Search Results (78)

Drought is becoming more frequent and severe in many regions, particularly in Mediterranean climates, where water demand is increased by warming and changes in precipitation regimes. A long-term assessment of meteorological drought at the Lisbon climatological station is provided in this study using the Standardized Precipitation Index (SPI) and the Reconnaissance Drought Index (RDI) over the period 1864–2021. Monthly precipitation and temperature data are used to compute SPI and RDI at 3-, 6-, and 12-month time scales, so that short-, mid-, and long-term droughts and their temporal evolution can be characterized. RDI is evaluated with three widely used empirical potential evapotranspiration (PET) formulations—Hargreaves, Thornthwaite, and Blaney–Criddle—in order to examine how PET estimations influence drought classification. Given the absence of a physically based reference PET—such as FAO-56 Penman–Monteith—for this station, the focus is on the internal consistency of the PET methods. Furthermore, the Hargreaves formulation is retained as a representative empirical PET for subsequent SPI–RDI comparison. The results show broadly consistent standardized RDI behavior across PET methods; it is indicated that drought conditions are captured more comprehensively by RDI than by SPI because both precipitation deficits and enhanced evaporative demand are included. At the Lisbon station, the estimated average return periods for short-, mid-, and long-term droughts are 3.79, 7.31, and 7.92 years according to RDI, compared with 3.86, 5.69 and 10.88 years from SPI. Several severe drought episodes are identified, including the years 1907, 1922–1923, 1944–1945, 1976, 1981, 1992–1993, 2005, and 2018. While no formal attribution analysis is performed, the drought characteristics are interpreted in the context of observed long-term warming and documented rainfall variability in Lisbon. The findings provide a single-station benchmark of historical drought behavior, by which local water-resources management can be supported and which can serve as a basis for future multi-station and climate-projection-based studies in Portugal. Full article

Post-fire rehabilitation structures are widely used in Mediterranean burned landscapes to reduce runoff and sediment transfer, yet their ecological associations with early vegetation recovery remain insufficiently documented. This observational study assessed vascular plant composition, species richness, vegetation cover, plant density, aboveground biomass, and soil properties across log barriers, wattles, and log dams in the burned landscape of Ancient Olympia, western Greece. The study area belongs to the humid climatic class of the United Nations Environment Programme (UNEP) aridity framework based on the Thornthwaite aridity index, providing a comparatively wetter Mediterranean post-fire context. Paired depositional and eroded microsites in operationally restored post-fire areas were monitored in 2022 and 2023. The sampling design comprised nine plots and 18 microsites (n = 9 plots, 18 microsites). Generalized estimating equations (GEE), change-score models, principal component analysis (PCA) and permutational multivariate analysis of variance (PERMANOVA) were performed to examine associations of monitoring year, microsite condition and rehabilitation structure type with soil and vegetation patterns. A total of 27 vascular plant species belonging to 16 families were recorded. The average vegetation cover increased from 39.17 ± 21.44% in 2022 to 75.11 ± 12.90% in 2023. Model-based marginal estimates with 95% confidence intervals indicated a large positive increase in vegetation cover over this period. Further, rapid early recovery was indicated by large increases in species richness, plant density and biomass. Depositional microsites were associated with stronger recovery signals than eroded ones, characterized by a larger increase in vegetation cover, density, biomass and species richness. Among rehabilitation structures, log dams showed the highest cumulative floristic richness and a broader observed floristic spectrum, although the species-level contingency analysis provided only marginal evidence for structure-associated differences in floristic composition. Changes in selected soil properties including total nitrogen (total N), ammonium nitrogen (NH4-N), nitrate nitrogen (NO3-N), pH, electrical conductivity (EC), and exchangeable calcium (Ca), magnesium (Mg), and potassium (K), were detected between 2022 and 2023; the multivariate soil pattern was driven primarily by mineral nitrogen, pH, and EC. These findings suggest that, under operational post-fire restoration conditions, rehabilitation structures are associated not only with erosion-control functions but also with microsite differentiation that may shape early plant establishment and biodiversity recovery in Mediterranean burned landscapes. Full article

