/green infrastructure, and conduct sensitivity, calibration, and error analyses (Rossman, 2008; James et al., 2010). Furthermore, PCSWMM has been widely used for a variety of modeling applications in urban areas (e.g., Ahiablame and Shakya, 2016; Akhter & Hewa, 2016; McDonough et al., 2017; Neupane, 2018; Park & Shin, 2014).
Input Datasets
Several geospatial datasets are necessary to build a complete hydrologic model in PCSWMM. A digital elevation model (DEM) with 3-meter spatial resolution was obtained to describe the watershed topography (USGS, 2009); where “no data” pixels within the DEM raster were filled using the Raster Calculator tool within ArcGIS (ESRI, 2011). The National Hydrography Dataset (USGS, 2001) stream network was utilized alongside the DEM within PCSWMM’s Watershed Delineation Tool (CHI, 2017) to automatically delineate the watershed area and create subcatchments according to a target discretization level of 500 acres. A total of 375 subcatchments were created in this process, along with the innumerable conduits and junctions, to represent the natural hydrology of the watershed.
The 2011 National Land Cover Dataset (NLCD) was used to describe land cover throughout the watershed at a 30-km resolution (Homer et al., 2015). PCSWMM’s Area Weighting Tool (CHI, 2017) was employed to determine the following model attributes for each subcatchment from the 2011 NLCD layer: percent impervious (%IMPERV), Manning’s roughness impervious (NIMPERV), Manning’s roughness pervious (NPERV), depression storage impervious (DSIMPERV), and depression storage pervious (DSPERV) (Table 1). Web Soil Survey spatial and tabular data (SSURGO 2.2) was acquired to describe soil hydraulic properties throughout the watershed (USDA-NRCS, 2016). The Area Weighting Tool was again applied using SSURGO 2.2 data to determine values of conductivity, suction head, and initial deficit (Table 2) for each subcatchment (James et al., 2010; USDA-NRCS, 2016).
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Table 1. Land use-derived model properties (James et al., 2010).
Land Use/ Land Cover
NLCD Gridcode %IMPERV DSPERV (in) DSIMPERV (in) NPERV NIMPERV
Open Water 11 0 0 0 0 0 Perennial Ice/Snow 12 0 0 0 0 0
Developed, Open Space 21 10 0.1 0.05 0.034 0.012
Developed, Low Intensity 22 30 0.1 0.05 0.034 0.012
Developed, Medium Intensity
23 60 0.1 0.05 0.034 0.012
Developed, High Intensity 24 90 0.1 0.05 0.034 0.012
Barren Land 31 0 0.1 0 0.05 0 Deciduous
Forest 41 0 0.3 0 0.40 0
Evergreen Forest 42 0 0.3 0 0.40 0
Mixed Forest 43 0 0.3 0 0.40 0 Dwarf Scrub 51 0 0.2 0 0.24 0 Shrub/Scrub 52 0 0.2 0 0.24 0 Grassland/
Herbaceous 71 0 0.2 0 0.24 0
Sedge/ Herbaceous 72 0 0.2 0 0.24 0
Lichens 73 0 0.2 0 0.15 0 Moss 74 0 0.2 0 0.15 0
Pasture/Hay 81 0 0.2 0 0.13 0
Cultivated Crops 82 0 0.2 0 0.17 0
Woody Wetlands 90 0 0.3 0 0.40 0
Emergent Herbaceous
Wetlands 95 0 0.3 0 0.15 0
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Table 2. Soil hydraulic properties by soil type used in the development of the model (James et al., 2010).
Soil Type Suction Head (in) Conductivity (in/hr) Initial Deficit (frac.)
Sand 1.95 4.74 0.417
Loamy Sand 2.41 1.18 0.401
Sandy Loam 4.33 0.43 0.412
Loam 3.5 0.13 0.434
Silt Loam 6.57 0.26 0.486
Sandy Clay Loam 8.6 0.06 0.33
Clay Loam 8.22 0.04 0.309
Silty Clay Loam 10.75 0.04 0.432
Sandy Clay 9.41 0.02 0.321
Silty Clay 11.5 0.02 0.423
Clay 12.45 0.01 0.385
The slope (%), area (acres), and width (ft) of each individual subcatchment were derived from the DEM layer in the delineation process. Subarea routing for all subcatchments was “PERVIOUS”, with the Zero Imperv (%) and Percent Routed (%) characteristics initially set at 50 and 25, respectively. The geographical cross-section of each conduit, or stream segment, within the model was determined by utilizing the DEM layer in conjunction with the Transect Creator tool in PCSWMM (CHI, 2017). The Manning’s Roughness coefficient (Manning’s N) for each stream segment and adjacent stream bank was assigned using visual imagery of each stream section and land use/land cover data (Table 3).
Table 3. Manning’s N values for each stream segment (James et al., 2010; Huffman et al., 2011).
Land Cover Manning’s N
Streambank
Bermuda Grass, short 0.034
Impervious (Concrete, Asphalt) 0.015
Wooded 0.40
Stream Channel
Natural channel, fairly regular 0.032
Natural channel, irregular with pools 0.05
Lined Channel 0.012
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The Green-Ampt Equation (Equation 1), which is an empirical equation used to estimate infiltration, was used as the infiltration model. The Green-Ampt Equation assumes “vertical flow, uniform initial water content, and uniform soil hydraulic conductivity” (Huffman et al., 2011).
𝐹𝐹 = 𝐾𝐾𝑒𝑒𝑡𝑡 + 𝑆𝑆𝑎𝑎𝑎𝑎𝑎𝑎𝑀𝑀 ln(1 + 𝐹𝐹𝑆𝑆𝑎𝑎𝑎𝑎𝑎𝑎𝑀𝑀
) (Equation 1)
The effective hydraulic conductivity (Ke), time (t), average matric suction at the wetting front (Savg), and fillable porosity (M) are used as inputs to calculate the cumulative infiltration depth, F, at time t (Huffman et al., 2011).
Dynamic wave routing, which solves the complete one-dimensional Saint-Venant flow equations, was chosen as the routing method for the model. The Saint-Venant flow equations calculate the flow within an individual conduit according to the continuity (Equation 2) and momentum (Equation 3) equations;
𝜕𝜕𝜕𝜕𝜕𝜕𝜕𝜕
+ 𝜕𝜕𝜕𝜕𝜕𝜕𝜕𝜕
= 0 (Equation 2)
∂Q∂t
+∂(𝑄𝑄
2
𝐴𝐴 )
∂x+ gA ∂H
∂x+ gA𝑆𝑆𝑓𝑓 + gAℎ𝐿𝐿 =0 (Equation 3)
where distance (x), time (t), cross-sectional area (A), flow rate (Q), hydraulic head (H), friction slope (Sf), local energy loss per unit length of the conduit (hL), and acceleration due to gravity (g) are the input parameters (James et al., 2010). Dynamic wave routing is considered the most “theoretically accurate” (James et al., 2010) routing method as it can account for channel storage, backwater flow, entrance/exit losses, flow reversal, and pressurized flow.
Observed, hourly precipitation from three locations (Table 4) throughout the Blue River Watershed were obtained from the National Oceanic and Atmospheric Administration (NOAA) Local Climatological Dataset (LCD). Each observed dataset was screened for errors and flags. Any trace amount of precipitation denoted with a “T”, which indicates a rainfall amount too small to measure (typically <0.005 inches), during the period of record were assumed to be zero. Time periods that were blank (e.g., unreported data) or tagged as missing were also assumed to be zero. Any data denoted with an “s” to designate a “suspect value” was assumed to be the amount written.
Table 4. Precipitation stations from NOAA LCD in the Blue River Watershed.
Name Network ID Latitude Longitude Period of Record
Olathe Johnson County Executive Airport, KS US
WBAN: 03967 38.85º -94.73917º 1/1/2006 – Present
Kansas City Downtown Airport, MO US
WBAN: 13988 39.1208º -94.5969º 1/1/1957 – Present
Lee’s Summit Municipal Airport, MO US
WBAN: 53879 38.95972º -94.37139º 1/1/2006 - Present
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Evaporation data from the Kansas City area was used to calculate average, monthly evaporation in the PCSWMM model (Table 5). The average, monthly pan evaporation for the Kansas City area (Table II; NOAA, 1982a) was multiplied by a coefficient of 74% (Map 4; NOAA, 1984b) to convert Class A pan evaporation to free water surface evaporation. Evaporation from the free water surface was used as the average, monthly evaporation rate in the model.
Table 5. Average monthly evaporation for Kansas City, Missouri.
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Average pan
evaporation (in) 1.37 1.83 3.47 5.45 7.34 7.94 8.84 8.09 5.69 4.47 2.39 1.56
Average free water surface
evaporation (in) 1.01 1.35 2.57 4.03 5.43 5.88 6.54 5.99 4.21 3.31 1.77 1.15
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Observed streamflow data was obtained from ten USGS gauge stations located throughout the Blue River Watershed (Table 6; Figure 1) for model calibration and validation purposes. Average daily streamflow data were obtained for the years 2001 through 2016, though the temporal availability of data between stations varied in this time period.
Table 6. USGS stream gauge stations in the Blue River Watershed.
Site ID Station Name Station Number Latitude Longitude Availability
1 Blue R NR Stanley, KS 06893080 38°48'45" 94°40'32" 9/20/1974-
Present
2 Kenneth Rd., Overland
Park, KS 06893100 38°50'32" 94°36'44"
4/16/2003-Present
3 Blue River at Blue Ridge
Blvd Ext in KC, MO 06893150 38°53'21.9" 94°34'50.4" 6/1/2002-Present
4 Blue River at
Kansas City, MO 06893500 38°57'25.2" 94°33'32.0" 5/1/1939-Present
5 Tomahawk C NR
Overland Park, KS 06893350 38°54'22" 94°38'24"
9/20/1974-Present
6 Indian C at
Overland Park, KS 06893300 38°56'26" 94°40'16" 3/7/1963-Present
7 Indian C at State Line Rd.,
Leawood, KS 06893390 38°56'18" 94°36'28"
4/22/2003-Present
8 Brush Creek at Rockhill
Road in Kansas City, MO 06893562 39°02'21.3" 94°34'43.4"
7/30/1998-Present
9 Brush Creek at Ward
Parkway in Kansas City, MO
06893557 39°01'59.1" 94°36'19.4" 7/15/1998-
Present
10 Blue River at Stadium
Drive in Kansas City, MO 06893578 39°03'30" 94°30'42" 7/1/2002-Present
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Figure 8. Location of the USGS stream gauges in the Blue River Watershed.
Calibration and Validation
Streamflow was calibrated and validated on a daily timescale at six USGS stream gauge stations within the study area. The following stations were used for calibration/validation using the Sensitivity/Based Radio Tuning Calibration (SRTC) tool: 06893080, 06893100, 06893300, 06893350, 06893557, and 06893578. The SRTC tool is an automatic calibration method that allows the user to calibrate each individual model parameter to a specified level of uncertainty by optimizing the Nash-Sutcliffe Efficiency (NSE) between the simulated and observed streamflow hydrographs (James et al., 2010; McDonough et al., 2017). A select group of model parameters were calibrated within an acceptable recommended level of uncertainty (Table 7), as recommended by James (2003).
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Table 7. Model parameter calibration uncertainty as recommended by James (2003).
Model Parameter Layer Uncertainty (%)
Invert Elevation Junctions 10
Baseline Junctions 25
Length Conduits 10
Roughness Conduits 10
Area Subcatchments 10
Width Subcatchments 100
Slope Subcatchments 100
% Impervious Subcatchments 50
N Imperv Subcatchments 25
N Perv Subcatchments 100
Dstore Imperv Subcatchments 50
Dstore Perv Subcatchments 100
Zero Impervious Subcatchments 100
Percent Routed Subcatchments 100
Suction Head Subcatchments 50
Conductivity Subcatchments 50
Initial Deficit Subcatchments 100
Left Bank Roughness Transects 10
Right Bank Roughness Transects 10
Channel Roughness Transects 10
The Nash-Sutcliffe Efficiency (NSE) is a statistical measure that compares the simulated hydrograph to the observed (Engel et al., 2007; Zeckoski et al., 2015; McDonough et al., 2017). The NSE is commonly used to assess the performance of a model through calibration and validation. “An NSE of 1 indicates perfect correlation; NSE < 0 indicates that an average of the observed data would be a better predictor than the simulated data,” (Zeckoski et al., 2015). A literature review of acceptable hydrologic modeling calibration statistics by Engel et al. (2007) found that model performance was deemed satisfactory with a NSE coefficient greater than 0.4. A range of NSE ratings proposed by Shamsi and Konan (2017) are similar, who stated that an NSE value within the range of 0.4-1.0 is acceptable for all model applications (Table 8).
