Search Results (236)

Heavy metals are a major cause for concern in relation to water systems, due to their high toxicity at elevated levels. The metals can originate from both natural processes, including geological weathering and volcanic activity, as well as anthropogenic activi-ties such as industrial discharges, agricultural runoff, mining, and urbanization, which significantly contribute to water pollution and environmental degradation. The as-sessment of these risks is crucial for protecting public health, especially in populations reliant on contaminated water sources. Exposure to such contaminants can result in severe health consequences, including neurological impairments, organ deterioration, and an elevated risk of cancer. To conduct this assessment study, six surface water sampling sites were selected (i.e., S1 (Gobia), S2 (Kouamefla), S3 (Benkro), S4 (Dou-kouya), S5 (Doka), and S6 (Zengue)) due to their proximity to mining activities. We used the hazard quotient (HQ) and hazard index (HI) methods to estimate the levels of non-carcinogenic health risk associated with heavy metals. Then, the assessment of carcinogenic health risk was carried out using the Incremental Lifetime Cancer Risk (ILCR) methods. First, the highest ILCR total values were observed in the Doya locality (i.e., 0.4237 for the children and 0.5650 for the adults) and during the great dry season (i.e., 0.4333 for the children and 0.5743 for the adults). These findings highlight that populations in this locale experience heightened exposure during the period of the Great Rainy Season. The results indicated that the population exposed to Cd and Hg may experience health concerns irrespective of season and locality. For As and Pb, risks are present in both seasons (i.e., Short Dry Season (SDS) and Short Rainy Season (SRS)). On the other hand, the HIs are well above 1, indicating that the population may be exposed to non-carcinogenic diseases associated with the metals, regardless of the season or locality. To further explore the results, the assessment by ILCR was em-ployed, which demonstrated that for all the designated localities, the ILCRs of As and Cd are well above 10⁻⁴ for the entire population, indicating that the population con-suming this water may develop major carcinogenic risks. In addition, the highest ILCR values were obtained for Cd, regardless of the age group. It should be noted that sea-sonal variation had no significant effect on the trend in ILCRs determined for the en-tire population. Full article

The reducing streamflow is a major concern in the Yilong Lake Basin (YLB), which supplies water for agriculture and the growing population in the basin and to maintain the health of the regional ecosystem. The YLB has experienced remarkable land use/land cover change (LUCC) and climate change (CC) in recent years. To understand the drivers of the streamflow change in this basin, the effects of the land use change and climate variation on the temporal flow variability were studied using the Soil and Water Assessment Tool (SWAT). The calibration and validation results indicated that the SWAT simulated the streamflow well. Then the streamflow responses to the land use change between 2010 and 2020 and climate change with future climate projections (SSP245, SSP370, and SSP585) were evaluated. Results showed that the LUCC in the YLB caused a marginal decline in the annual streamflow at the whole basin scale but significantly altered rainfall–runoff relationships and intra-annual discharge patterns; e.g., monthly streamflows decreased by up to 3% in the dry season under the surface modification, with subbasins of the YLB exhibiting divergent responses attributed to spatial heterogeneity in land surface transitions. Under future climate scenarios, streamflow projections revealed general declining trends with significant uncertainties, particularly under high-emission pathways, e.g., SSP370 and SSP585, in which the streamflow could be projected to reduce by up to 5.9% in the mid-future (2031–2045). In addition, droughts were expected to intensify, exacerbating seasonal water stress in the future. It suggests that integrated water governance should synergize climate-resilient land use policies with adaptive infrastructure to address regional water resources challenges. Full article

Sustained reductions in terrestrial water storage (TWS) have been observed globally using Gravity Recovery and Climate Experiment (GRACE) satellite data since 2002. However, the underlying mechanisms remain incompletely understood due to limited record lengths and data discontinuity. Recently, explainable artificial intelligence (XAI) has provided robust tools for unveiling dynamics in complex Earth systems. In this study, we employed a deep learning technique (Long Short-Term Memory network, LSTM) to reconstruct global TWS dynamics, filling gaps in the GRACE record. We then utilized the Local Interpretable Model-agnostic Explanations (LIME) method to uncover the underlying mechanisms driving observed TWS reductions. Our results reveal a consistent decline in the global mean TWS over the past 22 years (2002–2024), primarily influenced by precipitation (17.7%), temperature (16.0%), and evapotranspiration (10.8%). Seasonally, the global average of TWS peaks in April and reaches a minimum in October, mirroring the pattern of snow water equivalent with approximately a one-month lag. Furthermore, TWS variations exhibit significant differences across latitudes and are driven by distinct factors. The largest declines in TWS occur predominantly in high latitudes, driven by rising temperatures and significant snow/ice variability. Mid-latitude regions have experienced considerable TWS losses, influenced by a combination of precipitation, temperature, air pressure, and runoff. In contrast, most low-latitude regions show an increase in TWS, which the model attributes mainly to increased precipitation. Notably, TWS losses are concentrated in coastal areas, snow- and ice-covered regions, and areas experiencing rapid temperature increases, highlighting climate change impacts. This study offers a comprehensive framework for exploring TWS variations using XAI and provides valuable insights into the mechanisms driving TWS changes on a global scale. Full article

