Search Results (1,115)

Contemporary approaches to urban water management increasingly rely on concepts such as Nature-Based Solutions (NBSs), Green Infrastructure, and Blue-Green Infrastructure. Although these frameworks have gained broad acceptance, their typological character provides limited guidance for project-oriented decision-making, as they primarily describe infrastructure types rather than their functions within integrated hydrological systems. To address this gap, this study proposes a complementary functional-operational framework for interpreting ecological infrastructures in urban flood mitigation. Employing a qualitative comparative case study methodology, we analysed four diverse international models—the Dutch Water Squares (Rotterdam), Tokyo’s underground flood control system, Copenhagen’s Cloudburst Management Plan, and Singapore’s ABC Waters Programme—to examine the systemic interaction between grey, green, and blue infrastructures at different watershed scales. The results indicate that flood mitigation effectiveness depends less on the predominance of a single infrastructure type and more on the functional coupling among them. Specifically, three primary functions were identified: rapid conveyance (grey infrastructure), infiltration and thermal regulation (green infrastructure), and dynamic storage and biodiversity support (blue infrastructure). Despite the contextual limitations and varying scales of the selected cases, blue infrastructure universally emerges as a systemic buffer that enhances urban resilience by regulating excess volumetric flows. Ultimately, the proposed framework introduces an actionable interpretative layer that complements existing typological classifications, providing planners and urban designers with a robust, scalable basis for implementing integrated ecological infrastructures. Full article

Floodplain lake ecosystems around the world have witnessed growing environmental degradation under combined natural climatic variability and anthropogenic activities. Reconstructing their long-term ecological change is vital for lake ecosystem conservation and management. Cladoceran subfossils are used as an important proxy indicator to reconstruct ecological evolution of floodplain lake systems worldwide. The sedimentary record of Zhangdu Lake, a shallow floodplain lake in the middle and lower reaches of the Yangtze River in China, is important for reconstructing more than 150 years of environmental history and tracing the lake ecosystem’s transition from a natural flood-pulse system to a new regime driven by anthropogenic disturbances. Integration of subfossil cladoceran data with other biological proxies (diatoms and testate amoebae) and physicochemical sedimentary proxies successfully identified the period of river–lake disconnection and the associated ecological processes and succession in Lake Zhangdu. An abrupt disconnection of the lake from the Yangtze River in the early 1950s led to a sudden ecological vulnerability together with a drastic community decline. Sequential t-test Analysis of Regime Shifts (STARS) identified cladoceran community shifts in 1966 and 1999, with regime shift index (RSI) values of 1.195 and 3.29, respectively, reflecting multi-phase ecological reorganization following the 1950s disconnection. Differences among the proxies in the timing and magnitude of change and in their apparent drivers reflected group-specific habitat preferences, response thresholds, and trophic positions. This study shows that the assessment of multi-taxa paleoecological indicators can provide a strong evidence base for guiding restoration efforts in degraded floodplain lake ecosystems in China and elsewhere. Full article

Changes in river channel morphology under the influence of natural and anthropogenic factors pose a serious threat to the stability of aquatic ecosystems and water resource use, especially in regions with limited hydrological information. This study presents, for the first time, a three-dimensional numerical investigation of channel processes in the Talas River (Kazakhstan), employing the Volume of Fluid (VOF) method for free-surface flow simulation and a non-Newtonian model for sediment transport and riverbed morphodynamics. To verify the developed mathematical model, experimental data on the flow in the L-shaped channel and Earthfill dam break were used, which provided high reliability of the calculated results. The calculations showed a significant increase in the channel area in the studied section of the Talas River (from 41,334.92 m² to 56,890.17 m²) for the period from 2019 to 2024, mainly due to the intensification of the dynamics of currents and the formation of additional vortex zones with a diameter of 50 to 200 m. It was found that in places of local flow acceleration, water velocity increased up to 4.5 m/s, leading to bank erosion and channel widening, whereas after redistribution of channel flows, the maximum velocity decreased to 2.8 m/s, ensuring stabilisation of morphological changes. The results of the study underline the need for an integrated approach to river morphodynamics management using numerical modelling to predict channel changes, minimise flood risks and optimise the use of water resources. The presented computational approach can be adapted to analyse hydrodynamic processes in other poorly studied river systems, which significantly expands its scientific and practical value. Full article

