BioEarth: Envisioning and developing a new regional earth system model to inform natural and agricultural resource management

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

CLIMATE CHANGE IMPACTS ON AGRICULTURAL WATER SUPPLY AND DEMAND, IRRIGATION EFFICIENCY AND FARMERS’ ADAPTATION DECISIONS: A CASE STUDY OF THE YAKIMA RIVER BASIN

Climate change impacts the agriculture through a myriad of ways: e.g., through elevated CO2, higher temperatures and an altered water cycle. Although climate change can positively impact agriculture, in many parts of the world the overall direction of these impacts are expected to be negative, potentially threatening the food security of the world’s increasing population. To minimize climate change’s negative consequences, farmers are likely to take adaptive actions. However, these actions may also result in unintended consequences for food supply and other sectors of industry, such as those that also rely on surface water availability. The overarching objective of this research is to develop the understanding of complex interactions between climate, the hydrologic cycle, crop growth and phenology, and human decision making over the Western United States. To satisfy this overall objective we performed the following:• developed a tightly coupled modeling platform (VIC-CropSyst) which mechanistically simulates hydrologic processes at the regional scale while capturing agricultural processes and management at field scales; this framework allows us to investigate the interactions among water/energy cycles and crop management in agricultural river basins (Chapter One),• embedded an irrigation module into VIC-CropSyst for mechanistic simulate of irrigation losses and to assess the impact of climate change on the efficiency of irrigation systems (Chapter Two), and• developed a hydrologic-agricultural-economic modeling platform that simulates how farmers’ investment decisions into more efficient irrigation technology may be impacted by climate change (Chapter Three).The case study area is Washington State’s Yakima River Basin (YRB), a watershed in the western U.S.’s that is representative of other heavily irrigated agricultural basins that are sensitive to climate change. The results indicate that the severity and frequency of droughts are increasing in the YRB; this provides financial incentives for farmers to switch to new irrigation systems. The results also show that climate change causes an increase in irrigation evaporative losses with a decrease in reusable non-evaporative losses, thus reducing future return flows and causing further water stress for downstream water users

Input and Output Files

Input and Output files can be downloaded from here<br

Water rights shape crop yield and revenue volatility tradeoffs for adaptation in snow dependent systems

Studies on examining the climate impact on irrigated agriculture do not account for regional specific details. Here the authors studied both the direct and indirect impact of climate change on irrigated agriculture in the Yakima River Basin (YRB) and found that increasingly severe droughts and temperature driven reductions in growing season significantly reduces expected annual agricultural productivity

Incorporating Social System Dynamics in the Columbia River Basin: Food-Energy-Water Resilience and Sustainability Modeling in the Yakima River Basin

In the face of climate change, achieving resilience of desirable aspects of food-energy-water (FEW) systems already strained by competing multi-scalar social objectives requires interdisciplinary approaches. This study is part of a larger effort exploring “Innovations in the Food-Energy-Water Nexus (INFEWS)” in the Columbia River Basin (CRB) through coordinated modeling and simulated management scenarios. Here, we focus on a case study and conceptual mapping of the Yakima River Basin (YRB), a sub-basin of the CRB. Previous research on FEW system management and resilience includes some attention to social dynamics (e.g., economic and governance systems); however, more attention to social drivers and outcomes is needed. Our goals are to identify several underutilized ways to incorporate social science perspectives into FEW nexus research and to explore how this interdisciplinary endeavor alters how we assess innovations and resilience in FEW systems. First, we investigate insights on FEW nexus resilience from the social sciences. Next, we delineate strategies for further incorporation of social considerations into FEW nexus research, including the use of social science perspectives and frameworks such as socio-ecological resilience and community capitals. Then, we examine a case study of the YRB, focusing on the historical development of the FEW nexus and innovations. We find that a resilience focus applied to the FEW nexus can inadvertently emphasize a status quo imposed by those already in power. Incorporating perspectives from the social sciences, which highlight issues related to inequality, power, and social justice, can address these shortcomings and inform future innovations. Finally, we use causal loop diagrams to explore the role of the social in the FEW nexus, and we suggest ways to incorporate social aspects into an existing stock and flow object-oriented modeling system. This project represents a starting point for a continued research agenda that incorporates social dynamics into FEW system resilience modeling and management in the CRB

Large Ensemble Diagnostic Evaluation of Hydrologic Parameter Uncertainty in the Community Land Model Version 5 (CLM5)

