comparing different approaches of catchment delineation · comparing different approaches of...

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Comparing Different Approaches Of Catchment Delineation Mi Chen, Ph.D. 1 , Cindi Tucker 2 , Srini Vallabhaneni. P.E., DEE 3 , Joe Koran, P. E. 4 , Melissa Gatterdam 4 , Derek Wride, P. E. 1 Abstract Catchment delineation is one of essential steps for sewershed modeling studies. The traditional manual catchment delineation method for large-scale sewersheds is time consuming. Advanced functions in GRID module of ArcInfo help modelers to automatically delineate watersheds. By adapting these functions, three automatic approaches to delineate catchments were developed with consideration of sewer network characteristics. It was unknown, however, to what extent the modeling results differed based on the manual and different automated methods. This paper presents the development of automatic delineations and compares the modeling results from automatic approaches and from manual operation to explore potential applications of GIS to sewershed studies. 1 CDM, 8805 Governor’s Hill Dr. Suite 260, Cincinnati, OH 45249 2 CDM, 50 Hampshire St., Cambridge, MA 02139 3 CDM, 3750 Priority Way S. Dr., Suite 114, Indianapolis, IN 46240 4 Metropolitan Sewer District of Greater Cincinnati, OH. 1600 Gest St., Cincinnati, OH 45204

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Page 1: Comparing Different Approaches Of Catchment Delineation · Comparing Different Approaches Of Catchment Delineation Mi Chen, Ph.D.1, Cindi Tucker 2, Srini Vallabhaneni. P.E., DEE 3,

Comparing Different ApproachesOf Catchment Delineation

Mi Chen, Ph.D.1, Cindi Tucker 2, Srini Vallabhaneni. P.E., DEE 3, Joe Koran, P. E.4,Melissa Gatterdam 4, Derek Wride, P. E.1

Abstract

Catchment delineation is one of essential steps for sewershed modeling studies.The traditional manual catchment delineation method for large-scale sewershedsis time consuming. Advanced functions in GRID module of ArcInfo helpmodelers to automatically delineate watersheds. By adapting these functions,three automatic approaches to delineate catchments were developed withconsideration of sewer network characteristics. It was unknown, however, towhat extent the modeling results differed based on the manual and differentautomated methods. This paper presents the development of automaticdelineations and compares the modeling results from automatic approaches andfrom manual operation to explore potential applications of GIS to sewershedstudies.

1 CDM, 8805 Governor’s Hill Dr. Suite 260, Cincinnati, OH 452492 CDM, 50 Hampshire St., Cambridge, MA 021393 CDM, 3750 Priority Way S. Dr., Suite 114, Indianapolis, IN 462404 Metropolitan Sewer District of Greater Cincinnati, OH. 1600 Gest St., Cincinnati, OH 45204

Page 2: Comparing Different Approaches Of Catchment Delineation · Comparing Different Approaches Of Catchment Delineation Mi Chen, Ph.D.1, Cindi Tucker 2, Srini Vallabhaneni. P.E., DEE 3,

Introduction

A watershed (or drainage basin) is a spatial unit where integrated watermanagement can be accomplished (Singh, 1995). Searching for approaches forwatershed protection has been a major task for water resource scientists and engineers.Watershed (drainage basin) modeling is a tool for the watershed management.Physically based methods are preferred, based on recent advances in watershedhydrological modeling (Bhaskar et al., 1991). Physical-based distributed models accountfor the spatial heterogeneity through an analysis based on principles of conservation ofmass, on quantities of motion, and on energy to evaluate the evolution of the physicalsystem (Colosimo and Mendicino, 1996). The accuracy of the model simulation largelydepends on how correctly modelers describe the variables in a basin system and theresolution of the cell in which hydrological quantities can be speculated as beinghomogeneous (Wilson et al., 1984).

Due to spatial and temporal variations of the characteristics of a watershed, it isoften necessary to delineate a watershed into smaller-sized modeled areas wherevariables can be considered homogenous. The size of a modeled area is based on thedegree of the study details and the assumption that homogeneity of the watershedcharacteristics can be considered by the modelers. The smallest area that a hydrologicmodel can be applied to is called a catchment in this study. Therefore, the process ofcatchment delineation is an important step that impacts the hydrologic modeldevelopment. Catchment delineation can be very tedious without automatic methodswhen very detailed catchments (more than hundreds catchments) are delineated in awatershed and hundreds of watersheds are defined in an entire study area.

