Drought Duration Research Articles

Study on the multi-type drought propagation process and driving factors on the Tibetan Plateau

Drought propagation is a complex process that involves various components of the water cycle. Clarifying the pathways and mechanisms of propagation for various types of droughts is crucial. However, most current analyses of drought propagation focus on the relationship between just two types of drought, with limited research on multi-type drought propagation. This study elucidates the propagation pathways of multi-type drought on the Tibetan Plateau (TP) using extended convergent cross mapping (CCM) to determine the propagation time. Additionally, the CCM-based drought duration propagation index (CDDP) and drought intensity propagation index (CDIP) were constructed, and the driving factors of drought propagation were preliminarily explored using the geographic detector. The results indicate that between 1997 and 2017, drought propagation on the TP followed the sequence of meteorological drought, hydrological drought, and agricultural drought, with propagation times of 4.6 months, 4.9 months, and 4.2 months, respectively. Although the overall trends in multi-type drought propagation characteristics are relatively balanced, significant differences exist within individual basins, and neighboring regions exhibit heterogeneous drought propagation patterns. The key driving factors for different types of drought propagation vary, with natural factors and human activities significantly influencing the spatial distribution of drought propagation characteristics, with CDDP being particularly sensitive to these driving factors. This study further elucidates the processes and driving factors behind multi-type drought propagation, offering new research perspectives for understanding the mechanisms of drought propagation.

Remotely Sensed Comparative Spatiotemporal Analysis of Drought and Wet Periods in Distinct Mediterranean Agroecosystems

Drought is a widespread natural hazard resulting from an extended period of reduced rainfall, with significant socioeconomic and ecological consequences. Drought severity can impact food security globally due to its high spatial and temporal coverage. The primary objective of this paper consists of a comparative spatiotemporal analysis of environmental extremes (drought/wetness) through the estimation of a twelve-month Standardized Precipitation Index (SPI12) between three distinct vulnerable agricultural regions in the Mediterranean basin (i.e., Spain, Lebanon and Tunisia), under a climate change environment in the last 38 years (1982–2020). The added value of this paper lies in the simultaneous estimation of temporal and spatial variability of drought and wetness periodic events, paying special attention to the geographical patterns of these extremes both in annual and interannual (seasonal) time scales. The results indicated that Spain and Tunisia (western Mediterranean) exhibit similar patterns over the studied period, while Lebanon demonstrates contrasting trends. Comparing the two extreme dry hydrological years, the Spanish study area faced the highest drought intensity, areal extent and duration (SPI12 = −1.18; −1.84; 28–78%; 9–12 months), followed by the Lebanese (SPI12 = −1.28; −1.39; 37–50%; 7–12 months) and the Tunisian ones (SPI12 = −1.05; −1.08; 10–34%; 8 months). Concerning the wettest hydrological years, the Lebanese study domain has recorded the highest SPI12 values, areal extent and duration (SPI12 = 1.58; 2.28; 66–83%; 8–11 months), followed by the Tunisian (SPI12 = 1.55; 1.79; 49–73%; 7–10 months) and Spanish one (SPI12 = 1.07; 1.99; 21–73%; 4–11 months). The periodicity of drought/wetness episodes is about 20 years in Spanish area and 10 years in the Lebanese area (for drought events), whereas there seems no periodicity in the Tunisian one. Understanding the spatial distribution of drought is crucial for targeted mitigation strategies in high-risk areas, potentially avoiding broad, resource-intensive measures across entire regions.

Development of DRIP - drought representation index for CMIP climate model performance, application to Southeast Brazil

With the escalating impacts of drought events driven by climate change, reducing the uncertainty of drought projections becomes critical for enhancing risk management and adaptation strategies. This study aimed to develop an index for assessing the performance of CMIP6 Global Climate Models in simulating meteorological drought scenarios across regional hydrological systems, intended to provide more reliable information for management purposes. Named the ‘Drought Representation Index for CMIP Climate Model Performance’ (DRIP), this index evaluates CMIP models' performance to represent drought severity, duration, and return period. DRIP was used to select CMIP models and create an ensemble of the best-performing models (E-DRIP) to improve the reliability of drought projections. E-DRIP was then compared with a general ensemble of available CMIP6 models (E-CMIP). We applied this method in Southeast Brazil, a region known for its climate uncertainties and low predictability; specifically, it was implemented within the Paraíba do Sul River Basin, a nationally strategic watershed in a highly populated and industrialized area, which has recently faced unprecedented drought-related water crises. Results showed that DRIP effectively assessed the individual performance of CMIP models, which exhibited considerable variability, and identified the top-performing models for a multi-model ensemble. Additionally, the E-DRIP ensemble significantly reduced uncertainties in drought projections, achieving an average reduction of 63 % in the study area compared to E-CMIP. Furthermore, the proposed method enables evaluations across any standardized drought index scale, reference period, or threshold, and can be readily adapted to other hydrological systems.

