Overview: Assessing the Impact of Maneuver Training on
Nonpoint Source Pollution and Water Quality (Project #CP-1339)
1
Steichen ,
James M.
Phillip L.
1
and Naiqian Zhang
1
Barnes ,
Stacy L.
1Department
1
Hutchinson ,
J.M. Shawn
2
Hutchinson ,
Philip B.
3
Woodford ,
2Department
of Biological & Agricultural Engineering, and
of Geography, Kansas State University, Manhattan, Kansas 66506;
3Integrated Training Area Management (ITAM), Fort Riley, Kansas 66442
Monitoring Sediment Concentration at Low-Water Stream
Crossings using an Optical Sediment Sensor
A GIS-Enabled Kinematic Wave Approach for Calculating the
Transition between Sheet and Concentrated Flows
Naiqian Zhang1, Yali Zhang1, Wei Han1, Quentin Stoll1, Darrell Oard1, James Steichen1, Philip Woodford2, Philip
Barnes1, and Stacy Hutchinson1
Stacy L. Hutchinson1, J.M. Shawn Hutchinson2, and Ik-Jae Kim1
1Department
1Department
of Biological & Agricultural Engineering, Kansas State University; 2ITAM Program, Range Division, Fort Riley
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.
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 sedimentconcentration 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.
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.
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.
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.
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
Installation
The Effects of Different Resolution DEMs in Determining
Overland Flow Regimes
Gilbert Malinga1, James Steichen1, Stacy Hutchinson1 ,Phillip Woodford2 , Tim Keane3, and Amanda Pollock4
Stacy L. Hutchinson1, J.M. Shawn Hutchinson2, Ik-Jae Kim1, and Philip Woodford3
1Department
2ITAM
3Department
of Biological & Agricultural Engineering, Kansas State University;
Program, Range Division, Fort Riley;
of Landscape
Architecture/Regional and Community Planning, Kansas State University; 4Department of Landscape Architecture, Kansas State University
1Department
of Biological & Agricultural Engineering, Kansas State University; 2Department of Geography, Kansas State University; 3ITAM Program, Range
Division, Fort Riley
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 highflow 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.
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.
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.
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.
Spatial and Temporal Analysis of Soil Moisture using MODIS
NDVI and LST Products
Effects of Microtopography and Vegetation Growth on
Nonpoint Source Pollution Control in Tallgrass Buffers
J.M. Shawn Hutchinson1, Thomas J. Vought1, and Stacy L. Hutchinson2
Stacy L. Hutchinson1, Ik-Jae Kim1, Philip Woodford2, Monte Cales3, Philip L. Barnes1, and Amy K. Good1
1Department
1Department
of Geography and 2Department of Biological & Agricultural Engineering, Kansas State University
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.
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.
of Biological and Agricultural Engineering, Kansas State University; 2Integrated Training Area Management, Fort Riley; 3USDA-NRCS
DEM60
DEM100
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.