Recently, many studies addressed the importance and procedures for river basinwatershed delineation using GIS (Geographic Information System) tools. Following thesame procedures, a large watershed can be delineated into several sub-watersheds, oreven many catchments at a finer level. The available procedures delineate thewatershed (sub-watershed or catchment) boundaries, based on the topography of thesurface, to determine the concentrated channel flow directions. An urban drainagebasin (watershed) boundary, however, is strongly influenced by the topology of thesewer system rather than by the natural river basin. This impact is sometimes displayedby the aspect that the directions of flow in the sewer system do not agree with thedirections of the surface runoff along the topography of a basin (watershed). This isbecause underground man-made sewer networks do not always follow the surfacetopography with consideration of the location of a wastewater treatment plant (WWTP)and the service area of a WWTP. This kind of urban drainage basin (watershed) is oftencalled a sewershed. Therefore, the GIS functions frequently implemented to delineatesub-sewersheds (and catchments) may not properly or accurately perform withoutconsidering the sewer system impact, which will ultimately influence modeling results.Consequently, new methods were developed based on an integration of the watersheddelineation functions in the GRID module of ArcInfo with the sewer system topology.

In this study, three automatic catchment delineation methods were developed.These methods have been named (1) the Watershed method, (2) the Basin method, and(3) the Proxy method. These three automated methods and the traditional manualmethod were applied to delineate catchments in a sewershed. Using the four different

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products of delineated catchments, a hydrologic model - SWMM (Storm WaterManagement Model) - was applied to generate the hydrological responses of thesewershed. The modeling results from the four different methods were comparedagainst the observed data. The purpose of this study was to explore the feasibility andeffectiveness of the automatic catchment delineation methods and to evaluate theirimpacts on the hydrologic modeling.

Experiment Design

1.0 Study Area

Two study sewersheds were selected from the recently developed System WideModel (SWM) Project in Cincinnati, Ohio. The SWM Project was conducted by theMetropolitan Sewer District of Greater Cincinnati (MSD), where Camp Dresser & McKeeInc. (CDM) was the lead consultant managing the team effort, including a number a sub-consultants, to develop and calibrate a computer model of the wastewater collectionsystem. Sophisticated computer models for the entire MSD sewer system weredeveloped for the evaluation of various planning scenarios. The entire study area(shown in Figure 1-1) was about 257 mi2 with 42,084 modeled pipes and 42,206 modeledmanholes

Due to the large scale of the system, the study area was divided into drainagebasins and sub-basins at several different levels in order to organize and manage themodel input data. Following the three major river basins, the three major drainagebasins shown in Figure 1-2 were defined: the Mill Creek Drainage Basin, the LittleMiami Drainage Basin, and the Great Miami Drainage Basin. Following wastewatertreatment plant (WWTP) service boundaries rather than river basin boundaries,modeled WWTP service areas shown in Figure 1-3 were defined. The seven major MSDWWTP service areas were the Mill Creek, Little Miami, Muddy Creek, Sycamore, PolkRun, Taylor Creek, and Indian Creek WWTP service areas. An additional finer level ofbasin delineation was at the sub-basin level, as shown in Figure 1-4. The eighteendrainage sub-basins were further subdivided into approximately 300 sewersheds, asshown in Figure 1-5, to provide a finer level of detail for supporting project execution.The flow monitoring program associated with the SWM Project was organized at thesewershed level--each sewershed had one flow monitoring station installed at the outlet.In this project, the finest level of basin delineation was at the catchment level.

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The catchments were required and delineated during model development torepresent the drainage area associated with each flow loading point on the modeledsewer network. The sewershed characteristics (i.e., inflow/infiltration parameters forseparate sewersheds, and runoff parameters for combined sewers) were determined atthe catchment level and used as model input.

