Agricultural Non-Point Source Model Research Articles

Introducing QAnnAGNPS - A QGIS plugin to facilitate the use of AnnAGNPS (Annualized Agricultural Nonpoint source model)

AnnAGNPS is a watershed-scale hydrological model designed to analyze the impact of nonpoint source pollution in agricultural environments. Its unique capabilities have defined it as an essential model that is used globally to evaluate agricultural management scenarios. However, it does not currently have a user-friendly graphical interface that provides a simple way for users to perform simulations. This article presents QAnnAGNPS, a plugin developed in QGIS to facilitate access to the simulation capabilities of AnnAGNPS through a user-friendly interface and the addition of extra features, including data visualization. QAnnAGNPS, in addition to fulfilling this valuable task, opens the door to the incorporation of additional functions already included in other similar hydrological models. The plugin has been tested in the Latxaga cereal basin in Navarra, Spain, and has demonstrated that it provides a simpler way to perform simulations and visualize results compared to AnnAGNPS.

Effectiveness and resilience of BMPs to watershed climate adaptation considering the uncertainty of hydrological model and GCMs

Climate change significantly impacts catchment hydrologic and water quality processes. Best management practices (BMPs) can serve as adaptation strategies to negate the impact of climate change on sediment and total nitrogen (TN) loads. One major controversial issue in climate change adaptation studies is the highly uncertain nature of such changes. Previous studies have rarely focused on the combined impact of the uncertainty in climate change and watershed model parameters, which could be the main sources of uncertainty in climate change adaptation research. In this study, the effectiveness and resilience (defined as continued effectiveness under a changing climate) of BMPs in reducing sediment and TN loads were explored under future climate change in the Shanmei Reservoir watershed (SMW) of Southeast China. Climate change projections provided by 10 general circulation models (GCMs) under the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios from 2031 to 2060 were applied in the Annualized Agricultural Nonpoint Source (AnnAGNPS) model to evaluate the effectiveness and resilience of 4 BMPs (riparian buffers (RB), no-tillage (NT), fertilization reduction (FR), and parallel terraces (PT)). The ensemble average of 10 GCMs and 10 behavior parameter groups were adopted to reduce the uncertainty resulting from the hydrological model parameters and GCMs. The results indicated that the average annual temperature and precipitation in the SMW will increase in the future. On a seasonal scale, the average temperature during all seasons will increase, and precipitation will decrease in summer and autumn but increase in spring and winter. The annual sediment and TN loads will decrease, but the loads in spring and winter will increase. BMPs could be effective as climate adaptation strategies for reducing sediment and TN loads under future climate conditions, with PT as the most effective option. Structural BMPs were more effective in reducing sediment and TN loads in spring and winter, whereas nonstructural BMPs were more effective in reducing loads in summer and autumn. BMPs were more resilient when future watershed runoff changes were slight or climate sensitivity was reduced, with higher BMP resilience in spring and winter than in summer and autumn. This study aimed to provide systematic references for watersheds through the implementation of BMPs for mitigating the effects of climate change and extending the boundaries of the AnnAGNPS model application.

Deriving Land Management Practices for Reduced Nutrient Movement from an Agricultural Watershed Using the AGNPS Model

