Performance analysis method for model-based irrigation strategies under uncertainty

F.D. Mondaca-Duarte*, M. Heinen, S. van Mourik

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)


There is a necessity to increase the performance of food production in agriculture, this means, that precise management support in farming systems is required to reduce water use and drainage while avoiding crop stress. Management support based on model predictions is used to increase the performance of food production. However, sources of uncertainty affect the model predictions. Uncertainty in soil properties and uncertain evapotranspiration translate into uncertain predictions, and consequently in risk of performance loss. This paper presents the code and method to analyze performance uncertainty (and risk of performance loss) due to uncertain circumstances. The method is based on using the De Graaf evapotranspiration model and the EMMAN3G model, a Richards equation-based soil water model, as modules to conduct a performance uncertainty study.

Original languageEnglish
Article number101075
Publication statusPublished - Jan 2020


  • Drainage
  • Monte Carlo
  • Richards equation
  • Uncertainty framework for model-based irrigation


Dive into the research topics of 'Performance analysis method for model-based irrigation strategies under uncertainty'. Together they form a unique fingerprint.

Cite this