USING A DISTRIBUTED ROUTING RAINFALL-RUNOFF MODEL1

ABSTRACT: Urban storm water data from four catchments near Miami, Florida, were collected and compiled by the U.S. Geological Survey and were used for testing the applicability of deterministic modeling for characterizing storm water flows from small land use areas. The four sites were:

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USING INFILTRATION ENHANCEMENT AND SOIL WATER MANAGEMENT TO REDUCE DIAZINON IN RUNOFF1

ABSTRACT: Pesticide runoff from dormant sprayed orchards is a major water quality problem in California's Central Valley. During the past several years, diazinon levels in the Sacramento and San Joaquin Rivers have exceeded water quality criteria for aquatic organisms. Orchard water management, via post‐application irrigation, and infiltration enhancement, through the use of a vegetative ground cover, are management practices that are believed to reduce pesticide loading to surface waters. Field experiments were conducted in Davis, California, to measure the effectiveness of these management practices in reducing the toxicity of storm water runoff. Treatments using a vegetative ground cover significantly reduced peak concentrations and cumulative pesticide mass in runoff for first flush experiments compared with bare soil treatments. Post‐application irrigation was found to be an effective means of reducing peak concentrations and cumulative mass in runoff from bare soil treatments, but showed no significant effect on vegetated treatments.     

PREDICTING TEMPORAL AND SPATIAL FLOOD DYNAMICS USING A PRECALIBRATED MODEL1

ABSTRACT: A large storm in December 1990 allowed the evaluation of flood predictions from a hydrologic model (TOPMODEL) that had been previously calibrated on the West Fork of Walker Branch Watershed, a gauged 37.5 ha catchment near Oak Ridge, Tennessee. The model predicts both hydrograph dynamics and the spatial distribution of overland flow using an index based on topography. Maximum extent of overland flow during the storm was determined from patterns of leaf litter removal from valley bottoms. Both the flood hydrograph and the extent of overland flow were accurately predicted using model parameters obtained from a three-month period of normal flow conditions during 1983.     

APPLICABILITY OF THE GREEN AND AMPT INFILTRATION EQUATION TO RANGELANDS1

ABSTRACT: The objective of this study was to investigate the use of Green and Ampt infiltration equation parameters (determined by least squares fitting of field infiltration data or predicted from soil texture properties) to characterize infiltration on spatially varying rangeland sites. It was found that a least squares regression approach reduces the physically based parameters in the Green and Ampt to empirical coefficients since negative coefficients are obtained, particularly on plots with low infiltration rates. Green and Ampt parameters predicted from soil texture data describe infiltration rates less than 3 cm/hr. The applicability of these Green and Ampt parameters appears limited to sites with lower infiltration rates. Results indicate that soil texture predictive triangles, developed to describe infiltration on agricultural soils, need revision to adequately describe infiltration patterns on rangelands.     

USING CURVE NUMBERS TO DETERMINE BASELINE VALUES OF GREEN-AMPT EFFECTIVE HYDRAULIC CONDUCTIVITIES1

ABSTRACT: Since the trend in infiltration modeling is currently toward process-based approaches such as the Green-Ampt equation, more emphasis is being placed on methods of determining appropriate parameters for this approach. The SCS curve number method is an accepted and commonly used empirical approach for estimating surface runoff, and is based on numerous data from a variety of sources. The time and expense of calibrating process-based infiltration parameters to measured data are often prohibitive. This study uses curve number predictions of runoff to develop equations to estimate the “baseline” hydraulic conductivities (K_b) for use in the Green-Ampt equation. Curve number predictions of runoff were made for 43 soils. K_b values in the Water Erosion Prediction Project (WEPP) model were then calibrated so that the annual runoff predicted by WEPP was equal to the curve number predictions. These calibrated values were used to derive an equation that estimated K_b based on the percent sand, percent clay, and cation exchange capacity of the soil. Estimated values of K_b from this equation compared favorably with measured values and values calibrated to measured natural runoff plot data. WEPP predictions of runoff using both optimized and estimated values of K_b were compared to curve number predictions of runoff and the measured values. The WEPP predictions using the optimized values of K_b were the best in terms of both average error and model efficiency. WEPP predictions using estimated values of K_b were shown to be superior to predictions obtained from the curve number method. The runoff predictions all tended to be biased high for small events and low for larger events when compared to the measured data. Confidence intervals for runoff predictions on both an annual and event basis were also developed for the WEPP model.     

