Abstract
Understanding how irrigation is used across agricultural landscapes is essential to support efforts to grow more food while reducing pressures on limited freshwater resources. However, to date, few studies have analyzed the underlying spatial and temporal variability in farmers’ individual water use decisions at a landscape scale. We compare estimates of irrigation water requirements derived using state-of-the-art remote sensing models with metered abstraction records for 1400 fields over a 13 year period in the US state of Nebraska, one of the world’s most intensively irrigated agricultural regions. We show that farmers’ observed water use decisions often diverge significantly from biophysical estimates of crop irrigation requirements. In particular, our findings are consistent with widespread use of water conservation practices by farmers in drought years as an adaptive response to rising irrigation costs and regulatory water supply constraints in these years. We also demonstrate that, in any individual year, farmers observed water use exhibits large field-to-field variability, which cannot be explained fully by differences in weather, soil type, crop choice, or technology. Our results highlight the value of using both in situ monitoring and remote sensing to evaluate farmers’ individual water use behavior and understand likely responses to future changes in climate or water policy. Moreover, our findings also demonstrate potential challenges for current efforts in developed and developing countries to apply model-based approaches for field-level water use accounting and enforcement of irrigation water rights.
Highlights
As the largest consumer of water globally, agriculture is both sensitive to water scarcity and a major driver of inter-sectoral water conflict
In wetter years we observe that farmers actual water use on average is greater than model estimates of biophysical water requirements, whereas in drought years farmers increasingly irrigate below full water requirements
Comparing in situ water use observations and remotely sensed estimates of crop irrigation water requirements offers a valuable opportunity to understand how water is used across agricultural landscapes and, in doing so, support the management of limited freshwater resources
Summary
As the largest consumer of water globally, agriculture is both sensitive to water scarcity and a major driver of inter-sectoral water conflict. Water balance and crop growth models have been widely utilized for several decades to quantify irrigation water requirements as a function of agronomic, soil, and climatic conditions, and inform decisionmaking about irrigation water management at fieldto-landscape scales [1–4]. Model-based assessments of irrigation water use provide estimates of the variability in irrigation water requirements due to biophysical factors such as weather, soil type, and crop choice. In addition to these biophysical drivers, farmers actual irrigation decision-making may be influenced by a variety of other factors. These include physical or regulatory limits to available water and individual farm management strategies, which reflect underlying economic and social conditions (e.g. crop and input prices, labor availability), and behavioral choices and uncertainty (e.g. risk aversion, irrigation heuristics)
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