Drought Return Periods Research Articles

Which droughts are becoming more frequent? A copula entropy analysis on the return period of droughts in Europe

AbstractClimate change and global warming have increased the frequency of extreme events, particularly over the past decades. Changes in drought frequency are not yet understood, especially regarding which drought features are becoming more frequent (e.g., are longer or high-magnitude droughts becoming more frequent, or both?). In this study, we present a novel methodology to accurately and consistently estimate changes in return periods of different types of droughts. For this purpose, we implemented copula-entropy theory to assess drought frequencies and their changes. As an example of the application of the proposed method, we used data from the European Climate Assessment and Dataset (ECA&D), from which we selected 26 stations in Central Europe with over 100 years of data and low incidence of missing days ($$\le$$ ≤ 0.3%). The results of the new analysis indicate that there was a high variability in the frequency change patterns across Central Europe over the last century; however, most regions have experienced an increase in the frequency of medium-to-high intensity droughts. The use of the copula-entropy theory to assess drought frequency is a reliable method that allows systematic monitoring and easy updating of current knowledge, and is computationally efficient and statistically robust.

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.

Long-Term Seasonal and Annual Rainfall Trend Analysis of Giridih District, Jharkhand, India

District Giridih is primarily rain dependent on its 95 per cent net cultivable land under summer-monsoon crops. It is classified as a mono-cropping area as it lacks irrigation facilities, essential for winter crops. In the last few years, the district experienced water stress due to the shortage of monsoon rainfall. We study long term seasonal and annual rainfall trend analyses for the Giridih district of Jharkhand in India using linear regression modelling. The last 100 years of data were taken for the study and were divided into two-time phases of 50 years each to analyse the changing pattern of rainfall trends. We found a decreasing trend in monsoon rainfall from 1 mm y-1 to 3 mm y-1 between the initial (1921-1971) and final (1972-2021) phase of the study period. Similarly, the return period of droughts (rainfall deficit years) has also reduced from 11 years to 5 years. The study has shown that the rainfall pattern has changed, with the winter months showing a decrease and the pre-monsoon months an increase in their relative contributions to the annual rainfalls. The study may help in the formulation of water resource conservation-oriented decision-making to cope-up with the rainfall uncertainties and meet the future water demand.

Anthropogenic and atmospheric variability intensifies flash drought episodes in South Asia

Flash droughts are abrupt and rapid intensification of droughts that affect agriculture, water, and ecosystems and are commonplace in South Asia. Despite their potential impact, flash drought evolution characteristics and underlying mechanisms in South Asia remain underexplored. We use a multivariate approach to analyze the onset speed, frequency, severity, duration, and return period of flash droughts, and the role of atmospheric circulation and human-induced climate change. We find that flash droughts are more common and intense in the crop season, especially in central India, western Pakistan, and eastern Afghanistan. They are caused by persistent atmospheric patterns that block moisture transport to South Asia. Additionally, anthropogenic climate change has intensified flash droughts in the spring-summer season, with a median fraction of attributable risk of 60%, 80%, and 90% for Afghanistan, Pakistan, and India, respectively. Our results suggest that flash droughts will expand and worsen in the future, requiring adaptation measures for the water, agriculture, and energy sectors.

Climate Change Impact Assessment and Disaster Risk Financing Strategies in Mali: A Comprehensive Analysis of Drought and Flood Events

Climate change impact increasingly led to humanitarian assistance increase and needed. To better address climate change impacts mitigation, a suitable financing instrument is essential to facilitate government, humanitarian, and other stakeholders' finance mobilization. However, few studies have been done on disaster risk profiling to guide decision-makers in their choices. Disaster risk profile analysis has been conducted in Mali to facilitate financial resources mobilization and climate finance instrument choice by identifying Historical drought and flood events. To do so, published papers; and some international institution websites dealing with climate hazard events such as Reliefweb, Hazard/risk, climate information services, Relief Web; CRED- EM-DAT; World Bank Climate Knowledge Portal, World Bank- UNDRR -ThinkHazard, WFP ARC/GeoNode/VAM/DataViz addressing Mali country have been assimilated for evidence accumulation and synthesis and presented in a database. Furthermore, national statistics and national reports on hazards have been also reviewed. Before starting the reading exercise, a reading/analytical framework has been elaborated. In Mali the year 1984 to 2019, 21 flood events occurred in Mali and the most exposed regions to floods are Koulikoro, Bamako and Gao. From 1969 to 2020, 21 drought events were registered in in Mali and the most affected regions are Koulikoro, Mopti, Gao, Kayes. The time return period of drought has been estimated to 3 years while the time return of flood has been estimated to be about 2 years. Drought events are less frequent than flood events, however, drought events affect more population than floods. Also, Also, the yearly response cost for drought events is USD million 277.46 with an average US USD 204.37 cost per affected population. For the flood, even the yearly response cost is USD 11.107 million With USD 261.82 per affected population. Macro-insurance and CAT bonds are more suitable disaster risk financing instruments and are recommended to better address drought events while Anticipatory action and government contingency funds are more suitable climate disaster risk financing instruments to better address flood events in Mali.

