Overview: Assessing the Impact of Maneuver Training on Overview: Assessing the Impact of Maneuver Training on Nonpoint Source Pollution and Water Quality (Project #CP-1339)Nonpoint Source Pollution and Water Quality (Project #CP-1339)James M. Steichen1, Phillip L. Barnes1, Stacy L. Hutchinson1, J.M. Shawn Hutchinson2, Philip B. Woodford3,and Naiqian Zhang1

1Department of Biological & Agricultural Engineering, and 2Department of Geography, Kansas State University, Manhattan, Kansas 66506; 3Integrated Training Area Management (ITAM), Fort Riley, Kansas 66442

Monitoring Sediment Concentration at Low-Water Stream Monitoring Sediment Concentration at Low-Water Stream Crossings using an Optical Sediment SensorCrossings using an Optical Sediment SensorNaiqian Zhang1, Yali Zhang1, Wei Han1, Quentin Stoll1, Darrell Oard1, James Steichen1, Philip Woodford2, Philip Barnes1, and Stacy Hutchinson1

1Department of Biological & Agricultural Engineering, Kansas State University; 2ITAM Program, Range Division, Fort Riley

Sediment concentration is defined as the weight of suspended soil particles per unit volume of water. Turbidity is usually referred to as the optical properties of suspended/dissolved materials in water on transmitting, reflecting, absorbing, and scattering light. Thus, traditional turbidity sensors are not sediment-concentration sensors. A sediment sensor developed in this study uses LEDs that emit lights at three visible and infrared “feature wavelengths”, which were selected through a spectroscopic analysis, and light detectors arranged at different angles from the light sources. Statistical models established based on test data allowed the sensor to be basically insensitive to non-soil, suspended and dissolved objects, such as algae, organic matter, and various microorganisms, and less sensitive to soil texture.

A prototype sensor was tested at combinations of four water types and five soil textures in the laboratory. Statistical and neural-network models successfully predicted sediment concentration across samples of all the combinations with R2 values of no lower than 0.95. An outdoor experiment proved that the influence of ambient light on sediment measurement can be largely eliminated by modulating the lights.

More than ten prototype sensors of different designs have been fabricated and calibrated. Several sensors were placed at low-water crossings at Ft. Riley and Ft. Benning for long-term, sediment-runoff monitoring. The sensor case has been modified to improve its waterproof capability. Difficulties encountered during the long-term tests included signal drifting and occultation of the optical lenses by algae and soil particles. Modifications in sensor and hardware/software have been made to solve these problems.

Work towards remote, real-time monitoring and data storage through the Internet is in progress. The system involves a wireless sensor network that covers multiple “motes”, which directly acquire data from the sediment sensors, interface to a commercial wireless telephone system, and a server on the Internet.

Stream Crossings: Effects on Streams at Fort Riley Military Stream Crossings: Effects on Streams at Fort Riley Military InstallationInstallationGilbert Malinga1, James Steichen1, Stacy Hutchinson1 ,Phillip Woodford2 , Tim Keane3, and Amanda Pollock4 1Department of Biological & Agricultural Engineering, Kansas State University; 2ITAM Program, Range Division, Fort Riley; 3Department of Landscape Architecture/Regional and Community Planning, Kansas State University; 4Department of Landscape Architecture, Kansas State University

Military maneuvers involve effectively moving soldiers and equipment across Fort Riley military installation training areas, and this sometimes involves crossing streams. Prior to 1992, the military randomly selected where they would cross a stream or constructed earthen fords to cross. During or after high-flow events, both the randomly selected sites and earthen fords posed a safety issue for soldiers and equipment. Furthermore, use of the randomly selected sites and earthen fords caused tremendous degradation to the streams through tearing of stream banks and generation of excessive amounts of sediment, exceeding Total Maximum Daily Load (TMDL) limits for water quality downstream.

In 1992, a Low Water Stream Crossing (LWSC) project was initiated at Fort Riley to address problems related to use of earthen fords and randomly selected crossing sites. New designs were developed. Selected stream crossing sites were modified by hardening stream beds and approach roads with rock and gravel. By 2002, the LWSC project was generally considered a success. Project achievements realized were: Provided safer training conditions for military, improved access to additional training areas, and alleviated some of the environmental impacts related to crossing streams.

