The Benefit of Using an Ensemble of Global Hydrological Models in Surface Water Availability for Irrigation Area Planning

Alexander Kaune (), Patricia López, Anouk Gevaert, Ted Veldkamp, Micha Werner and Charlotte Fraiture
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Alexander Kaune: IHE Delft Institute for Water Education
Patricia López: Deltares
Anouk Gevaert: VU University
Ted Veldkamp: VU University
Micha Werner: IHE Delft Institute for Water Education
Charlotte Fraiture: IHE Delft Institute for Water Education

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2020, vol. 34, issue 7, No 7, 2240 pages

Abstract: Abstract Hydrological data and information on the availability of water are essential to support water allocation decisions in irrigated agriculture, especially under increasingly water scarce conditions. However, in many agricultural regions hydrological information is scarce, leading to sub-optimal water allocation decisions and crop yield reduction. Here we assess the benefit of using surface water availability estimates derived from an ensemble of global hydrological models for establishing the potential area that can be irrigated; where the size is determined based on agreed water supply reliability targets. Risky outcomes of the annual agricultural production due to the true occurrence of water scarcity are generated for both the reference and established irrigation areas, resulting in a Relative Utility Value (RUV) that expresses the utility of the information used. Results show that using an ensemble of global hydrological models provides more robust estimates of the planned area compared to using any of the single global models that constitutes the ensemble. A comparison of the information content in the ensemble shows that an ensemble with a period of record of 15 years has an information content equivalent to a single model of 30 years.

Keywords: Hydrological information; Water allocation decisions; Irrigated agriculture; Irrigation demand (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s11269-020-02544-1

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