Enhanced effects of species richness on resistance and resilience of global tree growth to prolonged drought

The increasing duration of drought induced by global climate change has reduced forest productivity. Biodiversity is believed to mitigate the effects of drought, thereby enhancing the stability of tree growth. However, the effects of species richness on tree growth stability under droughts with different durations remain uncertain. Here, we used tree ring data from 4,072 sites globally, combined with climate and plant richness data, to evaluate the effects of species richness on the resistance and resilience of trees to short-term and prolonged droughts. We found that species richness enhanced resistance but weakened resilience of trees to drought globally. Compared to short-term drought, species richness further increased tree growth during prolonged drought but reduced the growth afterward, resulting in stronger effects on resistance and resilience. In addition, as the degree of drought intensified and regional aridity levels increased, the effects of richness on resistance and resilience under short-term drought were enhanced, but these trends were reduced or even reversed under prolonged drought. These results reveal the global effects of species richness on resistance and resilience of tree growth to droughts with different durations and highlight that species richness plays a crucial role in resisting prolonged drought.

A novel statistical framework of drought projection by improving ensemble future climate model simulations under various climate change scenarios.

Unlike other natural disasters, drought is one of the most severe threats to all living beings globally. Due to global climate change, the frequency and duration of droughts have increased in many parts of the world. Therefore, accurate prediction and forecasting of droughts are essential for effective mitigation policies and sustainable research. In recent research, the use of ensemble global climate models (GCMs) for simulating precipitation data is common. The objective of this research is to enhance the multi-model ensemble (MME) for improving future drought characterizations. In this research, we propose the use of relative importance metric (RIM) to address collinearity effects and point-wise discrepancy weights (PWDW) in GCMs. Consequently, this paper introduces a new statistical framework for weighted ensembles called the discrepancy-enhanced beta weighting ensemble (DEBWE). DEBWE enhances the weighted ensemble data of precipitation simulated by multiple GCMs. In DEBWE, we addressed uncertainties in GCMs arising from collinearity and outliers. To evaluate the effectiveness of the proposed weighting framework, we compared its performance with the simple average multi-model ensemble (SAMME), Taylor skill score ensemble (TSSE), and mutual information ensemble (MIE). Based on the Kling-Gupta efficiency (KGE) metric, DEBWE outperforms all competitors across all evaluation criteria. These inferences are based on the analysis of historical simulated data from 22 GCMs in the CMIP6 project. The quantitative performance indicators strongly support the superiority of DEBWE. The median and mean KGE values for DEBWE are 0.2650 and 0.2429, compared to SAMME (0.1000, 0.0991), TSSE (0.2600, 0.2397), and MIE (0.1550, 0.1511). For drought assessment, we computed the adaptive standardized precipitation index (SPI) for three future scenarios: SSP1-2.6, SSP2-4.5, and SSP5-8.5. The steady-state probabilities suggest that normal drought (ND) is the most frequent condition, with extreme events (dry or wet) being less probable.

Mitigating the negative effects of droughts on alpine grassland productivity in the northern Xizang Plateau via degradation-combating actions