The effect of nutrient management practices and the land-use system on nutrient enrichment in water resources of a hilly watershed was assessed with an event-based agricultural non-point source (AGNPS) model. The model intended to assess the runoff, sediment and nutrient loads in a typical hilly agricultural watershed. The model was calibrated, evaluated and applied in integration with GIS to predict the soil and nutrient loss. Two nutrient management scenarios were simulated with 25 and 50% reductions in the nutrient application from the present nutrient application. The third scenario was simulated by converting 25% of the agricultural land-use to tea plantations. A total of 15 simulations were run for the different rainfall intensities of the year 2017. The existing land-use scenario simulated the maximum soil loss and Nitrogen and phosphorus load of 8.23 t ha−1, 22.8 and 5.0 kg ha−1. The 50% nutrient reduction scenario reduced 48 and 36% of the Nitrogen and phosphorus load compared to the existing farmers’ practice. The same nutrient dose was compared with the STCR equation, developed for major crops such as potato and carrot in Nilgiris soil, and confirmed the sufficient nutrient supply to produce a sustainable yield. The conversion of 25% of the agricultural land-use to tea plantations reduced the soil loss by 10% from the current land-use. The Nitrogen and phosphorus load was reduced to 56 and 48%, respectively. Hence, the farmers may convert 25% of the land area to tea plantations and reduce 50% of the present fertilizer dose for the major vegetable crops with INM to reduce the nutrient enrichment in the surface water bodies. This study demonstrated the applicability of the AGNPS model in similar watersheds for deriving possible management strategies to reduce soil loss and nutrient movement. Further, the hydrological models can provide valuable insights for promptly prioritizing and making policy decisions in ungauged/data-scarce watersheds.

Analysis of the Development Trend in Agriculture Non-point Source Pollution Based on CiteSpace

This paper uses CiteSpace to visualize and analyze the literature related to agricultural non-point source pollution in China Knowledge Network (CNKI) from 1993~2022. The results showed that the research on agricultural non-point source pollution has gone through three stages: the beginning (1993~2006), booming development (2007~2011), and stable development (2011-2022). The research on agricultural non-point source pollution focuses mainly on agricultural non-point source pollution, pollution control, and model simulation. Agricultural non-point source pollution has always played a leading role in the development of the research field since the research until now, and model simulation and spatial distribution have been continuously cited from the emergence of clustering until now, and are widely available in the research field.

Empirical tool development for prairie pothole management using AnnAGNPS and random forest

Watershed models are robust tools that inform management and policy in a variety of sectors, but these models are often neglected through time due to economic or technical constraints. Additionally, they are not readily accessible tools for key decision makers. Conversely, machine learning models are robust alternatives to common hydrologic modeling frameworks. The random forest algorithm specifically is an interpretable predictive tool. We couple Annualized Agricultural Non-Point Source (AnnAGNPS) model output, an abstract, anthropogenic flood risk metric, and develop a random forest model to provide an empirical tool that benefits decision makers in the Des Moines Lobe of the Prairie Pothole Region in north-central Iowa. The developed model has the capacity to predict our flood risk metric (calibration: R2 > 0.9, validation: R2 > 0.7) for individual farmed prairie potholes across a variety of morphologic and management conditions and can be used iteratively to assess alternative actions.

Riparian Zone Nitrogen Management through the Development of the Riparian Ecosystem Management Model (REMM) in a Formerly Glaciated Watershed of the US Northeast

The Riparian Ecosystem Management Model (REMM) was developed, calibrated and validated for both hydrologic and water quality data for eight riparian buffers located in a formerly glaciated watershed (upper Pawcatuck River Watershed, Rhode Island) of the US Northeast. The Annualized AGricultural Non-Point Source model (AnnAGNPS) was used to predict the runoff and sediment loading to the riparian buffer. Overall, results showed REMM simulated water table depths (WTDs) and groundwater NO3-N concentrations at the stream edge (Zone 1) in good agreement with measured values. The model evaluation statistics showed that, hydrologically REMM performed better for site 1, site 4, and site 8 among the eight buffers, whereas REMM simulated better groundwater NO3-N concentrations in the case of site 1, site 5, and site 7 when compared to the other five sites. The interquartile range of mean absolute error for WTDs was 3.5 cm for both the calibration and validation periods. In the case of NO3-N concentrations prediction, the interquartile range of the root mean square error was 0.25 mg/L and 0.69 mg/L for the calibration and validation periods, respectively, whereas the interquartile range of d for NO3-N concentrations was 0.20 and 0.48 for the calibration and validation period, respectively. Moreover, REMM estimation of % N-removal from Zone 3 to Zone 1 was 19.7%, and 19.8% of N against actual measured 19.1%, and 26.6% of N at site 7 and site 8, respectively. The sensitivity analyses showed that changes in the volumetric water content between field capacity and saturation (soil porosity) were driving water table and denitrification.

