IMPROVED RAINFALL/RUNOFF ESTIMATES USING REMOTELY SENSED SOIL MOISTURE1

ABSTRACT: Remotely sensed soil moisture data measured during the Southern Great Plains 1997 (SGP97) experiment in Oklahoma were used to characterize antecedent soil moisture conditions for the Soil Conservation Service (SCS) curve number method. The precipitation‐adjusted curve number and the soil moisture were strongly related (r²= 0.70). Remotely sensed soil moisture fields were used to adjust the curve numbers and the runoff estimates for five watersheds, in the Little Washita watershed; the results ranged from 2.8 km² to 601.6 km². The soil moisture data were applied at two spatial scales, a finer one (800 m) measuring spatial resolution and a coarser one (28 km). The root mean square error (RMSE) and the mean absolute error (MAE) of the runoff estimated by the standard SCS method was reduced by nearly 50 percent when the 800 m soil moisture data were used to adjust the curve number. The coarser scale soil moisture data also significantly reduced the error in the runoff predictions with 41 percent and 28 percent reductions in MAE and RMSE, respectively. The results suggest that remote sensing of soil moisture, when combined with the SCS method, can improve rainfall runoff predictions at a range of spatial scales.     

SIMULATION OF SEDIMENT AND PLANT NUTRIENT LOSSES BY THE CREAMS WATER QUALITY MODEL1

ABSTRACT: CREAMS was applied to a field-sized watershed planted to cotton in the Limestone Valley region of northern Alabama. The field was cultivated for three years with conventional tillage (CvT) followed by three years of conservation tillage (CsT). CREAMS is composed of three components: hydrology, erosion, and chemistry. Surface runoff and losses of sediment, N and P were simulated and results were compared with the observed data from the watershed. Curve numbers recommended in the CREAMS user's guide were not adequate for the watershed conditions. The hydrology submodel improved runoff simulation from CvT and CsT when field-data based curve numbers were used. The erosion submodel demonstrated that CsT reduced sediment loss more than CvT, even though CsT had higher runoff than CvT. The nutrient submodel based on the simulated runoff and sediment underpredicted N loss for both CvT and CsT. This submodel, however, accurately predicted P loss for CvT, but underpredicted for CsT (50 percent lower than the observed). The results of CREAMS simulation generally matched the observed order of magnitude for higher runoff, lower sediment, and higher N and P losses from CsT than from CvT.     

RELIABILITY OF THE DESIGN STORM CONCEPT IN EVALUATING RUNOFF PEAK FLOW1

A comparative study was undertaken to evaluate peak runoff flow rates using (1) a continuous series of actual rainfall events and (2) design storms. The ILLUDAS computer model was used to simulate runoff over a catchment within the city of Montreal, Canada. A ten-year period, five-minute increment rainfall data base was used to derive peak flow frequency curves. Two types of design storms were analyzed: one derived from intensity duration frequency curves (Chicago type), the other from averaging actual rainfall patterns (Huff type). Antecedent soil moisture conditions were considered in the analyses. It was found that the probability distribution of runoff peak flow was sensitive to the choice of design storm pattern and to the antecedent soil moisture condition. A symmetrical, Chicago-type design storm with antecedent dry soil moisture produced a flow frequency curve similar to the one obtained from a series of historical rainfall events.     

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.     

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.     

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.     

Curve Number Derivation for Watersheds Draining Two Headwater Streams in Lower Coastal Plain South Carolina,USA

The objective of this study was to assess curve number (CN) values derived for two forested headwater catchments in the Lower Coastal Plain (LCP) of South Carolina using a three‐year period of storm event rainfall and runoff data in comparison with results obtained from CN method calculations. Derived CNs from rainfall/runoff pairs ranged from 46 to 90 for the Upper Debidue Creek (UDC) watershed and from 42 to 89 for the Watershed 80 (WS80). However, runoff generation from storm events was strongly related to water table elevation, where seasonally variable evapotranspirative wet and dry moisture conditions persist. Seasonal water table fluctuation is independent of, but can be compounded by, wet conditions that occur as a result of prior storm events, further complicating flow prediction. Runoff predictions for LCP first‐order watersheds do not compare closely to measured flow under the average moisture condition normally associated with the CN method. In this study, however, results show improvement in flow predictions using CNs adjusted for antecedent runoff conditions and based on water table position. These results indicate that adaptations of CN model parameters are required for reliable flow predictions for these LCP catchments with shallow water tables. Low gradient topography and shallow water table characteristics of LCP watersheds allow for unique hydrologic conditions that must be assessed and managed differently than higher gradient watersheds.     

