Search Results (4,679)

Understanding the spatiotemporal dynamics of coastal intertidal meta-ecosystems in response to sea-level rise (SLR) is essential for understanding the interactions between terrestrial and aquatic meta-ecosystems. However, given that annual SLR changes are typically measured in millimeters, ecosystems may take decades to exhibit noticeable shifts. As a result, the extent of lateral responses at a single point is constrained by the fragmented temporal and spatial scales. We integrated the tidal inundation gradient of a coastal meta-ecosystem—comprising a high-elevation flat (H), low-elevation flat (L), and mudflat—to quantify the potential application of inferring the spatiotemporal impact of environmental features, using China’s Yangtze Estuary, which is one of the largest and most dynamic estuaries in the world. We employed both flood ratio data and tidal elevation modeling, underscoring the utility of spatial modeling of the role of SLR. Our results show that along the tidal inundation gradient, SLR alters hydrological dynamics, leading to environmental changes such as reduced aboveground biomass, increased plant diversity, decreased total soil, carbon, and nitrogen, and a lower leaf area index (LAI). Furthermore, composite indices combining the enhanced vegetation index (EVI) and the land surface water index (LSWI) were used to characterize the rapid responses of vegetation and soil between sites to predict future ecosystem shifts in environmental properties over time due to SLR. To effectively capture both vegetation characteristics and the soil surface water content, we propose the use of the ratio and difference between the EVI and LSWI as a composite indicator (ELR), which effectively reflects vegetation responses to SLR, with high-elevation sites driven by tides and high ELRs. The EVI-LSWI difference (ELD) was also found to be effective for detecting flood dynamics and vegetation along the tidal inundation gradient. Our findings offer a heuristic scenario of the response of coastal intertidal meta-ecosystems in the Yangtze Estuary to SLR and provide valuable insights for conservation strategies in the context of climate change. Full article

To promote sustainable development and guide the responsible use of natural ecosystems, the United Nations introduced the concept of ecosystem accounting. Ecosystem services are key components of ecosystem accounting. Water-related ecosystem services (ES) are of primary importance for Armenia due to relatively dry climate, and dependence on irrigation water for agriculture. This study aims to conduct a pilot-level quantitative scoping assessment and mapping of key water-related regulating ES in accordance with the SEEA-EA guidelines, and to offer recommendations to initiate their accounting in Armenia. We used three Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) models—Seasonal Water Yield, Sediment Delivery Ratio, and Urban Flood Risk Mitigation. Input data for these models were sourced from global and national databases, as well as ESRI land cover datasets for 2017 and 2023. Government-reported data on river flow and water consumption were used to assess the ES supply–use balance. The results show that natural ecosystems contribute between 11% and 96% of the modeled ES, with the strongest impact on baseflow supply and erosion prevention. The average current erosion is estimated at 2.3 t/ha/year, and avoided erosion at 46.4 t/ha/year. Ecosystems provide 93% of baseflow, with an average baseflow index of 34%, while on bare ground it is only 3%. Changes in land cover from 2017 to 2023 have resulted in alterations across all assessed ES. Comparison of total water flow and baseflow with water consumption revealed water-deficient provinces. InVEST models show their general operability at the scoping phase of ecosystem accounting planning. Advancing ES accounting in Armenia requires model calibration and validation using local data, along with the integration of InVEST and hydrological and meteorological models to account for the high diversity of natural conditions in Armenia, including terrain, geological structure, soil types, and regional climatic differences. Full article

Natural ecosystems, especially those regulated by floods, are sensitive to prolonged temperature fluctuations that affect hydrology and the lateral connection between the river and its floodplain. Here, we analyzed a series of zooplankton data collected monthly from 2007 to 2016 during the ice-free period in Kopački Rit Nature Park in the Middle Danube, an area important as a food source and nursery area for fish stocks in the Danube. The aim was to find out how the long-term change in temperature and fluctuating environmental parameters affect the succession of zooplankton in the warmer (from April to September) and colder parts of the year (from October to March). Throughout the decade, total nitrogen concentrations showed significant differences between years, with an increase since 2012. Despite the increase in nitrogen levels and the expected increase in primary production, the higher nitrogen levels were accompanied by lower zooplankton biomass. A significant difference was found between the values of the zooplankton geometric mean index, with 73% of the variance explained by the difference between groups. In general, a trend toward a significant decrease in zooplankton biomass, with a simultaneous increase in the number of species and high turnover rates, was observed throughout the decade. Full article