Characterization of prairie pothole inundation using AnnAGNPS under varying management and drainage scenarios

Farmed prairie potholes are small, isolated depressions frequently classified as semi-permanent wetlands that make up a significant portion of land area in the Des Moines Lobe (DML) of the larger Prairie Pothole Region (PPR). Historically, these depressions have been subjected to significant drainage to improve their agricultural capacity. However, many assessments of the economic return of continuing to farm these depressions suggest that continued attempts to produce conventional row crops is not profitable and has other ecological consequences beyond crop drownout. This study expands the existing discussion of land use and drainage alternatives in a watershed modeling context. This study utilized the Annualized Agricultural Non-Point Source (AnnAGNPS) model to individually simulate the long-term hydrology of 6 prairie potholes using a matrix of land use and drainage modifications. Results suggest the presence of artificial drainage is the dominant factor in prairie pothole hydrology, while retirement and no-till practices can provide moderate reductions in flood inundation. Conservation tillage induces minimal change on flood metrics. Results show that average annual maximum inundated surface area is reduced by at most 50% across all simulations and the median annual days flooded could be reduced by 25 days, though this is less consistent when isolating high-precipitation years. Regardless of drainage status, in all scenarios there are, on average, more than two inundations events per year lasting 2–4 days. Longer events occur approximately once per year on average. Area inundation frequency curves suggest up to a 20% reduction in maximum pothole area inundated annually can be achieved at the 2-year return frequency. The availability of this data helps characterize the hydrology of farmed potholes more generally over a wide range of conditions, providing a reference for the prioritization of potholes for conservation or alternative management.

Assessment of Input Parameters and Calibration Methods for Simulating Prairie Pothole Hydrology using AnnAGNPS

HighlightsModel equifinality incurs user-driven decisions when modeling with AnnAGNPS.Prairie pothole models should be calibrated using a limited parameter search space.LiDAR-derived surface areas best represent prairie pothole hydrology in AnnAGNPS.Modeling field-scale prairie pothole spill-and-fill dynamics is currently limited.Abstract. The Annualized Agricultural Non-Point Source (AnnAGNPS) model was used to predict water volume in individual prairie potholes within the Des Moines Lobe of Iowa. AnnAGNPS can represent prairie potholes as static wetland areas located on preferential flow paths at field scale, whereas standard practice of watershed modeling is to fill depressions while preparing input data, and whereas models have lumped parameters at scales too large for individual pothole representation, or are considered too complex for widespread implementation. Here, we assess how key user inputs affect hydrologic calibration of 6 AnnAGNPS prairie pothole models, suggest methods for calibrating and modeling the impact of some potholes at field scale, and explain challenges in modeling prairie potholes with AnnAGNPS. Results indicate that user-defined pothole surface area does not significantly affect statistical calibration of the model. Nash-Sutcliffe Efficiency 0.26 to 0.79, R2 ranged from 0.37 to 0.80 and RSR ranged from 0.46 to 0.86. The area that best simulates pothole hydrology and expected physical parameters is derived from LiDAR and is considered the maximum extent of the pothole. Potholes were calibrated using a stepwise, iterative, limited search space method using multiple representations of their inundation extent. We graphically assessed statistical parameters to identify calibrated models and chose input parameters within reasonable ranges of published literature. This helped formulate our recommendation for the modeled pothole area. Finally, AnnAGNPS is limited in its ability to simulate field-scale pothole networks due to the placement of potholes within the model’s subbasin network. Investigating high-resolution subbasin delineation or more specific wetland placement may alleviate this issue. Keywords: AnnAGNPS, Farmed wetlands, Hydrology, Prairie potholes, Prairie pothole region.

