ABSTRACT Terminal basins provide unique aquatic environments that are often highly sensitive to streamflow contributions, making them a focal point for environmental water management. However, the water needs for terminal lake, wetland, and river ecosystems, and how they relate, remain a fundamental knowledge gap that constrains our ability to efficiently manage these globally critical and imperiled systems. Recent efforts to increase inflows to Great Salt Lake (GSL) and reverse lake decline underscore the need to simultaneously consider environmental water needs for contributing rivers and peripheral wetlands, so water dedicated and delivered to GSL can achieve additional ecological benefits to the larger basin as a whole. This paper introduces a functional flows framework for the GSL basin, USA. Functional flows are specific components of the annual hydrograph and interannual hydrologic variability that are critical to aquatic ecosystem health. We conceptually characterize functional flows and associated hydrologic metrics for GSL basin's rivers and wetlands and then quantify functional flow metrics for reference stream gages on rivers across the basin. Finally, we discuss how a functional flows approach could help address persistent environmental water management challenges in the GSL basin related to coordination, adaptive management, and resource constraints. Functional flows provide a framework for consistently and transparently quantifying when, where and how much water is needed to achieve critical environmental functions in upland rivers and wetlands as well as GSL itself.

ABSTRACT Hydroclimate change is stressing dams and their management, altering the benefits, costs, and risks of built water infrastructure for people and the environment. Removing obsolete dams and barriers may hold promise as a nature‐based solution to adapt to climate change‐related events, including more severe droughts and floods. While most dam removal studies describe the impacts of dams on people and the environment, few studies directly connect removal with climate change, resilience, or adaptation. To explore the potential link between dam removal and climate resilience, we reviewed 50 studies and reports, including peer‐reviewed and gray literature. We interpret climate resilience broadly, encompassing environmental, economic, engineering, social, and cultural criteria. Removing dams and barriers enhances climate resilience by reconnecting rivers, enhancing fisheries, cooling stream temperatures, and providing access to stream temperature refuges, and reducing risk where changing hydrology exceeds dam design standards. We highlight several cases where dams and barriers have already been removed to improve climate resilience and identify over 70 unique metrics of climate resilience. There is no universal approach for measuring resilience, as river systems and objectives vary. Many dams are instrumental for flood risk reduction, water supply reliability, hydropower generation, water temperature management, novel ecosystems, and blocking dispersal of invasive species. Research linking dam removal to climate resilience is still emerging and is essential for prioritizing the removal of unsafe, underperforming, and obsolete dams, thereby directing funding for maintaining and rehabilitating valuable water infrastructure to withstand extreme climate events. This article is categorized under: Science of Water > Water and Environmental Change Engineering Water > Sustainable Engineering of Water

Irrigation organizations (IOs) in the arid US West manage water supply, own water rights, and deliver water shares to their users. In delivering most of the water used for irrigated agriculture, the influence of the water managers who run them on water futures cannot be overstated. Yet, the perspectives of both water managers and IOs regarding nimble strategies for water management under scarcity remain understudied. One water management strategy, water banking, was introduced in Utah in 2020, but formal uptake has been slow. Using data collected from individual agricultural water managers within IOs in Utah, we show that water managers are familiar with water markets, but that they do not believe their IOs are interested in increasing the number they engage in. Further, we find that most IOs would have little to no water to place in a future water bank, and that over half of the water managers surveyed believe none of their shareholders would be interested in participating. Finally, government meddling, fear of forfeiture, and economic impacts are all barriers to banking, but water infrastructure improvements might act as bridges to finding more "wet" water for banking and other transactions. This study helps clarify whether and how water markets might be integrated into a more secure water future for Utah and the arid West. While water banking remains one tool for flexible and adaptive water management, we underscore that barriers to banking may limit its uptake in Utah.

