SUSCEPTIBILITY OF INDIANA WATERSHEDS TO HERBICIDE CONTAMINATION1

ABSTRACT: An index of watershed susceptibility to surface water contamination by herbicides could be used to improve source water assessments for public drinking water supplies, prioritize watershed restoration projects, and direct funding and educational efforts to areas where the greatest environmental benefit can be realized. The goal of this study is to use streamflow and herbicide concentration data to develop and evaluate a method for estimating comparative watershed susceptibility to herbicide loss. United States Geological Survey (USGS) concentration data for five relatively water soluble herbicides (alachlor, atrazine, cyanazine, metolachlor, and simazine) were analyzed for 16 Indiana watersheds. Correlation was assessed between observed herbicide losses and: (1) a herbicide runoff index using GIS‐based land use, soil type, SCS runoff curve number, tillage practice, herbicide use estimates, and combinations of these factors; and (2) predicted herbicide losses from a non‐point source pollution model (NAPRA‐Web, an Internet‐based interface for GLEAMS). The highest adjusted R²value was found between herbicide concentration and the runoff curve number alone, ranging from 0.25 to 0.56. Predictions from the simulation model showed a poorer correlation with observed herbicide loss. This indicates potential for using the runoff curve number as a simple herbicide contamination susceptibility index.     

Land-cover change in upper Barataria Basin estuary,Louisiana, 1972-1992: increases in Wetland area

The Barataria Basin, Louisiana, USA, is an extensive wetland and coastal estuary system of great economic and intrinsic value. Although high rates of wetland loss along the coastal margin of the Barataria Basin have been well documented, little information exists on whether freshwater wetlands in the upper basin have changed. Our objectives were to quantify land-cover change in the upper basin over 20 years from 1972–1992 and to determine land-cover transition rates among land-cover types. Using 80-m resolution Landsat MSS data from the North American Landscape Characterization (NALC) data archive, we classified images from three time steps (1972, 1985, 1992) into six land-cover types: agriculture, urban, bottomland hardwood forest, swamp forest, freshwater marsh, and open water. Significant changes in land cover occurred within the upper Barataria Basin over the study period. Urban land increased from 8% to 17% of the total upper basin area, primarily due to conversions from agricultural land, and to a lesser degree, bottomland forest. Swamp forest increased from 30% to 41%, associated with conversions from bottomland hardwood forest and freshwater marsh. Overall, bottomland forest decreased 38% and total wetland area increased 21%. Within the upper Barataria, increases in total wetland area may be due to land subsidence. Based on our results, if present trends in the reduction of bottomland forest land cover were to continue, the upper Barataria Basin may have no bottomland hardwood forests left by the year 2025, as it is subjected to multiple stressors both in the higher elevations (from urbanization) and lower elevations (most likely from land subsidence). These results suggest that changes in the upper freshwater portions of coastal estuaries can be large and quite different from patterns observed in the more saline coastal margins.     

NEAR REAL-TIME MAPPING OF THE 1975 MISSISSIPPI RIVER FLOOD IN LOUISIANA USING LANDSAT IMAGERY1

ABSTRACT: The project described in this report was undertaken by the Louisiana State Planning Office to establish the extent of backwater flooding in Louisiana in April 1975. Band 7 Landsat imagery, enlarged to a scale of 1:250,000 was used to visually identify flooded areas. Inundated areas were delineated on overlays keyed to 1:250,000 U.S. Geological Survey topographic quadrangles. Tabular data identifying acres flooded, according to land use type, were derived by merging the flood map overlays with computerized 1972 land use data. Approximately 1.12 million acres of the state were inundated by flood waters. The total acreage and land use types affected by flooding were determined within 72 hours from the time the flood areas were imaged. Flooded maps were prepared for 26 parishes. Field observations were made by Louisiana Cooperative Extension Service county agents in order to determine the accuracy of parish flood maps and flood acreage figures by land use type. Results indicated that this was a fast, accurate, and relatively inexpensive method of compiling flood data for disaster planning and postflood analysis.     

