Search Results (487)

Drought disturbances are becoming more frequent with global warming. Accurately assessing the regulatory effect of drought on vegetation phenology is key to understanding terrestrial ecosystem response mechanisms in the context of climate change. Previous studies on cumulative and lagged effects of drought on vegetation growth have mostly focused on a single vegetation type or the overall vegetation NDVI, overlooking the possible influence of different adaptation strategies of different vegetation types and differences in drought effects on different phenological nodes. This study investigates the cumulative and lagged effects of drought on vegetation phenology across a region of East Asia from 2001 to 2020 using NDVI data and the Standardized Precipitation Evapotranspiration Index (SPEI). We analyzed the start of growing season (SOS) and end of growing season (EOS) responses to drought across four vegetation types: deciduous needleleaf forests (DNFs), deciduous broadleaf forests (DBFs), shrublands, and grasslands. Results reveal contrasting phenological responses: drought delayed SOS in grasslands through a “drought escape” strategy but advanced SOS in forests and shrublands. All vegetation types showed earlier EOS under drought stress. Cumulative drought effects were strongest on DNFs, SOS, and shrubland SOS, while lagged effects dominated DBFs and grassland SOS. Drought impacts varied with moisture conditions: they were stronger in dry regions for SOS but more pronounced in humid areas for EOS. By confirming that drought effects vary by vegetation type and phenology node, these findings enhance our understanding of vegetation adaptation strategies and ecosystem responses to climate stress. Full article

Effective water governance is essential for sustainable development amidst water scarcity challenges in semi-arid regions like Esmeraldas Province, which has substantial agrotourism potential. Yet, fragmented governance and chronic water shortages threaten its viability. Using a mixed-method approach, this study analyzed how sustainable water governance can support agrotourism development in Esmeraldas Province, Ecuador. This study combined policy gaps analysis, stakeholder surveys (policymakers, farmers, community leaders, and tourism operators), and water availability using the Standardized Precipitation Evapotranspiration Index (SPEI) from 1980 to 2022. The results revealed a lack of policy regulation and water infrastructure as the major governance gaps that need more intervention. The survey respondents indicated that water is mainly used for domestic and economic activities and the conservation of natural ecosystems. The SPEI revealed a significant drought trend falling below −3, with severe drought years coinciding with many crop losses and a fall in tourism. This study highlights the interconnection between water governance and agrotourism in Esmeraldas, Ecuador, proposing a strategic framework that incorporates adaptive governance principles and inclusive participation mechanisms, emphasizing targeted capacity building to strengthen water management practices and enhance the Sustainable Development Goals for agrotourism resilience. Full article

As an extreme event driven by global climate change, drought poses a severe threat to terrestrial ecosystems. The Yangtze River Basin (YZRB) and Yellow River Basin (YRB) are key ecological barriers and economic zones in China, holding strategic importance for exploring the evolution of drought patterns and their ecological impacts. Using meteorological station data and Climatic Research Unit Gridded Time Series (CRU TS) data, this study analyzed the spatiotemporal characteristics of drought evolution in the YZRB and YRB from 1961 to 2021 using the standardized precipitation evapotranspiration index (SPEI) and run theory. Additionally, this study examined drought effects on ecosystem carbon sequestration (CS) at the city, county, and pixel scales. The results revealed the following: (1) the CRU data effectively captured precipitation (annual r = 0.94) and temperature (annual r = 0.95) trends in both basins, despite significantly underestimating winter temperatures, with the optimal SPEI calculation accuracy found at the monthly scale; (2) both basins experienced frequent autumn–winter droughts, with the YRB facing stronger droughts, including nine events which exceeded 10 months (the longest lasting 25 months), while the mild droughts increased in frequency and extreme intensity; and (3) the drought impacts on CS demonstrated a significant threshold effect, where the intensified drought unexpectedly enhanced CS in western regions, such as the Garzê Autonomous Prefecture in Sichuan Province and Changdu City in the Xizang Autonomous Region, but suppressed CS in the midstream and downstream plains. The CS responded positively under weak drought conditions but declined once the drought intensity surpassed the threshold. This study revealed a nonlinear relationship between drought and CS across climatic zones, thereby providing a scientific foundation for enhancing ecological resilience. Full article

