Search Results (394)

Assessing run-of-river small hydropower (SHP) potential requires balancing conflicting technical, economic, and socio-environmental criteria. Traditional assessment frameworks rely on discrete point-based site inventories, which often overlook regional landscape constraints and project overlap. To overcome this limitation, this study introduces the concept of a Feasibility Surface ($FS$), a novel, continuous spatial landscape that maps overall development viability across an entire drainage basin. Operating within a Geographic Information System ($GIS$), we integrated the Analytic Hierarchy Process ($AHP$) to systematically weight nine multi-dimensional variables across Economic, Ecological, and Social criteria. Input layers were max-normalized using criterion-specific rules and aggregated through a weighted linear combination to generate a continuous Feasibility Index ($FI$). Applied to the Huazuntlán River basin in Mexico, the resulting continuous surface successfully delineates optimal development corridors, moving beyond fixed-point targets. Local one-at-a-time sensitivity analyses confirmed that these spatial clusters are physically robust and highly stable under weight variations. Furthermore, an exhaustive combinatorial search was executed over the continuous surface to extract optimal, non-overlapping multi-plant portfolios that avoid hydraulic interference. Mathematically and practically, this continuous feasibility landscape provides a valuable macro-screening tool for sustainable water resource planning. It allows environmental managers and energy developers to prioritize alternative exploitation corridors, balance localized ecological constraints, and optimize distributed renewable energy portfolios without compromising basin-scale ecological integrity. Full article

The Chushandian Irrigation Area (CSDIA) lacks a comprehensive drought index integrating meteorological and hydrological information, hindering accurate drought assessment and sustainable water resource management under changing climatic conditions. To address this, a multivariate standardized drought index (MSDI) based on a Copula function was developed, combining precipitation and runoff. Optimized run theory identified compound drought events, and cross-wavelet power spectrum explored large-scale climate drivers. Results show that MSDI correlates strongly with both the Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI) (Pearson’s r > 0.75, p < 0.01) at the monthly scale, effectively capturing drought onset, duration, and termination. From 1960 to 2018, 110 compound drought events were identified, characterized by short durations (mean 3.82 months) and low intensities (mean 4.43). The most severe event (August 1960–October 1961, duration 15 months, intensity 22.72) has a return period of about 40 years. Among nine teleconnection factors, ENSO is the dominant driver, followed by sunspot activity (SSI). BEAST change-point detection revealed a shift toward drought intensification after 1990, underscoring the need for adaptive water management strategies. These findings provide scientific support for sustainable drought monitoring, climate-resilient agricultural planning, and adaptive water management in CSDIA, contributing to the broader goal of ensuring food security and water sustainability in monsoon-dependent irrigation systems. Full article

This study aims to assess the impact of the October 2023 Gaza War on water and sanitation systems and propose actionable solutions for effective management. The study adopted a mixed-methods approach (quantitative and qualitative). Primary data were collected through semi-structured interviews, targeted questionnaires, and direct field observations. Secondary data were gathered from reports by international organizations (UNRWA, OCHA, WHO), Palestinian authorities, academic research, in addition to satellite imagery and Geographic Information System (GIS) data for damage assessment. The results showed that the institutional level of emergency preparedness before the war varied significantly. Despite the existence of pre-developed emergency plans (mean score 3.26, relative weight 65.28%, p = 0.0355), there were significant shortcomings in practical staff training (mean score 2.64, relative weight 52.83%, p = 0.006), logistical readiness, and the activation of international partnerships. The study also revealed major challenges faced in providing water and sanitation services during the war, including fuel and resource shortages, safety risks for field teams, weak coordination with security agencies, lack of materials and equipment, insufficient emergency funding, coordination gaps, staff displacement, communication breakdowns, difficulty accessing water sources, area division and blockade, and loss of personnel. Specifically, the inability to access water sources was a critical challenge (mean score 4.30, relative weight 86.04%, p < 0.0001), as was indiscriminate shelling impacting field team safety (mean score 4.19, relative weight 83.77%, p < 0.0001) and lack of materials and equipment (mean score 4.15, relative weight 83.02%, p < 0.0001). Residents reported water availability only every 10–15 days, and over 70% of water and sanitation systems were damaged. While funding proposals were being prepared (mean score 3.26, relative weight 65.28%, p = 0.02), weaknesses in reporting systems and coordination of roles were observed (mean score 2.55, relative weight 50.94%, p < 0.0001). The research contributes to guiding local and international efforts towards reconstruction, enhancing resilience, and ensuring the provision of safe drinking water and adequate sanitation for the affected population, thereby reducing the risks of waterborne diseases and improving public health. Full article

