Statistical emulators of irrigated crop yields and irrigation water requirements
Abstract
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.
- Publication Date:
- Research Org.:
- Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- OSTI Identifier:
- 1800817
- Alternate Identifier(s):
- OSTI ID: 1776481
- Grant/Contract Number:
- FG02-94ER61937
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Agricultural and Forest Meteorology
- Additional Journal Information:
- Journal Volume: 284; Journal ID: ISSN 0168-1923
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; crop yields; irrigation; crop model; statistical model; water withdrawals; climate change
Citation Formats
Blanc, Élodie. Statistical emulators of irrigated crop yields and irrigation water requirements. United States: N. p., 2020.
Web. doi:10.1016/j.agrformet.2019.107828.
Blanc, Élodie. Statistical emulators of irrigated crop yields and irrigation water requirements. United States. https://doi.org/10.1016/j.agrformet.2019.107828
Blanc, Élodie. Wed .
"Statistical emulators of irrigated crop yields and irrigation water requirements". United States. https://doi.org/10.1016/j.agrformet.2019.107828. https://www.osti.gov/servlets/purl/1800817.
@article{osti_1800817,
title = {Statistical emulators of irrigated crop yields and irrigation water requirements},
author = {Blanc, Élodie},
abstractNote = {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.},
doi = {10.1016/j.agrformet.2019.107828},
journal = {Agricultural and Forest Meteorology},
number = ,
volume = 284,
place = {United States},
year = {Wed Jan 15 00:00:00 EST 2020},
month = {Wed Jan 15 00:00:00 EST 2020}
}
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