Search Results (625)

Contamination of drinking water by potentially toxic elements (PTEs) remains a critical public-health concern in Uganda. This systematic review compiled and harmonized quantitative concentrations (mg/L) for key PTEs, lead (Pb), cadmium (Cd), arsenic (As), chromium (Cr), mercury (Hg), copper (Cu), zinc (Zn), nickel (Ni), cobalt (Co), manganese (Mn), and iron (Fe), across various potable and informal water sources used for drinking, including municipal tap water, boreholes, protected and unprotected springs, wells, rainwater, packaged drinking water, rivers, lakes, and wetlands. A comprehensive search of different databases and key institutional repositories yielded 715 records; after screening and eligibility assessment, 161 studies met the inclusion criteria, and were retained for final synthesis. Reported PTE concentrations frequently exceeded WHO and UNBS drinking water guidelines, with Pb up to 8.2 mg/L, Cd up to 1.4 mg/L, As up to 25.2 mg/L, Cr up to 148 mg/L, Fe up to 67.3 mg/L, and Mn up to 3.75 mg/L, particularly in high-risk zones such as Rwakaiha Wetland, Kasese mining affected catchments, and Kampala’s urban springs and drainage corridors. These hotspots are largely influenced by mining activities, industrial discharges, agricultural runoff, and corrosion of aging water distribution infrastructure, while natural geological conditions contribute to elevated background Fe and Mn in several regions. The review highlights associated health implications, including neurological damage, renal impairment, and cancer risks from chronic exposure, and identifies gaps in regulatory enforcement and routine monitoring. It concludes with practical recommendations, including stricter effluent control, expansion of low-cost adsorption and filtration options at household and community level, and targeted upgrades to water-treatment and distribution systems to promote safe-water access and support Uganda’s progress toward Sustainable Development Goal 6. Full article

This paper presents the results of assessing the influence of siltation factors in 23 ponds in one of the most agriculturally developed macro-regions of European Russia—the Central Russian Upland. Key natural and anthropogenic factors determining the intensity of pond siltation have been identified, and a typification of ponds has been developed to predict the rate of accumulation of bottom sediments in them. For the typification, statistical methods such as correlation analysis (Spearman’s coefficient), cluster and factor analysis, and the Random Forest machine learning algorithm were used. Correlation analysis revealed that the percentage of catchment cultivation has a significant effect (r = 0.55, p < 0.01) on the volume of bottom sediments, while soil loss (r = 0.47, p < 0.05) and vertical terrain dissection (r = 0.43, p < 0.05) have a moderate effect. The most important factors in the siltation process are the average slope of the catchment (24.5%), the percentage of cultivated soils (18.8%), and the average annual soil loss (14.1%). All factors were grouped into three clusters, which explained 77.8% of the variance. As a result, four pond types were identified, differing in their dominant limiting factors: pond hydrological characteristics, catchment morphometry, and the degree of anthropogenic transformation of the catchment. Verification of the typification was carried out based on the calculation of annual soil losses considering the sediment delivery coefficient; the discrepancies between the calculated and actual pond sediment volumes were 1.2–10.0%. The proposed approach, which recommends a multi-scale assessment of potential sediment formation volumes using remote sensing data and thematic mapping, offers heuristic potential for identifying the most degraded water bodies. This enables the planning of priority sites and rehabilitation measures for their restoration within the framework of regional soil and water conservation programs. Full article