Using AnnAGNPS to Simulate Runoff, Nutrient, and Sediment Loads in an Agricultural Catchment with an On-Farm Water Storage System

On-farm water storage (OFWS) systems are best management practices that consist of a tailwater recovery (TWR) ditch used with a storage pond to provide irrigation water and improve downstream water quality. These systems have been increasingly implemented in the southeastern US, but the individual and cumulative effects of these systems on a watershed scale are unknown. In this study, the runoff, nutrient, and sediment loads entering a TWR ditch in an agricultural catchment were quantified, and contributing sources were identified using the annualized agricultural non-point source (AnnAGNPS) model. Fields with larger areas and soils with a high runoff potential produced more runoff. The volume of runoff exceeded the TWR ditch storage volume approximately 110 times, mostly during the winter and spring seasons. During years when corn and winter wheat were planted, NO3–N loads increased because these crops need nitrogen fertilization to grow. Planting winter wheat in priority subwatersheds reduced the total phosphorous (TP) and sediment loads by about 19% and 13%, respectively, at the TWR ditch inlet. Planting winter wheat can reduce runoff, TP, and sediment loads but also result in higher NO3–N loads. AnnAGNPS simulations quantified the benefits of an OFWS system to advance the understanding of their impact on water availability and quality at a watershed scale.

Identifying threshold storm events and quantifying potential impacts of climate change on sediment yield in a small upland agricultural watershed of Ontario

AbstractAgricultural zones are significant sediment sources, but it is crucial to identify critical source areas (CSAs) of sediment yield within these zones where best management practices (BMPs) can be applied to the best effect in reducing sediment delivery to receiving water bodies rather than the economically nonviable alternative of randomly or sweepingly implementing BMPs. A storm event of a specific magnitude and hyetograph profile may, at different times, generate a greater or lesser sediment yield. The widely used agricultural nonpoint source (AGNPS) model was used to identify CSAs for sediment losses in Southwestern Ontario's agriculture‐dominated 374‐ha Holtby watershed. A storm threshold approach was adopted to identify critical periods for higher sediment losses. An AGNPS model for the Holtby watershed was set up, calibrated, and validated for run‐off volume, peak flow rate, and sediment yield for several storms. The calibrated and validated model was run for storms of increasing return periods to identify threshold storm events that would generate sediment yield greater than an acceptable value for early and late spring, summer, and fall seasons. Finally, to evaluate the potential impacts of climate change, we shifted shorter duration summer storms into spring conditions and quantified the changes in sediment yield dynamics. A 6‐hr, 7.5‐year early spring storm would generate sediment losses exceeding the acceptable limit of 0.34 t ha−1 for the season. However, summer storms (2 hr, up to 100 years) tended to generate sediment yields below those of an identifiable threshold storm. If such shorter duration summer storms occurred in spring, the sediment yield would increase by more than fivefold. A 5‐year future storm would generate an equivalent effect of a 100‐year current spring event. The high sediment delivery to be expected will have significant implications regarding the future management of water quality of receiving waters. Appropriate placement of BMPs at CSAs will thus be needed to reduce such high sediment delivery to receiving waters.

The reduction effects of riparian reforestation on runoff and nutrient export based on AnnAGNPS model in a small typical watershed, China.

The continuous deterioration of the aquatic environment in rivers and streams is increasingly causing social and political tensions. To alleviate aquatic environmental problems, especially for the nonpoint source pollution, establishment of riparian forest buffers has been demonstrated as an effective control measure. However, few comprehensive studies of the reduction effects of riparian reforestation on the aquatic environment have been performed, particularly in identifying the suitable widths of reforestation projects. In this paper, the Annualized Agricultural Non-Point Source (AnnAGNPS) model was used to simulate the reduction effects of riparian reforestation on runoff and nutrient loads in Wucun watershed, China. The results showed that 20-m, 40-m, and 60-m widths of riparian buffer reforestation had significant effects on the yearly loads of total nitrogen (TN) and total phosphorus (TP), with reduced rates of 23.21 to 56.2% and 18.16 to 52.14%, respectively. The reduction effect on annual runoff varied from 2.8 to 5.4%. Furthermore, the reduction effect of nutrients performed best during the transition period, while the best runoff reduction was found during the dry period. These distinct reductions indicated that the implementation of riparian forest buffers was capable of reducing the risk and frequency of flooding and eutrophication, especially during the wet and transition periods. Additionally, the 20-m width of riparian buffer reforestation achieved the highest reduction efficiency for runoff, and the 40-m width was the most suitable reforested riparian buffer width for TN and TP. Therefore, 40m may be the optimum buffer width for the implementation of riparian reforestation in the Wucun watershed. These research results provided scientific information on selecting the optimum buffer width for aquatic environmental regulators and managers as the reduction effects of different widths of riparian buffers on runoff and nutrients were different when considering buffer reforestation.