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Table 8. Recommended statistical ratings for model calibration/validation. Adapted from Shamsi and Konan (2017).
NSE Range Rating Model Application
0.5-1.0 Excellent Planning, preliminary design, final design
0.4-0.49 Very good Planning, preliminary design, final design
0.3-0.39 Good Planning, preliminary design
0.2-0.29 Fair Planning
<0.2 Poor Screening
Both continuous and event-based calibration methods were used to assess the overall performance of the model. Traditionally, event-based methods have been used for calibration and validation due to the limited availability of continuous observed streamflow datasets. The event-based method compares the simulated hydrograph to the observed hydrograph for a minimum of five to ten storm events (Shamsi and Konan, 2017). As continuous streamflow datasets have become more available, continuous calibration and validation methodology has become more popular. Continuous calibration compares the simulated hydrograph against the observed hydrograph over a continuous period of time. For a complete description of the two calibration and validation methodologies, refer to Shamsi and Konan (2017).
Calibration and Validation Results
Continuous and event-based calibration was conducted at six locations throughout the Blue River Watershed. The model was calibrated from June 1, 2014 - September 30, 2014 and validated from April 1, 2014 - May 31, 2014. The model was calibrated to optimize the NSE for total streamflow on both an event- and continuous-basis.
Results show, on a continuous basis, that the model-simulated streamflow was comparable to observed streamflow with a rating of “very good” or “excellent” at all locations (Table 9; Figure 9). The average NSE value for the calibration period, validation period, and overall were 0.60, 0.65, and 0.60, respectively. These results demonstrate that the model, in its current state, accurately simulates the surface hydrology mechanisms of the Blue River Watershed is suitable for associated planning, preliminary design, and final design purposes (Table 8).
Table 9. Continuous streamflow (cfs) calibration/validation results for Blue River Watershed model.
Location Calibration
(6/1/2014-9/30/2014) Validation
(4/1/2014-5/31/2014) Overall
(4/1/2014-9/30/2014) 1
(06893080) 0.563 0.65 0.569
2 (06893100)
0.486 0.622 0.47
6 (06893300)
0.665 0.552 0.621
5 (06893350)
0.562 0.589 0.567
4 (06893500)
0.647 0.787 0.677
10 (06893578)
0.672 0.701 0.678
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Figure 9. Continuous calibration/validation results throughout the Blue River Watershed at a) J06893080, b) J06893100, c) J06893350, d) J06893300, e) J06893500, f) J06893578.
In addition to continuous calibration, the model was calibrated to optimize the total streamflow of the model at each location on an event-basis. The simulated total streamflow was comparable to observed streamflow with all reported NSE values above 0.4 (Table 10). The average NSE values for the calibration period, validation period, and overall were 0.75, 0.70, and 0.69, respectively. Again, and similarly to the results of the continuous calibration, these results demonstrate that the model in its current state accurately simulates the surface hydrology mechanisms of the Blue River Watershed and is suitable for associated planning, preliminary design, and final design purposes (Table 8).
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Table 10. Event-based total streamflow calibration and validation results for the Blue River Watershed model.
Location Calibration (6/1/2014-9/30/2014)
Validation (4/1/2014-5/31/2014)
Overall (4/1/2014-9/30/2014)
1 0.913 0.76 0.896
2 0.576 0.923 0.6
6 0.874 0.46 0.44
5 0.802 0.658 0.827
4 0.587 0.712 0.627
10 0.746 0.707 0.738
The model behavior for event-based mean streamflow and event-based maximum streamflow is also reported (Table 11; Table 12). While the model was not calibrated to specifically optimize these parameters, knowledge of how the model is performing for all aspects of the hydrograph will be important in the assessment of future results. The reported NSE was above 0.4 for the majority of locations for both mean and maximum streamflow. The average NSE for mean streamflow was 0.67, 0.70, and 0.73 for the calibration period, validation period, and overall, respectively, and the average NSE for maximum streamflow was 0.41, 0.49, and 0.43 for the same periods.
Table 11. Event-based mean streamflow calibration and validation results for the Blue River Watershed model.
Location Calibration (6/1/2014-9/30/2014)
Validation (4/1/2014-5/31/2014)
Overall (4/1/2014-9/30/2014)
1 0.887 0.739 0.86
2 0.641 0.945 0.653
6 0.623 0.371 0.87
5 0.686 0.693 0.709
4 0.497 0.701 0.559
10 0.701 0.768 0.711
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Table 12. Event-based maximum streamflow calibration and validation results for the Blue River Watershed model.
Location Calibration (6/1/2014-9/30/2014)
Validation (4/1/2014-5/31/2014)
Overall (4/1/2014-9/30/2014)
1 0.454 0.521 0.468
2 0.36 0.519 0.373
6 0.544 0.533 0.558
5 0.204 0.417 0.221
4 0.491 0.42 0.503
10 0.418 0.502 0.43
Those locations that reported lower NSE values (e.g., 06893300, 06893100, 06893350) are located in the headwaters of the watershed. These lower NSE values indicate that the model does not capture the hydrograph extremes well, particularly the peaks. However, the lower NSE values in the headwaters may be attributed to the generally “flashy” behavior of watersheds in these areas, which was extremely difficult for the model to capture. The headwaters are flashy in comparison to other areas of the watershed due to the stream channels being narrower and having a smaller time of concentration. To maintain computational efficiency, the model does not include the extensive artificial stormwater network that is maintained throughout the Blue River Watershed. The lack of inclusion of features characteristic to the stormwater network, such as box culverts and levees, may be one reason that the model does not simulate flashy behavior as well as it could. Unfortunately, a dataset that describes the artificial stormwater network in this area was not available at the time of model development but future iterations of this model may consider including this information to improve simulation accuracy. Future applications of this model in its current state should proceed with caution when reporting streamflow extremes, particularly in reference to maximum streamflow values.
Scenario Modeling
Numerous scenarios that combined varying degrees of land development, conservation, and green infrastructure were applied within the model and compared in order to understand the most effective means for the enhancement of natural hydrologic mechanisms throughout the entire ecosystem, with a particular focus on increasing the flood mitigation capability of the Watershed. Kansas State University developed thirteen Blue River Watershed scenarios (Table 13) and twelve Tomahawk Creek Watershed scenarios (Table 14) to be applied within the modeling software, PCSWMM, and represented varying configurations of land use and management within the watersheds. Calibrated current land use conditions, as described by the NLCD 2011 dataset, were used as the baseline for comparison purposes in this study (unless otherwise specified). All results from each scenario are compared to this baseline, thus enabling discussion on the impact of management or land use change on hydrology.
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Table 13. Summary of modeling scenarios applied within the PCSWMM Blue River Watershed model.
Scenario Number
Description
BRW1
Current Conditions • 1A: 2011 NLCD1; roughly 38,000 acres of impervious area • 1B: 2011 NLCD with 300-foot buffer (12,000 acres) around the conduit
system, representing the riparian buffer around main channels • 1C: 2011 NLCD with 300-foot buffer (37,000 acres) around National
Hydrologic Dataset streams layer (including ephemeral streams) • 1D: 2011 NLCD with 150-foot buffer (6,000 acres) around the conduit
system, representing the riparian buffer around main channels • 1E: existing land use as defined by the “LU_BASE” data layer of the
MARC2 Transportation Outlook 2040 data and includes nearly 13,000 acres of impervious area
BRW2 (Baseline: BRW1B)
Conversion of Riparian Buffer to Managed Green Space 1B with conversion of 10,125 acres of the riparian buffer area, previously natural vegetation, to a managed green space (e.g., turf grass)
3 (Baseline: BRW1C)
Restoration of Riparian Buffer of All Streams 1C with conversion of 5,441 acres of impervious area to natural wooded cover to represent restoration of the riparian buffer within 300-feet of all streams, including ephemeral streams
5 (Baseline: BRW1D)
Restoration of Riparian Buffer of Main Channels 1D with conversion of 785 acres of impervious area to deciduous forest to represent restoration of the riparian buffer within 150-feet around main channels
6 (Baseline: BRW1E)
Transportation Outlook 2040 – Fully Developed (LU_Fore) The maximum impervious development in the Watershed as defined by MARC’s “LU_FORE” data layer and includes 16,200 acres of impervious cover
7 (Baseline: BRW1E)
Transportation Outlook 2040 – Adapted Land Use Recommendation (LU_ADAP) The recommended development scenario as defined by MARC’s “LU_ADAP” data layer and includes 13,000 acres of impervious cover
8 (Baseline: BRW1E)
8A: Transportation Outlook 2040 – Adapted Land Use Recommendation with Restoration of Riparian Corridor Land use defined by MARC’s “LU_ADAP” data layer and conversion of 20,000 acres of land within 100-ft of the main channel to deciduous forest 8B: Transportation Outlook 2040 – Fully Developed, Restoration of Riparian Buffer Fully developed land use as defined by MARC’s “LU_FORE” data layer and conversion of 20,000 acres of land within 100-ft of the main channel to deciduous forest
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9 (Baseline: BRW1E)
9A: Transportation Outlook 2040 – Adapted Land Use Recommendation with Restoration of Riparian Corridor and Conservation Development Land use defined by MARC’s “LU_ADAP” data layer and conversion of 20,000 acres of fully restored riparian buffer with conservation development, restricting percent impervious to 29% within outer buffer which was determined by steep slopes and proximity to the riparian buffer. Less than two acres of impervious cover were lost due to conservation development in outer buffer 9B: Transportation Outlook 2040 – Forecasted Land Use with Restoration of Riparian Corridor and Development Max in Outer Buffers The forecasted land use. “LU_FORE,” defined by MARC was used in this scenario. Full riparian buffer restoration was implemented within 100-feet of the main channels. All area in the outer buffer, as defined in Scenario 9A, was developed to the maximum value allowed of 29% impervious. A total of 17,600 acres of impervious cover exist.
1. National Land Cover Data (https://www.mrlc.gov/) 2. Mid-America Regional Council (https://www.marc.org/)
Table 14. Summary of detailed green infrastructure modeling scenarios applied within the PCSWMM Tomahawk Creek Watershed model. The percent routed subcatchment parameter
was adjusted to simulate changing percentages of green infrastructure.
Scenario Description
TCW0 0% routed to pervious, no added deciduous forest riparian buffer
TCW5 5% routed to pervious, no added deciduous forest riparian buffer, “current conditions or baseline”
TCW25 25% routed to pervious, no added deciduous forest riparian buffer
TCW50 50% routed to pervious, no added deciduous forest riparian buffer
TCW75 75% routed to pervious, no added deciduous forest riparian buffer
TCW100 100% routed to pervious, no added deciduous forest riparian buffer
TCW0R 0% routed to pervious, with 150 ft deciduous forest riparian buffer
TCW5R 5% routed to pervious, with 150 ft deciduous forest riparian buffer
TCW25R 25% routed to pervious, with 150 ft deciduous forest riparian buffer
TCW50R 50% routed to pervious, with 150 ft deciduous forest riparian buffer
TCW75R 75% routed to pervious, with 150 ft deciduous forest riparian buffer
TCW100R 100% routed to pervious, with 150 ft deciduous forest riparian buffer
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Precipitation
Once developed, each scenario was run in the PCSWMM model to simulate the response of the watershed to five event-based storm events (Table 15). Rainfall data from NOAA’s Atlas 14 Point Precipitation Frequency Estimates (NOAA Atlas 14) was used to represent the precipitation depth for each precipitation event at the Shawnee 2 S station. The Shawnee 2 S station was used to represent the precipitation throughout the entire watershed as the other observed precipitation station in the watershed, Olathe 3 E, was within 0.04 inches of the Shawnee 2 S for every average recurrence interval. The event-based storm events were modeled using the SCS Type II rainfall distribution with a 15-minute hydrograph interval.
Table 15. NOAA Atlas 14 event-based precipitation depths for the Shawnee 2 S station (NOAA, 2017).
Storm Recurrence Interval & Duration Precipitation Depth with 90% confidence interval (in)
1 1-year, 24-hour 3.08 (2.53-3.79)
2 2-year, 24-hour 3.65 (2.99-4.49)
3 5-year, 24-hour 4.63 (3.78-5.69)
4 10-year, 24-hour 5.48 (4.45-6.76)
5 25-year, 24-hour 6.71 (5.32-8.49)
Additional analysis was conducted to assess the usefulness of meteorological data from global climate models through the validation of precipitation from the Coupled Model Intercomparison Project Phase 5 (CMIP5) from 1950-2005, across the Blue River Watershed in the Kansas City area. A set of global climate models (GCMs) within the CMIP5 dataset was validated using historical, observed precipitation data on a monthly and annual basis (Figures 11-14).