Abstract Land surface models such as the Community Land Model version 5 (CLM5) seek to enhance understanding of terrestrial hydrology and aid in the evaluation of anthropogenic and climate change impacts. However, the effects of parametric uncertainty on CLM5 hydrologic predictions across regions, timescales, and flow regimes have yet to be explored in detail. The common use of the default hydrologic model parameters in CLM5 risks generating streamflow predictions that may lead to incorrect inferences for important dynamics and/or extremes. In this study, we benchmark CLM5 streamflow predictions relative to the commonly employed default hydrologic parameters for 464 headwater basins over the conterminous United States (CONUS). We evaluate baseline CLM5 default parameter performance relative to a large (1,307) Latin Hypercube Sampling‐based diagnostic comparison of streamflow prediction skill using over 20 error measures. We provide a global sensitivity analysis that clarifies the significant spatial variations in parametric controls for CLM5 streamflow predictions across regions, temporal scales, and error metrics of interest. The baseline CLM5 shows relatively moderate to poor streamflow prediction skill in several CONUS regions, especially the arid Southwest and Central U.S. Hydrologic parameter uncertainty strongly affects CLM5 streamflow predictions, but its impacts vary in complex ways across U.S. regions, timescales, and flow regimes. Overall, CLM5's surface runoff and soil water parameters have the largest effects on simulated high flows, while canopy water and evaporation parameters have the most significant effects on the water balance

Image2_Downscaling global land-use/cover change scenarios for regional analysis of food, energy, and water subsystems.TIF

Integrated assessment models (IAMs) capture synergies between human development and natural ecosystems that have important implications for the food-energy-water (FEW) nexus. However, their lack of fine-scale representation of water regulatory structure and landscape heterogeneity impedes their application to FEW impact studies in water-limited basins. To address this limitation, we developed a framework for studying effects of global change on regional outcomes for food crops, bioenergy, hydropower, and instream flows. We applied the new methodology to the Columbia River Basin (CRB) as a case study. The framework uses the Demeter land-use and land-cover change (LULCC) downscaling tool, which we updated so that water rights are spatially integrated in the land allocation process. We downscaled two LULCC scenarios (SSP2-RCP 4.5 and SSP5-RCP 8.5) under three levels of irrigation expansion: no expansion (historical extent), moderate expansion (all land presently authorized by a water right is irrigated), and maximum expansion (new water rights are granted to cover all irrigable land). The downscaled scenarios were evaluated using a hydrology-cropping systems model and a reservoir model coupled in a linear fashion to quantify changes in food and bioenergy crop production, hydropower generation, and availability of instream flows for fish. The net changes in each sector were partitioned among climate, land use, and irrigation-expansion effects. We found that climate change alone resulted in approximately 50% greater production of switchgrass for bioenergy and 20% greater instream flow deficits. In the irrigation-expansion scenarios, the combination of climate change and greater irrigated extent increased switchgrass production by 76% to 256% at the cost of 42% to 165% greater instream flow deficits and 0% to 8% less hydropower generation. Therefore, while irrigation expansion increased bioenergy crop productivity, it also exacerbated seasonal water shortages, especially for instream use. This paper provides a general framework for assessing benchmark scenarios of global LULCC in terms of their regional FEW subsystem outcomes.</p

Image3_Downscaling global land-use/cover change scenarios for regional analysis of food, energy, and water subsystems.TIF

Integrated assessment models (IAMs) capture synergies between human development and natural ecosystems that have important implications for the food-energy-water (FEW) nexus. However, their lack of fine-scale representation of water regulatory structure and landscape heterogeneity impedes their application to FEW impact studies in water-limited basins. To address this limitation, we developed a framework for studying effects of global change on regional outcomes for food crops, bioenergy, hydropower, and instream flows. We applied the new methodology to the Columbia River Basin (CRB) as a case study. The framework uses the Demeter land-use and land-cover change (LULCC) downscaling tool, which we updated so that water rights are spatially integrated in the land allocation process. We downscaled two LULCC scenarios (SSP2-RCP 4.5 and SSP5-RCP 8.5) under three levels of irrigation expansion: no expansion (historical extent), moderate expansion (all land presently authorized by a water right is irrigated), and maximum expansion (new water rights are granted to cover all irrigable land). The downscaled scenarios were evaluated using a hydrology-cropping systems model and a reservoir model coupled in a linear fashion to quantify changes in food and bioenergy crop production, hydropower generation, and availability of instream flows for fish. The net changes in each sector were partitioned among climate, land use, and irrigation-expansion effects. We found that climate change alone resulted in approximately 50% greater production of switchgrass for bioenergy and 20% greater instream flow deficits. In the irrigation-expansion scenarios, the combination of climate change and greater irrigated extent increased switchgrass production by 76% to 256% at the cost of 42% to 165% greater instream flow deficits and 0% to 8% less hydropower generation. Therefore, while irrigation expansion increased bioenergy crop productivity, it also exacerbated seasonal water shortages, especially for instream use. This paper provides a general framework for assessing benchmark scenarios of global LULCC in terms of their regional FEW subsystem outcomes.</p