Road-crossing structures limit organism movement, but their passabilities are rarely measured because they are numerous and time-consuming to survey. Instead, road-crossing passability could be treated in one of four ways: assuming equal passability at all locations (uniform method), assigning random passability values sampled from barrier surveys (random sample method), using remote sensing data to infer presence (presence/absence method) or rate passability (rating category method). Each prediction method produces different passability estimates for individual barriers, but how these differences affect river connectivity estimates has not been systematically evaluated. We compared river connectivity estimates from these four road-crossing passability prediction methods in the Bear River Basin, USA. We parameterized barrier passability methods with Bonneville Cutthroat Trout Oncorhynchus clarkii utah passage survey data at 140 road crossings. Road crossings blocked fish passage at 37% of survey locations. Those road-crossing barriers that obstructed fish movement also decreased the proportion of connected reaches in the river network from 12% (with dams and all road crossings assumed to be passable) to just 3%. All passability prediction methods produced similar results and had considerable uncertainty predicting passability for individual barriers. Our findings suggest that simpler methods, like uniform or random sample road-crossing passability predictions, are sufficient to characterize river connectivity. Our work highlights the importance of identifying road crossings that act as barriers to organism passage and identifies critical limitations to predicting barrier status for connectivity analysis and conservation planning.

Study region: California, United States. Study focus: In California, historical water system channelization disturbed the natural water system, making agricultural and wetland deliveries share the same water supply system. Climate change has intensified the competition between agricultural and environmental water uses. In the face of escalated climate change, this study tackles the critical challenge of optimizing water allocation to balance the needs of agriculture and the environment. A landscape-level, implicit stochastic deterministic linear hydro-economic optimization model is used with limited foresight to evaluate the combined impacts of climate change and water management policies on local water allocation decisions in California. The aim is to provide decision-support information for regional water cost-efficient water reallocation for climate change adaptation. New hydrological insights for the region: Climate change has reshaped water allocation ratios and caused agricultural water use to compromise with environmental water use. In water-scarce regions, the reduction of agricultural water use is most prominent in the wet years of the Mediterranean climate when both agricultural and environmental water use demands are high. The research identified when, where, and how much groundwater recharge benefit is acquired from prioritizing wetland deliveries to inform water use co-benefits and moderate conflicts. Climate change has also increased the overall value and variation across areas in the economic value of water, creating momentum for a cost-efficient market-based water reallocation approach.

Urban flooding presents a global challenge, disproportionately affecting socially vulnerable communities. In the U.S., catastrophic floods are compounded by climate change, aging infrastructure, rapid land development, and population growth. Flooding causes more damage than any other severe weather-related event, with an annual average cost of US $4.5 billion and an average of 17 fatalities per year between 1980 and 2024. FEMA’s outdated 100-year floodplain delineations fail to capture evolving flood risk, leading to development inside and outside of 100-year floodplains and potentially higher flood risk for vulnerable communities. Excluding development in 500-year floodplains would reduce risk, although encroachment of urban development into 500-year floodplains exacerbates risks. Despite extensive coastal flood risk and environmental justice research, few studies have been conducted in inland areas like the Intermountain West. Our study analyzes FEMA’s National Flood Hazard Layer and data from the 2017–2021 American Community Survey to quantify flood injustices in Salt Lake County, Utah. We develop a straight-forward and easily implementable approach for city and county level planning and flood injustice policymaking. Our objectives include assessing demographic attributes within and outside 500-year floodplains, identifying household and population flood injustices, and overlaying 500-year floodplain maps and selected flood injustice variables. Results show that although 44% of Salt Lake County’s 500-year floodplain is in the City of South Salt Lake, the cities of Millcreek and South Jordan emerge as most vulnerable for 500-year flood injustices, these cities have flood risk ratios of 1.92 and 1.67, respectively, where a risk ratio greater than 1.00 indicates potentially concerning flood injustice. These findings highlight observed inequities but do not indicate or prove systematic, intentional, or historical biases resulting from past or present discriminatory policies and practices within these cities. This study contributes to a deeper understanding of flood injustices in inland urban areas, shedding light on the intersection of flood risk and social vulnerability at microscales. Identifying flood injustice communities can inform targeted interventions and policy measures to mitigate flood injustices and enhance flood resilience and adaptation in inland urban areas for vulnerable communities.

