Yakima River Basin Research Articles

Incorporation of climate change into a multiple stressor risk assessment for the Chinook salmon (Oncorhynchus tshawytscha) population in the Yakima River, Washington, USA.

One outcome of the 2022 Society of Environmental Toxicology and Chemistry Pellston Workshop on incorporating climate change predictions into ecological risk assessments was the key question of how to integrate ecological risk assessments that focus on contaminants with the environmental alterations from climate projections. This article summarizes the results of integrating selected direct and indirect effects of climate change into an existing Bayesian network previously used for ecological risk assessment. The existing Bayesian Network Relative Risk Model integrated the effects of two organophosphate pesticides (malathion and diazinon), water temperature, and dissolved oxygen levels on the Chinook salmon population in the Yakima River Basin (YRB), Washington, USA. The endpoint was defined as the entity, Yakima River metapopulation, and the attribute was defined as no decline to a subpopulation or the overall metapopulation. In this manner, we addressed the management objective of no net loss of Chinook salmon, an iconic and protected species. Climate change-induced changes in water quality parameters (temperature and dissolved oxygen levels) used models based on projected climatic conditions in the 2050s and 2080s by the use of a probabilistic model. Pesticide concentrations in the original model were modified assuming different scenarios of pest control strategies in the future, because climate change may alter pest numbers and species. Our results predict that future direct and indirect changes to the YRB will result in a greater probability that the salmon population will continue to fail to meet the management objective of no net loss. As indicated by the sensitivity analysis, the key driver in salmon population risk was found to be current and future changes in temperature and dissolved oxygen, with pesticide concentrations being not as important. Integr Environ Assess Manag 2024;20:419-432. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

The importance of explicitly representing the streambed in watershed models

AbstractThe streambed is the critical interface between the aquatic and terrestrial systems and hosts important biogeochemical hot spots within river corridors. Although the streambed characteristics are significantly different from those of its surrounding soil, the streambed itself has not been explicitly represented in watershed models. Here, we explicitly incorporated a streambed layer into an integrated hydrologic model through model parameterization and discretization. We examined the hydrological effects of streambed characteristics, including hydraulic conductivity (K), layer thickness, and resolution, on the exchange fluxes across the streambed as well as the streamflow at the watershed outlet. The numerical experiments were performed in the American River Watershed, a headwater, mountainous watershed within the Yakima River Basin in central Washington. Despite having a negligible effect on the watershed streamflow, an explicit representation of the streambed with distinctive properties dramatically changed the magnitude and variability of the exchange flux. In general, a larger streambed K along with a thicker streambed layer induced larger exchange fluxes. The exchange flux was most sensitive to the streambed resolution. A finer streambed resolution increased exchange fluxes per unit area while reducing the overall exchange volumes across the entire streambed. The amount of baseflow decreased by 6% as the streambed resolution increased from 250 to 50 m. This finding is important because these hydrological changes may, in turn, affect the exchange of nutrients and contaminants between surface water and groundwater and the associated biogeochemical processes. Our work demonstrated the importance of representing streambeds in fully distributed, process‐based watershed models to better capture the exchange flow dynamics in river corridors.

Riverine organic matter functional diversity increases with catchment size

A large amount of dissolved organic matter (DOM) is transported to the ocean from terrestrial inputs each year (~0.95 Pg C per year) and undergoes a series of abiotic and biotic reactions, causing a significant release of CO2. Combined, these reactions result in variable DOM characteristics (e.g., nominal oxidation state of carbon, double-bond equivalents, chemodiversity) which have demonstrated impacts on biogeochemistry and ecosystem function. Despite this importance, however, comparatively few studies focus on the drivers for DOM chemodiversity along a riverine continuum. Here, we characterized DOM within samples collected from a stream network in the Yakima River Basin using ultrahigh-resolution mass spectrometry (i.e., FTICR-MS). To link DOM chemistry to potential function, we identified putative biochemical transformations within each sample. We also used various molecular characteristics (e.g., thermodynamic favorability, degradability) to calculate a series of functional diversity metrics. We observed that the diversity of biochemical transformations increased with increasing upstream catchment area and landcover. This increase was also connected to expanding functional diversity of the molecular formula. This pattern suggests that as molecular formulas become more diverse in thermodynamics or degradability, there is increased opportunity for biochemical transformations, potentially creating a self-reinforcing cycle where transformations in turn increase diversity and diversity increase transformations. We also observed that these patterns are, in part, connected to landcover whereby the occurrence of many landcover types (e.g., agriculture, urban, forest, shrub) could expand DOM functional diversity. For example, we observed that a novel functional diversity metric measuring similarity to common freshwater molecular formulas (i.e., carboxyl-rich alicyclic molecules) was significantly related to urban coverage. These results show that DOM diversity does not decrease along stream networks, as predicted by a common conceptual model known as the River Continuum Concept, but rather are influenced by the thermodynamic and degradation potential of molecular formula within the DOM, as well as landcover patterns.