This study presents an integrated spatiotemporal assessment of drought conditions in the Thung Kula Ronghai region of Northeastern Thailand from 2001 to 2023. Multiple satellite-derived drought indices, including SPI, SPEI, RDI, and AI, together with NDVI anomalies, were used to detect seasonal and long-term drought dynamics affecting rainfed Hom Mali rice production. The results show that dry season droughts now affect up to 17 percent of the region’s agricultural land in some years, while severe drought zones persist across more than 2.5 million hectares over the 20-year period. In the most recent 5 years, approximately 50 percent of cultivated areas experienced moderate to severe drought conditions. The RDI showed the strongest correlation with NDVI anomalies (r = 0.22), indicating its relative value for assessing vegetation response to moisture deficits. The combined index approach delineated high-risk sub-regions, particularly in central Thung Kula Ronghai and lower Surin, where drought frequency and severity have intensified. These findings underscore the region’s increasing exposure to dry-season water stress and highlight the need for site-specific irrigation development and adaptive cropping strategies. The methodological framework demonstrated here provides a practical basis for improving drought monitoring and early warning systems to support the resilience of Thailand’s high-value rice production under changing climate conditions. Full article

Accurate drought monitoring depends on selecting an appropriate cumulative distribution function (CDF) to model the original data, resulting in the standardized drought indices. In the numerous research studies, while rigorous validation was not made by scrutinizing the model assumptions and uncertainties in identifying theoretical drought CDF models, such oversights lead to biased representations of drought evaluation and characteristics. This research compares the parametric theoretical and empirical CDFs for a comprehensive evaluation of standardized Drought Indices. Additionally, it examines the advantages, disadvantages, and limitations of both empirical and theoretical distribution functions in drought assessment. Three drought indices, Standardized Precipitation Index (SPI), Streamflow Drought Index (SDI), and Standardized Precipitation Evapotranspiration Index (SPEI), cover meteorological and hydrological droughts. The assessment spans diverse applications, covering different climates and regions: Durham, United Kingdom (SPEI, 1868–2021); Konya, Türkiye (SPI, 1964–2022); and Lüleburgaz, Türkiye (SDI, 1957–2015). The findings reveal that theoretical and empirical CDFs demonstrated notable discrepancies, particularly in long-term hydrological drought assessments, where underestimations reached up to 50%, posing risks of misinformed conclusions that may impact critical drought-related decisions and policymaking. Root Mean Squared Error (RMSE) for SPI3 between empirical and best-fitted CDF was 0.087, and between empirical and Gamma it was 0.152. For SDI, it ranged between 0.09 and 0.143. The Mean Absolute Error (MAE) for SPEI was approximately 0.05 for all timescales. Additionally, it concludes that empirical CDFs provide more reliable and conservative drought assessments and are free from the constraints of model assumptions. Both approaches gave approximately the same drought duration with different intensities regarding drought characteristics. Due to the complex process of drought events and different definitions of drought events, each drought event must be studied separately, considering its effects on different sectors. Full article

Global climate change has increased the frequency of compound drought–heatwave events (CDHEs), seriously threatening tropical forest ecosystems. However, due to the complex structure of natural tropical forests, related research remains limited. To address this, we focused on rubber plantations on Hainan Island, which have simpler structures, to explore the impacts of CDHEs on their primary productivity. We used Pearson and Spearman correlation analyses to select the optimal combination of drought and heatwave indices. Then, we constructed a Compound Drought–Heatwave Index (CDHI) using Copula functions to describe the temporal patterns of CDHEs. Finally, we applied a Bayes–Copula conditional probability model to estimate the probability of GPP loss under CDHE conditions. The main findings are as follows: (1) The Standardized Precipitation Evapotranspiration Index (SPEI-3) and Standardized Temperature Index (STI-1) formed the best index combination. (2) The CDHI successfully identified typical CDHEs in 2001, 2003–2005, 2010, 2015–2016, and 2020. (3) Temporally, CDHEs significantly increased the probability of GPP loss in April and May (0.58 and 0.64, respectively), while the rainy season showed a reverse trend due to water buffering (lowest in October, at 0.19). (4) Spatially, the northwest region showed higher GPP loss probabilities, likely due to topographic uplift. This study reveals how tropical plantations respond to compound climate extremes and provides theoretical support for the monitoring and management of tropical ecosystems. Full article

