Search Results (328)

This study proposes an innovative framework that combines hydroclimatic and agro-environmental predictors, including nitrate concentration and NDVI, with climatic factors such as Rainfall, temperature, and evapotranspiration to forecast piezometric level variations in the Saïss Basin, Morocco. Eight Machine Learning (ML) models were benchmarked, and feature importance was assessed using Shapley Additive exPlanations (SHAP) to ensure model transparency and interpretability. In parallel, the PELT algorithm was applied to detect structural change points, while Sen’s slope estimator and the Mann–Kendall test were used to quantify long-term trends. The Extra Trees (ET) model achieved the best performance (R² = 0.92), with Rainfall emerging as the most influential predictor, followed by nitrate concentration, confirming the added value of hydrochemical indicators for groundwater forecasting. Change-point analysis revealed significant declines during the 1980s and 1990s, followed by lower-amplitude fluctuations since the late 2000s. Projections toward 2050 suggest partial stabilization in the central part of the basin under favorable recharge conditions, whereas persistent declines are expected to continue in peripheral areas subjected to sustained groundwater abstraction pressure. These findings provide a robust and transferable decision-support tool for the sustainable management of groundwater resources in semi-arid agricultural area. Full article

Climate change is driving hydroclimatic changes that are not fully captured by conventional trend analyses. This study presents a multidimensional assessment of hydroclimatic changes in Northern Cyprus using observational records from 27 precipitation stations and 12 temperature stations, with precipitation records spanning 35–46 years and temperature records spanning 21–30 years. Modified Mann–Kendall (MMK), Pettitt (PT), Innovative Trend Analysis (ITA), and Structural Trend and Variability Identification (STVI) methods were integrated to examine monotonic trends, abrupt shifts, distribution-dependent changes, and mean–variability interactions at annual and seasonal scales. Results revealed pronounced spatial heterogeneity and seasonal asymmetry in precipitation totals and their temporal evolution. Increasing tendencies were mainly concentrated in the Kyrenia mountainous region and parts of the western coast, whereas several eastern coastal stations showed drying tendencies, particularly in spring. Winter exhibited the most coherent wetting signal, while spring was more fragmented and drying-dominated. Monthly mean of daily maximum temperature (Tmax) and monthly mean of daily minimum temperature (Tmin) generally showed widespread warming, although Tmin responses were more localized and season-dependent. ITA indicated asymmetric precipitation behavior, with medium and high precipitation values generally increasing, while low values often decreased or showed mixed responses. STVI further revealed that precipitation changes involved substantial restructuring of both mean and variability components, whereas temperature changes were mainly mean-driven. The findings provide a more comprehensive understanding of evolving hydroclimatic conditions, which can support climate adaptation and water resources management in semi-arid Mediterranean regions. Full article

Although drought is recognized as one of the major hydroclimatic hazards affecting the Mediterranean Basin, local-scale assessments to support planning for its agricultural, hydrological, and food security impacts remain limited. This study investigates historical and future drought dynamics in Manisa (Western Türkiye) using a multi-scale framework integrating the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) with CMIP6 climate projections. A comprehensive dataset including ERA5-Land, CHIRPS, TerraClimate, and station observations was evaluated, revealing strong agreement in temperature but higher uncertainty in precipitation. SPI results indicate recurrent short-term droughts with extreme events reaching −2.5 in 2007–2008, alongside intensified long-term hydrological droughts since the early 1990s, while SPEI reveals a stronger temperature-driven drought signal, peaking near −2.0 during 2020–2024 as the most severe cumulative drought period in the past 40 years. Rapid wet–dry transitions have increased since 2000, indicating a more unstable hydroclimatic regime. Future projections (2025–2100) under a high-emission scenario suggest a progressive intensification of thermally driven drought conditions, with SPEI trends declining more steeply than SPI, indicating that evapotranspiration-driven water deficits may increasingly outweigh precipitation deficits as a driver of future drought risk. These findings offer localized, data-driven evidence relevant to climate adaptation and water resource planning in semi-arid Mediterranean agricultural regions. Full article

Ornamental plants constitute an important sector of the agricultural market, with global relevance. The impacts of climate change also affect flowering plants, increasing susceptibility to stress conditions. The most common effects are related to germination capacity and uniformity, which can indirectly compromise aesthetic value. Seed priming represents a promising environmentally friendly strategy to improve germination performance and stress tolerance in ornamental plants. This review gives an overview of the most recent advances in priming applied to ornamental species, highlighting the physiological, biochemical, and molecular impacts of the technique. Priming approaches can differ (e.g., hydro-, osmotic, hormonal, nano-based), with the common aim of enhancing germination efficiency, seed vigor, and promoting greater uniformity and quality of plantlets under stress conditions. Up to now, a bottleneck in the use of this promising tool has been represented by different responses related to species and protocol standardization. Molecular evaluation is required to monitor the long-term effectiveness of priming. The use of priming represents a sustainable and low-cost tool to enhance the adaptability of ornamental species in stress conditions, supporting the transition to new sustainable solutions for the future of ornamental plant production. Full article

