Journal of The American Water Resources Association最新文献

Across the United States, policymakers are busy developing incentive programs and mandatory policies to speed up adoption of consolidations and reduce the number of regulated water systems. Little attention, however, has been paid to why water system managers themselves, whose cooperation, if not leadership, is often required, pursue consolidation and how they characterize the benefits. Here we leverage novel, representative data from the California Water System Consolidation Survey to shed light on these questions. We find that consolidation is motivated by a diverse array of concerns within and among projects. In 80% of cases, managers reported benefits pertaining to their motivations, suggesting an overall high level of effectiveness. One exception is motivations related to technical, managerial, and financial capacity for which respondents reported fewer related benefits. Many also reported additional benefits beyond those specifically related to their motivations. We identify several factors that are associated with increased consolidation effectiveness and with specific benefits including geographic isolation of the systems, previous relationships between water systems, and water system initiation of consolidation. The results highlight opportunities to advance beneficial, community-driven projects as well as challenges meriting scholarly and policy attention, including the need to align consolidation rhetoric with the priorities and experiences of managers themselves.

The agriculture sector is a significant consumer of water, and sustainable water use begins with monitoring irrigated land. Delineating irrigated land supports decision-makers and promotes the sustainable use of this crucial resource. This study focuses on the Nubian Sandstone Aquifer System (NSAS), the largest aquifer in the world, which spans Egypt, Sudan, Libya, and Chad. Built upon long-term satellite remote sensing observations, the study aims to: (1) quantify the increase in irrigated hectares (both pivot and non-pivot) during the last decade; (2) identify major irrigated crop types and their water requirements; and (3) quantify the increase in crop water use from the NSAS from 2000 to 2024. The findings indicate that irrigated areas fluctuate over time, but the overall irrigated area under the NSAS has increased. The total irrigated area nearly doubled from 14,635 km² in 2000 to 24,811 km² in 2024, while the area irrigated directly from the NSAS increased from 1257 to 3268 km² over the same period. Correspondingly, crops water use from the NSAS increased from an estimated 1.4 km³ in 2000 to 3.64 km³ in 2024. These results have important implications for water and land use, and policymakers in NSAS to ensure the sustainable use of these vital resources for the present and future generations.

Stream assessments are needed to inform regulatory decisions, mitigation and restoration design, and other management practices. Many methods have emerged to meet regional needs and specific management contexts. The number of available approaches creates confusion over the relative merits of methods and appropriate use cases. Furthermore, the complexity of these approaches ranges from rapid evaluations requiring minutes to complete to detailed methods needing weeks of effort. However, the level of effort associated with approaches is rarely tracked for method selection. Differences in measurement metrics and data collection create obstacles to consistent, meaningful comparisons across methods and regions. We compiled and analyzed 188 stream assessment methods, revealing four core challenges: (1) inefficient identification of methods, (2) diverse metrics for ecosystem condition, (3) a wide range of resource needs, and (4) limited comparability of results. While geomorphic (59%) and biological (46%) metrics are common, few methods (5%) comprehensively evaluate a broader set of ecosystem functions. Although many methods exist, the most pressing challenges in stream assessment are choosing appropriate methods, ensuring adaptability, and enabling comparability. Finally, we identify recommendations for improving the practice of stream assessment, including clearer guidance and standardized protocols for assessment.

The study is focused on the evaluation of multi-site and multi-variable calibration of the Soil and Water Assessment Tool model. The variables used for the multi-calibration approach comprised snow water equivalent, soil water content, and discharge. The calibrated model was further used to investigate the influence of small water reservoirs on the runoff regime in the Upper Vydra catchment, Czech Republic (89.9 km²). The multi-calibration approach led to significantly improved estimation of snow accumulation/melt, soil water storage, as well as discharge at incorporated subbasins. The values of the Nash-Sutcliffe coefficient in the validation period improved from 0.65 to 0.82 for snow water equivalent, from −25.6 to 0.13 for soil water storage, and from 0.39 to 0.41 for discharge on average for all measuring stations. At the expense of the multi-calibration approach, the Nash-Sutcliffe coefficient decreased from 0.61 to 0.53 for discharge simulation in the closing profile. Due to their small storage volumes, the small water reservoirs had a modest effect on mitigating low-flow conditions. In two pronounced drought periods in 2015 and 2018, the number of days with the discharge below minimum sustainable flow was reduced by 7 and 8 days, respectively. The volume of four inspected peak flows was reduced by less than 1%, indicating minimal impact of the reservoirs when used as the only flood mitigation measure.

The U.S. Geological Survey is developing nationally consistent water-use modeling approaches to replace previous methods relying on locally specific reported and estimated data. These national assessments require datasets that incorporate water withdrawal variability across the United States and over long periods. However, source data often have unclear definitions, missing or varied units, differing temporal resolutions, varied data quality, and inconsistent formats, which hinder automation and require individualized processing. The public-supply datasets described in this paper were used in machine learning models to estimate annual and monthly public-supply water use for 2000–2020 for the conterminous United States (CONUS) and in a model to estimate public-supply deliveries. Public-supply withdrawal data were acquired for the CONUS and the District of Columbia; however, 11 states had annual data for only 1 year, and 10 states had no monthly data. Annual withdrawal data were acquired for 81% of public-supply water service areas, and monthly withdrawal data were acquired for 47% for at least 1 year from 2000 to 2020. These datasets and methods provide the most comprehensive collection of reported public-supply withdrawals to date and can be used by water-use managers, the scientific community, and the broader public. The extensive data processing described herein can be applicable to datasets representing other categories of water use.

The lower Yellow River is a key watershed between the Haihe and Huaihe Rivers. The Kaifeng section, as a key river segment, holds significant geographical and ecological importance, and studying its shallow groundwater hydrochemistry is crucial for sustainable groundwater use. This study systematically analyzes the hydrochemical characteristics of shallow groundwater in the region using methods like Piper diagrams, Gibbs plots, ion ratios, and mathematical analysis to elucidate groundwater formation mechanisms, thereby filling a critical gap in systematic research on the influence of the Yellow River on adjacent groundwater systems. The findings show that shallow groundwater in the Kaifeng section is weakly alkaline, dominated by $��{\mathrm{HCO}}_3^{-}�$, Ca²⁺, Na⁺, and Mg²⁺, with HCO₃-Ca (Mg, Na) type water accounting for 88.7%. The main hydrochemical mechanism is water-rock interaction, with silicate and carbonate minerals as the primary sources. Moreover, groundwater composition is significantly influenced by lateral seepage from the Yellow River, especially on $��{\mathrm{HCO}}_3^{-}�$, Na⁺, and Ca²⁺ concentrations. $��{\mathrm{HCO}}_3^{-}�$ accounts for > 65.0% of anions, and Na⁺ + Ca²⁺ exceed 75.0% of cations. Groundwater recharge mainly comes from precipitation and river inflow. The ratios of $��{\mathrm{HCO}}_3^{-}�$, Na⁺, and Ca²⁺ indicate that Yellow River seepage influence diminishes with distance, while rainfall impact increases.