Yakima Basin Integrated Plan—A collaborative partner's perspective

AbstractResilience to climate change is not a process that can be done single‐handedly. Centring the focus around building both a climate‐resilient system and well‐rounded partnerships, the Kittitas Reclamation District (KRD), Washington State, USA, as part of the Yakima River Basin Integrated Water Resource Management Plan (YBIP), has been successful in mitigating water scarcity in the Kittitas Valley and benefitting the larger Yakima River Basin. By using collaborative governance, a decision‐making process that breaks down barriers and engages people across the boundaries of public agencies, different levels of government and the public, the KRD has modified its long‐term operational goals. The priority is now to establish if a proposed project can provide benefits to other interests and their water needs throughout the Yakima River Basin. We must work together to look at the big picture of a large geographical area in an effort to solve multiple water issues through a single project. As part of YBIP, the goals come to fruition through comprehensive planning for water conservation and the established relationships the partners have with each other. We work together using trust, respect and civility to move towards action and acknowledging that achieving our goals is made possible through collaboration. Opportunities to work together are sought out and taken so that water conservation and other water resiliency projects can be funded and implemented as quickly as possible in an effort to plan for future water scarcity. Protecting the certainty of the water supply for the future of the farms and the ecosystem is of utmost importance.

Scalable deep learning for watershed model calibration

Watershed models such as the Soil and Water Assessment Tool (SWAT) consist of high-dimensional physical and empirical parameters. These parameters often need to be estimated/calibrated through inverse modeling to produce reliable predictions on hydrological fluxes and states. Existing parameter estimation methods can be time consuming, inefficient, and computationally expensive for high-dimensional problems. In this paper, we present an accurate and robust method to calibrate the SWAT model (i.e., 20 parameters) using scalable deep learning (DL). We developed inverse models based on convolutional neural networks (CNN) to assimilate observed streamflow data and estimate the SWAT model parameters. Scalable hyperparameter tuning is performed using high-performance computing resources to identify the top 50 optimal neural network architectures. We used ensemble SWAT simulations to train, validate, and test the CNN models. We estimated the parameters of the SWAT model using observed streamflow data and assessed the impact of measurement errors on SWAT model calibration. We tested and validated the proposed scalable DL methodology on the American River Watershed, located in the Pacific Northwest-based Yakima River basin. Our results show that the CNN-based calibration is better than two popular parameter estimation methods (i.e., the generalized likelihood uncertainty estimation [GLUE] and the dynamically dimensioned search [DDS], which is a global optimization algorithm). For the set of parameters that are sensitive to the observations, our proposed method yields narrower ranges than the GLUE method but broader ranges than values produced using the DDS method within the sampling range even under high relative observational errors. The SWAT model calibration performance using the CNNs, GLUE, and DDS methods are compared using R2 and a set of efficiency metrics, including Nash-Sutcliffe, logarithmic Nash-Sutcliffe, Kling-Gupta, modified Kling-Gupta, and non-parametric Kling-Gupta scores, computed on the observed and simulated watershed responses. The best CNN-based calibrated set has scores of 0.71, 0.75, 0.85, 0.85, 0.86, and 0.91. The best DDS-based calibrated set has scores of 0.62, 0.69, 0.8, 0.77, 0.79, and 0.82. The best GLUE-based calibrated set has scores of 0.56, 0.58, 0.71, 0.7, 0.71, and 0.8. The scores above show that the CNN-based calibration leads to more accurate low and high streamflow predictions than the GLUE and DDS sets. Our research demonstrates that the proposed method has high potential to improve our current practice in calibrating large-scale integrated hydrologic models.