Aquatic habitat suitability models are increasingly coupled with water management models to estimate environmental effects of water management. Many types of habitat models exist, but there are no standard methods to compare predictive performance of habitat model types for use with water management models. In this study, we compared three common aquatic habitat model types: a hydraulic-habitat model, a habitat threshold model, and a geospatial model. Each of the models predicted native Bonneville Cutthroat Trout distribution in the Bear River Watershed (Utah, Idaho, and Wyoming, USA) at a monthly timestep. We compared the differences in predictive performance among models by validating 1) environmental predictors of the models with field observations from summer 2022, using the coefficient of determination (R2), Nash-Sutcliffe efficiency (NSE) index, and percent bias (PBIAS) and 2) habitat suitability estimates generated by each model with fish presence data and three accuracy metrics developed for this study. Validation of environmental predictors revealed observed conditions were not well represented by any of the three models-a function of either outdated, incorrect, or over-generalized input data. Validation of habitat suitability predictions using Bonneville Cutthroat Trout presence data showed the habitat threshold model most accurately classified fish presence observations in suitable habitat, but suitable habitat was likely overpredicted. While more precise habitat modeling methods may be useful to support generalized habitat estimates for native fish, overall, simple models, like the habitat threshold model, are promising for incorporating ecological objectives into water management models.

Fish from Cambodia's Tonle Sap Lake are economically, culturally, and nutritionally significant for people in the Lower Mekong Basin, providing income, livelihoods, and protein. Fish in this system generally migrate toward upstream Mekong River in dry season and return in early wet season. However, drivers of fish migration from Tonle Sap Lake to the Mekong River are not well-understood. In this paper, we utilized Mixed Effects Random Forest to predict the catch weight of six fish species migrating from the Tonle Sap Lake to the Mekong River using precipitation, lunar cycle, and hydrologic conditions like river stage, streamflow, flow magnitude, and timing as predictors. As a surrogate for fish migration, we used daily fish catch weight from 2002 through 2008 at the bagnet, or Dai , fisheries along Tonle Sap River, a migration corridor connecting Tonle Sap Lake to the Mekong River. We found that migration of large fish was mainly cued by streamflow and flow magnitude, while smaller fish migrate depending on the combination of streamflow and flow timing. Streamflow less than average cumulative flow was the most important driver for migration of Pangasianodon hypophthalmus , and Cirrhinus microlepis . Migration of Cyclocheilichthys enoplos and Osteochilus melanopleurus was highly dependent on the number of low- and minimum-flow days. Cumulative flows, period of high flow and water level were the main predictors of the small mud-carp Henicorhynchus entmema's migration, while individuals of Labiobarbus leptocheilus migrated out of the Tonle Sap Lake depending on the number of days after 7-, 30-, and 90-day minimum flows. These results suggest that flow characteristics can be used to aid conservation and adaptive management of Cambodia's Dai fisheries.

Groundwater return flow to streams is important for maintaining aquatic habitat and providing water to downstream users, particularly in irrigated watersheds experiencing water scarcity. However, in many agricultural regions, increased irrigation efficiency has reduced return flows and their subsequent in‐stream benefits. Agricultural managed aquifer recharge (Ag‐MAR)—where artificial recharge is conducted via irrigation canals and agricultural fields—may be a tool to recover these return flows, but implementation is challenged by water supply and water management. Using climate‐driven streamflow simulations, an integrated operations‐hydrology model, and a regional groundwater model, we investigated the potential for Ag‐MAR to recover return flows in the Henrys Fork Snake River, Idaho (USA). We simulated potential Ag‐MAR operations for water years 2023–2052, accounting for both future water supply conditions and local water management rules. We determined that Ag‐MAR operations reduced springtime peak flow at the watershed outlet by 10%–14% after accounting for return flows. Recharge contribution to streamflow peaked in July and November, increasing July–August streamflow by 6%–14% and November–March streamflow by 9%–14%. Furthermore, sites where Ag‐MAR was conducted incidental to flood irrigation had more water available for recharge, compared to sites requiring recharge rights, which are junior in priority to agricultural rights. Mean annual recharge volume for the incidental recharge sites averaged 12% of annual natural streamflow, ranged from 269 to 335 Mm3, and was largely available in April and October. We demonstrate Ag‐MAR can effectively recover groundwater return flows when applied as flood irrigation on agricultural land with senior‐priority water rights.

