Journal of The American Water Resources Association最新文献

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.

The complementary relationship of evapotranspiration (CRE) hypothesis has been widely used to estimate actual evapotranspiration (AET) indirectly under various climatic conditions. However, its applicability in monsoon-dominated regions remains underexplored. This study investigates the dynamics of potential evapotranspiration (PET) and AET in the Yongdam dam basin, a representative monsoon climate region in Korea, using flux tower observations and meteorological data. PET and wet-environment evapotranspiration (WET) were calculated using the FAO Penman–Monteith and Priestley–Taylor equations, respectively. Our findings reveal significant deviations from the expected CRE pattern in monsoon regions due to the dominant influence of external air mass inflow, which disrupts the correlation between soil moisture and atmospheric humidity. These results empirically demonstrate the deviation of the CRE hypothesis in monsoon climates, emphasizing the need for region-specific evaluations of evapotranspiration dynamics. This study provides critical insights into evapotranspiration processes, offering valuable directions for refining hydrological models and improving water resource management in dynamic climatic regions.

Access to safe and sustainable wastewater treatment is a challenge for many people in the United States. Data describing the location and status of wastewater infrastructure are critical for addressing infrastructure gaps. Onsite wastewater treatment systems (OWTSs) are an important component of wastewater infrastructure; however, there is a dearth of available OWTS data across the United States, making it difficult to locate, evaluate, maintain, and improve wastewater systems. Where data are available, it can be an arduous task to acquire and transform them into usable formats. Thus, the purpose of this study was to create an interactive inventory of OWTS data to increase data accessibility and inform the development of a national OWTS data repository. Here, we identified (1) where OWTS data are available and (2) the attributes of available data (e.g., data format). We conducted an iterative internet search for OWTS data at state and local scales (by county, or town in Connecticut) in all 50 states. We discovered that OWTS data were available at parcel resolution for 41% of the United States and 30% of the contiguous United States (by area). The resulting inventory can be accessed at https://aub.ie/owtsdatainventory and will increase accessibility to currently available data for the OWTS community, from OWTS professionals to regulators to scientific researchers. Additionally, this work provides commentary on potential data challenges and the next steps necessary in building a complete national OWTS database.

Urban stormwater runoff is a major concern for water quality. Impervious surfaces, especially in urban environments, can allow stormwater direct access to receiving waterbodies and make up nearly 90% of land cover in downtown Minneapolis, Minnesota. A study of stormwater runoff from impervious surfaces in downtown Minneapolis, Minnesota, USA, was conducted to understand the potential impacts of different types of impervious surfaces (i.e., streets, sidewalks, parking lots, and rooftops). A rainfall simulator delivered water to the street, sidewalk, and parking lot sites and the rooftop runoff characteristics were studied separately using automated samplers and rain gauges. ANOVA statistical analysis was used to determine whether stormwater runoff pollutant concentrations (chloride, total suspended solids, and total phosphorus) varied significantly within surface types, between surface types, and across seasons. Results showed that the first flush of runoff contained higher pollutant concentrations than the whole rain event, and water quality differences for all surfaces were relatively minor for the summer and fall seasons. In contrast, pollutant concentrations were significantly higher in the spring, particularly on streets. Among all surface types, streets exhibited the highest event-mean concentrations (EMCs) for all pollutants. The study highlights the importance of surface-specific stormwater management strategies and the need for tailored BMP design and policies to enhance the effectiveness of mitigating water quality impairments in urban environments.