Sewer systems are essential for sustainable infrastructure management, influencing environmental, social, and economic aspects. However, sewer network capacity is under significant pressure, with many systems overwhelmed by challenges such as climate change, ageing infrastructure, and increasing inflow and infiltration, particularly through groundwater infiltration (GWI). Current research in this area has primarily focused on general sewer performance, with limited attention to high-resolution, spatially explicit assessments of sewer exposure to GWI, highlighting a critical knowledge gap. This study responds to this gap by developing a high-resolution GWI assessment. This is achieved by integrating fuzzy-analytical hierarchy process (AHP) with geographic information systems (GISs) and machine learning (ML) to generate GWI probability maps across the Dawlish region, southwest United Kingdom, complemented by sensitivity analysis to identify the key drivers of sewer network vulnerability. To this end, 16 hydrological–hydrogeological thematic layers were incorporated: elevation, slope, topographic wetness index, rock, alluvium, soil, land cover, made ground, fault proximity, fault length, mass movement, river proximity, flood potential, drainage order, groundwater depth (GWD), and precipitation. A GWI probability index, ranging from 0 to 1, was developed for each 1 m × 1 m area per season. The model domain was then classified into high-, intermediate-, and low-GWI-risk zones using K-means clustering. A consistency ratio of 0.02 validated the AHP approach for pairwise comparisons, while locations of storm overflow (SO) discharges and model comparisons verified the final outputs. SOs predominantly coincided with areas of high GWI probability and high-risk zones. Comparison of AHP-weighted GIS output clustered via K-means with direct K-means clustering of AHP-weighted layers yielded a Kappa value of 0.70, with an 81.44% classification match. Sensitivity analysis identified five key factors influencing GWI scores: GWD, river proximity, flood potential, rock, and alluvium. The findings underscore that proxy-based geospatial and machine learning approaches offer an effective and scalable method for mapping sewer network exposure to GWI. By enabling high-resolution risk assessment, the proposed framework contributes a novel proxy and machine-learning-based screening tool for the management of smart cities. This supports predictive maintenance, optimised infrastructure investment, and proactive management of GWI in sewer networks, thereby reducing costs, mitigating environmental impacts, and protecting public health. In this way, the method contributes not only to improved sewer system performance but also to advancing the sustainability and resilience goals of smart cities. Full article

Earthen archaeological sites are particularly vulnerable to rain and winds, whose effects may compromise their integrity. The Huaca Chotuna (HC; 8th–16th Century AD) is an adobe platform in Peru’s semi-arid Lambayeque region, and it is in an area with exposure to rain and winds associated with the El Niño Southern Oscillation (ENSO) events. Here we present the results from an orthophotogrammetric and morphometric study aimed at quantifying the effects of erosion and deposition at the HC. The novelty of our approach consists of merging topographic, hydrological, and wind parameters to recognize the sector of the HC with exposure to potentially damaging natural climatic phenomena. We identify zones affected by erosion and deposition processes. Results of a diffusion model aimed to estimate the HC sectors where these processes will act in the next century are also presented. Gully erosion from rainfall indicates a vertical erosion rate of approximately 0.2 m/century, demonstrating the low preservation potential of the HC. Rainwater also deteriorates adobe bricks and triggers water/mud flows. Conversely, sediment-laden winds contribute to the partial burial of the HC. The findings highlight significant hazards to the HC’s structural integrity, including gravity instability. The interdisciplinary methodology we adopt offers a key framework for assessing and protecting other earthen sites globally against the escalating impacts of climate change. Full article

Coastal lagoons provide vital ecological functions, supporting diverse flora and fauna while being highly sensitive to environmental changes. In the southern Baltic Sea, the Puck Lagoon is a hydrologically distinct subregion of the Gulf of Gdańsk characterized by variable exchange of water with the outer bay and substantial freshwater inflows. Its benthic communities are particularly sensitive to salinity, yet the processes shaping this parameter remain insufficiently understood. In situ measurements in summer 2020 revealed relatively high salinity in the lagoon (up to 7.7 PSU) compared to the adjacent outer bay (7.2–7.4 PSU), with localized reductions near the Kuźnica Passage and the Reda River mouth. As a first step toward explaining the hydrodynamic processes responsible for these anomalies, we applied a high-resolution, two-dimensional model focused on three fundamental physical drivers: river inflows, open-boundary exchange, and wind forcing. These processes represent the primary controls on salinity in shallow lagoons and provide a basis for evaluating additional mechanisms. The model reproduced observed patterns with a mean absolute error of 0.15 PSU, confirming that this selective framework captures the key features of salinity variability and establishes a baseline for future three-dimensional modeling that will incorporate further processes such as vertical mixing, precipitation, and evaporation. Full article

