Nonpoint Source Model Research Articles

Verification of Nutrient Transport Modelling of a Bison Feedlot

Runoff from an unpaved bison feedlot was measured for 2 yr. The objective were to determine a runoff curve number, develop a relationship between rainfall and runoff, and evaluate the equations in the Erosion–Productivity Impact Calculator (EPIC) and Agricultural Non-point Source (AGNPS) models for the prediction of runoff nutrient contents from a bison feedlot. A runoff curve number of 93 was determined using rainfall/runoff data. A simple regression equation was developed to estimate runoff as a linear function of rainfall. Organic-N and P were predicted with high correlation coefficients of 0·89 and 0·81, respectively. Results showed that use of EPIC and AGNPS model equations is a promising method for runoff quality/quantity estimation.

Watershed Environmental Hydrology Model: Environmental Module and Its Application to a California Watershed

A newly developed watershed environmental hydrology (WEHY) model is presented as a state-of-the-art nonpoint source (NPS) model. The model consists of hydrologic and environmental modules, and describes environmentally relevant hydrologic processes based upon physically based governing equations to model the fate of pollutants such as sediment and phosphorus in the watershed. Unlike other physically based NPS models, the WEHY model is unique in its upscaling approach to the governing equations of hydrologic and environmental processes, which results in the governing equations that are compatible with the computational grid resolution while accounting for subgrid heterogeneities through upscaled model parameters. Upscaling was performed by means of a technique called ensemble averaging. The model was tested at the Ward Creek Watershed in Lake Tahoe Basin for its performance in a subalpine watershed setting. Comparisons of predicted and observed values were in good agreement and showed good promise of the approach used in the development of the model. Because of the physical basis of the WEHY model and its use of upscaled conservation equations, the model has the advantage of being applicable to ungauged basins and to large watersheds.

Evaluation of AnnAGNPS in cold and temperate regions

Identification of the pollution sources and understanding the processes related to runoff generation and pollution transportation is effective for the water quality management and selection of the Best Management Practices. The ANNualized AGricultural Non-Point Source (AnnAGNPS) model was applied to a watershed in Southern Ontario to evaluate the hydrology and sediment component from the non-point sources. The model was run for two years (1998 to 1999); one year's data was used to calibrate and the second year's data was used for validation purposes. The model has under predicted runoff amount and over predicted the sediment yield. However, the simulated runoff and sediment yield compared fairly well with the observed data indicating that the model had an acceptable performance in simulation of runoff and sediment. The study is still in progress to assess its performance for estimation of TMDL and improvements needed for the model to use under Ontario conditions.

SUBSURFACE FLOW COMPONENT FOR ANNAGNPS

The Annualized Agricultural Non-Point Source Pollutant Loading (AnnANPSPL) model is a watershed scale,continuous simulation, daily time step model that is currently utilized in many locations of the United States by theEnvironmental Protection Agency, Natural Resources Conservation Service, and others to estimate the impact of bestmanagement practices on non-point source pollution. The model has many unique and powerful capabilities, but prior toAnnAGNPS version 2.2, subsurface lateral flow and subsurface drainage features were not available. Subsequently,subsurface lateral flow, including a subsurface drainage feature, was incorporated into AnnAGNPS and is described in thisarticle. Subsurface lateral flow was defined based on Darcys equation and subsurface drainage was determined usingHooghoudts equation. Users have several options available within AnnAGNPS to determine the impact of subsurfacedrainage based on the availability of information on the drainage system. Subsurface lateral flow and subsurface drainagewere assumed to occur only when the soil becomes saturated. As part of an inter-agency sedimentation project, the modelwith the subsurface enhancements was applied to the Ohio Upper Auglaize watershed non-point source modeling project toevaluate alternative agricultural management scenarios in reducing soil erosion and sediment loading within the watershed.The application illustrated the importance of including subsurface capabilities in watershed models by indicating thatsubsurface drainage systems within the watershed increased total runoff, but reduced direct surface runoff that, in turn,reduced soil erosion and sediment delivery from the watershed. Sediment loadings for drained conditions were less thanloadings for un-drained conditions in all simulated scenarios; and the sediment loadings for drained conditions were reducedby 7% to 16% compared with un-drained conditions. Furthermore, the model indicated that application of various areas ofno-till or grassland to the watershed could reduce the sediment loading transported from the watershed to a range of 39%to 82% of the existing condition.