In recent years, under the influence of climate change and human activities, droughts and floods have occurred frequently in the Yangtze River Basin (YRB), seriously threatening socioeconomic development and ecological security. The topography and climate of the YRB are complex, so it is crucial to develop appropriate drought and flood policies based on the drought and flood characteristics of different sub-basins. This study calculated the water storage deficit index (WSDI) based on the Gravity Recovery and Climate Experiment (GRACE) and GRACE-Follow On (GFO) mascon model, extended WSDI to the bidirectional monitoring of droughts and floods in the YRB, and verified the reliability of WSDI in monitoring hydrological events through historical documented events. Combined with the wavelet method, it revealed the heterogeneity of climate responses in the three sub-basins of the upper, middle, and lower reaches. The results showed the following. (1) Compared and verified with the Standardized Precipitation Evapotranspiration Index (SPEI), self-calibrating Palmer Drought Severity Index (scPDSI), and documented events, WSDI overcame the limitations of traditional indices and had higher reliability. A total of 21 drought events and 18 flood events were identified in the three sub-basins, with the lowest frequency of drought and flood events in the upper reaches. (2) Most areas of the YRB showed different degrees of wetting on the monthly and seasonal scales, and the slowest trend of wetting was in the lower reaches of the YRB. (3) The degree of influence of teleconnection factors in the upper, middle, and lower reaches of the YRB had gradually increased over time, and, in particular, El Niño Southern Oscillation (ENSO) had a significant impact on the droughts and floods. This study provided a new basis for the early warning of droughts and floods in different sub-basins of the YRB. Full article

This study compares three Standardized Precipitation and Evapotranspiration Index (SPEI) prediction models at different time scales: (1) Kalman filter with exogenous variables (DKF-ARX-Pt, FK), (2) gated recurrent unit (GRU), and (3) autoregressive neural networks with external input (NARX). Using observed data from meteorological stations in the State of Mexico and Mexico City, considering performance metrics, such as mean absolute error (MAE), mean square error (MSE), root mean square error (RMSE), coefficient of determination (R²), Nash–Sutcliffe efficiency coefficient (NSE) and Kling–Gupta efficiency (KGE). The results indicate that the FK model with exogenous variables is the most accurate model for SPEI prediction at different time scales, standing out in terms of stability and low variance in prediction error. GRU networks showed acceptable performance on long time scales (SPEI12 and SPEI24), but with lower stability on short scales. In contrast, NARX presented the worst performance, with high errors and negative efficiency coefficients at several time scales. Models based on Kalman filters can be key tools to improve drought mitigation strategies in vulnerable regions, as it has an improved average predictive accuracy by reducing the MAE by up to 68% and achieving higher consistency in KGE values at longer time scales (SPEI12 and SPEI24). Full article

Droughts accompanied by high temperatures are becoming increasingly frequent across Europe and globally. Both individual trees and entire forest ecosystems are exposed to drought stress, with prolonged drought periods leading to increased tree mortality. Therefore, continuous monitoring, data collection, and analysis of tree mortality are essential prerequisites for understanding the complex interactions between climate and trees. This study examined the effects of short-term and prolonged (multi-year) droughts on the mortality of individual trees and forests in Serbia. The analysis was based on datasets from our previous research on the influence of drought and drought duration on individual tree mortality in Serbian forest ecosystems, supplemented with new data collected through the International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests). Additionally, we incorporated data from the public enterprise (PE) “Srbijašume”, which manages forests in Central Serbia, focusing on random yields resulting from natural disasters (droughts). These data enabled a comparative assessment of the findings on increased mortality and drought impact at both the individual tree level and the stand level. This study identifies key similarities and differences in tree mortality trends based on drought duration and examines their correlations within the same time frame (2004–2023). By analysing climatic conditions across Serbia, we provide evidence of the interaction between drought periods and increased forest mortality, which we further confirmed by calculating the Standardized Precipitation Evapotranspiration Index (SPEI). We also address the tree species that were most sensitive to the effects of drought. Our findings indicate that prolonged (multi-year) droughts, accompanied by high temperatures, have significantly contributed to increased tree mortality over the past decade. Successive multi-year droughts pose a substantial threat to both individual trees and entire forests, producing more severe and persistent responses compared to those caused by single-year droughts, which forests and individual trees are generally more capable of tolerating. Moreover, due to prolonged drought stress, trees weaken, leading to delayed mortality that may manifest several years after the initial drought event. The observed increase in tree mortality has been found to correlate with rising temperatures and the growing frequency of prolonged droughts over the past decade. Especially, intense droughts in the growing season (April–September) have a very negative impact on forests. Full article