Dams and reservoirs are often needed to provide environmental water and maintain suitable water temperatures for downstream ecosystems. Here, we evaluate if water allocated to the environment, with storage to manage it, might allow environmental water to more reliably meet ecosystem objectives than a proportion of natural flow. We use a priority-based water balance operations model and a reservoir temperature model to evaluate 1) pass-through of a portion of reservoir inflow versus 2) allocating a portion of storage capacity and inflow for downstream flow and stream temperature objectives. We compare trade-offs to other senior and junior priority water demands. In many months, pass-through flows exceed the volumes needed to meet environmental demands. Storage provides the ability to manage release timing to use water efficiently for environmental benefit, with a co-benefit of increasing reservoir storage to protect cold-water at depth in the reservoir. Allocating a proportion of water and storage for the environment allows water to efficiently meet environmental needs. This reduces inefficiencies caused by instream flows exceeding environmental demands.

Irrigated agriculture in semi-arid regions such as the western United States will likely face increased volatility in access to water under climate extremes. Competing water uses including community, tribal, urban and environmental, along with higher-temperature driven increases in irrigation requirements will further the gap between available water and overall system demands. This research explores case studies in three regions of the western United States namely, the southern San Joaquin Valley in California, the Cache Valley in Utah an the Mesilla Valley in New Mexico in terms of their future ability to fulfill agricultural water demands while supporting communities and ecosystems using a web platform. The San Joaquin Valley, chronically affected for decades by groundwater overdraft and demand hardening from permanent crops and livestock wet forages, will necesitate substantial reductions in consumptive use via permanent irrigated land idling to meet sustainable groundwater regulation. We present a wide range of scenarios including trading, deficit irrigation and water supply augmentation along with their economic impacts to explore tradeoffs among alternatives. For the Cache Valley in Utah, environmental flow requirements to regulate levels in the Great Salt Lake may require upstream diversion reductions that will likely affect irrigated forages the most. We present varios crop choice scenarios and water exchange to find least cost alternatives considering downstream sectors such as livestock. The Mesilla Valley in New Mexico, supplied by sufarce water from the Rio Grande and supplemental pumping from the underliying aquifer system in dry years, may see an overall allocation reduction presenting challenges for their high value vegetable and tree crops. We examine the impact of potential groundwater regulation and markets to secure future water access for agriculture and competing sectors.

Hydropower dams are a source of renewable energy, but dam development and hydropower generation negatively affect freshwater ecosystems, biodiversity, and food security. We assess the effects of hydropower dam development on spatial–temporal changes in fish biodiversity from 2007 to 2014 in the Sekong, Sesan, and Srepok Basins—major tributaries to the Mekong River. By analyzing a 7-year fish monitoring dataset, and regressing fish abundance and biodiversity trends against cumulative number of upstream dams, we found that hydropower dams reduced fish biodiversity, including migratory, IUCN threatened and indicator species in the Sesan and Srepok Basins where most dams have been constructed. Meanwhile, fish biodiversity increased in the Sekong, the basin with the fewest dams. Fish fauna in the Sesan and Srepok Basins decreased from 60 and 29 species in 2007 to 42 and 25 species in 2014, respectively; while they increased from 33 in 2007 to 56 species in 2014 in the Sekong Basin. This is one of the first empirical studies to show reduced diversity following dam construction and fragmentation, and increased diversity in less regulated rivers in the Mekong River. Our results underscore the importance of the Sekong Basin to fish biodiversity and highlight the likely significance of all remaining free-flowing sections of the Lower Mekong Basin, including the Sekong, Cambodian Mekong, and Tonle Sap Rivers to migratory and threatened fish species. To preserve biodiversity, developing alternative renewable sources of energy or re-operating existing dams to increase power generation are recommended over constructing new hydropower dams.

