Meteorological Drought Research Articles

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.

Drought risk in Moldova under global warming and possible crop adaptation strategies.

This study analyzes the relationship between drought processes and crop yields in Moldova, together with the effects of possible future climate change on crops. The severity of drought is analyzed over time in Moldova using the Standard Precipitation Index, the Standardized Precipitation Evapotranspiration Index, and their relationship with crop yields. In addition, rainfall variability and its relationship with crop yields are examined using spectral analysis and squared wavelet coherence. Observed station data (1950-2020 and 1850-2020), ERA5 reanalysis data (1950-2020), and climate model simulations (period 1970-2100) are used. Crop yield data (maize, sunflower, grape), data from experimental plots (wheat), and the Enhanced Vegetation Index from Moderate Resolution Imaging Spectroradiometer satellites were also used. Results show that although the severity of meteorological droughts has decreased in the last 170 years, the impact of precipitation deficits on different crop yields has increased, concurrent with a sharp increase in temperature, which negatively affected crop yields. Annual crops are now more vulnerable to natural rainfall variability and, in years characterized by rainfall deficits, the possibility of reductions in crop yield increases due to sharp increases in temperature. Projections reveal a pessimistic outlook in the absence of adaptation, highlighting the urgency of developing new agricultural management strategies.

A deep learning perspective on meteorological droughts prediction in the Mun River Basin, Thailand

A deep learning perspective on meteorological droughts prediction in the Mun River Basin, Thailand

Enhanced autumn phenology model incorporating agricultural drought

The impacts of various drought types on autumn phenology have yet to be extensively explored. We address the influence of pre-season agricultural and meteorological droughts on autumn phenology in the Northern Hemisphere. To this end, enhanced autumn phenology models incorporating drought factors was developed, contributing to a deeper understanding of these complex interactions. The study reveals that there was no significant trend of advancement or delay in the End of Season (EOS) across the Northern Hemisphere based on SIF estimates from 2001 to 2020. The cumulative and delayed impacts of pre-season agricultural drought on EOS were found to be more pronounced than those associated with meteorological drought. The analysis of various evaluation indexes shows that the performance of the Cooling Degree Days (CDD) model incorporating the Standardized Soil Moisture Drought Index (CDDSSMI) in simulating EOS in the Northern Hemisphere is >14 % higher than that of the standard CDD model. Additionally, the performance of the CDD model with the Standardized Precipitation Index (CDDSPI) in simulating EOS in the Northern Hemisphere is improved by >5.6 % compared to the standard CDD model. A comparison of future EOS projections across various models reveals that the CDD model significantly overestimates EOS in different scenarios (SSP245 and SSP585). The CDDSSMI model projects EOS approximately 7 days earlier than the CDD model, and the CDDSPI model projects EOS approximately 5 days earlier than the CDD model. This study highlights the diverse impacts of drought types on plant autumn phenology and underscores the significance of parameterizing drought impacts in autumn phenology models.

Disentangling the spatially combined and temporally lagged influences of climate oscillations on seasonal droughts in the East Asian monsoon influenced Poyang Lake Basin

Large-scale climate oscillations are the main forcings affecting regional meteorological droughts and being relevant to sources of their predictability. However, the physical mechanism of atmospheric teleconnections with respect to regional droughts is still not fully understood. In this study, a univariate-to-multivariate analysis framework is proposed to disentangle the spatially combined and temporally lagged effects of multiple oceanic-atmospheric oscillations on meteorological droughts at regional scale. Our study focuses on the largest freshwater lake basin of China, the Poyang Lake basin (PLB). Pearson's correlation coefficient and cross-wavelet transform are used to analyze the pair-wise linear and non-linear correlations between droughts and each climate oscillation. Random forests model is used to reveal the combined influences of multiple climate oscillations. The associated atmospheric mechanism for the identified combination of climate indices with changing lags is explored by performing composite analysis. Regarding the spatially combined influences, the concurrence of El Niño-Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO) are the most important drought precursors. Regarding the temporally lagged influences, ENSO with lag of 11 months and NAO with lag of 2–3 months trigger meteorological droughts. The combined effect of preceding winter El Niño and late-summer negative NAO is the primary cause for triggering autumn droughts. The positive Eurasian teleconnection pattern, triggered by ENSO and NAO and favorable for anomalous northerly currents, is the main drought-prone circulation pattern for the PLB. These findings contribute to improved understanding of joint effects of lagged teleconnections for meteorological droughts, which could eventually lead to more skillful seasonal drought forecasting.