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Figure 10. The Blue River Watershed study area and the location of six NOAA precipitation stations.
Continuous, historical daily precipitation data was obtained from 1950-2005 at six National Oceanic and Atmospheric Administration (NOAA) precipitation stations located within the Blue River Watershed (Table16). Stations were selected based on their length of coverage and availability. Then hindcast, simulated precipitation data was collected from two CMIP5 datasets. This included 18 GCMs from both the GDO LOCA and the MACA V2 methods for downscaled climate projection sources (Table 17).
Table 16. The selected NOAA stations, locations, and availability.
Station ID Station Name Abbreviation Latitude Longitude Availability Coverage
USC00234379 Kansas City U of MO, MO US
KansasCityU 39.03333 -94.58333 1/1/1950 – 5/31/1970 95%
USW00013988 Kansas City Downtown Airport, MO US
Downtown Airport
39.1208 -94.5969 1/1/1950 – 12/31/2005 91%
USC00145248 Merriam Overland Park, KS US
Merriam OP 38.98333 -94.68333 8/17/1951 – 2/11/1965 96%
USC00145245 Merriam, KS US Merriam 39.01667 -94.66667 1/1950 – 2/28/1965 95%
USC00145972 Olathe 3 E, KS US Olathe3 38.8875 -94.7602 1/1/1950 – 12/31/2005 96%
USC00147809 Stilwell, KS US Stilwell 38.7695 -94.6682 1/1/1950 – 12/31/2005 90%
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Table 17. The 18 selected GCMs name and model agency.
GCM NAME MODEL AGENCY BCC-CSM1-1 Beijing Climate Center, China Meteorological Administration BCC-CSM1-1-M Beijing Climate Center, China Meteorological Administration CANESM2 Canadian Centre for Climate Modeling and Analysis CCSM4 National Center of Atmospheric Research, USA CNRM-CM5 National Centre of Meteorological Research, France CSIRO-MK3-6-0 Commonwealth Scientific and Industrial Research
Organization/Queensland Climate Change Centre of Excellence, Australia
GFDL-ESM2M NOAA Geophysical Fluid Dynamics Laboratory, USA GFDL-ESM2G NOAA Geophysical Fluid Dynamics Laboratory, USA HADGEM2-CC365 Met Office HadleyCenter, UK HADGEM2-ES365 Met Office HadleyCenter, UK INMCM4 Institute for Numerical Mathematics, Russia IPSL-CM5A-LR Institut Pierre Simon Laplace, France IPSL-CM5A-MR Institut Pierre Simon Laplace, France MIROC5 Atmosphere and Ocean Research Institute (The University of
Tokyo), National Institute for Environmental Studies, and Japan Agency for Marine-Earth Science and Technology
MIROC-ESM Japan Agency for Marine-Earth Science and Technology, Atmosphere and Ocean Research Institute (The University of Tokyo), and National Institute for Environmental Studies
MIROC-ESM-CHEM Japan Agency for Marine-Earth Science and Technology, Atmosphere and Ocean Research Institute (The University of Tokyo), and National Institute for Environmental Studies
MRI-CGCM3 Meteorological Research Institute, Japan NORESM1-M Norwegian ClimateCenter, Norway
A validation process was used to examine the performance of the projected GCM precipitation against the observed NOAA precipitation datasets. Statistical analysis was completed using Mann-Kendall trend test (τ), Spearman’s correlation coefficient (ρ), percent bias (PBIAS), and root mean square error (RMSE). The trends and correlation of the models were then visually compared using Taylor diagrams and boxplots. Seven models performed with a ρ ≥ 0.4 and a positive trend (τ). These seven models were selected for further analysis to compare the models to each other, their location, and the observed precipitation, depicted on line plots.
Several statistical parameters were used to simplify the original 36 models down to 7 significantly performing models for the Blue River Watershed location. The Mann-Kendall non-parametric trend test was used to measure the strength of relationship between variables or the correlation between the modeled and observed data. Tau (τ) indicates the trend by a positive or negative value of correlation. Positive trend values were used in selecting significantly performing GCMs as a positive correlation indicates both variables are increasing together. Spearman’s correlation coefficient (ρ) accesses a degree of similarity between the interested variables. Spearman’s rho (ρ) ranges from -1 to 1 determining if the correlation between the model and observed data was significantly different from 0. For this analysis, all models with a ρ ≥ 0.4 were considered comparable to the observed data and were selected for further analysis. The percent bias (PBIAS), and root
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mean square error (RMSE) were also taken into consideration in determining how accurate the models were performing and associating a degree of uncertainty within each model estimations. Ideal performance would include a PBIAS and RMSE value close to zero, which indicates minimal error and accurate model simulation. The seven models selected for further analysis were selected based on a combination of these parameters (Table 18). Further analysis included methods to better visualize and compare how the selected models performed against each other, their location, and the observed precipitation using boxplots, Taylor diagrams and long-term trend models.
Table 18. The 7 selected GCM models names and agency.
GCM NAME MODEL AGENCY
GDO_CCSM4 National Center of Atmospheric Research, USA
GDO_MRI-CGCM3 Meteorological Research Institute, Japan
GDO_NorESM1-M Norwegian Climate Center, Norway
MACA_MIROC-ESM Japan Agency for Marine-Earth Science and Technology, Atmosphere and Ocean Research Institute (The University of Tokyo), and National Institute for Environmental Studies
MACA_MIROC-ESM-CHEM
Japan Agency for Marine-Earth Science and Technology, Atmosphere and Ocean Research Institute (The University of Tokyo), and National Institute for Environmental Studies
MACA_MRI-CGCM3 Meteorological Research Institute, Japan
MACA_NorESM1-M. Norwegian Climate Center, Norway
Boxplots were used to visualize the distribution of Spearman’s correlation coefficient (ρ) between monthly total or monthly maximum GCM precipitation and historical, observed precipitation on a location basis and a model basis. The boxplot shows comparatively how well the correlation coefficients distributions agree with each other. The median line depicts the middle or mid-point of the data values. The box size or interquartile range illustrates an overall level of agreement in data points between the 25th percentile and 75th percentile. Outliers (open dots) and whiskers (dotted upper lines) represent values that have a wider variability, indicating highest values, lowest values and points falling outside the overall distribution of data values. Figure 11 shows how the correlation between the monthly total precipitation of selected models and the observed precipitation is distributed at each location of the NOAA precipitation stations. From this figure, it was determined that the correlation coefficients performed similarly throughout the watershed at each of the NOAA locations with the exception of the Merriam OP (Overland Park) which had a lower validation performance, with a ρ value less than 0.3. Similarly, a boxplot was used to show the distribution of correlation of monthly maximum precipitation on a location basis (Figure 12). The distribution of correlation coefficients for the maximum precipitation preformed between 0.2 and 0.3 at each location except for at the Merriam OP location.
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Figure 11. The correlation (ρ) between the monthly total GCM precipitation and historical,
observed precipitation from NOAA on a location basis.
Figure 12. The correlation (ρ) between the monthly maximum GCM precipitation and historical, observed
precipitation from NOAA on a location basis.
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Furthermore, boxplots were used to visualize the distribution of correlation coefficients on a model basis for both the monthly total precipitation (Figure 13) and monthly maximum precipitation (Figure 14). The correlation coefficients were similarly distributed for each of the seven selected models.
Figure 13. The correlation (ρ) between the monthly total GCM precipitation and historical, observed precipitation from NOAA for each of the 7 significant GCMs.
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Figure 14. The correlation (ρ) between the monthly maximum GCM precipitation and historical,
observed precipitation from NOAA for each of the 7 significant GCMs.
The Taylor diagram was also used to visualize the overall validation performance. These diagrams provide a concise statistical summary of multiple parameters including Spearman’s correlation coefficient, standard deviation, and RMSE difference used in the validation process. The correlation coefficient is located along the curve relating to the angle from origin (black), standard deviation (blue) along the x-axis and root mean square difference is in a field that is proportional to the distance from the point on the x-axis representing the observed and detailed as a green square in the following diagrams (green). An ideal model performance would lie near the observed point on the x- axis. This would represent a model that has a low RMSE and high correlation and if the model lies on the same arc as the point then the model has a similar standard deviation indicating an accurate representation of the observed conditions.
The overall validation performance by NOAA location is illustrated by a Taylor Diagram in Figure 15. Each location has seven colored triangles that represent the seven selected model performance at the given location. It was observed that the Merriam OP location had a poorer validation performance, this was somewhat expected from the results observed in the boxplot visualizations (Figures 11-12). However, all other locations had a comparable performance across the NOAA locations. Performing on the same standard deviation curve, correlation coefficient near 0.4 and similar RMSE.
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Figure 15. Taylor diagram illustrating the overall validation performance by location of the NOAA
precipitation station. All GCMs were comparable across locations, with the exception of the Merriam OP location which showed poorer validation performance.
The overall validation performance by model can be observed in Figure 16. In this Taylor diagram, each of the selected models is represented by 6 colored triangles indicating the NOAA locations. The selected model performances were comparable. However, models GDO_CCSM4, GDO_MRI.CGCM3, and GDO_NorESM1.M proved to have a better performance overall. As these models were clustered along the same standard deviation curve, correlation coefficient of about 0.4 and similar RMSE.
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Figure 16. Taylor diagram illustrating the overall validation performance of each of the seven selected
models. Model performance was comparable, though GDO_CCSM4, GDO_MRI.CGCM3, and GDO_NorESM1.M demonstrate better validation performance overall.
Long-term trend models were used to visualize and compare the observed monthly precipitation to the modeled/projected precipitation of the seven selected models for a specific year and location. These long-term models allowed for a whole year to be observed at once and for peaks in observed precipitation and in projected precipitation to be compared. These long-term models assist in understanding what time points during the year the models are projecting the largest precipitation totals to occur. Figure 17 is a model that details the Downtown Airport location for the year 1950. The observed NOAA precipitation (NCEI black line) for 1950 peaked between the months of June and August; whereas the selected models followed a similar pattern, but a few models included an early season and late season peak in precipitation totals. A similar plot was constructed for the Downtown Airport location for the year 2001 (Figure 18). In 2001, the MACA_MIROC-ESM-CHEM model seems to more accurately model the observed precipitation. While the GDO_NorESM1-M model peaks later in the year during September, thus not following the observed NOAA precipitation pattern as well.
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Figure 17. NCEI (NOAA) observed monthly precipitation for the year 1950 at the Downtown
Airport Location and the projected precipitation by the 7 selected GCMs.
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Figure 18. NCEI (NOAA) observed monthly precipitation for the year 2001 at the Downtown
Airport Location and the projected precipitation by the 7 selected GCMs.
Through the validation and visualization of the CMIP5 datasets with the observed NOAA precipitation data, seven models were selected for the Blue River Watershed research area.
Analysis Locations
The subsequent output from each BRW scenario was analyzed at six gauged locations in the Blue River Watershed (Table 19; Figures 17-18). Each location is labeled with a numerical site ID, which corresponds with the assigned site ID in Table 19. Additional analysis was conducted at three modeling nodes, including the USGS gaging station on Tomahawk Creek (Site ID 5), within the more detailed Tomahawk Creek Watershed (Figure 6).
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Table 169. Locations of analysis for each scenario across the Blue River Watershed.
Site ID Station Name Station
Number Latitude Longitude
1 Blue R NR Stanley, KS 06893080 38°48'45" 94°40'32"
2 Kenneth Rd., Overland Park, KS 06893100 38°50'32" 94°36'44"
4 Blue River at Kansas City, MO 06893500 38°57'25.2" 94°33'32.0"
5 Tomahawk C NR Overland Park, KS 06893350 38°54'22" 94°38'24"
6 Indian C at Overland Park, KS 06893300 38°56'26" 94°40'16"
10 Blue River at Stadium Drive in Kansas City, MO 06893578 39°03'30" 94°30'42"
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Figure 19. Peak and total inflow are monitored at three locations (J17, J06893350, and J27)
in the Tomahawk Creek Watershed.
Scenario BRW1
This baseline scenario serves to represent existing conditions within the Blue River Watershed. Multiple baseline scenarios were created to facilitate correct routing through riparian buffers and reconcile geospatial and development differences in datasets that were used to create Scenarios BRW2-BRW9 and facilitate comparison between scenarios.