Achieving sustainable agricultural intensification in inland valleys while limiting the adverse environmental impacts and uncertainties related to water availability requires an analysis of the long-term hydrological behavior of the catchment. Such a task is particularly challenging in West Africa and Benin due to the limited availability of climate and hydrological data. This study evaluates the applicability of the lumped GR4J model for simulating streamflow in three inland valleys of the Sudanian zone of Benin (Lower-Sowé, Bahounkpo and Nalohou). Additionally, we test the reliability of satellite-based rainfall data (GPM-IMERG, CHIRPS or GSMAP) in modeling hydrological dynamics in these small catchments. The results demonstrate that the GR4J model is effective in simulating daily discharge in the three inland valleys (KGE > 0.5 during both calibration and validation periods), with particularly interesting performance in mean-flow conditions. The modeling using GPM-IMERG and GSMAP rainfall data shows mitigated results with acceptable performance at Nalohou and less accurate results at Bahounkpo and Lower-Sowé. CHIRPS emerged as the most consistent among the evaluated products, providing a sound basis for reconstructing general trends and seasonal variations in historical streamflow time series. The approach of combining historical CHIRPS data and the GR4J model provides insights and can support decision-making related to water resource management in terms of resource capacity and volume in the study area. Except for Nalohou (KGE = 0.19 with GPM-IMERG data), we observe limitations in predicting high flows with satellite-based climatic data at Bahounkpo (KGE = 0.02 with GPM-IR) and Lower-Sowé (KGE = −0.01 with CHIRPS), where the near-zero KGE scores indicate marginal improvement over a mean-flow benchmark. Future work should explore how hybrid or flexible modeling approaches can improve the accuracy of runoff simulations in inland valleys, particularly for extreme (low- and high-) flow conditions. Additionally, the analysis of the trends of indicators of hydrological alteration (IHA) must be deepened in these important ecosystems, especially under climate and land-use change scenarios. Full article

This study evaluated the water supply and regulation of the San Pedro River basin, located in the municipality of Puerto Libertador (Córdoba, Colombia), under climate change scenarios, using the SWAT (Soil and Water Assessment Tool) hydrological model. The model was calibrated and validated in SWAT-CUP using the SUFI-2 algorithm, based on observed streamflow series and sensitive hydrological parameters. Observed and satellite climate data, CHIRPS for precipitation and ERA5-Land for temperature, radiation, humidity, and wind, were employed. Climatic data were integrated along with spatial information on soils, land use, and topography, allowing for an adequate representation of the basin’s heterogeneity. The model showed acceptable performance (NSE > 0.6; PBIAS < ±15%), reproducing the seasonal variability and the average flow behavior. Climate projections under RCP 4.5 and RCP 8.5 scenarios, derived from the MIROC5 model (CMIP5), indicated a slight decrease in mean streamflow and an increase in interannual variability for the period 2040–2070, suggesting a potential reduction in surface water availability and natural hydrological regulation by mid-century. The Water Regulation Index (WRI) exhibited a downward trend in most sub-basins, particularly in areas affected by forest loss and agricultural expansion. The WRI showed a downward trend in most sub-basins, especially those with loss of forest cover and a predominance of agricultural uses. These findings provide basin-specific evidence on how climate change and land-use pressures may jointly affect hydrological regulation in tropical Andean–Caribbean basins. These results highlight the usefulness of the SWAT model as a decision-support tool for integrated water resources management in the San Pedro River basin and similar tropical Andean–Caribbean catchments, supporting basin-scale climate adaptation planning. They also emphasize the importance of conserving headwater ecosystems and forest cover to sustain hydrological regulation, reduce vulnerability to flow extremes, and enhance long-term regional water security. Full article

