Chemicals, Runoff, And Erosion From Agricultural Management Systems Research Articles

An improved MUSLE model incorporating the estimated runoff and peak discharge predicted sediment yield at the watershed scale on the Chinese Loess Plateau

An accurate prediction of sediment yield at the watershed scale is critical not only for sustainable watershed management but also for improving knowledge regarding the relationship between sediment yield and its determinant factors, which often rely on the varying model complexity. In this study, a modified sediment yield formula based on the modified universal soil loss equation (MUSLE) model was developed by introducing a channel factor into the original formula. The reliability of the proposed method was tested using data from 1,341 storm events in 38 watersheds and was applied to 256 storm events in five application watersheds using the optimized parameters. Results indicated that the proposed method is very accurate, as demonstrated by the Nash–Sutcliffe efficiency (NSE) values of 88.18 %, 85.72 %, and 85.51 % during calibration, validation, and application, respectively. The performance of the proposed model was superior to that of the original MUSLE model. Subsequently, the proposed method was used to predict sediment yield from the last five typical watersheds. This prediction utilized the parameters derived from the initial 38 watersheds; the peak discharge predicted by the modified Chemicals, Runoff, and Erosion from Agricultural Management Systems (CREAMS); and the runoff estimated by the modified Soil Conservation Service Curve Number (SCS-CN) method. Elevated NSE (61.88–81.42 %) and low root mean square error values (2.35–11.40 t ha−1) were calculated for the five watersheds. From the results, the proposed sediment yield model, combined with the modified SCS-CN method and CREAMS, was found to accurately predict the event-based sediment yield, peak discharge, and runoff in the Loess Plateau region under varying hydrological and geomorphic conditions.

An improved method that incorporates the estimated runoff for peak discharge prediction on the Chinese Loess Plateau

An accurate prediction of peak discharge in watersheds is critical not only for water resource management, but also for understanding the complex relationships of hydrological processes. In this study, a modified peak discharge formula based on the Chemicals, Runoff, and Erosion from Agricultural Management Systems (CREAMS) model was developed by introducing rainfall intensity and soil moisture factors. The reliability of the proposed method was tested with data from 1464 storm events in 41 watersheds and was applied to 256 storm events in five remaining typical watersheds using the optimized parameters. The results indicate that the proposed method is highly accurate in terms of model efficiency, as determined by Nash–Sutcliffe efficiencies (NSEs) of 88.60%, 74.04%, and 90.12% during the calibration, validation, and application cases, respectively. Furthermore, it performed better than the original and modified CREAMS methods. Subsequently, using the parameters derived from the initial 41 watersheds and the runoff estimated using the modified Soil Conservation Service curve number (SCS–CN) method, the proposed method was used to predict the peak discharge from the last five typical watersheds. Large NSE (63.88–80.83%) and low root mean square error (RMSE) values (0.31–35.93 m3s-1) were obtained for the five watersheds. Overall, the proposed peak discharge model, combined with the modified SCS-CN method, may accurately predict event-based peak discharge and runoff for general applications under various hydrological and geomorphic conditions in the Loess Plateau region.

CREAMS/GLEAMS: Model Use, Calibration, and Validation

The Chemicals, Runoff, and Erosion from Agricultural Management Systems (CREAMS) model was developed by a multidisciplinary team of research scientists from the USDA Agricultural Research Service. The primary purpose of the model was to aid the USDA Natural Resources Conservation Service (NRCS) specialists in assessing nonpoint-source pollution from agricultural areas and to compare impacts of alternative management practices. Existing readily modifiable and new components were assembled into a field-scale model. Modelers also were charged with publication of model documentation, validation, and a user manual. Model validation with available data and sensitivity analyses of parameters in the hydrology, erosion, plant nutrient, and pesticide components were essential to demonstrate the model capabilities and effectiveness. Technology transfer to NRCS personnel was necessary to gain acceptance and proper use as well as to identify weaknesses and areas for needed improvement. Following publication and NRCS acceptance, improvements to CREAMS were made to better represent soil layering, crop rotations, irrigation, soil water routing, and chemical movement, which resulted in the Groundwater Loading Effects of Agricultural Management Systems (GLEAMS) model. Climatic records were increased from a maximum of 20 years to 50 years. The modifications were validated with available data and included in subsequent publications. The user manual gives more comprehensive description of the model parameters and their relative sensitivity. This article describes the historical development of the CREAMS and GLEAMS models with an emphasis on providing model users with an understanding of the degree of model verification and validation that was undertaken during development of these multidisciplinary models. Model calibration is discussed, including sensitive parameters and recommended procedures. Finally, two specific case studies are presented along with brief synopses of numerous case studies that have been used to validate model components. Future users are encouraged to use the model source code to further expand its utility for analyzing the nonpoint-source pollution impacts of agricultural management practices.