A Modeling Approach for Evaluating Watershed-scale Water Quality Benefits of Vegetative Filter Strip - A Case Study in Ontario

Abstract. Vegetative filter strips (VFS) are globally recognized as an effective BMP in reducing non-point source pollution. Maximum effectiveness of a VFS at a watershed-level could be achieved by adequately installing and sizing a VFS along the edge of the field. Existing watershed models have limitations in appropriately representing and modeling VFS at the watershed scale. Therefore, in this research, a new modeling approach consisting of the Agricultural Non-Point Source (AGNPS) model, AGNPS_VFS toolkit, and a regression equation is developed to explore the effectiveness of VFS applied along the edge of fields. AGNPS cells are identified as locations where the edge of the field VFS is to be installed. Further, the approach was tested with a case study. The model was calibrated and validated for a flow and sediment load at the watershed outlet. Thereafter, the modeling approach is used to compute sediment reducing efficiency (SRE) for the edge of the field VFS. Objectives of this study were to test the effectiveness of uniform VFS (5 × 18 m) lengths located at several locations (draining an upstream area of 3, 4, 6 ha, and at spatially variable locations) within a watershed to demonstrate the ability of the developed approach to evaluate effectiveness of VFS application in sediment abatement. Maximum SRE was observed for VFS placed at spatially variable locations; the developed approach reduced nearly 23.03% of sediment yield, while VFS placed along cells draining an upstream area of 3, 4, and 6 ha removed 9.59%, 12.39%, and 5.91% of sediment loads respectively. Keywords: Non-point source pollution, Sediment transport, Vegetative filter strip (VFS), VFSMOD.

Evaluation of Alternative Management Practices With the AnnAGNPS Model in the Carapelle Watershed

AbstractThe Annualized Agricultural Non-point Source (AnnAGNPS) model can be used to analyze the effects of management practices on sediment loads in agricultural watersheds. The study was performed in a 506 km2 Mediterranean watershed located in Apulia, Southern Italy, planted with mostly winter wh

Evaluation of the AnnAGNPS Model for Predicting Runoff and Nutrient Export in a Typical Small Watershed in the Hilly Region of Taihu Lake.

The application of hydrological and water quality models is an efficient approach to better understand the processes of environmental deterioration. This study evaluated the ability of the Annualized Agricultural Non-Point Source (AnnAGNPS) model to predict runoff, total nitrogen (TN) and total phosphorus (TP) loading in a typical small watershed of a hilly region near Taihu Lake, China. Runoff was calibrated and validated at both an annual and monthly scale, and parameter sensitivity analysis was performed for TN and TP before the two water quality components were calibrated. The results showed that the model satisfactorily simulated runoff at annual and monthly scales, both during calibration and validation processes. Additionally, results of parameter sensitivity analysis showed that the parameters Fertilizer rate, Fertilizer organic, Canopy cover and Fertilizer inorganic were more sensitive to TN output. In terms of TP, the parameters Residue mass ratio, Fertilizer rate, Fertilizer inorganic and Canopy cover were the most sensitive. Based on these sensitive parameters, calibration was performed. TN loading produced satisfactory results for both the calibration and validation processes, whereas the performance of TP loading was slightly poor. The simulation results showed that AnnAGNPS has the potential to be used as a valuable tool for the planning and management of watersheds.

