Food supply is affected by a complex nexus of land, atmosphere, and human processes, including short- and long-term stressors (e.g., drought and climate change, respectively). A simulation platform that captures these complex elements can be used to inform policy and best management practices to promote sustainable agriculture. We have developed a tightly coupled framework using the macroscale variable infiltration capacity (VIC) hydrologic model and the CropSyst agricultural model. A mechanistic irrigation module was also developed for inclusion in this framework. Because VIC–CropSyst combines two widely used and mechanistic models (for crop phenology, growth, management, and macroscale hydrology), it can provide realistic and hydrologically consistent simulations of water availability, crop water requirements for irrigation, and agricultural productivity for both irrigated and dryland systems. This allows VIC–CropSyst to provide managers and decision makers with reliable information on regional water stresses and their impacts on food production. Additionally, VIC–CropSyst is being used in conjunction with socioeconomic models, river system models, and atmospheric models to simulate feedback processes between regional water availability, agricultural water management decisions, and land–atmosphere interactions. The performance of VIC–CropSyst was evaluated on both regional (over the US Pacific Northwest) and point scales. Point-scale evaluation involved using two flux tower sites located in agricultural fields in the US (Nebraska and Illinois). The agreement between recorded and simulated evapotranspiration (ET), applied irrigation water, soil moisture, leaf area index (LAI), and yield indicated that, although the model is intended to work on regional scales, it also captures field-scale processes in agricultural areas.

The western U.S. is expected to experience more frequent and severe droughts as a result of climate change, with potentially large impacts on agricultural production and the economy. Irrigated farmers have multiple options for minimizing the impact of drought including switching to more efficient irrigation technologies. More efficient technologies that increase the fraction of the water available to the crop root zone would allow farmers to maintain current production levels with less water. However, these systems are capital intensive. The objective of this study is to explore when (and under what climatic conditions) it makes economic sense for farmers to invest in new irrigation systems. We examine this in the Yakima River Basin in Washington State of the U.S. We use VIC‐CropSyst, a large‐scale grid‐based modeling framework that mechanistically simulates hydrologic and agricultural processes. Water supply simulated by VIC‐CropSyst drives a river system and water management model (YAK‐RW). A computational platform was developed to perform the economic analysis for each grid cell, crop type, and future climate scenario separately, which allowed us to explore whether the implementation of more efficient irrigation systems would be economically viable. Our results indicate that investing in a more efficient irrigation system improves agricultural economy of the Yakima River Basin (9% −25%). We also show that at the farm level, more significant droughts can provide economic incentives for investment up to a point. For severe climate change projections, droughts become frequent and severe enough that economic benefits of improving water use efficiency do not exceed investment costs.

As managers of agricultural and natural resources are confronted with uncertainties in global change impacts, the complexities associated with the interconnected cycling of nitrogen, carbon, and water present daunting management challenges. Existing models provide detailed information on specific sub-systems (e.g., land, air, water, and economics). An increasing awareness of the unintended consequences of management decisions resulting from interconnectedness of these sub-systems, however, necessitates coupled regional earth system models (EaSMs). Decision makers’ needs and priorities can be integrated into the model design and development processes to enhance decision-making relevance and “usability” of EaSMs. BioEarth is a research initiative currently under development with a focus on the U.S. Pacific Northwest region that explores the coupling of multiple stand-alone EaSMs to generate usable information for resource decision-making. Direct engagement between model developers and non-academic stakeholders involved in resource and environmental management decisions throughout the model development process is a critical component of this effort. BioEarth utilizes a bottom-up approach for its land surface model that preserves fine spatial-scale sensitivities and lateral hydrologic connectivity, which makes it unique among many regional EaSMs. This paper describes the BioEarth initiative and highlights opportunities and challenges associated with coupling multiple stand-alone models to generate usable information for agricultural and natural resource decision-making.