Hydrological Drought Research Articles

Spatiotemporal analysis of tropical vegetation ecosystems and their responses to multifaceted droughts in Mainland Southeast Asia using satellite-based time series

ABSTRACT Drought ranks among the costliest of all climate-related phenomena and manifests in various forms, posing significant challenges in understanding its influence on agriculture and natural ecosystems. Mainland Southeast Asia (MSEA), a significant region of tropical agriculture and vegetation ecosystems, has become increasingly susceptible to drought hazards. In this study, we characterized and assessed vegetation dynamics and their drought impacts using correlation analysis and explainable machine learning methods under different vegetation types and elevation zones during the dry growing seasons from 2000 to 2022. Specifically, we characterized the vegetation dynamics and their trend in space and time. Next, we assessed vegetation-drought responses in consideration of meteorological, hydrological, and agricultural droughts under different land cover types and elevation characteristics. Lastly, we used an explainable machine learning method to quantify the drivers and impacts of multifaceted droughts on natural and undisturbed vegetation ecosystems. Our findings revealed that nearly 70% of the MSEA region experienced a greening trend despite large areas of vegetative damage during the drought years. Vietnam witnessed increasing vegetation condition in most observed years while the declining trend was mainly found in Cambodia and southern Laos. Vegetation-drought responses showed that tropical vegetation had a high sensitivity to drought conditions, and stronger responses were observed in rainfed crop, mixed forest, and deciduous forest at lower altitude areas. In natural and undisturbed ecosystems, short-term meteorological and agricultural drought disturbances accounted for nearly 93% of variations in tropical vegetation. Among the different examined drought indices, the 3-month Standardized Precipitation Evapotranspiration (SPEI-3) and Temperature Condition Index (TCI) were identified as the factors having the largest influence, together explaining about 55% of the observed natural undisturbed vegetation variations. These findings deepen our understanding of tropical vegetation-drought responses and the underlying drivers of natural and undisturbed ecosystems. Such insights could provide valuable information to assist national and local governments in the MSEA region in developing effective drought management and adaptation programs to safeguard tropical agricultural production and natural ecosystems amidst growing climate challenges.

Hydrological drought assessment of the Sava River basin in South-Eastern Europe

ABSTRACT Hydrological drought poses significant challenges to water resources, ecosystems, and human activities, necessitating comprehensive investigation. Monthly streamflow data from 12 monitoring stations across the Sava River basin were utilized to compute the streamflow drought index (SDI). The Mann–Kendall test evaluated trends, and the SDI's hydrological states were classified based on cumulative streamflow volumes. The study identified an alarming 83.3% of stations exhibiting statistically significant decreases in summer streamflow, indicating a widespread and concerning trend of declining water availability in the Sava River basin. Drought severity was particularly pronounced in tributaries such as the Vrbas and Bosna rivers, emphasizing the heterogeneous nature of hydrological changes. These findings underscore the urgent need for adaptive water resource management strategies in the face of escalating hydrological drought risks, especially given the far-reaching consequences on agriculture, industry, ecosystems, and social well-being. The study provides crucial insights for developing targeted resilience measures tailored to the specific challenges presented by the diverse hydrological conditions in the Sava River basin.

Assessment of dynamic hydrological drought risk from a non‐stationary perspective

AbstractThe stationarity hypothesis of hydrometeorological elements has been questioned in the context of global warming and intense human disturbance. The conventional drought index and methods of frequency analysis may no longer be applicable for hydrological drought risk evaluation under a changing environment. In this study, a new dynamic hydrological drought risk evaluation framework is proposed for application to the Hanjiang River basin (HRB), which simultaneously considers the non‐stationarity in the construction of drought index as well as in the frequency analysis. First, a non‐stationary standardized runoff index (NSRI) is developed using a generalized additive model for location, scale and shape (GAMLSS) framework. Then, hydrological drought characteristics including duration and severity are identified, and their marginal distributions are established. Finally, based on the dynamic copula, considering the non‐stationarity of the dependence structure, the dynamic joint probability distribution, conditional probability distribution and return period of the bivariate hydrological drought properties are analysed. Results showed that NSRI, which integrates the impacts of climate change and anthropogenic activities on the non‐stationarity of runoff series, had a better ability to capture runoff extremes than had SRI. In addition, it is indispensable to consider the non‐stationarity of the dependence structure between variables when discussing the multivariate joint risk of hydrological drought. The risk of hydrological drought in the study area has shown an increasing trend in the past 65 years, and the drought conditions from upstream to downstream have been alleviated first and then intensified. This study provides valuable information for regional drought risk estimation and water resources management from a non‐stationary perspective.