Using AnnAGNPS to Predict the Effects of Tile Drainage Control on Nutrient and Sediment Loads for a River Basin.

Controlled tile drainage (CTD) can reduce pollutant loading. The Annualized Agricultural Nonpoint Source model (AnnAGNPS version 5.2) was used to examine changes in growing season discharge, sediment, nitrogen, and phosphorus loads due to CTD for a ∼3900-km agriculturally dominated river basin in Ontario, Canada. Two tile drain depth scenarios were examined in detail to mimic tile drainage control for flat cropland: 600 mm depth (CTD) and 200 mm (CTD) depth below surface. Summed for five growing seasons (CTD), direct runoff, total N, and dissolved N were reduced by 6.6, 3.5, and 13.7%, respectively. However, five seasons of summed total P, dissolved P, and total suspended solid loads increased as a result of CTD by 0.96, 1.6, and 0.23%. The AnnAGNPS results were compared with mass fluxes observed from paired experimental watersheds (250, 470 ha) in the river basin. The "test" experimental watershed was dominated by CTD and the "reference" watershed by free drainage. Notwithstanding environmental/land use differences between the watersheds and basin, comparisons of seasonal observed and predicted discharge reductions were comparable in 100% of respective cases. Nutrient load comparisons were more consistent for dissolved, relative to particulate water quality endpoints. For one season under corn crop production, AnnAGNPS predicted a 55% decrease (CTD) in dissolved N from the basin. AnnAGNPS v. 5.2 treats P transport from a surface pool perspective, which is appropriate for many systems. However, for assessment of tile drainage management practices for relatively flat tile-dominated systems, AnnAGNPS may benefit from consideration of P and particulate transport in the subsurface.

Effectiveness of alternative management scenarios on the sediment load in a Mediterranean agricultural watershed

The Annualised Agricultural Non-point Source model was used to evaluate the effectiveness of different management practices to control the soil erosion and sediment load in the Carapelle watershed, a Mediterranean medium-size watershed (506 km<sup>2</sup>) located in Apulia, Southern Italy. The model was previously calibrated and validated using five years of runoff and sediment load data measured at a monitoring station located at Ordona - Ponte dei Sauri Bridge. A total of 36 events were used to estimate the performance of the model during the period 2007-2011. The model performed well in predicting runoff, as the high values of the coefficients of efficiency and determination during the validation process showed. The peak flows predictions were satisfactory especially for the high flow events; the prediction capability of sediment load was good, even if a slight over-estimation was observed. Simulations of alternative management practices show that converting the most eroding cropland cells (13.5% of the catchment area) to no tillage would reduce soil erosion by 30%, while converting them to grass or forest would reduce soil erosion by 36.5% in both cases. A crop rotation of wheat and a forage crop can also provide an effective way for soil erosion control as it reduces erosion by 69%. Those results can provide a good comparative analysis for conservation planners to choose the best scenarios to be adopted in the watershed to achieve goals in terms of soil conservation and water quality.

Modelling soil erosion and sediment transport under different land management options in a southern-italy watershed

The aim of this study is to investigate the infl uence of different land management options on the sediment load at the watershed scale. To reach this, the Annualized agricultural non-point source model was used in the Candelaro basin (2300 km 2 ). The watershed is located in a semi-arid area of southern Italy (Puglia region) and is affected by extensive erosion processes on the hillslopes. The sediment transport simulations have been compared with the 15 years (1970–1984) data coming from measures taken in two sub-watersheds (Vulgano and Salsola). Later, the model has been applied for a period of 24 years (1985–2008) to evaluate the effects of different land management options on the sediment yield: traditional best management practices, environmentally targeted agricultural practices and water and soil conservation works. The results obtained in the fi rst part of the work show that the Annualized agricultural non-point source model performs well in simulating runoff and sediment yields at the watershed scale. Furthermore, the analysis carried out shows that the model is an effi cient tool to assess the infl uence of different management options in the long term and in different weather conditions.