The occurrence of gypsum in clastic rocks of continental saline lake basins reflects complex depositional and diagenetic processes. However, its genesis remains relatively understudied. Based on core descriptions and thin-section analyses, this study investigates the occurrence types and genetic mechanisms of gypsum in the Bottom Sandstone Member of the northern Tabei Uplift. Five types of gypsum occurrences are identified: layered gypsum, gypsum clasts, spotted gypsum, gypsum nodules, and a mixed deposition of clastic rocks and gypsum. The mixed deposition of clastic rocks and gypsum includes gypsiferous mudstone, muddy gypsum, gypsiferous mudstone containing muddy clasts, and sandy gypsum. Layered gypsum, spotted gypsum, gypsiferous mudstone, and muddy gypsum mainly result from in situ chemical precipitation during periods of high evaporation and reduced runoff. In contrast, gypsum clasts, gypsiferous mudstone containing muddy clasts, and sandy gypsum reflect processes of transportation and reworking induced by flood events. Seasonal variations in hydrodynamic conditions play a critical role in the formation and distribution of gypsum. During dry periods, surface runoff weakens or ceases, and the salinity of lake water or pore water in clastic deposits increases due to intense evaporation, promoting gypsum precipitation. During flood periods, increased runoff can erode previously formed gypsum, which is subsequently transported and deposited as gypsum clasts. The morphology of gypsum varies with its transport distance. These findings enhance our understanding of clastic–evaporite mixed systems in arid continental lacustrine settings and provide insights into sedimentary processes influenced by seasonal climatic fluctuations. Full article

This study presents a global assessment of the climatological seasonal variability of river discharge into the oceans, based on an expanded dataset comprising 958 gauging stations across 136 countries. Monthly discharges were compiled for 145 major rivers and tributaries, with a focus on improving the accuracy and spatial coverage of global freshwater flux estimates. Compared to previous datasets, this updated compilation includes a broader set of rivers, explicitly integrates tributary inflows, and quantifies both the absolute and relative seasonal amplitudes of discharge variability. The results reveal substantial differences among ocean basins. The Atlantic Ocean, although receiving the highest total runoff, shows relatively weak seasonal variability, with a coefficient of variation of CV = 12.6% due to asynchronous peak discharge from its major rivers (Amazon, Congo, Orinoco). In contrast, the Indian Ocean exhibits the most pronounced seasonal cycle (CV = 88.3%), driven by monsoonal rivers. The Pacific Ocean shows intermediate variability (CV = 62.1%), influenced by a combination of monsoon rains and snowmelt. At the river scale, Orinoco and Changjiang display high seasonal amplitudes, exceeding 89% of their mean flows, whereas more stable regimes are found in equatorial and temperate rivers like the Amazon and Saint Lawrence. In addition, the critical role of tributaries in altering discharge magnitude and seasonal variability is well established. This study provides high-resolution monthly discharge climatologies at global and basin scales, enhancing freshwater forcing in OGCMs. By improving the representation of land–ocean exchanges, it enables more accurate simulations of salinity, circulation, biogeochemical cycles, and climate-sensitive processes in coastal and open-ocean regions. Full article

Understanding tidal changes and their potential forcing mechanisms enables a better assessment of non-stationary tidal effects for projecting extreme sea levels and nuisance flooding. In this study, we investigate the seasonal and interannual changes in the M₂ tidal current off the Guangdong coast using currents observed via two different types of high-frequency radar from 2019 to 2022. The results indicate significant seasonal changes in the M₂ tidal current in the coastal areas of the Pearl River Estuary and Cape Maqijiao, with the largest relative deviations occurring in summer, reaching 10–20%. Observations of thermohaline profiles from 2006 to 2007 and 1978 to 1988 show that runoff in summer can reach these two areas and change the stratification of seawater, in turn affecting tidal currents. A comparative analysis of the two areas suggests that the greater the runoff, the wider the area where the M₂ tidal current experiences significant seasonal variation. No significant interannual changes in the M₂ tidal current were detected offshore of Guangdong during the observation period. However, an abrupt change occurred in the coastal area of Shantou in 2021, primarily caused by the distortion of the antenna patterns. Full article

