Journal of The American Water Resources Association最新文献

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.

Resilience is a critical issue for water resource systems. Over the past few decades, these systems have been significantly disrupted by natural disasters and human activities, resulting in substantial economic losses. This study develops a resilience evaluation framework based on a comprehensive literature review and applies it to assess the resilience of the Yangtze River Basin (YRB). The results reveal a significant improvement in the basin's water resources resilience from 2010 to 2023, particularly in the upper and middle reaches. However, the overall resilience level remained below 0.6, indicating moderate resilience. While hydraulic infrastructure improved resilience in the upper and middle sections during dry seasons, it had adverse effects on downstream areas. Economic factors were identified as key contributors to resilience gaps, underscoring their importance in ensuring sustainable water resource management. Critical factors influencing resilience included total water resources, the number of large and medium-sized reservoirs, and urban storage capacity. These findings offer valuable insights for developing targeted strategies and policies to enhance water resource resilience in the YRB.

Accurate identification of groundwater contamination sources is crucial for effective water pollution prevention, yet precise quantitative methods remain limited. This study investigates the sources of groundwater contamination in the Hutuo River area, a region heavily influenced by human activities, using hydrochemical analysis, the positive matrix factorization (PMF) model, and geostatistical methods. The findings reveal that the groundwater is slightly alkaline, with total hardness (TH) and nitrate (NO₃⁻) concentrations exceeding standards at rates of 81.5%–85.2% and 44.4%–59.3%, respectively, indicating significant human impact. Based on hydrochemical methods, it has been identified that SO₄²⁻ in groundwater primarily originates from the dissolution of gypsum, while Ca²⁺ and Mg²⁺ mainly come from the dissolution of carbonates. NO₃⁻ is predominantly sourced from fertilizers and sewage. The PMF model identifies industrial wastewater, domestic sewage, water−rock interactions, and nonpoint source pollution as the primary sources. Domestic and industrial sewage contribute 44.1%, 34.9%, and 28.3% to groundwater pollution during the dry, flood, and normal water seasons, respectively, while industrial sewage contributes 24.1%, 19.2%, and 20.9%. Our research findings provided a scientific basis for preventing the deterioration of groundwater quality and protecting the ecological environment in areas strongly affected by human activities.

A set of analytical equations has been derived to directly quantify the average hydrologic performance of low-impact development facilities such as bioretention cells and green roofs. These analytical equations, collectively referred to as the analytical probabilistic stormwater models (APSWMs), have been previously validated for representing regional rainfall conditions for regions across the US using selected example locations. This study evaluates APSWMs' capability to accurately represent small temporal changes in rainfall conditions at the same locations and small spatial changes in rainfall conditions between nearby locations. Results from the US EPA's Stormwater Management Model (SWMM), a continuous simulation tool representing rainfall conditions using long-term observed series, are used as the basis for comparisons. For the 176 hypothetical cases of bioretention cells and 208 cases of green roofs, the temporal performance differences between early and recent periods as determined by APSWM and SWMM were within ±0.03 for green roofs and up to ±0.08 for bioretention cells, while the spatial performance differences between paired locations averaged about 3% in relative terms. These results demonstrate that APSWM is capable of consistently and accurately representing the small spatial and temporal rainfall-condition changes. They also provide additional evidence of APSWMs' reliability and support jurisdictions to use APSWMs in the planning and design of LID facilities.

Sea level rise and storm surges resulting from climate change are expected to increase the frequency and intensity of floods. Aging and/or inefficient drainage systems can significantly exacerbate flood damage. Effective flood defense policies must categorize flood damage and provide a detailed assessment of each contributing factor. In this study, we evaluated the cost of flood damage in Busan—the second most populous city on the coast of South Korea. Flood damage costs were analyzed based on an object-based approach across 10 scenarios, which accounted for variations in storm surge frequency, climate change impacts, and drainage efficiency. Flood damage costs for four categories, namely buildings, agriculture, human casualties, and vehicles, were examined across different administrative regions. Results reveal that flood damage costs increase with higher storm surge frequencies and climate change effects, while reduced drainage efficiency further amplifies these costs. Given that damage costs are predominantly concentrated in coastal areas, future data-based flood defense policies should be developed to reflect the specific vulnerabilities and damage patterns of each administrative region.