URBAN STORMWATER QUANTITY/QUALITY MODELING USING THE SCS METHOD AND EMPIRICAL EQUATIONS1

ABSTRACT: Runoff depth and pollutant loading (Biological Oxygen Demand [BOD₅], Total Suspended Solids [TSS], Total Kjeldahl Nitrogen [TKN] and lead [Pb]) computations of urban stormwater runoff from four small sites (i.e., 14.7–58.3 ac) in South Florida were performed using the Soil Conservation Service (SCS) hydrology method and empirical equations developed by the U.S. Environmental Protection Agency (EPA). Each site had different predominant land uses (i.e., low density residential, high density residential, highway and commercial). Quantity and quality data from 95 storm events at these sites were measured by the U.S. Geological Survey (USGS), and used for calibration of the methodology to derive appropriate input parameters. Calibrated input parameters were developed for each land use to test the applicability of the methodology in small sub-tropical urban watersheds, and to provide hydrologists with a way to select appropriate parameter values for planning studies. A total of 16 independent rainfall events were used for verification of the methodology. Comparisons of predicted versus measured data for both hydrographs and pollutant loadings were performed.     

Sensitivity of SCS Models to Curve Number Variation1

ABSTRACT: The Soil Conservation Service (SCS) models, including the TR-20 computer program and the simplified methods in TR-55, are widely used in hydrologic design. The runoff curve number (CN), which is an important input parameter to SCS models, is defined in terms of land use tretments, hydrologic, condition, antecedent soil moisture, and soil type. The objective of this study was to evaluate the sensitivity of the SCS models to errors in CN estimates. The results show that the effects of CN variation decrease as the design rainfall depth increases, such as for the larger storm events. The value and use of the sensitivity curves are demonstrated using a comparison of Landsat and conventionally derived curve numbers for three watersheds in Pennsylvania.     

Modeling the relationship between development and storm water and nutrient runoff

The EPA Storm Water Management Model was used to model the effects of urban and agricultural development on storm water runoff from uplands bordering a Louisiana swamp forest. Using this model, we examined the effects of changing land use patterns. By 1995 it is projected that urban land on the uplands bordering the swamp will increase by 321 percent, primarily at the expense of land currently in agriculture. Simulation results indicate that urbanization will cause storm water runoff rates to be up to 4.2 times greater in 1995 than in 1975. Nutrient runoff will increase 28 percent for nitrogen (N) and 16 percent for phosphorus (P) during the same period. The environmental effects of these changes in the receiving swamp forest are examined.     

UNCERTAINTY ANALYSIS OF RUNOFF ESTIMATES FROM A RUNOFF CONTOUR MAP1

ABSTRACT: The U.S. Environmental Protection Agency (EPA) in cooperation with the U.S. Geological Survey (USGS) conducted an analysis to quantify the uncertainty associated with interpolating runoff to specific sites using a runoff contour map. We interpolated runoff to 93 gaged watersheds from a runoff contour map using (1) hand interpolation to the watershed outlet, (2) a computer interpolation to the watershed outlet, and (3) hand interpolation to the watershed centroid. We compared the interpolated values to the actual gaged values and found that there was a bias in the average interpolated value for runoff estimated at basin outlets, with interpolated values being less than the actual. We found no significant difference between the hand interpolation method and the computer interpolation method except that the computer method tended to have higher variability due to factors inherent to the software used. There were no strong spatial correlations or regional patterns in the runoff interpolations, which indicates that there are no regional biases introduced in the development of the contour map. We determined that we could estimate runoff, on the average, within approximately 8.9 cm (3.5 in; 15 percent) of the measured value using the three methods. The results of this work indicate that runoff contour maps can he used in regional studies to estimate runoff to ungaged systems with quantifiable uncertainty.     

COMPUTATION OF RUNOFF REDUCTION CAUSED BY FARM PONDS1

ABSTRACT: A two-parameter farm pond storage index, FPSI, was Used to adjust computed surface. runoff using the partial area runoff contribution resulting from runoff captured by farm ponds. The validity of the index method was tested by fitting a continuous accounting version of the Soil Conservation Service curve number procedure to surface runoff data from each of three watersheds, first with and then without the FPSI routine. Evapotranspiration computed with the Jensen-Haise method and rainfall were input to the model. A linear relationship was assumed between the storage index and the portion of the controlled drainage area that was contributing to runoff. Adjusting the computed runoff with the FPSI reduced the coefficient of variation of monthly measured versus computed surface runoff for each of the three watersheds. The correlation coefficients for the same comparisons were increased. The annual predicted surface runoff Was improved for 12 of the 17 station years of data tested. The farm pond storage index could be used with any surface runoff model to improve the prediction of runoff from watersheds with drainage areas greater than 1 square mile and with about 20 percent or more of the drainage area controlled by farm ponds.     