Climate change is expected to increase the frequency and severity of drought events in Europe, necessitating the identification of more water-efficient cropping systems. This study compared the evapotranspiration dynamics, water-use efficiency, and yield performance of maize (Zea mays L.) and grain sorghum (Sorghum bicolor L. Moench) under controlled field conditions using a Thornthwaite–Mather-type compensation evapotranspirometer. Three water regimes (100%, 50%, and 30% of optimal water supply) were applied during the reproductive stage, combined with weed-free and weed-infested treatments. Under moderate water deficit (50% water supply), grain sorghum maintained stable grain yield, while maize grain yield decreased by 17.98%. Under severe water deficit (30% water supply), grain yield reductions reached 36.04% in maize and 42.80% in sorghum. Grain sorghum consistently required less water and used 2.87–38.17% less water to produce 1 kg of grain compared to maize across treatments. Weed interference was associated with a lower yield and water-use efficiency in both species, while severe water deficit (70%) caused substantial declines in all measured parameters. Evapotranspiration was primarily driven by solar radiation and temperature, with reduced sensitivity under increasing water limitation. Overall, the results suggest that grain sorghum may represent a viable alternative to maize under moderate drought conditions; however, both crops require supplemental irrigation under severe water scarcity. The study highlights the importance of integrated weed management and provides novel insights into crop water-use dynamics under combined abiotic and biotic stress conditions. Full article

Climate change poses an escalating threat to global water resources, with semi-arid regions such as Morocco being particularly vulnerable due to high climatic variability and limited adaptive capacity. In these regions, including the Tassaoute watershed in central Morocco, data scarcity and uncertainties related to data availability and quality frequently hinder robust assessments of climate change impacts. Recent advances in data science and remote sensing offer promising alternatives to overcome these limitations. This study investigates the potential of the PERSIANN-CDR satellite-derived precipitation product for assessing climate change impacts on water resources. The capability of PERSIANN-CDR to reproduce observed precipitation patterns and associated hydrological responses is evaluated through a comparative analysis using observed precipitation data. Results indicate that PERSIANN-CDR generally underestimates peak precipitation events and total rainfall amounts compared to in situ observations. Runoff is simulated using two hydrological models: GR2M (Génie Rural 2 parameters Mensuel) and the Thornthwaite water balance method, both driven by observed meteorological data and PERSIANN-CDR precipitation. The future water availability was assessed using 5 climate models, under two scenarios: RCP4.5 and RCP8.5 for the periods 2030–2060 and 2061–2090. Results show a marked temperature increase of 2–3 °C across all models, accompanied by a general decline in precipitation ranging from −30% to −60% under RCP4.5 and −20% to −80% under RCP8.5. These climatic changes translate into substantial reductions in runoff, with stronger decreases projected under the high-emission scenario and during the dry season. Monthly analyses reveal pronounced seasonal contrasts, highlighting the increased sensitivity of low-flow periods to climate forcing. Overall, runoff is projected to decrease by 50–90%, with model and data-source differences highlighting the importance of multi-model and satellite-derived approaches in data-sparse regions. These results emphasize the utility of satellite precipitation datasets in guiding climate-adaptive water management strategies. Full article