Phosphogypsum (PG), a gypsum-rich by-product of wet-process phosphoric acid production, is increasingly considered for land application because it can supply calcium and sulfur and alleviate constraints such as sodicity, subsoil acidity, and vegetation establishment limitations. However, PG may also contain residual acidity, soluble salts, fluoride, heavy metals, and naturally occurring radionuclides, creating multiple exposure pathways. This critical review distinguishes direct PG evidence from gypsum or sulfate analogue evidence, life cycle assessment/material flow analysis evidence, and risk control studies. It evaluates PG land application according to receiving soil conditions, diagnosed constraints, exposure pathways, and environmental safety boundaries. The strongest evidence supports use in diagnosed sodic and saline–sodic soils, whereas applications in Al-toxic acid subsoils, flooded paddy systems, contaminated or degraded soils, and non-food vegetated systems require conditional assessment. PG should therefore be treated as a context-specific management option rather than an unrestricted disposal route. By linking waste valorization with soil demand, source quality, exposure control, and long-term monitoring, the proposed framework contributes to sustainability by integrating circular resource use with soil health, water protection, food/feed safety, and risk-informed governance, while helping to prevent the transfer of environmental burdens across ecosystems or generations. Full article

Rapid peri-urban sprawl is intensifying flood risk by replacing natural landscapes with dense, impervious residential developments. Thailand’s land use regulations require a 5% minimum green space allocation for new housing developments as a measure to promote livability and well-being. Green space also has the potential to sustainably manage stormwater runoff, but for Thailand’s peri-urban development, the question remains whether 5% green space is sufficient to reduce flood risk. As such, this study critically evaluates whether this 5% green space guideline is sufficient for peri-urban runoff and flood management in peri-urban Pathum Thani, particularly given the acceleration of Bangkok’s urban sprawl over the past 30 years. Using a multi-scalar framework, we integrated GIS spatial analysis of 164 gated communities (1995–2025) with site-specific PCSWMM hydrologic modeling to test baseline conditions and Nature-based Solution (NbS) interventions against 5-, 10-, 50-, and 100-year design storms. Findings reveal developers generally adhere to the 5% guideline, thereby addressing policy while maximizing salable land space. PCSWMM simulations show the 5% baseline alone does not adequately manage runoff, with localized residential flooding expected for a 5-year design storm under current baseline conditions. Scenario testing indicates a hybrid grey–green infrastructure approach would optimally manage flooding. Given economic barriers to expanding open space, converting roads to permeable pavements offers a possible optimization strategy. Ultimately, static area-based regulations remain insufficient; policies must transition to performance-based volumetric retention targets to mitigate downstream flooding and foster resilient communities. Full article

Improving the flood adaptability of urban waterfront spaces is an essential entry point for enhancing regional stormwater regulation capacity, scientifically preventing flood disasters, and stabilizing urban water security. Existing flood adaptability assessments mostly rely on single weighting methods and individual evaluation models, inevitably causing systematic bias and low result robustness. Against this limitation, this study integrates remote sensing intelligent interpretation, spatiotemporal landscape pattern analysis, and multi-criteria decision theory to construct a comprehensive flood adaptability evaluation system under the pressure–state–response (PSR) framework. Innovatively, a game-theoretic combined weighting scheme integrating the entropy weight method, CRITIC method, and standard deviation method is proposed, and three complementary models including TOPSIS, VIKOR, and EDAS are coupled for cross-verification evaluation, which effectively improves the objectivity and robustness of spatial flood adaptability quantification. Taking Anqing City as a typical case, this study adopts Sentinel-2 time-series remote sensing images from 2016 to 2023 and applies an optimized random forest algorithm to automatically classify land cover. Five underlying surface types, including water bodies, vegetation, farmland, built-up areas, and bare land, are accurately extracted with an overall classification accuracy of around 90% for most years. Core landscape metrics such as Shannon’s diversity index and patch density are selected to systematically analyze the spatiotemporal differentiation characteristics of waterfront landscape patterns during the study period. The results indicate the obvious spatial heterogeneity of flood adaptability in Anqing City. Yingjiang District and Yuexi County present high comprehensive flood adaptability, while Wangjiang County and Huaining County show relatively low performance. Urban areas gain strong flood resistance from complete disaster prevention infrastructures and economic resilience; mountainous areas possess natural advantages in flood retention and drainage due to high vegetation coverage and topographic relief; by contrast, plain districts are severely restricted by low-lying terrain and insufficient drainage systems, resulting in prominent flood vulnerability. The proposed method is helpful for providing reliable scientific support for waterfront landscape optimization, zoned flood disaster management, and resilient water space planning in riverine cities. Full article