Decreased Runoff Response to Precipitation,Little Missouri River Basin,Northern Great Plains,USA

High variability in precipitation and streamflow in the semiarid northern Great Plains causes large uncertainty in water availability. This uncertainty is compounded by potential effects of future climate change. We examined historical variability in annual and growing season precipitation, temperature, and streamflow within the Little Missouri River Basin and identified differences in the runoff response to precipitation for the period 1976‐2012 compared to 1939‐1975 (n = 37 years in both cases). Computed mean values for the second half of the record showed little change (<5%) in annual or growing season precipitation, but average annual runoff at the basin outlet decreased by 22%, with 66% of the reduction in flow occurring during the growing season. Our results show a statistically significant (p < 0.10) 27% decrease in the annual runoff response to precipitation (runoff ratio). Surface‐water withdrawals for various uses appear to account for <12% of the reduction in average annual flow volume, and we found no published or reported evidence of substantial flow reduction caused by groundwater pumping in this basin. Results of our analysis suggest that increases in monthly average maximum and minimum temperatures, including >1°C increases in January through March, are the dominant driver of the observed decrease in runoff response to precipitation in the Little Missouri River Basin.     

RELATIONSHIP BETWEEN ANNUAL RUNOFF AND WATERSHED AREA FOR THE EASTERN UNITED STATES1

ABSTRACT: As part of the U.S. Environmental Protection Agency's effort to determine the long-term effects of acidic deposition on surface water chemistry, annual runoff was estimated for about 1000 ungaged sites in the eastern U.S. using runoff contour maps. One concern in using contour maps was that a bias may be introduced in the runoff estimates due to the size of the 1000 ungaged sites relative to the size of the watersheds used in developing the maps. To determine if a bias was present the relationship between the annual runoff (expressed as depth) and the watershed area for the Northeast (NE) and Southern Blue Ridge Province (SBRP) was tested using five regional data bases. One short-term data base (1984 Water Year, n = 531) and two long-term data bases (1940–57, n = 134 and 1951–80, n = 342) were used in the NE. In the SBRP one short-term database (1984 Water Year, n = 531) and one long-term data base (1951–80, n = 60) were used. For the NE and the SBRP, runoff was not directly correlated with watershed area using the five regional databases. Also, runoff normalized by precipitation was not related to watershed area.     

Assessing Water Quality at Large Geographic Scales: Relations Among Land Use,Water Physicochemistry,Riparian Condition,and Fish Community Structure

Data collected from 172 sites in 20 major river basins between 1993 and 1995 as part of the US Geological Survey's National Water-Quality Assessment Program were analyzed to assess relations among basinwide land use (agriculture, forest, urban, range), water physicochemistry, riparian condition, and fish community structure. A multimetric approach was used to develop regionally referenced indices of fish community and riparian condition. Across large geographic areas, decreased riparian condition was associated with water-quality constituents indicative of nonpoint source inputs—total nitrogen and suspended sediment and basinwide urban land use. Decreased fish community condition was associated with increases in total dissolved solids and rangeland use and decreases in riparian condition and agricultural land use. Fish community condition was relatively high even in areas where agricultural land use was relatively high (>50% of the basin). Although agricultural land use can have deleterious effects on fish communities, the results of this study suggest that other factors also may be important, including practices that regulate the delivery of nutrients, suspended sediments, and total dissolved solids into streams. Across large geographic scales, measures of water physicochemistry may be better indicators of fish community condition than basinwide land use. Whereas numerous studies have indicated that riparian restorations are successful in specific cases, this analysis suggests the universal importance of riparian zones to the maintenance and restoration of diverse fish communities in streams.     

A COMPUTERIZED DATA BASE FOR FLOOD PREDICTION MODELING1

ABSTRACT: A computerized geographic information system (GIS) was created in support of data requirements by a hydrologic model designed to predict the runoff hydrograph from ungaged basins. Some geomorphologic characteristics (i.e., channel lengths) were manually measured from topographic maps, while other parameters such as drainage area and number of channels of a specified order, land use, and soil type were digitized and manipulated through use of the GIS. The model required the generation of an integrated Soil Conservation Service (SCS) curve number for the entire basin. To this end, soil associations and land use (generated from analysis of Landsat satellite data) were merged in the GIS to acquire a map representing SCS runoff curve numbers. The volume of runoff obtained from the Watershed Hydrology Simulation (WAHS) Model using this map was compared to the volume computed by hydrograph separation and found to be accurate within 19 percent error. To quantify the effect of changing land use on basin hydrology, the GIS was used to vary percentages from the drainage area from forest to bare soil. By changing the basin runoff curve numbers, significant changes in peak discharge were noted; however, the time to peak discharge remained essentially independent of change in area of land use. The GIS capability eliminated many of the more traditional manual phases of data input arid manipulation, thereby allowing researchers to concentrate on the development and calibration of the model and the interpretation of presumably more accurate results.     