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.

Spatio-temporal analysis of meteorological drought return periods in a Mediterranean arid region, the center of Morocco

ABSTRACT Morocco has recently witnessed a surge in drought occurrences, leading to considerable socioeconomic damages. The standardized precipitation index (SPI) at 3- and 12-month timescales was employed to assess spatiotemporal drought characteristics across the Marrakech-Safi arid region. Mann-Kendall and Sen's slope methods were adopted to assess SPI trends. Furthermore, the Gumbel Copula was employed to construct the joint distribution function of three drought variables: duration, severity, and intensity. The spatial distribution of drought return period for different scenarios was carried out. Results revealed notable interannual fluctuations of wet and drought cycles, with the driest years being 1983 and 2005 and a mixture of positive and negative trends of SPI-12 and SPI-3 over the 1972–2018 period. Nevertheless, statistical significance was observed in only 50% of the SPI-12 trends and 27% of the SPI-3 trends. The drought severity in the region was highest in the plain area, with droughts lasting 6–20 months for 75% of all drought events for SPI-12. The coastal strip exhibited the lowest drought recurrences. Furthermore, dry periods exhibited greater temporal variability over shorter timescales. Finally, trivariate return periods of drought events were the longer, averaging 93 months for SPI-12.

Forecasting Meteorological Drought Conditions in South Korea Using a Data-Driven Model with Lagged Global Climate Variability

Drought prediction is crucial for early risk assessment, preventing negative impacts and the timely implementation of mitigation measures for sustainable water management. This study investigated the relationship between climate variations in three seas and the prediction of December meteorological droughts in South Korea, using the Standardized Precipitation Evapotranspiration Index (SPEI). Climate indices with multiple time lags were integrated into multiple linear regression (MLR) and Random Forest (RF) models and evaluated using Pearson’s correlation coefficients (PCCs) and the Root Mean Square Error (RMSE). The results indicated that the MLR model outperformed RF model in the western inland region with a PCC of 0.52 for predicting SPEI-2. On the other hand, the RF model effectively predicted drought states of ‘moderate drought’ or worse (SPEI < −1) nationwide, achieving an average hit rate of 47.17% and Heidke skill score (HSS) of 0.56, particularly excelling in coastal areas. Nino 3.4 turned out to be the most influential factor for short-period extreme droughts (SPEI-2) with a three-month lag, contributed by the Pacific, Atlantic, and Indian Oceans. For periods of four months or longer, climate variations had a lower predictive value. However, integrating autocorrelation functions to account for the previous month’s drought status improved the accuracy. A HYBRID model, which blends linear and nonlinear approaches, further enhanced reliability, making the proposed model more applicable for drought forecasting in neighboring countries and valuable for South Korea’s drought monitoring system to support sustainable water management.

Meteorological drought in the upper Noteć catchment area (Central Poland) in the light of NDVI and SPI indicators

The currently used standardised precipitation index (SPI) does not allow for a reliable assessment of the impact of drought due to the small and unevenly distributed network of meteorological stations. Hopes for developing methods to assess the impact of droughts are pinned on remote data acquisition and the use of analysis of aerial photographs and satellite scenes. The aim of this study is to assess the occurrence of drought based on the normalised difference vegetation index (NDVI) and SPI at multiple time scales (1-, 3-, and 6-, 9- and 12-month). NDVI values do not simply reflect meteorological drought. However, the spatial co-occurrence of meteorological drought with drought defined on the basis of the NDVI index was demonstrated. The study presents a new approach to identifying drought characterized by SPI and NDVI based on the bivariate choropleth map method, which can indicate the actual places of drought occurrence. The study was carried out for the upper Noteć catchment located in Central Poland.