Block 116 has an annual oil production of 10.2 × 10⁴ t, yet the increasing edge-water encroachment has raised the natural decline rate from 7.8% to 11.4%, significantly deteriorating production performance. The field data shows an edge-water rise rate of 0.4 m/a. Since 2023, 11 flank wells have experienced water breakthrough, resulting in a daily loss of 12.6 t and contributing 4.6% to the overall decline. To address these challenges, this study systematically evaluates development characteristics, identifies key influencing factors, and establishes optimal injection–production parameters through an integrated experimental and numerical approach. The research results show that a novel combined flooding formulation—water + foaming agent + polymer (viscoelastic) + N₂—is proposed and validated, achieving the highest recovery efficiency of 63.09%, which is 22.99% higher than conventional waterflooding. This confirms that switching to a multimedium injection strategy at mid- to high-water-cut stages can substantially improve ultimate recovery. Numerical simulation quantitatively delineates the remaining oil distribution across individual sublayers, revealing that residual recoverable reserves (76.6 × 10⁴ t) are predominantly concentrated in five specific sand bodies, providing precise targets for infill drilling. A comprehensive field-scale adjustment strategy is formulated—integrating optimized technical policies, planar and vertical injection–production improvements, and coordinated end-to-end management—which, over the 15-year forecast period, is projected to increase cumulative oil output from 149.4 × 10⁴ t to 168.1 × 10⁴ t, raising the recovery factor by 3.3%. These findings offer both theoretical insights and practical guidance for sidetracking and effective reserve utilization in analogous low-permeability reservoirs within the Changqing Oilfield and beyond. Full article

Natural floods are unusual extreme events resulting from significant or prolonged rainfall, which sometimes turn into disasters. Trends indicate that these phenomena may become more frequent in the future. Therefore, many solutions are being implemented in practice to deal with the problem. In the European Union, enhanced measures have been taken, including the assessment and mapping of flood risks, triggered by the adopted legislation. Despite these solutions, flood disasters continue to occur, even in areas included in Flood Risk Management Plans but outside the territories designated as vulnerable. To investigate the reason, a study was conducted accounting for flood genesis and the role of flood debris and anthropogenic waste as a factor that can worsen the harmful impact of these events. It was considered whether there is a gap in the application of current methods and legislation. A brief review was performed concerning the physical description of the phenomenon and the evaluation methods used, accounting for the role that debris and anthropogenic waste play in them. Some main practices and applicable tools were also discussed in brief. As an illustration of the impact, a case study of a recent significant flood in Bulgaria was also presented. This flood affected an area that is not identified as at risk under the Flood Risk Management Plans developed in accordance with the European and Bulgarian legislation and requirements. The information presented here confirms the significant role that debris and anthropogenic waste play in the process of turning a flood into a disaster and highlights the need for additional work concerning their proper incorporation in both the regulation and assessment processes. Full article

Flooding is one of the most damaging natural hazards worldwide, particularly in data-scarce watersheds where long-term hydrometeorological records are limited. This study focuses on the R’Dom watershed in the Meknes region, Morocco, and aims to improve flood susceptibility and relative flood risk assessment by integrating remote sensing, Geographic Information Systems (GIS), and multi-criteria decision-making (MCDM) approaches. The Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy Process (Fuzzy AHP/FAHP) were applied to evaluate flood hazard, vulnerability, and overall risk using seventeen conditioning factors, including topographic, hydrological, geological, land-cover, socio-economic, and infrastructure-related variables. The Flood Hazard Index (FHI), Flood Vulnerability Index (FVI), and Flood Risk Index (FRI) were calculated to produce flood susceptibility, vulnerability, and relative flood risk maps. Model validation was performed using a point-based flood inventory dataset composed of 900 locations, including 450 flood and 450 non-flood points, compiled from historical flood information, field observations, local information, official reports, and satellite-based interpretation. The dataset was divided into 70% for training and 30% for testing, and model performance was assessed using receiver operating characteristic–area under the curve (ROC-AUC) analysis. The AHP and Fuzzy AHP models showed good to excellent predictive performance, with testing AUC values ranging from 0.767 to 0.935. The AHP-based models achieved the highest testing performance, while Fuzzy AHP remained useful for representing uncertainty in expert judgment and gradual spatial transitions. The final flood risk map indicates that approximately 18.78% of the study area, corresponding to 240.62 km², is classified as having a high to very high flood risk, mainly around the Meknes conurbation and locally near the El Hajeb region. These results provide a practical decision-support tool for identifying priority areas for flood mitigation, land-use planning, and watershed management. However, the proposed GIS–MCDA approach produces relative flood susceptibility and risk classes and does not replace hydrological or hydraulic modeling for estimating flood depth, discharge, inundation extent, or return-period-based flood hazard. Full article