ANALYSIS AND MODELING OF LONG-TERM STREAM TEMPERATURES ON THE STEAMBOAT CREEK BASIN,OREGON: IMPLICATIONS FOR LAND USE AND FISH HABITAT1

ABSTRACT: Steamboat Creek basin is an important source of timber and provides crucial spawning and rearing habitat for anadromous steelhead trout (Oncorhynchus mykiss). Because stream temperatures are near the upper limit of tolerance for the survival of juvenile steelhead, the possible long-term effect of clear-cut logging on stream temperatures was assessed. Twenty-year (1969–1989) records of summer stream temperature and flow from four tributaries and two reaches of Steamboat Creek and Boulder Creek (a nearby unlogged watershed) were analyzed. Logging records for the Steamboat Creek basin and air temperature records also were used in the analysis. A time-series model of the components of stream temperature (seasonal cycle of solar radiation, air temperature, streamflow, an autoregressive term of order 1, and a linear trend variable) was fitted to the water-temperature data. The linear trend variable was significant in all the fitted models except Bend Creek (a tributary fed by cool ground-water discharge) and Boulder Creek. Because no trends in either climate (i.e., air temperature) or streamflow were found in the data, the trend variable was associated with the pre-1969 loss and subsequent regrowth of riparian vegetation and shading canopies.     

RUNOFF SIMULATION USING RADAR RAINFALL DATA1

ABSTRACT: Rainfall data products generated with the national network of WSR-88D radars are an important new data source provided by the National Weather Service. Radar-based data include rainfall depth on an hourly basis for grid cells that are nominally 4 km square. The availability of such data enables application of improved techniques for rainfall-runoff simulation. A simple quasi-distributed approach that applies a linear runoff transform to grid-ded rainfall excess has been developed. The approach is an adaptation of the Clark conceptual runoff model, which employs translation and linear storage. Data development for, and results of, an initial application to a 4160 km² watershed in the Midwestern U.S. are illustrated.     

APPLICATION OF THE SNOWMELT RUNOFF MODEL USING MULTIPLE-PARAMETER LANDSCAPE ZONES ON THE TOWANDA CREEK BASIN,PENNSYLVANIA1

ABSTRACT: The Snowmelt Runoff Model (SRM) is designed to compute daily stream discharge using satellite snow cover data for a basin divided into elevation zones. For the Towanda Creek basin, a Pennsylvania watershed with relatively little relief, analysis of snow cover images revealed that both elevation and land use affected snow accumulation and melt on the landscape. The distribution of slope and aspect on the watershed was also considered; however, these landscape features were not well correlated with the available snow cover data. SRM streamflow predictions for 1990, 1993 and 1994 snowmelt seasons for the Towanda Creek basin using a combination of elevation and land use zones yielded more precise streamflow estimates than the use of standard elevation zones alone. The use of multiple-parameter zones worked best in non-rain-on-snow conditions such as in 1990 and 1994 seasons where melt was primarily driven by differences in solar radiation. For seasons with major rain-on-snow events such as 1993, only modest improvements were shown since melt was dominated by rainfall energy inputs, condensation and sensible heat convection. Availability of GIS coverages containing satellite snow cover data and other landscape attributes should permit similar reformulation of multiple-parameter watershed zones and improved SRM streamflow predictions on other basins.     

AN OBJECTWE TEST FOR HYDROLOGIC SCALE1

ABSTRACT: Improving the reliability of parametric hydrologic models (sometimes called cenceptual rainfall-runoff models) in the continuous simulation of runoff from ungaged catchments has been frustrated by difficulties in estimating model parameters from catchment characteristics. An underlying problem is that these models use parameters to represent catchments as a whole, whereas data on catchment characteristics are collected at multiple field locations and are difficult to transform into one measure of collective impact. Subdividing the catchment and calibrating a stochastic parametric model to estimate distributions for the parameters that covered the range of observed streamflow values was found to improve the simulations. This paper presents an optimization of the amount of subdivision to use in simulation with a version of the Stanford Watershed Model using available climatological data. The calibration process assumes that catchment heterogeneity introduces errors that can be reduced by calibrating parameters as spatial distributions rather than single values. Calibrations for three diverse small gaged catchments located in California and in Virginia found the optimal number of subdivisions to range from 4 to 25 and the optimal scale to range from 0.3 to 2.1 mi².     