Figure 1-1 Entire study area – MSD System Wide Model

Note: red lines: combined sewers; blue lines: sanitary sewers

Page 5: Comparing Different Approaches Of Catchment Delineation · Comparing Different Approaches Of Catchment Delineation Mi Chen, Ph.D.1, Cindi Tucker 2, Srini Vallabhaneni. P.E., DEE 3,

Figure 1-3 Seven major WWPT service areas – MSD – System Wide Model

G r e a t M i a m i

M i l l C r e e k

L i t t l e M i a m i

Ohio River Downtown Cincinnati, OH

Figure 1-2 Major drainage basins Ö MSD System Wide Model

Page 6: Comparing Different Approaches Of Catchment Delineation · Comparing Different Approaches Of Catchment Delineation Mi Chen, Ph.D.1, Cindi Tucker 2, Srini Vallabhaneni. P.E., DEE 3,

Two types of sewersheds were selected in this study based on (1) the

Ohio RiverDowntownCincinnati, OH

Figure 1-4 Eighteen Sub-basins – SWM System Wide Model

Ohio RiverDowntownCincinnati, OH

Selected Sanitary Sewershed

Selected Combined Sewershed

Figure 1-5 Sewersheds – MSD –System Wide Model

Page 7: Comparing Different Approaches Of Catchment Delineation · Comparing Different Approaches Of Catchment Delineation Mi Chen, Ph.D.1, Cindi Tucker 2, Srini Vallabhaneni. P.E., DEE 3,

characteristics of the sewer system in the sewershed, (2) the consideration of cleanobserved flow data obtained from the flow monitoring station located at the outlet of thesewershed, and (3) the different approaches of model development. One sewershed(Sanitary Sewershed) included all sanitary sewers and another (Combined Sewershed)included mostly combined sewers. Sanitary sewers carry wastewater discharged fromhomes, businesses, industries, etc., and exclude direct storm water runoff from asewershed. Combined sewers carry the wastewater discharged from consumers as wellas storm water runoff during rainfall events. The size of the Sanitary Sewershed was122 acres, with 77 manholes and 77 sanitary sewer pipes. This sewershed waspredominantly residential area with 577 households. A flow monitor was installed atthe outlet of the sewershed. Figure 1-6 displays the map of the sanitary sewershed. Thesize of the Combined Sewershed was 473 acres, with 448 manholes and 455 combinedsewer pipes. There were 1,797 buildings, with the majority being residential and a fewcommercial and school areas included. A flow monitor was installed at the outlet of thesewershed. Figure 1-7 displays a map of the Combined Sewershed.

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Sewersheds

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Modeled Sewers

# Modeled Manholes%[ Flow Monitor Location

Buildings

MSD Manholes#

Legend

800 0 800 Feet

Figure 1-6 Map of Sanitary Sewershed

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2.0 Materials and Methods

The required GIS data for catchment delineation were either directly obtained orderived from the Cincinnati Area Geographic Information System (CAGIS) by the modelingteam. CAGIS is a mature GIS established “to offer government, utility companies, groups,or citizens a new, intelligent, and cost-effective tool to make informed decisions based onshared data.” CAGIS established the “foundation for automating the functions ofgovernment and utilities whose activities create the inventories of sewers, land records,water, drainage, electrical systems, streets, right of way, etc., for supporting the community”(http://www.cagis.hamilton-co.org/CAGIS/DataDictionary/Cagorganization.html).Among the many GIS shape files provided, the major files used for the delineation effortincluded: (1) the modeled sewer network data, including pipes and manholes (individualunique identified database records with attributes of x-y grid coordinates, invert elevations,pipe diameters, plan lengths, and pipe material, manhole rim elevations, manhole depths,etc.); (2) two-foot contours; (3) loading points; (4) property parcel lines; and (5) sewershedboundaries. The modeled sewer network data were derived using ArcView 3.X from theCAGIS MSD sewer shape file. Based on the project scope, the modeled sewer pipesincluded sanitary sewers with a diameter of 12 inches or greater and combined sewers witha diameter of 18 inches or greater. The 2-foot contours were directly from CAGIS. Theloading points were determined by the modelers by using ArcView 3.X and the MSD sewer

Figure 1-7 Map of Combined Sewershed

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%[

Sewersheds

Msd Sewers

StreetsStreams

Modeled Sewers

# Modeled Manholes

%[ Flow Monitor LocationBuildings

MSD Manholes#

Legend

1000 0 1000 2000 Feet

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manhole shape file. The general rule was to consider each sanitary manhole as a loadingpoint, where feasible. For the combined sewershed, the guidelines for determining loadingpoints included the manholes where direct stormwater runoff entered the sewer system viastormwater inlets. The sewershed boundaries were derived as presented in the previoussection.