Design and construction of LWSC is working well, but the major concern is site selection for stream crossings. Riffles are best locations for LWSCs, while pools, meander bends, and tributary entry locations should be avoided. Sediment transported from approach roads is another major concern. Gravelling of roads, at least up to 200 ft on either side of LWSC will reduce amount of sediment detached from the roads. Creation of water bars (built across roads) to divert storm runoff to riparian management zones will reduce amount of sediment from upland areas delivered through approach roads into the streams.

A GIS-Enabled Kinematic Wave Approach for Calculating the A GIS-Enabled Kinematic Wave Approach for Calculating the Transition between Sheet and Concentrated FlowsTransition between Sheet and Concentrated FlowsStacy L. Hutchinson1, J.M. Shawn Hutchinson2, and Ik-Jae Kim1

1Department of Biological & Agricultural Engineering and 2Department of Geography, Kansas State University

Non-point source (NPS) pollution has been called the nation’s largest water quality problem, and its reduction is a major challenge facing our society today. As of 1998 over 290,000 miles of river, almost 7,900,000 acres of lake and 12,500 square miles of estuaries failed to meet water quality standards. Military training maneuvers have the potential to significantly alter land surfaces in a manner that promotes NPS pollution, resulting in the inability of military installations to meet water quality standards and the decline of training lands.

Currently, most efforts to reduce NPS pollution focus on the use of watershed water quality models. Identification of overland flow networks is a vital preprocessing step for these NPS models. Flow networks are used to determine transport routes for pollution and optimal placement of best management practices. One practice that is widely adopted for reducing NPS pollution is the vegetated buffer system (VBS). The primary hydrologic consideration for VBS design and function is uniform sheet flow. With time, however, overland flow concentrates and channelizes, reducing contact time with vegetation and NPS pollution reduction efficiency.

The kinematic wave approximation is a useful technique for calculating overland flow time of concentration within a drainage area. Digital elevation models (DEMs) are widely used for determining various landscape variables, as well as for delineating overland flowpath networks and drainage area boundaries. Using topographic variables estimated from DEMs and applying the kinematic wave theory in a GIS environment, it is possible to estimate the length and travel time of overland flow providing an improved understanding of VBS placement for maximum water quality benefit, as well as a reduction in gully erosion caused by concentrated flow.

The Effects of Different Resolution DEMs in Determining The Effects of Different Resolution DEMs in Determining Overland Flow RegimesOverland Flow RegimesStacy L. Hutchinson1, J.M. Shawn Hutchinson2, Ik-Jae Kim1, and Philip Woodford3

1Department of Biological & Agricultural Engineering, Kansas State University; 2Department of Geography, Kansas State University; 3ITAM Program, Range Division, Fort Riley

A gully head is a unique landscape feature where concentrated overland flow begins to cause significant erosion. The impacts of four different resolution digital elevation models (DEMs), three (3, 10, and 30 m) developed using a differential global positioning system (GPS) survey and the USGS 30 m DEM, were used to identify transitional flow areas on a grassland hillslope. A simple erosion model, nLS, based on Manning’s kinematic wave theory, was used to determine where overland flow transitioned from sheet flow to concentrated flow. The accumulated erosive energy was estimated using the nLS model, where, n is Manning’s coefficient, L is the overland flow length, and S is the slope. In addition to the DEMs, spatial analyses for soil (SSURGO) and land cover (Kansas GAP) were conducted in a geographic information system (GIS). First order streams were delineated using each resolution DEM (contributing area: 900 m2) and overlaid with the concentrated flow data obtained from the nLS model results. The intersected area was buffered by 3, 6, 10, or 15 m, depending on the DEM resolution.

Results showed that average topographic and hydrologic variables varied between the different DEM resolutions. The 3 m DEM produced the best model accuracy, predicting two gully head locations. The recommended buffer radius was found to be 6 m, which is 2 times of the grid size. The efforts to develop finer data resolution should be supported in assessing reliable erosion potential for watershed management.