Grass swales have emerged as a cost-effective and sustainable stormwater management solution, addressing the increasing challenges of urbanization, flooding, and water pollution. This study conducted a bibliometric analysis of 224 publications to assess research trends, key contributors, and knowledge gaps in grass swale applications. Findings highlighted the growing emphasis on optimizing hydrological performance, particularly in response to intensifying climate change and urban flood risks. Experimental and simulation-based studies have demonstrated that grass swale efficiency is influenced by multiple design factors, including vegetation type, substrate composition, hydraulic retention time, and slope gradient. Notably, pollutant removal efficiency varies significantly, with total suspended solids (TSS) reduced by 34.09–89.90%, chemical oxygen demand (COD) by 7.75–56.71%, and total nitrogen (TN) by 32.37–56.71%. Additionally, studies utilizing the Storm Water Management Model (SWMM) and TRAVA models have demonstrated that integrating grass swales into urban drainage systems can result in a 17% reduction in total runoff volume and peak flow attenuation. Despite these advancements, key research gaps remain, including cost-effective design strategies, long-term maintenance protocols, and integration with other green infrastructure systems. Future research should focus on developing innovative, low-cost swale designs, refining optimal vegetation selection, and assessing seasonal variations in performance. Addressing these challenges will enhance the scientific foundation for grass swale implementation, ensuring their sustainable integration into climate-resilient urban planning. Full article

Rapid economic development, accelerated urbanization, and agricultural modernization in eastern China have exacerbated pollution in rivers discharging into the sea, challenging regional ecological security and water resource sustainability. This study investigates ten main rivers in eastern China using monthly water quality and hydrological data from 2021 to 2023. Pollutant fluxes for permanganate index (${\mathrm{COD}}_{\mathrm{Mn}}$), ammonia nitrogen (AN), total phosphorus (TP), and total nitrogen (TN) were calculated, and their temporal and spatial variations were analyzed using descriptive statistics, two-way analysis of variance (ANOVA), and principal component analysis (PCA). Results show significant spatial heterogeneity, with the Yangtze (YAR) and Pearl Rivers (PER) exhibiting the highest fluxes due to high basin runoff and intense human activities. Seasonal variations significantly affect ${\mathrm{COD}}_{\mathrm{Mn}}$, TP, and TN fluxes, with summer runoff and agricultural activities enhancing pollutant transport. Moreover, flood periods markedly increase pollutant fluxes compared to non-flood periods. PCA further reveals that the pollutant flux patterns of YAR and PER are clearly distinct from those of the other rivers, indicating the joint influence of geographic conditions and anthropogenic activities. This study provides quantitative evidence for regional water environment management and offers crucial guidance for developing sustainable, differentiated pollution control strategies. Full article

Water quality in urban streams is critical for the health of aquatic and human life, as it impacts both the environment and water availability. The strong impacts of changing climate and land use on water quality necessitate a better understanding of how stream water quality changes over space and time. To this end, four key water-quality parameters—Escherichia coli (E. coli), nitrate (NO₃⁻), sulfate (SO₄²⁻), and chloride (Cl⁻)—were collected at 12 sites along Fall Creek and Pleasant Run streams in Indianapolis, Indiana USA from 2003 to 2021 on a seasonal basis: March, July, and October each year. Two-way ANOVA tests were used to determine the impacts of seasonality and location on these parameters. Correlation and RDA (redundancy analysis) were used to determine the importance of climatic drivers. Linear regressions were used to quantify the impacts of land-use types on water quality integrating buffer zone size and sub-watershed analysis. Strong seasonal variations of the water-quality parameters were found. March had higher levels of NO₃⁻, SO₄²⁻, and Cl⁻ than other months. July had the highest E. coli concentrations compared to March and October. Seven-days antecedent snow and precipitation were found to be significantly related to Cl⁻ and log₁₀(E. coli) and can explain up to 53% and 31% of their variations, respectively. Spatially, urban built-up land in a 1000 m buffer around the sampling sites was positively correlated with the log₁₀(E. coli) variation, while lawn cover was positively related to NO₃⁻ concentrations within 500 m buffers. Conversely, NDVI (Normalized Difference Vegetation Index) values were negatively related to all variables. In conclusion, E. coli is more impacted by higher precipitation and urban land coverage, which could be related to more combined sewer overflow events in July. Cl⁻ peaking in March and its relationship with snow indicate salt runoff during snow melting events. NO₃⁻ and SO₄²⁻ increases are likely due to fertilizer input from residential lawns near streams. This suggests that Indianapolis stream water-quality changes are influenced by both changing climate and land-cover/-muse types. Full article