2.1 Three Automated Catchment Delineation Methods

The Watershed Method

In the ArcInfo and ArcInfo GRID environments, catchments were delineatedwith an automated GIS method. The method was based on the work done by Olivera(1996) at the Center for Research in Water Resources at the University of Texas at Austin(Maidment, 2003). The Center identified a method for “burning” a stream network intoa Digital Elevation Model (DEM), thus, forcing flow direction into the stream network.Our study adapted the “stream burning” method for sewershed catchment delineation.In this method, the processed CAGIS GIS data included two-foot contours, modeledsewers, loading points, and sewershed boundaries. Using several ArcInfo commandsand GRID functions, the sewer network was “burned” into the DEM that was createdfrom the contour elevations, and GRID’s WATERSHED function was applied to createthe catchments.

To begin, all CAGIS data was converted to coverage format. A depressionlessDigital Elevation Model (DEM) shown in Figure 2-1 was created from the two-footcontours and the sewer network and loading points were both converted to grids, takingcare to be sure that the grid cells overlay by choosing equivalent parameters (cell sizeand X, Y extents) for each grid. A depressionless DEM is a surface that has beencorrected for sinks or other errors so that the grid is hydrologically correct. The loadingpoints grid was created with the POINTGRID command but to create the sewer networkgrid, several commands and grid functions were used. The sewer grid created was athree-dimensional representation of the modeled sewer network where the only grid cellvalues populated were those that overlay the arcs in the sewer coverage. All other gridcells had a no data value, creating a three-dimensional pipe alignment. Pipe flowdirection was maintained within the sewer pipe alignment based on the flow directionof the sewer pipe and the invert elevations. This was accomplished by creating twosewer grids, the first with the LINEGRID command, and the second with theTOPOGRID command. Once checked for errors, the first grid was set as a mask(SETMASK command) and merged (MERGE function) with the second grid to create thefinal sewer grid that was “burned” into the DEM.

To burn in the sewer network, the DEM elevations were raised by a constantvalue. This was done to avoid negative elevations. The sewer grid was merged(MERGE function) with the raised DEM, as illustrated in Figure 2-2, and served as theinput for the FLOWDIRECTION and WATERSHED functions. The merge functionignores the “no data” cells in the pipe grid and transfers only the populated cell valuesonto the raised DEM, thus, imprinting or “burning” the sewer network into the DEM.The flow direction grid determined the flow direction from each cell to its steepest down

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slope neighbor, showing how water flows out of each cell. If there were obvious errorsin the data, this grid would help to determine where these errors existed so that theycould be corrected prior to the catchment delineation.

Figure 2-1 DEM of Combined Sewershed

Finally, catchment delineation was done with the WATERSHED function. TheWATERSHED function determined the contributing area above a set of cells in a grid.The flow direction grid and loading point grid were used as input to the watershedfunction. The loading points became the outlet or pour points that determined how thesewershed was divided into catchment boundaries. The catchment grid was convertedback into a coverage and the vestige cell boundaries were smoothed.

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Figure 2-2 “Burned” Surface of Combined Sewershed

The Basin Method

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The Basin Method was performed in much the same way as the WatershedMethod. The same grids produced using the Watershed Method were applied to dividethe sewershed into catchment areas. Therefore, all of the steps performed prior to usingthe WATERSHED function were exactly the same. The difference was that the BASINfunction was used to determine the catchment boundaries from the flow direction grid.The BASIN function delineated drainage basins by identifying ridge lines betweenbasins. In addition, the contributing areas for any pour points and sinks present in theflow direction grid were delineated.

The Proxy Method

For this study, sewer catchments were delineated using a Proximity Analysismethod within the ArcView 3.X environment. Proximity analysis attempts to mimic themanual techniques used to delineate catchments primarily in sanitary sewershed areas.This method dissolves parcel boundaries based on each parcel’s proximity to ageneralized sewer network. The CAGIS parcel, modeled sewers, and loading pointswere used to perform the analysis.

To generalize the modeled sewer network, a trace routine was developed usingthe Avenue programming language. The script traced the sewer network downstreamfrom loading points, generalized the sewer network between loading points to create asewer pipe reach, and coded the sewer pipe reach with the upstream and downstreamloading point identifier (the reaches shown in different colors in Figure 2-3). To definethe catchment boundaries, the nearest pipe reach was determined for each individualparcel. The parcels were coded with the pipe reach identifier and dissolved on thisattribute. The final result is shown in Figure 2-3.

