Publications by authors named "Ammar B Bhandari"

Cover crop biomass is helpful for weed and pest control, soil erosion control, nutrient recycling, and overall soil health and crop productivity improvement. These benefits may vary based on cover crop species and their biomass. There is growing interest in the agricultural sector of using remotely sensed imagery to estimate cover crop biomass.

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Process-based computer models have been proposed as a tool to generate data for Phosphorus (P) Index assessment and development. Although models are commonly used to simulate P loss from agriculture using managements that are different from the calibration data, this use of models has not been fully tested. The objective of this study is to determine if the Agricultural Policy Environmental eXtender (APEX) model can accurately simulate runoff, sediment, total P, and dissolved P loss from 0.

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Article Synopsis
  • The research focuses on developing a regional parameterization of the APEX model to estimate phosphorus loss and runoff in Missouri and Kansas, using site-specific models as a basis.
  • The newly created regional model performed acceptably for runoff and total phosphorus loss simulations but struggled significantly with sediment loss, making it less reliable for that aspect.
  • Despite not achieving a strong model for sediment and total phosphorus losses, the regional model's runoff estimates are deemed useful for assessing phosphorus Index evaluations.
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The Agricultural Policy Environmental eXtender (APEX) model is capable of estimating edge-of-field water, nutrient, and sediment transport and is used to assess the environmental impacts of management practices. The current practice is to fully calibrate the model for each site simulation, a task that requires resources and data not always available. The objective of this study was to compare model performance for flow, sediment, and phosphorus transport under two parameterization schemes: a best professional judgment (BPJ) parameterization based on readily available data and a fully calibrated parameterization based on site-specific soil, weather, event flow, and water quality data.

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