THE APPLICATION OF HYDROLOGIC MODELS TO SMALL WATERSHEDS HAVING MILD TOPOGRAPHY1

ABSTRACT: The application of hydrologic models to small watersheds of mild topography is not well documented. This study evaluates the applicability of hydrologic models described by Huggins and the Soil Conservation Service to small watersheds by comparing the simulated and actual hydrograph for both gaged and ungaged situations. The annual maximum rainfall events plus storms exceeding 2.5 inches from 25 years of rainfall and runoff data for two small watersheds were selected for the model evaluations. These storms had a variety of patterns and occurred on many different watershed conditions. Simulated and actual hydrographs were compared using a parameter which contained volume, peak, and shape factors. One-half of the selected storms were used to calibrate the models. For both models, there were no significant differences between the simulated and actual runoff volumes and peak runoff rates. Parameters obtained during the calibration process and relationships developed to estimate antecedent moisture and to modify tabulated runoff curve numbers were used to simulate the runoff hydrograph from the remaining storms. These remaining storms or test storms were simulated only once in order to imitate an ungaged situation. In general, both the Huggins and SCS model performed similarly on the test storms, but the level of model performance was lower than that for the calibration storms. For both models, the two-day antecedent rainfall was more important than the five-day in determining antecedent moisture and modifying tabulated curve numbers. The time of concentration which resulted in good hydrograph simulations was about three times larger than that estimated using published empirical relationships.     

Investigation of the Curve Number Method For Surface Runoff Estimation In Tropical Regions

This study tests the applicability of the curve number (CN) method within the Soil and Water Assessment Tool (SWAT) to estimate surface runoff at the watershed scale in tropical regions. To do this, surface runoff simulated using the CN method was compared with observed runoff in numerous rainfall‐runoff events in three small tropical watersheds located in the Upper Blue Nile basin, Ethiopia. The CN method generally performed well in simulating surface runoff in the studied watersheds (Nash‐Sutcliff efficiency [NSE] > 0.7; percent bias [PBIAS] < 32%). Moreover, there was no difference in the performance of the CN method in simulating surface runoff under low and high antecedent rainfall (PBIAS for both antecedent conditions: ~30%; modified NSE: ~0.4). It was also found that the method accurately estimated surface runoff at high rainfall intensity (e.g., PBIAS < 15%); however, at low rainfall intensity, the CN method repeatedly underestimated surface runoff (e.g., PBIAS > 60%). This was possibly due to low infiltrability and valley bottom saturated areas typical of many tropical soils, indicating that there is scope for further improvements in the parameterization/representation of tropical soils in the CN method for runoff estimation, to capture low rainfall‐intensity events. In this study the retention parameter was linked to the soil moisture content, which seems to be an appropriate approach to account for antecedent wetness conditions in the tropics.     

Hydrology of small field plots used to study phosphorus runoff under simulated rainfall

Use of small plots and rainfall simulators to extrapolate trends in runoff water quality requires careful consideration of hydrologic process represented under such conditions. A modified version of the National Phosphorus Runoff Project (NPRP) protocol was used to assess the hydrology of paired 1 x 2 m plots established on two soils with contrasting hydrologic properties (somewhat poorly drained vs. well drained). Rain simulations (60 mm h(-1)) were conducted to generate 30 min of runoff. For the somewhat poorly drained soil, simulations were conducted in October and May to contrast dry conditions typically targeted by NPRP protocols with wet conditions generally associated with natural runoff. For the well-drained soil, only dry conditions (October) were evaluated. Under dry antecedent moisture conditions, an average of 64 mm of rainfall was applied to the somewhat poorly drained soil to generate 30 min of runoff, as opposed to 96 mm to the well-drained soil. At an extreme, differences in rainfall were equivalent to a 50-yr rainfall-return period. An absence of detectable spatial trends in surface soil moisture suggests uniformity of runoff processes within the plots. No differences in applied rainfall were evident between wet and dry antecedent conditions for the somewhat poorly drained soil. However, significant differences in runoff generation processes were observed in dissolved P concentrations between wet and dry conditions. As natural runoff from the somewhat poorly drained soil is largely under wet antecedent conditions, this study highlights the need for care in interpreting findings from generalized protocols that favor infiltration-excess runoff mechanisms.     