Analysing spatio-temporal drought characteristics and copula-based return period in Indian Gangetic Basin (1901-2021).

Uncertainty and uneven distribution of monsoonal rainfall and its consequences on crop production is a matter of serious concern in India, specifically, in theIndo-Gangetic plainregion. In this study, drought patterns were investigated through standardised precipitation index (SPI) of varying timescales, using the India Meteorological Department (IMD) precipitation data (1901-2021). We analysed the spatio-temporal pattern of different drought characteristics (frequency, duration, severity, intensity) of the Indian Gangetic basin using run theory. The bivariate copula method has been incorporated to combine two drought properties (severity and duration). Copula integrates multivariate distribution and considers the dependency rate among the variables. The five most widely used copulas from various copula families, elliptical (normal, t-copula) and Archimedean (Clayton, Gumbel, Frank), were estimated for modelling, and the best fit copula was selected. The study revealed that seasonal drought is more frequent and intense in the Upper and Middle Gangetic Plain, whereas annual drought is quite scattered in nature. It is worthy to mention that downward drought trends were observed in this agricultural belts significantly after 1965; specifically, in the Upper, Middle, and Trans Gangetic Plain regions. With increasing drought duration and severity, the drought return period raised, but the frequency decreased gradually. Most of the droughts characterised by less duration and severity occurred with a return period below 10years for the whole region. The major 100 + years return period droughts were to be found after 1960 and their frequencies were significantly higher after 2000. The most recent remarkable droughts with more than 100years of return occurred during 2008-2011 and 2016-2018 in the Upper and Middle Gangetic plains, whereas in the Lower Gangetic plain, a hundred-year return period drought was occurred during 2010-2013. This study provides agroclimatic-zones-wise significant information of drought characteristics and its nature of occurrence in the Indian Ganga Basin. The results enhance the understanding of drought management and formulation of adaptive strategies to mitigate the adverse impact of droughts.

Bivariate regional drought frequency analysis using multivariate approaches: a case study in southwestern Iran

Abstract Bivariate approaches in Regional Frequency Analysis (RFA) address two issues: first, to evaluate the homogeneity of regions, and second, to estimate the joint return periods. This study was conducted to investigate the joint return period of a severe historical drought in southwestern Iran. Fifty-nine rain gauges were first clustered into three, four, and five regions using the fuzzy c-means clustering (FCM) algorithm. Then bivariate discordancy and homogeneity tests were applied to adjust the initial clusters. The results showed that only in the case of three clusters were all the regions homogeneous. Therefore, it can be inferred that combining clustering analysis and discordancy test is insufficient to form homogeneous regions. Finally, the joint return period, by choosing Generalized Logistic and Wakeby as marginal distributions and Clayton as a copula, was estimated for all the sites in the three regions. Since no three-parameter distribution function fitted well to the variable severity, the bivariate homogeneity index does not necessarily attest to region homogeneity regarding the marginal distribution functions. It is also deduced that sites with higher mean annual precipiataion (MAP) and, correspondingly, higher elevation are more likely to experience shorter return periods of same drought events, in contrast to sites with lower MAP or lower elevation.

Spatiotemporal Variation in the Meteorological Drought Comprehensive Index in the Beijing–Tianjin–Hebei Region during 1961–2023