Estimation of Runoff, Peak Discharge and Sediment Load at the Event Scale in a Medium‐Size Mediterranean Watershed Using the Annagnps Model

AbstractIn this paper, the Annualized Agricultural Non‐Point Source (AnnAGNPS) model has been used to estimate runoff, peak discharge and sediment load at the event scale in a Mediterranean watershed. The study area is the Carapelle torrent, Southern Italy (area = 506 km2), where continuous rainfall, streamflow and sediment load data are available. Nineteen flood events have been registered in the period 2007–2009 and were used for the application of the model.The aim of the paper is to evaluate the predictive accuracy of the model at the event scale, in a medium‐size watershed, given the specific conditions of the semi‐arid environments. A sensitivity analysis has been carried out to assign the correct parameterization: the mean normalized output variation of the most meaningful input parameters pointed out the influence of the curve number on runoff, peak discharge and sediment load predictions (values greater than 1); the MN Manning's roughness coefficient and K, C and P factors of the universal soil loss equation showed a moderate influence on sediment load simulations (values between 0·5 and 1).The selection of the Soil Conservation Service synthetic storm types has been based on the observed storm events analysis to improve the peak discharge simulations. The model prediction has proved to be good for runoff (R2 = 0·74, NSE = 0·75, W = 0·92) and peak discharge (R2 = 0·85, NSE = 0·70, W = 0·94), and satisfactory for sediment yield (R2 = 0·70, NSE = 0·63, W = 0·91). The relative error is lower for high events; this result is quite interesting in semi‐arid environments, where most of the annual sediment yield is concentrated in a few, severe events. Copyright © 2013 John Wiley & Sons, Ltd.

Coupling agricultural non-point source (AgNPS) model and geographic information system (GIS) tools to predict peak runoff and sediment generation in the upper River Njoro catchment in Kenya

Human interference in the upper River Njoro catchment has led to the increased exposure of the land to accelerated erosion. An application that combined the capabilities of remote sensing, geographic information system (GIS) and agricultural non-point source (AgNPS) model was used to estimate peak runoff rate and sediment yield from the upper River Njoro catchment. Remotely sensed Landsat Thematic Mapper (TM) images were used to obtain land cover and associated AgNPS model input parameters. Other input parameters for the model were extracted from GIS layers using the agricultural non-point source-integrated land and water information system (AgNPS-ILWIS) interface. Surface water quantity and quality data including peak runoff and sediment yield of selected storm events were obtained from two gauging stations, within the catchment. Base flow separation was done so that measured direct peak runoff rate and sediment yield generated by direct runoff could be determined and compared directly with the model simulated results. Simulated peak runoff rates in Upstream (Treetop) station were satisfactory with an EFF of 0.78 and a percent error of 4.1%. The sediment yield was also reasonably estimated with an EFF of 0.88 and a 2% error. The downstream (Egerton) station results were also satisfactorily predicted with peak runoff rate having an EFF of 0.69 and a 5.5% error of estimates, while the estimated sediment yield had an EFF of 0.86 and a 2.5% error. Key words: Peak runoff, sediment, agricultural non-point source (AgNPS), geographic information system (GIS), integrated land and water information system (ILWIS), soil loss.

Estimating sediment, nitrogen, and phosphorous loads from the Pipestem Creek watershed, North Dakota, using AnnAGNPS

Agricultural pollution is a significant problem in North Dakota. Water quality in the Pipestem Creek watershed upstream of Pingree, North Dakota, USA, has been a major environmental concern amongst other adjacent watersheds within the region. The annualized agricultural non-point source (AnnAGNPS) model, a large-scale watershed model designed to predict sediment and nutrient loads, was used to evaluate non-point source pollution in a typical agricultural watershed. The best available data were assembled and used in the analysis. The model predicted runoff of 0.31 m 3/s, compared to a measured value of 0.46 m 3/s. A poor correlation was observed when comparing the model's predicted nitrogen, phosphorus, and sediment with the observed counterparts. The model's poor performance was most likely a result of the large size of the study area and the high variability in land use and management practices.