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Quantifying the interconnected impacts of climate change and irrigation on surface water flows is critical for the proactive management of our water resources and the ecosystem services they provide. Changes in streamflow across the Western U.S. have generally been attributed to an aridifying climate, but in many basins flows can also be highly impacted by irrigation. We developed a 35-year dataset consisting of streamflow, climate, irrigated area, and crop water use to quantify the effects of both climate change and irrigation water use on streamflow across 221 basins in the Colorado, Columbia, and Missouri River systems. We demonstrate that flows have been altered beyond observed climate-related changes and that many of these changes are attributable to irrigation. Further, our results indicate that increases in irrigation water use have occurred over much of the study area, a finding that contradicts government-reported irrigation statistics. Increases in crop consumption have enhanced fall and winter flows in some portions of the Upper Missouri and northern Columbia River basins, and have exacerbated climate change-induced flow declines in parts of the Colorado basin. We classify each basin’s water resources sustainability in terms of flow and irrigation trends and link irrigation-induced flow changes to irrigation infrastructure modernization and differences in basin physiographic setting. These results provide a basis for determining where modern irrigation systems benefit basin water supply, and where less efficient systems contribute to return flows and relieve ecological stress.

 

The Western United States (U.S.) relies heavily on scarce water resources for both ecological services and irrigation. However, the response of irrigation water use during drought is not well documented. Irrigation decision‐making is complex and influenced by human and environmental factors such as water deliveries, crop yields, equipment, labor, crop prices, and climate variability. While few irrigation districts have plans to curtail water deliveries during droughts, water rights, fallowing patterns, crop rotations, and profit expectations also influence irrigation management at the farm scale. This study uses high‐resolution satellite data to examine the response of irrigators to drought by using a novel measure of irrigation management, the Standardized Irrigation Management Index. We assess the state of drought at the field and basin scales in terms of climate and streamflow and analyze the importance of variations in crop price and drought status on decision‐making and water use. We show significant variability in field‐scale response to drought and that crop type, irrigation type, and federal management explain regional and field‐scale differences. The relative influence of climate and prices on crop transitions indicate prices more strongly drive crop planting decisions. The study provides insights into irrigation management during drought, which is crucial for sustainable water supply in the face of the ongoing water supply crisis in the U.S. Southwest.

 

Growing demand for water resources coupled with climate-driven water scarcity and variability present critical challenges to agriculture in the Western US. Despite extensive resources allocated to downscaling climate projections and advances in understanding past, current, and future climatic conditions, climate information is underutilized in decisions made by agricultural producers. Climate information providers need to understand why this information is underutilized and what would better meet the needs of producers. To better understand how agricultural producers perceive and utilize climate information, we conducted five focus groups with farmers and ranchers across Montana. Focus groups revealed that there are fundamental scalar issues (spatial and temporal) that make climate information challenging for producers to use. While climate information is typically produced at regional, national, or global spatial scales and at a seasonal and mid- to end-of-century temporal scales, producers indicated that decision-making takes place at multiple intermediate and small temporal and spatial scales. In addition, producers described other drivers of decision-making that have little to do with climate information itself, but rather aspects of source credibility, past experience, trust in information, and the politics of climate change. Through engaging directly with end-users, climate information providers can better understand the spatial and temporal scales that align with different types of agricultural producers and decisions, as well as the limitations of information provision given the complexity of the decision context. Increased engagement between climate information providers and end-users can also address the important tradeoffs that exist between scale and uncertainty. 

High frequency and spatially explicit irrigated land maps are important for understanding the patterns and impacts of consumptive water use by agriculture. We built annual, 30 m resolution irrigation maps using Google Earth Engine for the years 1986–2018 for 11 western states within the conterminous U.S. Our map classifies lands into four classes: irrigated agriculture, dryland agriculture, uncultivated land, and wetlands. We built an extensive geospatial database of land cover from each class, including over 50,000 human-verified irrigated fields, 38,000 dryland fields, and over 500,000 km 2 of uncultivated lands. We used 60,000 point samples from 28 years to extract Landsat satellite imagery, as well as climate, meteorology, and terrain data to train a Random Forest classifier. Using a spatially independent validation dataset of 40,000 points, we found our classifier has an overall binary classification (irrigated vs. unirrigated) accuracy of 97.8%, and a four-class overall accuracy of 90.8%. We compared our results to Census of Agriculture irrigation estimates over the seven years of available data and found good overall agreement between the 2832 county-level estimates (r 2 = 0.90), and high agreement when estimates are aggregated to the state level (r 2 = 0.94). We analyzed trends over the 33-year study period, finding an increase of 15% (15,000 km 2 ) in irrigated area in our study region. We found notable decreases in irrigated area in developing urban areas and in the southern Central Valley of California and increases in the plains of eastern Colorado, the Columbia River Basin, the Snake River Plain, and northern California. 

Abstract The 2017 flash drought arrived without early warning and devastated the U.S. northern Great Plains region comprising Montana, North Dakota, and South Dakota and the adjacent Canadian Prairies. The drought led to agricultural production losses exceeding $2.6 billion in the United States, widespread wildfires, poor air quality, damaged ecosystems, and degraded mental health. These effects motivated a multiagency collaboration among academic, tribal, state, and federal partners to evaluate drought early warning systems, coordination efforts, communication, and management practices with the goal of improving resilience and response to future droughts. This essay provides an overview on the causes, predictability, and historical context of the drought, the impacts of the drought, opportunities for drought early warning, and an inventory of lessons learned. Key lessons learned include the following: 1) building partnerships during nondrought periods helps ensure that proper relationships are in place for a coordinated and effective drought response; 2) drought information providers must improve their understanding of the annual decision cycles of all relevant sectors, including, and beyond, direct impacts in agricultural sectors; and 3) ongoing monitoring of environmental conditions is vital to drought early warning, given that seasonal forecasts lack skill over the northern Great Plains. 

Abstract Patterns of energy and available moisture can vary over small (<1 km) distances in mountainous terrain. Information on fuel and soil moisture conditions that resolves this variation could help to inform fire and drought management decisions. Here, we describe the development of TOPOFIRE, a web-based mapping system designed to provide finely resolved information on soil water balance, drought, and wildfire danger information for the contiguous United States. We developed 8-arc-second-resolution (~250 meter) daily historical, near real-time, and 4-day forecast radiation, temperature, humidity, and snow water equivalent data and used these grids to calculate a suite of drought and wildfire danger indices. Large differences in shortwave radiation and surface air temperature with aspect contribute to greater snow accumulation and delays in melt timing on north-facing slopes, delaying fuel conditioning on shaded slopes. These datasets will help advance our understanding of the role of topography in wildland fire spread and ecological effects. Integration with national programs like the Wildland Fire Assessment System, the Wildland Fire Decision Support System, and drought early warning systems could support more proactive management of wildland fires and refine the characterization of drought in mountainous regions of the United States.