Climate change is increasingly altering rainfall regimes and hydrological processes, posing major challenges to reservoir operation, flood control, and hydropower production. Understanding its impacts on the Ban Chat reservoir in Northwest Vietnam is therefore crucial for ensuring reliable water resource management under future uncertainties. This study aims to assess potential changes in streamflow to the Ban Chat reservoir under different climate change scenarios. The study employed nine Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) under three Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5). Future climate projections were bias-corrected using the Quantile Delta Mapping (QDM) method and used as input for the Hydrological Engineering Center–Hydrological Modeling System (HEC-HMS) to simulate future inflows. Streamflow changes were evaluated for near- (2021–2040), mid- (2041–2060), and late-century (2061–2080) periods relative to the baseline (1995–2014). Results show that under SSP1-2.6, mean annual discharge and flood-season flows steadily increase (up to +6.9% by 2061–2080), while storage deficits persist (−27.7% to −13.1%). Under SSP2-4.5, changes remain small, with flood peaks limited to +4.5% mid-century, but severe dry-season deficits continue (−29.5% to −24.4%). In contrast, SSP5-8.5 projects strong late-century increases in mean flows (+7.5%) and flood peaks (+8.2%), though early-century flood flows decline (−2.1%). These findings provide essential scientific evidence for adaptive reservoir operation, hydropower planning, and flood risk management, underscoring the significance of incorporating climate scenarios into sustainable water resource strategies in mountainous regions. Full article

Reservoir evaporation is a vital component of the hydrological cycle and presents considerable challenges for sustainable water management, especially in arid and semi-arid regions. This study assesses the effectiveness of two Artificial Intelligence (AI) methods: Multilayer Perceptron (MLP) and Adaptive Neuro-Fuzzy Inference System (ANFIS), a combination ANN with fuzzy logic, in estimating daily evaporation from a large reservoir in a semi-arid region. Using eight years of hydrometeorological data from a nearby station, the study employed the ReliefF algorithm as a feature selection method for relevant input variables. The dataset was divided into training, validation, and testing subsets with 5% and 10% validation ratios, using four train–test splits of 70:30, 75:25, 80:20, and 85:15. Various training algorithms (e.g., Levenberg–Marquardt) and membership functions (e.g., generalized bell-shaped functions) were tested for both models. MLP consistently outperformed ANFIS on the test sets, showing higher R² and lower RMSE values. In the best-performing 70:30 split, MLP achieved an R² of 0.8069 and RMSE of 0.0923, compared to ANFIS with an R² of 0.3192 and RMSE of 0.2254. The findings highlight the AI-based approaches’ potential to support improved evaporation forecasting and integration into decision support tools for water resource planning amid changing climatic conditions. Full article

With climate change, the frequency and severity of localized heavy rainfalls are increasing. Thus, for urban drainage networks (UDNs), particularly those in aging cities such as Seoul, Republic of Korea, flood risk management challenges are mounting. Conventional design standards typically apply uniform roughness coefficients based on new pipe conditions, neglecting the ongoing performance degradation from physical influences. This study introduces a methodology that systematically incorporates pipe age and size into roughness coefficient scenarios for higher-accuracy 1D–2D rainfall–runoff hydrologic–hydraulic simulations. Eleven roughness scenarios (a baseline and ten aging-based scenarios) are applied across seven UDNs using historical rainfall data. The most representative scenario (S3) is identified using a Euclidean distance metric combining the peak water-level error and root mean square error. For two rainfall events, S3 yields substantial increases in the simulated mean flood volumes (75.02% and 76.45%) compared with the baseline, while spatial analysis reveals significantly expanded inundation areas and increased flood depths. These findings underscore the critical impact of pipe deterioration on hydraulic capacity and demonstrate the importance of incorporating aging infrastructure into flood modeling and UDN design. This approach offers empirical support for updating UDN design standards for more resilient flood management. Full article