The Manual Method

In the ArcView 3.X environment, the catchments were delineated manually byour modeling team members. For the Combined Sewershed, the loading points wereselected from the CAGIS MSD Manhole shape file by identifying the manholes wherenon-modeled pipes joined and where stormwater runoff discharged to the sewersystem. Following the surface flow directions indicated by the 2-foot contour lines, thecatchment boundaries were traced by a line perpendicular to the contour lines at theupstream area of each loading point. For the Sanitary Sewershed, each manhole wasconsidered as a loading point and the parcel lines were used as major dividers ofcatchment boundaries. Following the flow directions in the sewers, each catchmentcontained one loading point.

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2.2 Modeling Simulations

After catchments were delineated for each sewershed, the smallest modelingunits were set up. There was a need to manually adjust some loading point locationscorresponding to the finished catchment boundaries. The associated catchmentinformation regarding the size, location in a sewershed, the number of households, thewater consumption records from each household, land uses, soils, and surface slopes,etc., was required and derived based on the delineated catchments to develop the modelinput data set. According to the four catchment delineation methods, there were fourinput data sets for the Sanitary Sewershed and the Combined Sewershed. In the fourmodel data sets for the two sewershed types, the difference was made to the inputsassociated with the delineated catchments and loading points while the remaining inputdata remained unchanged. For each of the model input datasets (four for Sanitary; four

Figure 2-3 Pipe reaches and catchments results with the Proxy Method

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for Combined; eight in total), the runoff was simulated for three historical rainfall eventsusing the RUNOFF (hydrologic) and EXTRAN (hydraulic) modules of the SWMMsoftware (24 total simulations). For the Sanitary Sewershed, the three selected rainfallevents occurred on 2/09/2001, 2/25/2001 , and 4/15/2001. For the CombinedSewershed, the three selected rainfall events occurred on 3/25/2002, 4/21/2002, and5/12/2002. For each rainfall event simulation, the model flow results from each of thefour methods were compared against each other at the outlet point of the sewershed andthe observed flow data were used as the reference. The compared results included thetotal volume of the runoff, the peak flow rate, and the first peak flow time.

Table 2-1 Simulations for different catchment delineations in a given rainfall event

Different Catchment Delineations

WatershedMethod Basin Method Proxy Method

ManualMethod

Sanitary Sewershed Simulation 1 Simulation 2 Simulation 3 Simulation 4

Combined Sewershed Simulation 1 Simulation 2 Simulation 3 Simulation 4

3.0 Results and Discussions

3.1 Sanitary Sewershed

The products of delineated catchments using the different methods for theSanitary Sewershed are displayed in Figures 3-1, 3-2, 3-3, and 3-4. The results indicatethat the different delineation methods generated the catchments quite differently. Theareas of the catchments delineated by the Watershed Method, the Basin Method, theProxy Method, and the Manual Method covered about 80 percent, 100 percent, 66percent, and 89 percent of the sewershed, respectively. Table 3-1 lists the number ofcatchments and the smallest and largest sizes of the catchments based on the fourmethods. It reveals that the catchments generated by the Proxy Method were close tothe catchments generated from the Manual Method; however, the Proxy Method missedsome part of the sewershed shown in Figure 3-2. For the Sanitary Sewershed, both theManual Method and the Proxy Method used a similar approach in that the propertyparcel boundaries were used as major dividers of the catchments. The figures show thatthe automatic delineation methods created more or less sliver polygons at the edge of

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the sewershed boundary. The Basin Method created the most sliver polygons as shownin Figure 3-3. These polygons were consolidated with the adjacent catchments;however, some major missing areas of the sewershed caused by the Watershed andProxy Methods impacted the modeling results.