The Qinghai-Xizang Plateau, hosting the world’s largest alpine pastures, plays a pivotal environmental role in Asia. These ecosystems face alterations driven by both climate change and anthropogenic activities, resulting in the widespread consideration of grassland degradation. From 2000 to 2020, the northern Xizang Plateau experienced a pronounced escalation in drought conditions, particularly following a management policy aimed at combating grassland degradation, via restricting livestock numbers and implementing fencing enclosures, initiated in 2009. Specially, following the enforcement of this policy (2010–2020), there was a substantial 13.5 % reduction in soil moisture levels compared to the pre-implementation period (2000–2009), accompanied by a 42.8 % increase in drought severity (measured by the Palmer Drought Severity Index, PDSI) and an 11.6 % rise in drought duration. Under these challenging drought conditions, we identified negative trends of potential grassland Net Primary Productivity (NPP) which in absence of anthropogenic influence, as simulated by terrestrial ecosystem model (TEM). Contrary to this simulation, satellite time series observations revealed a widespread increase in actual grassland productivity. Remarkably, despite the challenging drought conditions between 2010 and 2020, we observed a substantial increase of 4.8 % in actual NPP (measured by light use efficiency model), 2.7 % in Normalized Difference Vegetation Index (NDVI), 10 % in solar-induced chlorophyll fluorescence (SIF), and 7.95 % in Gross Primary Productivity (GPP), respectively. Much of this enhancement in grassland productivity occurred in areas where livestock populations had markedly declined. Notably, the percentage of NPP increase mainly caused by degradation-combating actions doubled from 24.8 % during 2000–2009 to 49.8 % during 2010–2020 across the northern Xizang Plateau. In conclusion, our findings highlight the potential of large-scale degradation-combating actions to mitigate the negative impacts of climate change and contribute to a greener Earth.

Procedure for detecting drought trends using Şen’s innovative trend analysis methodology

The increasing occurrence of drought has negative effects on water resources. To prevent these negative effects, it is of great importance to know drought trends over time. Many methods are used in the literature to determine the severity of drought, one of which is the standard precipitation index (SPI), which is calculated based on precipitation data. The SPI method was chosen in this study because it is widely used in the literature for its simplicity, flexibility and effectiveness in characterising drought duration and intensity. There are different classifications of drought severity in the SPI method, so it is very important to know the individual trends for each classification. Classical trend detection methods (such as the Mann–Kendall method) require a separate analysis for each drought classification. However, using Şen’s innovative trend analysis, it becomes possible to determine the trends for all drought classifications on a single graph. In this way, the change of drought events over time can be easily determined for all drought classifications.

Predictor of willingness to pay for early warning climate system and agronomy advisories services in Albania: A case study of medicinal plant in “Malesi e Madhe”

Abstract Access to useful climate information is critical for adaptation needs of Albanian smallholder farmers, yet empirical studies documenting the socioeconomic, environmental and household predictors of access to and willingness to pay for climate information services have been limited to date. This paper addresses the need by identifying the predictors of access to and willingness to pay for climate information by smallholder farmers in the northern area of Albania, a “dangerous hotspot” where slight changes in rainfall and temperature often result in considerable yield losses. The study uses data collected from 201 household surveys in 5 communities across 29 districts in the “Malesia e Madhe” region of Albania using a simple random sampling method. Sampling was conducted in end 2023 and start of 2024 and participants were interviewed face to face by questionnaires following a contingent valuation method for collecting data for willingness to pay for early warning climate system. The EFA analysis was performed on farmer’s awareness to climate changes and their impact on quality and productivity. Our findings suggest that the majority of smallholders are aware of duration of drought (95%), increase of number of hot days (88.1%) and presence of weeds (59.7%). From the findings, farmers perceive that climate changes have affected the quality of medicinal plants in the last 5 years, by increasing the number of hot days (96%), number of rainy days (93.5%) and duration of drought (86.6%), also farmers perceive that climate change has impacted the yield level by duration of drought (87.1%), increase of hot nights (78.1%) and number of rainy days (76.1%). The findings suggest that the majority of smallholder farmers were not willing to pay for the cost of receiving climate information delivered via SMS. The results from the marginal analysis suggest that access to climate information is influenced by farm topology factors. The marginal effects logistic regression shows statistically significant effect in household predictors such as farmer’s size and income. Results suggest that the provision of climate information should be defined and adopted to meet the needs of smallholder farmers with different socioeconomic backgrounds to enable farmers manage climate risks and build reasonable adaptive capacity.

Research on the risk of drought disasters in the middle reaches of the Yellow River coupled with ecosystem entity

ABSTRACT Drought is one of the most significant natural disasters. In this study, we utilized the middle reaches of the Yellow River as the subject of our investigation. We characterized the exposure of ecosystem disaster-bearers by NDVI and established a probabilistic framework for assessing the vulnerability of ecosystems under drought stress, coupling ecosystems and human society disaster-bearers. The SPI was selected to identify the attributes of drought by employing the travel theory, and the bivariate joint distribution of drought duration and intensity was constructed by utilizing the Copula function. The temporal and spatial changes in drought risk in the middle reaches of the Yellow River are investigated using the risk calculation formula defined by the IPCC. The results indicate that a few areas, including the Wei River, Wuding River, Fen River, and Yiluo River basins, are prone to drought events with low drought duration and low drought intensity. The drought risk exhibited an upward trend, gradually expanding outward from the mainstem area. The area of high drought risk in the two-variable AND relationship migrated upstream from the downstream of the Wuding River, the Beiluo River, the Jing River, the Wei River, and the Fen River.