Global climate change and rapid urbanization have intensified extreme precipitation events, making urban pluvial flood risk management particularly urgent. However, existing research exhibits theoretical and methodological limitations in reconciling pluvial flood resilience within high-density urban development, especially lacking a quantitative framework for human mobility resilience based on natural hydrological units. To address this, this study takes 48 natural catchment areas in Shenzhen as research units. By integrating mobile phone signaling data, remote sensing imagery, and multi-dimensional spatial form indicators, it constructs a post-disaster recovery curve based on population dynamics to quantify human mobility resilience. Using Principal Component Analysis (PCA), Ordinary Least Squares (OLS) regression, and the K-means clustering method, this research analyzes the mechanisms through which green infrastructure, road network structure, and three-dimensional building morphology influence resilience. The results show that three-dimensional building morphology is the core driver of post-disaster recovery capacity, with Floor Area Ratio (FAR), Standard Deviation of Building Height (SDBH), and Building Coverage Ratio (BCR) significantly promoting recovery, while Building Shape Coefficient (BSC) exerts an inhibitory effect. A key comparative analysis reveals that the model based on natural catchment areas has significantly better explanatory power than the model using stormwater management units, and the dominant factors differ: building morphology factors are more prominent in natural hydrological units, whereas road network structure factors are more significant in stormwater management units. This study confirms that natural geographic boundaries can more authentically reveal the intrinsic “morphology–resilience” relationship, providing an important theoretical and empirical basis for optimizing the planning and management units of sponge cities in high-density urban areas. Full article

Resilience and adaptation to extreme climate events have become an urgent necessity. As cities grow denser, increasing numbers of people are exposed to water scarcity, flooding, and power grid disruptions. Immediate action is required to safeguard human lives and property. Residential buildings exert a significant environmental impact throughout their operational phase, contributing to air, land, and water pollution. A more sustainable and proactive approach to building management is essential to reduce the consumption, processing, and disposal of natural resources. This article explores the potential for biogas production from decentralised/on-site wastewater treatment systems through the co-digestion of blackwater (BW) and kitchen waste (KW) for existing residential buildings located in densely populated urban areas using hybrid grids. It addresses the importance of wastewater source separation, the use of BW and KW blends to achieve the best biogas production, and the environmental, economic and social aspects of these systems’ implementation. An extensive literature review and state-of-the-art analysis were conducted to assess the potential, main challenges, and research directions in this field. The results indicate that decentralised anaerobic systems can be technically feasible, reducing grid energy dependence, optimising water use, and valorising digestate as fertiliser—fully aligned with the EU’s Green Deal and the UN Sustainable Development Goals regarding sustainability and circularity. However, few studies address the feasibility of BW (vacuum toilet) and KW co-digestion for combined heat and power generation in hybrid grids. Further pilot- and full-scale research is therefore needed to increase system reliability and social acceptance. Full article

Participatory citizenship plays a critical role in strengthening climate change resilience, particularly in the context of natural disasters such as floods and other hydrological extremes. Citizen-generated data shared through social media platforms offer valuable real-time insights that can complement traditional environmental monitoring systems. This study proposes a machine learning-based framework to analyze multilingual news data and global X (formerly known as Twitter) data that can complement street level sensor data for improved detection and understanding of extreme hydrological events: floods and landslides. The approach identifies and filters tweets related to hazards such as floods and contextualizes them with information extracted from news reports to enhance event characterization. In addition, sentiment and emotion analysis are applied to assess public reactions and perceived event intensity. By integrating physical event signals with societal responses, the method provides a broader perspective on disaster impacts and the effectiveness of emergency responses. The results highlight the potential of combining social media analytics and machine learning to support hydrological monitoring, enhance situational awareness, and contribute to more responsive disaster management strategies in the face of increasing climate-related risks. Full article