Evaluation of annualized agricultural nonpoint source model for a watershed in the Siwalik Hills of Nepal

A study was undertaken to determine the predictive capability of Annualized Agricultural NonPoint Source (AnnAGNPS) model with respect to runoff volume, peak flows, and sediment yield from a 130.8 ha watershed in the Siwalik Hills of Nepal. AnnAGNPS simulations are compared with two years of field observations from the study watershed. The model predicted the runoff volume within the range of acceptable accuracy. The event-based peak flows were overpredicted by 105% with R 2 of 0.85 during calibration and 162% with R 2 of 0.77 during validation. Similarly, the model overpredicted the event-based sediment yield by 59% with R 2 of 0.63 during calibration and 92% with R 2 of 0.59 during validation. These results show that the model performs well in simulating runoff volumes compared to the peak flows and sediment yields. It is observed that there is a need to modify or improve the estimation methods of the peak flow and sediment yield to increase the performance of the model which can aid watershed management in local conditions.

Calibration and Validation of AnnAGNPS Model in a Watershed in Southern Ontario

Calibration and Validation of AnnAGNPS Model in a Watershed in Southern OntarioFor more than two decades, watershed based non-point source models have been recognized to be an effctive tool to identify the pollution sources and selection of the best management practices. The Annualized Agricultural Nonpoint Source model (AnnAGNPS) is one of those models and was calibrated and validated for Canagagigue watershed situated at the Grand River basin of Southern Ontario. The model...Author(s)S. DasR. P. RudraB. GharabaghiP. K GoelS. GebremskelN. GuptaSourceProceedings of the Water Environment FederationSubjectSession 3A: Modeling of Management PracticesDocument typeConference PaperPublisherWater Environment FederationPrint publication date Jan, 2005ISSN1938-6478SICI1938-6478(20050101)2005:3L.310;1-DOI10.2175/193864705783967205Volume / Issue2005 / 3Content sourceTMDLS ConferenceFirst / last page(s)310 - 322Copyright2005Word count216

Characterizing soil spatial variability with apparent soil electrical conductivity: I. Survey protocols

Spatial characterization of the variability of soil physico-chemical properties is a fundamental element of (i) soil quality assessment, (ii) modeling non-point source pollutants in soil, and (iii) site-specific crop management. Apparent soil electrical conductivity (EC a) is a quick, reliable measurement that is frequently used for the spatio-temporal characterization of edaphic (e.g., salinity, water content, texture, and bulk density) and anthropogenic (e.g., leaching fraction) properties. It is the objective of this paper to provide the protocols for conducting a field-scale EC a survey (Part I) and apply these protocols to a soil quality assessment in central California's San Joaquin Valley (Part II). The protocols are comprised of eight general steps: (i) site description and EC a survey design; (ii) EC a data collection with mobile GPS-based equipment; (iii) soil sampling design; (iv) soil core sampling; (v) laboratory analysis; (vi) calibration of EC a to EC e; (vii) spatial statistical analysis; (viii) GIS database development and graphic display. For each outlined step, detailed discussion and guidelines were presented. The developed protocols provide the guidelines to assure reliability, consistency, and compatibility of EC a survey measurements and their interpretation.

