Search Results (4,443)

Single-species hedges can help mitigate a range of urban and climate change-related issues, such as slowing stormwater flow and reducing rainfall runoff, particularly during the growing season. There is, however, little information on the service delivery of mixed hedges and their comparison to single-species, year-round, as well as on the practicality of functional rather than ornamental plant mixing. Here, we report on an initial case study to address this. Chosen hedge taxa (Crataegus monogyna, Elaeagnus × submacrophylla ‘Gilt Edge’, Ligustrum ovalifolium, Thuja plicata ‘Atrovirens’) represented a range of plant characteristics. These were trialled outdoors in Reading (SE England, UK) as treatment groupings of either single-species or mixed-species (‘evergreen’ and ‘broadleaf’ mix), along with a bare soil control, in 110 L troughs. We applied 5 min simulated rainfall onto each treatment twice in every meteorological season and assessed canopy throughfall. We also monitored substrate moisture content change as a proxy for evapotranspiration and substrate storage capacity of subsequent rainfall. During summer, the deciduous taxa and mixed hedges had the highest evapotranspiration rates, suggesting their potential to influence soil water storage, but in our experimental setup, that did not translate into significant differences in substrate moisture between treatments. During autumn and winter, the single-species Thuja treatment had the highest rainfall interception rate, followed by both mixed species treatments. In winter, canopy and leaf characteristics rather than physiological activity correlated with increased rainfall attenuation. However, by the end of the experiment (spring 2023), Crataegus, Thuja and both mixed hedge treatments had significantly lower throughfall (higher interception) compared to bare soil. We are continuing to test these treatments in a longer-term field experiment. Management of mixed-species hedges for rainfall attenuation is practically achievable, despite some differences in individual species’ growth rates and plant habits. Full article

Urbanization, together with shifts in rainfall patterns, has become an increasingly important driver of hydrological extremes in many rapidly developing tropical regions. In the Cimanceuri River Basin, Tangerang Regency, Indonesia, these processes have intensified over the last decade, raising concerns regarding flood risk. This study examines the combined influence of urban expansion and rainfall variability on flood dynamics over 2013–2025. Multi temporal land use classification based on Landsat imagery indicates a pronounced growth of impervious surfaces, primarily driven by rapid urban development and the conversion of agricultural land. To assess the hydrological consequences of these changes, rainfall–runoff processes and flood inundation were simulated using the Soil Conservation Service Curve Number (SCS–CN) method within a coupled HEC-HMS and HEC-RAS 2D modelling framework. Simulations were performed for multiple temporal conditions and design rainfall scenarios. Model calibration relied on observed flood events recorded in March 2025 in the Mustika Residential Area, Tangerang. The results suggest that urbanization has contributed to measurable increases in both peak discharge and inundation extent. Between 2013 and 2025, impervious surface coverage expanded by approximately 67%, accompanied by a rise in the composite Curve Number from 85.86 to 86.63 and an estimated 5.2% increase in flood extent. Also, the design rainfall increased from 85.01 to 90.95 with an average increase of 7.34%. Comparison between simulated inundation patterns and aerial imagery shows satisfactory agreement, with an average deviation of less than 10%, indicating acceptable model performance. Hydrologic analyses generated two discharge scenarios, consisting of event-based flow from the 5 March 2025 rainfall data and return-period flows derived from design rainfall under different rainfall-shift periods. The rainfall-shift analysis quantified changes in design rainfall and corresponding discharge using progressively updated rainfall records. Together, the results emphasize the combined effects of urban expansion and shifting rainfall patterns on flood dynamics, underscoring the need for adaptive land-use planning and climate-responsive water management in rapidly urbanizing catchments. Full article

Accurate flood simulation in regulated, low-lying river basins is crucial for forecasting and risk mitigation, but performance depends strongly on whether models represent floodplain hydrodynamics and human regulation. This study evaluates three coupled hydrological–hydrodynamic schemes in the Huai River Basin upstream of Bengbu Station using identical meteorological forcing and VIC-generated runoff: (I) a linear routing scheme (VIC–Routing), (II) a natural hydrodynamic scheme (VIC–CaMa-Flood), and (III) an extended hydrodynamic scheme that incorporates reservoir regulation and levee effects (VIC–CaMa-Flood with Dam). Results reveal clear spatial differences in scheme suitability. The linear routing scheme performs best in upstream reaches, with NSE and KGE generally exceeding 0.81, but tends to overestimate peak discharge in downstream lowland sections. Incorporating hydrodynamic processes and regulation representation further reduces peak flow bias. Scheme III achieves the most consistent downstream improvement, particularly for high flows (>2000 m³/s), with NSE exceeding 0.80 in long-term simulations and improved agreement with satellite-driven inundation patterns. However, simplified reservoir operating rules can increase uncertainty in water level dynamics. During the 2020 plum rain flood, Scheme II yielded more accurate water levels in some reaches, suggesting that generalized operation rules may introduce compensating errors even when discharge accuracy improves. Overall, reliable flood simulation in well-managed basins requires an explicit representation of both floodplain hydrodynamics and regulation, and scheme selection should be guided by the dominant controls along the river network. Full article