MEASURED AND CREAMS-PREDICTED NITROGEN LOSSES FROM TOMATO AND CORN MANAGEMENT SYSTEMS1

Nitrogen runoff and leaching losses from two tomato and four corn field plots were compared to model predictions by CREAMS, a field-scale model for Chemicals, Runoff, and Erosion from Agricultural Management Systems. The tomato treatments were (1) trickle irrigation with one-half of applied N at preplant and one-half of applied N through the trickle irrigation system and (2) overhead sprinkler irrigation with one-half of applied N at preplant and one-half of applied N in two equal sidedressings. The corn treatments consisted of multiple N applications, minimum tillage, and “conventional” management. Soil type appeared to influence the ability of CREAMS to predict seasonal trends and treatment influences. Model predictions for N losses from tomato and corn treatments that were located on sandy soils often disagreed with measured values. Treatment influences and seasonal trends for N losses from corn treatments that were located on a higher clay content soil were more satisfactorily predicted by CREAMS. Even though model input parameter estimation and measurement techniques may be imperfect, the simulation ability of CREAMS for predicting N leaching losses from systems on deep sands probably needs to be improved. Sensitivity analyses indicated that annual NC₃^?-N leaching loss predictions were either minimally or not affected by changes in saturated hydraulic conductivity. Input estimations of the fraction of soil pore space filled at field capacity and soil organic matter were inversely related to annual NO₃^?-N leaching losses, while potential mineralizable N was directly related to yearly N leaching losses.     

MONTHLY RUNOFF PREDICTIONS BASED ON RAINFALL FORECASTS IN A SMALL OKLAHOMA WATERSHED1

ABSTRACT: Conditions under which monthly rainfall forecasts translate into monthly runoff predictions that could support water resources planning and management activities were investigated on a small watershed in central Oklahoma. Runoff response to rainfall forecasts was simulated using the hydrologic model SWAT. Eighteen scenarios were examined that represented combinations of wet, average, and dry antecedent rainfall conditions, with wet, normal, and dry forecasted rainfall. Results suggest that for the climatic and physiographic conditions under consideration, rainfall forecasts could offer potential application opportunities in surface water resources but only under certain conditions. Pronounced wet and dry antecedent rainfall conditions were shown to have greater impact on runoff than forecasts, particularly in the first month of a forecast period. Large forecast impacts on runoff occurred under wet antecedent conditions, when the fraction of forecasted rainfall contributing to runoff was greatest. Under dry antecedent conditions, most of the forecasted rainfall was absorbed in the soil profile, with little immediate runoff response. Persistent three‐month forecasts produced stronger impacts on runoff than one‐month forecasts due to cumulative effects in the hydrologic system. Runoff response to antecedent conditions and forecasts suggest a highly asymmetric utility function for rainfall forecasts, with greatest decision‐support potential for persistent wet forecasts under wet antecedent conditions when the forecast signal is least dampened by soil‐storage effects. Under average and dry antecedent conditions, rainfall forecasts showed little potential value for practical applications in surface water resources assessments.     

CONTAMINANT LEVELS IN PRECIPITATION AND URBAN SURFACE RUNOFF1

ABSTRACT: Precipitation and resultant runoff were sampled for a series of storm events over the period of one year. The test site was the parking lot of a large suburban shopping mall in the Syracuse, New York, area. Both precipitation and runoff were tested for lead, zinc, copper, cadmium, and petroleum hydrocarbons: substantial amounts were detected in each. No correlation was found between precipitation contaminant concentration and the length of the antecedent dry period. A weak, but apparently inverse relationship was noticed between concentration and amount of precipitation. Poor correlations were obtained between runoff contaminant concentration and the antecedent dry period. The variability attributable to different precipitation volumes was removed by converting to a unit-area basis. The variability attributable to precipitation contaminant load was removed by subtraction. The resultant value, dryfall accumulation, then correlated well with the length of the antecedent dry period. Metal ions were found in both precipitation and runoff and were hypothesized to come from atmospheric fallout as a result of distant emissions and from very localized sources, primarily vehicle traffic on the parking facility. Petroleum residues were believed to be the sole result of automobile losses, since none could be detected in precipitation samples.     