Validation of agricultural non-point source (AGNPS) pollution model in Kori watershed, South Wollo, Ethiopia

Soil erosion is a major problem on the Ethiopian highlands. The poor soil management and land use practices are the causes of high soil erosion rate. Despite the extensive soil and water conservation programs launched by the Government of Ethiopia throughout the country, the achievements are far from satisfactory. One of the reasons was the inappropriate method used for assessment of soil erosion processes.This study was conducted to test and validate the agricultural non-point source (AGNPS) model in Kori gauged-watershed, South Wollo zone. Primary and secondary data collection methods were used to derive the spatial and attribute data. The primary data collection involved field survey. The soil conservation research project (SCRP) has collected hydrology and soil erosion data in the catchment since 1981. Some of the input parameters were also determined from digitized slope map using GIS.Ten rainfall events from 1989 and 1993 were used to calibrate the model. Sensitivity analysis conducted on the AGNPS model showed that curve number (CN) and universal soil loss equation (USLE) C factor were the most sensitive parameters and were subjected to calibration.The model calibration resulted in model efficiencies of 0.73, 0.53 and 0.90 for surface runoff, peak runoff rate, and sediment yield, respectively. The correlation coefficients were 0.87, 0.81 and 0.99, respectively, all significant at p≤0.01. Eight rainfall events from 1992 were used to validate the model. Validation results produced model efficiencies of 0.86, 0.65 and 0.88 for surface runoff, peak runoff rate and sediment yield, respectively. Surface runoff and peak flow simulations were improved in the validation stage. The corresponding correlation coefficients were 0.94, 0.90 and 0.98, all significant at p≤0.01, which showed the high linear correlation between measured and predicted values. It can be concluded that the AGNPS model is a useful prediction tool for understanding erosion processes on the Ethiopian highlands and for locating and targeting specific areas within the watershed that have high potential for soil loss, thus helping the conservation planner to design conservation plans.

Assessment of Agricultural NonPoint Source Model for a Watershed in Tropical Environment

Very little work on the application of watershed modeling has been done in the tropical climatic conditions of Thailand to explore the nature of environmental problems arising from nonpoint source pollution due to agricultural activities, and to evaluate possible remedial measures and strategies. The present study attempts to verify the suitability of a nonpoint source pollution model, the Agricultural NonPoint Source model, for the Huai Nong Prong watershed in Southeastern Thailand. Extensive fieldwork was carried out to collect data and information needed for the model preparation and application. The study has revealed that simulated runoff volume, sediment, and nutrient yield from the watershed with mixed land use and relatively high slopes match favorably with observed data. For the ten rainfall events simulated, the coefficient of performance, a measure of model efficiency (equal to zero for a perfect match), was 0.09, 0.47, 0.09, and 0.03 for runoff volume, sediment yield, total nitrogen, and total phosphorus, respectively. The model, however, could not accurately simulate peak flow rates, suggesting the need for changes in the modeling approach or governing equations and relationships to calculate peak discharges in a tropical environment.

Physically-based hydrological modelling for non-point dissolved phosphorus transport in small and medium-sized river basins / Modélisation hydrologique à bases physiques et du transport de phosphore dissous diffus en bassins versants de petite et moyenne tailles

Current research suggests that strategies to control sediment and phosphorus loss from non-point sources should focus on different runoff components and their spatial and temporal variations within the river basin. This is a prerequisite for determining effective management measures for reducing diffuse source pollution. Therefore, non-point source models, especially in humid climatic regions, should consider variable hydrologically active source areas. These models should be able to consider runoff generation by saturated overland flow, as well as Hortonian overland flow. A combination of the hydrological model WaSiM-ETH and the erosion and P-transport model AGNPS was chosen for this study. The models were run in the WaSiM runoff generation mode (Green & Ampt/TOPMODEL or Richards equation approach) and the SCS curve number mode to assess the effect of these different runoff calculation procedures on the dissolved phosphorus yield. A small and a medium-sized river basin, of the area of 1.44 and 128.9 km2, respectively, in central Germany were selected for the investigation. The results show that the WaSiM–AGNPS coupling produces more accurate results than the SCS curve number method. For the spatial distribution, the more physically-based model approach computed a much more realistic distribution of water and phosphorus yield-producing areas.