Separating the impact of climate change and human activities on the connection between meteorological and hydrological drought

AbstractUnderstanding the transition from meteorological to hydrological drought is essential for accurately predicting hydrological droughts. However, the factors driving this transition are intricate, and a comprehensive understanding of how direct human activities influence this shift in drought is lacking. In this study, we initially explored the spatiotemporal correlation between the occurrence of meteorological and hydrological droughts. Subsequently, we formulated multiple hydrological replenishment scenarios using the soil and water assessment tool (SWAT) model to assess the environmental impact of the transition from meteorological to hydrological droughts. The Xijiang River Basin (XRB), the primary tributary of the Pearl River basin, was selected as the study area. Our results identified 91 meteorological droughts in the XRB, and only 66 hydrological droughts from 1978 to 2018. The transition rate from meteorological to hydrological drought demonstrated large spatial variability, with a basin‐average rate of 56% and the lowest transition rate of 45% in the headstream The transition from meteorological to hydrological drought was mostly rapid between November and December (~2 months), but can be prolonged during spring (about 3–5 months) and winter (around 7–9 months). Additionally, analysis of regeneration scenarios indicated that human activity has mitigated drought severity over recent decades. The primary driver affecting drought duration and frequency during the transition from meteorological to hydrological droughts shows conspicuous spatial disparities in densely populated areas. Although human activity significantly contributes to drought duration and severity compared to climate change during the transition in the headstream, its effects are more pronounced downstream in terms of drought duration and frequency. One plausible explanation is that increased water consumption downstream has considerably prolonged drought progression, whereas water management has counteractive effects on drought progression due to climate change in the headstream. Our findings offer valuable insights into the transition process from meteorological to hydrological droughts in the presence of extensive human activities.

Semi-arid rather than arid regions of China deserve the priority in drought mitigation efforts

The integration of drought assessment, mitigation priority analysis and mitigation measures development is a forward-looking strategy to achieve water resources allocation, implement anti-drought techniques and formulate corresponding mitigation measures strategies. However, since most drought indices cannot be based on surface water-balance to estimate water demand for drought recovery, there is a gap between drought assessment and proactive drought mitigation. Here, we established the Standardized Water Availability Index (taking water yield as surface water deficit/surplus) to identify hydrological drought, and further use it to determine the water demand for hydrological drought mitigation. On that basis, a comprehensive framework, integrating with drought assessment-resilience-recovery and water scarcity stress, was proposed to investigate the hydrological drought mitigation priority for basins in different climate regions in China. The results show that non-humid river basins have greater water scarcity stress, lower resilience to hydrological drought, but less water demand for hydrological drought mitigation (3 mm ∼ 7 mm in mild drought, 5 mm ∼ 14 mm in moderate drought, 7 mm ∼ 21 mm in severe drought). In contrast, humid river basins have greater water demand for hydrological drought mitigation (15 mm ∼ 49 mm in mild drought, 27 mm ∼ 93 mm in moderate drought, 32 mm ∼ 119 mm in severe drought), but higher resilience to hydrological drought. The densely populated semi-arid river basins in China should be given priority attention in mitigating hydrological drought on account of their greatest water scarcity stress, lower drought resilience, and less water demand for drought mitigation. This work highlights the complexity of the hydrological drought mitigation, and our findings can help stakeholders to make precise drought mitigation measures and adapt drought-relative water management.

Drought Characterization With GPS: Insights Into Groundwater and Surface‐Reservoir Storage in California

