Search Results (2,696)

In the Plitvice Lakes National Park, several hydrogeological catchments can be distinguished, but their boundaries are not clearly defined. This study focused on the Matica River catchment area, which covers the main contributors to the lake system and its overall water balance. An initial assessment indicated that the Matica River catchment is among the most vulnerable areas due to the anticipated land-use expansion related to agriculture and tourism. This research provides critical hydrogeological data supporting sustainable management in response to the increasing extremes of floods and droughts induced by climate change. Two separate campaigns (March 2023 and April 2025) were carried out, each involving three simultaneous tracer injections using different fluorescent dyes. The results of earlier tracer tests were evaluated; furthermore, a hydrochemical analysis of the spring water offered valuable insights into subsurface processes and anthropogenic impacts. Tracing in the southwest clarified the boundary between the Plitvice Lakes and Una River catchments. In the Homoljac polje, the tracer responses highlighted a triple junction between the Plitvice Lakes, Gacka, and Una River catchments. In the southeastern Brezovac polje, the boundary between the Crna Rijeka and Bijela Rijeka catchments was delineated in detail. Full article

Santa Ana winds are extreme meteorological events that strongly affect the U.S.–Mexico border region, often associated with droughts, high fire risk, and hydrological imbalance. Understanding the temporal behavior of key atmospheric variables during these events is crucial for integrated water resource management in semi-arid regions such as the Guadalupe Basin in northern Baja California. In this study, we explored the predictive capability of several hybrid deep learning architectures—Long Short-Term Memory (LSTM), Convolutional Neural Network combined with LSTM (CNN–LSTM), and Bidirectional LSTM with Attention (BiLSTM–Attention)—to model the temporal evolution of wind speed, wind direction, temperature, relative humidity, and atmospheric pressure using Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis data from 1980 to 2020. Model performance was evaluated using RMSE, MAE, and R² metrics and compared against persistence and climatology baselines. The BiLSTM–Attention model achieved the best overall performance, showing particularly high accuracy for temperature (R² = 0.95) and relative humidity (R² = 0.76), while maintaining angular errors below 35° for wind direction. The results demonstrate the potential of hybrid deep learning models to capture nonlinear temporal dependencies in meteorological time series and provide a methodological framework to enhance hydrometeorological understanding and water resource management in the Guadalupe Basin under Santa Ana wind conditions. Full article

Ethiopia is among the most climate-vulnerable countries in Africa, with agriculture, water resources, health, and disaster risk management highly exposed to climate variability and change. This study examines the role of climate services in supporting climate change adaptation in Ethiopia by combining analyses of historical climate trends, future projections, national policy frameworks, and survey data from both users and providers of climate information. Results show that rainfall and temperature time-series exhibit significant variability, with increasing frequency of droughts and rising temperatures already threatening livelihoods and food security. Climate projections indicate continued warming and uncertain but increasingly extreme rainfall patterns, underscoring the urgency of adaptation. National strategies—including the Climate Resilient Green Economy (CRGE) Strategy, Growth and Transformation Plans (GTP I and II), and the National Adaptation Plan (NAP-ETH)—highlight the centrality of climate services in guiding adaptation across sectors. Survey findings reveal that climate services provided by the Ethiopian Meteorological Institute (EMI) are widely valued, particularly seasonal climate predictions, but challenges persist in accessibility, capacity, infrastructure, and alignment with user needs. Despite high satisfaction levels among users and providers, gaps remain in technical expertise, dissemination mechanisms, and service co-production. Strengthening climate services—through improved technical capacity, institutional coordination, and user-driven design—will be critical for enhancing Ethiopia’s resilience. The lessons drawn are also relevant to other African countries where climate services can play a critical role in bridging the gap between climate science and climate-resilient development. Full article