Enhancing RUSLE to include runoff‐driven phenomena

AbstractRUSLE2 (Revised Universal Soil Loss Equation) is the most recent in the family of Universal Soil Loss Equation (USLE)/RUSLE/RUSLE2 models proven to provide robust estimates of average annual sheet and rill erosion from a wide range of land use, soil, and climatic conditions. RUSLE2's capabilities have been expanded over earlier versions using methods of estimating time‐varying runoff and process‐based sediment transport routines so that it can estimate sediment transport/deposition/delivery on complex hillslopes. In this report we propose and evaluate a method of predicting a series of representative runoff events whose sizes, durations, and timings are estimated from information already in the RUSLE2 database. The methods were derived from analysis of 30‐year simulations using a widely accepted climate generator and runoff model and were validated against additional independent simulations not used in developing the index events, as well as against long‐term measured monthly rainfall/runoff sets. Comparison of measured and RUSLE2‐predicted monthly runoff suggested that the procedures outlined may underestimate plot‐scale runoff during periods of the year with greater than average rainfall intensity, and a modification to improve predictions was developed. In order to illustrate the potential of coupling RUSLE2 with a process‐based channel erosion model, the resulting set of representative storms was used as an input to the channel routines used in Chemicals, Runoff, and Erosion from Agricultural Management Systems (CREAMS) to calculate ephemeral gully erosion. The method was applied to a hypothetical 5‐ha field cropped to cotton in Marshall County, MS, bisected by a potential ephemeral gully having channel slopes ranging from 0·5 to 5% and with hillslopes on both sides of the channel with 5% steepness and 22·1 m length. Results showed the representative storm sequence produced reasonable results in CREAMS indicating that ephemeral gully erosion may be of the same order of magnitude as sheet and rill erosion. Copyright © 2010 John Wiley & Sons, Ltd.

A Review of New Zealand Research Measuring Phosphorus in Runoff from Pasture

AbstractNew Zealand pastoral farm land is intensively grazed and receives predominantly single superphosphate fertilizer. Resource managers and policymakers are concerned about the effects of such land use on P enrichment of waterways and lakes. This paper reviews New Zealand research on the effects of agricultural land use on P losses in water runoff and highlights priorities for management and future research. Diffuse agricultural sources contribute about 91% of total P entering fresh waters annually, with 0.11 to 1.67 kg P ha−1 yr−1 being removed, mostly in particulate forms. Despite a number of studies showing good site‐specific correlation, no widely applicable soil test method for estimating runoff dissolved P concentration has been found. The effects of (i) fertilizer application in increasing surface runoff P concentrations (ii) riparian areas in both source and control roles, and (iii) subsurface drainage, in reducing losses of P in surface runoff from pasture land, are reported. A catchment scale simulation model, Basin New Zealand (BNZ), for intensively grazed pastures, has been produced based on CREAMS (chemicals, runoff, and erosion from agricultural management systems). This model adequately predicts P loss at the field scale but is less reliable at the catchment scale, which indicates differences in predominant P and sediment sources at the two scales. Corrective management has alleviated eutrophication problems in some lakes and waterways; however better information is yet required to understand, model, and manage the more insidious losses of P to waterways from New Zealand farm land.