Evaluating Net Primary Productivity (NPP) variations driven by climatic variability and mining activities is fundamental for understanding ecological dynamics in high-intensity open-pit mining areas. Focusing on high-intensity open-pit mining areas of Qian’an, China, from 2016 to 2022, by integrating Sentinel-2, ERA-5 Land reanalysis dataset and Dynamic World V1, we employed an improved Carnegie–Ames–Stanford Approach (CASA) framework alongside the Thornthwaite Memorial algorithm to quantify actual NPP (ANPP) and potential NPP (PNPP). Additionally, the Relative Contribution Index (RCI) was utilized to explicitly isolate mining-driven NPP (MNPP) variations. The results revealed a significant downward trajectory in ANPP within the high-intensity open-pit mining area, with a cumulative reduction of 5.3 × 10⁸ gC a⁻¹. This productivity loss exhibited significant spatial heterogeneity, with the most severe degradation concentrated in core mining districts, including Malanzhuang, Caiyuan, Yangdianzi, and Muchangkou. ANPP, MNPP, and PNPP maintained relative stability overall but displayed significant interannual fluctuations during 2019–2022. RCI analysis indicated MNPP dominated ANPP in 62.67% of the study area, with mining impacts intensifying in 62.83% of the region. Driver mechanisms identified precipitation as the dominant climatic factor enhancing ANPP, whereas mining activities constituted the primary driver of ANPP reduction. Mining accounted for 61.33% of ANPP changes, significantly exceeding climatic variability’s 38.67% contribution. In conclusion, these findings provide a scientific foundation for developing ecological carbon sink systems and optimizing ecological restoration strategies. Full article

Chieng Hac in northern Vietnam is expanding maize cultivation, intensifying water competition and soil erosion. This study mapped regional water balance and erosion using remote sensing and GISs by coupling the Thornthwaite–Mather (TM) water balance model with the Revised Universal Soil Loss Equation (RUSLE) at 12.5 m resolution. Land cover was classified into maize, tree crops, paddy, forest, and other types using Random Forest. The TM model used 2021 precipitation and temperature measurements to estimate evapotranspiration, surplus, and deficit, while the RUSLE quantified soil loss. Two scenarios were evaluated: a baseline reflecting existing land use and an adjusted case applying strip cropping on 10–20° maize slopes and converting maize to tree crops on slopes > 20°. Tree crop conversion increased evapotranspiration and prolonged seasonal deficits relative to maize, increasing water deficit from 1013.6 to 1022.2 mm/year. In contrast, the interventions reduced mean soil loss from 15.52 to 11.51 t/ha/year, with the largest decline in the 5–25 t/ha/year class. Residual hotspots persisted on steep slopes and near drainage lines. The integrated framework highlights trade-offs between erosion control and seasonal water availability, supporting slope-based land-use planning in upland agricultural systems. These findings offer guidance for slope-based land-use planning by indicating that intervention priorities should vary depending on slope conditions and local water availability. Full article

Climate change poses increasing threats to water security in Colombia, particularly in regions where groundwater monitoring remains limited. This study evaluated groundwater potential as an adaptation measure across six strategic regions covering 16.5% of Colombian territory: Tolima-Huila, Boyacá-Santander, Caribe Oriental, Caribe Occidental, Cauca-Nariño, and Meta-Vichada. We integrated a multi-source methodological approach combining conceptual hydrogeological characterization, potential recharge estimation using the Thornthwaite–Mather method, and groundwater storage anomaly analysis through GRACE satellite data coupled with the GLDAS model for the period 1992–2022. Potential recharge was evaluated for the historical period (1992–2022) and projected under SSP2-4.5 and SSP5-8.5 climate change scenarios (2040–2070) using global circulation models. Results revealed significant regional heterogeneity, with critical recharge reductions reaching 230 mm/month in Cauca-Nariño and 202 mm/month in Meta-Vichada under SSP5-8.5 compared to the historical baseline. Positive groundwater storage anomalies identified sectors with exploitation potential even in low-recharge areas, particularly in northern Tolima-Huila. Priority zones were defined for implementing adaptation measures, including artificial recharge, strategic use of fractured media, and strengthened water governance. The proposed methodology provides replicable technical foundations for climate-resilient planning at regional and local scales, which is particularly relevant for contexts with scarce hydrogeological information. Full article