PeLM: Modeling of Pesticide-Losses Through Runoff and Sediment Transport

A GIS-aided pesticide loss model (PeLM) was developed to simulate pesticide losses through surface runoff and sediment transport in watershed systems. The PeLM could tackle the movement of eroded soil along with surface runoff as well as the pesticide losses in adsorbed and dissolved phases. The contributions of different soil types in the sediment were also examined. The model was applied to the Kintore Creek Watershed of southern Ontario, Canada. The simulation results were verified through observed data, indicating a correlation level of 0.89–0.98. The results also showed that clay particles usually held the largest share of contributions to pesticide losses through soil erosion. This study is significant in the efforts for modeling nonpoint source pollution in watershed systems. It provides useful information and support for the related decisions of watershed management.

PeLM: Modeling of Pesticide-Losses Through Runoff and Sediment Transport

Abstract A GIS-aided pesticide loss model (PeLM) was developed to simulate pesticide losses through surface runoff and sediment transport in watershed systems. The PeLM could tackle the movement of eroded soil along with surface runoff as well as the pesticide losses in adsorbed and dissolved phases. The contributions of different soil types in the sediment were also examined. The model was applied to the Kintore Creek Watershed of southern Ontario, Canada. The simulation results were verified through observed data, indicating a correlation level of 0.89–0.98. The results also showed that clay particles usually held the largest share of contributions to pesticide losses through soil erosion. This study is significant in the efforts for modeling nonpoint source pollution in watershed systems. It provides useful information and support for the related decisions of watershed management.

MODELING MINERAL NITROGEN EXPORT FROM A FOREST TERRESTRIAL ECOSYSTEM TO STREAMS

Terrestrial ecosystems are major sources of N pollution to aquatic ecosystems. Predicting N export to streams is a critical goal of nonpoint-source modeling. This study was conducted to assess the effect of terrestrial N cycling on stream N export using long-term monitoring data from Hubbard Brook Experimental Forest (HBEF) in New Hampshire. The field- scale DAYCENT model was used to quantify N pools and long-term annual streamflow and mineral N export for six subwatersheds at the HBEF. By combining DAYCENT with the Soil and Water Assessment Tool (SWAT) watershed model, mineral N export simulations were extended to the watershed scale. Our study indicated that only 13% of external N input was exported to streams during 1951-2000 at HBEF. As much as 4763 kg/ha of N was stored in forest litter, soil organic matter (SOM), and living plant biomass. Net N mineralization of SOM and forest litter contributed 93% of total available N for export within the HBEF ecosystem. The Nash-Sutcliffe coefficient (Ens) evaluating model performance of DAYCENT at six subwatersheds ranged from 0.72 to 0.82 for simulating annual streamflow (1964-2000) and from 0.48 to 0.67 for annual mineral N export (1971-1995), indicating reasonable simulated values. DAYCENT successfully predicted the effect of ecosystem disturbance such as forest cut and insect invasion on stream mineral N export. The watershed-scale simulation suggested that soil spatial variability affects stream N export in addition to the accepted controls of land cover, external N input, climate, and ecosystem disturbance.

FARM–LEVEL OPTIMIZATION OF BMP PLACEMENT FOR COST–EFFECTIVE POLLUTION REDUCTION

With best management practices (BMPs) being used increasingly to control agricultural pollutant losses to surfacewaters, establishing the environmental effectiveness of these practices has become important. Additionally, cost implicationsof establishing and maintaining environmentally effective BMPs are often a crucial factor in selecting and adopting BMPs.This article considers both water quality and economic concerns and presents a methodology developed for determining costeffectivefarm- or watershed-level scenarios through optimization. This optimization technique uniquely incorporates threeexisting tools: a genetic algorithm (GA), a watershed-level nonpoint-source model (Soil and Water Assessment Tool, SWAT),and a BMP tool. The GA combines initial pollutant loadings from SWAT with literature-based pollution reduction efficienciesfrom the BMP tool and with BMP costs to determine cost-effective watershed scenarios. The methodology was successfullyapplied to a 300 ha farm within the Cannonsville Reservoir watershed, a phosphorus (P) restricted reservoir within New YorkCitys water supply system. An average reduction in dissolved P of 60% over the lifetime of the BMPs was set as the pollutanttarget. A baseline scenario was established to represent practices on the farm before BMP implementation. The most costeffectivescenario for the farm, under the presented methodology, achieved a cost-effectiveness of 0.6 kg dissolved P reductionper dollar spent per year. Additionally, the methodology determined alternative scenarios for the farm, which met the pollutionreduction criterion cost-effectively. The methodology, as developed, is extendable to multi-farm or watershed-level evaluations.