GROUND WATER MANAGEMENT OPTIMIZATION USING GENETIC ALGORITHMS AND SIMULATED ANNEALING: FORMULATION AND COMPARISON1

ABSTRACT: Genetic algorithms (GA) and simulated annealing (SA), two global search techniques, are coupled with MODFLOW, a commonly used groundwater flow simulation code, for optimal management of ground water resources under general conditions. The coupled simulation-optimization models allow for multiple management periods in which optimal pumping rates vary with time to reflect the changing flow conditions. The objective functions of the management models are of a very general nature, incorporating multiple cost terms such as the drilling cost, the installation cost, and the pumping cost. The models are first applied to two-dimensional maximum yield and minimum cost water supply problems with a single management period, and then to a multiple management period problem. The strengths and limitations of the GA and SA based models are evaluated by comparing the results with those obtained using linear programming, nonlinear programming, and differential dynamic programming. For the three example problems examined in this study, the GA and SA based models yield nearly identical or better solutions than the various programming methods. While SA tends to outperform GA in terms of the number of forward simulations needed, it uses more empirical control parameters which have significant impact on solution efficiency but are difficult to determine.     

EFFECTS OF BASIN-SCALE TIMBER HARVEST ON WATER YIELD AND PEAK STREAMFLOW1

ABSTRACT: Streamflow changes resulting from clearcut harvest of lodgepole pine (Pinus contorta) on a 2145 hectare drainage basin are evaluated by the paired watershed technique. Thirty years of continuous daily streamflow records were used in the analysis, including 10 pre-harvest and 20 post-harvest years of data. Regression analysis was used to estimate the effects of timber harvest on annual water yield and annual peak discharge. Removal of 14 million board feet of lodgepole pine (Pinus contorta) from about 526 hectares (25 percent of the basin) produced an average of 14.7 cm additional water yield per year, or an increase of 52 percent. Mean annual daily maximum discharge also increased by 1.6 cubic meters per second or 66 percent. Increases occurred primarily during the period of May through August with little or no change in wintertime streamflows. Results suggest that clearcutting conifers in relatively large watersheds (> 2000 ha) may produce significant increases in water yield and flooding. Implications of altered streamflow regimes are important for assessing the future ecological integrity of stream ecosystems subject to large-scale timber harvest and other disturbances that remove a substantial proportion of the forest cover.     

HYDROLOGIC LANDSCAPES ON THE DELMARVA PENINSULA PART 1: DRAINAGE BASIN TYPE AND BASE-FLOW CHEMISTRY1

ABSTRACT: The relation between landscape characteristics and water chemistry on the Delmarva Peninsula can be determined through a principal-component analysis of basin characteristics. Two basin types were defined by factor scores: (1) well-drained basins, characterized by combinations of a low percentage of forest cover, a low percentage of poorly drained soil, and elevated channel slope; and (2) poorly drained basins, characterized by a combinations of an elevated percentage of forest cover, an elevated percentage of poorly drained soil, and low channel slopes. Results from base-flow sampling of 29 basins during spring 1991 indicate that water chemistry of the two basin types differ significantly. Concentrations of calcium, magnesium, potassium, alkalinity, chloride, and nitrate are elevated in well-drained basins, and specific conductance is elevated. Concentrations of aluminum, dissolved organic carbon, sodium, and silica are elevated in poorly drained basins whereas specific conductance is low. The chemical patterns found in well-drained basins can be attributed to the application of agricultural chemicals, and those in poorly drained basins can be attributed to ground-water flowpaths. These results indicate that basin types determined by a quantitative analysis of basin characteristics can be related statistically to differences in base-flow chemistry, and that the observed statistical differences can be related to major processes that affect water chemistry.     

MODEL ACCURACY IN SNOWMELT-RUNOFF FORECASTS EXTENDING FROM 1 TO 20 DAYS1

ABSTRACT: This paper examines the performance of snowmelt-runoff models in conditions approximating real-time forecast situations. These tests are one part of an intercomparison of models recently conducted by the World Meteorological Organization (WMO). Daily runoff from the Canadian snowmelt basin Illecille. waet (1155 km², 509–3150 m a.s.l.) was forecast for 1 to 20 days ahead. The performance of models was better than in a previous WMO project, which dealt with runoff simulations from historical data, for the following reasons: (1) conditions for models were more favorable than a real-time forecast situation because measured input data and not meteorological forecast inputs were distributed to the modelers; (2) the selected test basin was relatively easy to handle and familiar from the previous WMO project; and (3) all kinds of updating were allowed so that some models even improved their accuracy towards longer forecast times. Based on this experience, a more realistic follow-up project can be imagined which would include temperature forecasts and quantitative precipitation forecasts instead of measured data.     