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Figure 3-1 Catchments delineated by the Watershed method for SanitarySewershed

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Figure 3-3 Catchments delineated by the Basin method for Sanitary Sewershed

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Figure 3-4 Catchments delineated by the Manual Method for Sanitary Sewershed

Table 3-1 Comparing Sanitary Sewershed catchment delineation results

Catchment DelineationNumber ofCatchments

The SmallestCatchment

(ac)

The LargestCatchment

(ac)

Watershed Method 33 0.1 24

Basin Method 149 0.1 33

Proxy Method 71 0.1 7

Manual Method 67 0.2 10

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The simulated and observed hydrographs at the outlet of the Sanitary Sewershedare shown in Figures 3-5, 3-6, and 3-7 for the three rainfall events. The flow patternsgenerated based on the four catchment delineation methods agreed with the observedflow pattern. Table 3-2 summarizes the comparisons between the four methods. Thetotal amount of flow had slight differences from the observed flow. As expected, theProxy Method had larger under-predictions for all events due to some un-delineatedsewered areas in the sewershed. The same reason caused the lower peak flow rates fromthe Proxy Method. Compared to the observed time to peak, less than 10 minutesdifference was observed in the times to peak from all methods for the last two rainfallevents, while the predicted times to peak exhibited 20 to 25 minutes lag for the firstevent. The simulated times to peak based on the four methods, however, were veryconsistent, with less than a 10-minute discrepancy. In general, the simulations based onthe four catchment delineation methods had very good predictions for the total amountof flow and the time to peak. Regarding the peak flow rate, the Manual and BasinMethods generated better results than the Proxy and Watershed Methods for the firstand second rainfall events, while the Proxy and Watershed Methods generated betterresults for the last rainfall event.

Figure 3-5 The observed and simulated hydrographs at the outlet of SanitarySewershed during the 2/09/01 rainfall event

Gray: observed flow data

Black: the result from the Manual method

Red: the result from the Proxy method

Purple: the result from the Watershed method

Green: the result from the Basin method

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Gray: observed flow data

Black: the result from the Manual method

Red: the result from the Proxy method

Purple: the result from the Watershed method

Green: the result from the Basin method

Figure 3-6 The observed and simulated hydrographs at the outlet of SanitarySewershed during the 2/25/01 rainfall event

Figure 3-7 The observed and simulated hydrographs at the outlet of SanitarySewershed during the 4/15/01 rainfall event

Gray: observed flow data

Black: the result from the Manual method

Red: the result from the Proxy method

Purple: the result from the Watershed method

Green: the result from the Basin method

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Table 3-2 Comparison between the observed and simulated flow data for SanitarySewershed

2/09/2001 Rainfall Event

ManualMethod

BasinMethod

ProxyMethod

WatershedMethod

ObservedData

Total Volume (ft3) 6.39x104 6.25x104 5.62x104 5.83x104 6.16x104

Maximum Flow (cfs) 1.345 1.284 1.008 1.105 1.33

Minimum Flow (cfs) 0.154 0.154 0.154 0.0 0.101

Difference between the Total Observedand Simulated Volume

3.7% 1.5% -8.8% -5.4% 0.0%

Difference between the MaximumObserved and Simulated Flow

1.1% -3.5% -24.2% -16.9% 0.0%

Peak Flow Time 19:25 19:35 19:30 19:30 19:10

2/25/2001 Rainfall Event

ManualMethod

BasinMethod

ProxyMethod

WatershedMethod

ObservedData

Total Volume (ft3) 5.48x104 5.42x104 5.01x104 5.15x104 5.33x104

Maximum Flow (cfs) 0.815 0.756 0.591 0.648 0.979

Minimum Flow (cfs) 0.191 0.167 0.166 0.166 0.161Difference between the Total Observed

and Simulated Volume2.8% 1.7% -6.0% -3.4% 0.0%

Difference between the MaximumObserved and Simulated Flow

-16.8% -22.8% -39.8% -33.8% 0.0%

Peak Flow Time 5:00 5:05 5:05 5:05 4:55

4/15/2001 Rainfall Event

ManualMethod

BasinMethod

ProxyMethod

WatershedMethod

ObservedData

Total Volume (ft3) 5.00 x104 4.94 x104 4.66 x104 4.76x104 5.07 x104

Maximum Flow (cfs) 0.946 0.914 0.746 0.801 0.825

Minimum Flow (cfs) 0.142 0.142 0.142 0.142 0.161Difference between the Total Observed