PARAMETER UNCERTAINTY IN RAINFALL-RUNOFF MODELING FOR POLDER SYSTEM DESIGN1

ABSTRACT: An approach is developed for incorporating the uncertainty of parameters for estimating runoff in the design of polder systems in ungaged watersheds. Monte Carlo Simulation is used to derive a set of realizations of streamflow hydrographs for a given design rainstorm using the U. S. Soil Conservation Service (SCS) unit hydrograph model. The inverse of the SCS curve number, which is a function of the antecedent runoff condition in the SCS model, is the random input in the Monte Carlo Simulation. Monte Carlo realizations of streamfiow hydrographs are used to simulate the performance of a polder flood protection system. From this simulation the probability of occurrence of flood levels for a particular hydraulic design may be used to evaluate its effectiveness. This approach is demonstrated for the Pluit Polder flood protection system for the City of Jakarta, Indonesia. While the results of the application indicate that uncertainty in the antecedent runoff condition is important, the effects of uncertainty in rainfall data, in additional runoff parameters, such as time to peak, in the hydraulic design, and in the rainfall-runoff model selected should also be considered. Although, the SCS model is limited to agricultural conditions, the approach presented herein may be applied to other flood control systems if appropriate storm runoff models are selected.     

FLOW PERSISTENCE AS A MODIFIER OF SEASONAL RUNOFF PATTERNS1

ABSTRACT: The effect of flow persistence on seasonal patterns of watershed runoff was modeled by using runoff of the immediate antecedent month as an index. Monthly runoff was expressed as a function of monthly rainfall, season of the year, and runoff of the antecedent month. The three independent variables were expressed functionally as sliding polynomials, thus producing a piece-wise, form-free, three-dimensional causative structure. A model form allowing complete interactivity of the three independent variables could not be optimized because of insufficient data with high values of both antecedent runoff and monthly rainfall. A model with reduced interactivity was successfully optimized. Data sets from five watersheds ranging from 0.14 to 398 square miles were analyzed. Results were presented as a series of contour maps that showed contours of monthly runoff in the data space of season and monthly rain. In the series of maps, the patterns of the runoff contours changed with changing values of antecedent runoff. During the wet season of the year the contours changed significantly with antecedent runoff, but changes in the dry season were minimal. The quantitative change of runoff was more readily portrayed with cross-sections through the contoured surfaces.     

Effects of Spatial Distribution of Prairie Vegetation in an Agricultural Landscape on Curve Number Values

The curve number (CN) method is used to calculate runoff in many hydrologic models, including the Soil and Water Assessment Tool (SWAT). The CN method does not account for the spatial distribution of land cover types, an important factor controlling runoff patterns. The objective of this study was to empirically derive CN values that reflect the strategic placement of native prairie vegetation (NPV) within row crop agricultural landscapes. CNs were derived using precipitation and runoff data from a seven‐year period for 14 small watersheds in Iowa. The watersheds were planted with varying amounts of NPV located in different watershed positions. The least squares and asymptotic least squares methods (LSM) were used to derive CNs using an initial abstraction coefficient (λ) of 0.2 and 0.05. The CNs were verified using leave‐one‐out cross‐validation and adjustment for antecedent moisture conditions (AMC) was tested. The asymptotic method produced CN values for watersheds with NPV treatment that were 8.9 and 14.7% lower than watersheds with 100% row crop at λ = 0.2 and λ = 0.05, respectively. The derived CNs produced Nash‐Sutcliffe efficiency values ranging from 0.4 to 0.7 during validation. Our analyses show the CNs verified best for the asymptotic LSM, when using λ of 0.05 and adjusting for AMC. Further, comparison of derived CNs against an area weighted CN indicated that the placement of vegetation does impact the CN value. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

A STRIP MODEL APPROACH TO PARAMETERIZE A COUPLED GREEN‐AMPT KINEMATIC WAVE MODEL1

ABSTRACT: Infiltration processes at the plot scale are often described and modeled using a single effective hydraulic conductivity (Kg) value. This can lead to errors in runoff and erosion prediction. An integrated field measurement and modeling study was conducted to evaluate: (1) the relationship among rainfall intensity, spatially variable soil and vegetation characteristics, and infiltration processes; and (2) how this relationship could be modeled using Green and Ampt and a spatially distributed hydrologic model. Experiments were conducted using a newly developed variable intensity rainfall simulator on 2 m by 6 m plots in a rangeland watershed in southeastern Arizona. Rainfall application rates varied between 50 and 200 mm/hr. Results of the rainfall simulator experiments showed that the observed hydrologic response changed with changes in rainfall intensity and that the response varied with antecedent moisture condition. A distributed process based hydrologic simulation model was used to model the plots at different levels of hydrologic complexity. The measurement and simulation model results show that the rainfall runoff relationship cannot be accurately described or modeled using a single Kg value at the plot scale. Multi‐plane model configurations with infiltration parameters based on soil and plot characteristics resulted in a significant improvement over single‐plane configurations.     

