Application of AnnAGNPS to model an agricultural watershed in East-Central Mississippi for the evaluation of an on-farm water storage (OFWS) system

Karki, Ritesh; Tagert, Mary Love M.; Paz, Joel O.; Bingner, Ronald L.

doi:10.1016/j.agwat.2017.07.002

Cited by 19 publications

(9 citation statements)

References 16 publications

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“…Sediment yields had a trend similar to that of runoff generation, whereby the model seemed to underestimate sediment yields at low rainfall volumes and overestimate values at higher rainfall volumes. Similar results were obtained by Shrestha et al (2006), Shamshad et al (2008), andKarki et al (2017). Suttles et al (2002) suggested that runoff and sediment load plots exhibited the same trends due to the sediment transport capacity.…”

Section: Sediment Yieldsupporting

confidence: 74%

“…Most of the previous studies that have evaluated the AnnAGNPS model (Shrestha et al, 2006;Licciardello et al, 2007;Shamshad et al, 2008;Chahor et al, 2014;Luo et al, 2015;Karki et al, 2017) found that CN was the most sensitive input parameter for surface runoff prediction. In this study, we successfully calibrated the AnnAGNPS model for runoff simulation by adjusting the CN values (Table 2).…”

Section: Model Calibration and Validationmentioning

confidence: 99%

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Performance of AnnAGNPS model in predicting runoff and sediment yields in Nan Province, Thailand

Jirasirichote

Ninsawat

Shrestha

et al. 2021

Heliyon

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Section: Sediment Yieldsupporting

confidence: 74%

Section: Model Calibration and Validationmentioning

confidence: 99%

Performance of AnnAGNPS model in predicting runoff and sediment yields in Nan Province, Thailand

Jirasirichote

Ninsawat

Shrestha

et al. 2021

Heliyon

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“…Their results showed that the AnnAGNPS model can acquire a satisfactory accuracy for annual streamflow simulation, and the accuracy of the nutrient loading simulation is moderate, and monthly nitrogen loading evaluation has higher accuracy than monthly phosphorus loading. Karki, et al [ 106 ] to evaluate runoff, nutrients, and sediment for an agricultural watershed of 30.3 ha in East-Central Mississippi by applying the AnnAGNPS model. They indicated that AnnAGNPS can perform better for runoff evaluation than sediment and phosphorus load assessments on a longer time scale.…”

Section: Watershed-scale Nonpoint Source Pollution Model Evaluationmentioning

confidence: 99%

Review of Watershed-Scale Water Quality and Nonpoint Source Pollution Models

2020

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Watershed-scale nonpoint source (NPS) pollution models have become important tools to understand, evaluate, and predict the negative impacts of NPS pollution on water quality. Today, there are many NPS models available for users. However, different types of models possess different form and structure as well as complexity of computation. It is difficult for users to select an appropriate model for a specific application without a clear understanding of the limitations or strengths for each model or tool. This review evaluates 14 more commonly used watershed-scale NPS pollution models to explain how and when the application of these different models are appropriate for a given effort. The models that are assessed have a wide range of capacities that include simple models used as rapid screening tools (e.g., Long-Term Hydrologic Impact Assessment (L-THIA) and Nonpoint Source Pollution and Erosion Comparison Tool (N-SPECT/OpenNSPECT)), medium-complexity models that require detail data input and limited calibration (e.g., Generalized Watershed Loading Function (GWLF), Loading Simulation Program C (LSPC), Source Loading and Management Model (SLAMM), and Watershed Analysis Risk Management Frame (WARMF)), complex models that provide sophisticated simulation for NPS pollution processes with intensive data and rigorous calibration (e.g., Agricultural Nonpoint Source pollution model (AGNPS/AnnAGNPS), Soil and Water Assessment Tool (SWAT), Stormwater Management Model (SWMM), and Hydrologic Simulation Program Fortran (HSPF)), and modeling systems that integrate various sub-models and tools, and contain the highest complexity to solve all phases of hydrologic, hydraulic, and chemical dynamic processes (e.g., Automated Geospatial Watershed Assessment Tool (AGWA), Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) and Watershed Modeling System (WMS)). This assessment includes model intended use, components or capabilities, suitable land-use type, input parameter type, spatial and temporal scale, simulated pollutants, strengths and limitations, and software availability. Understanding the strengths and weaknesses of each watershed-scale NPS model will lead to better model selection for suitability and help to avoid misinterpretation or misapplication in practice. The article further explains the crucial criteria for model selection, including spatial and temporal considerations, calibration and validation, uncertainty analysis, and future research direction of NPS pollution models. The goal of this work is to provide accurate and concise insight for watershed managers and planners to select the best-suited model to reduce the harm of NPS pollution to watershed ecosystems.

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“…The main components within AnnAGNPS are the combination of the Soil Conservation Service (SCS) curve number (CN) technique [59] used to generate daily runoff and RUSLE 1.05 tool (USDA-ARS, Washington, DC, USA) [54] to produce daily sheet and rill erosion from fields [60]. AnnAGNPS divides the watershed into drainage areas called 'cells' that can have any shape, and each cell is assumed to have homogenous management and soil [28]. These cells portray the spatial variability of land use, soil, and topography within the watershed.…”

Section: Hydrological Modeling Component In Annagnpsmentioning

confidence: 99%

Evaluation of AnnAGNPS Model for Runoff Simulation on Watersheds from Glaciated Landscape of USA Midwest and Northeast

Tamanna

Pradhanang

Gold

et al. 2020

Water

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Runoff modeling of glaciated watersheds is required to predict runoff for water supply, aquatic ecosystem management and flood prediction, and to deal with questions concerning the impact of climate and land use change on the hydrological system and watershed export of contaminants of glaciated watersheds. A widely used pollutant loading model, Annualized Agricultural Non-Point Source Pollution (AnnAGNPS) was applied to simulate runoff from three watersheds in glaciated geomorphic settings. The objective of this study was to evaluate the suitability of the AnnAGNPS model in glaciated landscapes for the prediction of runoff volume. The study area included Sugar Creek watershed, Indiana; Fall Creek watershed, New York; and Pawcatuck River watershed, Rhode Island, USA. The AnnAGNPS model was developed, calibrated and validated for runoff estimation for these watersheds. The daily and monthly calibration and validation statistics (NSE > 0.50 and RSR < 0.70, and PBIAS ± 25%) of the developed model were satisfactory for runoff simulation for all the studied watersheds. Once AnnAGNPS successfully simulated runoff, a parameter sensitivity analysis was carried out for runoff simulation in all three watersheds. The output from our hydrological models applied to glaciated areas will provide the capacity to couple edge-of-field hydrologic modeling with the examination of riparian or riverine functions and behaviors.

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Application of AnnAGNPS to model an agricultural watershed in East-Central Mississippi for the evaluation of an on-farm water storage (OFWS) system

Cited by 19 publications

References 16 publications

Performance of AnnAGNPS model in predicting runoff and sediment yields in Nan Province, Thailand

Performance of AnnAGNPS model in predicting runoff and sediment yields in Nan Province, Thailand

Review of Watershed-Scale Water Quality and Nonpoint Source Pollution Models

Evaluation of AnnAGNPS Model for Runoff Simulation on Watersheds from Glaciated Landscape of USA Midwest and Northeast

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