Agricultural Responses to Changing Water Supplies in Imperial Valley, California

Keywords: water resources, agriculture, mixed methods, Imperial Valley
Session Type: Virtual Paper Abstract
Day: Friday
Session Start / End Time: 2/25/2022 03:40 PM (Eastern Time (US & Canada)) - 2/25/2022 05:00 PM (Eastern Time (US & Canada))
Room: Virtual 53

Abstract

The Imperial Valley is an agricultural region along the United States-Mexico border that produces a large share of winter crops for the United States. The Valley’s crop irrigation system is dependent upon water imported from the Colorado River. In 2003, the Quantification Settlement Agreement (QSA) was enacted to reduce California’s dependence on the Colorado River. Water-governing parties at federal, state, and regional levels devised a series of agriculture-to-urban water transfers from the Imperial Irrigation District (IID) to surrounding water districts. To conserve the massive volumes of water for transfer, the QSA incentivized water-conserving fallowing and on-farm efficiency programs in the IID. The fallowing program offered farmers compensation to intermittently fallow portions of their land for 2-3 years at a time. Though the fallowing program ended in 2017, it has not been fully investigated in terms of its regional impact on the Imperial Valley. While annual crop reports provide numerical clues to the Valley’s response to reductions in water supply, resulting hydrologic patterns, cropping choices, and responses by local stakeholders remain unknown. This study asks: How did the Imperial Valley agricultural system respond to changes in water supplies brought on by the QSA? Using a mixed-methods approach, I synthesized data on hydrologic change, trends from cropped and fallowed fields, and key informant narratives illustrate the Valley-wide reaction to QSA policy and programs. Results suggest that the Imperial Valley adapted to an overall reduction in water supply by increasing water productivity, strategic crop switching, and implementing a more dynamic business model.