Adaptation of water resources management under climate change

The rapid growth of demand in agricultural production has created water scarcity issues worldwide. Simultaneously, climate change scenarios have projected that more frequent and severe droughts are likely to occur. Adaptive water resources management has been suggested as one strategy to better coordinate surface water and groundwater resources (i.e., conjunctive water use) to address droughts. In this study, we enhanced an aggregated water resource management tool that represents integrated agriculture, water, energy, and social systems. We applied this tool to the Yakima River Basin (YRB) in Washington State, USA. We selected four indicators of system resilience and sustainability to evaluate four adaptation methods associated with adoption behaviors in alleviating drought impacts on agriculture under RCP4.5 and RCP 8.5 climate change scenarios. We analyzed the characteristics of four adaptation methods, including greenhouses, crop planting time, irrigation technology, and managed aquifer recharge as well as alternating supply and demand dynamics to overcome drought impact. The results show that climate conditions with severe and consecutive droughts require more financial and natural resources to achieve well-implemented adaptation strategies. For long-term impact analysis, managed aquifer recharge appeared to be a cost-effective and easy-to-adopt option, whereas water entitlements are likely to get exhausted during multiple consecutive drought events. Greenhouses and water-efficient technologies are more effective in improving irrigation reliability under RCP 8.5 when widely adopted. However, implementing all adaptation methods together is the only way to alleviate most of the drought impacts projected in the future. The water resources management tool helps stakeholders and researchers gain insights in the roles of modern inventions in agricultural water cycle dynamics in the context of interactive multi-sector systems.

An investigation of coupled natural human systems using a two-way coupled agent-based modeling framework

Improving the understanding of coupled natural human systems (CNHS) can better inform environmental policymaking. We investigated the co-evolution (i.e., bidirectional interactions) issues in CNHS via two-way coupling RiverWare (RW; a river-reservoir routing model) with agent-based models (ABMs, human decision models) in the Yakima River Basin in Washington, US. Results show that coupled models can better capture the historical irrigation diversion (human) and streamflow (nature) dynamics. We further demonstrated the effect of social norms (i.e., the influence of neighbors) among farmers and tested a “water reallocation” scenario to evaluate the influence of water policies on irrigation diversion behaviors. Detailed model structure and parameter uncertainty analysis are suggested to further quantify the benefit of CNHS models in multi-level water resources governance.

A Process-Conditioned and Spatially Consistent Method for Reducing Systematic Biases in Modeled Streamflow

Abstract Water resources planning often uses streamflow predictions made by hydrologic models. These simulated predictions have systematic errors that limit their usefulness as input to water management models. To account for these errors, streamflow predictions are bias corrected through statistical methods that adjust model predictions based on comparisons to reference datasets (such as observed streamflow). Existing bias correction methods have several shortcomings when used to correct spatially distributed streamflow predictions. First, existing bias correction methods destroy the spatiotemporal consistency of the streamflow predictions when these methods are applied independently at multiple sites across a river network. Second, bias correction techniques are usually built on time-invariant mappings between reference and simulated streamflow without accounting for the processes that underpin the systematic errors. We describe improved bias correction techniques that account for the river network topology and allow for corrections that account for other processes. Further, we present a workflow that allows the user to select whether to apply these techniques separately or in conjunction. We evaluate four different bias correction methods implemented with our workflow in the Yakima River basin in the northwestern United States. We find that all four methods reduce systematic bias in the simulated streamflow. The spatially consistent bias correction methods produce spatially distributed streamflow as well as bias-corrected incremental streamflow, which is suitable for input to water management models. We demonstrate how the spatially consistent method avoids creating flows that are inconsistent between upstream and downstream locations, while performing similar to existing methods. We also find that conditioning on daily minimum temperature, which we use as a proxy for snowmelt processes, improves the timing of the corrected streamflow. Significance Statement To make streamflow predictions from hydrologic models more informative and useful for water resources management they are often postprocessed by a statistical procedure known as bias correction. In this work we develop and demonstrate bias correction techniques that are specifically tailored to streamflow prediction. These new techniques will make modeled streamflow predictions more useful in complex river systems undergoing climate change.

Multiple Indicators of Extreme Changes in Snow-Dominated Streamflow Regimes, Yakima River Basin Region, USA