Laboratory rainfall simulator studies of selected open-cut coal mine overburden spoils from Central Queensland

Data on the erodibility of overburden spoils resulting from open-cut coal mining are limited. These data are required to derive parameters for erosion prediction models which can be used in the design of re-formed landscapes after mining. In this study, laboratory rainfall simulation data were used to derive CREAMS (Chemicals, Runoff and Erosion from Agricultural Management Systems) interrill erodibility parameters K and nbov for Central Queensland coal mine overburden spoils. For the spoils studied, K values ranged from 0·0111 to 0·1398 Mg·ha·h/(ha·MJ·mm) and nbov values ranged from 0·0004 to 0·0081. Sediment yield was transport controlled. Results for 1 spoil, South Blackwater Terang, showed that total soil loss increased linearly with slope, and both K and nbov varied non-linearly with slope. If a constant set of K and nbov values is used in modelling, CREAMS over-predicts spoil loss for slopes greater than that for which the parameter values were determined, and under-predicts spoil loss for slopes less than that for which the parameter values were determined. The results show evidence of differences between mine spoils and agricultural soils, including modality of size distribution of surface sediment available for erosion, a higher percentage of dispersed clays in eroded sediment from mine spoils than from agricultural soils, and the observed amount of surface sealing and crust formation. These differences indicate that erosion{erodibility parameters for mine spoils should be measured and that agricultural soil parameters should not be a basis for estimates of mine spoil parameters.

Using a Geographic Information System (GIS) for Herbicide Management

An algorithm was developed for use in a geographic information system (GIS) to model the surface movement of herbicide in response to a rainfall event as modulated by slope, soil, management practices, and time of herbicide application. This algorithm was implemented in the GIS software Geographic Resource Analysis Support System (GRASS) and uses as submodels the Natural Resources Conservation Service (NRCS) curve number procedure, the Universal Soil Loss Equation (USLE), and the pesticide submodel from the model Chemicals, Runoff, and Erosion from Agricultural Management Systems (CREAMS). The algorithm estimates the loss of pesticide from field areas, runoff flow patterns, and the accumulation of pesticide downslope in response to a rainfall event. The simulated movement of atrazine, cyanazine, and alachlor was studied under hypothetical management scenarios in the Lake Pittsfield watershed in Pike Co., IL. Tillage for the simulation was by moldboard plow. An alternate no-till scenario was simulated to test tillage effect on atrazine movement. Herbicides were applied either PPI, PRE, POST, or early preplant for no-till (treated as same application time as PPI but without incorporation). The experiment was designed to incorporate timing of application as a management factor from the standpoint of a single rain event on May 16. The results used for comparison were data from 1 d after POST application, 15 d after PRE application and 30 d after PPI application. The algorithm showed that areas of greater herbicide risk can be located within a watershed and that the effect of alternative management practices can be evaluated using a GIS.

Calibration and Testing of Simulation Models for Evaluation of Trench Cap Designs

AbstractA prototype decision support system (PDSS) using multi‐objective decision theory and embedded simulation models is being developed to evaluate landfill cover designs for low‐level radioactive waste disposal sites. To evaluate the performance of the PDSS, the simulation models, which are used to parameterize the decision model when data are not available, must be calibrated and tested. The two linked simulation models embedded in the PDSS are the HELP (hydrologic evaluation of landfill performance) and CREAMS (chemicals, runoff, and erosion from agricultural management systems) models. Data from a field demonstration study at Hill Air Force Base were used to calibrate the simulation models. The models were calibrated using water balance and erosion parameters for two alternative designs, a control soil cover and a modified USEPA Resource Conservation and Recovery Act design. Simulations were run using the calibrated model parameters for a 200‐yr period to evaluate the long‐term performance of the models. The progressive annual average for all of the output parameters was within the 95% confidence limits of the long‐term mean by Year 60 for both of the cover designs evaluated. The results of the calibration and long‐term evaluation of the simulation models were reasonable for the length of the data set. To fully validate and test the simulation models, other data sets of landfill covers in a variety of climates are needed.

Evaluation of a Prototype Decision Support System for Selecting Trench Cap Designs

AbstractA computer‐based prototype decision support system (PDSS) to assist the risk manager in selecting an appropriate trench cap design for waste disposal sites is evaluated. The selection of the “best” design among feasible alternatives requires consideration of multiple and often conflicting objectives. The methodology used in the selection process consists of: selecting and parameterizing decision variables, using data, simulation models, or expert opinion; selecting feasible trench cap design alternatives; ordering the decision variables and ranking the design alternatives. The simulation models incorporated in the PDSS are the Hydrologic Evaluation of Landfill Performance (HELP) model which is used to simulate the trench cap water balance and the Chemicals, Runoff, and Erosion from Agricultural Management Systems (CREAMS) erosion component that is used to simulate trench cap erosion. The decision model is based on multi‐objective decision theory and uses a unique approach to order the decision variables and rank the design alternatives. The PDSS is evaluated using the Hill Air Force Base landfill cover demonstration project. The water balance and surface erosion of four alternative landfill cover designs were monitored for a 4‐yr period. Two of the cover designs were used to calibrate and test the simulation models. The results of the PDSS, using both data from all four designs and long‐term simulations from two of the designs, illustrate the relative advantages of each of the cover designs and which cover is the “best” alternative for a given set of criteria and a particular importance order of those decision criteria.