and Simulated Volume-1.4% -2.6% -8.1% -6.1% 0.0%

Difference between the MaximumObserved and Simulated Flow

14.7% 10.8% -9.6% -2.9% 0.0%

Peak Flow Time 11:00 11:05 11:10 11:10 11:00

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3.2 Combined Sewershed

The products of delineated catchments based on the four catchment delineationmethods for the Combined Sewershed are illustrated in Figures 3-8, 3-9, 3-10, and 3-11.The results indicate that the different delineation methods generated the catchmentsquite differently. As noted earlier, Table 3-3 lists the number of catchments and thesmallest and largest sizes of the catchments based on the four methods. This reveals thatthe catchments generated by the Watershed Method more closely resembled thecatchments generated from the Manual Method. The explanation is that the WatershedMethod used the most selected loading points with the “burned” sewer network in theDEM to generate the catchments, which was similar to the approach used for manuallydelineating the catchments. The Basin Method, however, generated the catchmentsbased on automatically selected loading points formed by the topography of the DEMwith the “burned” sewer network.

Table 3-3 Comparing Combined Sewershed catchment delineation results

Catchment DelineationNumber ofCatchments

The SmallestCatchment

(ac)

The LargestCatchment

(ac)Watershed Method 60 0.9 55

Basin Method 18 1 152

Proxy Method 102 0.1 79

Manual Method 76 0.3 54

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Figure 3-10 Catchments delineated by the Proxy method for Combined Sewershed

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Figure 3-11 Manually delineated catchments for Combined Sewershed

The observed and simulated hydrographs at the outlet of the sewershed for thethree rainfall events are illustrated in Figures 3-12, 3-13, and 3-14. The general patternsof the results from the four methods agree fairly consistently with the pattern of theobserved flow data. Compared to the observed flow volume, there was no systematicunder- or over-predictions based on the four methods. The times to peak based on thefour catchment delineation methods were very close to the observed times to peak forthe three rainfall event simulations. There were considerable discrepancies, however,between the observed and the simulated total amount of flow and the peak flow rate.Table 3-4 compares the differences in the total amount of flow, the maximum andminimum flows, and the time to peak between the simulated results and observed data.Investigation of the model development process revealed that simulated runoff resultswere strongly influenced by several model inputs. These inputs were the entiremodeled areas, the pervious and impervious land areas, the widths of the catchments,and the soil infiltration parameters. They were calculated based on the land uses andsoils data in a delineated catchment. Defining the land uses and soils data in a

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delineated catchment was accomplished by deriving the information from CAGIS soiland land use shape files on the delineated catchment level. In another words, if thedelineated catchments were different, these parameters were generated differently,which altered the modeling results. Based on the previous discussions, the resultsindicate that the delineated catchments varied significantly between the four catchmentdelineation methods. Therefore, this study shows that the four delineation methods hada strong impact on the modeling results for the Combined Sewershed. It also indicatesthat the initial products of the delineated catchments should be modified by themodeling team’s judgment to be applicable for model inputs. The level of themodification depends on the level of the study detail and accuracy. In addition, modelcalibration is needed after model development.

Figure 3-12 Observed and simulated hydrographs at the outlet of CombinedSewershed using the 3/15/02 rainfall event

Gray: observed flow data

Black: Results from Manual Method

Red: Results from Proxy Method

Purple: Results from Watershed Method

Green: the result from the Basin method

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Gray: The observed flow data

Black: Results from Manual Method

Red: Results from Proxy Method

Purple: Results from Watershed Method

Green: the result from the Basin method

Figure 3-13 Observed and simulated hydrographs at the outlet of CombinedSewershed using the 4/21/02 rainfall event

Gray: The observed flow data

Black: Results from Manual Method

Red: Results from Proxy Method

Purple: Results from Watershed

Method

Green: the result from the Basin

method

Figure 3-14 Observed and simulated hydrographs at the outlet of CombinedSewershed using the 5/12/02 rainfall event

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Table 3-4 Comparison between the simulated and observed flow data forCombined Sewershed