Validation of an agricultural non-point source model in a watershed in southern Ontario

As part of an integrated watershed management study for watersheds of southern Ontario, the agricultural non-point source (AGNPS) model was interfaced with a decision support system that reduces the time-consuming data input steps and scenario testing. The objectives of this study were to define appropriate model input parameters for the region and to define a protocol for model validation at the sub-watershed and watershed scale. The model provided realistic estimates of nutrient loads in run-off water for a wide range of storm events. For tested grid sizes, both the peak flows and historic run-off values were well reproduced by the AGNPS model. High coefficient of efficiency (CE) values of 0.821–0.919 for peak flows and of 0.713 for run-off volumes were obtained. The CE values for nutrient loads are extremely high: 0.990 for nitrogen and 0.965 for phosphorus. These results show that the model is well suited to applications in southern Ontario, and with the described interface, should be a useful tool for watershed management by conservation authorities in the region.

WATERSHED OPTIMIZATION OF AGRICULTURAL BEST MANAGEMENT PRACTICES: CONTINUOUS SIMULATION VERSUS DESIGN STORMS1

ABSTRACT: Nonpoint source (NPS) models and expert opinions are often used to prescribe best management practices (BMPs) for controlling NPS pollution. An optimization algorithm (e.g., a genetic algorithm, or GA) linked with a NPS model (e.g., Annualized AGricultural Nonpoint Source pollution model, or AnnAGNPS), can be used to more objectively prescribe BMPs and to optimize NPS pollution control measures by maximizing pollutant reduction and net monetary return from a watershed. Pollutant loads from design storms and annual loads from a continuous simulation can both be used for optimizing BMP schemes. However, which strategy results in a better solution (in terms of providing water quality protection) for a watershed is not clear. The specific objective of the study was to determine the differences in watershed pollutant loads, in an experimental watershed in Pennsylvania, resulting from optimization analyses performed using pollutant loads from a series of five 2‐yr 24‐hr storm events, a series of five 5‐yr 24‐hr storm events, and cumulative pollutant loads from a continuous simulation of five years of weather data. For each of these three different event alternatives, 100 near optimal solutions (BMP schemes) were generated. Sediment (Sed), sediment nitrogen (SedN), dissolved N (SolN), sediment organic carbon (SedOC), and sediment phosphorus (SedP) loads from a different five‐year period (an evaluation period) suggest that the optimal BMP schemes resulting from the use of annual cumulative pollutant loads from a continuous simulation of five years of weather data provide smaller cumulative NPS pollutant loads at the watershed outlet.

Water quality modeling of the Cahaba River, Alabama

The Cahaba River, a sixth-order stream, tributary to the Mobile-Alabama River, is one of the few free-flowing rivers in Alabama. The Cahaba River lies in north-central Alabama and its watershed includes a variety of land uses from forested and agricultural to urban. Water quantity and quality modeling of the Cahaba River using several modules of the hydrologic simulation program FORTRAN (HSPF) and the nonpoint source model (NPSM) using the GIS-based BASINS package showed good agreement with measured flow data for low- and high-flow years but poor agreement with total nitrogen concentrations in the water column. Disparities between modeling and measured water quality data are attributed to the limited point source data available for nitrogen inputs to the stream and the lack of nitrogen-transformation process modeling with the NPSM. Future simulations should include use of models with detailed nitrogen transformation modules.