Arid sandy soils are characterized by poor water retention, low nutrient availability, and limited productivity, posing major constraints to sustainable date palm cultivation under increasing water scarcity. A three-year field experiment was conducted to evaluate the combined effects of bentonite (BN), humic substances (HS), and Bacillus polymyxa (BP) under three irrigation regimes (70, 85, and 100% of crop evapotranspiration (ETc)) on soil hydro-physical properties, nutrient uptake, and fruit quality of ‘Siwi’ date palm (Phoenix dactylifera L.). Twelve treatment combinations (3 irrigation regimes × 4 soil amendment treatments) were evaluated over three consecutive growing seasons. The integrated application of BN, HS, and BP significantly improved soil hydro-physical properties by increasing field capacity and plant-available water while reducing bulk density. These improvements were associated with enhanced leaf N, P, and K concentrations and greater accumulation of total soluble solids, total and reducing sugars, phenolic compounds, flavonoids, and β-carotene compared with the untreated control. The combined application of BN (12 kg palm⁻¹) + HS (1 L palm⁻¹) + BP (28 mL palm⁻¹) produced the most favorable overall responses. Moderate deficit irrigation (85% ETc) provided the best balance between fruit quality and water conservation, maintaining superior fruit biochemical quality while reducing irrigation water use by approximately 15% compared with full irrigation. Multivariate analyses further supported these findings by revealing strong positive associations among soil water availability, nutrient status, sugars, and antioxidant-related compounds, while climatic variables were closely associated with seasonal variation in fruit biochemical characteristics. Overall, the integrated application of bentonite, humic substances, and B. polymyxa under 85% ETc irrigation represents an effective management strategy for improving soil performance, enhancing fruit nutritional quality, and increasing water-use irrigation efficiency in sandy soils under arid conditions. Full article

Pumped hydro storage is a well-established and reliable form of energy storage, with construction scale expanding steadily in recent years. Underground cavern excavation is an indispensable part of pumped storage construction, while sustained cavern inflow poses potential threats to engineering and regional water security. This study first summarizes the hydrochemical characteristics of cavern inflow from 62 pumped-storage projects in China. Combining field investigations, water pressure tests, hydrochemical analyses, and multi-method inflow forecasting, the study further discusses the cavern inflow features of two typical projects under different climatic environments. The results indicate that across the 62 projects, total dissolved solids (TDS) in inflow water range from 21.0 to 4270.7 mg/L, with pH values of 6.7–8.3, and are dominated by HCO₃-Ca type. Moving from humid toward arid regions, TDS shows a continuous increase, while pH exhibits no significant variation. At the Shanshan site, controlled by evaporation, silicates weathering and evaporite dissolution, cavern inflows are dominated by high-salinity SO₄-Mg type water with pronounced SO₄²⁻ enrichment. Predicted inflows of the underground powerhouse and water conveyance tunnels are 1247.96–5542.97 m³/d and 105.85–211.69 m³/d, respectively. The Ningshanbei site, located in the humid area, is characterized by low-salinity HCO₃-Ca freshwater controlled by carbonate dissolution, with a high conveyance system inflow of 2914.71–3413.91 m³/d. The two sites differ markedly in recharge conditions, inflow characteristics, and water quality, requiring site-specific water management. This study provides engineering references for inflow hazard control, groundwater resource management, and ecological protection in pumped-storage projects across different climatic zones. Full article

Accurate reservoir performance assessment increasingly relies on hydrological model-derived inflow series; however, the effects of hydroclimatic forcing pathways on reservoir design outcomes remain insufficiently understood. This study evaluates the sensitivity of reservoir performance to alternative forcing pathways by comparing observed inflows with SWAT+-simulated streamflow driven by ERA5-Land reanalysis data in the Cidadelhe catchment, Portugal. An integrated hydrology–reservoir modeling framework couples SWAT+ simulations with three analytical approaches: Behavior Analysis, the Modified Sequent Peak Algorithm (MSPA), and the Resilience-Regulated MSPA-2024. Results show that, despite strong hydrological model performance (NSE up to 0.83), SWAT+-simulated inflows exhibit systematic attenuation of variability, approximately 20–25%, leading to substantially lower storage capacity (up to 60–65%) and evaporation estimates relative to those derived from observed data. While volumetric reliability remains largely insensitive to forcing pathways, resilience, sustainability, and drought risk indices display pronounced method-dependent behavior. MSPA-2024 demonstrates strong robustness by maintaining near-invariant performance metrics across forcing conditions through embedded resilience constraints. These findings show that inflow statistical structure, rather than mean flow alone, controls reservoir design outcomes and that forcing-pathway consistency is critical for reliable performance assessment. The proposed SWAT+–MSPA-2024 framework supports more reliable model-based reservoir planning, particularly in data-scarce basins and climate-scenario applications. Full article