Reliable and harmonised soil information remains critically limited across Africa, constraining soil monitoring, climate-resilient agriculture, and evidence-based land management. Existing soil resources are often fragmented, spatially uneven, outdated, or derived from legacy observations, limiting their usefulness for contemporary continental-scale assessment. The Soils4Africa project implemented a coordinated field campaign across 33 African countries between 2022 and 2025 to establish a harmonised soil monitoring framework for agricultural lands. Using a hierarchical probabilistic sampling design, 24,951 soil samples were collected from 14,311 locations, supported by standardised field protocols, digital data capture, QR-based sample traceability, and centralised quality control. This paper presents the conceptual, operational, and data-management framework underpinning the survey and reports baseline field observations on farming systems, land management, vegetation structure, and soil physical constraints. The framework achieved more than 70% of planned sampling coverage despite major logistical, environmental, and security-related constraints. Baseline observations show that African agricultural landscapes remain dominated by smallholder systems, low external input use, limited soil and water conservation, and widespread dependence on rainfed production. Field indicators also reveal sparse woody vegetation cover and common physical constraints, including compaction, coarse fragments, shallow effective rooting depth, and subsoil barriers. Unlike earlier continental resources based largely on legacy profiles or site-based surveillance, Soils4Africa provides a contemporary, harmonised, spatially structured field-survey framework designed to support future laboratory-based soil assessment, digital soil mapping, land suitability analysis, and long-term soil monitoring. The study therefore provides a scalable model for coordinated soil monitoring across diverse African agroecosystems and establishes an operational baseline for subsequent analytical studies. Full article

Accurate drought prediction is essential for sustainable water resource management, agricultural planning, and climate resilience. However, drought signals are inherently nonlinear and non-stationary, making reliable predictions particularly challenging. Although current models have demonstrated promising prediction capabilities, their performance is often limited when learning directly from complex drought signals. To address this challenge, we proposed a novel drought prediction model that integrates the Overcomplete Rational Dilation Wavelet Transform (ORDWT) with a Stacked Long Short-Term Memory (SLSTM) network, referred to as the ORDWT-SLSTM. The proposed model first decomposes drought signals into multiple frequency components using ORDWT to preserve multi-scale characteristics while minimizing information loss. Subsequently, the decomposed components are modeled using SLSTM to capture complex temporal dependencies and long-term drought persistence patterns. The effectiveness of the proposed model was evaluated using the standardized precipitation index (SPI) at multiple prediction horizons (SPI-1, SPI-3, SPI-6, and SPI-12) across three climatic regions in Queensland, Australia, namely, Mackay, Gatton, and Darling Downs. The proposed model, the ORDWT-SLSTM, is compared with several benchmark models, including Gated Recurrent Unit (GRU), Long Short-Term Memory (LSTM), and Bidirectional Long Short-Term Memory (BiLSTM). The Root-Mean-Square Error (RMSE), Mean Absolute Error (MAE) and Nash–Sutcliffe efficiency (NSE) are used to evaluate the proposed models. The proposed model, the ORDWT-SLSTM, obtained the best prediction performance compared with the state-of-the-art models: RMSE = 0.215, MAE = 0.125, NSE = 0.986; RMSE = 0.260, MAE = 0.147, NSE = 0.973; RMSE = 0.225, MAE = 0.130, NSE = 0.980 for Darling Downs, Gatton, and Mackay, respectively. The obtained results demonstrated the efficiency of the proposed ORDWT-SLSTM model in long-term and short-term drought prediction. The proposed ORDWT-SLSTM model offers significant practical value for operational drought management by providing reliable early-warning information that supports agricultural planning, water allocation decisions, and drought risk mitigation. Full article