Forest-type national nature reserves and their surrounding areas have experienced a series of drought events, which have influenced forest ecosystem stability. Assuming that drought events do not cause a shift in the ecosystem’s stable state, we quantified the stability of forest ecosystems in China’s national nature reserves and their surrounding areas in response to drought events from 2000 to 2018, using satellite-observed Enhanced Vegetation Index (EVI) and Standardized Precipitation Index (SPI) data. We further examined differences in ecosystem stability across regions and forest types, and identified the impacts of environmental factors using correlation analysis, analysis of variance (ANOVA), and random forest models. The results show that both national nature reserves and their surrounding areas primarily experienced single, moderate-intensity drought events, most of which occurred in spring and summer. Compared with surrounding areas, national nature reserves exhibited higher ecosystem stability, with a mean drought resistance index of 31.45 ± 21.09. The difference in ecosystem stability between reserves and their surrounding areas was most pronounced in deciduous forests, which was attributed to their high hydraulic conductivity and distinctive leaf phenological traits. Additionally, climatic factors were the dominant drivers of both resistance and recovery rate, each contributing more than 30% to the overall explained variance. Our results provide valuable guidance for enhancing drought resilience and promoting the sustainable management of China’s national forest reserves. Full article

Climate change and its impacts on precipitation patterns have intensified the occurrence of prolonged dry periods in agricultural regions of Brazil, particularly in the MATOPIBA region (comprising the states of Maranhão, Tocantins, Piauí, and Bahia). This study analyzes the seasonal variability and trends of the Consecutive Dry Days (CDDs) index in the MATOPIBA region from 1981 to 2023. Daily precipitation data from the Brazilian Daily Weather Gridded Data (BR-DWGD) dataset were used for the analysis. The novelty of this work lies in its focus on the seasonal characterization of CDD across the entire MATOPIBA field of agriculture, addressing the following main research question: how have the frequency and persistence of dry spells evolved during the rainy and dry seasons over the past four decades? The methodology involved trend detection using the Mann–Kendall test and Sen’s Slope estimator. The results indicated that during the rainy season, the average CDD ranged from 20 to 60 days, with higher values concentrated in the states of Piauí and Bahia. In contrast, during the dry period, averages exceeded 100 days across most of the region. Trend analysis revealed a significant increase in CDD over extensive areas, particularly in Tocantins and Southern Bahia. The increasing trends were estimated at 1 to 4 days per decade during the rainy season and 4 to 14 days per decade in the dry period. Although a decreasing CDD trend was observed in small areas of Northern Maranhão, possibly associated with the influence of the Intertropical Convergence Zone, the overall scenario indicates a greater persistence of long dry spells. This pattern suggests an increase in vulnerability to water scarcity and agricultural losses. These findings highlight the need for implementing adaptation strategies, such as the use of drought-tolerant cultivars, conservation management practices, irrigation expansion, and public policies aimed at promoting climate resilience in the MATOPIBA region. Full article

Drought is a major climatic hazard affecting water resources, agriculture, and livelihoods in semi-arid regions, with increasing severity under climate change. This study assessed long-term drought in Dura City, Palestine, from 2000 to 2023 using the Standardized Precipitation Index (SPI) at 3-, 6-, and 12-month timescales. Monthly precipitation and temperature data were obtained from local meteorological stations, with mean annual precipitation of 408 mm and average summer and winter temperatures of 28 °C and 12 °C, respectively. Trends were analyzed using the Mann–Kendall test and Sen’s slope estimator. SPI-3 values ranged from −3.13 to 3.87, including 67 moderates to severe drought months and 12 extreme wet months. SPI-6 ranged from −2.97 to 2.53, showing 34 drought months and 40 wet months, while SPI-12 ranged from −1.94 to 2.32, reflecting generally stable long-term precipitation. Annual rainfall exhibited no significant trend (Sen’s slope = −1.34 mm/year, p = 0.785), whereas yearly average temperature increased significantly by 0.054 °C/year (p = 0.02), raising evapotranspiration and drought risk. Results indicate high short- and medium-term drought variability despite stable annual precipitation, underscoring the need for integrated water management strategies, including rainwater harvesting, groundwater protection, and efficient irrigation, to improve resilience under evolving climate conditions. Full article