Scenario BRW1A
Scenario BRW1A is the original, calibrated model that is described in detail in the “Model Development” section of this report and represents current, existing watershed conditions based upon the 2011 NLCD land cover dataset (Homer et al., 2011). The only parameter that differentiated from the method described in the “Model Development” section of this report was the percent impervious cover (IMPERV) parameter, which was determined using the NLCD 2011 dataset (Homer et al., 2011) and was not calibrated. Scenario BRW1A was run for all five event-based storm events and all metrics are direct output from the model simulation.
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Scenario BRW1B
Scenario BRW1B is the baseline, calibrated model (Scenario BRW1A) with the addition of a 300-foot buffer around all main streams (e.g., the conduit layer in Scenario BRW1A; Figure 20). No changes to land cover or model parameters were made. The addition of the buffer was simply incorporated to facilitate an easier comparison between current, existing conditions (Scenario BRW1B) and Scenario BRW2, by making the hydrologic routing between subwatersheds in the two scenarios equitable. Scenario BRW1B will act as the “baseline” scenario for Scenario BRW2.
Figure 20. Scenario BRW1B required the integration of a 300-foot buffer around main channels,
which are represented by the model conduit network.
To build Scenario BRW1B, a 300-foot buffer was created around the stream corridor (conduit) layer from the original, calibrated scenario (Scenario BRW1A) in ArcGIS. This buffer was joined to the original subcatchments layer from Scenario BRW1A using the ‘Union’ tool in ArcGIS to create a new subcatchment layer (Figure 21). To be clear, no land mass was added in the form of a riparian buffer, but rather stream-adjacent subwatersheds from Scenario BRW1A were reduced in size to accommodate a 300-ft riparian buffer surrounding the stream channel. Finally, the overland flow path for each subcatchment was manually adjusted so that any overland flow runoff would flow through the riparian corridor subcatchment prior to entering the stream.
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Figure 21. The updated subcatchment layer includes the new, 300-foot riparian buffer surrounding the
stream corridor (yellow). The dashed, blue line shows the updated flow path of the subcatchment through the riparian corridor subcatchment to the outlet.
Five subcatchment parameters within the riparian corridor subcatchments were updated in Scenario BRW1B using the Area Weighting Tool to represent the current land use conditions from the 2011 National Land Cover Dataset (Table 1), although these parameters were not calibrated. (Note: Calibrated parameter values refer to the values that were adjusted in the model calibration and validation process, which is described in the “Model Development” section of this report. Uncalibrated values were the values used for these parameters prior to the calibration process, such as those listed in Table 1 or Table 2.) Uncalibrated values were used for consistency since the values in Scenario BRW2, which is the scenario that will be compared to this one, will also be un-calibrated. Percent impervious (IMPERV), depression storage (DSPERV; DSIMPERV), and Manning’s roughness coefficient (NPERV; NIMPERV) are the five uncalibrated parameters that were changed to reflect this update. Note that no subcatchment parameters outside of the riparian corridor subcatchments were changed.
Scenario BRW1C
Scenario BRW1C is the baseline, calibrated model (Scenario 1A) with the addition of a 300-foot riparian buffer around the National Hydrography Dataset (Figure 22). This scenario creates a 300-foot riparian buffer around all streams, including ephemeral streams, within the Blue River Watershed. This scenario will act as the “baseline” scenario for Scenario BRW3.
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Figure 22. Scenario BRW1C required the addition of a 300-foot buffer around the National Hydrography
Dataset, representing all streams in the Watershed. Approximately 36,825 acres of land were included in this buffer system.
To build this scenario, a 300-foot buffer was created around the National Hydrography Dataset in ArcGIS. The National Hydrography Dataset represents the surface flow hydrography throughout the Blue River Watershed and includes ephemeral streams. This buffer layer was joined to the original subcatchments layer from Scenario BRW1A using the ‘Union’ tool in ArcGIS to create a new subcatchment layer (Figure 21). The overland flow path for each subcatchment was manually adjusted so that any overland flow runoff would flow through the riparian corridor subcatchment prior to entering the stream.
Five subcatchment parameters within the riparian corridor buffer were updated in Scenario BRW1C using the Area Weighting Tool to represent the current land use conditions from the 2011 National Land Cover Dataset (Table 1), although these parameters were not calibrated. (Note: Calibrated parameter values refer to the values that were adjusted in the model calibration and validation process, which is described in the “Model Development” section of this report. Uncalibrated values were the values used for these parameters prior to the calibration process, such as those listed in Table 1 or Table 2.) Uncalibrated values were used for consistency since the values in Scenario 3, which is the scenario that will be compared to this one, will be using uncalibrated values. Percent impervious (IMPERV), depression storage (DSPERV; DSIMPERV), and Manning’s roughness coefficient (NPERV; NIMPERV) are the five parameters that were changed to reflect this update. No subcatchment parameters outside of the riparian corridor subcatchments were changed.
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Scenario BRW1D
Scenario BRW1D is the baseline, calibrated model (Scenario 1A) with the addition of a 150-foot riparian buffer around all existing streams, which are represented by the conduit layer in Scenario BRW1A (Figure 23). This scenario will act as the “baseline” scenario for Scenario BRW5.
Figure 23. Scenario BRW1D required the addition of a 150-foot buffer around the conduit system, which represents the main channel system in the Watershed. Approximately 6,000 acres of land
was included in this buffer system.
To build this scenario, a 150-foot buffer was created around the stream (conduit) layer from the original, calibrated scenario in ArcGIS. This buffer was joined to the original subcatchments layer from Scenario BRW1A using the ‘Union’ tool in ArcGIS to create a new subcatchment layer. The overland flow path for each subcatchment was manually adjusted so that any overland flow runoff would flow through the riparian corridor subcatchment prior to entering the stream (Figure 21).
Five subcatchment parameters within the riparian corridor subcatchments were updated using the Area Weighting Tool in Scenario BRW1D to represent the current land use conditions from the 2011 National Land Cover Dataset (Table 1), although these parameters were not calibrated. (Note: Calibrated parameter values refer to the values that were adjusted in the model calibration and validation process, which is described in the “Model Development” section of this report. Uncalibrated values were the values used for these parameters prior to the calibration process, such as those listed in Table 1 or Table 2.) Uncalibrated values were used for consistency since the values in Scenario BRW5, which is the scenario that will be compared to this one, will also be un-calibrated. Percent impervious (IMPERV), depression storage (DSPERV; DSIMPERV), and Manning’s roughness coefficient (NPERV; NIMPERV) are the five parameters that were changed to reflect this update. No subcatchment parameters outside of the riparian corridor subcatchments were changed.
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Scenario BRW1E
Scenario BRW1E is the baseline, calibrated model (Scenario BRW1A), but with an updated land use/land cover layer as defined by the Mid-America Regional Council for the Transportation Outlook 2040 (Figure 24). Scenario 1E will act as the “baseline” scenario for Scenarios BRW6-BRW9.
Five subcatchment parameters were updated in Scenario BRW1E using the Area Weighting Tool to represent the current land use conditions as defined by the Transportation Outlook 2040 land use/land cover layer. Percent impervious (IMPERV), depression storage (DSPERV; DSIMPERV), and Manning’s roughness coefficient (NPERV; NIMPERV) are the five parameters that were changed to reflect this update. The percent impervious was estimated using the gross building footprint area and impervious cover estimates for similar land use classes within the 2012 NLCD land use/land cover layer. The values for depression storage and Manning’s roughness coefficient were assigned based on the surface properties of each land use category (Table 20). Please note that none of the updated values were calibrated.
Figure 24. Existing land use in the Blue River Watershed as defined
by the Mid-America Regional Council (2012).
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Table 20. Land use classes within the Transportation Outlook 2040 dataset and associated subcatchment parameters.
Land Use Description IMPERV (%)
DSPERV (in)
DSIMPERV (in) NPERV NIMPERV
Vacant/Agriculture 0 0.2 0 0.13 0 Rural Policy Area 1 0.2 0.1 0.13 0.012 Rural Residential 1 0.1 0.05 0.034 0.012 Urban Fringe 2.1 0.1 0.05 0.034 0.012 Residential SF Large Lot 3.9 0.1 0.05 0.034 0.012 Residential SF Very Low 7.6 0.1 0.05 0.034 0.012 Residential SF Low 11.7 0.1 0.05 0.034 0.012 Residential SF Medium 13.1 0.1 0.05 0.034 0.012 Residential SF High 13.1 0.1 0.05 0.034 0.012 Residential MF Low 9.7 0.1 0.05 0.034 0.012 Residential MF Low-Med 12.8 0.1 0.05 0.034 0.012 Residential MF Medium 13.9 0.1 0.05 0.034 0.012 Residential MF High 20.3 0.1 0.05 0.034 0.012 Residential MF Very High 29.6 0.1 0.05 0.034 0.012 Residential 40 29.6 0.1 0.05 0.034 0.012 Residential 60 29.6 0.1 0.05 0.034 0.012 Residential 80 29.6 0.1 0.05 0.034 0.012 Residential 120 29.6 0.1 0.05 0.034 0.012 Mixed Use (Low) 10 0.1 0.05 0.034 0.012 Mixed Use (High) 55 0.1 0.05 0.034 0.012 Mixed Use (Very High) 65 0.1 0.05 0.034 0.012 Mixed Use (Urban) 90 0.1 0.05 0.034 0.012 Indust./Bus. Park (Low) 10 0.1 0.05 0.034 0.012 Indust./Bus. Park (High) 55 0.1 0.05 0.034 0.012 Indust./Bus. Park (Very High) 65 0.1 0.05 0.034 0.012 Indust./Bus. Park (Urban) 90 0.1 0.05 0.034 0.012 Office (Low) 10 0.1 0.05 0.034 0.012 Office (Med) 30 0.1 0.05 0.034 0.012 Office (High) 55 0.1 0.05 0.034 0.012 Office (Very High) 65 0.1 0.05 0.034 0.012 Office (Urban) 90 0.1 0.05 0.034 0.012 Office (High Urban) 100 0.1 0.05 0.034 0.012 Commercial (Low) 10 0.1 0.05 0.034 0.012 Commercial (High) 55 0.1 0.05 0.034 0.012 Commercial (Very High) 65 0.1 0.05 0.034 0.012 Commercial (Urban) 90 0.1 0.05 0.034 0.012
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Parks, Open Space 10 0.1 0.05 0.034 0.012 Public/Semipublic (Low) 10 0.1 0.05 0.034 0.012 Public/Semipublic (High) 55 0.1 0.05 0.034 0.012 Public/Semipublic (Very High) 65 0.1 0.05 0.034 0.012 Public/Semipublic (Urban) 90 0.1 0.05 0.034 0.012 Condo 30 0.1 0.05 0.034 0.012 Railroad right-of-way 10 0.1 0.05 0.034 0.012 Right-of-way 10 0.1 0.05 0.034 0.012 Unknown 0 0.1 0.05 0.034 0.012 None 0 0.1 0.05 0.034 0.012 Developed 30 0.1 0.05 0.034 0.012
Scenario BRW2: Conversion of the Riparian Buffer to Managed Green Space
Scenario BRW2 is the baseline model (Scenario BRW1B) that has been adjusted to remove existing wooded cover, grasslands, and wetlands within the 300-foot riparian buffer (Table 21). The intent of this scenario was to simulate and understand the hydrologic response of the Blue River Watershed following the removal of natural riparian cover along the stream corridor. The existing wooded cover, grasslands, and wetlands within the riparian corridor were replaced with turf grass (Figure 25). Other existing land use/land cover within the buffer, such as developed land use classes, were not changed and no changes were made to land use/land cover outside of the 300-foot riparian buffer.
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Figure 25. Conversion of riparian corridors from wooded cover, grasslands,
and wetlands (left) to turf grass (right).
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Four subcatchment parameters within the 300-ft riparian buffer of Scenario 2 were updated using the Area Weighting Tool in PCSWMM to represent the conversion of existing land use conditions within the riparian corridor from wooded cover, grasslands, and wetlands to turf grass. Depression storage (DSPERV; DSIMPERV) and Manning’s roughness coefficient (NPERV; NIMPERV) are the four parameters that were changed to reflect this update. Values for depression storage and Manning’s roughness coefficient were assigned based on the surface properties of turf grass (Table 21).
Table 21. Adjusted subcatchment parameters for select land use classes, representing the land cover conversion to turf grass within the 300-foot riparian buffer, in Scenario 2.