AGRICULTURE LAND‐USE EFFECTS ON NUTRIENT LOSSES IN WEST TIAOXI WATERSHED,CHINA1

ABSTRACT: Five types of land use/land covers in the West Tiaoxi watershed of China were studied for nutrient losses in artificial rainstorm runoff. A self‐designed rainfall simulator was used. In situ rainfall simulations were used to: (1) compare the concentrations of nitrogen and phosphorous in different land use/land covers and (2) evaluate the flux of nitrogen and phosphorous export from runoff and sediment in various types of land use/land covers. Three duplicated experiments were carried out under rain intensity of 2 mm/min, each lasting 32 minutes on a 3 m² plot. Characteristics of various species of nitrogen and phosphorous in runoff and sediment were investigated. The results showed that the concentrations of total nitrogen (TN) and total phosphorous (TP) were greatest in runoff from mulberry trees and smallest from pine forest. The TN and TP export was mainly from suspended particulate in runoff. TN and TP exports from the top 10 cm layer of five types of land use/land covers were estimated as high as 4.66 to 9.40 g/m² and 2.57 to 4.89 g/m², respectively, of which exports through sediment of runoff accounted for more than 90 percent and 97 percent. The rate of TN and TP exports ranged from 2.68 to approximately 14.48 and 0.45 to approximately 4.11 mg/m²/min in runoff; these rates were much lower than those of 100.01 to approximately 172.67 and 72.82 to approximately 135.96 mg/m²/min in the runoff sediment.     

ESTIMATING TMDL BACKGROUND SUSPENDED SEDIMENT LOADING TO GREAT LAKES TRIBUTARIES FROM EXISTING DATA1

ABSTRACT: The total maximum daily load (TMDL) for suspended sediment is the maximum quantity of suspended sediment that can enter a waterway without affecting the beneficial uses of the waterway. It is calculated as the sum of permissible allotments of point sources of suspended sediment, permissible allotments of nonpoint sources of suspended sediment, background (natural) loading of suspended sediment, and a margin of safety. The goal of this project was to develop methods for estimating background levels of sediment loads in tributaries of the Great Lakes. Such quantification is key to determining permissible TMDL in waters that do not meet water quality standards under the Clean Water Act of 1972. Suspended sediment loading for 46 rivers was estimated from data collected at U.S. Geological Survey (USGS) gages. Land use and physiographic attributes were estimated for these gaged basins with a geographic information system (GIS). Basin attributes and sediment yield data are the basis for examining two approaches to estimating background suspended sediment loads. One method, based upon envelope curves of sediment yield and drainage area, will be shown to have considerable merit. A second method, based upon correlation of sediment yield to various basin attributes such as drainage area and land use, will be shown to be fraught with difficulties.     

SCS URBAN CURVE NUMBERS FROM A LANDSAT DATA BASE1

Estimating the Curve Numbers used in the Soil Conservation Service hydrologic models is a tedious and costly task. Recent advances in remote sensing and data processing have led to the development of readily available land cover data bases for many areas of the United States. This study evaluated the potential of using a Landsat data base to make the Curve Number estimation process more cost-effective and less tedious. Ten watersheds in the Washington, D.C., area were evaluated using a Landsat land cover data base developed by the U.S. Geological Survey. Results showed that these data can be useful. Predictions can be improved if ancillary data on residential lot size are included. It was concluded that this type of data base must be examined carefully before implementation.     

ANALYSIS AND PREDICTION OF SURFACE RUNOFF IN AN URBANIZING WATERSHED USING SATELLITE IMAGERY1

ABSTRACT: This paper demonstrates how satellite image data [e.g., from Landsat 5 Thematic Mapper (TM)], in conjunction with an urban growth model and simple runoff calculations, can be used to estimate future surface runoff and, by implication, water quality within a watershed. To illustrate the method, predictions of land use change and surface runoff are shown for Spring Creek Watershed, a medium sized urbanizing watershed in Central Pennsylvania. Land cover classifications for this watershed were created from images for summertime 1986 and 1996 and subsequently used as input to the Clarke urban growth model, called SLEUTH, to predict land use changes to the year 2025. Simulations with this model show a progressive growth in the percentage of urban pixels and in impervious surface area in the watershed but also an increase in woodland, primarily in previously clear‐cut areas. Given that woodland area will continue to increase in area, surface runoff into Spring Creek is predicted to remain only slightly above present level. However, should the woodland amount fail to increase, surface runoff is then predicted to increase more significantly during the next 25 years. Finally, the concept of urban sprawl is addressed within the context of predicted increases in urbanization by relating the implied increase in impervious surface area to population density within the watershed.     