Gridded meteorological data sources, such as reanalysis datasets, are increasingly used to estimate evapotranspiration, a key variable for surface water-budget analyses at regional and national scales and for assessing plant water requirements for irrigation. This study, conducted over mainland Portugal for the 44-year reference period from 1980 to 2023, first presents a comprehensive comparative analysis of the spatial patterns of potential ($Ep$) and reference ($Eto$) evapotranspiration at a 0.1° spatial resolution using daily data. Estimates derived from two high-resolution datasets (GLEAM and ERA5-Land) are compared with those obtained from the Thornthwaite, Hargreaves–Samani, and Penman–Monteith models. Secondly, trend analyses of $Eto$ magnitudes on a monthly and annual basis in a gridded format were conducted. The resulting spatial distributions of $Ep$ and $Eto$ show higher values in milder and flatter southern Portugal and lower values in the cooler and more mountainous northern regions, in agreement with existing knowledge. The Penman–Monteith model exhibited the highest reliability, while the Thornthwaite model generally underestimated evapotranspiration across the country, and the Hargreaves–Samani model showed underestimation in coastal areas. Trend analysis of $Eto$ indicates an overall increase in atmospheric evaporative demand over the full study period, with a more pronounced rise during the recent 22-year period (2002–2023) compared with the earlier period (1980–2001). These increases are statistically significant in August and October and may reflect a climate shift towards a progressively longer dry season. Understanding how changes in evapotranspiration affect hydrological processes—including surface water availability, river discharge, reservoir performance, and crop requirement—is critical. This study aims to contribute to addressing these emerging challenges. Full article

This study examines the hydrological response of the Klambu Dam Catchment in Central Java, Indonesia, to climatic and land cover changes from 2000–2023, with simulations extending to 2040. Utilizing CHIRPS satellite data calibrated with six ground stations, monthly precipitation and temperature datasets were analyzed and projected via linear regression aligned with IPCC scenarios, revealing a marginal temperature decline of 0.21 °C (from 28.25 °C in 2005 to 28.04 °C in 2023) and a 17% increase in rainfall variability. Land cover assessments from Landsat imagery highlighted drastic changes: a 73.8% reduction in forest area and a 467.8% increase in mixed farming areas, alongside moderate fluctuations in paddy fields and settlements. The Thornthwaite-Mather water balance method simulated monthly discharge, validated against observed data with Pearson correlations ranging from 0.5729 (2020) to 0.9439 (2015). Future projections using Cellular Automata-Markov modeling indicated stable volumetric flow but a temporal shift, including a 28.1% decrease in April rainfall from 2000 to 2040, contracting the wet season and extending dry spells. These shifts pose significant threats to agricultural and aquaculture activities, potentially exacerbating water scarcity and economic losses. The findings emphasize integrating dynamic land cover data, climate projections, and empirical runoff corrections for climate-resilient watershed management. Full article

The Tensift River Basin, part of the Mediterranean region, faces significant agricultural losses due to increasing drought frequency and severity, impacting up to 15% of the national GDP. The increasing climate crisis demands our immediate attention and proactive adaptation measures, including the enhancement of early-warning tools to support timely and informed responses. To this end, our study aims to achieve the following goals: (1) evaluate satellite and reanalysis products against in situ observations using statistical metrics; (2) identify the best probability distribution for calculating drought indices using goodness-of-fit testing; (3) compare the performances of the Standardized Precipitation Index (SPI) and the Standardized Precipitation and Evapotranspiration Index (SPEI) at different aggregation timescales by comparing index-based and reported (i.e., impact-based) drought events using receiver operating characteristic (ROC) analysis. Our findings indicate that CHIRPS and ERA5-Land datasets perform well compared to in situ measurements for drought monitoring in the Tensift River Basin. Pearson Type 3 was identified as the optimal distribution for SPI calculation, while log-logistic was confirmed for SPEI. We also explored the effect of using the Thornthwaite method and the Hargreaves method when computing the SPEI. These results can serve as a basis for drought monitoring, modeling, and forecasting, to support decision-makers in the sustainable management of water resources. Full article