Population growth and agricultural expansion are threatening groundwater resources in the Maze Zenti catchment, Southern Ethiopia. This study evaluated groundwater suitability for drinking and irrigation by analyzing 30 samples using an integrated approach. This approach included GIS-based IDW interpolation, hydrochemical characterization, drinking water quality index, entropy weight, pollution index of groundwater, multivariate statistics, Piper, Gibbs, and Wilcox diagrams, ANOVA, and irrigation indices based on WHO standards. The correlation matrix revealed strong associations between Na⁺-TDS (r = 0.77) and Na⁺-Ca²⁺ (r = 0.68), indicating mineral dissolution, ion exchange, and agricultural inputs as key factors. Weak correlations were found for NO₃⁻ and F⁻, reflecting localized anthropogenic and geogenic influences. Component analysis identified four components explaining 78.2% (wet season) and 81.2% (dry season) of the variance, highlighting mineralization and anthropogenic inputs. Hydrochemical facies were mainly Ca-Mg-HCO₃ with some localized Na-HCO₃, suggesting that rock–water interactions are the primary source of geochemical control. Drinking water quality assessment showed that, during the wet season, 52.8% of the catchment had excellent water quality, 45.8% was good, and 1.4% was poor–very poor. In the dry season, 51.6% was excellent, 47.4% was good, 0.8% was poor, and 0.2% was very poor. The results of the entropy-weighted analysis indicated seasonal improvement, with excellent areas increasing from 13.1% to 31.4% and poor zones decreasing from 7.5% to 3.4%. Irrigation indices (Na%, PI, MAR, SAR) and Wilcox analysis (86.4% C2S1) suggested low sodicity and salinity hazards. This study provides the first integrated seasonal mapping of drinking and irrigation water quality, entropy-weighted water quality, and pollution index for the Maze Zenti catchment, establishing a hydrogeochemical baseline. Overall, groundwater in the area is generally suitable for drinking and irrigation. However, localized monitoring and sustainable land-use practices are recommended to mitigate contamination risks. Full article

Soil erosion remains a critical global concern, yet long-term catchment-scale assessments that explicitly link historical land-use transitions with erosion responses remain limited. This study evaluates how ±240 years record of historical and projected land-use changes influence soil erosion in the Myjava Basin by integrating parcel-level land-use reconstructions from 1787 to 2030 into a distributed USLE-2D framework. R, K, and parcel-based C and P factors were temporally standardized, and LS was derived using an ensemble of four widely applied algorithms. A PCA was applied to quantify the relative contribution of RUSLE factors across time, and all analyses were performed within a reproducible geospatial modelling environment. The results indicated a long-term decline in total erosion of ±78% at the landscape scale and ±60% within arable land from the 19th century to the present, driven mainly by a major reduction in arable land (from ±62% to ±37%) and expansion of forest and shrub vegetation. Despite this decline, persistent hotspots remain concentrated on steep upland slopes with high LS (>10%), while agricultural parcels experienced erosion rates 10–20 times higher than the basin-wide mean across all periods. PCA shows that LS and rainfall erosivity dominate erosion variability (PC loadings ±0.78–0.84), while C and P factors increase in influence in recent and projected periods, contributing up to ±40% of total explained variance. These findings demonstrate that long-term land-use transitions have substantially reduced basin-scale erosion risk. Full article

This study examines the hydrological response of the Klambu Dam Catchment in Central Java, Indonesia, to climatic and land cover changes from 2000–2023, with simulations extending to 2040. Utilizing CHIRPS satellite data calibrated with six ground stations, monthly precipitation and temperature datasets were analyzed and projected via linear regression aligned with IPCC scenarios, revealing a marginal temperature decline of 0.21 °C (from 28.25 °C in 2005 to 28.04 °C in 2023) and a 17% increase in rainfall variability. Land cover assessments from Landsat imagery highlighted drastic changes: a 73.8% reduction in forest area and a 467.8% increase in mixed farming areas, alongside moderate fluctuations in paddy fields and settlements. The Thornthwaite-Mather water balance method simulated monthly discharge, validated against observed data with Pearson correlations ranging from 0.5729 (2020) to 0.9439 (2015). Future projections using Cellular Automata-Markov modeling indicated stable volumetric flow but a temporal shift, including a 28.1% decrease in April rainfall from 2000 to 2040, contracting the wet season and extending dry spells. These shifts pose significant threats to agricultural and aquaculture activities, potentially exacerbating water scarcity and economic losses. The findings emphasize integrating dynamic land cover data, climate projections, and empirical runoff corrections for climate-resilient watershed management. Full article

