Search Results (791)

Rainfall variability strongly influences both flood and drought hazards, especially in climatic transition zones where precipitation is highly seasonal and spatially heterogeneous. This study assessed long-term changes in rainfall patterns and compound flood–drought hazard in the Huaihe River Basin, China, using ERA5-Land-derived daily precipitation series at 174 spatial sampling locations during 1950–2025. Rainfall pattern indicators, flood-related rainfall extremes, and SPI-3-based drought indicators were calculated to characterize rainfall amount, frequency, intensity, dry–wet persistence, heavy rainfall events, and meteorological drought conditions. The Mann–Kendall test and Sen’s slope estimator were used to detect long-term trends, and a compound flood–drought hazard classification framework was developed based on a flood-related rainfall hazard index (FHI) and a drought-related hazard index (DHI). The results showed that annual total precipitation, wet days, and consecutive wet days decreased significantly, indicating reduced rainfall occurrence and wet spell persistence. Flood-related rainfall indicators generally showed decreasing tendencies, with more evident declines in persistent multi-day extremes than in single-day rainfall. In contrast, mean SPI-3 showed a significant drying tendency, although drought frequency, severe drought frequency, and drought intensity did not exhibit significant monotonic trends. Spatially, rainfall pattern, flood-related, and drought-related indicators showed clear heterogeneity across the basin. The compound hazard classification identified flood-dominated and drought-dominated areas as the two major hazard types, each accounting for 31.03% of the spatial sampling locations, while low compound hazard and compound flood–drought hazard areas each accounted for 18.97%. These findings indicate that flood- and drought-related hazards coexist but vary spatially across the Huaihe River Basin. The proposed framework provides preliminary rainfall-based information for differentiated flood–drought hazard assessment, climate-adaptive water resources planning, and the sustainable management of water resources in regions facing spatially heterogeneous hydroclimatic hazards. Full article

Understanding the spatiotemporal evolution of runoff and its driving mechanisms is of great significance for water resources development, utilization, and sustainable management in mid- to high-latitude river basins under climate change. However, runoff variability is jointly influenced by multiple meteorological factors, and a comprehensive understanding of its multi-scale response characteristics and the relative contributions of different drivers remains limited. In this study, runoff data from three hydrological stations in the Songhua River Basin during 1980–2022 were analyzed. A set of statistical and time-series methods, including the Mann–Kendall test, Pettitt change-point test, Hurst exponent, wavelet analysis, and wavelet coherence, was applied, and a random forest model was used to quantify the influence of key climatic factors such as precipitation, air temperature, and evapotranspiration. The results show that air temperature exhibits significant increasing trends in all four seasons, with the strongest warming occurring in spring (Sen’s slope ≈ 0.06 °C a⁻¹). Precipitation displays pronounced spatial heterogeneity and interannual variability, while evapotranspiration shows an overall increasing trend. Both runoff and major meteorological variables exhibit significant spatial heterogeneity across the basin. Hydro-meteorological variables also show distinct periodic variations among seasons, with temperature, precipitation, and evapotranspiration exhibiting stronger seasonal fluctuations during summer. Wavelet coherence analysis indicates that short-term runoff variability is mainly driven by temperature and precipitation. Temperature exhibits significant coherence with runoff across multiple time scales ranging from approximately 2 to 20 years, whereas precipitation shows stronger coherence at medium- to long-term scales (approximately 10–35 years), with evident seasonal differences. Random forest results indicate that evapotranspiration is the most important contributor to runoff variability at all three stations, accounting for 33.5%, 28.6%, and 26.2% of the total importance at Jiamusi, Fuyu, and Jiangqiao stations, respectively. Temperature and sunshine duration rank second, while precipitation and relative humidity contribute comparatively less. These findings indicate that evapotranspiration plays a key regulatory role in long-term water balance. In addition, runoff exhibits multi-scale variability and a transition from gradual changes to stage-like abrupt shifts. The findings provide a scientific basis for water resources management, flood mitigation, and climate change adaptation in the Songhua River Basin. Full article