Evaluation of the CREAMS model. 4. Derivation of interrill erodibility parameters from laboratory rainfall simulator data and prediction of soil loss under a field rainulator using the derived parameters

This study investigated the use of laboratory rainfall simulator data for the derivation of CREAMS (chemicals runoff, and Erosion from Agricultural Management Systems) interrill erodibility parameters K and nbov. The laboratory rainfall simulator method of collecting erosion data was validated using the surface of an Irving clay (black earth). Reliable CREAMS K and nbov values for this Irving clay had previously been determined from field rainulator data. In this study, CREAMS erodibility parameters were derived for the same soil type using laboratory rainfall simulator data. The values of these parameters fell within the 90% confidence region for parameters derived from non-rilled field rainulator plots. Both nbov and K, determined from laboratory data, varied with slope, indicating that the slope gradient response predicted by CREAMS may not be applicable for interrill erosion on short, steep slopes. For slopes < 8%, a default value of nbov = 0.01 with K = 0.37 (English units) gave good predictions of observed soil losses. However, for slopes > 8%, there was an over-prediction of observed soil loss up to 60% when these parameter values were used. The data indicate that for predictions of interrill soil loss from steeper slopes, nbov and K values should be adjusted to achieve greater accuracy. When values of K = 0.37 and nbov = 0.01 were used with field data obtained from a site with a slope of 4%, predicted interrill soil losses correlated well with both the estimated interrill component of measured field soil losses and observed soil losses from interrill field plots. It is concluded that the laboratory rainfall simulator used in this study produces hydrology and erosion data that can be used to derive realistic CREAMS parameters for interrill erosion.

Basin‐Scale Modeling as Tool for Water‐Resource Planning

A basin‐scale model was developed to simulate long‐term average losses of water, sediment, and nutrients from large rural watersheds. In addition to simulating diffuse sources using the Chemicals, Runoff, and Erosion from Agricultural Management Systems (CREAMS) model, the model incorporates point sources, nitrogen leaching from septic tanks, riparian and stream channel attenuation processes, and routing algorithms. When applied to a 73‐km2 basin in New Zealand, the model predicted a 14‐year annual average water yield of 740 mm, very close to the observed value of 738 mm. Predictions of long‐term average sediment and nutrient losses were generally within 30% of those estimated from data gathered for the basin outlet. Importantly, the model was able to predict well the direction and magnitude of changes in pollutant loss brought about by implementation of a riparian pasture retirement scheme, a popular best management practice in New Zealand. Model predictions of soluble nutrient losses were sensitive to variation in stream attenuation coefficients, and we conclude that further development of basin‐scale models will require a better understanding of riparian and stream‐channel processes.

Evaluation of Runoff and Erosion Models

Runoff and sediment yield for 30 runoff events on three experimental watersheds are calculated using the agricultural non–point-source pollution model (AGNPS), areal non–point-source watershed environmental response simulation (ANSWERS), and chemicals runoff and erosion from agricultural management systems (CREAMS) runoff-erossion models. The results are compared with measured runoff and sediment yield. The computed and measured runoffs show reasonable to poor agreement. The average ratios of computed to measured sediment yields for the various storms and watersheds show a large scatter. ANSWERS provides the most consistent results for estimates of runoff and sediment yield. All three models tend to underestimate sediment yield for large storms. For high intensity and low intensity storms on two small watersheds, the detachment models in ANSWERS and CREAMS have biases (ratio of calculated to measured sediment yields) that range between 0.9–1.0 and 0.4–1.6, respectively.