The Lake Worth Lagoon is an urban subtropical estuary impaired by discharge conveyed through the C-51 canal. To date, the origin of impairment has not been rigorously demonstrated. This study successfully applied a balance-of-flow framework to identify the predominant water source(s) conveyed to the S5A Complex, located at the headwaters of the C-51 canal. The results reveal distinct seasonal differences. During the dry season, water delivered to the S5A Complex was predominantly derived from Lake Okeechobee. During the wet season, agricultural runoff was the predominant source. Over the duration of the study, S5A Complex water management operations released 72% of the annual flow into the C-51 canal during the dry season. During the wet season, the predominant source of water flowing through the C-51 canal was locally derived from urban stormwater runoff. These findings contradict previous studies that have reported that Lake Worth Lagoon pollutant loads are derived from wet-season agricultural runoff. The analysis also revealed that recent construction upgrades designed to improve the quality of water released to the northern Everglades have (1) reduced the volume of lake water delivered to the S5A Complex during the dry season and (2) created a novel water source that, at times, contributes substantially to the S5A Complex. The results of this study deviate substantially from the currently accepted paradigm regarding the origin of Lake Worth Lagoon impairment, thus affirming the value of the periodic reassessment of adaptive management plans to ensure resource management and restoration strategies are based upon the best available information. Full article

Flood risks are escalating under climate change, necessitating advanced methods to improve runoff prediction and multivariate flood-risk assessment. In this study, a physics–XGBoost-based Bayesian model averaging with bivariate copulas (PXB-BVC) framework was developed by integrating the Soil and Water Assessment Tool (SWAT), the Hydrologiska Byråns Vattenbalansavdelning (HBV) model, Extreme Gradient Boosting (XGBoost), Bayesian model averaging (BMA), and bivariate copulas. Spatially detailed underlying surface parameters including 30 m land-use data derived from the 2000 China land-use remote sensing monitoring data were pre-processed and reclassified using ArcGIS to support spatially explicit hydrological simulation. The framework was applied to the Xiangxi River Basin (XXRB), China, under four general circulation models and three shared socioeconomic pathways. PXB-BVC improved daily runoff simulation by combining process-based hydrological information with nonlinear machine learning correction, achieving Nash–Sutcliffe efficiency (NSE) values of 0.95 during calibration and 0.89 during validation. Future runoff generally increased from the near-term to the late-century period, with stronger changes under SSP585 and Sen slopes reaching up to 0.46 m³ s⁻¹ yr⁻¹, although the magnitude and significance of trends varied among GCMs. The dependence structures among flood peak, flood volume, and flood duration showed non-stationary behavior under future climate forcing, with Kendall’s tau for peak–volume pairs mostly ranging from 0.6 to 0.8. The revised bivariate return-period analysis further indicates that inferred flood-risk changes depend on the joint risk definition. Under SSP245 and ACCESS-ESM1–5, OR-type joint return periods show that representative near-future 50-year events may become more frequent in 2061–2100, whereas AND-type return periods show weaker and less uniform changes among flood-characteristic pairs. Conditional probability analysis also indicates enhanced compound risk under high-emission conditions: given an extreme peak flow, the probability of accompanying high flood volume increases from 0.23 to 0.56, while the probability of prolonged duration increases from 0.18 to 0.45. These results demonstrate that the PXB-BVC framework can support non-stationary multivariate flood-risk assessment and provide useful information for climate-resilient water-resource management and infrastructure planning. Full article

Water Resources Plans (WRPs) are foundational policy instruments globally, yet implementation rates remain persistently low. Without consistent action classification, policymakers cannot define what to measure, track outcomes systematically, or generate evidence for adaptive learning. This study develops and validates a comprehensive typology of water resources actions, positioning it as a foundational framework for systematic performance measurement and international transferability. The typology was constructed through a rigorous multi-phase methodology: initial consolidation and unification of actions from Ceará’s hydrographic plans (serving as a methodological foundation due to the state’s comprehensive participatory water resources planning process, 2021–2024), expert consensus via focal group discussions, and empirical validation across the entire Brazilian national context. Validation encompassed 53 Water Resources Plans (20 Brazilian state plans, 14 Brazilian river basin plans, and 19 international plans), achieving 99.6% applicability. The typology operationalizes action classification through 13 first-order categories and 160 subtypes, organized around the concept of ‘deliverable’—a governance-neutral principle that permits instantiation across diverse institutional arrangements. The identified action categories reflect universal principles of water management maturity recognized in international planning contexts (European Water Framework Directive, Turkish and Moroccan water governance systems), demonstrating that the typology captures generalizable patterns of adaptive planning behavior rather than Brazil-specific peculiarities. Furthermore, the typology’s governance-agnostic design—based on deliverable-centered logic rather than institutional-specific procedures—enables its adaptation to diverse water governance models, from highly decentralized (Brazil’s basin committees) to centralized systems (as in other countries). By offering a structured and comprehensive categorization, this typology functions as a valuable menu of action types for future Water Resources Plans development, ensuring a holistic consideration of potential interventions. Its dual role—as a precursor to robust indicator development and as a guide for future planning—underscores its transformative potential for both assessing past actions and informing prospective water management. Full article