Plant growth-promoting bacteria (PGPB) associated with Coffea arabica L. and Coffea canephora Pierre ex Froehner offer a viable strategy to reduce synthetic inputs and enhance resilience in coffee agroecosystems. This review synthesizes evidence from the past decade on rhizosphere-associated and endophytic taxa, their plant growth-promotion and biocontrol mechanisms and the resulting agronomic outcomes. A compartment-specific core microbiome is reported, in the rhizosphere of both hosts, in which Bacillus and Pseudomonas consistently dominate. Within endophytic communities, Bacillus predominates across tissues (roots, leaves and seeds), whereas accompanying genera are host- and tissue-specific. In C. arabica, endophytes frequently include Pseudomonas in roots and leaves. In C. canephora, root endophytes recurrently include Burkholderia, Kitasatospora and Rahnella, while seed endophytes are enriched for Curtobacterium. Functionally, coffee-associated PGPB solubilize phosphate; fix atmospheric nitrogen via biological nitrogen fixation; produce auxins; synthesize siderophores; and express 1-aminocyclopropane-1-carboxylate deaminase. Indirect benefits include the production of antifungal and nematicidal metabolites, secretion of hydrolytic enzymes and elicitation of induced systemic resistance. Under greenhouse conditions, inoculation with PGPB commonly improves germination, shoot and root biomass, nutrient uptake and tolerance to drought or nutrient limitation. Notable biocontrol activity against fungal phytopathogens and plant-parasitic nematodes has also been documented. Key priorities for translation to practice should include (i) multi-site, multi-season field trials to quantify performance, persistence and economic returns; (ii) strain-resolved omics to link taxa to functions expressed within the plant host; (iii) improved bioformulations compatible with farm management and (iv) rationally designed consortia aligned with production goals and biosafety frameworks. Full article

Understanding how climate change will reshape drought dynamics is essential for planning sustainable water and agricultural systems in tropical regions. However, large uncertainties in existing projections limit effective adaptation. To address this, we applied machine learning-enhanced climate projections and satellite-based drought indices to assess drought dynamics in Ethiopia’s Ganale Dawa Basin as a case study. Agricultural and hydrological droughts were analyzed for a historical baseline (1982–2014) and three future periods (2015–2040, 2041–2070, 2071–2100) under SSP2-4.5 (a moderate-emission pathway) and SSP5-8.5 (a high-emission pathway) scenarios. Results show that agricultural droughts occurred 34 times during the historical baseline. Under SSP2-4.5, their frequency declined to 10 in the mid-future, before rising to 16 events in the far future. In contrast, SSP5-8.5 projected increased variability with 33 events in the near future, dropping to 2 in the mid-future, and increasing again to 19 in the far future. Hydrological droughts were more persistent, with a baseline frequency of 31 events, and 26–36 events over future periods under both scenarios. These findings reveal increasing variability in agricultural drought and continued recurrence of hydrological drought. The findings emphasize a dual adaptation approach combining immediate agricultural responses with sustained water management and climate mitigation. Full article

To mitigate the impact of north–south strip errors inherent in Gravity Recovery and Climate Experiment (GRACE) spherical harmonic coefficient solutions, this research develops a state-space model to generate a more robust solution. The efficacy of the state-space model is demonstrated by comparing its performance with that of conventional filtering methods and hydrological modeling schemes. The method is subsequently applied to estimate the GRACE Groundwater Drought Index in the California Central Valley basin, a region significantly affected by drought during the GRACE observation period. This analysis quantifies the severity of droughts and floods while investigating the direct influences of precipitation, runoff, evaporation, and anthropogenic activities. By incorporating the El Niño–Southern Oscillation (ENSO) and the Pacific Decadal Oscillation, the study offers a detailed causal analysis and proposes a novel methodology for water resource management and disaster early warning. The results indicate that a moderate-duration flood event in 2006 resulted in a recharge of 19.81 km³ of water resources in the California Central Valley basin, whereas prolonged droughts in 2008 and 2013, lasting over 15 months, led to groundwater depletion of 41.53 km³ and 91.45 km³, respectively. Precipitation and runoff are identified as the primary determinants of local drought and flood conditions. The occurrence of ENSO events correlates with sustained precipitation variations over the subsequent 2–3 months, resulting in corresponding changes in groundwater storage. Full article