The construction of the Xinyang Urban Water Supply Project, centered on the Chushandian Reservoir, required a thorough investigation of high–low runoff encounters between the water source and receiving areas to optimize water allocation and operational scheduling. Based on the hydrological stations at Changtaiguan (CTG) on the main stream of the Huaihe River (HR) in the water source area and Miaowan (MW) on the main stream of the Honghe River in the receiving area, the trends and abrupt change characteristics of monthly runoff from 2014 to 2024 were analyzed using methods such as extremum symmetry mode decomposition (ESMD) and heuristic segmentation, with spatial encounter patterns determined using Copula functions. The results indicate that (1) the runoff in the water source area showed a quasi-6.05-month periodic characteristic on a monthly scale, while the runoff in the receiving area exhibited a quasi-6.72-month periodic characteristic on a monthly scale; (2) the water source area experienced runoff mutation in August 2015 (extreme drought) and June 2024 (extreme precipitation), with the receiving area responding 7 months earlier than the water source area, revealing differences in system vulnerability; (3) synchronous hydrological states were significantly more likely to occur (51.2%) compared with asynchronous conditions (25.2%), with the highest probability of “concurrent drought” (19.8%) and a high-risk “normal water source—receiving area drought” combination (14.1%). These findings provide theoretical and technical support for the optimized scheduling of the Chushandian Reservoir, improving the resilience and adaptability of the Xinyang Urban Water Supply Project to climate fluctuations and extreme hydrological events. Full article

This review examines South Africa’s escalating flood vulnerability through a synthesis of over 80 peer-reviewed articles, historical records, policy reports, and case studies. Using a PRISMA-guided analysis, the study identifies key climatic drivers, including extreme rainfall from tropical–temperate interactions, cut-off lows, and La Niña conditions that interact with structural weaknesses such as inadequate drainage, poorly maintained stormwater systems, and rapid urban expansion. Apartheid-era spatial planning has further entrenched risk by locating marginalised communities in floodplains. Governance failures like weak disaster risk reduction (DRR) policies, fragmented institutional coordination, and insufficient early warning systems intensify flood vulnerabilities. Catastrophic events in KwaZulu-Natal (KZN) and the Western Cape (WC) illustrate the consequences exemplified by the April 2022 KZN floods alone, which caused over 450 deaths, displaced more than 40,000 people, and generated damages exceeding ZAR 17 billion. Nationally, more than 1500 flood-related fatalities have been documented in the past two decades. Emerging resilience pathways include ecosystem-based adaptation, green infrastructure, participatory governance, integration of Indigenous knowledge, improved hydrological forecasting, and stricter land-use enforcement. These approaches can simultaneously reduce physical risks and address entrenched socio-economic inequalities. However, significant gaps remain in spatial flood modelling, gender-sensitive responses, urban–rural disparities, and policy implementation. The review concludes that South Africa urgently requires integrated, multi-scalar strategies that combine scientific innovation, policy reform, and community-based action. Embedding these insights into disaster management policy and planning is essential to curb escalating losses and build long-term resilience in the face of climate change. Full article

Urbanization is a driving force of landscape transformation. One of the ecosystems most vulnerable to urban expansion processes is montane forests located in high altitude mountainous regions. Despite their significance for biodiversity, regulation of the hydrological cycle, stability, prevention of soil erosion, and potential for organic carbon storage, these forest ecosystems show high vulnerability and risk due to the global urbanization process. We analyzed the potential variations produced by land cover change in some attributes related to soil organic matter in transitional forest fragments due to the expansion of a predominantly urban matrix landscape. We identified and characterized a fragment of a high montane evergreen forest in the Western Cordillera of the Northern Andes located in the urban limits of Quito. Then, we comparatively analyzed the variations in the attributes associated with soil organic carbon: soil organic matter, density, texture, nitrogen, phosphorus, and pH. We also considered the following soil coverages: forest, eucalyptus plantations, and grassland. We viewed the latter two as hinge coverages between forests and urban expansion. Finally, we estimated variations in soil organic carbon stock in the three analyzed coverages. For the montane forest fragment, we identified 253 individuals distributed among 18 species, corresponding to 10 families and 14 genera. We found significant variations in soil attributes associated with organic matter and an estimated 66% reduction in the carbon storage capacity of montane soils when they lose their natural cover and are replaced by Eucalyptus globulus plantations. Urban planning strategies should consider the conservation and restoration of natural and degraded peri-urban areas, ensuring sustainability and utilizing nature-based solutions for global climate change adaptation and mitigation. Peri-urban agroforestry systems represent an opportunity to replace and restore conventional forestry or crop plantation systems in peri-urban areas that affect the structure and function of ecosystems and, therefore, the goods and services derived from them. Full article