Indian metropolitan cities such as Mumbai grapple with rapid urbanisation, extreme urban density, high built-up areas, loss of green cover, and shrinking open spaces, resulting in increased impermeable surfaces, urban heat island effects, and frequent flooding occurrences. Modern stormwater management has increasingly been characterised by integrated grey-green approaches; however, cities in the Global North benefit from established policies, technical expertise, and financial resources that enable the systematic and large-scale integration of Blue-Green Infrastructure (BGI) through district-wide geospatial assessment frameworks, unlike many cities in the Global South. Despite growing interest in nature-based stormwater solutions, there remains a dearth of geospatial empirical research from India examining the placement, distribution, performance, and functionality of BGI integrated with existing stormwater management systems in cities such as Mumbai. Furthermore, hydrological modelling using tools such as the Storm Water Management Model (SWMM) for the design, planning, and implementation of BGI in Indian cities remains largely unexplored. This study explores the role of BGI strategies in improving urban stormwater management within high-density Indian cities under a 25-year return period extreme rainfall scenario. Using an integrated approach that combines QGIS-based spatial analysis with EPA-SWMM hydrologic-hydraulic modelling, the research examines runoff behaviour, identifies flooding hotspots, and evaluates the effectiveness of Low Impact Development (LID)-based BGI measures such as permeable pavements, infiltration trenches, and green roofs applied at the ward level in Mumbai’s F/North and G/North Wards. Detailed land use classification, spatial mapping, and rainfall simulation corresponding specifically to a 25-year return period rainfall event was used to assess pre- and post-intervention conditions. The findings indicate that the applied BGI measures led to a 12.6% reduction in peak runoff (137.6 m³/s to 120.2 m³/s) and a 5.5% decrease in total runoff volume (783,510 m³ to 740,410 m³). More importantly, the peak flooding flow rate decreased by 45% (94.1 m³/s to 51.7 m³/s), demonstrating that BGI measures can efficiently reduce peak flooding flows by extending runoff hydrographs during extreme rainfall events. These findings are specifically applicable to the simulated 25-year return period extreme rainfall scenario and may vary under different rainfall intensities or return periods. Less extreme events could potentially experience even greater relative reductions or prevent flooding altogether, while also easing downstream hydraulic loads. Overall, strategically placed BGI interventions can significantly reduce surface runoff and peak flow, thereby enhancing stormwater resilience within spatially constrained urban environments. This study provides a replicable, data-driven framework for catchment-scale stormwater planning in dense Indian cities under extreme rainfall conditions, offering practical insights into methods, local contextual considerations, and spatial planning strategies for policymakers and urban planners seeking to retrofit and adapt existing infrastructure under increasing hydrologic stress and climate variability. Full article

Reliable estimates of future precipitation are essential for adaptive water management in large river basins. This study presents a machine-learning approach that combines six CMIP6 models to examine precipitation changes in the Yangtze River Basin. ERA5 monthly precipitation for 1979–2025 served as the reanalysis reference. The random forest model incorporated individual model outputs, ensemble statistics, geographic variables, and monthly cyclic terms. It was trained with data from 1979–2009, evaluated for 2010–2014, and then applied to the period 2015–2099 under SSP1-2.6, SSP2-4.5, and SSP5-8.5. Compared with the simple multi-model mean, the proposed method showed better agreement with ERA5 and generally smaller reconstruction errors during the validation period. Annual precipitation is projected to increase under all three pathways, with the largest increase under SSP5-8.5. Precipitation remains concentrated from May to August, while spring totals and intra-annual variability increase more clearly under high-emission conditions. Mean precipitation remains highest in the humid middle and lower reaches, while the magnitude and significance of future trends vary across the basin. Inter-model spread remains greater than the differences among emission pathways and reaches 85.92 mm under SSP5-8.5 during 2071–2099. These results represent uncertainty-aware climate estimates rather than verified forecasts. They can support flood-risk assessment, reservoir planning, and adaptive water management in the Yangtze River Basin. Full article

Climate change is intensifying flood risks globally, yet preparedness behaviors vary dramatically across governance contexts. While past disaster research suggests that institutional trust enables individual preparedness, this relationship remains unexplored in high-capacity governance systems where citizens hold exceptionally strong confidence in government response. We examined this dynamic in the United Arab Emirates, where several surveys have found extremely high levels of public confidence in the local government institutions. In our survey of 900 respondents in the emirates of Dubai and Sharjah we also found that 97% of the respondents had confidence in local government institutions. However, interestingly we also found that while 77% of residents reported past experience with floods, household flood preparedness was markedly low. Using covariance-based structural equation modeling, we tested whether government trust mediates relationships between flood experience, risk perception, and household preparedness. The results revealed that government trust exhibited a strong negative association with flood preparedness, suggesting that institutional confidence may suppress rather than enable household protective action. Notably, flood experience was associated with reduced government trust, likely reflecting the impact of disappointment with service restoration times that exceeded individual expectations. This erosion of trust created positive mediation, indicating that flood experience was associated with increased preparedness. Conversely, higher risk perception was associated with increased trust, which was associated with reduced preparedness through negative mediation. Direct relationships between flood experience and preparedness were statistically non-significant, indicating complete mediation through the trust pathway. Socioeconomic status was positively associated with flood preparedness, with wealthier residents displaying higher protective behaviors. While these findings seem to challenge conventional disaster preparedness theory, the results align with the moral hazard and dependency arguments. Our results show that state-led disaster management in high-capacity governance systems may inadvertently create dependency that increases systemic vulnerability crowding out endogenous adaptive behavior. Building resilience in such contexts requires reframing institutional trust to emphasize shared responsibility rather than externalized protection. Full article