Gridded precipitation products are widely used in hydroclimatic studies, yet their suitability for anomaly-sensitive applications cannot be determined from magnitude-based statistics alone. This study introduces Bidirectional Extreme Response Analysis (BERA), a class-based evaluation framework designed to assess the ability of precipitation datasets to reproduce anomalously dry, near-normal, and anomalously wet monthly conditions. BERA decomposes gauge and product-based precipitation series into calendar-month-specific anomaly classes and quantifies agreement, no-response, false-extreme, and opposite-direction outcomes through a directional agreement matrix. The framework was demonstrated in the Upper Tigris River Catchment in southeastern Türkiye using monthly observations from 11 TSMS gauge stations and six precipitation products: CHIRPS v3.0, GPCP v3.3, ERA5, MSWEP v2.80, CHELSA, and CMIP6 EC-Earth3 over the common 1983–2011 period. Results show that conventional metrics alone provide contradictory product rankings, whereas BERA reveals distinct directional performance differences that are directly relevant to anomaly-sensitive applications. CHELSA achieved the highest overall BERA agreement rate (0.757), followed by GPCP v3.3 (0.705), whereas CMIP6 showed the weakest class reproduction (0.340) and the largest share of opposite-direction responses. Across most products, wet anomalies were reproduced more successfully than dry anomalies, indicating that precipitation deficits remain more difficult to identify reliably. Elevation-based comparisons further showed that high-elevation gauges were associated with weaker magnitude performance, while class-based agreement did not decline monotonically with altitude. Station-level differences further indicate that anomaly-class agreement is influenced by local hydroclimatic variability and gauge–grid representativeness, rather than by elevation alone. These findings show that BERA captures a distinct dimension of precipitation product behavior by separating magnitude errors from directional class misclassification. Because of its flexible classification structure, the framework can also be refined for different levels of anomaly severity or application-specific thresholds, allowing product performance to be interpreted according to the criticality of the intended use. Full article

Flooding associated with rising inland lake levels represents a distinct and understudied hazard compared to conventional river or coastal flooding. Unlike riverine floods, lake inundation develops gradually and persists over extended periods, yet integrated flood risk assessments specifically addressing this phenomenon remain scarce. This study uses Lake Baringo in Kenya’s Rift Valley as a case study, a lake that has experienced exceptional water level rises of nearly 10 m since 2010, to assess flood risk through the integration of scenario-based flood hazard modelling, spatial exposure assessment, and household vulnerability analysis. Three lake level scenarios were developed, spanning from maximum observed conditions to a worst-case threshold at the lake’s sill point. Results show that under the worst-case scenario, the lake area could expand by approximately 64%, potentially exposing nearly 18,000 people and 156 km of road infrastructure. A Flood Vulnerability Index (FVI) ranging from 0.58 to 0.73 indicated consistently high socioeconomic vulnerability across all shoreline communities, with vulnerability accounting for 42–53% of overall flood risk across scenarios. Flood risk was highest along the flat southern shoreline, where topography amplifies lateral inundation extent. The findings highlight the importance of integrating lake level dynamics into spatial planning and flood risk management, and the need for improved monitoring, livelihood diversification, and institutional coordination in semi-arid inland lake regions facing increasing hydro-climatic variability. Full article