AbstractDrought intensity is commonly characterized using meteorologically‐based metrics that do not provide insight into water deficits within deeper hydrologic systems. In contrast, global positioning system (GPS) displacements are sensitive to both local and regional hydrologic‐storage fluctuations. While a few studies have leveraged this sensitivity to produce geodetic drought indices, hydrologic drought characterization using GPS is not commonly accounted for in drought assessment and management. To motivate this application, we produce a new geodetic drought index (GDI) and quantify its ability to characterize hydrologic drought conditions in key surface and sub‐surface hydrologic reservoirs/pools across California. In northern California, the GDI exhibits a strong regional association with surface‐reservoir storage at the 1‐month time scale (correlation coefficient: 0.83) and groundwater levels at the 3‐month time scale (correlation coefficient: 0.87), along with moderate associations with stream discharge at the daily (instantaneous) time scale (correlation coefficient: 0.50). Groundwater in southern California is best characterized with a 12‐month GDI (correlation coefficient: 0.77), and surface‐reservoir storage is optimized with the 3‐month GDI (correlation coefficient: 0.72). Two sigma uncertainties are ±0.03. Differences between northern and southern California reveal that the GDI is sensitive to unique aquifer and drainage basin characteristics. In addition to capturing long‐term hydrologic trends, rapid changes in the GDI initiate during clusters of large atmospheric river events that closely mirror fluctuations in traditional hydrologic and meteorological observations. We show that GPS‐based hydrologic drought indices provide a significant opportunity to improve drought assessment, in California and beyond, by improving our understanding of the hydrologic cycle.

The changing characteristics of propagation time from meteorological drought to hydrological drought in a semi‐arid river basin in India

AbstractThis study employs an event‐based approach to analyse drought propagation from meteorological to hydrological drought via agricultural drought in the semi‐arid Krishna River basin of India. The Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Soil Moisture Index (SSMI) and Standardized Streamflow Index (SSI) representing meteorological, agricultural and hydrological drought, respectively, were estimated. Two different cases of drought propagation are analysed: meteorological‐to‐agricultural (SPEI‐to‐SSMI) and agricultural‐to‐hydrological (SSMI‐to‐SSI). The drought propagation is analysed using three‐time matrices, namely the time difference between initiation (), peak () and termination () at multiple timescales of 1, 3, 6, 9 and 12 months using different drought threshold values 0, −0.5, −1 and − 1.5, respectively, to delineate shifts from mild to extreme drought conditions in detail. The results indicate that the propagation time from SPEI‐to‐SSMI drought decreased for most of the tributaries using multiple timescales at different threshold values, whereas it increased significantly for SSMI‐to‐SSI drought. The drought propagation changes with respect to time as well as magnitude (intensity and severity). The propagation factor (PF), defined as the ratio of the average value of succeeding drought to preceding drought characteristics, has also been studied. For SPEI‐to‐SSMI drought, the duration PF shrinks across all tributaries using multiple timescales at different threshold values, whereas it expands for SSMI‐to‐SSI drought. On the other hand, the severity and intensity PF magnify for SPEI‐to‐SSMI drought, whereas it experiences dampening effects for SSMI‐to‐SSI drought. Thus, the proposed study provides valuable insights into drought propagation dynamics, aiding in managing and mitigating droughts in the semi‐arid river basin and elsewhere.

Escalating Wildfires in Siberia Driven by Climate Feedbacks Under a Warming Arctic in the 21st Century

AbstractSiberian wildfire is of paramount importance in the carbon cycle and climate change as it is a major disturbance in the pan‐Arctic ecosystems. In recent decades, the Siberian wildfire regime has been shifting; however, less is known about its process‐based feedback mechanisms. By integrating in‐situ and satellite observational data sets as well as chemistry‐climate coupled modeling, we find that central Siberia has featured the most prominent wildfire escalation during the past two decades, which is closely related to hydrological drought with decreasing rainfall and drying soil under a fast‐warming Arctic. Furthermore, fire‐emitted aerosols compound the increasing wildfires via serving as cloud condensation nuclei and suppressing precipitation, forming self‐amplifying feedback. As the Arctic warming is projected to continue, wildfires are estimated to more than double by the end of this century. This work highlights the great importance of fire risk management based on a fundamental scientific understanding of the complex climate system.

Identifying regional hotspots of heatwaves, droughts, floods, and their co-occurrences