The impacts of land use on stormwater runoff quality and Best Management Practices to mitigate these impacts have been investigated since the 1970s, yet challenges remain in providing a modeling approach that concomitantly considers contributions from different land use types. In densely developed urban areas, a buildup/washoff approach is often applied, while in rural areas, some type of erosion modeling is employed, as the processes of detachment, entrainment, and transport are fundamentally different. This study presents a coupled modeling approach within PCSWMM, integrating exponential buildup/washoff for impervious surfaces with the Modified Universal Soil Loss Equation (MUSLE) for pervious areas, including construction sites, to characterize water quality in the large mixed urban–rural Sparrovale catchment in Geelong, Australia. The watershed includes an innovative cascading system of 12 online NbS wetlands along one of the main tributaries, Armstrong Creek, to manage runoff quantity and quality, as well as 16 offline NbS wetlands that are tributary to the online system. A total of 78 samples for Total Suspended Solids (TSS), Total Phosphorus (TP), and Total Nitrogen (TN) were collected from six monitoring sites along Armstrong Creek during wet- and dry-weather events between May and July 2024 for model validation. The data were supplemented with six other catchment stormwater quality datasets collected during earlier studies, which provided an understanding of water quality status for the broader Geelong region. Results showed that average nutrient concentrations across all the sites ranged from 0.44 to 2.66 mg/L for TP and 0.69 to 5.7 mg/L for TN, spanning from within to above the ecological threshold ranges for eutrophication risk (TP: 0.042 to 1 mg/L, TN: 0.3 to 1.5 mg/L). In the study catchment, upstream wetlands reduced pollutant levels; however, downstream wetlands that received runoff from agriculture, residential areas, and, importantly, construction sites, showed a substantial increase in sediment and nutrient concentration. Water quality modeling revealed washoff parameters primarily influenced concentrations from established urban neighborhoods, whereas erosion parameters substantially impacted total pollutant loads for the larger system, demonstrating the importance of integrated modeling for capturing pollutant dynamics in heterogeneous, urbanizing catchments. The study results emphasize the need for spatially targeted management strategies to improve stormwater runoff quality and also show the potential for cascading wetlands to be an important element of the Nature-based Solution (NbS) runoff management system. Full article

Hydrological behavior plays a critical role in seasonally dry forest ecosystems, as it underpins water availability for multiple productive activities, including forestry, agriculture, grazing, and urban supply. This study evaluated the hydrological effects of thinning treatments in a semi-arid oak–pine forest of Chihuahua, Mexico, using a Before–After–Control–Impact (BACI) design. Three Micro-catchments (MC) with initially comparable tree density and canopy cover were monitored during the rainy seasons of 2018 (pre-thinning) and 2019 (post-thinning). Thinning treatments were applied at 20% and 60% canopy cover in two MC, while a third remained unthinned as a 100% control. Precipitation and surface runoff were recorded at the event scale, and data were analyzed using Weibull probability models with a log link to capture the frequency and magnitude of runoff events. Precipitation patterns were broadly comparable across years, although 2018 included an extreme storm event (59 mm). In contrast, runoff volumes in 2019 were lower despite marginally higher seasonal rainfall, reflecting the absence of large storms. Statistical modeling indicated that for each additional millimeter of precipitation, mean runoff increased by approximately 12%, although thinning significantly altered baseline conditions. Relative to 2018, mean runoff ratios were 0.087 in the 100% canopy catchment, 0.296 in the 60% treatment, and 0.348 in the 20% treatment, suggesting that reduced canopy cover retained proportionally more runoff than the control. BACI contrasts confirmed that thinned catchments maintained higher proportions of runoff than the unthinned control, although statistical significance was marginal for the 20% canopy treatment. Overall, the study provides ecohydrological insights relevant to the management of semi-arid forest ecosystems. Full article