This study assesses the impact of climate change and glacier retreat on river runoff in the high-altitude Terek River Basin using the physically based ECOMAG hydrological model. Sensitivity experiments examined the influence of glaciation, precipitation, and air temperature on runoff variability. Results indicate that glacier retreat primarily affects streamflow in upper reaches during peak melt (July–October), while precipitation changes influence both annual runoff and peak flows (May–October). Rising temperatures shift snowmelt to earlier periods, increasing runoff in spring and autumn but reducing it in summer. The increase in autumn runoff is also due to the shift between solid and liquid precipitation, as warmer temperatures cause more precipitation to fall as rain, rather than snow. Scenario-based modeling incorporated projected glacier area changes (GloGEMflow-DD) and regional climate data (CORDEX) under RCP2.6 and RCP8.5 scenarios. Simulated runoff changes by the end of the 21st century (2070–2099) compared to the historical period (1977–2005) ranged from −2% to +5% under RCP2.6 and from −8% to +14% under RCP8.5. Analysis of runoff components (snowmelt, rainfall, and glacier melt) revealed that changes in river flow are largely determined by the elevation of snow and glacier accumulation zones and the rate of their degradation. The projected trends are consistent with current observations and emphasize the need for adaptive water resource management and risk mitigation strategies in glacier-fed catchments under climate change. Full article

Estimating the impacts of climate change on streamflow in the Xiaoxingkai Lake Basin is vital for ensuring sustainable water resource management and transboundary cooperation across the entire Xingkai Lake Basin, a transboundary lake system shared between China and Russia. In this study, 11 Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) under two Shared Socioeconomic Pathways (SSP245 and SSP585) were used to drive the Soil and Water Assessment Tool Plus (SWAT+) model. Streamflow projections were made for two future periods: the 2040s (2021–2060) and the 2080s (2061–2100). To correct for systematic biases in the GCM outputs, we applied the Delta Change method, which significantly reduced root mean square error (RMSE) in both precipitation and temperature by 3–35%, thereby improving the accuracy of SWAT+ simulations. To better capture inter-model variability and enhance the robustness of streamflow projections, we used the Bayesian Model Averaging (BMA) technique to generate a weighted ensemble, which outperformed the simple arithmetic mean by reducing uncertainty across models. Our results indicated that under SSP245, greater increases were projected in annual streamflow as well as in wet and normal-flow seasons (e.g., streamflow in normal-flow season in the 2080s increased by 13.0% under SSP245, compared to 7.0% under SSP585). However, SSP585 produced a much larger relative amplification in the dry season, with percentage changes relative to the historical baseline reaching up to +171.7% in the 2080s, although the corresponding absolute increases remained limited due to the low baseline flow. These findings quantify climate-driven hydrological changes in a cool temperate lake basin by integrating climate projections, hydrological modeling, and ensemble techniques, and highlight their implications for understanding hydrological sustainability under future climate scenarios, providing a critical scientific foundation for developing adaptive, cross-border water management strategies, and for further studies on water resource resilience in transboundary basins. Full article

Mosses are key players in semi-arid ecosystems; however, the functional roles of mosses on hydrologic buffering and water quality have hardly been assessed. In the present study, the water storage, saturation dynamics, and ion release experiment of a set of four moss species (Hypnum lacunosum, Homalothecium lutescens, Dicranum scoparium, and Tortella tortuosa) was performed by a more simplified immersion and drainage procedure with water chemistry analyses. All species reached a sorption equilibrium between 10 and 20 min, with pleurocarpous taxa retaining 20–35% more water than acrocarpous species and possessing water-holding capacities (WHCs) between 300% and 700% of dry weight. Species-specific differences in water chemistry (pH, EC, and TDS) were observed: Tortella tortuosa presented the greatest ionic flux, and Hypnum lacunosum presented little variation in pH and electrical conductivity. These findings imply that the mosses operate as micro-scale buffers regulating both water quantity and water quality, and thereby the soil stability, infiltration, and drought resilience. The combined hydrological and biogeochemical view offers a novel understanding of bryophyte ecohydrology and highlights the significance of mosses in the practice of watershed management and climate-change mitigation. Full article