In this paper we present a framework to aid in the selection of optimal environmental indicators for detecting and mapping extreme events and analyzing trends in heatwaves, meteorological and hydrological droughts, floods, and their compound occurrence. The framework uses temperature, precipitation, river discharge, and derived climate indices to characterize the spatial distribution of hazard intensity, frequency, duration, co-occurrence, and dependence. The relevant climate indices applied are Standardized Precipitation Index, Standardized Precipitation and Evapotranspiration Index (SPEI), Standardized Streamflow Index, heatwave indices based on fixed (HWIS\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_\ extrm{S}$$\\end{document}) and anomalous temperatures (HWIE\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_\ extrm{E}$$\\end{document}), and Daily Flood Index (DFI). We selected suitable environmental indicators and corresponding thresholds for each hazard based on estimated extreme event detection performance using receiver operating characteristics (ROC), area under curve (AUC), and accuracy, which is defined as the proportion of correct detections. We assessed compound hazard dependence using a Likelihood Multiplication Factor (LMF). We tested the framework for the case of Sweden, using daily data for the period 1922–2021. The ROC results showed that HWIS\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_\ extrm{S}$$\\end{document}, SPEI12 and DFI are suitable indices for representing heatwaves, droughts, and floods, respectively (AUC > 0.83). Application of these indices revealed increasing heatwave and flood occurrence in large areas of Sweden, but no significant change trend for droughts. Hotspots with LMF > 1, mostly concentrated in Northern Sweden from June to August, indicated that compound drought-heatwave and drought-flood events are positively correlated in those areas, which can exacerbate their impacts. The novel framework presented here adds to existing hydroclimatic hazard research by (1) using local data and historical records of extremes to validate indicator-based hazard hotspots, (2) evaluating compound hazards at regional scale, (3) being transferable and streamlined, (4) attaining satisfactory performance for indicator-based hazard detection as demonstrated by the ROC method, and (5) being generalizable to various hazard types.

Evolution Characteristics of Meteorological and Hydrological Drought in an Arid Oasis of Northwest China

In the context of global warming, the acceleration of the water cycle increases the risk of meteorological drought (MD) and hydrological drought (HD) in the arid region of Northwest China. The Manas River Basin is a typical agricultural oasis and the largest oasis farming area in Xinjiang, Northwest China. Droughts in this basin have significant implications for both agricultural production and the livelihoods of inhabitants. To evaluate the MD and HD and provide information for drought relief in the MRB, the standardized precipitation evapotranspiration index (SPEI) and standardized runoff index (SRI) were calculated using long-term rainfall and runoff data. Subsequently, combined with ArcGIS 10.3 software and the trend analysis method, the SPEI and SRI characteristics were evaluated at different time scales (1-, 3-, 6-, and 12-month). There were three main findings. First, both MD and HD were alleviated, with significantly more HD alleviation. MDs in spring and autumn exhibited a trend of aggravation. The SRIs in summer, autumn, and winter increased significantly at a confidence level of p < 0.01, with an insignificant decline in spring. In the 2010s, the frequency of light drought of MD was stable at 10% to 20%, while severe and extreme droughts increased. The frequency of HDs has decreased since the 1990s. Second, on annual and seasonal scales, MDs occurred mainly as light and moderate droughts. The highest frequency of MD was 24% of moderate droughts in winter. Spatially, the northern region of the MRB was characterized by more frequent light and extreme droughts. Third, runoff in the Manas River Basin increased significantly during the 1990s, which may have been related to the acceleration of glacial retreat in the Tianshan Mountains. This study can effectively reveal the changes in meteorological and hydrological drought in NWC and provide the basis for risk decision-making and management for watershed managers.

Evaluating the spatiotemporal dynamics of driving factors for multiple drought types in different climate regions of China

Extreme weather events and natural hazards are increasingly prevalent with global warming, making it imperative to focus on the driving factors and dynamic changes associated with drought—a disaster with widespread impacts and significant losses. This study used a longtime-series of ERA5 reanalysis data to elucidate the dynamic change characteristics of direct and indirect driving factors across China. Ground observation data spanning an extended period were used to estimate the performance of the reanalysis data. The selected driving factors for drought included precipitation (PRE), potential evapotranspiration, soil moisture (SM), bare soil evapotranspiration (BSET), vegetation canopy evapotranspiration (VCET), subsurface runoff (SUBRO), surface runoff (SURRO), temperature (TEM), specific humidity, and near-surface wind speed (WS). Meteorological drought, hydrological drought, and agricultural drought were delineated using the Standardized Precipitation Evapotranspiration Index, Standardized Runoff Index, and Standardized Soil Moisture Index. The Random Forest method was used to ascertain the relative importance of driving factors and their main contributions to different types of droughts. The findings revealed that ERA5 exhibited great simulation performance compared to observational data. However, the correlation coefficient of SM might be relatively lower than that of other driving factors across China. Notably, BSET and PRE exhibited higher relative importance degrees (RID) for meteorological drought in subregions 1, 2, and 3. At the same time, SUBRO demonstrated a more statistically significant influence in subregions 3, 4, and 5. SURRO played a statistically significant role in subregion 1. Moreover, BSET and PRE were pivotal for meteorological drought in northern China, whereas VCET assumes importance for hydrological drought in southern China and the North China Plain. Across different types of droughts, PRE, SM, and TEM generally exhibited relatively large RID values in China. The dynamic changes in RID for both direct and indirect driving factors varied for different drought types across different subregions of China. Notably, the RID displayed contrasting dynamic changes between PRE and BSET for meteorological drought in most subregions. Additionally, the degree of relative importance of near-surface WS tended to be lower for hydrological drought across various subregions. This study contributed to a deeper understanding of drought evolution and enhanced monitoring efforts.