Soil erosion and nutrient loss degrade the soil resource base and water quality in dryland agricultural landscapes, yet optimal design of vegetation buffers for soil conservation under intensifying rainfall remains poorly quantified, particularly for nutrient retention. This study is novel in integrating event-scale rainfall-simulation experiments, Bayesian hierarchical modelling, Causal Forest analysis, and WEPP simulations to quantify how the sequential addition of biocrusts and grasses to shrub buffers shifts density thresholds for runoff, soil loss, and nutrient export across varying rainfall intensities. Experiments were conducted across a continuous shrub-density gradient (0–11,429 plants ha⁻¹) representing three configurations: shrub monoculture, shrub-biocrust, and shrub-biocrust-grass on agricultural hillslopes of the Chinese Loess Plateau. Runoff, soil loss, and exports of total nitrogen (TN) and total phosphorus (TP) were measured. Results demonstrate three main findings. First, multilayer shrub–biocrust–grass buffers exhibited lower soil loss than monocultures. Posterior estimates indicate reductions from approximately 3.8 t ha⁻¹ at moderate monoculture density to below 1.0 t ha⁻¹ at lower planting densities, with 94% of the highest-density intervals reflecting uncertainty in these estimates. Second, Causal Forest analysis reveals a functional separation of controls: rainfall intensity dominates soil loss (88% importance) and runoff (84%), whereas nutrient retention responds more strongly to buffer structure and density management. Third, WEPP simulations across rainfall intensities (50–180 mm h⁻¹) and slopes (10–30%) identify an optimal multilayer buffer density of 3800–5700 plants ha⁻¹, which delivers robust multifunctional benefits with 50–67% lower planting requirements than conventional high-density monocultures. These findings demonstrate that multilayer vegetation buffers enhance soil retention and reduce nitrogen and phosphorus losses from hillslopes, sustaining the soil resource base and protecting water quality in dryland agricultural landscapes. The integrated modelling framework provides transferable, evidence-based density recommendations for climate-resilient soil conservation in similar dryland regions. Full article

Climate change poses a significant threat to water resources and agricultural sustainability, particularly in semi-arid and socio-economically vulnerable regions such as South Africa. This review synthesizes empirical, modelling, and policy-based evidence on the impacts of climate change on water availability, crop production, and adaptation strategies in the country, drawing on approximately 162 peer-reviewed studies and institutional reports published between 2010 and 2025. The findings indicate that rising temperatures, shifting rainfall patterns, and an increasing frequency of extreme events, such as droughts and floods, are intensifying water stress and disrupting agricultural systems. Hydrological models consistently project declines in runoff, soil moisture, and streamflow, while crop simulation models predict reductions in the yields of major staple crops, including maize, wheat, and sorghum, particularly under high-emission scenarios. Although localized improvements in water availability and crop productivity may occur, these tend to be limited and highly context-specific. In response, South Africa has implemented a range of adaptation strategies, including climate-smart agriculture, water-efficient irrigation, ecosystem-based approaches, and policy-driven interventions. However, their effectiveness remains constrained by institutional fragmentation, limited financial capacity, and persistent socio-economic inequalities, particularly among smallholder farmers. The review underscores the need for integrated, inclusive, and context-specific adaptation strategies that strengthen governance, enhance the science–policy interface, and improve access to climate finance. The insights provided offer valuable guidance for advancing climate resilience in South Africa and other vulnerable regions across the Global South. Full article