It is crucial to investigate the characteristics of meteorological drought in the Beijing–Tianjin–Hebei (BTH) region to improve the accuracy of agriculture and water resource monitoring and management. In this study, using instrumental observation data from 85 meteorological stations in the BTH region during 1961–2023 derived from the National Meteorological Information Center, we first calculated the meteorological drought comprehensive index (MCI) and analyzed the spatiotemporal characteristics of the MCI. In the BTH region, the MCI intensity from May to June was the most severe in the intraseasonal variation. The trend of the decreasing drought intensity in May–June has occurred for the past 60 years. The southern region in the BTH region was more likely to experience droughts. Next, the spatial patterns of the top two EOF modes of the May–June MCI were depicted. The primary spatial pattern of the BTH, which was characterized by consistent changes in the MCI throughout the entire BTH region, could be represented by the first mode’s R2 of 69.01%. Then, we compared the spatial pattern of the MCI intensity under different return periods. Using the May–June MCI of 1961–2023, the drought intensity gradually increased from northwest to southeast for the 10-, 20-, and 50-year return periods. However, the drought intensity decreased and then increased from northwest to southeast based on the 1991–2023 MCI. Notably, a 20-year return period of severe drought affected Beijing and northern Hebei in 2023. Finally, we discussed the linkages of drought in the BTH region and atmospheric circulation/sea surface temperature (SST) anomalies, which were calculated using the Pearson correlation coefficient and wavelet coherence. We suggest that the MCI variations in the BTH region may be related to the SST anomalies of the Indian Ocean in 1961–1990 and the Pacific Ocean in 1991–2023, respectively. The abovementioned studies have enlightened us to focus on predicting the Pacific SST for drought, which will facilitate agricultural production and water resource management in the BTH region.

Quantifying Drought Characteristics in Complex Climate and Scarce Data Regions of Afghanistan

Droughts cause critical and major risk to ecosystems, agriculture, and social life. While attempts have been made globally to understand drought characteristics, data scarcity in developing countries often challenges detailed analysis, including climatic, environmental, and social aspects. Therefore, this study developed a framework to investigate regional drought analysis (RDA) using regional drought intensity-duration-frequency (RD-IDF) curves and regional drought risk assessment (RDRA) based on the drought hazard indicator (DHI) and drought vulnerability indicator (DVI) for scarce data regions in Afghanistan. The drought characteristics were analyzed using the regional standardized-precipitation-index (SPI), and standardized precipitation-deficit distribution (SPDD). Further, L-moment statistics were used to classify different homogenous regions based on regional frequency analysis (RFA). The historical monthly precipitation data from 23 rainfall stations for the years 1970 to 2016 were collected from the Ministry of Water and Energy of Afghanistan. Based on the analysis performed, the area was classified into six homogeneous regions R-1, R-2, R-3, R-4, R-5, and R-6. The drought was very consistent—almost 50% of the years—irrespective of the homogeneous region classified. R-4, located in the northeast of the country, had a one-year extreme drought with high resiliency and low risk to drought compared to other regions. As R-1, R-3 and R-5 are located in the southwest, center and southeast parts of Afghanistan, they experience moderate drought with low resiliency and high drought risk due to long period of droughts. Moreover, the uniform distribution of precipitation deficit (Dm), was less in arid climate regions. In contrast, the semi-arid climate regions showed higher values of Dm. Furthermore, in the results in all the regions, the IDF curves showed a high drought intensity with increasing drought return periods. In contrast, the intensity significantly decreased when the time scale increased, and fewer were enhanced within the increasing drought return period. However, the outcome of this study may contain essential information for end users to make spatially advanced planning for drought effect mitigation in Afghanistan.

Joint Modelling of Drought Severity and Duration using Copula Theory: A Case Study of Ghana

Analysing and understanding the occurrence and development of droughts is of great significance in mitigating drought impacts. This study assessed the possible changes in the joint distribution of drought duration and severity in two major cities of Ghana, Accra and Yendi. The duration and severity of droughts, estimated using the Standardized Precipitation Index (SPI), were determined based on run theory. The best-fitted Copula models were used to combine the drought duration and severity to analyse the drought return period. The gamma, lognormal and Weibull distributions were considered to select the marginal distributions for the duration and severity, while the normal, t, Gumbel, Joe, Clayton and Frank copulas to select the best-fit Copula model. Bias corrected climate simulations of six Global Climate Models (GCMs) of the CMIP6 were used to project drought characteristics for the near and far futures. The results showed the Clayton and Frank copulas as the most suitable for fitting the joint distribution of drought duration and severity at Accra and Yendi, respectively. Lognormal and Weibull distributions were the most suitable for the marginal distributions of severity and duration, respectively. The joint return periods of droughts showed almost no change in the future compared to the historical period in Accra with a historical mean of 11.36 and a near and far future mean of 12.26 and 10.30 respectively but significantly reduced return periods in the future in Yendi with a near and far future means of 1.47 and 2.13 respectively compared to a historical mean of 17.40. The drought risks estimated for different future periods can provide useful information in planning, management, and assessing the adequacy of the water structures in the region.