Snow plays a major role in the hydrological cycle. Variations in snow duration and timing can have a negative impact on water resources. Excluding predicted changes in snowmelt rates and amounts could result in deleterious infrastructure, military mission, and asset impacts at military bases across the US. A change in snowpack can also lead to water shortages, which in turn can affect the availability of irrigation water. We performed trend analyses of air temperature, snow water equivalent (SWE) at 22 SNOTEL stations, and streamflow extremes for selected rivers in the snow-dependent and heavily irrigated Yakima River Basin (YRB) located in the Pacific Northwest US. There was a clear trend of increasing air temperature in this study area over a 30 year period (water years 1991–2020). All stations indicated an increase in average air temperatures for December (0.97 °C/decade) and January (1.12 °C/decade). There was also an upward trend at most stations in February (0.28 °C/decade). In December–February, the average air temperatures were 0.82 °C/decade. From these trends, we estimate that, by 2060, the average air temperatures for December–February at most (82%) stations will be above freezing. Furthermore, analysis of SWE from selected SNOTEL stations indicated a decreasing trend in historical SWE, and a shift to an earlier peak SWE was also assumed to be occurring due of the shorter snow duration. Decreasing trends in snow duration, rain-on-snow, and snowmelt runoff also resulted from snow modeling simulations of the YRB and the nearby area. We also observed a shift in the timing of snowmelt-driven peak streamflow, as well as a statistically significant increase in winter maximum streamflow and decrease in summer maximum and minimum streamflow trends by 2099. From the streamflow trends and complementary GEV analysis, we show that the YRB basin is a system in transition with earlier peak flows, lower snow-driven maximum streamflow, and higher rainfall-driven summer streamflow. This study highlights the importance of looking at changes in snow across multiple indicators to develop future infrastructure and planning tools to better adapt and mitigate changes in extreme events.

Adult Sockeye Salmon Responses to Transplanting Upstream of an Impassable Dam

AbstractThe Yakama Nation manages a program for reintroducing Sockeye Salmon Oncorhynchus nerka upstream of Cle Elum Dam in the Yakima River basin. The program involves transplanting of a mix of adult Sockeye Salmon from two middle Columbia River donor stocks, Lake Wenatchee (WEN) and Osoyoos Lake (OSO), with the goal of establishing a self‐sustaining population in the basin. In 2017, a subset of the transplanted population was radio‐tagged and monitored to assess stock‐specific responses to transplanting, including downstream entrainment at Cle Elum Dam (“fallback”) and prespawn mortality. Tagged fish were active during the first 2 weeks after release. Some fish moved upstream into the Cle Elum River and then returned to the reservoir; other fish moved downstream and passed Cle Elum Dam. Movement within the study area diminished during August but increased in September when fish began migrating up the Cle Elum River for spawning. A greater proportion of WEN fish (76.3%) was detected entering the river compared to OSO fish (53.9%). The hazard ratio from a multistate analysis of fish behavior indicated that WEN fish were nine times more likely to enter the river than OSO fish. The WEN fish also initiated upstream movement 3 weeks earlier than OSO fish. We found that 27.0% of all tagged fish were lost to the spawning population through fallback (20.7%) and prespawn mortality (6.3%). Fallback and prespawn mortality occurred for a greater percentage of OSO fish (26.9% and 7.7%) than WEN fish (15.3% and 5.1%), but these differences were not statistically different. These results provide foundational information from the early phase of a reintroduction effort. Continued monitoring will be required as Sockeye Salmon evolve to conditions upstream of Cle Elum Dam, and results from these efforts will provide valuable insights for this reintroduction effort and others in river systems with similar characteristics.

Long‐Term Disconnect Between Nutrient Inputs and Riverine Exports in a Semi‐Arid, Agricultural Watershed: Yakima River Basin 1945–2012

AbstractNutrient budgets are useful tools in addressing impaired water quality from increasing anthropogenic nitrogen (N) and phosphorus (P) inputs to watersheds. Long term analyses can identify temporal ecological responses to past nutrient management strategies. Multidecadal watershed analyses of nutrient dynamics traditionally have been limited to large humid or mesic river basins focused primarily on a single nutrient (N or P). Here we present a long term, dual N and P input‐output budget for the agriculturally rich Yakima River Basin (YRB) located in the semi‐arid western U.S. We quantified N and P terrestrial inputs from 1945 to 2012 using past agricultural and water quality data to investigate interactions between water flow and N and P exports in the YRB. Between 1945 and 2012, N and P inputs to agricultural lands increased by over 18 and 10‐fold, respectively, with synthetic fertilizer accounting for the majority of input increases. While such increases in nutrient inputs were comparable to other U.S. basins, observed riverine N and P export did not significantly increase over time. Rather, we found that since the mid‐1970s both N and P loads and concentrations in the Yakima River have decreased, indicating a temporal disconnect between nutrient inputs and riverine exports in the YRB. This disconnect highlights a need to further investigate nutrient dynamics at local scales in semi‐arid watersheds. Our analysis raises questions about long‐term N and P retention in the YRB and potential impacts on future water quality across the western US.