Generalizable methods that identify suitable aquatic habitat across large river basins and regions are needed to inform resource management. Habitat suitability models intersect environmental variables to predict species occurrence, but are often data intensive and thus are typically developed at small spatial scales. This study estimated mean monthly aquatic habitat suitability throughout Utah (USA) for Bonneville Cutthroat Trout (Oncorhynchus clarkii utah) and Bluehead Sucker (Catostomus discobolus) with publicly available, geospatial datasets. We evaluated 15 habitat suitability models using unique combinations of percent of mean annual discharge, velocity, gradient, and stream temperature. Environmental variables were validated with observed conditions and species presence observations to verify habitat suitability estimates. Stream temperature, gradient, and discharge best predicted Bonneville Cutthroat Trout presence, and gradient and discharge best predicted Bluehead Sucker presence. Simple aquatic habitat suitability models outperformed models that used only streamflow to estimate habitat for both species, and are useful for conservation planning and water resources decision-making. This modeling approach could enable resource managers to prioritize stream restoration across vast regions within their management domain, and is potentially compatible with water management modeling to improve ecological objectives in management models.

Reservoirs are sometimes managed to meet agricultural and other water demands, while also maintaining streamflow for aquatic species and ecosystems. In the Henrys Fork Snake River, Idaho (USA), irrigation-season management of a headwater reservoir is informed by a flow target in a management reach similar to 95 km downstream. The target is in place to meet irrigation demand and maintain aquatic habitat within the 11.4 km management reach and has undergone four flow target assignments from 1978 to 2021. Recent changes to irrigation-season management to maximize reservoir carryover warranted investigation into the flow target assignment. Thus, we created a streamflow-habitat model using hydraulic measurements, habitat unit mapping, and published habitat suitability criteria for Brown Trout (Salmo trutta), Rainbow Trout (Oncorhynchus mykiss), and Mountain Whitefish (Prosopium williamsoni). We used model output to compare habitat availability across two management regimes (1978-2017 and 2018-2021). We found that efforts to minimize reservoir releases in 2018-2021 did not reduce mean irrigation-season fish habitat relative to natural flow, but did reduce overall fish habitat variability during the irrigation season compared to streamflow management in 1978-2017. Field observations for this research led to an adjusted flow target in 2020 that moved the target location downstream of intervening irrigation diversions. Using our model output, we demonstrated that moving the location of the target to account for local irrigation diversions will contribute to more consistently suitable fish habitat in the reach. Our study demonstrates the importance of site selection for establishing environmental flow targets.

Predictive models are widely used to investigate relationships between the distribution of fish diversity, abundance, and the environmental conditions in which they inhabit, and can guide management actions and conservation policies. Generally, the framework to model such relationships is established; however, which models perform best in predicting fish diversity and abundance remain unexplored in the Mekong River Basin. Here, we evaluated the performance of six single statistical models namely Generalized Linear Model, Classification and Regression Tree, Artificial Neural Network, k-Nearest Neighbor, Support Vector Machine and Random Forest in predicting fish species richness and abundance in the Lower Mekong Basin. We also identified key variables explaining variability and assessed the variable's sensitivity in prediction of richness and abundance. Moreover, we explored the usefulness of an ensemble modeling approach and investigated if this approach improved model performance. Our results indicated that, overall, the six single statistical models successfully predicted the fish species richness and abundance using 14 geo-hydrological, physicochemical and climatic variables. The Random Forest model consistently out-performed all single statistical models for predicting richness (R-2 = 0.85) and abundance (R-2 = 0.77); whereas, Generalized Linear Model performed the worst of all models (R-2 = 0.60 and 0.56 for richness and abundance). The most important predictors of variation in both richness and abundance included water level, distance from the sea and alkalinity. Additionally, dissolved oxygen, water temperature and total nitrate were important predictors of species richness, while conductivity was important for fish abundance. We found that species richness increased with increasing water level, dissolved oxygen and water temperature, but decreased with increasing distance from the sea, alkalinity and total nitrate. Fish abundance increased with conductivity, but decreased with increasing distance from the sea, water level and alkalinity. Finally, our results highlighted the usefulness of ensemble modeling (R-2 = 0.90 and 0.85 for richness and abundance) for providing better predictive power than any of the six single statistical models. Our results can be used to support Mekong River management, particularly fisheries in the context of contemporary regional and global changes.