Global climate change has profoundly affected agricultural ecosystems by altering the spatiotemporal patterns of temperature and precipitation, disrupting ecological equilibrium, and increasing environmental variability for crop growth, thereby posing significant challenges to food security. Based on 1 km-resolution gridded datasets of mean precipitation and temperature for Liaoning Province from 1950 to 2023, this study integrated the Miami and Thornthwaite Memorial models with climate tendency rate analysis, Mann–Kendall trend tests, and inverse distance weighting interpolation to assess spatiotemporal changes in climate potential productivity (CPP) and its relationship with grain yield dynamics. The results show that, from 1950 to 2023, annual precipitation exhibited a fluctuating downward trend (−8.5 mm/10a), while mean annual temperature increased significantly (0.3 °C/10a). Consequently, precipitation-based climatic production potential declined at a rate of 10.4 g·m⁻²·(10a)⁻¹, whereas temperature-based, evapotranspiration-based, and standard climate potential productivity (Yb) increased at rates of 23.3-, 6.6-, and 5.7 g·m⁻²·(10a)⁻¹, respectively. Spatially, CPP displayed a distinct gradient characterized by higher values in the southeast and lower values in the northwest, with a stronger correlation to precipitation than to temperature. Climate classification analysis indicated that warm-humid conditions enhanced CPP, whereas cold-dry, cold-humid, and warm-dry conditions reduced productivity. Although grain yield per unit area and climate resource utilization efficiency increased by 89.4 g·m⁻²·(10a)⁻¹ and 9.0% per decade, respectively, the yield-increasing potential declined by 84.1 g·m⁻²·(10a)⁻¹, indicating that while advances in agricultural technology have improved resource conversion efficiency, the potential for further yield gains through climate-dependent strategies alone is increasingly limited. Full article

This study aims (1) to study the trend and characteristics of monthly air temperature, monthly rainfall, and potential evapotranspiration (PET) in Thailand over the mid-21st century (2022–2060) period, and (2) to create a climate pattern map using the New Thornthwaite Climate Classification in Thailand over the same period under RCP4.5 and RCP8.5 scenarios using CSIRO-Mk3 in the CMIP5 dataset with Empirical Quantile Mapping (EQM) statistical downscaling. Spatial analyses of temperature and PET reveal significant warming trends, with temperatures rising by approximately 0.033 °C/year and PET rising by about 10 mm/year, especially in the Bangkok Metropolitan Region due to the urban heat island effect, with temperature values under RCP8.5 remaining consistently higher than those under RCP4.5. Rainfall projections show relatively stable spatial patterns across both scenarios, with higher concentrations along the Andaman coast, the eastern peninsula, and northeastern Thailand; these are areas influenced by the southwest monsoon and tropical cyclones. Central Thailand, however, exhibits persistently low rainfall, likely due to rain-shadow effects. PET patterns mirror early 21st-century observations, with the highest values projected in central Thailand and increasing trends under both scenarios, suggesting heightened drought risks. By 2060, The New Thornthwaite Climate Classification indicates that Moist climate zones are projected to disappear nationwide, with Semi-arid and Dry climates dominating under both RCP4.5 and RCP8.5 scenarios. Annual mean temperature will rise by 0.033 °C/year and PET by ~10 mm/year, while rainfall trends remain nearly stable. The classification’s reliance on minimal parameters—temperature, precipitation, and PET—provides a practical tool for climate monitoring and policy development. Full article