Can Managed Aquifer Recharge Overcome Multiple Droughts?

Frequent droughts, seasonal precipitation, and growing agricultural water demand in the Yakima River Basin (YRB), located in Washington State, increase the challenges of optimizing water provision for agricultural producers. Increasing water storage through managed aquifer recharge (MAR) can potentially relief water stress from single and multi-year droughts. In this study, we developed an aggregated water resources management tool using a System Dynamics (SD) framework for the YRB and evaluated the MAR implementation strategy and the effectiveness of MAR in alleviating drought impacts on irrigation reliability. The SD model allocates available water resources to meet instream target flows, hydropower demands, and irrigation demand, based on system operation rules, irrigation scheduling, water rights, and MAR adoption. Our findings suggest that the adopted infiltration area for MAR is one of the main factors that determines the amount of water withdrawn and infiltrated to the groundwater system. The implementation time frame is also critical in accumulating MAR entitlements for single-year and multi-year droughts mitigation. In addition, adoption behaviors drive a positive feedback that MAR effectiveness on drought mitigation will encourage more MAR adoptions in the long run. MAR serves as a promising option for water storage management and a long-term strategy for MAR implementation can improve system resilience to unexpected droughts.

Integrating Metapopulation Dynamics into a Bayesian Network Relative Risk Model: Assessing Risk of Pesticides to Chinook Salmon (Oncorhynchus tshawytscha) in an Ecological Context.

The population level is often the biological endpoint addressed in ecological risk assessments (ERAs). However, ERAs tend to ignore the metapopulation structure, which precludes an understanding of how population viability is affected by multiple stressors (e.g., toxicants and environmental conditions) at large spatial scales. Here we integrate metapopulation model simulations into a regional-scale, multiple stressors risk assessment (Bayesian network relative risk model [BN-RRM]) of organophosphate (OP) exposure, water temperature, and DO impacts on Chinook salmon (Oncorhynchus tshawytscha). A matrix metapopulation model was developed for spring Chinook salmon in the Yakima River Basin (YRB), Washington, USA, including 3 locally adapted subpopulations and hatchery fish that interact with those subpopulations. Three metapopulation models (an exponential model, a ceiling density-dependent model, and an exponential model without dispersal) were integrated into the BN-RRM to evaluate the effects of population model assumptions on risk calculations. Risk was defined as the percent probability that the abundance of a subpopulation would decline from their initial abundance (500 000). This definition of risk reflects the Puget Sound Partnership's management goal of achieving "no net loss" of Chinook abundance. The BN-RRM model results for projection year 20 showed that risk (in % probability) from OPs and environmental stressors was higher for the wild subpopulations-the American River (50.9%-97.7%) and Naches (39.8%-84.4%) spring Chinook-than for the hatchery population (CESRF 18.5%-46.5%) and the Upper Yakima subpopulation (21.5%-68.7%). Metapopulation risk was higher in summer (58.1%-68.7%) than in winter (33.6%-53.2%), and this seasonal risk pattern was conserved at the subpopulation level. To reach the management goal in the American River spring Chinook subpopulation, the water temperature conditions in the Lower Yakima River would need to decrease. We demonstrate that 1) relative risk can vary across a metapopulation's spatial range, 2) dispersal among patches impacts subpopulation abundance and risk, and 3) local adaptation within a salmon metapopulation can profoundly impact subpopulation responses to equivalent stressors. Integr Environ Assess Manag 2021;17:95-109. © 2020 SETAC.

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

Irrigated agriculture in snow-dependent regions contributes significantly to global food production. This study quantifies the impacts of climate change on irrigated agriculture in the snow-dependent Yakima River Basin (YRB) in the Pacific Northwest United States. Here we show that increasingly severe droughts and temperature driven reductions in growing season significantly reduces expected annual agricultural productivity. The overall reduction in mean annual productivity also dampens interannual yield variability, limiting yield-driven revenue fluctuations. Our findings show that farmers who adapt to climate change by planting improved crop varieties may potentially increase their expected mean annaul productivity in an altered climate, but remain strongly vulnerable to irrigation water shortages that substantially increase interannual yield variability (i.e., increasing revenue volatility). Our results underscore the importance for crop adaptation strategies to simultaneously capture the biophysical effects of warming as well as the institutional controls on water availability.