Unraveling the hydropower vulnerability to drought in the United States

Abstract Drought, a potent natural climatic phenomenon, significantly challenges hydropower systems, bearing adverse consequences for economies, societies, and the environment. This study delves into the profound impact of drought on hydropower generation (HG) in the United States, revealing a robust correlation between hydrologic drought and hydroelectricity generation. Our analysis of the period from 2003 to 2020 for the Contiguous United States (CONUS) indicates that drought events led to a considerable decline in hydroelectricity generation, amounting to approximately 300 million MWh, and resulting in an estimated loss of $28 billion to the sector. Moreover, our findings highlight the adverse environmental effect of drought-induced HG reductions, which are often compensated by increased reliance on natural gas usage, which led to substantial emissions of carbon dioxide (CO2), sulfur dioxide (SO2), and nitrogen oxide (NO X ), totaling 161 700 kilotons, 1199 tons, and 181 977 tons, respectively. In addition to these findings, we assess the state-level vulnerability of hydropower to drought, identifying Washington and California as the most vulnerable states, while Nevada exhibits the least vulnerability. Overall, this study enhances understanding of the multifaceted effects of drought on hydropower, which can assist in informing policies and practices related to drought management and energy production.

Trends of meteorological and hydrological droughts and associated parameters using innovative approaches

Climate change and drought have profound effects on hydro-meteorological series. In addition to spatial, these effects could be on annual, seasonal, monthly, or daily temporal scales. In the literature, seasonal Mann-Kendall and Kendall Tau, Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and Standardized Runoff Index are mostly used to detect seasonal effects (autumn, winter, spring, and summer), despite some restrictive assumption. Innovative Polygon Trend Analysis (IPTA) method developed from Innovative Trend Analysis (ITA) analyzes monthly effects on hydro-meteorological variables without restrictive assumptions. In this study, the IPTA method is revised and developed as Periodic Innovative Polygon Trend analysis (P-IPTA) to analyze hydro-meteorological series in periods of 1, 3, 6, 9, and 12 months instead of one-month duration. The method turns to the IPTA for one-month evaluations. Also, ITA method is improved by adding the frequencies for each drought classification (F-ITA). For the precipitation and water availability (Istanbul, Türkiye) and stream flow (Danube River, Romania) series, the P-IPTA method has been used in addition to the SPI, SPEI, and SDI methods to detect the trends in meteorological and hydrological droughts, and their associated parameters. There are generally decreasing trends, increasing drought frequencies, and decreasing wet event frequencies in the study areas. As the period lengths of the hydro-meteorological series increase, drought becomes more evident. Unlike these methods, the method results are consistent with the F-ITA SPI, SPEI, and SDI graphs and can give drought and wet periods. Similarly, the new P-IPTA method will enable researchers to investigate seasonal effects not only on hydro-meteorological series but also on any variable.

Probability-Based Propagation Characteristics from Meteorological to Hydrological Drought and Their Dynamics in the Wei River Basin, China

Understanding the propagation characteristics and driving factors from meteorological drought to hydrological drought is essential for alleviating drought and for early warning systems regarding drought. This study focused on the Weihe River basin (WRB) and its two subregions (the Jinghe River (JRB) and the middle reaches of the Weihe River (MWRB)), utilizing the Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI) to characterize meteorological and hydrological drought, respectively. Based on Copula theory and conditional probability, a quantification model for the propagation time (PT) of meteorological–hydrological drought was constructed. The dynamic characteristics of PT on annual and seasonal scales were explored. Additionally, the influences of different seasonal meteorological factors and underlying surface factors on the dynamic changes in PT were analyzed. The main conclusions were as follows: (1) The PT of meteorological–hydrological drought was characterized by faster propagation during the hot months (June–September) and slower propagation during the cold months (December to March of the following year); (2) Under the same level of hydrological drought, as the level of meteorological drought increases, the PT of the drought shortens. The propagation thresholds of meteorological to hydrological drought in the WRB, the JRB, and the MWRB are −0.69, −0.81, and −0.78, respectively. (3) In the dynamic changes in PT, the WRB showed a non-significant decrease; however, both the JRB and the MWRB exhibited a significant increase in PT across different drought levels. (4) The influence of the water and heat status during spring, summer, and winter on PT was more pronounced, while in autumn, the impact of the basin’s water storage and discharge status was more significant in the JRB and the MWRB.

