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

Sundar Niroula, Kevin Wallington, Ximing Cai

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)213-225
Number of pages13
JournalJournal of the American Water Resources Association
Issue number2
StatePublished - Apr 2023


  • Corn Belt watersheds
  • SWAT
  • data challenges
  • multisite and multivariable calibration
  • water quality

ASJC Scopus subject areas

  • Ecology
  • Water Science and Technology
  • Earth-Surface Processes


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