Effects of Microtopography and Vegetation Growth on Effects of Microtopography and Vegetation Growth on Nonpoint Source Pollution Control in Tallgrass BuffersNonpoint Source Pollution Control in Tallgrass BuffersStacy L. Hutchinson1, Ik-Jae Kim1, Philip Woodford2, Monte Cales3, Philip L. Barnes1, and Amy K. Good1

1Department of Biological and Agricultural Engineering, Kansas State University; 2Integrated Training Area Management, Fort Riley; 3USDA-NRCS

Vegetated buffer systems (VBS) are considered one of the most sustainable BMPs for mitigating NPS pollution. In this study, the efficiency of tallgrass VBS was evaluated on 3-meter by 20-meter tallgrass buffers during the summer and early fall. Using data collected with double-ring infiltrometers, infiltration rates were estimated by the Green-Ampt approximation (GA). Three vegetation parameters, canopy height, dry biomass, and photosynthetically active radiation (PAR) over leaf area, were monitored during the period of study to assess the impact of vegetation development on runoff generation and transport. A 60-cm and 100-cm resolution digital elevation model (DEMs) were developed using a total station survey to investigate the impact of slope variation and flow length on time of concentration for overland flow using Manning’s kinematic equation and the Darcy-Weisbach equation.

The VBS trapping efficiency was 99 % of TSS, 97 % of T-N, 88% of T-P, and 87 % of PO4--P on average. While infiltration was overestimated in August, the difference between estimated infiltration from GA and calculated infiltration using a water balance significantly decreased in October as vegetation senesced. Switch grass (Panicum virgatum) growth averaged 7.0 mm/day between August and early September and declined to 0.9 mm/day between September and early October. Vegetation clipping did not influence the runoff ratio or water quality, indicating that upper vegetation canopy does not retain significant water. The higher resolution DEM (DEM60) showed more detailed slope variation and flow direction, particularly for smoother buffer topography. Manning’s kinematic estimation yielded more accurate times of concentration than the Darcy-Weibach estimation.

Spatial and Temporal Analysis of Soil Moisture using MODIS Spatial and Temporal Analysis of Soil Moisture using MODIS NDVI and LST ProductsNDVI and LST ProductsJ.M. Shawn Hutchinson1, Thomas J. Vought1, and Stacy L. Hutchinson2

1Department of Geography and 2Department of Biological & Agricultural Engineering, Kansas State University

Soil moisture is an important input for hydrologic and climate models but often exhibits significant spatial and temporal variation. The water content of soils affects a variety of physical and biological processes in the biosphere and links the Earth's surface and atmosphere through its influence on surface energy and moisture fluxes. In addition, antecedent soil moisture conditions affect the hydrologic behavior of land surfaces by controlling, in part, the infiltratration capacity of soils and the partioning of precipitation into runoff and storage terms. This study uses normalized difference vegetation index (NDVI) and land surface temperature (LST) data, acquired by the Moderate Resolution Imaging Spectrometer (MODIS), in a linear regression model to predict volumetric water content (VWC) of near surface soils for Fort Riley. the northeastern Kansas to estimate regional soil moisture levels. These estimates will be used to evaluate antecedent soil moisture conditions and used as input into a landscape-scale surface water quality model to evaluate the effectiveness of riparian buffers in filtering sediments transported from upland sites within mechanized military training areas.

A strong negative relationship exists between surface temperature and greenness for different biomes, which can be used as a landscape-level proxy for surface wetness. Near real time MODIS satellite data products were obtained from the EOS Data Gateway. Land surface temperature and NDVI data is in the form of 8-day and 16-day maximum value composites, respectively, at a spatial resolution of 1 kilometer. Soil moisture was measured weekly at 80 control points using a portable time-domain reflectometer (TDR).

Using a geographic information system (GIS), LST, NDVI, and TDR points were overlaid to create a table of values that could be input into a linear regression model to that could be “inverted” to predict soil moisture content based upon NDVI and LST image data alone. Early results are promising as the amount of variation in measured soil moisture explained by MODIS LST and NDVI image bands was strong, especially considering image grain. Daily estimates of soil moisture with an approximate standard of 9% have been produced. DEM60 DEM100