High-resolution Standardized Precipitation Evapotranspiration Index (SPEI) reveals trends in drought and vegetation water availability in China

Understanding vegetation water availability can be important for managing vegetation and combating climate change. Changes in vegetation water availability throughout China remains poorly understood, especially at a high spatial resolution. Standardized Precipitation Evapotranspiration Index (SPEI) is an ideal water availability index for assessing the spatiotemporal characteristics of drought and investigating the vegetation-water availability relationship. However, no high-resolution and long-term SPEI datasets over China are available. To fill this gap, we developed a new model based on machine learning to obtain high-resolution (1 km) SPEI data by combining climate variables with topographical and geographical features. Here, we analyzed the long-term drought over the past century (1901–2020) and vegetation-water availability relationship in the past two decades (2000–2020). The century-long drought trend analyses indicated an overall drying trend across China with increasing drought frequency, duration, and severity during the past century. We found that drought events in 1901–1961 showed a larger increase than that in 1961–2020, with the Tibetan Plateau showing a significant drying trend during 1901–1960 but a wetting trend during 1961–2020. There were 13.90% and 28.21% of vegetation in China showing water deficit and water surplus respectively during 2000–2020. The water deficit area significantly shrank from 2000 to 2020 across China, which is dominated by the significant decrease in water deficit areas in South China. Among temperature, precipitation, and vegetation abundance (LAI), temperature is the most important factor for the vegetation-water availability dynamics in China over the past two decades, with high temperature contributing to water deficit. Our findings are important for water and vegetation management under a warming climate.

Assessment of drought changes, trends, frequency and duration in the Gulf of Guinea region (west africa)

Assessment of drought changes, trends, frequency and duration in the Gulf of Guinea region (west africa)

The effects of climate change and regional water supply capacity on integrated drought risk

Due to climate change, the frequency and duration of meteorological drought have increased. In addition, local water supply capacity has not met water demand in many regions, which will eventually lead to serious water shortages. To mitigate the effects of drought on sustainable water use, it is necessary to understand how climate change affects regional water supply capacity and drought risk. To this end, this study evaluated the drought response capacity of regional water supply systems and assessed the comprehensive drought risk in terms of drought hazard, vulnerability, and response capacity. To avoid subjectivity in risk analysis, structural equation modeling was used to select primary indicators and probability and statistical methods were used to assign weights to the indicators. The changes in drought risk in different climate change scenarios were assessed using sensitivity analyses. The overall results indicate that the future drought risks in Gyeonggi, Gyeongsang, Chungcheong, Jeolla, and Gangwon are 18, 12, 13, 9, and 10% higher, respectively, than the current risk level. The sensitivity analyses showed that Jinju in Gyeongsang province, which has a high drought response capacity, had the largest decreasing rate in drought risk. The quantified changes in drought risk under future climate change scenarios will be useful for identifying areas with a high drought risk and making decisions about drought mitigation under climate change.

Biomass burning in Peninsular Southeast Asia intensifies meteorological drought in Southwest China

Biomass burning in Peninsular Southeast Asia (BB–PSEA) affects the climate in downwind regions, especially precipitation (PRE) in southern China. However, the impact of BB–PSEA on the meteorological drought in Southwest China (SWC), where closes to PSEA and often occurs seasonal drought, have not been clear yet. We selected a severe drought event in SWC from January to April 2010 and conducted sensitivity simulations using WRF–Chem (Weather Research and Forecasting model coupled with Chemistry) to evaluate the impact of BB–PSEA on the meteorological drought in SWC. Comparisons with observations revealed that the model performed well in simulating the spatiotemporal evolution of the drought in SWC. BB–PSEA increased the drought severity by 0.01–0.75 levels, enlarged drought areas by about 10%, and prolonged the drought duration mainly by one month in SWC. The impact of BB–PSEA on the drought in SWC in March/April was almost tenfold that in January/February, due to the higher emissions of BB–PSEA in March/April. The mechanism that BB–PSEA influenced drought predominantly involved the reduction of PRE, potential evapotranspiration (PET), and moisture fluxes in SWC. BB–PSEA aerosols warmed the air at 600–800 hPa and cooled the air near the surface in SWC, which stabilized the atmosphere and suppressed PRE and reduced PET in SWC. BB–PSEA aerosols also increased the sea surface temperature in South China Sea and the geopotential heights in the north of the Bay of Bengal, where the moisture sources of SWC originated from. This perturbation reduced the moisture fluxes across the west and south boundaries of SWC, resulting in the reduction of the water vapor content and PRE in SWC. Through elucidating the impact of BB–PSEA on the drought in SWC, this study clarified how BB–PSEA affected the climate in the downwind region and provided new understanding for drought prediction in SWC.