Meteorological Drought Analysis and Regional Frequency Analysis in the Kızılırmak Basin: Creating a Framework for Sustainable Water Resources Management

Drought research is needed to understand the complex nature of drought phenomena and to develop effective management and mitigation strategies accordingly. This study presents a comprehensive regional frequency analysis (RFA) of 12-month meteorological droughts in the Kızılırmak Basin of Turkey using the L-moments approach. For this purpose, monthly precipitation data from 1960 to 2020 obtained from 22 meteorological stations in the basin are used. In the drought analysis, the Standard Precipitation Index (SPI), Z-Score Index (ZSI), China-Z Index (CZI) and Modified China-Z Index (MCZI), which are widely used precipitation-based indices in the literature, are employed. Here, the main objectives of this study are (i) to determine homogeneous regions based on drought, (ii) to identify the best-fit regional frequency distributions, (iii) to estimate the maximum drought intensities for return periods ranging from 5 to 1000 years, and (iv) to obtain drought maps for the selected return periods. The homogeneity test results show that the basin consists of a single homogeneous region according to the drought indices considered here. The best-fit regional frequency distributions for the selected drought indices are identified using L-moment ratio diagrams and ZDIST goodness-of-fit tests. According to the results, the best-fit regional distributions are the Pearson-Type 3 (PE3) for the SPI and ZSI, generalized extreme value (GEV) for the CZI, and generalized logistic distribution (GLO) for the MCZI. The drought maps obtained here can be utilized as a useful tool for estimating the probability of drought at any location across the basin, even without enough data for hydrological research.

Characteristics of groundwater drought and its propagation dynamics with meteorological drought in the Sanjiang Plain, China: Irrigated versus nonirrigated areas

Study regionSanjiang Plain, China Study focusThe characterization of groundwater drought is inadequate, particularly in terms of the differences in the drought propagation dynamics between cropland and other regions. In this study, we identified groundwater drought events and characteristics in the Sanjiang Plain, using the standardized groundwater drought index (SGDI); we also quantified the mechanism of dynamic factors influencing drought propagation characteristics based on the geodetector method and wavelet coherence analysis and discussed the correlation between the NDVI and SGDI.New Hydrological Insights for the Region: The drought propagation time was shorter during summer and longer during spring and autumn in irrigated areas than in nonirrigated areas. The groundwater system exhibited greater resistance to drought during summer, and spatially nonirrigated area was more vulnerable to meteorological drought. The factor that best explained the variation in propagation time and threshold differed across seasons. A significant correlation time-frequency domain existed between all the factors and SGDI in nonirrigated area, with the SGDI exhibiting the fastest response to soil moisture. The relationship between the SGDI and factors was characterized by a discontinuous response of less than 8 months and a continuous response of more than 30 months. The correlations between the SGDI and NDVI in irrigated and nonirrigated area exhibit different changes due to groundwater exploitation and differences in plant physiology between artificial crops and natural vegetation.

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.

The Influence of Dynamical Downscaling and Boundary Layer Selection on Egypt’s Potential Evapotranspiration using a Calibrated Version of the Hargreaves-samani Equation: RegCM4 Approach

Potential Evapotranspiration (PET) is an important variable for monitoring daily agricultural activity as well as meteorological drought. Therefore, it is necessary to investigate the influence of different options of the physical dynamical downscaling and boundary layer schemes on the simulated PET. Using the RegCM4 regional climate model, four simulations were conducted (two for each case) in the period 1997 to 2017. In all simulations, the RegCM4 was configured with 25 km resolution and downscaled by the ERA-Interim reanalysis dataset. To ensure a reliable estimation of the PET, a calibrated version of the Hargreaves-Samani equation was adopted. A high-resolution product of the ERA5 was used as the observational dataset. Results showed that the simulated PET is insensitive either to the dynamical downscaling or the boundary layer options. Concerning the annual climatological cycle, the RegCM4’s performance varies with month and location. Quantitatively, a root mean square error lies between 1 mm and 1.6 mm day-1, the Nash-Sutcliffe efficiency between 0.2 and 0.6, and the coefficient of determination between 0.5 and 0.75. Additionally, the Linear Scaling (LS) method showed its added value in the evaluation/validation periods. In conclusion, the RegCM4 can be used to develop a regional PET map of Egypt using the LS either in the present climate or under different future scenarios.