Land Use/Land Cover NLCD Gridcode DSPERV (in) DSIMPERV (in) NPERV NIMPERV
Deciduous Forest 41 0.1 0 0.02 0
Evergreen Forest 42 0.1 0 0.02 0
Mixed Forest 43 0.1 0 0.02 0
Dwarf Scrub 51 0.1 0 0.02 0
Shrub/Scrub 52 0.1 0 0.02 0
Grassland/ Herbaceous 71 0.1 0 0.02 0
Woody Wetlands 90 0.1 0 0.02 0 Emergent Herbaceous Wetlands 95 0.1 0 0.02 0
Scenario BRW3: Restoration of Riparian Buffer of All Streams (Including Ephemeral)
Scenario BRW3 is the baseline model (Scenario BRW1C), but with the conversion of developed, agricultural, and barren land use/land cover to forested land use/land cover within a 300-foot riparian corridor. The intent of this scenario was to simulate and understand the hydrologic response of the Blue River Watershed to the restoration of the riparian corridor along all surface riparian areas, including ephemeral streams. All developed, agricultural, and barren land use/land cover within the 300-foot riparian buffer were converted to deciduous forest to represent the “restoration” of the riparian corridor surrounding all riverine areas. Any other land use/land cover within the riparian buffer, such as herbaceous land cover, was left unchanged and no changes to land use/land cover outside of the 300-foot riparian buffer were made (Figure 26).
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Figure 26. Restoration of the riparian buffer required conversion of all agricultural
and developed land (left) to deciduous forest (right).
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Five subcatchment parameters were updated using the Area Weighting Tool in PCSWMM to represent the conversion of land use conditions within the riparian corridor subcatchments (Table 22). Percent impervious (IMPERV), depression storage (DSPERV; DSIMPERV), and Manning’s roughness coefficient (NPERV; NIMPERV) are the five parameters that were changed to reflect this update. The percent impervious (IMPERV) parameter was assigned to be zero for all land use classes since there is no impervious cover present in forested land cover classes. Values for depression storage and Manning’s roughness coefficient were assigned based on the surface properties of deciduous forest cover (Table 1).
Table 22. Adjusted subcatchment parameters for select land use classes, representing the land cover conversion to forested land cover within the 300-foot riparian buffer, in Scenario 3.
Land Use/ Land Cover
NLCD Gridcode
%IMPERV DSPERV (in) DSIMPERV (in) NPERV NIMPERV
Developed, Open Space
21 0 0.3 0 0.4 0
Developed, Low Intensity
22 0 0.3 0 0.4 0
Developed, Medium Intensity
23 0 0.3 0 0.4 0
Developed, High Intensity
24 0 0.3 0 0.4 0
Barren Land 31 0 0.3 0 0.4 0
Pasture/Hay 81 0 0.3 0 0.4 0
Cultivated Crops 82 0 0.3 0 0.4 0
Scenario BRW5: Restoration of the Riparian Buffer of Main Channels
Scenario BRW5 is the baseline model (Scenario BRW1D) that has been updated with floodplain restoration through the implementation of a 150-foot forested riparian buffer. To simulate a full restoration of the buffer, all developed, agricultural, and barren lands within the buffer were converted to deciduous forest (Figure 27). Any other land use/land cover within the riparian buffer, such as herbaceous land cover, was left unchanged and no changes to land use/land cover outside of the 150-foot riparian buffer were made.
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Figure 27. The conversion of developed, agricultural, and barren land cover (left)
within the 150-foot riparian buffer to deciduous forest (right).
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Five subcatchment parameters were updated using the Area Weighting Tool in PCSWMM to represent the conversion of land use conditions within the riparian corridor subcatchments (Table 23). Percent impervious (IMPERV), depression storage (DSPERV; DSIMPERV), and Manning’s roughness coefficient (NPERV; NIMPERV) are the five parameters that were changed to reflect this update. Percent impervious was assigned to be zero for all land use classes since there is no impervious cover present in forested land cover classes. Values for depression storage and Manning’s roughness coefficient were assigned based on the surface properties of deciduous forest cover.
Table 23. Adjusted subcatchment parameters for selected land use classes, representing the land cover conversion to forested cover within the 150-foot riparian buffer, in Scenario 5.
Land Use/ Land Cover
NLCD Gridcode
%IMPERV DSPERV (in) DSIMPERV (in) NPERV NIMPERV
Developed, Open Space
21 0 0.3 0 0.4 0
Developed, Low Intensity
22 0 0.3 0 0.4 0
Developed, Medium Intensity
23 0 0.3 0 0.4 0
Developed, High Intensity
24 0 0.3 0 0.4 0
Barren Land 31 0 0.3 0 0.4 0
Pasture/Hay 81 0 0.3 0 0.4 0
Cultivated Crops 82 0 0.3 0 0.4 0
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Scenario BRW6: Transportation Outlook (TO) 2040- Forecasted Fully Developed
Scenario BRW6 is the Mid-America Regional Council’s forecasted fully developed scenario under the Transportation Outlook 2040 dataset (Figure 28). Scenario BRW6 is compared to the baseline Scenario BRW1E to assess how changes in development affect the surface hydrology of the Blue River Watershed. This scenario aims to identify how the Blue River Watershed’s hydrology might be impacted by future land development due to urbanization. In short, this is the “worst case” scenario as defined by MARC in terms of land development for 2040.
Figure 28. Forecasted land use scenario from the Transportation Outlook 2040 “LU_FORE”
provided by the Mid-America Regional Council.
Under the Transportation Outlook 2040 “LU_FORE” forecasted development scenario, land cover around the main stream channel and in the headwaters of the Blue River Watershed is relatively low in impervious cover (Figure 29). The upper Watershed is less impervious than the lower Watershed, which is seen under current conditions as well. Subcatchments along the main channel of the Blue River are typically kept at or below 10% impervious. The Indian Creek area has a greater number of higher percent impervious subcatchments than other tributaries of the Blue River.
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Figure 29. Percent impervious (IMPERV) across the watershed as defined by MARC’s forecasted fully developed land use dataset.
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In order to more thoroughly understand the forecasted land use (Scenario BRW6), the baseline land use (Scenario BRW1E) should be considered. The forecasted land use shows an increase in impervious cover throughout most of the watershed, especially in the headwaters which currently has seen very little development. Near the outlet of the Blue River Watershed, however, a decrease in impervious cover is observed along the main channel of the Blue River (Figure 30). It is important to understand the changes in percent impervious of each subcatchment under the forecasted land use in relation to the current land use. A small increase in impervious in a subcatchment in the headwaters could actually double the existing impervious cover in that subcatchment (Figure 30).
Figure 30. The change in percent impervious from the current scenario, Scenario BRW1E, to the forecasted scenario, Scenario BRW6 (top figure) and percent change in impervious, calculated by dividing the change in
impervious between Scenario BRW1E and Scenario BRW6 by the percent impervious of BRW1E (bottom figure) of each subcatchment as defined by MARC’s Transportation Outlook 2040 dataset.
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Five subcatchment parameters were updated using the Area Weighting Tool to represent the projected, fully developed land use conditions as defined by the Transportation Outlook 2040 "LU_FORE” land use/land cover layer (Table 20). Percent impervious (IMPERV), depression storage (DSPERV; DSIMPERV), and Manning’s roughness coefficient (NPERV; NIMPERV) are the five parameters that were changed to reflect this update. The percent impervious was estimated using the gross building footprint area and impervious cover estimates for similar land use classes within the 2012 NLCD land use/land cover layer. Values for depression storage and Manning’s roughness coefficient were assigned based on the surface properties of each land use category (Table 20).
Scenario BRW7: TO 2040 with Adapted Land Use Recommendation
Scenario BRW7 is the Mid-America Regional Council’s adapted scenario "LU_ADAP” under the Transportation Outlook 2040 dataset (Figure 31). Scenario BRW7 is compared to the baseline Scenario BRW1E to assess how changes in development affect the surface hydrology of the Blue River Watershed.
Figure 31. Adapted land use scenario as part of the Transportation Outlook 2040 project
provided by the Mid-America Regional Council.
Five subcatchment parameters were updated using the Area Weighting Tool to represent the projected, adapted land use conditions as defined by the Transportation Outlook 2040 “LU_ADAP” land use/land cover layer (Table 20). Percent impervious (IMPERV), depression storage (DSPERV; DSIMPERV), and Manning’s roughness coefficient (NPERV; NIMPERV) are the five parameters that were changed to reflect this update.
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The percent impervious was estimated using the gross building footprint area and impervious cover estimates for similar land use classes within the 2012 NLCD land use/land cover layer. Values for depression storage and Manning’s roughness coefficient were assigned based on the surface properties of each land use category (Table 20).
Similar to Scenario BRW6, the land use recommendation has a lower percent impervious in the headwaters of the Blue River Watershed, due to the lack of development in that area (Figure 32). Land in the headwaters of the Blue River Watershed and at the start of the majority of tributaries to the Blue River are preserved, which is reflected in the very low percent impervious cover in those areas.
Figure 32. The percent impervious of the adapted land use recommendation “LU_ADAP”
as defined by MARC (Scenario BRW7).
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There are slight increases in development in areas of the lower Watershed in Scenario BRW7, while further development in the upper Watershed is minimized. The preservation of land in the headwaters resulted in a decrease in impervious cover from MARC‘s forecasted “LU_FORE” land use to the recommended “LU_ADAP” land use (Figure 33). For instance, some areas in the headwaters see a very small change in overall percent impervious (Figure 33), but when this is normalized, it equates to a reduction in impervious cover somewhere in the range of 55-100% (Figure 33).
Figure 33. (top) The change in percent impervious for each subcatchment from forecasted to recommend
land use as defined by MARC’s TO 2040 demonstrates land preservation efforts in most of the upper Watershed and continued development in the lower Watershed (bottom).
The percent change in impervious cover between these scenarios with respect to the forecasted land use is
presented, allowing changes in imperviousness to be put into perspective.
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The adapted land use recommendation (Scenario BRW7) focuses efforts on preventing development in the headwaters of the Blue River Watershed and of each tributary. The main areas that are allowed to further develop under the recommended land use, compared to MARC’s forecasted land use “LU_FORE,” are located on the Missouri side of the Watershed. On the Kansas side of the Watershed, the impervious cover is reduced in the majority of subcatchments under the recommended land use.
Scenario BRW 8A: TO 2040 with Adapted Land Use Recommendation and Restoration of the Riparian Corridor
Scenario BRW8 is the Mid-America Regional Council’s adapted land use recommendation scenario, “LU_ADAP” under the Transportation Outlook 2040 dataset, coupled with full restoration of a 150-foot riparian buffer. To create this scenario, the subcatchment layer from Scenario BRW7 was joined with the riparian corridor subcatchments from Scenario BRW5. The intent of this scenario was to simulate the hydrologic response of the Blue River Watershed under a future development scenario (MARC’s adapted land use recommendation as defined in the Transportation Outlook 2040) coupled with a restored 150-foot riparian buffer. No changes were made to the land use/land cover properties from Scenarios BRW5 and BRW7. In general, this scenario represents low development in the headwaters of the Watershed and reveals small increases in development in the lower Watershed with the addition of a riparian buffer.
Scenario BRW8B: TO 2040 with Forecasted Land Use and Restoration of the Riparian Corridor
Scenario BRW8B is the Mid-America Regional Council’s forecasted land use, “LU_FORE” under the Transportation Outlook 2040 dataset, coupled with full restoration of a 150-foot riparian buffer. To create this scenario, the subcatchment layer from Scenario BRW6 was joined with the riparian corridor subcatchments from Scenario BRW5. The intent of this scenario was to simulate the hydrologic response of the Blue River Watershed under a future development scenario (MARC’s forecasted land use as defined in the Transportation Outlook 2040) coupled with a restored 150-foot riparian buffer. No changes were made to the land use/land cover properties from Scenarios BRW5 and BRW6. Thus, the riparian buffer was fully restored to deciduous forest and land outside of the buffer is the forecasted land use. Again, the main difference between Scenarios BRW8A and BRW8B is the land cover of land outside of the riparian buffer. This scenario does not utilize the adapted recommended use, so it represents the impact of no change in the current development strategy but rather the enforcement of a riparian buffer conservation policy.
Scenario BRW9A: TO 2040 with Adapted Land Use Recommendation and Restoration of the Riparian Corridor and Conservation Development
Scenario BRW9A is the combination of the Mid-America Regional Council’s Transportation Outlook 2040 adapted land use recommendations, restoration of riparian corridor, and conservation development. The land use defined by the Transportation Outlook 2040 as the adapted land use “LU_ADAP” was utilized. The riparian buffer, including the FEMA floodplain, is fully preserved, allowing natural deciduous forest vegetation to grow in the area around waterways. Conservation development is utilized in areas with slopes greater than 15% within 250-feet of the riparian buffer and all land within 75-feet of the riparian buffer. In these areas, it is assumed that 60% of the area remains as developed, open space assuming 0% impervious within this area and the remaining 40% of the area can be developed to a maximum of 72%, the TR-55 value for office/industrial use.