Hydrothermal environments lead to differences in the radial growth response of Pinus tabulaeformis to climate in the monsoon marginal zone, Northwestern China

Regional climatic differences increase the complexity of tree radial growth responses to climate change in the monsoon marginal zones and may alter the carbon sequestration capacity of forests. In this study, we collected cores of Pinus tabulaeformis trees at nine sampling sites across different regions. We analysed the relationship between tree-ring width chronology and climatic factors at different sites using dendroecological methods. We used the tree-ring index to calculate resistance, recovery, and resilience as well as to explore the capacity of radial growth to cope with drought events. The results indicate that (1) Drought was the primary factor limiting tree growth, and tree-ring climate response patterns varied across three regions. Tree growth was sensitive to both temperature and precipitation in the eastern Qilian Mountains, while it was more sensitive to temperature in the Hassan Mountains and more sensitive to precipitation in the Helan Mountains. (2) The tree-ring climate response pattern remained unstable over time, and the relative influence of current climate on tree growth increased. (3) The ecological resilience of trees to extreme events varies across three regions, which could be attributed to regional moisture conditions and the duration of drought. In the context of the management and protection of trees in the study area in the future, more attention should be paid to the elasticity of tree growth after drought events.

Improved identification and monitoring of meteorological, agricultural, and hydrological droughts using the modified nonstationary drought indices in the Yellow River Basin of China

Non-stationarity in hydro-meteorological series complicates drought monitoring and assessment. Our study aimed to better identify and monitor meteorological, agricultural and hydrological droughts in the Yellow River Basin (YRB) of China. We constructed nonstationary standardized precipitation index (NSPI), nonstationary standardized precipitation evapotranspiration index (NSPEI), nonstationary standardized soil moisture index (NSSMI) and nonstationary standardized runoff index (NSRI) based on the Generalized Additive Models for Location, Scale, and Shape (GAMLSS). We also investigated the performance of NSPI/NSPEI/NSSMI/NSRI by comparing them with historical drought events. Our results revealed that: (1) The probability distribution function (PDF), smoothing function (SF), and degrees of freedom (DF) significantly influenced the fitting effect of the GAMLSS model. The PDF emerged as the most critical factor in determining fitting accuracy, while SF and DF played crucial roles in preventing overfitting and accurately depicting data variations. (2) Stationary GAMLSS models were primarily suited for time series with lower-scales (1- and 3-month scales), whereas nonstationary models exhibited better suitability for time series with higher-scale (6- and 12-month scales). (3) NSPI and NSPEI demonstrated heightened sensitivity in identifying meteorological droughts, with NSPEI showing greater precision in determining drought intensity and duration. However, compared to SSMI, while NSSMI aligned more closely with historical agricultural drought events, it exhibited limited responsiveness to mild and moderate drought. (4) NSRI indicated that hydrological droughts in the tributaries of the YRB were significantly influenced by meteorological droughts, and the intensity of hydrological drought was stronger than that in the mainstream of the YRB. In conclusion, the nonstationary drought indices could better identify drought events in the period of climate change, and provide valuable information for drought management in the climate change environment.