Detection and Attribution of Meteorological Drought to Anthropogenic Climate Change (Case Study: Ajichay basin, Iran)

Detection and Attribution of Meteorological Drought to Anthropogenic Climate Change (Case Study: Ajichay basin, Iran)

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.

Comparison of three reanalysis‐driven regional climate models over New Zealand: Climatology and extreme events

AbstractThree ~12‐km reanalysis‐driven regional climate models (RCMs) are evaluated in terms of capturing climatologies and extremes of precipitation, temperature and surface wind over Aotearoa/New Zealand (NZ). NZ provides an excellent case study for evaluating high‐resolution RCMs due to its coastal and complex terrain and isolated geographical position in the midlatitudes, exposed to both tropical and polar influences. Overall, we find that the RCMs faithfully reproduce the observed climate, with precipitation and temperature climatologies particularly well‐captured. However, the RCMs display significant differences from observations in capturing the surface wind climatology, highlighting a remaining key challenge. The excess “drizzle problem” is apparent to varying degrees, leading to a weaker representation in the length of meteorological drought in some regions. The RCMs also diverge in reproducing diurnal temperature range which appears partly related to cloud cover. Finally, we discuss the important role of observational uncertainty in the context of model evaluation.

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.

Economic Impact of the Drought in Spain: Measurement for the Adoption of Measures

This paper aims to evaluate the economic implications of meteorological drought in Spain. The study seeks to provide decision-makers with crucial insights into the macroeconomic effects of drought, enabling them to devise mitigation strategies and minimize its impact on economic activity. The Partial Hypothetical Extraction Method (HEM) is employed within the Input-Output analysis framework extended to a Social Accounting Matrix (SAM) of Spain to achieve this goal. The database utilized for this analysis is the FNAM for Spain in 2017, in millions of euros, obtained from the Full International and Global Accounts for Research in Input-Output Analysis (FIGARO) project, a collaboration between Eurostat and the European Commission. The study aims to estimate the economic impact of drought on the productive sectors of the Spanish economy in terms of sectoral production and GDP. This involves simulating the partial reduction in value-added resulting from variations in average water productivity per gross value added, based on the drought indicator SPI-24. Three scenarios are generated: (1) drought, (2) moderate drought and (3) severe drought. In quantitative terms, the simulated drought scenarios could lead to a drop in GDP of 0.88% for the drought scenario, 1.61% for the moderate drought scenario, and 1.76% for the severe drought scenario. Additionally, it is important to recognize that water scarcity hampers the social and economic development of cities and regions beyond the results in quantitative terms.

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.

Assessing the dynamics and trigger factors of drought propagation in the China-Pakistan economic corridor: A three-dimensional perspective

Effectively managing drought in the China-Pakistan Economic Corridor (CPEC) region requires a precise understanding of the three-dimensional characteristics of meteorological drought (MD) and agricultural drought (AD), as well as the factors that trigger their propagation. This study employed non-stationary drought indices (NSPEI and SSMI) to develop a cutting-edge 3-dimensional drought identification model. This model was used to detect MD and AD patterns from 1981 to 2022 in the CPEC region and was integrated with binomial logistic regression to identify the critical factors that drive drought propagation. This study's key findings include: 1) Between 1981 and 2022, droughts in Xinjiang, China, exhibited a discernible southward migration trend, while in Pakistan, droughts showed a northward migration pattern. Drought frequency and extent have increased over time, with affected regions becoming more widespread in CPEC. Notably, drought events with higher preceding drought contagion indices (DCI) were more likely to evolve into extreme, long-term droughts. 2) Drought area emerged as a significant positive triggering factor for drought propagation in the CPEC region. Conversely, snowmelt in Xinjiang and the leaf area index for low vegetation in Pakistan acted as triggering elements affecting negatively. 3) Various factors played a pivotal role during drought propagation process, including geographical coordinates of drought centroids, DCI, and temperature variations. Additionally, snowmelt and snow evaporation significantly impacted drought propagation in Xinjiang, while vegetation cover in Pakistan played a crucial role during the drought propagation process. By utilizing four regression models and conducting comprehensive attribution analysis, this study sheds light on the characteristics of drought propagation and the factors influencing it. These findings are valuable for enhancing early warning systems and implementing effective drought mitigation strategies in the CPEC region.