Uncertainty analysis of an irrigation scheduling model for water management in crop production

S. Mun, G. F. Sassenrath, A. M. Schmidt, N. Lee, M. C. Wadsworth, B. Rice, J. Q. Corbitt, J. M. Schneider, M. L. Tagert, J. Pote, R. Prabhu

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


Irrigation scheduling tools are critical to allow producers to effectively manage water resources for crop production. To be useful, these tools need to be accurate, complete, and relatively reliable. The current work presents an uncertainty analysis and its results for the Mississippi Irrigation Scheduling Tool (MIST) model, showing the margin of error (uncertainty) of the resulting irrigation advice arising solely from the propagation of measurement uncertainty through the MIST calculations. The final relative uncertainty in the water balance value from MIST was shown to be around 9% of that value, which is in the normal range of the margin of error and acceptable for agronomic systems. The results of this research also indicate that accurate measurements of irrigation and rainfall are critical to minimizing errors when using MIST and similar scheduling tools. While developed with data from Mississippi, the results of this uncertainty analysis are relevant to similar tool development efforts across the southern and southeastern United States and other high-rainfall areas, especially for locations lacking high-quality co-located weather stations.

Original languageEnglish (US)
Pages (from-to)100-112
Number of pages13
JournalAgricultural Water Management
StatePublished - Jun 1 2015


  • Agricultural production tools
  • Crop water management
  • Irrigation schedule modeling
  • Soil water balance
  • Uncertainty analysis

ASJC Scopus subject areas

  • Agronomy and Crop Science
  • Water Science and Technology
  • Soil Science
  • Earth-Surface Processes


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