This study evaluates nitrogen (N) and phosphorus (P) pollution in the Ankara River Sub-basin, Türkiye, using the grey water footprint (GWF) approach. A Tier-1 GWF approach was applied, complemented by a sensitivity analysis to assess the influence of key parameters, including leaching–runoff fractions and water quality thresholds. The results should be interpreted as indicative rather than absolute values, as they depend on assumptions related to leaching fractions and background concentrations. By integrating data from agricultural diffuse sources and municipal wastewater treatment plants (WWTPs), the research identifies critical pollution hotspots and sectoral pressures on water resources, causing water quality degradation. The results reveal that P is the primary limiting pollutant governing GWF magnitudes across the sub-basin. The total GWF was estimated at 8294 million m³ yr⁻¹ in the sub-basin outlet. Approximately 10% and 31% of the basin-wide GWF were associated with fertilizer-based diffuse sources and WWTP1, respectively. The study demonstrates that regulatory compliance alone does not guarantee the protection of a river’s assimilative capacity. These results provide a basis for policy development, emphasizing the need to move beyond concentration-based regulations toward management frameworks that explicitly consider assimilative capacity and cumulative basin-scale impacts. Full article

Household rainwater tanks (HRWTs) have re-emerged globally as a decentralised strategy to address water scarcity, climate variability, and increasing urban water demand. In several jurisdictions, including New South Wales, Australia, rainwater tanks have been chosen to meet the mandatory potable water reduction target in new residential developments for nearly two decades; however, growing evidence indicates persistent underutilisation and variable performance in practice. Despite their recognised benefits in reducing potable water demand, mitigating stormwater runoff, and enhancing urban resilience, the global HRWT research landscape remains fragmented across disciplinary and thematic boundaries. This paper presents a multifaceted review, defined here as an approach that synthesises multiple perspectives on the topic. It integrates systematic mapping of peer-reviewed literature with a critical thematic analysis across four dominant research domains: technological and design innovation, policy and governance frameworks, environmental performance, and social–behavioural dimensions. The findings reveal a strong research focus on technical optimisation, while policy effectiveness, environmental trade-offs, and household-level behavioural factors receive comparatively uneven attention. Regulatory and incentive-based instruments are shown to produce inconsistent outcomes, shaped by local institutional capacity to design, implement, enforce, and sustain programs, as well as by climatic context and household acceptance. Environmental assessments identify both benefits and burdens, including energy use, treatment requirements, and operational complexity. Social and behavioural studies indicate growing acceptance of household rainwater tank (HRWT) systems. However, financial constraints, local conditions, and ongoing maintenance demands continue to influence adoption and performance. A key insight from this review is the limited attention given to households’ lived experiences, particularly how users adopt, adapt, operate, and maintain HRWT systems over time. This gap constrains progress across technical, policy, environmental, and social dimensions and risks cycles of early policy uptake followed by stagnation. The review highlights the need to integrate household perspectives into future research, policy design, and industry practice to improve system performance, user experience, and the long-term contribution of HRWTs to sustainable urban water management. Full article

Groundwater level (GWL) variations in the arid regions of Northwest China are driven by both natural processes and human activities. Identifying causal links between hydrological variables is fundamental to understanding groundwater evolution and conducting dynamic simulations. This study integrates the Mann–Kendall test, Seasonal-Trend decomposition using Loess, and the Peter and Clark Momentum-threshold and Momentary Conditional Independence (PCMCI) causal inference to analyze GWL variation characteristics and causal response processes across seven sub-basins in the Tarim Basin using multi-source remote sensing data. Results show an overall decline in GWL, primarily in the north-central part of the basin, with the Kaidu–Konqi River Basin reaching a maximum rate of 0.51 m/year. The trend components reveal localized depletion alongside broad stability, while seasonal components exhibit three types of temporal shifts in fluctuations. A mismatch exists between the prevalence of environmental influences and their causal strength. Daytime land surface temperature (LST_D), surface runoff (RO), and evapotranspiration (ET) show the highest detection frequencies, yet volumetric soil water in layers 2 (SWVL₂) and RO exhibit the largest ranges in strength and drive variations at specific sites. Response times are asymmetric. Negative effects from ET on GWL transmit quickly, while positive recovery is slow. Conversely, positive recharge from volumetric soil water in layer 1 (SWVL₁) is faster than its negative lag. At the basin scale, surface processes recharge GWL while mediating indirect influences from other variables. Climate and agricultural irrigation act as direct sinks. Depending on local conditions, three regional patterns emerge: direct climate-driven depletion, obstructed shallow water retention, and indirect compensation from agricultural water use. Causal networks indicate that RO and SWVL₁ have the highest centrality and dominate water output, whereas SWVL₂ acts as a passive receiver. Pathways from the surface to GWL are also asymmetric. The most frequent path involves step-by-step infiltration along RO → ET → SWVL₁ → SWVL₂ → GWL. In contrast, the paths with the highest cumulative strength are shorter and faster, specifically RO → ET → GWL and RO → SWVL₁ → GWL. The identified pathways and lag parameters provide a direct basis for groundwater dynamic modeling and water resource management in the basin. Full article