Riverine heavy metal (HM) pollution, a critical global environmental issue, severely affects water quality, ecosystem health, and human well-being. The Huaihe River, once among China’s most polluted, has seen water quality improvements due to strict pollution controls, yet the extent of HM pollution reduction remains uncertain. Here, we investigated the distribution, sources, and potential ecological and health risks of nine typical HMs (Cr, Mn, Ni, Cu, Zn, As, Cd, Pb, and Hg) in surface water and sediment in the Anhui section of the river. Seasonal variations in HM concentrations were observed, with most values below drinking water safety limits, except for Mn and Cd at specific sites and seasons. Indices including the HPI, HEI, HQ, and HI showed low contamination and health risks, yet children are more vulnerable to non-carcinogenic hazards, notably from Cd and As. Sediment HMs trends decreased as Mn > Zn > Cr > Pb > Ni > Cu > As > Cd > Hg, with moderate pollution from Cd, Mn, and Pb based on CF, EF, and I_geo assessments. PLI and NPI suggested moderate ecological risks in midstream areas due to HM accumulation. The correlation analysis and PCA revealed that HMs in uncontaminated sediments were mainly of geogenic origin, while contaminated sediments were largely influenced by anthropogenic activities, including agricultural runoff, industrial waste, and domestic sewage discharge. Overall, our findings highlight that control of anthropogenic activities within the Huaihe River basin is essential for reducing HM pollution in the river. Full article

Water scarcity in Chile, particularly in the Mediterranean region, has been exacerbated by prolonged drought and climate change. Rainwater harvesting systems (RHS) have emerged as viable solutions for addressing water shortages, particularly for agricultural irrigation and aquifer recharge. This study evaluated the implementation and efficiency of RHS in rural areas of the Biobío Region, Chile, through the design and construction of two pilot systems in Arauco and Florida. These systems were assessed based on their water collection capacity, storage efficiency, and monitoring of water level variations in wells after rainwater incorporation, using depth probes to quantify stored volumes. The hydrological design incorporated site-specific precipitation analyses, runoff coefficients, and catchment area dimensions, estimating annual precipitation of 861 mm/year for Arauco and 611 mm/year for Florida. The RHS Arauco collected and stored 40 m³ of rainwater in a flexible tank, while RHS Florida stored 10 m³ in a polyethylene tank, demonstrating the effectiveness of the system. Additionally, we analyzed the economic feasibility and quality of harvested rainwater, ensuring its suitability for agricultural use according to Chilean regulations. The cost-effectiveness analysis indicated that the cost of stored water was $263.51 USD/m³ for Arauco and $841.07 USD/m³ for Florida, highlighting larger systems are more cost-effective owing to economies of scale. The Net Present Value (NPV) was calculated using a discount rate of 6% and a useful life of 10 years, yielding CLP $9,564,745 ($10,812.7 USD) for the Florida and CLP $2,216,616 ($2505.8 USD) for the Arauco site. The results indicate that both projects are financially viable and highly profitable, offering rapid payback periods and sustainable long-term benefits. RHS significantly contributes to water availability during the dry season, reducing dependence on conventional water sources and enhancing agricultural sustainability. Based on the evaluation of the cost–benefit, water availability, and infrastructure adaptability, we infer the feasibility of large-scale implementation at locations with similar characteristics. These findings support the role of RHS in sustainable water resource management and strengthening rural resilience to climate variability, highlighting their potential as an adaptation strategy to climate change in water-scarce Mediterranean regions. Full article

Global and regional climate change and their water-related impacts are a key component in future development scenarios to guide sustainable water management. Climatic changes may lead to an undesirable redistribution of water supplies and potentially harmful extremities in river flows throughout the year. If we add to this the uneven spatial distribution of water resources in Kazakhstan, the importance of assessment of the intra-annual distribution of river flows under historical and present climatic conditions becomes evident. The presented scientific study analyzes decadal regional trends from 1985 to 2022 in the intra-annual distribution of river runoff in selected catchments in Kazakhstan, including Buktyrma River, Zhabay River, and Ulken-Kobda River. The river basins were selected to cover diverse regions in terms of geographical features and hydrological conditions, significantly affected by climate change. We applied statistical analysis methods using multiyear values of mean monthly and mean annual river flows, mean monthly air temperatures, and mean monthly precipitation. To analyze the intra-annual distribution of annual river flow in the context of climate change, a computational method was used, in which the actual current river flow (modern river flow taking into account non-stationarity of climatic changes) was compared with the conditionally natural flow obtained by modeling and corresponding to the natural regime of the river. The long-term dynamics of flow-forming factors and runoff parameters with regard to phases of different water content (25%, 50%, and 75%) were considered. Statistical analysis of seasonal changes in water content of modeled and actual river flow, taking into account climatic non-stationarity, allowed us to identify significant trends of flow redistribution within the year: indicating a decrease in the volume of spring floods, an increase in winter flow and increase in seasonal variability, especially for the Ulken Kobda River. It appears that atmospheric circulation significantly affects annual and seasonal variations of water availability. The shift in western circulation type (W) contributes to increased average annual river flow, while the shift in eastern circulation type (E) is associated with amplification of extreme flood-type events. The results obtained are important for adapting sustainable water management practices under a changing climate, helping to anticipate the availability of water resources and allowing pro-active measures to mitigate hydrological extremes. Full article