As a critical ecologicalbarrier in the semi-arid to semi-humid transition zone of northern China, the interaction between afforestation and climatic stressors in the Yellow River Basin constitutes a pivotal scientific challenge for regional sustainable development. However, the synthesis effects of afforestation and climate on primary productivity require further investigation. Integrating multi-source remote sensing data (2000–2020), meteorological observations with the Standardized Precipitation Evapotranspiration Index (SPEI) and an improved CASA model, this study systematically investigates spatiotemporal patterns of vegetation net primary productivity (NPP) responses to extreme drought events while quantifying vegetation coverage’s regulatory effects on ecosystem drought sensitivity. Among drought events identified using a three-dimensional clustering algorithm, high-intensity droughts caused an average NPP loss of 23.2 gC·m⁻² across the basin. Notably, artificial irrigation practices in the Hetao irrigation district significantly mitigated NPP reduction to −9.03 gC·m⁻². Large-scale afforestation projects increased the NDVI at a rate of 3.45 × 10⁻⁴ month⁻¹, with a contribution rate of 78%, but soil moisture competition from high-density vegetation reduced carbon-sink benefits. However, mixed forest structural optimization in the Three-North Shelterbelt Forest Program core area achieved local carbon-sink gains, demonstrating that vegetation configuration alleviates water competition pressure. Drought amplified the suppressive effect of afforestation through stomatal conductance-photosynthesis coupling mechanisms, causing additional NPP losses of 7.45–31.00 gC·m⁻², yet the April–July 2008 event exhibited reversed suppression effects due to immature artificial communities during the 2000–2004 baseline period. Our work elucidates nonlinear vegetation-climate interactions affecting carbon sequestration in semi-arid ecosystems, providing critical insights for optimizing ecological restoration strategies and climate-adaptive management in the Yellow River Basin. Full article

The Tarim River Basin is an important grain and cotton base in Xinjiang, China. Indeed, cotton production in this basin accounts for one-third of the total cotton production in China. The Tarim River Basin is characterized also by the presence of forestry activities and fruit plantations. However, frequent long-term droughts have seriously affected local agricultural productivity. In this paper, a new standardized precipitation evapotranspiration index (nSPEI), with an improved drought detection effect, was constructed based on the standardized precipitation index (SPI) and the standardized precipitation evapotranspiration index (SPEI). This drought index was subsequently employed as a hazard indicator of disaster-causing factors in the Tarim River Basin. In addition, a drought disaster risk assessment model was constructed using the natural disaster system theory. This model was applied to analyze the hazard of drought-disaster-causing factors, the exposure of disaster-affected bodies, the vulnerability of disaster-bearing environments, drought prevention/mitigation capabilities, and comprehensive drought disaster risks in the Tarim River Basin over the 2001–2021 period. The results demonstrated the applicability of the 12-month nSPEI (nSPEI-12) in the Tarim River Basin. Specifically, the nSPEI-12 values exhibited a decreasing trend, highlighting an aridification trend in the basin. In addition, a 25% increase in the vegetation cover of the Tarim River Basin was observed from 2000 to 2023 and remained unchanged at 4.5%. On the other hand, a decreasing trend of the vegetation cover was found in the remaining parts of the basin. The hazard level of the disaster-causing factors and the exposure of bearing bodies were high in the northeastern and northwestern parts of the Tarim River Basin, respectively. The disaster prevention/mitigation capacity was greater in the northern and southwestern parts, while the vulnerability level of disaster-bearing environments decreased from the northwestern part to the southeastern part. The western and northern parts of the Tarim River Basin exhibited the highest drought risk levels, followed by the northeastern and southeastern parts. Full article

This study investigates the spatio-temporal distribution of meteorological drought in the upper Cheliff basin, Algeria, downstream of the Boughzoul dam, between September 1982 and August 2021. This research use two drought indices—the Standardised Precipitation Index (SPI) and the Standardised Precipitation and Evapotranspiration Index (SPEI)—to evaluate drought trends, frequency, duration, severity, and number of events across various time scales (1 year, 1 month, 3 months, 6 months, 9 months, and 12 months). The results identify five major drought periods (1983/84, 1993/94, 1987/88, 1999/2000–2001/2002, and 2020/21). Both the SPI and the SPEI capture the monthly variability of drought on various time scales, with different intensities. The SPEI identifies a higher number of drought events than the SPI, particularly on shorter time scales (1 and 3 months). However, at longer timescales (6, 9, and 12 months), the number of drought events detected by both indices converges. The correlation between SPI and SPEI (R ranging from 0.73 to 0.93) across the same time scales is notably high, though the lowest correlation was found in the western part of the catchment area. This suggests that for accurate meteorological drought identification in this region, particularly in its intensively irrigated agricultural areas, SPI and SPEI should be considered. Full article