3/25/2002 Rainfall Event

ManualMethod

BasinMethod

ProxyMethod

WatershedMethod

ObservedData

Total Volume (ft3) 6.89x105 1.12x106 1.15x106 1.32x106 1.11x106

Maximum Flow (cfs) 29.9 35.9 45.0 51.8 27.8

Minimum Flow (cfs) 1.8 0.6 0.6 0.6 1.7

Difference between the TotalObserved and Simulated Volume

-37.9% 0.9% 3.6% 18.9% 0.0%

Difference between the MaximumObserved and Simulated Flow

7.7% 29.1% 62.2% 86.5% 0.0%

First Peak Flow Time 23:05 23:05 23:05 23:05 23:05

4/21/2002 Rainfall Event

ManualMethod

BasinMethod

ProxyMethod

WatershedMethod

ObservedData

Total Volume (ft3) 1.57x106 8.06x105 7.56x105 7.87x105 2.01x106

Maximum Flow (cfs) 138.4 108.4 82.5 106.0 141.6

Minimum Flow (cfs) 0.0 0.5 0.6 0.5 0.0

Difference between the TotalObserved and Simulated Volume

-21.9% -59.9% -62.4% -60.8% 0.0%

Difference between the MaximumObserved and Simulated Flow

-2.2% -23.4% -41.7% -25.1% 0.0%

First Peak Flow Time 13:50 13:55 13:50 13:50 13:50

5/12/2002 Rainfall Event

ManualMethod

BasinMethod

ProxyMethod

WatershedMethod

ObservedData

Total Volume (ft3) 2.67x106 2.75x106 2.91x106 3.26x106 2.51x106

Maximum Flow (cfs) 84.3 82.3 84.1 61.1 99.6

Minimum Flow (cfs) 0.0 0.5 0.6 0.5 1.2

Difference between the TotalObserved and Simulated Volume

6.4% 9.6% 15.9% 29.9% 0.0%

Difference between the MaximumObserved and Simulated Flow

-15.4% -17.4% -15.5% -38.7% 0.0%

First Peak Flow Time 22:35 22:35 22:35 22:35 22:30

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Conclusions

A catchment is the smallest unit of delineated area in a sewershed for this study.Accuracy of catchment delineations played an important role in the hydrologic andhydraulic model development and calibration. Catchment characteristics and modelingapproaches are different for combined and separate sanitary systems. Two types ofsewersheds (i.e., combined and separate sanitary) were selected to evaluate threedifferent GIS based automatic catchment delineation methods. Manual catchmentdelineation was also performed to verify the success of automatic methods. In general,of the three automated methods investigated in this study, the Proxy Method was themore effective approach to delineate catchments for separate sanitary sewersheds whilethe Basin Method yielded better results for the combined sewersheds.

The automated methods using GRID module of ArcInfo are effective indelineating initial catchment boundaries for a large modeling study area consisting ofthousands of catchments, as in the case of the MSD System Wide Model Project.Automatically generated catchment boundaries often required manual refinementduring the model development and calibration; however, they reduced the overallefforts required for catchment delineation.

A successful GIS based automatic catchment delineation depends on thefollowing factors: the extent and accessibility of the data sources, the type and uniquefeatures of the modeled sewer systems, and the accuracy and competence of the GISdata base. Manual refinement of the initial delineated catchments is anticipated in orderto render a final product for successful model development. The level of manualrefinement of the initial catchment delineations depends on the project-specific level ofdetail and modeling objectives. The automatic catchment delineation methodsdiscussed in this paper can provide a means to significantly expedite the process ofdeveloping initial catchment delineations for large-scale study areas.

References

Bhaskar, N. R., W. P. James, and R. S. Devulapalli, 1991. Hydrologic parameterestimation using Geographic Information System. Journal of Water Resources Planning andManagement, Vol. 118(5) : 492-511.

Colosimo, C. and G. Mendicino, 1996. GIS for Distributed Rainfall-Runoff Modeling. InGeographic Information Systems in Hydrology, Edited by V. P. Singh and M. Fiorentino,Kluwer Academic Publishers, the Netherlands.

Maidment D. V., 2003. http://www.ce.utexas.edu/prof/maidment/home.html.

Singh, V. P., 1995. Watershed modeling. In Computer Models of Watershed Hydrology,edited by V. P. Singh. Water Resources Publications, P. O. Box 260026, Highlands Ranch,CO.

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Olivera, F., 1996.http://www.crwr.utexas.edu/gis/gishyd98/atlas/EXERCISE/URUBAMBA/Peru.htm.

Wilson, B. N., B. J. Barfield, A. D. Ward, I. D. Moore, 1984. A hydrology andsedimentology watershed model. Part I: Operational format and hydrologic component.Transactions of the ASAE, Vol.27 (5) : 1370-1377.