Characteristics of drought, low temperature, and concurrent events of maize in Songliao Plain

AbstractMaize is susceptible to drought and low temperatures. In recent years, drought, low temperatures, and their composite events have often occurred during the growth period of maize, causing a huge impact. In this study, maize in the Songliao Plain was used as the research object. Based on the crop water surplus deficit index (CWSDI) and heat index (F(T)), combined with the Theil–Sen median and Mann–Kendall tests (Sen–MK) and empirical orthogonal function (EOF), the temporal trends and spatial patterns of drought and low temperatures in different growth periods of maize were obtained. Copula modelling was used to analyse the joint probability distribution and return period of drought and low temperatures. The results showed that the temporal variation trend of the CWSDI was significantly different at different growth periods of maize, and there were different trends and spatial modal distributions. However, the temporal variation trend of F(T) was similar, showing a downward trend over the entire region. There was no obvious asymmetry or skew‐dependent structure in the distribution of concurrent events of drought and low temperature; however, the joint probability contours of different growth periods were biased to the upper left. The recurrence period of drought and low‐temperature concurrent events was within 2 years, and the recurrence period was basically between 2 and 5 years, with a reduction in drought or low temperatures.

A New Agricultural Drought Disaster Risk Assessment Framework: Coupled a Copula Function to Select Return Periods and the Jensen Model to Calculate Yield Loss

China is one of the regions with the most frequent drought disasters and serious social and economic losses. Agricultural drought is the most serious natural disaster. Due to climate change, the regional agricultural drought risk assessment has always been the focus of the academic circle. This study takes Zunyi City as an example, which is the most typical city of karst landform development. The monthly precipitation data set of ground meteorological observation stations in Zunyi City from 1956 to 2020 was selected, and the drought characteristic variables were extracted by the coupled use of the precipitation anomaly percentage (Pa) index and the theory of runs. A copula function was applied to establish the joint distribution model of characteristic variables, obtaining the drought frequency and drought return periods. Combined with the Jensen model, the agricultural drought loss rate under different drought return periods in the target year (2020) was calculated and evaluated. The results showed that the Gumbel-Hougaard copula function was suitable for the joint distribution of drought joint variables in Zunyi City. From 1956 to 2020, fewer droughts occurred in Zhengan and Wuchuan, and the most droughts took place in Fenggang, Meitan, and Yuqing. The average drought duration in each county was about 1.5 months, and the average drought severity was about 0.35 in spatial distribution. Crop loss rate caused by drought increased and the affected area expanded with the increase of drought return periods (5, 10, 20, 50, and 100 years) in temporal distribution. Meanwhile, the drought disaster was most drastic in the eastern region, followed by the south, north, west, and central area. The results were highly consistent with the historical drought in Zunyi City, which verified the validity of the model. This study could provide scientific knowledge for drought resistance and reasonable mitigation programing for the security of the regional agricultural production and the sustainability of social and economic development.

Multi-temporal SPI and RDI Based on the Modified Meteorological Draught and Hydrological Drought of Marathwada Region of Maharashtra, India

The meteorological and hydrological drought indices are mostly applying as a tool for observing changes in drought situations. In the present research work, evaluated the performance of two modified meteorological drought indices i.e. modified standardized precipitation index (SPIe) and modified recoinnaissance drought index (RDIe) and hydrological drought indices i.e stream-flow drought index (SDI). The effective precipitation was used instead of precipitation for modification of meteorological drought indices. The assessment of drought trends at multi-temporal such as 1, 3, 6 and 12 months was done by using popular Mann-Kendall test and the probability and return period of occurrence of severe and extreme drought condition of the meteorological and hydrological drought events. Finally results were non-significant trend (either positive or negative) at 95% confidence limit and the 43 years reoccurrence interval of extreme meteorological drought for Latur and Parabhani districts, the 10.75, 21.5 and 14.33 years return period of severe meteorological drought for Latur, Nanded and Parabhani districts. Also, the 18, 18 and 43 years reoccurrence interval of severe hydrological drought for Latur, Nanded and Parabhani districts was calculated.

Strategic analysis of the drought resilience of water supply systems

Severe droughts can result in shortages of water supplies, with widespread social and economic consequences. Here we use a coupled simulation model to assess the reliability of public water supplies in England, in the context of changing scenarios of water demand, water regulation and climate change. The coupled simulation model combines climate simulations, a national-scale hydrological model and a national-scale water resource systems model to demonstrate how extreme meteorological droughts translate into hydrological droughts and water shortages for water users. We use this model to explore the effectiveness of strategic water resource options that are being planned in England to secure water supplies to most of England's population up to a drought return period of 1 in 500 years. We conclude that it is possible to achieve a 1-in-500-years standard in locations where strategic resource options are used, while also reducing water abstraction to restore the aquatic environment. However, the target will be easier to achieve if effective steps are also taken to reduce water demand.This article is part of the Royal Society Science+ meeting issue ‘Drought risk in the Anthropocene’.