Urban grey infrastructure, including transport corridors, flood-control systems, drainage facilities, railway margins, and industrial brownfields, is often treated in conventional planning as functionally vacant or ecologically marginal space. In this study, grey infrastructure is defined as engineered or infrastructure-dominated urban spaces and their residual or edge landscapes, rather than as green infrastructure. Yet such spaces may still contain spontaneous vegetation, water edges, soil patches, and sheltered microhabitats that can support birds, insects, small mammals, and other urban species in highly urbanized environments. From a multispecies justice perspective, this study examines spatial mismatches between PPGIS-derived public recognition and habitat quality modeled using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model in urban grey infrastructure. Using Zhanggong District, Ganzhou, China, as a case study, we developed an integrated framework that combines public participation geographic information systems (PPGIS), grid-based public recognition mapping, and the InVEST Habitat Quality model. Based on 260 valid questionnaires, participants identified locations associated with aesthetic preference and perceived habitat potential. These mapped perception points were converted into a grid-based public recognition indicator and compared with modeled habitat quality. The results indicate a marked perception-habitat mismatch. High public recognition was frequently associated with visually ordered, accessible, and highly managed urban spaces, whereas high modeled habitat quality was more strongly related to vegetated, riverine, peripheral, and semi-natural spaces. The spatial classification shows that aesthetic mismatch areas, where public recognition was high but modeled habitat quality was low, covered 43.20 km², accounting for 7.16% of the study area, whereas hidden ecological value areas, where modeled habitat quality was high but public recognition was low, covered 118.21 km², accounting for 19.59%. This study provides a replicable framework for identifying perception–habitat mismatches and supports more ecologically informed and inclusive strategies for regenerating urban grey infrastructure. More specifically, the study extends an established perception-ecology debate to grey infrastructure and residual urban spaces and demonstrates how PPGIS-derived public recognition and InVEST-modeled habitat quality can be compared within the same grid framework to locate spatially explicit alignment and mismatch. Full article

Flooding is a destructive natural hazard intensified by climate change, posing challenges to sustainable disaster risk management. This study developed and evaluated machine learning models for flood severity prediction within a hexagonal grid system (H3, resolution 8) under rainy season conditions in Maha Sarakham, Thailand. Four models Random Forest (RF), XGBoost, Gradient Boosting (GB), and Support Vector Machine (SVM) were trained using 11 environmental variables across historical years (2018, 2021, 2022) and tested on a projected year (2025) under SSP scenarios. XGBoost demonstrated the most stable performance (accuracy > 0.95 across all years), while SVM achieved high historical accuracy (0.970 average) but failed to detect positive flood cases in 2025 (recall = 0), highlighting the importance of temporal validation. Topographic variables were the most consistent predictors, but NSMI (soil moisture) emerged as the top SHAP predictor in 2025 (r = 0.52), suggesting a shift in flood-generating mechanisms under climate change. A polarization pattern was observed: flood-affected area declined to 6.8% in 2025 (79% reduction from 2022), yet maximum flood point counts remained high at 14.0, indicating more concentrated but intense flooding. Under SSP projections, using the historical baseline (27.5%), SSP1-2.6 (45.2%) and SSP2-4.5 (45.0%) indicate increased flood risk relative to the historical baseline through 2040. The SSP5-8.5 projection (3.4%) is identified as a model extrapolation artifact through formal out-of-distribution assessment (Mahalanobis distance = 8.72, p < 0.001) and is therefore excluded from policy recommendations. Although GRU and LSTM achieved marginally higher AUC values in retrospective validation, we recommend XGBoost for operational forecasting due to its temporal stability, computational efficiency, and interpretability. We further recommend integrating real-time soil moisture monitoring into early warning systems and shifting to hotspot-targeted adaptation strategies. Full article

Quantifying the net hydrological impact of large dams amidst climatic and anthropogenic influences remains a major challenge. This study isolates the effect of Three Gorges Dam (TGD) regulation on discharge at Jiujiang Station in the middle Yangtze River (2009–2016) using a novel scenario-based framework. A Long Short-Term Memory (LSTM) network, optimized by the Sparrow Search Algorithm (SSA), simulated daily discharge with high accuracy (Nash–Sutcliffe Efficiency coefficient > 0.97). By comparing a “with-TGD” simulation against a “without-TGD” scenario—generated by replacing the dam’s regulated outflow with its reconstructed natural inflow—we quantified the net impact ($\Delta Q$). Results show that $\Delta Q$ is substantially modulated by river–lake interactions. For example, in December, the backwater effect from Poyang Lake amplified the direct flow reduction by an additional −82.5 m³/s. The “peak-shaving” effect was context dependent: TGD regulation increased high flows (>30,870 m³/s) by an average of +372 m³/s while slightly decreasing low flows (<12,711 m³/s) by −31 m³/s. The impact exhibits strong seasonality alongside considerable intra-seasonal variability, reflecting multi-objective operations (flood control, power generation, water supply). This framework provides a transferable approach for attributing hydrological change in large regulated rivers and supports integrated water resources management. Full article