Drought is a key climatic driver of grassland degradation; however, the coupling mechanisms between drought-triggering thresholds and ecosystem resilience under different hydroclimatic conditions, as well as their spatial heterogeneity, remain insufficiently understood. Here, we investigated Central Asian grasslands by integrating Copula-based joint probability analysis, drought-triggering threshold identification, and quantitative assessment of vegetation resilience. We systematically revealed spatial patterns of leaf area index (LAI) loss probability, as well as gradient-dependent transitions in the coupling between triggering thresholds and resilience across aridity gradients. Results showed that the probability of LAI loss (LAI ≤ 40th percentile) increased from 36.35% under mild drought to 39.99% under extreme drought, while more severe losses (LAI ≤ 10th percentile) increased from 11.16% to 12.62%. For a given drought intensity, more severe vegetation loss required substantially stronger water deficit conditions. Triggering thresholds increased along the aridity gradient, with the eastern Kazakhstan and western Xinjiang regions showing the highest drought sensitivity. Vegetation resilience also exhibited pronounced spatial differentiation, with the Balkhash Lake region, southern Inner Mongolia, and Gansu showing the lowest resilience and longest recovery times, whereas humid regions exhibited significantly higher resilience. Most importantly, the relationship between triggering thresholds and resilience shifted systematically across aridity gradients, changing from a significant negative correlation in semi-arid regions (synergy pattern) to a positive correlation in humid regions (trade-off pattern), with transition points at AI = 0.45–0.46. This indicated that hydroclimatic conditions fundamentally regulated the coupling between drought resistance strategies and recovery capacity. This study provides a robust scientific basis for accurately assessing drought vulnerability and developing differentiated adaptation strategies for grassland ecosystems under climate gradients. Full article

Tree-ring chronologies are essential proxies for investigating ecosystem dynamics and reconstructing environmental variability, yet integrative approaches for assessing chronology quality and sampling representativeness across heterogeneous regions remain limited. We analyzed 190 tree-ring chronologies distributed across Mexico and developed two composite indicators: the Signal Quality Index (SQI), integrating internal coherence, interannual sensitivity, common growth signal strength, and the Sampling Representativeness Index (SRI), quantifying the statistical adequacy of sampling efforts. Both indices were standardized and evaluated using Moran’s I, Local Indicators of Spatial Association (LISA), Getis–Ord Gi* hotspot analysis, and correlations with climatic, hydrological, and edaphic variables. Results revealed a marked decoupling between chronology signal quality and sampling representativeness. SQI exhibited significant positive spatial autocorrelation, with clusters of high and low values associated with hydroclimatic gradients. It was strongly related to indicators of water availability and atmospheric evaporative demand, suggesting greater growth coherence under water-limited conditions. In contrast, SRI displayed weak spatial structure and largely non-significant relationships with environmental variables, indicating that representativeness is driven primarily by methodological decisions and sampling design. These findings highlight complementary ecological (SQI) and methodological (SRI) dimensions of dendrochronological networks and provide a practical framework for improving chronology evaluation, comparability, and network development across environmentally heterogeneous regions. Full article

Prolonged drought in Chile has imposed increasing pressures on water-dependent tourism activities, although its effects have been assessed only fragmentarily and rarely linked to tourism-relevant indicators. This study provides an integrated hydro-climatic and economic assessment of drought impacts on two tourism categories especially sensitive to water availability: snow and mountain tourism, and tourism related to water bodies and watercourses. For this purpose, time series of snow cover, streamflow, precipitation, and water quality were analyzed for 2000–2024, complemented by sectoral statistics and indirect indicators of economic impact. Trend analyses used linear regression, the Mann–Kendall test, Sen’s slope, Pettitt change-point detection, and Spearman correlations between hydroclimatic variables and tourism proxies. Results show a significant decline in snow cover across most of northern and central Chile, with strong signals in basins critical for winter tourism and a common temporal break in 2009. Widespread streamflow reductions were also detected in rivers from central, southern, and Patagonian Chile, although with differing magnitude and timing. In contrast, water-quality changes were limited and spatially heterogeneous. In the ski sector, reduced snow accumulation was associated with shorter ski seasons, fewer skier-days, and lower direct employment. For rafting, declining streamflow was associated with reduced hydrological suitability, indicating less favorable potential operating conditions. Overall, drought affects tourism significantly but unevenly, depending on geography, hydrological regime, activity type, and data availability. The proposed integrated assessment helps identify differentiated drought-impact pathways and supports more climate-resilient tourism management. Full article

Water scarcity and increasing energy demand are critical challenges that often characterize Mediterranean regions, especially islands such as Crete. A sustainable solution for a combined water and energy supply lies in the domain of hybrid renewable energy systems. This research study evaluates a large-scale wind-driven desalination system with pumped-hydro energy storage for the Regional Unit of Rethymno, Crete, focusing on climate-driven demand and air temperature variation. The proposed system integrates wind energy production, seawater desalination, pumped-hydro storage, and water supply both for domestic and for irrigation purposes. Four scenarios, each with increasing air temperature, are examined in order to assess their effect on water demand and system performance. The analysis evaluates electricity allocation, the production of desalinated water, domestic and irrigation coverage, as well as the economic performance of the system. The results indicate that domestic water demand is almost fully covered in all four scenarios, reaching nearly 99.9%, while irrigation water coverage decreases from 82% under present conditions to 67% under higher-temperature scenarios. Wind-generated electricity is mainly used for water-related processes, with a constant share supplied to the grid. The economic assessment indicates that the system can operate under break-even conditions using realistic water and electricity prices. Full article