Investigating how drought and flooding stresses interact during drought–flood abrupt alternation events and their impact on rice photosynthetic carboxylation capacity ($V_{cmax}$) is critical for improving crop growth and yield models under environmental stress conditions. However, there is limited research on the specific role of these combined stresses on $V_{cmax}$ in rice. This study aims to address this gap by examining the effects of drought and flooding on rice $V_{cmax}$. Using data from drought–flood experiments conducted in 2017 and 2018, we calculated $V_{cmax}$ by combining observed gas exchange parameters with photosynthetic biochemical models. The results revealed that $V_{cmax}$ damage caused by drought and flooding stresses was eventually repaired. Notably, $V_{cmax}$ recovered more quickly when mild drought preceded flooding stress. In contrast, severe and moderate drought treatments showed synergistic effects, where the preceding drought and subsequent flooding exacerbated the damage to $V_{cmax}$. However, the pre-mild drought stress antagonistically mitigated the damage to $V_{cmax}$ of rice induced by flooding stress, showing an antagonistic effect. Additionally, rice increased intrinsic water use efficiency (${WUE}_i$; $A_n/g_s$) by increasing investment in $V_{cmax}$ after drought and flooding stress, but rice yield was not improved. The preceding drought is probably beneficial for yield of rice experiencing subsequent flooding stress at relatively low $V_{cmax}$, while subsequent flooding stress exacerbated the reduction in yield of rice experiencing preceding drought stress. This research enhances our understanding of how the interaction between drought and flooding affects rice’s photosynthetic capacity and emphasizes that appropriate drought and flooding management may have potential optimizing effects on rice yield and water use, and provides an important theoretical basis and practical guidance for paddy water management. Full article

Early seedling survival is a key determinant of reforestation success under increasingly variable climatic conditions. Fertilizers used to mitigate nutrient limitations are believed to mitigate early establishment stress, but their effectiveness under heterogeneous field conditions remains uncertain. This study specifically tests whether an amino-acid-based nitrogen fertilizer can provide a more efficient and ecologically sustainable Nitrogen source compared with conventional mineral formulations. Using a dataset of 6238 seedlings from seven operational Austrian reforestation sites, we quantify amendment performance and examine interactions with relief, soil depth, water availability, and management practices. We apply CatBoost to identify influential predictors of mortality and summarize results across repeated evaluations. Further, for the reported settings, we can reliably predict tree seedling mortality for three out of four seedlings, with an average model accuracy of 76.4% and an AUC of 0.82 across sites. The arginine-based fertilizer increased survival probabilities by up to 15% on moist, deep soils but showed no consistent benefit under shallow or drought-prone conditions. The results highlight the potential of amino-acid-based N supply as a more ecologically aligned alternative and support operational decisions on when and where fertilizers may improve oak establishment under changing climatic conditions. Full article

Dams play a vital role in hydropower generation and water management, yet growing environmental and societal demands increasingly require reoperation to balance multiple purposes. Despite this shift, few studies have quantitatively evaluated how converting an existing hydropower dam to multipurpose operation affects downstream hydrology and water quality. This study examines the Hwacheon Dam in South Korea, which was converted to multipurpose use, to assess the effects of this operational change. The analysis focused on changes in the number and frequency of non-release days, downstream flow regime variation, and water quality responses evaluated using the national water quality standards and the real-time water quality index (RTWQI). After the transition, non-release days decreased sharply and the dam maintained continuous releases of 22.2 cubic meters per second (CMS), ensuring stable water supply and consistent downstream flow. Results show that flood, high, and normal flows decreased by 51.4% (from 1037.0 CMS to 503.5 CMS), 21.7% (from 54.4 CMS to 42.6 CMS), and 13.0% (from 23.9 CMS to 20.8 CMS), respectively. In contrast, the low flow increased by 7.4 times (from 2.4 CMS to 20.2 CMS) after the transition to multipurpose operation, while the drought flow increased from 0 CMS to 17.8 CMS. Water quality also improved across all downstream stations, with both national water quality standards and RTWQI scores indicating excellent and stable conditions. The multipurpose operation of the Hwacheon Dam stabilized hydrologic and water quality conditions, demonstrating the potential of dam reoperation for sustainable water and ecosystem management. Full article