The vulnerability of reservoirs in Mediterranean regions to eutrophication is attributable to two key factors: strong seasonal hydrological variability and intensive agricultural activity. The present study evaluated the trophic state of 47 reservoirs in the Ebro Basin in Spain using two complementary approaches: the Organisation for Economic Co-operation and Development (OECD) classification system and the criteria set out in Royal Decree (RD) 47/2022. Chlorophyll-a, total phosphorus and transparency data were monitored from 2023 to 2024. While most of reservoirs were classified as oligotrophic to mesotrophic under the OECD thresholds, the RD 47/2022 identified 87% as being at risk of eutrophication. A significant variation in transparency was observed among the different reservoir types (p < 0.05), with high-altitude systems showing higher levels of water transparency. However, chlorophyll-a and total phosphorus had a significant spatial variability, exhibiting only modest correlations. Chlorophyll-a was weakly but significantly correlated to transparency (r = −0.21), while total phosphorus was not significantly associated with either variable, suggesting a decoupling between nutrient availability and phytoplankton biomass. The observed discrepancy between the two classification frameworks is indicative of divergent conceptual approaches (ecological condition versus management risk). It underscores the requirement for integrated monitoring that incorporates chemical, biological and catchment-scale indicators. These findings offer new insight into the trophic dynamics of Mediterranean reservoirs and highlights the importance of adapting regulatory assessment methods to region-specific climatic and hydrological contexts. Full article

Understanding hydrochemical evolution and apportioning pollution sources are prerequisites for effective groundwater protection at the regional scale; nevertheless, the governing processes and anthropogenic drivers in arid regions remain poorly constrained. Here, we present a comprehensive geochemical survey of the Datong River Basin, a representative arid catchment in north-western China. Thirty-seven groundwater samples were analyzed with hydrochemical methods and Positive-Matrix Factorization (PMF) to delineate natural controls and contaminant sources. Results showed that the aquifer is dominated by HCO₃–Ca(Mg) water controlled predominantly by silicate and carbonate weathering, modified locally by evapo-concentration and human activities. Water-quality indices classify 70.3% of the samples as excellent, but spatially restricted degradation is evident. PMF resolved three independent sources: a natural end-member enriched in Mn, Na⁺ and Cl⁻; a mixed source reflecting domestic wastewater, agricultural fertilizers and rock weathering; and an industrial source dominated by Fe. The mixed source contributes most major ions and chemical oxygen demand (COD), whereas the industrial source accounts for 75.7% of total Fe. These findings provide a robust scientific basis for groundwater management and pollution mitigation in arid regions under similar hydrogeological settings. Full article

Understanding how water-quality models perform across different hydrological and biogeochemical contexts is essential for managing nutrient losses in agricultural catchments. This study evaluated SimplyP, a parsimonious phosphorus model, adapted to better represent Irish agricultural catchments and implemented within the flexible Mobius2 framework. Long-term, high-frequency monitoring data from the Agricultural Catchments Programme (ACP) were used for two sites: Ballycanew, a grassland catchment dominated by surface runoff, and Castledockrell, an arable, groundwater-driven catchment. Model calibration and validation were performed for streamflow (Q), suspended sediment (SS), and multiple phosphorus (P) fractions, with performance assessed using Kling–Gupta efficiency (KGE). In Ballycanew, the model reproduced Q, SS, and total P load well, with weaker agreement for total reactive phosphorus (TRP), likely reflecting unaccounted point sources during low flows. In Castledockrell, performance was moderate for Q and SS, but TRP and other P fractions were not adequately captured, highlighting the need for more detailed representation of subsurface P pathways in groundwater-dominated systems. Overall, SimplyP is well-suited to surface-runoff-dominated catchments with conventional phosphorus mobilisation. Its flexible implementation in Mobius2 allows relatively straightforward modifications, such as including groundwater-mediated P processes, to extend applicability to more complex systems. High-resolution ACP datasets were crucial for identifying model strengths and limitations, supporting refinement for improved nutrient management across diverse agricultural landscapes. Full article