Global warming intensifies the hydrological cycle by altering the rate of water fluxes to and from the terrestrial surface, resulting in an increase in extreme precipitation events and longer dry spells. Prior hydrological intensification work has largely focused on precipitation without joint consideration of evaporative demand changes and how plants respond to these changes. Informed by state‐of‐the‐art climate models, we examine projected changes in hydrological intensification and its role in complicating water resources management using a framework that accounts for precipitation surplus and evaporative demand. Using a metric that combines the difference between daily precipitation and daily evaporative demand (surplus events) and consecutive days when evaporative demand exceeds precipitation (deficit time), we show that, globally, surplus events will become larger (+11.5% and +18.5% for moderate and high emission scenarios, respectively) and the duration between them longer (+5.1%; +9.6%) by the end of the century, with the largest changes in the northern latitudes. The intra‐annual occurrence of these extremes will stress existing water management infrastructure in major river basins, where over one third of years during 2070–2100 under a moderate emissions scenario will be hydrologically intense (large intra‐annual increases in surplus intensity and deficit time), tripling that of the historical baseline. Larger increases in hydrologically intense years are found in basins with large reservoir capacity (e.g., Amazon, Congo, and Danube River Basins), which have significant populations, irrigate considerable farmland, and support threatened and endangered aquatic species. Incorporating flexibility into water resource infrastructure and management will be paramount with continued hydrological intensification.

Public concern over environmental issues such as ecosystem degradation is high. However, restoring coupled human-natural systems requires integration across many science, technology, engineering, management, and governance topics that are presently fragmented. Here, we synthesized 544 peer-reviewed articles published through September 2020 on the desiccation and nascent recovery of Lake Urmia in northwest Iran. We answered nine questions of scientific and popular interest about causes, impacts, stabilization, recovery, and next steps. We find: (1) Expansion of irrigated agriculture, dam construction, and mismanagement impacted the lake more than temperature increases and precipitation decreases. (2) Aerosols from Lake Urmia's exposed lakebed are negatively impacting human health. (3) Researchers disagree on how a new causeway breach will impact salinity, evaporation, and ecosystems in the lake's north and south arms. (4) Most researchers tried to restore to a single, uniform, government specified lake level of 1274.1 m intended to recover Artemia. (5) The Iranian government motivated and funded a large and growing body of lake research. (6) Ecological and limnological studies mostly focused on salinity, Artemia, and Flamingos. (7) Few studies shared data, and only three studies reported engagement with stakeholders or managers. (8) Researchers focused on an integration pathway of climate downscaling, reservoirs, agricultural water releases, and lake level. (9) Numerous suggestions to improve farmer livelihoods and governance require implementation. We see an overarching next step for lake recovery is to couple human and natural system components. Examples include: (a) describe and monitor the system food webs, hydrologic, and human components; (b) adapt management to monitored conditions such as lake level, lake evaporation, lake salinity, and migratory bird populations; (c) improve livelihoods for poor, chronically stressed farmers beyond agriculture; (d) manage for diverse ecosystem services and lake levels; (e) engage all segments of society; (f) integrate across restoration topics while building capacity to share data, models, and code; and (g) cultivate longer-term two-way exchanges and public support. These restoration steps apply in different degrees to other Iranian ecosystems and lakes worldwide.

Drought is a natural hazard that stresses ecosystems, agricultural production, food security, and local economies. Given ongoing hydropower dam development in the Sesan and Srepok Basins, the two most dammed tributaries in the Lower Mekong Basin, characterizing baseline drought events and understanding how dams modify downstream flow is needed to manage water resources and mitigate drought effects. We used the Soil & Water Assessment Tool (SWAT) to estimate streamflow data from 2001 to 2019. For both rivers, we found that runoff varied, but contributed about 75% of streamflow, followed by shallow and deep groundwater, which contributed up to 25%. We used the Standardized Runoff Index to characterize drought and detected frequent, severe, and prolonged drought events in the two basins. Severe and prolonged droughts in the 2009–2011 and 2015–2016 periods corresponded to the occurrence of Typhoon Ketsana and the El Niño-Southern Oscillation. Streamflow alteration can be caused by climatic conditions and anthropogenic activities such as hydropower dam development and operations (e.g., the timing and magnitude of water releases). Results from this study can be used as a baseline to gauge potential future droughts and design appropriate drought management plans to preserve ecosystems and food security in the Lower Mekong Basin and its tributaries.