Extreme climate events like droughts and floods are creating urgent challenges for sectors such as Agriculture or water management. Effective adaptation requires stakeholder collaboration, supported by stakeholder analysis (SA) methods, which are still evolving in environmental management. We briefly reviewed examples of recent existing systematic evidence syntheses on SA across different domains. This highlighted several SA challenges, including the lack of transparent, common methods—particularly for climate-induced extreme events—and weak links between SA results and policy or practice. We then present a case study that illustrates these challenges and suggests ways to address them. Cooperating with a local network organisation, the Living Lab Schouwen-Duiveland (LAB), we conducted a case study on the island of Schouwen-Duiveland (NL), which is trying to adapt to drought. Applying a novel stakeholder analysis method, the “Rings of involvement”, which enables the visualisation of stakeholders’ levels of affectedness regarding the issue, we were able to identify and categorise the stakeholder network in a systematic manner. We identified stakeholder groups, such as “Implementers”, who are not yet in the network but likely hold key practical knowledge to address local-regional climate adaptation. This calls for a better institutionalisation of and a more dynamic approach to SA in the local climate change adaptation practices. Based on our case study, we suggest that future studies could explore under which conditions a network organisation (such as the LAB) acts as a dynamic platform for facilitating stakeholder knowledge co-production. Full article

Climate change causes unpredictable weather patterns, leading to more frequent and severe droughts. Investigating the effects of drought and irrigation on soil water status and the performance of various cassava genotypes can provide valuable insights for mitigating drought through designing appropriate genotypes and water management strategies. The objective of this research was to evaluate soil moisture, growth rates, and final yields (total dry weight, storage root dry weight, harvest index and starch yield) of six cassava genotypes cultivated under drought conditions during the late growth phase, as well as under full irrigation. The study utilized a split-plot randomized complete block design with four replications, conducted over two growing seasons (2022/2023 and 2023/2024). The main plots were assigned as two water regimes to prevent water movement between plots: full irrigation and drought treatments. The subplot consisted of six cassava genotypes. Measurements included soil properties before planting, weather data, soil moisture content, relative water content (RWC) in cassava leaves, and several growth rates: leaf growth rate (LGR), stem growth rate (SGR), storage root growth rate (SRGR), crop growth rate (CGR), relative growth rate (RGR), as well as final yields. The results revealed that low soil moisture contents for drought treatment led to variation in RWC, growth, and yield among cassava genotypes. Variations in soil and weather conditions between the 2022/2023 and 2023/2024 growing seasons resulted in differences in the performance of the genotypes. Kasetsart 50 (2022/2023) and CMR38–125–77 (2023/2024) were top performers under late drought stress regarding storage root dry weight and starch yield, showing vigorous recovery upon re-watering, evidenced by their significant increase in LGR (between 240 and 270 DAP) and their high RGR (240–360 DAP). Rayong 9 (2023/2024) demonstrated strong performance in both during the drought period (180–240 DAP), efficiently allocating resources under water scarcity, with SRGR and starch yield reduced by 26.4% and 9.5%, respectively, compared to full irrigation. These cassava genotypes are valuable genetic resources for cassava cultivation and can be used as parental material in breeding programs aimed at improving drought tolerance. Full article

This research has used a multi-indices geospatial framework to combine the utilization of the Normalized Difference Vegetation Index (NDVI), Temperature Condition Index (TCI), and Standardized Precipitation Evapotranspiration Index (SPEI) to measure drought risk in Faisalabad Division, Pakistan (2015–2023). It integrated remote sensing, GIS analysis, and change detection in Land Use Land Cover (LULC) and used Moderate Resolution Imaging Spectroradiometer (MODIS) datasets along with SPEI grids. It was found that the spatial heterogeneity that occurred with District Jhang is at high risk because it is arid (SPEI −1.5), sparsely vegetated (NDVI 0.2), and has high thermal stress (TCI -30), whereas the central/eastern parts are resilient (NDVI 0.4) due to irrigation. Through MODIS LULC analysis, the occurrence of urban growth (13.42 km² of vegetative cover loss), agricultural intensification, and afforestation (147.34 km²) were identified. As per the risk map, 74 percent of the area was defined as low risk (74 percent), 20 percent as moderate risk, and 6 percent as high risk. The findings highlight the role of water management in climate resilience. Future research should integrate high-resolution imagery, machine learning, and socioeconomic data for improved prediction. Full article