As a form of green infrastructure, urban forests play a key role in the provision of hydrological ecosystem services (ESs) in cities. Understanding how urban forest structure and soil properties influence water regulation ESs is crucial for managing and planning green infrastructure in cities. We analysed two indicators—the runoff to precipitation (Q/P) and the evapotranspiration to precipitation (ETP/P) ratios—for five different urban forests. We used the hydrological model Brook90 over 16 years to simulate runoff, evapotranspiration, canopy interception, transpiration and soil evaporation. The results showed that mixed forests have the highest water retention capacity, with the lowest Q/P (0.41) and the highest ETP/P (0.59). In contrast, riparian deciduous forests had the lowest water retention capacity, with the highest Q/P (0.75) and the lowest ETP/P (0.25). Both indicators showed similar annual and seasonal results. However, Q/P showed strong inter-annual variation and a strong correlation with precipitation, while ETP/P remained consistent despite precipitation fluctuations in the observed years. In conclusion, the ETP/P ratio is better suited to assess the water regulation ES of urban forests. Full article

Coliform bacteria pollution poses a significant challenge to water quality in the Brunei River, a critical resource in Brunei Darussalam. This study investigates the impact of seasonal variations and population growth on coliform concentrations across eight monitoring stations while addressing data limitations in forecasting future trends. Seasonal variations, analyzed using box plots, revealed significantly higher coliform levels during the rainy season, driven by urban and residential runoff. Population growth, assessed using propensity score matching, showed that stations in densely populated areas experienced elevated contamination levels. Temporal trends, analyzed using the Rescaled Adjusted Partial Sums (RAPS) method, indicated a declining trend from 2013 to 2018, followed by a sharp increase post-2018, linked to urbanization, wastewater discharge, and overburdened sewage infrastructure, particularly in upstream stations. To forecast coliform levels, ARIMA, Logistic Regression, and Bidirectional Long Short-Term Memory (BiLSTM) models were employed and their predictive performance evaluated. Despite the constraints of a small dataset, the BiLSTM model outperformed others in most stations, emphasizing its ability to capture complex temporal relationships. Furthermore, a Mann–Kendall trend analysis of the BiLSTM predicted data over a five-year period and revealed significant upward trends in coliform levels. This study highlights the potential of combining advanced predictive models with robust analytical techniques and focused data collection efforts to support sustainable water quality management in data-scarce environments. Full article

Urban green spaces are important components of city spaces that are vulnerable to degradation in soil–water–climate processes. This vulnerability is exacerbated by current climate change and park usage density. This study examines the dynamics of soil water repellency in the topsoils of selected urban parks in Berlin, aiming to assess the relationships between weather conditions, soil water content, and soil water repellency. This study is based on monthly sampled soils from spots originating from three selected parks—Fischtal Park, Stadtpark Steglitz, and Rudolph-Wilde Park—between September 2022 and October 2023; two of the parks are exclusively rainwater fed, and one is irrigated during summer months. For each sample soil, water repellency persistence and severity were analyzed. Time series analysis was conducted including soil water content. In addition, the total organic carbon content (TOC) and sample texture were analyzed. The results show that the rainfall amount, number of dry days, and maximum temperature during different time intervals prior to the sampling date predominantly control the variation in the soil water repellency via the soil water content. Soil water repellency variations observed appear more event-related than monthly or seasonal, as rainfall is evenly distributed through the years without a distinct dry or wet season in Berlin. The non-repellency of the soil samples was usually observed when the associated water content was increased, which is linked to high cumulative rainfall and short dry periods. Low rainfall amounts and long dry periods in summer result in the re-establishment of the soil water repellency, possibly affecting increased runoff generation and soil erosion risk. Spatially, the repellency properties were observed at locations under healthy vegetation cover, while soils located on the upper slope locations and on the pathways lacked repellency characteristics. Full article