Local threshold limits translate abstract information on hydrological drought into concrete operational guidance for individual water resources. For reservoirs, surface water intakes, and groundwater sources that are important to a region, key monitored quantities and failure conditions are identified, critical levels corresponding to loss of function or unacceptable quality are derived, and an advance time to reach them is set. From these, threshold values analogous to flood stages are calculated, possibly varying over the year with the hydrological regime and demand. Implemented through regional drought plans and displayed in the HAMR (Hydrology–Agronomy–Meteorology–Retention drought monitoring and prediction system, hamr.chmi.cz), local threshold limits complement nationwide warnings by capturing the specific behaviour of each resource and enabling timely, proportionate and locally accepted drought management actions. Full article

In arid and semi-arid regions, groundwater recharge is a key process controlling the sustainability of subsurface water resources. This study aims to assess and map the groundwater recharge potential of the Oued Cherrat watershed (Morocco) using an integrated approach combining Geographic Information Systems (GIS) and the Analytic Hierarchy Process (AHP). Six controlling factors were considered: lithology, lineament density, drainage network density, slope, land use/land cover derived from the Normalized Difference Vegetation Index (NDVI), and rainfall. The relative weights of these factors were determined through pairwise comparisons using the Saaty fundamental scale, and the consistency of the judgments was verified (CR < 0.1). The reclassified thematic layers were integrated into a GIS-based weighted overlay model to generate the groundwater recharge potential map. Five recharge classes were identified, ranging from very low to very high. The results show that areas with moderate recharge potential are the most widespread (approximately 37% of the watershed), while high and very high potential zones account for about 25% of the total area. These zones are mainly associated with permeable lithologies, high densities of structural discontinuities, gentle slopes, and low drainage density. In contrast, low to very low recharge potential areas are related to low-permeability formations, steep slopes, and dense drainage networks. The resulting recharge potential map provides a useful decision-support tool for sustainable groundwater management and for identifying priority areas for aquifer protection and artificial recharge planning in the Oued Cherrat watershed. Full article

Standardized drought indices such as the Standardized Precipitation Index (SPI) are widely used in both monitoring and climate-change impact assessments. However, SPI values are not uniquely defined unless the reference climatology used for standardization is explicitly stated and justified−a methodological issue that becomes critical under non-stationary climate conditions. Here, we present a methodological assessment of how reference-climatology strategy affects SPI-based drought projections under climate change, using Türkiye’s 26 major basins as a hydroclimatically diverse testbed. These assessments inform sustainable water resources planning, agricultural adaptation, and climate-resilient infrastructure design under non-stationary climate. Daily precipitation projections from 56 GCM-RCM pairs (EURO-CORDEX EUR-11, 0.11° (approximately 12 km at the mid-latitudes of the study domain); CMIP5 RCP8.5) were bias-corrected against ERA5-Land and aggregated to basin means. We computed SPI-9 and compared two commonly used reference strategies: (i) a fixed historical baseline (1970–2005), applied consistently to both historical and future periods (fixed-baseline SPI); and (ii) a period-specific baseline (period-specific SPI; future SPI values are standardized to the climatology of the future evaluation period itself). Using the same climate simulations, the two strategies yield markedly different drought projections. At the country scale, end-of-century drought time reaches 458 months under the fixed-baseline strategy, whereas the period-specific strategy indicates 393 drought months. Corresponding severity summaries are likewise stronger under fixed-baseline standardization. The contrast is even stronger in several Mediterranean basins, where fixed-baseline standardization produces persistently severe drought conditions. These results show that SPI-based drought projections are substantially sensitive to the choice of reference-climatology strategy, and that the same climate ensemble can support materially different drought narratives depending on how anomalies are standardized. Because the two strategies differ in both reference-timing and calibration-window length (36 versus 95 years), the headline contrast should be interpreted as a combined effect rather than as a pure baseline-timing result. In the present implementation, the period-specific strategy uses a single future calibration period (2006–2100), so the comparison should be interpreted as a stress test of reference framing under non-stationary climate rather than as an equal-length baseline experiment. An equal-length late-baseline sensitivity check (1970–2005 versus 2065–2100; both spanning 36 years) shows that the fixed-to-late-baseline contrast is larger than the fixed-to-period-specific contrast in 25 of 27 spatial units, including a 3.0-fold amplification at the national scale, indicating that the reference-timing effect persists when calibration-window length is held constant. Because the analysis is based on a CMIP5-driven RCP8.5 ensemble, the numerical projections should be interpreted as a high-end stress-test envelope rather than as the most likely outcome. We therefore recommend that drought projection studies explicitly report the reference-climatology strategy, justify the calibration window, and distinguish between analyses designed to quantify change relative to a historical climate and analyses designed to describe anomalies relative to an evolving future climate. These methodological choices have direct implications for sustainable water resources management and drought-risk preparedness in water-stressed Mediterranean systems, and contribute to broader sustainability targets such as Sustainable Development Goal 6 (Clean Water and Sanitation), SDG 13 (Climate Action), and SDG 15 (Life on Land). Full article