CREAMS Representation for Hydrology and Sedimentology of Central Illinois

ABSTRACT The CREAMS (Chemicals, Runoff, and Erosion from Agricultural Management Systems) model was evaluated for predicting runoff and sediment delivery from central Illinois fields without initial calibration. CREAMS was found to be fairly accurate in predicting cumulative annual runoff and sediment delivery. However, care should be exercised in selecting parameter values by using data that are as representative of the characteristics of the fields as are available. The violation of the assumption of applying CREAMS to fields having uniform characteristics, was not critical if weighted averages for parameter values were used in representing the variability of a field..

Validation of SWRRB—Simulator for Water Resources in Rural Basins

A model called SWRRB (simulator for water resources in rural basins) was developed for simulating hydrologic and related processes in rural basins. The SWRRB model was developed by modifying the CREAMS (chemicals, runoff, and erosion from agricultural management systems) daily rainfall hydrology model for application to large, complex, rural, basins. The three major components of SWRRB are weather, hydrology, and sedimentation. Processes considered include surface runoff, return flow, percolation, evapotranspiration, transmission losses, pond and reservoir storage, sedimentation, and crop growth. SWRRB has been tested on 11 large watersheds from eight Agricultural Research Service (ARS) locations throughout the United States. The results show SWRRB can realistically simulate water and sediment yields under a wide range of soils, climate, land‐use, topography, and management conditions. SWRRB should provide a versatile and convenient tool for use in planning and designing water resources projects.

Simulator for Water Resources in Rural Basins

A model called SWRRB (Simulator for Water Resources in Rural Basins) was developed for simulating hydrologic and related processes in rural basins. The objective in model development was to predict the effect of management decisions on water and sediment yields with reasonable accuracy for ungaged rural basins throughout the United States. The three major components of SWRRB are weather, hydrology, and sedimentation. Processes considered include surface runoff, percolation, return flow, evapotranspiration, pond and reservoir storage, and sedimentation. The SWRRB model was developed by modifying the CREAMS (Chemicals, Runoff, and Erosion from Agricultural Management Systems) daily rainfall hydrology model for application to large, complex, rural basins. The major changes were: (1) A return flow component was added; (2) the model was expanded to allow simultaneous computations on several sub‐basins; (3) a reservoir storage component was added for use in determining the effects of farm ponds and other reservoirs on water and sediment yield; (4) a weather simulation model (precipitation, solar radiation, and temperature) was added to provide for longer‐term simulations and more representative weather inputs, both temporally and spatially; (5) a better method was developed for predicting the peak runoff rate; and (6) a simple flood routing component was added. Besides water, SWRRB also simulates sediment yield using the Modified Universal Soil Loss Equation (MUSLE) and a sediment routing model. Tests with data from a 538km2 basin in Oklahoma and a 17.7km2 basin in Texas indicate that SWRRB is capable of simulating water and sediment yield realistically.

SIMULATION OF HERBICIDE CONCENTRATIONS IN STORMFLOW FROM FORESTED WATERSHEDS1

SummaryThe breakpoint rainfall hydrology and pesticide options of the field scale model CREAMS (Chemicals, Runoff, and Erosion from Agricultural Management Systems) were used to predict average concentrations of hexazinone [3 cyclohexyl‐6‐(dimethyl‐amino)‐1‐methyl‐1,3,5‐triazine‐2,4(1H,3H)‐dione] in stormflow from four forested watersheds in the upper Piedmont region of Georgia. Predicted concentrations were compared with measured concentrations recorded over a 13‐month period. CREAMS accurately predicted hexazinone concetrations in the initial stormflow events which also contained the highest concentrations. The model underestimated the hexazinone concentrations in stormflow two months and greater following pesticide application. In a companion study, the daily rainfall option of the CREAMS model was used to evaluate the reltive risk associated with the maximum expected concentration of hexazinone, bromacil (5‐bromo‐3 sec‐butyl‐6 methyuracil), picloram (4‐amino‐3,5,6 trichloropicolinic acid), dicamba (3,6‐dichloro‐0‐anisic acid), and triclopyr {[(3,5,6‐trichloro‐2‐pyridinyl)oxy] acetic acid} in stormflow from small forested watersheds. The model predicted the following order of potential residue appearance in stormflow: bromacil>triclopyr>hexazinone>picloram>dicamba. Subsurface movement of residues via interflow and deep leaching losses are not simulated by the version of CREAMS used in these studies.