Journal of The American Water Resources Association最新文献

Sulfate concentrations of 500–2700 mg/L are widespread in Los Angeles Basin groundwater and surface waters, often exceeding chloride by factors of three to eight. This sulfate-dominant pattern contrasts with the chloride-driven salinity typical of coastal aquifers influenced by seawater intrusion or marine aerosols. Data from the western San Fernando Valley, Upper Los Angeles River, and Santa Monica Mountains indicate a geologic origin tied to Miocene marine sedimentary rocks of the Monterey, Modelo, and Topanga Formations. Oxidation of diagenetic pyrite and dissolution of secondary gypsum release large sulfate loads to groundwater and streams, confirmed by sulfate isotope signatures consistent with geologic rather than anthropogenic sources. Groundwater discharge contributes substantial sulfate to the Los Angeles River, while springs in the Santa Monica Mountains show similar isotopic values, underscoring the regional extent of this process. This study develops an integrated geochemical model linking marine deposition, microbial reduction, pyrite formation, tectonic uplift, oxidation, gypsum precipitation, and dissolution. The model highlights how geologic processes continue to shape modern groundwater chemistry, provides a framework for interpreting sulfate enrichment in Southern California coastal basins, and emphasizes the need to incorporate geologic sources into water quality management strategies.

The model-then-classify method allows resource managers to set nutrient concentration criteria to achieve biological targets, with a specified level of risk that the target will not be achieved. Because modeling precedes classification, the approach produces comprehensive criteria that apply to all waterbodies in a domain of interest. We demonstrate the approach for New Zealand rivers and periphyton biomass targets. We fitted generalized linear models expressing peak periphyton biomass at 268 monitoring sites as a function of nutrient concentrations (TN or TP) and other variables including site shade, temperature, and hydrology. We used the models to predict biomass along gradients in nutrient concentrations for all rivers nationally. The predictions were inverted and averaged within environmental classes to derive criteria for each nutrient, class, three biomass targets, and shaded or unshaded conditions. The criteria include choices of under-protection risk (UPR), which is the probability the target will be exceeded despite compliance with the criteria. The UPR provides transparency about the societal cost of reducing the risk of not achieving the target. A validation procedure demonstrated that, when concentrations comply with the criteria, the proportion of sites not achieving the target aligns with the UPR. The approach could be applied to other stressors and types of aquatic ecosystems.

Land desertification, a major form of ecosystem degradation, poses severe ecological and socio-economic challenges worldwide. The Xiliao River Basin, located in the semi-arid agro-pastoral transition zone of northern China, has long suffered desertification, making it crucial to clarify its dynamics for ecological restoration. In this study, a Desertification Difference Index (DDI) was reconstructed at 5-year intervals from 1985 to 2025 by integrating Landsat imagery on Google Earth Engine (GEE) with an Albedo–NDVI feature space. Fifteen natural and socio-economic indicators were incorporated into an XGBoost model with SHAP interpretability to quantify nonlinear contributions and factor associations. Results show: (1) desertification intensified from 1985 to 2000, with degraded land expanding 2.74% annually, but reversed in 2001–2025, when recovery exceeded degradation at 3.01% annually; (2) strong spatial heterogeneity was evident, with degradation concentrated in the Horqin Sandy Land, while Chifeng and Tongliao showed recovery; (3) the model achieved high accuracy (test R² = 0.98). SHAP analysis indicated irrigation water use (21.2%), precipitation (15.7%), and grazing (13.5%) dominated 1985–2000, whereas precipitation (26.5%), cropland reduction (16.8%), and soil moisture (14.7%) were key in 2001–2025. These results reveal interactive mechanisms and temporal shifts between climate and human activities, supporting targeted ecological management in semi-arid regions.

Simulating hydrological and sediment conditions in data-scarce regions is a key challenge in hydrology. This study focused on 14 data-scarce tributaries in the Henan boundary area of the Sanmenxia Reservoir. Using methods like parameter transfer, coefficient of variation, and watershed similarity evaluation, we selected data-rich reference watersheds and applied the Soil and Water Assessment Tool (SWAT) model to simulate runoff and sediment yield. Calibrated parameters were then transferred to the study watersheds. Results showed: (1) The Ba River and Hongnongjian River had a similarity of 0.89, while the Jian River and other small watersheds in the area had similarities between 0.75 and 0.95, indicating the Ba River and Jian River were suitable as reference watersheds. (2) The SWAT model simulated runoff and sediment yield for these watersheds from 1960 to 2022, with results calibrated and validated. (3) Transferred parameters were used to simulate runoff and sediment transport in each small watershed, yielding multi-year averages with low errors (1.54% for runoff, 7.1% for sediment). These findings provide valuable references for managing small watersheds in the Sanmenxia Reservoir area.

Floods, one of the most frequent natural disasters in urbanized plain river network regions, have been significantly altered by complex underlying surface changes. However, quantitative assessments of flood responses to various underlying surface factors at the event scale remain limited. This study examines the Changzhou Plain as a case study, analyzing changes in underlying surfaces (land use, river systems, and hydraulic structures) over the past 40 years and evaluating their impacts on flood processes using a coupled flood model. Both the coefficient of determination (R²) and the Nash–Sutcliffe efficiency (NSE) exceeded 0.90 during calibration and validation for the coupled flood model. Significant underlying surface changes, mainly including a 172.07% increase in urban land, a 67.63% decrease in agricultural land, a 7.55% reduction in river density (R_d), and an increase in hydraulic structures to 917. Hydraulic structure operations had a more substantial influence on both the magnitude and spatial distribution of floods compared to land use and river system changes, with their effects intensifying as flood magnitudes increased. These findings enhance the understanding of the impact mechanisms of complex underlying surface changes on flood processes and provide valuable guidance for future flood management.

There is still uncertainty about how agricultural watersheds will respond to changing future climate. This modeling study aims to evaluate different agricultural strategies for reducing runoff and hillslope soil losses in two Minnesota watersheds. The Water Erosion Prediction Project (WEPP) model was implemented to simulate various strategies and adoption rates of cover crops, reduced tillage systems, and perennial crops across the watersheds. Daily weather was simulated for 1965–2019, 2020–2059, and 2060–2099 in CLImate GENerator (CLIGEN) using climate projections from two Coupled Model Intercomparison Project Phase 5 models and three relative concentration pathway (RCP) emission scenarios. Results indicate that the modeled future scenarios will maintain or slightly decrease both runoff and hillslope soil losses in the two simulated watersheds, while steeper agricultural fields will remain at high risk based on the modeled unsustainable erosion rates. Among the agricultural strategies analyzed, the study revealed that integrating perennials into 50%–70% of fields decreased future watershed runoff by 2%–5% and hillslope soil losses by 24%–46%. Reduced tillage also proved substantial reductions in contrast to the negligible effects observed with cover crops. Given the uncertainty in future climate, further research is warranted to expand this type of scenario analysis to other parts of Minnesota and the Midwest USA, helping build better climate resilience into cropping systems.