Rapid urbanization, climate change, and biodiversity loss are intensifying environmental pressures on arid coastal cities through extreme heat, water scarcity, salinity intrusion, and increasing flood risks. Despite substantial investment in urban green spaces across the Gulf region, many public parks provide limited ecological functionality and climate adaptation benefits. This study evaluated the ecological performance of three coastal parks in Muscat, Oman Sarooj Beach Park (23,080 m²), Ghubrah Beach Park (34,818 m²), and Al Athaiba Beach Park (17,370 m²), to identify opportunities for more resilient landscape design. The assessment revealed that although green space occupied 76.8–82% of park areas, tree canopy cover remained low (8–12%), limiting thermal comfort, habitat provision, and ecological performance. Based on these findings, a Functional and Climate-Responsive Planting Strategy (FCRPS) was developed by integrating the 10–20–30 biodiversity guideline with performance-based planting criteria tailored to arid and saline environments. The framework was applied to the proposed Majis Beach Ecological Park in Sohar, Oman, to demonstrate the implementation of ecological urbanism and nature-based solutions in a hyper-arid coastal environment. The resulting design incorporates biodiversity-enhancing planting, blue–green infrastructure, wetland restoration, and climate-responsive spatial planning. The study demonstrates how multifunctional landscapes can enhance biodiversity, improve thermal comfort, strengthen stormwater management, and support community well-being while providing a transferable framework for resilient public park design in arid coastal cities. Full article

This study established a refined, distributed SWAT modeling framework that integrates elevation-band and snowmelt modules to reconstruct the alpine hydrological and sediment cycles of the Koshi River Basin (KRB) over the period 1990–2024, with climate scenarios constructed using the delta change approach. The KRB, a major transboundary watershed traversing China, Nepal, and India, was selected owing to its critical hydro-climatic role under the destabilizing “Asian Water Tower”; it generates substantial sediment yield, hosts the densest concentration of hydropower potential within the Ganges system, and spans an extreme vertical gradient from Mount Everest to the southern alluvial plains. Results reveal accelerated warming at a rate of 0.21 °C per decade and an overall warming–wetting trend, punctuated by an abrupt interdecadal shift around 2015. Precipitation dominated interannual streamflow variability, with enhanced rainfall triggering basin-wide sediment surges that overwhelmed the natural buffering capacity of the land surface. Conversely, rising temperatures intensified actual evapotranspiration, markedly depleting soil water and reducing total water yield and monsoon runoff, although sustained snow and glacier melt effectively elevated the dry-season low-flow baseline. The integrated climate forcing reshaped the disparity between hydrological extremes, imposing severe seasonal eco-hydrological stress that manifested as a pre-monsoon deficit in terrestrial green water and acute summer sediment outbursts for aquatic habitats. Furthermore, the flood regime exhibited an altered distribution, with mid-to-high frequency floods enhanced while low-frequency extreme flood peaks declined. The hydro-sedimentological regime consequently exhibits pronounced nonlinear responses to climate change, providing a critical, threshold-based scientific foundation for adaptive transboundary water resource management. Full article

Multiple factors such as global climate warming and environmental degradation have increased natural disaster frequencies, threatening the safety of citizens’ lives and properties seriously. Existing literature primarily focuses on livelihood diversification, resilience, and vulnerability in flood-prone areas, with limited research systematically examining farmers’ livelihood risks and management strategies across multiple dimensions. To address this gap, this study advances the understanding of multidimensional livelihood risks by systematically identifying the key risk perceptions and management strategy choices of farmers, thereby providing empirical evidence essential for designing targeted interventions and sustainable adaptation policies in flood-prone regions. Specifically, this study employs an unordered multinomial logistic model to examine farmers’ risk management strategy choices, drawing on a field survey of 540 farmers from floodplain areas in Sichuan Province, China. The analysis systematically covers four livelihood risk dimensions (health, environmental, financial, social) and five management strategies (expansion, adjustment-oriented, contraction, aid-oriented, dependency-based). The results indicate that: (1) The most significant livelihood risk is environmental, and the most commonly selected risk management strategy is adjustment-oriented management; (2) When farmers face health risks, they tend to adopt dependency-based management strategy; in dealing with financial and social risks, farmers perceive no significant difference in the selection of the five management strategies. Accordingly, targeted strategies are proposed: insurance and information for environmental risks, medical security for health, employment training for social, and income diversification for financial risks. Full article