In 2018, over half of the world’s population lived in urban areas, and this figure is expected to continue to increase over the next 25 years. Water security in growing urban areas is becoming increasingly important. Current global warming can pose additional challenges for sustainable water resource management. In this study, the city of Krakow (Poland) and its water supply system were considered. The MK and Spearman tests were used to detect trends in the studied data and the residuals from the Ensemble Empirical Mode Decomposition (EEMD) method. The analyses indicate that for 1971–2020, significant increasing trends (p < 0.05) in annual air temperature (0.36–0.46 °C/decade) were accompanied by significant trends in annual precipitation, with differences in direction and intensity (approx. −8 and 30 mm/decade). Similarly, significant trends in annual river flow for the two main sources of drinking water for Krakow (the Raba and Rudawa rivers) differed in both direction and intensity (0.51 m∙s⁻¹ and −0.05 m∙s⁻¹, respectively). The study also examined trends for individual months of the year, which largely explained the observed annual trends. Furthermore, the results of cross-correlation and autocorrelation analyses suggest that the identified decreasing trend in the Rudawa flow may be partly related to the significantly reduced underground recharge in the Rudawa catchment. The information obtained in this work can be used for more realistic and sustainable water resource management and urban-water-security planning. Full article

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

Groundwater level mapping is used in order to detect aquifer locations, flow paths, recharge zones, and contamination/pollution of groundwater. This is crucial for water management, environmental studies and resource planning focusing on landfills. This study involves the collection of monitoring well data and the mapping of the groundwater table at the Mavrorachi landfill site using Geographic Information Systems (GISs). The monitoring period spans from 2008 (startup) to 2025 (the current full year) for the 11 monitoring boreholes. Interpolation methods in GISs enabled us to map the groundwater level, while spatial analysis tools modeled the potential groundwater flow. The above process proved to be a valuable tool for modeling groundwater resources. The monitoring of groundwater level is essential to prevent the impact of leachate generated from landfill. Full article

The Tomarrazón-Camarones Basin (La Guajira, Colombia) is characterized by frequent, widespread flooding and, anthropogenically, by intense instream sediment mining. Mapping flood hazard is hence essential to develop effective flood management plans, and a knowledge of the water regime (duration curves) is also essential to estimate sediment transport and carry out sediment budgets to inform on the impacts and sustainability of the mining activity. However, neither water levels nor discharges are monitored by official gauging stations, and only a few rainfall gauging stations are available in the area, with daily records often affected by data gaps. Therefore, a first challenge is to reconstruct discharge time series by an affordable effort, scaled to the financial-labour resources available in that challenging context. This paper presents an integrated approach that combines satellite-derived rainfall data with ground observations. A semi-distributed hydrological model (HEC-HMS, SCS-CN method) is used to reconstruct the full flow-rate time series once calibrated and validated with data derived from automatic sensors and field measurements. The model is fed with hourly data derived from daily data at ground gauging stations temporally downscaled by adopting the spatially distributed hourly rainfall patterns obtained from satellite records. Before that, observed water levels in three stations equipped with water level sensors were translated into discharge time series using analytical relationships based on field-measured geometric and physical characteristics. Then, these event-based hydrographs were used to calibrate and validate the model. Results show good agreement with observations, with R² = 0.981 and a relative RMSE of 40% for overall hydrograph reproduction, and R² = 0.87 for peak flow estimation, supporting a reasonable confidence in the approach. The calibrated model is then applied to long-term datasets (1973–2024) to retrieve duration curves and return periods of peak discharges. Full article