Skip to main content
Dryad logo

Sustainable use of groundwater may dramatically reduce irrigated production of maize, soybean, and wheat

Citation

Lopez, Jose R. et al. (2021), Sustainable use of groundwater may dramatically reduce irrigated production of maize, soybean, and wheat, Dryad, Dataset, https://doi.org/10.5061/dryad.cc2fqz65x

Abstract

Groundwater extraction in the United States (US) is unsustainable, making it essential to understand the impacts of limited water use on irrigated agriculture. Here, we integrate a gridded crop model with satellite observations, recharge estimates, and water survey data to assess the effects of sustainable groundwater withdrawals on US irrigated agricultural production.  Our model agrees with satellite-based estimates of evapotranspiration (R2 = 0.68), as well as survey production estimates from the United States Department of Agriculture (R2 = 0.82 – 0.94 for county-level production and 0.37 – 0.54 for county-level yield). Using the optimistic assumption that groundwater extraction equals estimated effective aquifer recharge rate, we find that sustainable groundwater use decreases US irrigated production of maize, soybean, and winter wheat by 20%, 6%, and 25%, respectively. Using a more conservative assumption of groundwater availability, US irrigated production of maize, soybean, and winter wheat decreases by 45%, 37%, and 36%, respectively. The wide range of simulated losses is driven by considerable uncertainty in surface water and groundwater interactions, as well as accounting for adaptation and the many aspects of sustainability, including environmental flows. These results demonstrate the vulnerability of US irrigated agriculture to unsustainable groundwater pumping, highlighting the difficulty of expanding or even maintaining irrigated food production in the face of climate change, population growth, and shifting dietary demands. Our findings are based on reducing pumping by fallowing irrigated farmland, so alternate pumping reduction strategies or technological advances in crop genetics and irrigation technologies could produce different results.

Usage Notes

The archived data consists of 9 raster files, all of them in Network Common Data Form (NCDF). All files represent the continental United States at a 5 arc minute resolution.

The first three files contain the calibrated SLPF parameter for pDSSAT. They have two dimensions, i.e. latitude and longitude, and one variable, SLPF. The first three characters of the file name indicate the name of the crop simulated, namely mai for maize, soy for soybean, and wwh for winter wheat. The last five characters of the file names are "_slpf".

The other six files contain the pDSSAT model output. These files have  have 3 dimensions and 5 variables. The dimensions of the files are latitude, longitude, and time. The dimension time has 5 levels, one for each growing season simulated. The following variables are stored in these files:  total evapotranspiration between planting and harvest (mm; ETCP), yield (kg [dm]/ha; HWAM), season irrigation (mm; IRCM), physiological maturity date (YrDoy; MDAT), and planting date (YrDoy; PDAT). Same as the parameter files described above, the first three characters of the character file names indicate the name of the crop simulated. The last two characters indicate if the simulation is irrigated (Ir) or rainfed (Rf). 

Funding

National Science Foundation, Award: BCS 184018

National Institute of Food and Agriculture, Award: 2015‐68007‐23133

National Institute of Food and Agriculture, Award: 2018-67003-27406