Understanding the interactions between vegetation dynamics and surface water availability is essential for assessing the resilience of tropical floodplain ecosystems under increasing hydroclimatic variability. This study analyzes the spatio-temporal dynamics of vegetation cover, surface water, and land use in Zambrano, a floodplain-dominated sector of the lower Magdalena River basin (Colombian Caribbean), over the period 1990–2025. Multi-temporal Landsat imagery was used to derive the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI), enabling the evaluation of seasonal and interannual ecohydrological variability under contrasting dry and rainy conditions. In addition, land-use classification was performed using a CORINE Land Cover methodology adapted for Colombia (CLC-C) to characterize the spatial organization of the landscape and its influence on vegetation–water interactions. Results show that vegetation dynamics are strongly controlled by hydroclimatic seasonality. Dense vegetation consistently expands during rainy periods, while dry seasons promote the expansion of open and sparse vegetation, reflecting seasonal vegetation stress rather than long-term degradation. NDWI patterns indicate that surface water and soil moisture are highly seasonal and spatially constrained, with open water largely confined to the Magdalena River channel and localized floodplain depressions. Extreme hydroclimatic events associated with the El Niño–Southern Oscillation (ENSO) produce abrupt but temporary changes in vegetation structure and surface moisture distribution. A strong inverse correlation between NDVI and NDWI reflects the contrasting spectral responses of vegetation and water surfaces resulting from the shared near-infrared (NIR) band in both indices. This spectral relationship is consistent with the observed seasonal variations in vegetation greenness and surface moisture across the floodplain. Land-use analysis reveals the progressive consolidation of the landscape, where the agropastoral matrix expanded from ~18,000 ha in 1990 to over 22,000 ha by 2025, driving a systematic reduction in natural and semi-natural forest structures. Forest conservation areas serve as critical ecological buffers, exhibiting lower seasonal variability in vegetation greenness. Overall, the results indicate that the Zambrano floodplain functions as a structurally stable yet highly responsive ecohydrological system, where vegetation dynamics and surface water availability are predominantly governed by interannual hydroclimatic pulses rather than long-term directional degradation. These findings demonstrate that while the structural matrix of the floodplain exhibits strong baseline resilience, its ecological functioning remains critically coupled with, and vulnerable to, the extreme phase shifts in ENSO cycles. Full article

Plant diversity is often expected to enhance soil organic carbon (SOC) storage through greater and more heterogeneous plant inputs, but its relationships with functionally distinct SOC fractions in natural forests remain uncertain. This study compiled published SOC fraction data from 341 surface soil observations in natural forests across China and spatially matched these records with gridded plant alpha diversity, forest age, climate, topographic and soil properties datasets to evaluate biotic and abiotic associations with SOC, particulate organic carbon (POC), mineral-associated organic carbon (MAOC) and MAOC/SOC. Linear regression, multiple regression, piecewise structural equation modelling and stratified analyses were used to evaluate whether plant diversity was associated with the absolute accumulation and relative stabilization of SOC fractions. Plant alpha diversity was negatively associated with ln[SOC], ln[POC] and ln[MAOC] at the national scale, whereas its bivariate relationship with MAOC/SOC was weak. After accounting for forest age and environmental covariates, plant alpha diversity remained negatively related to the absolute contents of SOC fractions while showing a positive association with MAOC/SOC. Forest age was positively associated with ln[SOC], ln[POC] and ln[MAOC], and POC was more strongly related to plant diversity and forest age than MAOC. In contrast, MAOC and MAOC/SOC were more strongly associated with mineral protection potential, soil pH and precipitation background. Structural equation models indicated that mineral protection potential and mean annual precipitation were associated with greater MAOC accumulation and SOC allocation to the mineral-associated fraction, whereas temperature and topography were linked to MAOC partly through indirect associations with soil physicochemical conditions. Stratified analyses showed that plant diversity associations varied among forest types and climatic backgrounds. Additional interaction models showed that mineral protection potential significantly moderated the associations between plant alpha diversity and ln[SOC], ln[POC] and ln[MAOC], with negative diversity associations weakening under higher mineral protection potential. These findings indicate that plant diversity associations with SOC fractions in natural forests cannot be interpreted as universally positive input relationships. Instead, their direction and strength depend on hydroclimatic context and soil mineral protection, especially for the absolute accumulation of SOC fractions. Full article