Sustainable Urban Drainage Systems (SuDSs) represent a contemporary and eco-friendly method for managing surface water, with the goal of reducing flooding impacts while preserving the environment and enhancing water quality and biodiversity. In Bari, recurrent flooding stemming from water stagnation, extreme weather, and urban development poses challenges to sustainable growth. This study applies the ‘Sponge city’ concept to address these issues through an evaluation of current urban permeability and the implementation of Nature-Based Solutions (NBSs) to reduce runoff and manage underground flows. By assessing the climatic conditions and hydrological factors contributing to urban stagnation, this project seeks to create a resilient urban environment capable of adapting to climate change and effectively mitigating both significant and minor rainfall events. It aims to reduce runoff, while also promoting groundwater recharge and alleviating saline contamination effects in coastal areas, ultimately enhancing the safety and livability of urban landscapes. Full article

To address frequent street-level flooding, inadequate targeted management, and unbalanced cost-effectiveness in the old urban area, this study takes Yong’an Subdistrict in Quanshan District, Xuzhou, as a typical case, regards the street-level as its fundamental analytical unit and constructs a systematic “simulation–assessment–strategy” framework, focusing on evaluating and enhancing flood resilience in old urban districts. First, numerical simulation quantifies water depth under extreme rainfall to identify the flood risk spatial distribution. Second, a flood resilience assessment system is established based on the “exposure–vulnerability–adaptive capacity” framework, using the TOPSIS method to measure and grade street resilience. Finally, differentiated flood management strategies are proposed by integrating assessment results with regional characteristics. This study shows that high-risk flooding zones are clustered, with resilience results significantly correlated with the flood risk distribution. Low-resilience areas highly overlap with high-risk zones, mainly due to deficiencies in engineering, ecological, and social resilience. Accordingly, differentiated strategies—”pipe network upgrades + permeable paving”, “retention facilities + smart drainage”, and “micro-topography modifications”—are applied to old residential areas, core commercial districts, and new development peripheries. This approach balances management costs and effectiveness, providing theoretical and practical support for precise street-level flood management and spatial optimization in old urban districts. Full article

The Liujiaxia–Heishanxia reach is critical for water and sediment regulation in the upper Yellow River, where changes in runoff–sediment relationships greatly affect downstream channel stability and flood safety. Climate change and intensive human activities have substantially altered local hydrological regimes in recent decades. Using long-term hydrological records from five stations during 1956–2020, this study applied the Mann–Kendall test, moving t-test, wavelet analysis and XGBoost algorithms to analyze the trends, abrupt changes and periodic features of runoff and sediment load, and quantify the contributions of natural and human drivers. The results show that both runoff and sediment load decreased significantly, with a sharper decline in sediment load. Major abrupt changes occurred in 1969, 1986, 1996 and 2008, and both variables presented a dominant 40-year interdecadal cycle. Human-induced landscape changes became the leading factor driving hydrological variations after 1996. Our findings suggest that future watershed management should combine landscape optimization and climate adaptation to maintain stable runoff-sediment conditions. This work provides scientific references for water resource management and the construction of the Heishanxia Water Conservancy Project. Full article

In underwater navigation, MUVs risk damage from obstacles and equipment. Effective damage management supports timely decisions and maximizes functionality recovery. Existing approaches can be roughly categorized into rule-based reasoning, case-based reasoning and expert systems. However, the primary limitation of the existing approaches is their inability to adapt to dynamically changing scenarios. In this paper, an auxiliary decision-making system (ADMS) for manned underwater vehicle (MUV) damage management based on deep reinforcement learning (DRL) is proposed to address the problem of cabin flooding. This system is designed to provide auxiliary decision-making in emergency situations and help preserve MUV vitality. Furthermore, a comprehensive States–Actions cluster encompassing various damage management measures for real damage scenarios is constructed and digitized. Moreover, several novel reward functions are developed to ensure the DRL model obtains a safe strategy with ADMS operations. Finally, the MUV buoyancy and stability vitality evaluation criteria are defined and analyzed. The simulation results show that the auxiliary decision-making measures given by the ADMS in the damage state are effective and rational. The evaluation criterion for buoyancy vitality can exceed 38%, while the criterion for stability vitality can surpass 92%, with an optimal value exceeding 99%. Full article