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Assuming this distribution of land use, the weighted percent impervious of the outer buffer is 29%. Upon further investigation, it was determined that only two of the outer buffers required reduction in impervious cover. The impervious cover of these buffers was reduced to 29%. All other outer buffer zones had a percent impervious below the 29% threshold, thus were left at this value. All land outside of the conserved area and buffer was assigned the same land cover and hydrologic parameters as determined by the adapted land use recommendation established in Scenario 7. This development practice should reduce stress on the riparian buffer by encouraging more infiltration.
Scenario BRW9B: TO 2040 with Forecasted Land Use and Restoration of the Riparian Corridor and Development Max in Outer Buffers
Scenario BRW9B is the combination of the Mid-America Regional Council’s Transportation Outlook 2040 forecasted land use scenario, restoration of the 100-foot riparian corridor, and conservation development in an outer buffer. The riparian buffer, including the FEMA floodplain, is fully preserved, allowing natural deciduous forest vegetation to grow in the area around waterways. Conservation development is utilized in areas with slopes greater than 15% within 250-feet of the riparian buffer and all land within 75-feet of the riparian buffer. In these areas, restricted development with a percent impervious of 29% was allowed. Again, this percentage was determined under the assumption that 60% of the area remains as developed, open space assuming 0% impervious within this area and the remaining 40% of the area can be developed to a maximum of 72%, the TR-55 value for office/industrial use. In this scenario, all outer buffers were developed to the maximum impervious value allowed. In general, Scenario 9B represents the impact of the forecasted land use for 2040 but with restoration of the riparian buffer and maximum allowed development surrounding the riparian area.
Tomahawk Creek Scenarios
Twelve different scenarios with varying levels of green infrastructure were created to understand linkages between green infrastructure and possible reductions in peak inflow, total inflow volume, and flood extent. Flood extent was calculated as the distance of water inundation from the stream centerline during peak flow for each event. The percent routed subcatchment parameter was adjusted to simulate changing percentages of green infrastructure. This function does not change the amount of impervious cover, which can be hard to do in an almost entirely built-out environment. Instead, it changes the percentage of runoff from the impervious areas that is directed onto pervious area before reaching the subcatchment outlet or stream conduit. This is an example of increasing the disconnectedness of impervious surfaces, such as disconnecting storm drains, or adding bioretention cells in parking lots. This approach for simulating disconnection was also used to model decentralized green stormwater controls for the city of Austin Texas Watershed Protection Department (Geosyntec Consultants, 2017).
Half of the scenarios also include the full restoration of the floodplain with a 150 ft deciduous forest riparian buffer. Using the landcover from the 2016 NLCD, all developed (including impervious cover), agricultural, and barren lands within the 150 ft buffer were converted to deciduous forest. Any pre-existing water, forest, shrubland, or herbaceous land cover was not converted.
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Summary of Scenarios
In evaluating the impact of each land management scenario considered in this report, the amount of contributing impervious cover should be considered at each analysis location (Table 24). Scenario BRW2 did not require a change in impervious area throughout the Watershed, but other important hydrologic characteristics were altered when the riparian buffer was converted to a managed green space. Scenarios BRW3 and BRW5 involve removal of impervious cover from the Watershed through riparian buffer restoration.
Table 174. Summary of modeling scenarios with description of scenario and the amount of contributing impervious cover (%, with acres below) to each analysis location.
A brief description of each of the analysis locations is provided.
BRW Scenario Description
Location 1 2 6 5 4 10
Headwaters Highly Developed Tributaries
Mid-Watershed Outlet
1A, 1B, 1C, 1D Baseline, 2011 NLCD 6%
(1,736) 6%
(2,636) 36%
(6,517) 29%
(3,784) 19%
(22,012) 22%
(35,409)
2 Conversion of Riparian
Buffer to Managed Green Space
6% (1,736)
6% (2,635)
36% (6,517)
29% (3,767)
19% (22,012)
22% (35,409)
3 Restoration of Riparian Buffer of All Streams
5% (1,336)
5% (2,008)
30% (5,464)
26% (3,401)
16% (18,715)
19% (30,460)
5 Restoration of Riparian Buffer of Main Channels
6% (1,716)
6% (2,595)
35% (6,394)
28% (3,712)
19% (21,628)
22% (34,725)
1E Transportation Outlook (TO) 2040 Baseline
2% (565)
2% (818)
8% (1,883)
8% (1,047)
6% (7,207)
7% (12,093)
6 TO 2040, Forecasted 5% (1,350)
5% (1,906)
13% (2,416)
12% (1,627)
9% (10,276)
10% (15,464)
7 TO 2040, Adapted Land Use Recommendation
1% (374)
1% (586)
9% (1,600)
8% (1,099)
6% (6,953)
8% (12,168)
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8A
TO 2040, Adapted Land Use Recommendation with
Restoration of Riparian Buffer
1% (339)
1% (531)
8% (1,449)
8% (1,048)
5% (6,301)
7% (11,012)
8B TO 2040, Forecasted with
Restoration of Riparian Buffer
4% (1,150)
4% (1,602)
12% (2,182)
11% (1,481)
8% (9,098)
9% (13,757)
9A
TO 2040, Adapted Land Use Recommendation with
Restoration of Riparian Buffer and Conservation
Development
1% (339)
1% (531)
8% (1,451)
8% (1,046)
5% (6,299)
7% (11,070)
9B
TO 2040, Forecasted with Restoration of Riparian
Buffer and Max Development in Outer
Buffer
6% (1,821)
6% (2,695)
13% (2,404)
13% (1,636)
10% (11,454)
10% (16,901)
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Discussion
The overall trends in the single event model results are discussed below. The results that are reported include maximum depth, total inflow volume, total flooding volume, and time of peak.
General Trends
• The total inflow, flooding, and maximum depth increases at all locations with increases in precipitation depth.
• The impact of land development on surface hydrology varies spatially across the watershed due to the gradient in land use and the corresponding magnitude of changes. For instance, the restoration of the riparian buffer requires much less land conversion in the undeveloped headwaters than in the highly developed lower Watershed.
Hydrologic Trends
• Scenarios which decrease values of surface roughness (Manning’s N) and depression storage yield an increase in the runoff volume and increase the speed at which runoff moves over the landscape and through the system. This, in turn, increases stream flashiness and the risk of flooding due to the increase in the volume of water entering artificial and natural waterways within a given time period. Increases in impervious cover throughout the Watershed also contributes to this phenomenon.
• Alternatively, scenarios which restore natural land cover are more beneficial, in terms of flood reduction, than those which do not. The restoration of natural land cover increases the surface roughness and the associated storage capability of the surface landscape, which provides natural opportunities for overland flow to slow its velocity, be captured by natural vegetation, and infiltrated into the soil profile. This, in turn, reduces the volume of water that enters artificial and natural waterways, thereby reducing stream flashiness and the likelihood of a flood event.
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Geographic Trends
Notable geographic trends are reported on a station basis (Figure 8). The station location should be considered when examining the results to better understand the spatial impact of the land cover gradient and how changes made to land cover affect the watershed surface hydrology.
• No flooding was observed in the watershed headwaters (Station 1) during the event-based model runs for all scenarios due to high infiltration capacity and minimal flow accumulation, which stems from the lack of developed land cover in this area.
• Consistent flooding was evident under all scenarios at Station 2, except for 8A and 8B. These scenarios represent the Transportation Outlook 2040 predictions, adapted land use recommendation and forecasted land use, respectively, with incorporation of a fully restored riparian buffer around main channels. Under the conditions present in these scenarios, flooding was not observed for storm events up to a 4.63-in depth (Scenario 8A) and 3.65-in depth (Scenario 8B).
• The flooding at Stations 5 and 6, which are both located in the highly developed tributaries of Tomahawk Creek and Indian Creek respectively, was impacted by changes in land cover. Under current conditions, Station 6 has a contributing area of approximately 18,101 acres, of which 36% (6,517 acres) is impervious; whereas, Station 5 has a contributing area of 13,047 acres with 29% (3,784 acres) impervious cover. Restoration of the riparian buffer resulted in large decreases in contributing impervious cover at these stations under Scenarios 3, 5, 8A, 8B, 9A, and 9B compared to their respective baseline scenarios.
• Station 4 is located at the confluence of Indian Creek and the Blue River. This area is characterized by a reduction in natural vegetation cover as a result of urbanization, resulting in regular flooding and high inflow volumes. Flooding was reduced by many of the land management scenarios, however, under very few circumstances was flooding eliminated entirely. Under Scenarios 3 (restoration of the riparian buffer of all streams including ephemeral streams), 8A (TO 2040 adapted land use recommendation with riparian buffer restoration), and 8B (TO 2040 forecasted land use recommendation with riparian buffer restoration), flooding was eliminated for up to the 3.08-in, 3.65-in, and 4.63-in storms, respectively. Flooding occurred under all other scenario-storm combinations. Since Station 4 is located mid-watershed, eliminating flooding is difficult due to the accumulation of flow and increasing amount of contributing impervious area moving towards the outlet.
• Station 10 is located near the heavily urbanized outlet of the Watershed in Kansas City, MO. The scenarios that applied riparian buffers around all streams, including ephemeral (Scenario 3), and several of the Transportation Outlook 2040 adapted land use scenarios with riparian buffer inclusion (Scenarios 8A and 9A) provided the greatest flood reduction benefits. Under these scenarios, all flow was contained within the channel and flooding was eliminated for up to the 3.65-in, 4.63-in, and 5.48-in storms, respectively. Other scenarios involving the restoration of the riparian buffer (Scenarios 5, 8B, and 9B) provided fewer flood reduction benefits due to the smaller area of land converted back to natural vegetation in these scenarios across the Watershed.
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Scenario Trends
Scenario BRW2: Conversion of Riparian Buffer to Managed Green Space
• The impact of converting the riparian buffer to a managed green space, Scenario BRW2, was determined by comparing this scenario to its respective baseline, Scenario 1B.
• The conversion of land cover within the riparian buffer to a managed green space (Scenario BRW2) increased flood potential at Stations 4 and 10. The land conversion impact on flooding in other parts of the watershed varied and did not follow a consistent pattern. While this land cover change did not increase the impervious area in the riparian area, it did impact other hydrologic parameters (e.g., surface roughness) which play a large role in capability of an ecosystem to capture and infiltrate runoff.
• The greatest difference in total inflow is realized in the headwaters, due to the loss of natural vegetation and associated hydrologic benefits. A reduction in total inflow is observed in the more developed parts of the Watershed, such as Stations 5 and 6, likely because the conversion to managed green space is an improvement over the developed impervious land cover that was present before.
• In general, converting natural vegetation within the riparian buffer to a managed green space is not a beneficial watershed management practice. When natural land cover was removed, the roughness of the surface decreased. This allowed water to flow more quickly across it, reducing the amount of infiltration that occurs. Thus, more water finds its way to the stream, increasing the stress placed on the waterway and the risk of flooding.
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Scenario BRW3: Riparian Buffer Restoration of All Streams (Including Ephemeral)
• The impact of riparian buffer restoration of all streams including ephemeral streams, Scenario BRW3, was determined by comparing this scenario to its respective baseline, Scenario BRW1C.
• The restoration of the riparian buffer surrounding ephemeral streams (Scenario BRW3) provided the greatest flood reduction of all scenarios considered, through the elimination of flooding at Stations 5 and 6 for all 24-hour storms up to 4.63-in. This is due to the larger amount of land restored to natural vegetation in this scenario compared to other scenarios considered.
• The flood reduction impact of riparian buffer restoration surrounding ephemeral streams varies across the Watershed, largely due to the existing land cover gradient (Figure 34a-c).
Figure 34. Total inflow during a 4.63-in storm at various locations in the Watershed (Stations 2 (a), 6 (b), and 10 (c), respectively) under current conditions (Scenario 1C) and riparian buffer restoration within 300-feet of all streams (Scenario 3). Restoration of the riparian buffer provided substantial reductions in total inflow across the watershed.
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Scenario BRW5: Riparian Buffer Restoration of Main Channels
• The impact of riparian buffer restoration of main channels, Scenario BRW5, was determined by comparing this scenario to its respective baseline, Scenario BRW1D.
• Very little developed land had to be removed from the buffer leading to Station 2 in order to fully restore the buffer. For this reason, restoration did not have a large impact on the total inflow observed at this station. The same was observed at Station 1, also located in the headwaters (Figure 35).
• Maintaining undeveloped land in close proximity to the stream network showed a large reduction in flooding. As such, Station 6 experienced a 116,000 cubic foot reduction in flooding during a 4.63-in, 24-hour storm when the riparian buffer was restored (Scenario BRW5; Figure 35).