Effect of the Spatial Variability of Land Use,Soil Type,and Precipitation on Streamflows in Small Watersheds1

Abstract: The spatial variability of the data used in models includes the spatial discretization of the system into subsystems, the data resolution, and the spatial distribution of hydrologic features and parameters. In this study, we investigate the effect of the spatial distribution of land use, soil type, and precipitation on the simulated flows at the outlet of “small watersheds” (i.e., watersheds with times of concentration shorter than the model computational time step). The Soil and Water Assessment Tool model was used to estimate runoff and hydrographs. Different representations of the spatial data resulted in comparable model performances and even the use of uniform land use and soil type maps, instead of spatially distributed, was not noticeable. It was found that, although spatially distributed data help understand the characteristics of the watershed and provide valuable information to distributed hydrologic models, when the watershed is small, realistic representations of the spatial data do not necessarily improve the model performance. The results obtained from this study provide insights on the relevance of taking into account the spatial distribution of land use, soil type, and precipitation when modeling small watersheds.     

GIS‐Based Predictive Models of Hillslope Runoff Generation Processes1

Abstract: Successful nonpoint source pollution control using best management practice placement is a complex process that requires in‐depth knowledge of the locations of runoff source areas in a watershed. Currently, very few simulation tools are capable of identifying critical runoff source areas on hillslopes and those available are not directly applicable under all runoff conditions. In this paper, a comparison of two geographic information system (GIS)‐based approaches: a topographic index model and a likelihood indicator model is presented, in predicting likely locations of saturation excess and infiltration excess runoff source areas in a hillslope of the Savoy Experimental Watershed located in northwest Arkansas. Based on intensive data collected from a two‐year field study, the spatial distributions of hydrologic variables were processed using GIS software to develop the models. The likelihood indicator model was used to produce probability surfaces that indicated the likelihood of location of both saturation and infiltration excess runoff mechanisms on the hillslope. Overall accuracies of the likelihood indicator model predictions varied between 81 and 87% for the infiltration excess and saturation excess runoff locations respectively. On the basis of accuracy of prediction, the likelihood indicator models were found to be superior (accuracy 81‐87%) to the predications made by the topographic index model (accuracy 69.5%). By combining statistics with GIS, runoff source areas on a hillslope can be identified by incorporating easily determined hydrologic measurements (such as bulk density, porosity, slope, depth to bed rock, depth to water table) and could serve as a watershed management tool for identifying critical runoff source areas in locations where the topographic index or other similar methods do not provide reliable results.     

EFFECTS OF IMPROVED PRECIPITATION ESTIMATES ON AUTOMATED RUNOFF MAPPING: EASTERN UNITED STATES1

ABSTRACT: We evaluated maps of runoff created by means of two automated procedures. We implemented each procedure using precipitation estimates of both 5-km and 10-km resolution from PRISM (Parameter-elevation Regressions on Independent Slopes Model). Our goal was to determine if using the 5-km PRISM estimates would improve map accuracy. Visual inspection showed good general agreement among our runoff maps, as well as between our maps and one produced using a manual method. A quantitative uncertainty analysis comparing runoff interpolated from our maps with gage data that had been withheld showed slightly smaller actual and percentage interpolation errors for the 5-km PRISM-based maps. Our analyses suggest a modest region-wide improvement in runoff map accuracy with the use of PRISM-based precipitation estimates of 5-km (compared to 10-km) resolution.     

MONTHLY RUNOFF DISTRIBUTION RELATED TO BASIN GEOGRAPHY1

ABSTRACT: Mean monthly runoff from ungaged drainage basins that have significant snowpacks each year can be estimated quite well by assuming that the time duration between snowfall and snowmelt is the predominant factor in temporal runoff distribution. That time span is related to basin temperatures which are, in turn, functions of basin elevation and latitude. Regional hydrologic analyses of gaged basin data create regression equations for estimating runoff distribution by month. These equations then can be applied to ungaged basins. Basin latitude and mean elevation are two independent variables that can be used in estimating monthly runoff distributions.