Study of Drought Using the Theory of Run and Hydrological Drought Index and its Relationship to Reservoir Storage at the Batubai Dam and Pengga Dam

Drought is a frequent disaster in Indonesia, particularly in areas with long dry seasons. Several factors influencing drought in Indonesia include irregular rainfall patterns, climate change, and unsustainable water resource usage. This study was conducted to provide an overview of drought and its impact on the storage of the Batujai Dam and Pengga Dam. This research utilizes drought analysis and reservoir simulation analysis. The results of this study are as follows: a) The drought condition at the Batujai Dam based on the Theory of Run method has a maximum deficit value of -644.66 mm, and the drought based on the Hydrological Drought Index using inflow data from 2013 to 2022 has a maximum deficit value of -2.88 m³/s. Meanwhile, the drought condition at the Pengga Dam based on the Theory of Run method has a maximum deficit value of -407.86 mm, and the drought based on the Hydrological Drought Index using inflow data has a maximum deficit value of -2.371 m³/s. b) The impact of drought on the simulation of the Batujai Dam and Pengga Dam over specific periods shows that the Batujai Dam was full (overflowing) for 7 dekadal periods, whereas under existing conditions, it was never full. The Pengga Dam was full (overflowing) for 6 dekadal periods, while under existing conditions, it was only full once, with a K Factor (ratio of water supply to water demand) having a minimum value of 20% from October I to October III, 2018.

Drought risk in the Mahanadi River basin: a multi-dimensional approach for integrated urban-rural drought management strategies

ABSTRACT Droughts are one of the most spatially complex geohazards, having a significant impact on the economic status of any region. To mitigate drought risks, a comprehensive drought management plan is required, and the first step towards that goal is to assess the various aspects of drought risks in the preparation of a drought risk map. To produce an integrated drought risk map for Mahanadi River basin, India, the current study combines geospatial methodologies with the Analytical Hierarchy Process (AHP) technique to assess various dimensions, viz. hydrological, meteorological, agricultural and socio-economic drought risk in the region in view of integrated rural-urban management strategies. A total of 17 criteria from different aspects were taken into consideration in different groups. The results showed that districts like Raipur, Bilaspur, Durg and Ragnandgaon faced extreme drought conditions combining assessments of agriculture, water resources, socioeconomic factors and weather patterns, reveals varying levels of risk across the region. According to the findings, 22.01% of the region is vulnerable to extreme drought and 31.64% of the area is suffering from severe drought. The results indicate that the technique used for identifying the region's susceptibility to drought is effective, which will help planners develop strategies for mitigating drought.

Differences in drought characteristics, progression, and recession across ecosystem types in the pantropical region of the Lancang-Mekong River Basin

Exploring the development and impacts of drought across different ecosystems can offer new insights for mitigating the adverse effects of drought events. Using the pantropical Lancang-Mekong River Basin as the study region, we investigated the agricultural, ecological, and hydrological drought characteristics and explored their drought progression and recession rates across four vegetation ecosystem types: tropical forests, subtropical forests, shrubs, and crops. We utilized newly developed drought indices based on the ERA5-Land reanalysis dataset, GOSIF chlorophyll fluorescence data, and modified Moderate Resolution Imaging Spectroradiometer (MODIS) land cover data. The results showed that agricultural and hydrological droughts exhibited increasing trends from 2001 to 2021, whereas ecological drought displayed a decreasing trend over the same period. The cropland region experienced the fewest drought events, shortest drought durations, slowest progression rates, and lowest recession rates. By contrast, the two evergreen, broadleaf forest ecosystems (subtropical and tropical forests) experienced the highest number of drought events and fastest progression and recession rates. The findings suggest a trade-off relationship between vegetation resistance and recovery, where faster drought onset is associated with faster drought recession for ecological drought. Given the more severe challenges posed by agricultural and hydrological droughts, the riparian countries in the Lancang-Mekong River Basin should adopt proactive financial and management measures to mitigate the adverse impacts of these drought types. The insights gained from this study can inform the development of targeted strategies for drought monitoring, preparedness, and response across diverse ecosystems.