TESTS OF THE CREAMS MODEL ON AGRICULTURAL FIELDS IN VERMONT1

ABSTRACT: The computer model, CREAMS, has been developed for field-sized agricultural areas to aid in best management practices evaluation and planning. A test of CREAMS was performed by comparing monthly observed and simulated values for runoff, sediment, and phosphorus exports from two agricultural fields in Vermont to determine the applicability of the model in cold climates. Water quality samples were collected from field runoff and analyzed for both total suspended solids and total phosphorus. Generally, exports were overestimated during low flow months and underestimated during high flow months. Significant r²values (p <0.05), ranging from 0.78 to 0.90, between simulated and observed data were found for all comparisons except for sediment export from one field. Comparisons of the slopes of the regressions between observed and simulated values and the ideal slope of one using t-tests revealed significant differences between simulated and observed monthly runoff, sediment, and phosphorus exports. It is postulated that this lack of adequate prediction could be attributed to the use of average monthly, instead of daily, temperature and solar radiation in calculations of evapotranspiration and snowmelt, and the use of static parameter values for parameters that vary seasonally.     

Time Series Analysis of Nebraska Daily Rainfall Data to Simulate Atrazine Runoff1

Abstract: Measured atrazine concentrations in Nebraska surface water have been shown to exceed water‐quality standards, posing risks to humans and to the ecosystem. To assess this risk, atrazine runoff was simulated at the field‐scale in Nebraska based on the pesticide component of the AGNPS model. This project’s objective was to determine the frequency that the atrazine concentration at the field outlet exceeded three different atrazine water‐quality criteria. The simulation was conducted for different farm management practices, soil moisture conditions, and five Nebraska topographic regions. If the criteria were exceeded, a risk to the drinking water consumer or freshwater aquatic life was hypothesized to exist. Three pesticide fate and transport processes were simulated with the model. Degradation was simulated using first‐order kinetics. Adsorption/desorption was modeled assuming a linear soil‐water partitioning coefficient. Advection (runoff) was based primarily on the USDA‐NRCS curve number method. Daily rainfall from the National Weather Service was used to compute the soil moisture conditions for the 1985‐2000 growing seasons. After each runoff event, the pesticide runoff concentration was compared with each of the three atrazine water‐quality criteria. The results show that environmental receptors (i.e., freshwater aquatic species) are exposed to unacceptable atrazine runoff concentrations in 20‐50% of the runoff events.     

Inferring Hydrograph Components from Rainfall and Streamflow Records Using a Kriging Method-Based Linear Cascade Reservoir Model1

Cheng, Shin-jen, 2010. Inferring Hydrograph Components From Rainfall and Streamflow Records Using a Kriging Method-Based Linear Cascade Reservoir Model. Journal of the American Water Resources Association (JAWRA) 46(6):1171–1191. DOI: 10.1111/j.1752-1688.2010.00484.x Abstract: This study investigates the characteristics of hydrograph components in a Taiwan watershed to determine their shapes based on observations. Hydrographs were modeled by a conceptual model of three linear cascade reservoirs. Mean rainfall was calculated using the block Kriging method. The optimal parameters for 42 events from 1966-2008 were calibrated using an optimal algorithm. Rationality of generated runoffs was well compared with a trusty model. Model efficacy was verified using seven averaged parameters with 25 other events. Hydrograph components were characterized based on 42 calibration results. The following conclusions were obtained: (1) except for multipeak storms, a correlation between base time of the surface runoff and soil antecedent moisture is a decreasing power relationship; (2) a correlation between time lag of the surface flow and soil antecedent moisture for single-peak storms is an increasing power relationship; (3) for single-peak events, times to peak of hydrograph components are an increasing power correlation corresponding to the peak time of rainfall; (4) the peak flows of hydrograph components are linearly proportional to that of total runoff, and the peak ratio for the surface runoff to total runoff is approximately 78 and 13% for subsurface runoff to total runoff; and (5) the relationships of total discharges have direct ratios between hydrograph components and observations of total runoffs, and a surface runoff is 60 and 32% for a subsurface runoff.