Resistance of grassland productivity to drought and heatwave over a temperate semi-arid climate zone

Drought and heatwave are the primary climate extremes for vegetation productivity loss in the global temperate semi-arid grassland, challenging the ecosystem productivity stability in these areas. Previous studies have indicated a significant decline in the resistance of global grassland productivity to drought, but we still lack a systematic understanding of the mechanisms determining the spatiotemporal variations in grassland resistance to drought and heatwave. In this study, we focused on temperate semi-arid grasslands of China (TSGC) to assess the spatiotemporal variations of grassland productivity resistance to different climate extremes: compound dry-hot events, individual drought events, and individual heatwave events that occurred during 2000–2019. Based on the explainable machine learning model, we explored the resistance to the interaction of drought and heatwave and identify the dominant factors determining the spatiotemporal variations in resistance. The results revealed that grassland resistance to climate extremes had decreased in Xilingol Grassland and Mu Us Sandy Land, and had a not significant increase in Otindag Desert during 2000–2019. Human activities and the increase in CO2 concentration causes a decline in resistance in Mu Us Sandy Land, and the increase of VPD and shift of vegetation loss event timing caused a decline in resistance in Xilingol Grassland, while the weakening of climate extremes, especially the shortening of drought duration, increase the resistance in Otindag Desert. Mean annual temperature dominates the spatial differences in resistance among different grasslands. When drought and heatwave occur simultaneously, there is an additive effect on resistance and causes lower resistance to compound dry-hot events compared to individual drought and heatwave events. Our analysis provides crucial insights into understanding the impact of climate extremes on the temperate semi-arid grasslands of China.

Damage Inflicted by Extreme Drought on Poyang Lake Delta Wetland and the Establishment of Countermeasures

Due to the joint influence of climate change and human activities, the hydrological rhythm of Poyang Lake has changed in recent years, leading to an increasingly severe drought problem during autumn and winter in this region. Notably, the extreme drought that occurred in 2022 had profound impacts on shipping, water supply and the ecological environment of the wetlands in the Poyang Lake Delta, sparking widespread concern. Based on the historical hydrometeorological data of Poyang Lake, we used statistical models (such as Chow test, correlation analysis, etc.) to analyze the cause of the extreme drought in the Poyang Lake Delta from the perspectives of natural factors and human activity. Through correlation analysis, we found that the water level, discharge, and drought duration of the Poyang Lake Delta were all significantly affected by climate change, particularly rainfall in the Poyang Lake basin. Furthermore, combining the results of Chow test and correlation analysis, we also found that the operation of the Three Gorges Reservoir had a notable impact on the water level of the Poyang Lake Delta. Based on remote sensing images, ecological and environmental sampling monitoring, the damage inflicted by the extreme drought event on the Poyang Lake Delta was analyzed. The results show that the inundated area of the delta wetlands in the extreme-drought year (2022) decreased by 45.75% compared with that in a normal year (2017). In addition, the ecological environment of the wetlands deteriorated significantly. The water quality parameters (TN, TP, NH4+-N) increased by 50.2%, 240% and 64.7%, respectively. The concentrations of TN and TP were 3.8 mg/L and 0.17 mg/L, respectively, while the context values in the delta were 1.2 mg/L and 0.075 mg/L. The density and biomass of algae increased by 87.2% and 557.9%, respectively. In contrast, the density and biomass of benthos decreased by 59.9% and 78.5%, respectively. The control strategy for the Poyang Lake Delta under extreme drought was studied through an experiment on the operation of hydraulic controllers. The results show that under extreme drought conditions, the newly built hydraulic controllers could raise the water level of the delta from 9.1 ± 0.7 m to 14.2 ± 1.8 m, thus effectively solving the water cut-off problem in the four branches of the delta. Furthermore, by adjusting the distributive ratio of the main, north, middle and south branches of the delta to 50%, 4%, 24% and 22% through newly built hydraulic controllers, the water area can be increased by 56%.

Analysis of Meteorological Drought for Selected Districts of Saurashtra Region of Gujarat