Soil moisture (SM) plays a fundamental role in the water cycle and is an important variable for all processes occurring at the lithosphere–atmosphere interface, which are strongly affected by climate change. Among the different fields of application, accurate SM measurements are becoming more relevant for all studies related to extreme event (e.g., floods, droughts, and landslides) mitigation and assessment. In this study, data acquired by the advanced microwave sounding unit (AMSU) onboard the European Meteorological Operational Satellite Program (MetOP) satellites were used for the first time to extract information on the variability of SM by implementing the original soil wetness index (SWI). Long-term monthly SWI time series collected for the Basilicata region (southern Italy) were analyzed for drought assessment during the period 2007–2021. The accuracy of the SWI product was tested through a comparison with SM products derived by the Advanced SCATterometer (ASCAT) over the 2013–2016 period, while the Standardized Precipitation-Evapotranspiration Index (SPEI) was used to assess the relevance of the long-term achievements in terms of drought analysis. The results indicate a satisfactory accuracy of the SWI, with the mean correlation coefficient values with ASCAT higher than 0.7 and a mean normalized root mean square error less than 0.155. A negative trend in SWI during the 15-year period was found using both the original and deseasonalized series (linear and Sen’s slope ~−0.00525), confirmed by SPEI (linear and Sen’s slope ~−0.00293), suggesting the occurrence of a marginal long-term dry phase in the region. Although further investigations are needed to better assess the intensity and main causes of the phenomena, this result indicates the contribution that satellite data/products can offer in supporting drought assessment. Full article

This study analyzed the impact of land use and cover changes, along with climate variability, on water consumption by quantifying actual evapotranspiration (${\mathrm{ET}}_{\mathrm{a}}$) in the Tres Cruces River basin (TCR) in Uruguay. Using Landsat 8 and 9 images from 2014 to 2024, the SAFER method (Simple Algorithm for Evapotranspiration Retrieving), applied for the first time in Uruguay, estimated ${\mathrm{ET}}_{\mathrm{a}}$ for natural vegetation (grasslands and riparian forests) and commercial afforestation areas. Quality metrics, including determination coefficient (r² = 0.87), Pearson correlation (r = 0.94), root mean square error (RMSE = 1.46 mm/day), and Nash–Sutcliffe efficiency (NSE = 0.34), were utilized for SAFER’s optimal parameterization based on the literature. Results revealed monthly ${\mathrm{ET}}_{\mathrm{a}}$ variability and highlighted higher ${\mathrm{ET}}_{\mathrm{a}}$ values for afforestation areas, exceeding grasslands by 26.5% and riparian forests by 4.79%, reflecting increased water demand due to greater biomass and photosynthetic activity. Additionally, prolonged drought periods correlated with increased water consumption by forest vegetation, despite the Standardized Precipitation-Evapotranspiration Index (SPEI) remaining within normal bounds during the 2020–2023 drought. These findings underscore the significant hydrological implications of converting grasslands to afforestation and the need for integrated water resource management amid expanding commercial forestry in the region. Full article

This study investigates meteorological drought characteristics across three climatic zones in Benin using the SPEI (Standardized Precipitation Evapotranspiration Index) and SPI (Standardized Precipitation Index). A comprehensive statistical approach was employed, including the Mann–Kendall trend test, drought duration and intensity analysis, Pearson correlation, cross-wavelet transform, and the Standardized Relative Air Humidity Index (SRHI), to assess drought patterns and trends. The findings indicate increasing consistency between SPI and SPEI trends at longer timescales, though significant regional variations persist. In Zone 1 (northern Benin), SPI exhibited an increasing trend across all timescales, whereas SPEI demonstrated a decreasing trend at shorter timescales. In contrast, in Zones 2 (central Benin) and 3 (south Benin), both indices generally displayed a decreasing trend, except at the one-month scale. An analysis of drought duration and intensity revealed that, at shorter timescales (SPI and SPEI at 1- and 3-month intervals), the longest droughts occurred in Zones 1 and 3, while the most intense events were recorded in Zone 2. At longer timescales (SPI and SPEI at 6- and 12-month intervals), Zone 2 experienced the longest droughts, whereas Zone 3 exhibited the highest intensities. These findings illustrate the need for monitoring strategies tailored to a given area’s characteristics. Despite these insights, data uncertainties and regional differences present challenges for drought investigation. Future studies should incorporate more datasets and investigate different drought indices to improve decision-making and improve strategies for safeguarding Benin’s agricultural sector, ecosystems, and food supply. Full article