The development of effective source rocks is key to hydrocarbon accumulation. The Jinshan Rift Trough, located in the Ordos Basin, is generally considered to be a favorable zone for the formation of source rocks in the Mesoproterozoic Changcheng System. This study investigates mudstones of the Cuizhuang Formation (Changcheng System) from Well PT1 using petrological and geochemical methods to evaluate source rock potential and organic matter enrichment mechanisms. The results show that the original total organic carbon (TOC) and original S₁ + S₂ of the mudstone in the Cuizhuang Formation are 0.06–1.97% and 0.61–10.34 mg/g, respectively, and “good source rock” with a cumulative thickness of 6.7 m is developed in the lower part of the Cuizhuang Formation. The main hydrocarbon-forming organisms of the source rock are planktonic and benthic algae, among which planktonic algae account for a relatively high proportion. Equivalent vitrinite reflectance (R_o) exceeds 2%, indicating an over-mature stage. The TOC of the mudstone of the Cuizhuang Formation shows a weak relationship with the salinity and redox conditions of sedimentary water but has a significant correlation with the paleoproductivity and paleoclimate. Rather than anoxia or salinity, high productivity is the main controlling factor for the enrichment of organic matter in the Changcheng System. Under a warm–humid climate, increased surface runoff and terrestrial nutrient input promote the proliferation of bacteria and algae, leading to the formation and preservation of abundant sedimentary organic matter that forms “good source rocks”. This study provides a theoretical basis for the study of the petroleum system and oil and gas exploration in the Mesoproterozoic Changcheng System in the Ordos Basin. Full article

Snow water equivalent (SWE), the amount of water that will be liberated when a given snowpack melts, is considered an essential climate variable. Snowmelt drives annual run-off in snow-dominant basins. However, detecting daily SWE changes in lake-effect snowfall regions such as the Great Lakes Basin (GLB) is challenging with classical methods. We developed a Siamese U-Net (Si-UNet) model to detect and characterize daily changes and trends in SWE. Our Si-UNet detected daily changes in SWE over the GLB with an F1-score of 98.73%. To characterize the basin-wide extent of anomalies in SWE distribution, we compared SWE trends to a 35-year median (35YB) baseline and identified decadal trends in SWE. We found that the period from 1989 to 2008 was the temporal window with minimal anomalies, compared to the 35YB of ~0.5108. Positive deviations from the 35YB were prevalent over these 20 years, indicating less significant daily changes. A significant shift to daily SWE similarity below the 35YB occurred after 2009, especially in January and February. Daily changes in SWE were high in April, beginning in the second week. The strongest positive trend, likely associated with lake-effect snowfall, was observed in April 2000 (R² = 0.47). Full article

The primary aim of this study is to identify the driving mechanisms behind long-term water-level changes and drought–flood transitions in Dongting Lake. To achieve this, we employed methods including the Improved Standardized Water Level Index (ISWI), Mann–Kendall test, Sen’s slope estimator, and a random forest–SHAP model to analyze hydro-meteorological data from 1992 to 2023. The results demonstrate a significant overall decline and spatial heterogeneity in water levels, alongside a systemic shift in the regional pattern from flood-dominated conditions to frequent droughts with intense drought–flood abrupt alternations. Crucially, during the critical autumn water recession period, runoff anomalies from the Yangtze River’s three outlets emerged as the dominant factor driving water-level changes, far exceeding the influence of local precipitation. Furthermore, a recent downward shift in the water level–discharge relationship indicates that under identical inflow conditions, water levels are now 1.5 to 2.0 m lower than in previous decades. These general findings highlight that critical-period inflow reductions and altered boundary hydrodynamic conditions mutually amplify low-water-level risks, providing a scientific reference for adaptive water resource management in complex river-connected lakes. Full article