Glacial lake outburst floods (GLOFs) are a major cryosphere-related hazard in High Mountain Asia (HMA), where glacier mass loss and changing hydroclimatic conditions are reshaping glacial-lake systems and increasing the prevalence of potentially unstable lake–dam configurations. However, current knowledge remains fragmented across HMA. Therefore, this review synthesizes historical evidence, future changes, and risk-reduction strategies of GLOFs across HMA from a remote-sensing perspective. Historical evidence derived from satellite archives, multi-temporal lake inventories, geomorphological analyses, and documented event records indicate that reported GLOFs in HMA are strongly clustered by sub-region and dam type, with moraine-dammed lakes representing the dominant source of documented events, while ice-dammed lakes remain important in several mountain belts. The compiled record also shows that GLOFs have caused severe human, economic, geomorphic, and ecological losses. Future projections based on glacier evolution, glacial-lake expansion, and climate-sensitive hazard assessments indicate continued glacial-lake growth under global warming. However, reliable prediction of future GLOF event timing, magnitude, and frequency remains constrained by uncertainties in glacier evolution, dam stability, and triggering processes. This review further shows that effective GLOF risk reduction in HMA requires integrated systems that combine hazard and risk mapping, early warning, structural interventions, and non-structural measures. It also highlights the need to better link remote sensing with monitoring, assessment, and implementation frameworks, and proposes an integrated management cycle to support practical risk reduction. It concludes that the most urgent research priorities are harmonized multi-temporal lake inventories, targeted field observations, explicit consideration of heatwaves and compound extremes, transparent uncertainty propagation, and stronger operationalization of monitoring and warning systems to support durable climate adaptation and disaster risk reduction across HMA. Full article

Intensive human activities are reshaping inland tail-end deltas. Based on hydrological and sediment data from 1950 to 2023 and physical model experiments, this study examines the Ganjiang tail-end delta to analyze channel evolution, driving mechanisms, and management pathways. Results indicate that the Wan’an Reservoir and large-scale sand mining are the dominant drivers of flow-sediment regime shifts and channel reshaping. Sand mining has caused severe riverbed incision, with a local maximum depth of 16.5 m. During the dry season, the flow diversion ratio of the West Branch exceeds 90%, fundamentally altering the flow distribution pattern. Although riverbed incision has enhanced local flood conveyance, the overall flood discharge capacity of the tail-end delta remains limited due to backwater from Poyang Lake, introducing new flood risks. Reduced sediment supply and hydrological changes have exacerbated wetland shrinkage and eutrophication. Physical model experiments show that the comprehensive regulation project can raise dry-season water levels by approximately 5 m through sluice operation, optimize flow diversion, and increase wetland surface water area by 56%. This project integrates flood control, ecological protection, and water resource utilization, representing a proactive exploration of adaptive management for deltas and providing scientific references for understanding evolution and guiding management in similar inland tail-end deltas. Full article

The UNESCO World Heritage coastal zone of Cinque Terre (Liguria, northern Italy) is increasingly threatened by ongoing sea-level rise. To assess expected sea levels up to 2150 CE under the IPCC Sixth Assessment Report (AR6), we carried out a first evaluation of potential coastal flooding for Monterosso and Vernazza under different Shared Socioeconomic Pathways (SSPs), integrating high-resolution topography and bathymetry, geodetic data, historical tide-gauge evidence, and storm-surge modeling. The historical sea-level analysis indicates a non-stationary rising trend for the Ligurian sector. Relative sea-level rise (RSLR) projections were computed for SSP1-2.6, SSP3-7.0 and SSP5-8.5, including local land subsidence, and were used to map the potential inundated areas for 2030, 2050, 2100, and 2150 CE. In 2150, projected RSLR is expected to range from 0.60 m to 1.17 m, corresponding to flooded surfaces of 9931 m² and 22,079 m² in the SSP1-2.6 and SSP5-8.5 scenarios, respectively. Because site-specific long-term run-up observations are not available for formal calibration at the two study sites, the storm-surge simulations are interpreted as scenario-based hazard envelopes. Even within this framework, storm surges with return times of 1 and 100 years in the SSP5-8.5 scenario cause maximum wave run-up in the range of 5.12 m and 13.36 m. The results show that narrow pocket beaches and low-elevation harbor areas are the most critical receptors and that adaptation measures should focus on quay elevation, drainage/backwater management, and the protection of transport and tourism infrastructures. Full article