Statistical emulators of irrigated crop yields and irrigation water requirements

Journal Article · 14 January 2020 · Agricultural and Forest Meteorology

DOI: https://doi.org/10.1016/j.agrformet.2019.107828 · OSTI ID:1800817

Blanc, Élodie  ^[1]

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1. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States); OSTI

This study provides statistical emulators of global by gridded crop models included in the Inter-Sectoral Impact Model Intercomparison Project Fast Track project to estimate irrigated crop yields and associated irrigation water withdrawals simulated at the grid cell level. An ensemble of crop model simulations is used to build a panel of monthly summer weather variables and corresponding annual yields and irrigation water withdrawals from five gridded crop models. This dataset is then used to estimate crop-specific response functions for each crop model. The average normalized root mean square errors for the response functions range from 3% to 6% for irrigated yields and 2% to 8% for irrigated water withdrawal. Further in- and out-of-sample validation exercises confirm that the statistical emulators are able to replicate the crop models’ spatial patterns of irrigated crop yields and irrigation water withdrawals, both in levels and in terms of changes over time, although accuracy varies by model and by region. The emulators estimated in this study therefore provide a reliable and computationally efficient alternative to global gridded crop yield models.

• Research Organization: Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
• Sponsoring Organization: USDOE; USDOE Office of Science (SC), Biological and Environmental Research (BER)
• Grant/Contract Number: FG02-94ER61937
• OSTI ID: 1800817
• Journal Information: Agricultural and Forest Meteorology, Journal Name: Agricultural and Forest Meteorology Vol. 284; ISSN 0168-1923
• Publisher: ElsevierCopyright Statement
• Country of Publication: United States
• Language: English