Access to clean water remains a critical global challenge, particularly in arid and fog-rich regions where conventional resources are limited. Fog water harvesting has emerged as a low-energy alternative; however, the performance of traditional collectors (typically 3–10 L m⁻² day⁻¹) remains constrained by inefficient droplet capture and transport. This review provides a systematic and critical analysis of recent advances in membrane-based fog harvesting technologies, focusing on material design, surface engineering, and structural optimization. The analysis shows that nanostructured and electrospun membrane systems can enhance water collection rates to ~20–60 L m⁻² day⁻¹, representing up to a 5–6 times improvement over conventional meshes. Furthermore, biomimetic and Janus wettability designs significantly improve droplet nucleation and directional transport, while hierarchical micro/nanostructures accelerate coalescence and runoff dynamics. At the structural level, optimized collector geometries (vertical harp designs) demonstrate ~3–4 times higher collection efficiency compared to traditional Raschel mesh due to reduced clogging and enhanced drainage. Despite these advances, key challenges remain, including material durability, fouling resistance, lack of standardized testing protocols, and limited large-scale validation. This review identifies critical design–performance relationships and proposes a framework linking surface wettability, morphology, and environmental parameters to harvesting efficiency. Future directions emphasize the development of durable, scalable membrane systems and the integration of fog harvesting with hybrid water supply technologies. Full article

Urban cities have been intensely prone to floods during extreme rainfall events and water scarcity issues during dry periods in recent years. In this context, identifying rainwater harvesting potential (RWHP) regions in urban environments provides a sustainable approach to mitigate both urban flooding and water security, thereby improving urban stormwater management. Geospatial mapping of RWHP has tried to consider various hydrometeorological, topographical and other geospatial datasets, but integrating socio-economic factors over urban environments has not been explored much. The present study integrated remote sensing and hydrological-based information, such as slope, soil type, drainage density, geomorphology, topographic wetness index (TWI), land use land cover (LULC), rainfall, runoff coefficient, proximity to roads, and proximity to settlements for geospatial mapping of RWH potential zones for Hyderabad city using multi-criteria decision analysis (MCDA) and weighted overlay analysis (WOA). The resulting RWH potential map indicates that 80.20% of the area falls within the “low” potential category, 17.53% as “moderate”, 2.0% as “very low”, and only 0.25% as “high” potential, mainly in the southeastern portion near the Hussain Sagar outlet. These categories are spatially verified using Sentinel-2 LULC and Google Earth imagery to assess the qualitative plausibility of the mapped RWH potential zones. Northwestern areas, with loamy soils and mild slopes, demonstrate suitability for rooftop collection and percolation structures, highlighting the effectiveness of the proposed modelling framework for sustainable stormwater management for urban environments. Full article

Climate change and population growth are intensifying water scarcity in arid regions, yet previous analyses focusing on a single driver may not fully capture the compounded effects of climatic and anthropogenic factors. This study integrates water-balance analysis, trend analysis, and correlation-based statistical analysis to examine the combined effects of hydroclimatic anomalies and socioeconomic activities on water resource dynamics in ecologically vulnerable Northwest China. Our results show that despite increasing precipitation, warming-associated increases in evapotranspiration, together with irrigation-based water use accounting for 89.8% of total consumption, have offset the potential runoff gains, suggesting that agricultural water use is a major anthropogenic contributor to regional water stress. Based on these findings and a comparative review of representative arid-region practices in Israel, Australia, and Saudi Arabia, we propose a technology-market-institution tripartite governance framework for Northwest China. This framework is intended to support more proactive adaptation in regional water management and to provide a context-specific reference for advancing SDG 6 and SDG 13 in dryland regions. Full article

Many cities adopt greening strategies to reduce contamination from combined sewer overflows (CSOs). Nonetheless, quantifying the impact of urban greening on CSO-affected water quality at the city scale remains challenging. To address this challenge, this work leveraged supervised learning to link water swimmability with the greening of a CSO shed (the drainage area of a CSO outfall), using New York City (NYC) as a case study. Random forest classification models were built to predict water swimmability after rainfall at 46 sites in NYC water bodies impacted by CSOs. A 14-feature model (AUROC =0.81, accuracy = 0.78) revealed that greening improved local water quality. However, water flow speed, antecedent rain depth, and CSO shed area were also influential. A simplified four-feature model (AUROC = 0.8, accuracy = 0.75) explored links between levels of greening and the probability of non-swimmable waters ($P_{ns}$) following different 18 h rainfall depths. Increased greening was found to be most impactful in reducing $P_{ns}$ for CSO sheds discharging to water bodies with flow speeds < 6 cm/s. For CSO sheds discharging to water bodies with flow speeds $\ge$ 14.7 cm/s, urban greening had no impact on $P_{ns}$. The work illustrates the utility of supervised learning in supporting citywide decisions regarding urban greening investments. Full article