Implications of water management representations for watershed hydrologic modeling in the Yakima River basin

Abstract. Water management substantially alters natural regimes of streamflow through modifying retention time and water exchanges among different components of the terrestrial water cycle. Accurate simulation of water cycling in intensively managed watersheds, such as the Yakima River basin (YRB) in the Pacific Northwest of the US, faces challenges in reliably characterizing influences of management practices (e.g., reservoir operation and cropland irrigation) on the watershed hydrology. Using the Soil and Water Assessment Tool (SWAT) model, we evaluated streamflow simulations in the YRB based on different reservoir operation and irrigation schemes. Simulated streamflow with the reservoir operation scheme optimized by the RiverWare model better reproduced measured streamflow than the simulation using the default SWAT reservoir operation scheme. Scenarios with irrigation practices demonstrated higher water losses through evapotranspiration (ET) and matched benchmark data better than the scenario that only considered reservoir operations. Results of this study highlight the importance of reliably representing reservoir operations and irrigation management for credible modeling of watershed hydrology. The methods and findings presented here hold promise to enhance water resources assessment that can be applied to other intensively managed watersheds.

When Should Irrigators Invest in More Water‐Efficient Technologies as an Adaptation to Climate Change?

AbstractThe 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.

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.

Climate change reduces water availability for agriculture by decreasing non-evaporative irrigation losses

Irrigation efficiency plays an important role in agricultural productivity; it affects farm-scale water demand, and the partitioning of irrigation losses into evaporative and non-evaporative components. This partitioning determines return flow generation and thus affects water availability. Over the last two decades, hydrologic and agricultural research communities have significantly improved our understanding of the impacts of climate change on water availability and food productivity. However, the impacts of climate change on the efficiency of irrigation systems, particularly on the partitioning between evaporative and non-evaporative losses, have received little attention. In this study, we incorporated a process-based irrigation module into a coupled hydrologic/agricultural modeling framework (VIC-CropSyst). To understand how climate change may impact irrigation losses, we applied VIC-CropSyst over the Yakima River basin, an important agricultural region in Washington State, U.S. We compared the historical period of 1980–2010 to an ensemble of ten projections of climate for two future periods: 2030–2060 and 2060–2090. Results averaged over the watershed showed that a 9% increase in evaporative losses will be compensated by a reduction of non-evaporative losses. Therefore, overall changes in future efficiency are negligible (−0.4%) while the Evaporative Loss Ratio (ELR) (defined as the ratio of evaporative to non-evaporative irrigation losses) is enhanced by 10%. This higher ELR is associated with a reduction in return flows, thus negatively impacting downstream water availability. Results also indicate that the impact of climate change on irrigation losses depend on irrigation type and climate scenarios.

Habitat restoration incentives for major infrastructure projects

ABSTRACTIncentives for early consideration of habitat restoration measures for major infrastructure projects include public support, streamlined regulatory review, cost savings, and opportunities for innovation. Three case study projects in Washington State are used to demonstrate the benefits of these incentives: the Seattle Department of Transportation Elliott Bay Seawall Project in Seattle; the Washington State Department of Transportation State Route 520 Bridge Replacement and High-occupancy Vehicle Program between Seattle and Bellevue; and the Washington State Department of Ecology/U.S. Bureau of Reclamation Yakima River Basin Integrated Water Resource Management Plan in the Yakima River Basin. In all case studies, project proponents considered habitat restoration early in the design phase, and in some cases, incorporated habitat restoration into the design of the project, allowing them to develop innovative design approaches and partnerships to accommodate multiple stakeholder interests and provide ...

The Value of Heterogeneous Property Rights and the Costs of Water Volatility

The system of prior appropriation in the Western Unites States prioritizes property rights for water based on the establishment of beneficial use, creating a hierarchy where rights initiated first are more secure. I estimate the demand for security in water rights through their capitalization in agricultural property markets in the Yakima River Basin, a major watershed in Washington State. All water rights are satisfied in an average year, so the relative value of secure property rights is a function of water supply volatility and the costs of droughts are predominantly born by those with weak rights. In aggregate, security in water rights does not capitalize into property values at the irrigation district level; however, there is heterogeneity in the premium for secure water rights. The lack of a premium for district‐level water security is robust to a variety of econometric methods to account for correlated district unobservables, and the null result produces an economically significant upper bound on the value to water security for the district. The ability for farmers to adapt to water supply volatility, as well as expectations about water markets and government infrastructure investment, are leading explanations for the lack of an aggregate premium. These explanations are supported by the pattern of heterogeneity in the water security premium.