Modelling nutrient transport in Currency Creek, NSW with AnnAGNPS and PEST

The modelling package Annualized Agricultural Nonpoint Source Model (AnnAGNPS) was applied to the prediction of export of nitrogen and phosphorus from Currency Creek, a small experimental catchment within the Hawkesbury–Nepean drainage basin of the Sydney Region. The catchment is 255 ha in area and has experienced extensive soil erosion and losses of nutrients from intensive vegetable cultivation, irrigated dairy pasture and poultry farms. Simulations of nitrogen and phosphorus loads in the Currency Creek catchment were performed at various temporal scales and the degree of calibration was quantified by comparing the simulated data with the monitoring results. In addition, the model independent, nonlinear parameter estimation code PEST, was applied for sensitivity testing to determine and assess the relative importance of the key parameters of the model. Event flows were simulated satisfactorily with AnnAGNPS but only moderate accuracy was achieved for prediction of event-based nitrogen and phosphorus exports. The biggest deviations from the measured data were observed for daily simulations but trends in the generated nutrients matched observed data. Despite achieving good resemblance between measured and predicted phosphorus loads the model showed high level of sensitivity to assigned pH values for topsoil. Increase in pH by one unit resulted in up to 34% increase in model generated particulate phosphorus load.

The use of earth observation techniques to improve catchment-scale pollution predictions

Remote sensing can potentially provide information useful in improving pollution transport modelling in agricultural catchments. Realisation of this potential will depend on the availability of the raw data, development of information extraction techniques, and the impact of the assimilation of the derived information into models. High spatial resolution hyperspectral imagery of a farm near Hereford, UK is analysed. A technique is described to automatically identify the soil and vegetation endmembers within a field, enabling vegetation fractional cover estimation. The aerially-acquired laser altimetry is used to produce digital elevation models of the site. At the subfield scale the hypothesis that higher resolution topography will make a substantial difference to contaminant transport is tested using the AGricultural Non-Point Source (AGNPS) model. Slope aspect and direction information are extracted from the topography at different resolutions to study the effects on soil erosion, deposition, runoff and nutrient losses. Field-scale models are often used to model drainage water, nitrate and runoff/sediment loss, but the demanding input data requirements make scaling up to catchment level difficult. By determining the input range of spatial variables gathered from EO data, and comparing the response of models to the range of variation measured, the critical model inputs can be identified. Response surfaces to variation in these inputs constrain uncertainty in model predictions and are presented. Although optical earth observation analysis can provide fractional vegetation cover, cloud cover and semi-random weather patterns can hinder data acquisition in Northern Europe. A Spring and Autumn cloud cover analysis is carried out over seven UK sites close to agricultural districts, using historic satellite image metadata, climate modelling and historic ground weather observations. Results are assessed in terms of probability of acquisition probability and implications for future earth observation missions.

IMPACT OF CALIBRATION WATERSHED ON RUNOFF MODEL ACCURACY

Hydrologic/waterquality models often need calibration to minimize differences between observed and predictedwatershed responses. Often the measured data from the watershed where the models are applied are not available. Under thiscondition, models are calibrated using data from a different watershed having similar land use, soil, and hydrologicconditions. However, if the watershed used for model calibration is not the same as the watershed where the model is appliedfor hydrologic/waterquality predictions, then differences in watershed characteristics may induce errors in model output.The objective of this study was to quantify the error in model predictions when the modeled watershed is not the calibratingwatershed. The Agricultural NonPoint Source (AGNPS) model was used to quantify model errors using measured data fromwatersheds of varying sizes within the Little Washita Basin in Oklahoma. The study indicates that error in model outputsresults when a watershed different than the one of interest is used for model calibration. A significant difference in predictionerror was observed between scalingup and scalingdown conditions with mean relative error of runoff prediction being153% for the scalingdown condition and 69% for the scalingup condition. However, relative error of prediction showedno particular trend with the scaling ratios. A watershed having significantly higher or lower average curve number and slopecondition was not a candidate watershed for calibrating the AGNPS model.