• The restoration of the riparian buffer surrounding the main stream channels (Scenario BRW5) provided flood reduction benefits through the elimination of flooding at Stations 5 and 6 under 3.65-in and 3.08-in events, respectively. Flooding at Station 6 was less impacted than Station 5 by the restoration efforts due to the distribution of impervious cover and topography. Only 54 acres of impervious area was converted to natural cover within Station 6’s contributing area, as opposed to 122 acres for station 5.
Figure 35. Examining the total inflow at various locations in the Watershed, Stations 2 (a), 6 (b), and 10 (c), from a 4.63-in storm under current conditions (Scenario 1D) and riparian buffer restoration (Scenario 5) indicates restoration of the buffer improved the storage capacity of the system, reducing total inflow. Stations in in more developed tributaries, Station 6 included, saw the largest percent reductions in total inflow.
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Scenarios Defined by MARC’s Transportation Outlook 2040: BRW- 1E, 6, 7, 8A, 8B, 9A, 9B
Flooding and total inflow were not consistently reduced by implementation of MARC’s adapted land use recommendation (Scenario BRW7) compared to MARC’s forecasted land use (Scenario BRW6). Station 1 was the only station with a reduction in total inflow under MARC’s recommended land use (Figure 36), with a reduction of total inflow observed under all storms (Figure 37). After examining the results of the 3.08-in storm, all other stations did not experience a decrease in total inflow (Figure 36). This is likely due to the variation of changes in impervious cover across the Watershed. The reduction in impervious cover in the headwaters is not enough to reduce total inflow and flooding in the lower Watershed, especially since a slight increase in impervious cover was observed from Scenarios BRW6, forecasted, to BRW7, recommended, meaning more impervious cover was added in the lower Watershed (Figure 36; Figure 37).
Figure 36. Changes in inflow between MARC scenarios for a 3.08-in storm. Values are reported as a percent
change in inflow based on the difference between the scenarios listed. Scenario 6 and 7 represent forecasted and recommend land use respectively.
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Figure 37. Changes in inflow from MARC Scenario 6 (forecasted land use) to 7 (recommended land use).
• Further examination of the change in total inflow throughout the Watershed reveals the impact of land development on runoff patterns. Additionally, the amount of flow accumulation and impervious area play a substantial role in the magnitude of this impact. The highest percent increases in total inflow when moving from current conditions (Scenario 1E) to the forecasted (Scenario 6) or adapted recommendation (Scenario 7) land use were observed at Stations 1 and 2 which are located in the currently fairly undeveloped headwaters (Table 25). Stations in areas that are already developed (e.g., Stations 6, 5, 4, and 10) experienced increases in total inflow that were not as drastic in terms of percent change.
• The adapted land use recommendation (Scenario BRW7) only provided consistent reductions in total inflow at Station 1 compared to the forecasted land use (Scenario BRW6). Throughout the rest of the watershed, an increase in total inflow was observed under most precipitation events considered, with the 4.63-in storm at Station 4 being the only exception. This is due to the distribution of development in the adapted land use recommendation—the headwaters were preserved and the lower Watershed was further developed.
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Table 18. Percent change in inflow from one MARC scenario to another. Scenarios BRW- 1E, 6 and 7 represent current, forecasted, and adapted recommendation land use, respectively.
Values are reported as a percent. Cells highlighted in green indicate a decrease in inflow volume.
Storm Depth, in
Station 1 Station 2 Station 6 1E to 6 1E to 7 6 to 7 1E to 6 1E to 7 6 to 7 1E to 6 1E to 7 6 to 7
3.08 86 7 -43 176 176 0 3 5 2 3.65 69 12 -34 5 31 24 5 6 1 4.63 82 12 -39 5 30 24 -5 -4 2 5.48 38 12 -18 16 28 10 6 7 1 6.71 41 2 -27 0 9 9 2 4 2
Storm Depth, in
Station 5 Station 4 Station 10 1E to 6 1E to 7 6 to 7 1E to 6 1E to 7 6 to 7 1E to 6 1E to 7 6 to 7
3.08 7 17 9 5 10 5 2 8 6 3.65 2 6 4 3 9 6 1 7 6 4.63 -16 -14 3 6 -5 -11 1 2 0 5.48 16 28 10 5 6 1 1 4 3 6.71 16 35 17 12 17 4 1 3 3
• Flooding was reduced more inconsistently and less often by implementing MARC’s adapted land use recommendation (Scenario BRW7) as opposed to the forecasted land use (Scenario BRW6). No flooding was reported at Station 1 for any of the Transportation Outlook 2040 scenarios. Furthermore, changes in flooding varied across the Watershed. When the adapted land use recommendation (Scenario BRW7) was utilized in the model, flooding typically increased compared to current conditions (Scenario BRW1E) and the forecasted scenario (Scenario BRW6; Table 26). This is due to the increase in impervious cover in parts of the Watershed that are already highly developed due to the lack of natural land cover and the reduced ability to store water.
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Table 19. Summary of percent changes in flooding from one MARC scenario to another. Scenarios BRW-1E, 6 and 7 represent current, forecasted, and adapted recommendation land use, respectively.
Values are reported as a percent. Cells in green indicate a reduction in flooding was observed.
Storm Depth, in
Station 1 Station 2 Station 6 NA
(No Flooding Reported) 1E to 6 1E to 7 6 to 7 1E to 6 1E to 7 6 to 7
3.08 685 640 -6 NA 3.65 21 -22 -36 NA NA -100 4.63 -33 21 80 -94 -93 12 5.48 3 20 16 6 41 33 6.71 0 -3 -3 -23 -18 7
Storm Depth, in
Station 5 Station 4 Station 10 1E to 6 1E to 7 6 to 7 1E to 6 1E to 7 6 to 7 1E to 6 1E to 7 6 to 7
3.08 NA (No Flooding Reported)
13 34 18 NA 3.65 8 16 7 -5 132 144 4.63 NA NA 151 83 -4 15 20 7.4 11.8 5.48 146 269 50 -25 2 7 6 12.6 11.6 6.71 -34 76 165 44 2 8 6 4.2 9.7
82
• Implementation of MARC’s forecasted land use (Scenario BRW6) resulted in an increase in flooding across the Watershed. The greatest increase in flooding when moving from current conditions (Scenario BRW1E) to the forecasted land use (Scenario BRW6) was typically observed at Stations 4 and 5 (Figure 38a). These stations are in the middle of the Watershed, where runoff has the opportunity to accumulate more so than in the headwaters. In some cases, a reduction in flooding was observed in parts of the Watershed.
• In general, MARC’s adapted land use recommendation (Scenario BRW7) does not provide flood reduction benefits. Rather, an increase in flooding is expected under all precipitation events considered at most locations (Figure 38 b-c).
• Riparian buffer restoration under both the adapted land use recommendation (BRW8A) and the forecasted land use (BRW8B) provided a reduction in flooding at all stations. However, the forecasted land use with riparian buffer restoration (BRW8B) provided more inflow reduction benefits than the recommended land use with riparian buffer restoration (BRW8A). Scenario BRW8B contains roughly 3,000 more acres of impervious land than Scenario BRW8A. This demonstrates the importance of development patterns outside of the riparian buffer area, particularly the connectedness of impervious land use, and their impact on total inflow and flooding.
• Scenarios BRW8A and BRW9A both contain a fully restored riparian buffer and land use as defined by MARC’s TO 2040 adapted land use recommendation. Scenario BRW9A, however, also includes conservation development in a buffer surrounding the riparian buffer. Less than 2 acres of impervious cover had to be removed in the Watershed by abiding by the 29% maximum impervious cover guideline in the outer buffer. For this reason, Scenario BRW9A does not supply many added benefits compared to BRW8A due to the already low amount of impervious cover in the outer buffer.
• Scenario BRW9B, TO 2040 with forecasted land use, riparian buffer restoration, and maximum development in the outer buffers, developing the buffers to the 29% impervious maximum established during scenario planning, resulted in increases in total inflow and flooding (Scenario BRW9B).
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Figure 38. Examination of the percent change in flooding between (a) 1E to 6, (b) 1E to 7, and (c) 6 to 7 where land use of each scenario, 1E, 6, and 7, can be described as baseline, forecasted, and recommended respectively, demonstrated the forecasted land use (Scenario 6) is preferred to the recommended (Scenario 7).
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Land Development Trends
Riparian Buffers
• Scenario BRW2, which represents the conversion of riparian buffer into a managed green space, is not beneficial. The depth, flooding, and total inflow resulting from the conversion was greater than that of the baseline scenario. This was expected as the Manning’s N value decreased to account for the managed green space land cover, which offers less opportunity for runoff to slow down and be infiltrated when compared to traditional grassland or forest riparian cover.
• Scenario BRW3, which is the full restoration of the riparian buffer surrounding all streams (including ephemeral streams), is a beneficial practice. The conversion of land cover within this buffer to forested cover enables runoff to be captured and infiltrated on-site.
• Likewise, the restoration of the riparian buffer of main streams (i.e., ephemeral streams excluded) is a beneficial practice (Scenario BRW5). This conservation decision reduces the total inflow and flooding volumes throughout the watershed, and thus a reduction in maximum depth is observed as well.
• The restoration of the riparian buffer for all streams (Scenario BRW3) required 5,500 acres of land to be converted to deciduous forest from impervious cover. This is around 4,650 acres more land converted than was converted to achieve the full restoration of the 150-foot riparian buffer of main streams (riparian restoration of this scale required around 800 acres of land to be restored to deciduous forest). In order to determine if ephemeral stream or riparian buffer restoration is more beneficial, a cost estimation for each buffer option should be conducted. Although Scenario BRW3 typically provided a larger percent reduction in total inflow and flooding, the ratio of percent change in these parameters to acres converted is more often lower than that of Scenario BRW5 (Table 24). This means that riparian restoration around ephemeral streams is not as efficient in its reduction of total inflow and flooding per acre of land as riparian restoration around main channels. Different widths of ephemeral buffer restoration could be explored in the future to explore if buffer width improves the efficiency of the restoration. For instance, a 150-foot buffer around ephemeral streams would provide a better benefit efficiency comparison to Scenario BRW5 which utilizes a buffer of this same width but only around the main stream channels.
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Table 20. Change in total inflow and flooding volumes for a 4.63-inch storm event. Acres converted is based on the amount of impervious land located in the buffers prior to restoration of riparian vegetation.
Station Number Calculated Value Scenario 3 Scenario 5
Station 1
% Change in Inflow -38.4 -10.8 % Change Inflow/Acre Converted -0.0071 -0.0138
% Change in Flooding NA NA % Change Flooding/Acre Converted
Station 2
% Change in Inflow -53.6 8.2 % Change Inflow/Acre Converted -0.0099 0.0104
% Change in Flooding 183.1 -15.8 % Change Flooding/Acre Converted 0.0337 -0.0201
Station 6
% Change in Inflow -26.3 -16.5 % Change Inflow/Acre Converted -0.0048 -0.0210
% Change in Flooding -100.0 -91.9 % Change Flooding/Acre Converted -0.0184 -0.1171
Station 5
% Change in Inflow -25.1 -0.2 % Change Inflow/Acre Converted -0.0046 -0.0003
% Change in Flooding -100.0 9.2 % Change Flooding/Acre Converted -0.0184 0.0118
Station 4
% Change in Inflow -12.5 3.1 % Change Inflow/Acre Converted -0.0023 0.0040
% Change in Flooding -30.4 220.6 % Change Flooding/Acre Converted -0.0056 0.2810
Station 10
% Change in Inflow -18.3 -5.1 % Change Inflow/Acre Converted -0.0034 -0.0065
% Change in Flooding -60.2 -10.3 % Change Flooding/Acre Converted -0.0111 -0.0131
Overall, the riparian buffer restoration is a beneficial practice which provides reductions in total inflow and flood volume. These benefits are made possible due to the increased infiltration due to the increase in surface roughness (Manning’s N). Restoration of the riparian buffer area provides additional storage capacity for the system. In general, the more riparian buffer that is restored, the better.
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MARC Adapted Land Use Recommendation
• The adapted land use recommendation (Scenario BRW7) as defined by MARC’s Transportation Outlook 2040 preserved the land in the headwaters of each stream that contributes to the Blue River. Areas in the lower watershed were allowed to further develop. This method of land area conservation utilized did not provide the flood and total inflow reduction benefits that were desired. This is due to the increase in impervious cover in areas of the watershed that are already severely hydrologically damaged and do not contain much natural vegetation or green space where infiltration can occur. Since these areas are downstream from areas with substantial natural land cover remaining, runoff produced in the lower Watershed does not have the opportunity to infiltrate.