Landslides are among the most significant disasters that threaten communities worldwide. This study sampled 384 respondents, using standardized interviews and field observations, to analyze how they perceived the factors influencing the incidence of landslides in the Kivu catchment of Rwanda, especially in landslide-prone areas. This study employs a mixed-methods approach that combines household surveys and interviews with key informants to assess how residents perceive landslide causes, warning signs, and impacts, which were analyzed statistically using SPSS. For further analysis, a binary logistic regression model and chi-square tests were used. The chi-square test findings highlighted that heavy rainfall, inappropriate agricultural practices, steep slopes, deforestation, road construction, earthquakes, and climate change were strongly correlated with landslide occurrence, with a p < 0.05 level of significance, while mining activities were not correlated with landslides. On the other hand, a binary logistic regression model revealed that, among the selected factors influencing landslide occurrence in the Kivu catchment, road construction (B = −0.644; p = 0.014), inappropriate agriculturalpractices (−1.177; p = 0.000), steep slopes (B = −0.648; p = 0.018), deforestation (B = −0.854; p = 0.007), and earthquakes (B = −1.59; p = 0.008) were negatively correlated, while heavy rainfall (B = 1.686; p = 0.000) and climate change (B = 1.784; p = 0.001) were positively correlated, and this was statistically significant for landslide occurrence at a p-value < 0.05. In contrast, mining activities (B = −0.065; p = 0.917) showed a negative coefficient that was statistically insignificant with respect to landslide occurrence in the study area. Future studies should integrate surveys with landslide hazard modeling tools for better spatial prediction of vulnerability and economic losses. Therefore, the findings from this study will contribute to sustainable natural disaster management planning in the western region of Rwanda. Full article

Hydrological droughts represent a growing challenge for northern watersheds in Thailand, where climate change is projected to intensify seasonal water stress and destabilize agricultural productivity and water resource management. This study employed the Composite Hydrological Drought Index (CHDI) to evaluate the spatiotemporal characteristics of future droughts under representative concentration pathway (RCP) scenarios. The findings revealed a pronounced seasonal contrast: under RCP8.5, the CHDI values indicated more severe drought conditions during the dry season and greater flood potential during the wet season. Consequently, the region faces dual hydrological threats: prolonged water deficits and increased flood exposure within the same annual cycle. Drought persistence is expected to intensify, with maximum consecutive drought runs extending up to 10–11 months in future projections. The underlying mechanisms include increased actual evapotranspiration, which accelerates soil moisture depletion, enhanced rainfall variability, which drives the sequencing of floods and droughts, and catchment storage properties, which govern hydrological resilience. These interconnected processes alter the timing and clustering of drought events, concentrating hydrological stress during periods that are sensitive to agriculture. Overall, drought behavior in northern Thailand is projected to intensify in a spatially heterogeneous pattern, emphasizing the need for localized, integrated adaptation measures and flexible water management strategies to mitigate future risks of drought. Full article

Gully is the most visible sign of land degradation, but its effects on runoff and sediment dynamics during snowmelt conditions remain poorly understood. This study monitored a typical gully in the Mollisols region of Northeast China to investigate runoff and sediment transport at the Gully Head (GH) and Gully Tail (GT) during spring snowmelt. Results showed that gully significantly influenced snow distribution, with deeper snow accumulation than on slopes. Runoff at the GH lasted 9 days, while gully connectivity extended catchment runoff by 10 additional days. Runoff temporal variation at GH and GT was broadly consistent, with GH contributing 7.4% of the total runoff at GT. Peak runoff discharge and sediment concentration occurred on the sixth day after snowmelt onset, driven by snow cover and air temperature. Gully significantly increased the sediment concentration from the upslope runoff. Runoff responses to temperature varied by melt stage, with GT showing higher sensitivity, especially under high-runoff conditions. High sediment yield was linked not to snow depth, but to late-stage snowmelt and soil thawing, when erosion sensitivity peaked. Hysteresis analysis revealed dominant clockwise loops during this phase, contrasting with figure-eight and counterclockwise patterns in other stages. These findings highlight the importance of targeting erosion control during late snowmelt when runoff intensifies and soils thaw. Full article