Comprehensive evaluation of the response relationship between meteorological drought and hydrological drought in the Yalong River Basin, China

Extreme climate events are becoming increasingly severe owing to global warming. In recent years, the Yalong River has experienced frequent droughts, which has seriously hindered the development of hydropower. Based on standardized precipitation evapotranspiration index (SPEI) and standardized runoff index (SRI) values, this study employed transfer entropy, multivariate Copula functions, and a cloud model to study the response relationship and risk situation between meteorological and hydrological droughts. The results showed that: (1) The smaller the scale of SPEI and SRI, the more sensitive the identification of drought and the faster the detection of drought trend changes. (2) Combined with small-scale drought index analyses, the trend and severity of meteorological and hydrological droughts propagating from the upper and middle reaches to the lower reaches is increasing from year to year. (3) The Gumbel-Hougaard Copula function reveals the relationship between meteorological and hydrological drought, with the longest joint return period of 13–15 months. (4) In cloud model risk evaluation, the degree, uncertainty and stochasticity of drought risk in the basin are increasing, and the risk degree of interannual meteorological and seasonal hydrological droughts in the basin was high. This study provides theoretical support for optimizing water resource allocation and drought risk situation analysis in the basin.

Assessing drought in Turkish basins through satellite observations

AbstractDrought occurs when there is a sustained decrease in rainfall over an extended period, impacting the socio‐cultural and environmental aspects of humans and other living beings. The geographic distribution and timing of droughts play a crucial role in drought management and mitigation strategies. Identifying and predicting the onset of droughts in specific regions, especially in watershed areas, is a primary concern in the field of hydrology. This study focuses on how the spatiotemporal patterns of drought are developing in Turkish Basins using detailed data on Terrestrial Water Storage (TWS), precipitation, and temperature at the pixel level. GRACE (Gravity Recovery and Climate Experiment), PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks), and WorldClim (World Climate) data sets are employed to assess long‐term changes of drought on a basin‐scale. Spatial analyses are conducted in a Geographic Information System (GIS) environment for the derivation of basinal monthly mean, minimum, and maximum statistics of TWS, precipitation, and temperature anomalies within Turkish Basins. Time series analyses are implemented to investigate the temporal evolution of droughts in these basins, for the basinal monthly mean, minimum, and maximum statistics obtained. The Mann–Kendall trend test and Pettitt change point detection tests are used to assess the statistical significance of the calculated trends and to expose the existence of any change point therein, respectively. The findings of the study indicate that Turkiye faces a significant risk of drought development in nearly all its basins, particularly after 2016. The GRACE dataset provides realistic insights into the temporal behaviour of hydrological droughts. PERSIANN is effective in identifying years with extreme meteorological conditions, and the standardized precipitation index (SPI) shows similar effectiveness, while they are ineffective in exposing significant trends due to the nature of the precipitation data. WorldClim data proves insufficient for modelling the temporal behaviour of droughts in these basins.

A grid-wise approach for accurate computation of Standardized Runoff Index (SRI)

The Standardized Runoff Index (SRI) is a major indicator for evaluating hydrological drought conditions, accomplished by comparing the current runoff data with retrospective runoff conditions of an area for the same period. This hydrological drought indicator facilitates the characterisation of runoff variations across diverse regions. This study introduces a refined methodology for accurate computation of SRI by employing a grid-wise approach. Distinct probability distributions were fitted to each grid within the study area, diverging from the conventional practice of using a single probability distribution for the entire basin or sub-basin. The research endeavours to assess the efficacy of the grid-wise approach in improving the representation of drought characteristics when compared to the traditional areal approach. A comparative analysis between the performances of SRI computed through grid-wise fitting (where the probability distribution dynamically adapts to each grid) and the areal fitting approach (employing a uniform distribution across all grids) was conducted within the Godavari Basin, India. The findings in this study underscore that the misrepresentation of extreme events is inevitable for large heterogeneous basins like Godavari when the traditional areal approach was employed for SRI computation. Consequently, the grid-wise fitting emerges as a more accurate method for computing the SRI, particularly in characterising extreme dry or wet events.