HYDROLOGIC LANDSCAPES ON THE DELMARVA PENINSULA PART 2: ESTIMATES OF BASE-FLOW NITROGEN LOAD TO CHESAPEAKE BAY1

ABSTRACT: Base-flow samples were collected from 47 sampling sites for four seasons from 1990–91 on the Delmarva Peninsula in Delaware and Maryland to relate stream chemistry to a “hydrologic landscape” and season. Two hydrologic landscapes were determined: (1) a well-drained landscape, characterized by a combination of a low percentage of forest cover, a low percentage of poorly drained soil, and elevated channel slope; and (2) poorly drained landscape, characterized by a combination of an elevated percentage of forest cover, an elevated percentage of poorly drained soil, and low channel slope. Concentrations of nitrogen were significantly related to the hydrologic landscape. Nitrogen concentrations tended to be higher in well-drained landscapes than in poorly drained ones. The highest instantaneous nitrogen yields occurred in well-drained landscapes during the winter. These yields were extrapolated over the part of the study area draining to Chesapeake Bay in order to provide a rough estimate of nitrogen load from base flow to the Bay and its estuarine tributaries. This estimate was compared to an estimate made by extrapolating from an existing long-term monitoring station. The load estimate from the stream survey data was 5 ± 10⁶ kg of N per year, which was about four times the estimate, made from the existing long-term monitoring station. The stream-survey estimate of base flow represents about 40 percent of the total nitrogen load that enters the Bay and estuarine tributaries from all sources in the study area.     

MODELING THE BUILDUP AND WASHOFF OF POLLUTANTS ON URBAN WATERSHEDS1

ABSTRACT: A model for urban stormwater quality was developed in this study. The basis for the model is the process by which pollutants build up on the watershed surface. For the wet climate of the study site, it was assumed that there exists an interval of time over which the pollutant buildup equals the pollutant washoff (no accumulation of pollutant). The buildup model was represented by a linear function of the antecedent dry time. The buildup function was then linked with a pollutant washoff model represented by a power function of the storm runoff volume. Various time intervals for no net accumulation were tested to calibrate the model. The model was calibrated to observed data for two small urban basins in Baton Rouge, Louisiana, and model results were used to analyze the behavior of phosphorus concentrations in storm runoff from these basins over a long period of time.     

VALIDATION OF AGNPS FOR SMALL WATERSHEDS USING AN INTEGRATED AGNPS/GIS SYSTEM1

ABSTRACT: The AGNPS (AGricultural NonPoint Source) model was evaluated for predicting runoff and sediment delivery from small watersheds of mild topography. Fifty sediment yield events were monitored from two watersheds and five nested subwater-sheds in East Central Illinois throughout the growing season of four years. Half of these events were used to calibrate parameters in the AGNPS model. Average calibrated parameters were used as input for the remaining events to obtain runoff and sediment yield data. These data were used to evaluate the suitability of the AGNPS model for predicting runoff and sediment yield from small, mild-sloped watersheds. An integrated AGNPS/GIS system was used to efficiently create the large number of data input changes necessary to this study. This system is one where the AGNPS model was integrated with the GRASS (Geographic Resources Analysis Support System) GIS (Geographical Information System) to develop a decision support tool to assist with management of runoff and erosion from agricultural watersheds. The integrated system assists with the development of input GIS layers to AGNPS, running the model, and interpretation of the results.     

AN EVALUATION OF THE HYDROLOGIC SOIL GROUPS AS USED IN THE SCS RUNOFF METHOD ON RANGELANDS1

The U.S. Soil Conservation Service has developed a method for estimating runoff for small watersheds when stream flow data are not available. The technique is based on a simplified infiltration model of runoff using various kinds of soil, land use, and empirical approximation.     

WATER LOSS EQUATIONS AND COEFFICIENTS TO ESTIMATE RUNOFF FROM RAINFALL1

Infiltration models are based on physical characteristics of the soil and initial soil moisture. For a given soil it is based on the initial soil moisture distribution. A computer simulation model for flood runoff systems (FH-Model) was used to analyze 39 sets of rainfall-runoff data on four small watersheds ranging in size from 17 to 342 square kilometers located in the Yamaska River basin in Quebec. From these analyses, parameters and coefficients have been determined for a water loss (infiltration) equation. A method for determining the loss parameters, using a nonlinear least square curve fitting technique, is presented. Expressions were made to relate the loss parameters to antecedent precipitation. The equations were tested on 11 storm rainfall and runoff events on a watershed located in the same region and close agreements were found.