Climate Sensitivity of Agricultural Water Demand Depends on Control Over Growing Season

Changes to the relationship between precipitation and temperature due to climate change can exacerbate water scarcity by increasing evapotranspiration and reducing runoff and soil moisture. These changes are especially significant for the agricultural sector, where complex interactions between precipitation, temperature, and growing season dynamics produce deep uncertainties in agricultural water demands. While watershed managers have traditionally relied on “top-down” planning scenarios, these typically do not provide insights into the system’s internal variability, nor do they capture the range of plausible, yet deeply uncertain, changes in the regional hydroclimate. To address this shortcoming, we develop a multivariate, multisite, copula-based stochastic weather generator for bottom-up exploratory modeling analysis of agricultural water resources systems. Paired with a regional consumptive use model, this generator allows us to investigate differential impacts of climate change on diverse agricultural producers and crops. We demonstrate this framework in the Upper Colorado River Basin within the state of Colorado. The explored hydroclimatology shows precipitation and temperature as highly variable and elevation-dependent relative to their historical annual averages, spanning -95% and +600% and –10°C and +19°C at the extrema, respectively. As a result, we observe substantial changes in irrigation water requirements for agricultural parcels across the basin between –100% and +250% relative to historical averages; all producers see irrigation requirements increase higher than their historical averages in more than 50% of our sampled realizations, with producers at lower elevations seeing this increase in more than 75% of them. Global sensitivity analysis reveals that adequate access to water impacts producers' effective growing season lengths and thereby which climate variables most control crop water requirement: producers with adequate water are most sensitive to changes in temperature mean and variance while producers without adequate water are most sensitive to changes in precipitation variance—and not mean—with temperature contributions halving. These findings demonstrate how differential vulnerability drivers underscore the need for stakeholder-specific assessments that account for spatial heterogeneity and decision-relevant uncertainties in agricultural water demand.