• The total inflow and flooding, as a result of the adapted land use recommendation (Scenario BRW7), was consistently higher than that of other scenarios including the forecasted land use scenario (Scenario BRW6; Figure 30). This trend strengthens moving towards the outlet of the Watershed due to the increase in flow and contributing area.
• The inclusion of a riparian buffer improved the outlook of both the forecasted (Scenario BRW8b) and recommended (Scenario BRW8a) land uses, resulting in decreases in flooding and total inflow throughout the Watershed. Restoring the riparian buffer provided opportunities for water to infiltrate throughout the Watershed.
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Figure 10. Total inflow observed at various locations throughout the watershed under land use scenarios as
defined by MARC’s TO 2040 under the 5.48-in, 24-hour storm. Scenario 1E represents land use under current conditions. Scenario 6 represents the forecasted land use. Scenario 7 represents the adapted land use recommendation. Scenarios 8A and 8B represent Scenarios 7 and 6 respectively with the addition of a fully restored riparian buffer. Scenarios 9A and 9B build off of 8A and 8B respectively with the addition of
conservation development within an outer buffer of the riparian area, limited to 29% or less for Scenario 9A and maximum development of 29% in the outer buffer for Scenario 9B.
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1E 6 7 8A 8B 9A 9B
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Tomahawk Creek Watershed Scenarios
Results from the more detailed Tomahawk Creek analysis indicate that riparian buffer implementation/restoration and increasing the percent of water that flows through green spaces before reaching the stream to at least 25% reduces peak inflow, total volume of inflow, and flood extent. These reductions are most prominent for the water quality (1.37 inches, Table 28) and smaller storms. However, significant peak inflow and total inflow volume reductions were seen for all rainfall events, including the 100-year design storm, as compared to the baseline (Table 29).
Table 21. Percent reduction in peak inflow and total volume of inflow from current conditions for the 1.37-inch, 24-hour precipitation event. Shading indicates statistically significant results.
1.37-inch, 24-hour
Table 22. Results of the Tukey Honest Significant Difference test comparing the baseline TCW5 scenario to all other scenarios. Comparisons with a p-value of less than 0.05 indicate a significant
difference between the results, and are shaded in gray.
Scenarios J06893500 J17 J27 Peak Inflow Volume Peak Inflow Volume Peak Inflow Volume
5-0 Fail to Reject Fail to Reject Fail to Reject Fail to Reject Fail to Reject Fail to Reject 5-25 Fail to Reject Fail to Reject Fail to Reject Fail to Reject Significant Fail to Reject 5-50 Significant Fail to Reject Significant Fail to Reject Significant Significant 5-75 Significant Significant Significant Significant Significant Significant
5-100 Significant Significant Significant Significant Significant Significant 5-0R Fail to Reject Fail to Reject Fail to Reject Fail to Reject Fail to Reject Fail to Reject 5-5R Significant Fail to Reject Fail to Reject Fail to Reject Fail to Reject Fail to Reject
5-25R Significant Significant Fail to Reject Significant Significant Significant 5-50R Significant Significant Significant Significant Significant Significant
Peak Inflow (cms) Total Volume (m3) Scenario J17 J06893350 J27 J17 J06893350 J27 TCW0 -6.44 -9.36 -10.87 -8.60 -7.72 -7.97 TCW25 25.07 27.85 29.48 31.58 27.40 27.93 TCW50 51.25 44.57 27.66 61.13 50.42 50.76 TCW75 62.17 48.44 28.52 77.57 62.45 62.75 TCW100 89.20 52.82 30.13 93.36 73.19 72.87 TCW0R 23.61 18.49 16.43 22.92 19.68 18.87 TCW5R 30.12 25.39 21.23 29.78 26.03 25.48 TCW25R 51.93 45.46 35.46 53.77 47.66 47.64 TCW50R 69.55 57.28 38.27 74.48 64.51 64.44 TCW75R 80.46 59.47 43.33 86.60 73.51 73.48 TCW100R 94.95 61.93 46.57 95.34 78.52 77.85
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When comparing specific storms, the flood extent was reduced more than 8% for the 1, 5, and 10-year design storms with implementation of Scenario TCW25R (Figure 40; Tables 30-31). These results indicate that increasing green infrastructure does increase flood resiliency for storms up to 5.48 in (10 year, 24 hour event), which would help with the expected increase in storms as predicted by the IPCC (Revi, 2014). However additional structural flood control is needed to reduce flood extent greater than 10% and for flood control of larger events (e.g. design storms of 100+ years).
Figure 40. There was a 9.9% flood extent reduction for the 5-year, 24-hour storm in the Tomahawk Creek Watershed with maximum green infrstructure measures (Scenario TCW100R) implemented.
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Table 30. Percent reduction in peak inflow and total volume with addition of 150 ft. riparian buffer and 25% “disconnectedness”
through green infrastructure implementation. Shading indicates statistically significant results.
Scenario 25R
Peak Inflow (cms) Total Volume (m3)
Storm J17 J06893350 J27 J17 J0689335
0 J27
1in, 24-hour 90.31 58.90
36.10
59.29 56.42
56.60
1in, 6-hour 51.36 49.53
44.41
55.85 49.74
49.93
1.37in, 24-hour
51.93 45.46
35.46
53.77 47.66
47.64
1.37in, 6-hour
20.06 29.63
28.97
28.27 26.13
25.34
1-year, 24-hour
13.94 12.87
14.59 7.43 8.18 7.51
5-year, 24-hour
10.60 5.01 3.97 4.18 4.98 3.55
10-year, 24-hour 9.80 4.90 0.70 3.66 4.52 3.86
25-year, 24-hour 8.88 2.85 0.52 3.24 4.06 3.85
100-year, 24-hour 6.51 2.20 0.47 2.78 3.56 4.39
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Table 31. Percent reduction in peak inflow and total volume with addition of 150 ft. riparian buffer and 100% “disconnectedness”
through green infrastructure (GI). Shading indicates statistically significant results.
Scenario TCW100R, "Maximum GI Implementation"
Peak Inflow (cms) Total Volume (m3)
Storm J17 J06893350 J27 J17 J06893350 J27
1in, 24-hour 100.0 97.9 99.3 100.0 95.6 97.7
1in, 6-hour 100.0 77.3 71.1 99.9 86.4 86.9
1.37in, 24-hour 95.0 61.9 46.6 95.3 78.5 77.8
1.37in, 6-hour 42.5 43.6 39.5 50.7 44.8 43.3
1-year, 24-hour 22.0 24.6 22.6 13.0 15.1 14.2
5-year, 24-hour 20.9 11.3 10.8 8.1 9.9 7.4
10-year, 24-hour 20.1 10.7 4.3 7.1 8.8 7.6
25-year, 24-hour 19.2 7.3 5.8 6.4 7.9 7.4
100-year, 24-hour 19.2 7.5 1.6 8.3 11.4 12.1
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Conclusions
General Scenario Review
The intent of this study was to develop a general understanding of the value of green infrastructure for mitigating flood potential and creating a more resilient landscape. The study was conducted at a relatively large scale in order to understand potential general impacts across the watershed. The general consequences of each scenario should be considered when determining which land management practices are suitable for implementation in the Blue River Watershed (Table 29). Scenarios involving the preservation and/or restoration of natural land cover (e.g., Scenarios BRW3, BRW5, BRW8A, and BRW8B and all TCW with riparian buffers and increased disconnectedness) are desirable due to the increases in the ability to slow, capture, infiltrate, and store water. Ultimately, these natural hydrologic mechanisms reduce the total inflow volume, stream depth, and flood volume throughout the Watershed. When riparian buffer restoration was coupled with conservation development (e.g., Scenarios BRW9A and BRW9B in addition to the TCW disconnected scenarios) similar benefits were evident, albeit dependent on development limitations. Alternatively, disturbance of the riparian buffer (e.g., Scenario BRW2) or development of more land in the Watershed (e.g., Scenarios BRW6 and BRW7) was not beneficial compared to baseline scenarios and limited the hydrologic capabilities of the system.
These results show that green infrastructure, particularly green infrastructure that disconnects impervious landcover from flow paths such as riparian buffers, has the potential to create a more sustainable, resilient landscape. Future studies should be conducted at finer resolution to further understand and optimize types of green infrastructure (e.g. buffers, biorentention, wetlands, etc.) as well as geospatial placement of the infrastructure across the watershed.
Development
Continued development of the Blue River Watershed is expected to occur in the future. The removal of natural land cover for the development of neighborhoods, production agriculture, or other uses will negatively impact the hydrology of the Watershed and increase flood potential. However, careful planning and evaluation of potential development strategies before implementation could help minimize this impact. The spatial distribution and connectivity of green spaces, as well as the amount of development (i.e., impervious land cover), plays a substantial role in determining the overall watershed response.
From this standpoint, conservation development strategies would be beneficial for the Blue River Watershed. Scenario BRW7, the adapted land use recommendation as defined by MARC’s “LU_ADAP” data layer, was applied to explore a potential development strategy for the Watershed. Under this recommended land use, undeveloped land in the headwaters was preserved while land near the outlet typically remained the same or increased slightly in development. This approach focused on preventing further harm (in terms of development and the associated impact on hydrology) rather than undoing damage already done. However, model results indicated that this approach is not beneficial, in terms of providing system-wide flood reduction benefits, across the whole Watershed. Only headwater stations (Stations 1 and 2) experienced total inflow reduction benefits. Furthermore, flood reduction benefits were not uniform or consistent and were observed mainly in the headwaters (though there were a few instances of flood reduction in the lower and mid Watershed). With this in mind, simply preserving natural land in the headwaters of the Blue River Watershed is not sufficient to reduce the overall risk of flooding and excessive total inflow observed throughout the Watershed. A conservation development strategy suitable for the unique land use gradient in this watershed would likely need to incorporate more land restoration in the lower Watershed in addition to protection of
92
natural land cover in the upper Watershed to restore some of the natural hydrologic function throughout the Watershed. It should be noted that conservation of natural land and limitation of development in the upper Watershed is crucial to achieving flood reduction downstream and minimizing additional stress put on the Blue River.
When formulating a conservation development strategy for the Blue River Watershed, development restrictions could also be implemented. Scenarios BRW9A and BRW9B explored the benefit of restricting the development within an outer buffer of the stream network. This is especially helpful if development outside of these buffers exceeds the maximum development within the buffers; this was not the case in the scenarios explored in this study. With reduced development, less runoff is generated and overland flow has the opportunity to slow its velocity and infiltrate into the soil profile. Additionally, policies that protect riparian buffers from development would aid in reducing the strain on both natural and man-made waterways.
Policy
Policies which aim to protect the riparian buffer and increase disconnectedness of impervious surfaces and structures should be adopted consistently throughout the watershed. Restoration of the entire riparian corridor provided benefits as observed in Scenarios BRW3, BRW5, BRW8A, BRW8B, and BRW9A as well as in all TCW scenarios with the buffer. The TCW model runs also showed significant improvements in hydrologic function with increased disconnectedness of impervious surfaces, indicating the value of green infrastructure implementation and the reduction on direct outfalls into surface creeks. Alternatively, disturbance of this riparian area resulted in increased flooding and total inflow. Since a reduction in flooding in the lower Watershed is desired, disturbance of the riparian buffer should be avoided.
Restoration of the riparian buffer and the reduction of impervious connectedness through implementation of green infrastructure offers numerous hydrologic benefits throughout the Watershed. Since development reduces the ability for water to infiltrate, protecting natural hydrologic function throughout the Watershed with infiltrating green infrastructure (e.g. bioretention, rain gardens, etc.) and near the channel with riparian buffers is important. Without preservation of riparian area in the upper Watershed, the hydrologic benefits achieved in the lower, more developed parts of the Watershed are reduced. In general, consistent protection of the riparian corridor is needed to maximize the benefits provided throughout the Watershed.
Flood reduction benefits increase as more land is restored around streams. The greatest flood and total inflow reduction benefits are observed when ephemeral streams are included in the restored stream network. However, this restoration strategy requires a larger area of land to be protected, thus lowering the efficiency of the benefits (volume reduction / acre impervious converted). An evaluation of the restoration cost versus benefits provided is needed. In future analysis, other ecosystem services such as habitat restoration, biodiversity, and recreational opportunities should also be considered in the value of the total benefits provided by restoration and preservation of natural land at varying distances from the stream centerline. Inclusion of the value of these additional benefits provided by restoration must be included and thoroughly explored before management decisions are made. Incorporation of these benefits will require a robust analysis in order for their full value to be represented.
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