Drought, in particular, is a complex and recurring phenomenon triggered by insufficient precipitation or changes in its distribution, often resulting in decreased water availability. It evolves slowly, affecting large populations' access to food and water, disrupting the entire hydrological cycle, and causing long-term economic losses. The present study attempts a comprehensive analysis of meteorological drought characteristics for selected districts (Junagadh, Amreli, Jamnagar, and Rajkot) in the semi-arid Saurashtra region of Gujarat. The analysis of meteorological drought was performed using rainfall (RF), maximum temperature (Tmax), and minimum temperature (Tmin) data from four stations (each district has one station) for the 43 years duration (1981–2023). The Standardized Precipitation Evapotranspiration Index (SPEI) is utilized across multiple timescales to assess the number of drought affected years, occurrence of drought and drought parameters (total drought duration, magnitude, and intensity). The meteorological drought incidence varied significantly across Junagadh, Amreli, Jamnagar and Rajkot, with Junagadh experiencing droughts in 29% of years, Amreli in 32%, and higher rates in Jamnagar (37%) and Rajkot (36%). The most severe drought years in the four districts were 1987 and 2002, with additional major droughts occurred in 1985, 1986, 1987, 1993, 2002 and 2012. These districts also faced consecutive droughts from 1985 to 1987 and again from 1999 to 2002.Analysis of drought parameters in Junagadh, Amreli, Jamnagar and Rajkot districts showed that drought duration (DD) ranged from 29.46% (Junagadh) to 35.85% (Jamnagar) of months, drought magnitude (DM) varied between -37.58% (Jamnagar) and -34.10% (Junagadh), and drought intensity (DI) spanned from -1.17 (Rajkot) to -1.04 (Junagadh). The analysis of drought occurrence in all districts shows that mild and moderate droughts have been most frequent while severe and extreme droughts have been less common. The study's findings enhance water managers' understanding of how climate change influences drought patterns in the region, thereby assisting policymakers in conducting effective drought risk assessments.

Quantification of interactions among agricultural drought indices within Köppen–Geiger climate zones in Bangladesh

Agricultural productivity is highly correlated with climatic variations, including drought events. This study is aimed at performing a comprehensive assessment of agricultural drought conditions in the Köppen–Geiger climate zones in Bangladesh, based on the temperature condition index (TCI), vegetation condition index (VCI), and vegetation health index (VHI). The zones are classified as follows: temperate dry winter with a hot summer zone, tropical savannah zone, and tropical monsoon zone. The range of VHI is optimized based on its correlation with TCI and VCI. The correlation among the stratified drought indices is also examined to quantify and measure the strength and direction of the linear relationships between them. Moreover, Mann–Kendall test is conducted to assess the statistical trends in the spatiotemporal propagation of droughts across different climate zones. The balanced correlation approach for VHI reveals that vegetation health is governed by the temperature conditions. Certain variations in the drought intensity, frequency, and duration are observed across climatic zones in earlier years while the recent years are noted with less droughts. Normal or no drought conditions are noticed mostly in the tropical monsoon zone through VCI and VHI. The correlations among the drought classes indicate that VHI is more strongly correlated with TCI than with VCI, while NDVI exhibits stronger correlations with VCI than with either VHI or TCI. The Mann-Kendall test revealed that VCI has significant downward trends in drought categories and an upward trend in normal conditions, whereas VHI and TCI displayed inconsistency in statistical trends. By extensively exploring the agricultural drought conditions within specific climate zones, this study offers valuable insights for agronomists and stakeholders involved in climate resilience planning and agricultural development in Bangladesh.

Spatiotemporal analysis of compound droughts and heat waves in the Horn of Africa

AbstractClimate change has increased the frequency and severity of weather extremes, including droughts, heat waves and compound drought and heatwave (CDHW) events. CDHW events profoundly impact water availability, agriculture, public health and energy production, particularly in the Horn of Africa (HOA). This study examined the historical spatiotemporal patterns of CDHW periods in the HOA during three periods (1951–1980, 1971–2000 and 1991–2020) using the ERA5 reanalysis dataset. This study utilized monthly Standardized Precipitation Evapotranspiration Index (SPEI) data to detect droughts and daily maximum temperature data to identify heatwaves for characterizing the duration, severity and magnitude of CDHW events. The results show a substantial increase in the duration of CDHW events in recent years, with durations reaching up to 25 days. The average duration of heat waves also increased from 7 days before 1993 to 18 days by 2011, culminating in a record‐breaking 43‐day heat wave in 2019. Most areas experienced a significant increase in heatwave duration by more than 12 days from the early period of 1951–1980 to the late period of 1991–2020. Although around 76% and 69% of the HOA exhibited insignificant heatwave trends in the first two periods, Ethiopia and Kenya experienced substantial increases of more than 18 days during the most recent period, with some durations exceeding 25 days in recent decades. The magnitude of CDHW events generally decreased as drought duration intensified, but specific areas, particularly southwest Kenya and Eritrea, exhibited higher CDHW values in the last period. These findings underscore the urgent need to understand and address CDHW events in the HOA. Targeted interventions for disaster risk reduction and resilience‐building are needed to mitigate the adverse effects of these events in this vulnerable region. This study provides a basis for future research and policy formulation in the HOA.