This study focuses on the Alentejo and Algarve regions of southern Portugal, which is characterized by a typical Mediteranean climate. In the Mediterranean region, evaporation plays a significant role in reservoir water budgets. Therefore, estimating water surface evaporation is essential for efficient reservoir water management. This study aims to (i) assess the reservoir evaporation pattern in southern Portugal from meteorological offshore measures, (ii) benchmark various indirect methods for evaluating reservoir evaporation at a monthly scale, and (iii) provide recommendations on the most suitable indirect method to apply in operational practices. This study presents meteorological data collected from floating weather stations on instrumented platforms across nine reservoirs in Alentejo and Algarve. This is the first time that so many offshore local measurements have been made available in a Mediterranean climate region. The reservoir evaporation was estimated by the Energy Budget (Bowen Ratio) method, having concluded that monthly evaporation rates across the nine reservoirs ranged from 0.8 mm d${\phantom{­}}^{-1}$ in winter to 4.6 mm d${\phantom{­}}^{-1}$ in summer, with an annual average of 2.7 mm d${\phantom{­}}^{-1}$. Annual evaporation values ranged from 750 to 1230 mm, showing a positive gradient from the northern Alentejo region to the southwest Algarve region. To evaluate the performance of five empirical and semi-empirical evaporation indirect methods, a benchmarking analysis was conducted. The indirect methods studied are Mass Transfer (MT), Penman (PEN), Priestley and Taylor (PT), Thornthwaite (THOR), and Pan Evaporation (PE). Regarding the MT method, an N function of a reservoir superficial area is presented for the Mediterranean climate regions. In the Pan Evaporation method, the pan coefficient was considered equal to one. The benchmarking analysis revealed that all studied methods produced estimates that had good correlation with the Energy Budget method’s results across all reservoirs. All the methods showed small biases at the monthly scale, particularly in the dry semester. The estimates’ evaporation variability depended on the reservoir. Overall, the evaluation of evaporation methods concluded that (i) the stakeholders should considerer having an evaporation pan offshore; (ii) to manage the water balance of the studied reservoirs, the manager must apply the method with the best performance, depending on the data available; (iii) to manage other reservoirs located in the Mediterranean climate region, the manager must compare reservoir characteristics and the data available in order to choose the most suitable method to apply. Full article

The satellite-derived climatic variables offer extensive spatial and temporal coverage for research; however, their inherent biases can subsequently reduce their accuracy for water balance estimate. This study evaluates the effectiveness of bias correction in improving the Tropical Rainfall Measuring Mission (TRMM) rainfall and the Global Land Data Assimilation System (GLDAS) land surface temperature (LST) data and illustrates their long-term (2000–2019) hydrological assessment. The novelty lies in coupling the bias-corrected climate variables with the Thornthwaite–Mather water balance model as well as land use land cover (LULC) for improved predictive hydrological modeling. Bias correction significantly improved the agreement with ground observations, enhancing the R² value from 0.89 to 0.96 for temperature and from 0.73 to 0.80 for rainfall, making targeted inputs ready to predict hydrological dynamics. LULC mapping showed a predominance of agricultural land (64.5%) in the area followed by settlements (20.0%), forest (7.3%), barren land (6.5%), and water bodies (1.7%), with soils being silt loam, clay loam, and clay. With these improved datasets, the model found seasonal rise in potential evapotranspiration (PET), peaking at 120.7 mm in June, with actual evapotranspiration (AET) following a similar trend. The annual water balance showed a surplus of 523.8 mm and deficit of 121.2 mm, which proves that bias correction not only enhances the reliability of satellite data but also reinforces the credibility of hydrological indicators, with a direct, positive impact on evidence-based irrigation planning and flood mitigation and drought management, especially in data-scarce regions. Full article

This study investigates the spatio-temporal dynamics of Climate Potential Productivity (CPP) in Central Africa during 1901–2019 using the Thornthwaite Memorial model coupled with Mann–Kendall tests based on high spatial and temporal resolution data. The results demonstrate the climate–vegetation interactions under global warming: (1) Central Africa exhibited a statistically significant warming trend (r² = 0.33, p < 0.01) coupled with non-significant rainfall reduction, suggesting an emerging warm–dry climate regime that parallels meteorological trends observed in North Africa. (2) Central Africa exhibited an overall increasing trend in CPP, with temporal fluctuations closely aligned with precipitation variability. Specifically, the CPP in Central Africa has undergone three distinct phases: an increasing phase (1901–1960), a decreasing phase (1960–1980), and a slow recovery phase (1980–2019). The multiple intersection points between the UF and UB curves indicate that Central Africa’s CPP has been significantly affected by climate change under global warming. (3) The correlation of CPP–Temperature was mainly positive, mainly distributed in the Lower Guinea Plateau and the northern part of the Congo Basin (r² = 0.26, p < 0.1). The relationship of CPP–Precipitation showed predominantly a very strong positive correlation (r² = 0.91, p < 0.01). Full article