Addressing data challenges in riverine nutrient load modeling of an intensively managed agro-industrial watershed

Data limitations often challenge the reliability of water quality models, especially in intensively managed watersheds. While numerous studies report successful hydrological model setup and calibration, few have addressed in detail the data challenges for multisite and multivariable model calibration to an intensively managed watershed. In this study, we address some of these challenges based on our reflective experience calibrating the Soil and Water Assessment Tool (SWAT) to the Upper Sangamon River Watershed in central Illinois based on daily flow, annual crop yield, and monthly sediment, nitrate, and total phosphorus loads. We highlight some challenges in SWAT calibration processes due to data errors and inconsistencies, and insufficient precipitation and water quality observations. Following, we demonstrate the merits of additional weather and water quality observations that could help reduce input uncertainties, and we provide suggestions for selecting appropriate observations for the model calibration. After dealing with the data issues, we show that the SWAT model could be calibrated with acceptable results for the case study watershed.

Automated summary

Data limitations often challenge the reliability of water quality models in intensively managed watersheds. This study addresses the data challenges in calibrating the Soil and Water Assessment Tool (SWAT) to the Upper Sangamon River Watershed in central Illinois, highlighting errors and inconsistencies in data and insufficient precipitation and water quality observations. The study also demonstrates the benefits of additional weather and water quality observations for reducing input uncertainties and provides suggestions for selecting appropriate observations for model calibration. After addressing the data issues, the study shows that the SWAT model can be calibrated successfully for the case study watershed.