ABSTRACT Groundwater storage change in the Great Salt Lake Basin (GSLB) is difficult to quantify because monitoring data are uneven. We estimate groundwater storage anomalies over 2002–2024 with five methods: Gravity Recovery and Climate Experiment (GRACE) total water storage minus Global Land Data Assimilation System (GLDAS) land‐surface components (GRACE‐raw); the same with lake and reservoir storage removed (GRACE‐sw); a further correction for GRACE signal leakage, calibrated against in situ data (GRACE‐Lf); the GRACE‐assimilated GLDAS v2.2 product (GLDAS‐2.2); and an in situ reconstruction from groundwater‐level observations (GWDM). Four of the five methods show drawdowns in 2011–2016 and 2019–2022. Surface water, dominated by the Great Salt Lake, accounts for about 31% of the basin's storage signal. A leakage factor of 2.3 indicates that uncorrected GRACE captures less than half of the signal where pumping is concentrated along the Wasatch Front. Over 2011–2016, leakage‐corrected GRACE indicates a groundwater loss of 13.3 ± 7.8 km 3 and the in situ reconstruction 10.1 ± 1.8 km 3 , both consistent with an independent GPS‐based estimate of 10.9 ± 2.8 km 3 . With a calibrated leakage factor, GRACE and GLDAS data can update the basin's storage estimate as new data are released.
ABSTRACT Coastal, low‐lying Onsite Sewage Treatment and Disposal Systems (OSTDS) are increasingly vulnerable to sea‐level rise (SLR) and groundwater inundation. This study developed three spatially explicit GIS‐based multi‐criteria evaluation frameworks: Bathtub‐Current, Bathtub‐Future under 2 ft (0.6 m) of SLR and MODFLOW‐Future under 2 ft (0.6 m) of SLR, which assessed OSTDS vulnerability for current and future SLR and how alternative representations of SLR‐modeled groundwater response affect vulnerability classification and prioritization by integrating SLR responses, depth to water table, saltwater intrusion, recurrent flooding, storm surge and OSTDS density using Delphi elicitation, pairwise comparison weighting and Weighted Linear Combination. At 2 ft of SLR, the bathtub approach reproduced 86% of the MODFLOW inundation extent. The three vulnerability surfaces showed strong agreement, with Pearson correlations of 0.966–0.994 and RMSE values of 0.036–0.077, although individual OSTDS classes differed. At least one framework classified 1961 OSTDS as highly vulnerable, while all three frameworks classified 577 OSTDS as highly vulnerable, among the 56,080 OSTDS evaluated. Results show hydrostatic modeling is an acceptable screening tool for regional vulnerability assessments; however, it is not interchangeable with groundwater modeling or field verification. The framework provides a screening tool with a tiered approach to prioritize monitoring and resource allocation for at‐risk OSTDS.
ABSTRACT Water scarcity driven by climate change and urbanization has intensified interest in decentralized water reuse systems, particularly for residential light graywater (LGW). However, treatment performance data remain scarce, limiting policy development in Colombia. This study compares two integrated bench‐scale graywater treatment trains (GWTT) for LGW reclamation using a synthetic mixture of personal care products and secondary effluent to mimic household contaminants. GWTT1 combined sedimentation, slow sand filtration, ultrafiltration membrane, and ultraviolet disinfection, whereas GWTT2 integrated sedimentation, ozonation, granular activated carbon (GAC) filtration, and UV disinfection. GWTT2 achieved higher organic removal, with 99.6% turbidity and 78% chemical oxygen demand reduction, compared with 95.9% and 71.9%, respectively, for GWTT1. Linear regression indicated that GAC‐to‐biologically activated carbon maturation in GWTT2 (slope of 2.64 percentage points per sampling event, R 2 = 0.74) enabled passive performance gains without operational intervention. Despite a 7% increase in heterotrophic bacteria from GWTT2 biofilm detachment, GWTT1 provided more consistent microbiological control, reducing total coliforms by 91% and E. coli by 96%. These findings support the development of residential water reuse regulations in Colombia by addressing gaps in Resolution 1256 of 2021 and identifying operational trade‐offs for decentralized implementation.
ABSTRACT Rainfall–runoff modeling supports the prediction of potential floods, but accurate estimates depend on high‐quality observations that many watersheds lack, leaving incomplete and gapped runoff records. This study explores whether simulated runoff driven by rainfall generated under plausible atmospheric conditions can help fill such gaps. We focused on the extensive 6648 km 2 Chungju Dam watershed in South Korea, using the Weather Research and Forecasting (WRF) model. Seventeen distinct rainfall scenarios were produced for each annual flood event using various atmospheric configurations, and the Génie Rural à 4 paramètres Horaires (GR4H) model was used to simulate runoff for comparison with observations. The 17 scenarios bracketed the observed peak‐flow magnitudes and timings within the ensemble range, although the WRF rainfall systematically underestimated event totals and peak intensity. Frequency analysis showed that observed quantiles remained within the WRF‐generated range across return periods, but this containment reflects the ensemble spread rather than unbiased skill. These findings suggest that WRF‐generated rainfall can support water‐resources planning in watersheds with incomplete runoff records, provided the WRF rainfall bias is characterized or corrected. This was demonstrated for a large, monsoon‐dominated, comparatively well‐observed watershed; smaller, data‐sparse, or convection‐dominated basins require further validation.
ABSTRACT Low‐flow events trigger water‐supply shortages and supply–demand imbalances in water‐scarce developed basins; assessing their economic losses informs water‐security risk identification and water‐resources regulation. This paper establishes an economic loss assessment framework integrating water supply variability, water demand constraints, and sectoral disparities. Combining a risk loss integral model with Monte Carlo simulation, it quantifies water shortage economic impacts across agriculture, industry, domestic and ecological sectors for China's Yellow River Basin. Scenarios covering typical low flow years, prolonged low flow periods, and multi‐source regulation are constructed for 2022 (baseline) and 2035 (planned) to analyze spatiotemporal loss patterns and mitigation performance. Economic losses rise with low flow severity and spread toward the middle upper reaches. Basin‐wide losses reach 74.66–574.82 × 10 8 CNY for 2022 and 264.11–730.19 × 10 8 CNY for 2035 across 75%, 90%, and 95% inflow frequency scenarios. Losses accumulate markedly during sustained low flow episodes, mainly hitting Inner Mongolia, Ningxia, Gansu and Shaanxi. Supplementary water measures mitigate losses; combined schemes outperform single interventions, yet marginal benefits decline with increasing water supply volumes. Losses are co‐determined by local water endowment, water use structure, alternative water capacity and regulation policies.