Assessment of hydrological drought return periods with bivariate copulas in the Tigris river basin, Turkey

Assessment of hydrological drought return periods with bivariate copulas in the Tigris river basin, Turkey

Trivariate Analysis of Changes in Drought Characteristics in the CMIP6 Multimodel Ensemble at Global Warming Levels of 1.5°, 2°, and 3°C

Abstract Drought is a major natural hazard with far-reaching social, economic, and environmental impacts whose characteristics are highly interdependent across different spatial and temporal scales. Traditional global warming impact assessments on drought at the global scale have, however, taken into account only one drought characteristic at a time, likely leading to an underestimation of the overall impact. Here, we perform a trivariate analysis of changes in drought conditions at 1.5°, 2°, and 3°C global warming levels using 25 CMIP6 GCMs. Drought properties are characterized by the Standardized Soil Moisture Index (SSI). The future joint return periods of droughts historically associated with 10-, 20-, and 30-yr return periods are computed under the warming levels using copula functions considering drought duration, peak, and severity. Our comparative assessments of global warming impact on drought properties between univariate and trivariate analyses corroborate the substantial underestimation of the impact by the univariate analysis. The trivariate analysis shows that around 63%–91% of the global land will be subject to more recurrent droughts, while the percentage of the land reduces to 41%–56% for the univariate analysis. The difference between the univariate and trivariate analyses enlarges with global warming levels and the extremity of drought events. Based on the trivariate analysis, a 30-yr drought would become at least threefold more recurrent in 11%, 15%, and 20% of the global land at 1.5°, 2°, and 3°C warming levels, respectively, but the univariate analysis could not reach such large increases in drought conditions.

Drought Occurrence Probability Analysis Using Multivariate Standardized Drought Index and Copula Function Under Climate Change

This study aims to investigate the effect of climate change on the probability of drought occurrence in central Iran. To this end, a new drought index called Multivariate Standardized Drought Index (MSDI) was developed, which is composed of the Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Soil Moisture Index (SSI). The required data included precipitation, temperature (from CRU TS), and soil moisture (from the ESA CCA SM product) on a monthly time scale for the 1980–2016 period. Moreover, future climate data were downloaded from CMIP6 models under the latest SSPs-RCPs emission scenarios (SSP1-2.6 and SSP5-8.5) for the 2020–2056 period. Based on the normalized root mean square error (NRMSE), Cramer-von mises statistic (Sn), and Nash Sutcliffe (NS) evaluation criteria, the Galambos and Clayton functions were selected to derive copula-based joint distribution functions in both periods. The results showed that more severe and longer droughts will occur in the future compared to the historical period and in particular under the SSP5-8.5 scenario. From the derived joint return period, a drought event with defined severity or duration will happen in a shorter return period as compared with the historical period. In other words, the joint return period indicated a higher probability of drought occurrence in the future period. Moreover, the joint return period analysis revealed that the return period of mild droughts will remain the same, while it will decrease for extreme droughts in the future.

Evaluation of the climate change impact on the intensity and return period for drought indices of SPI and SPEI (study area: Varamin plain)

Abstract In this study, to investigate the climate change effect on meteorological drought in the next three decades of Varamin plain, the EC-EARTH model was selected from the (AR5) report with the high performance of temperature and precipitation simulation compared to the base period under RCP scenarios and then by LARS-WG software was downscaled. In addition, (intensity-duration) and the return period of drought indices of Standard precipitation index (SPI) and Standardized precipitation-evapotranspiration index (SPEI) in annual time series were evaluated. Results illustrated that the seasonal precipitation pattern has changed, and mean temperatures will increase by 1.4 °C compared to the base period. The results of the drought assessment showed that the intensity of drought in the future compared to the base period based on SPI and SPEI increased by 8 and 28%, respectively, indicating that the SPEI was more severe in all three scenarios than the SPI. It can mainly be explained by the contribution and effect of increasing the average temperature along with precipitation in the SPEI. Also, the return period of severe droughts under the RCP8.5 scenario for SPEI in the base and future periods is 8 and 6 years, respectively, which indicates a decrease in the return period of severe droughts and an increase in dry years in the future.

A Non-stationary and Probabilistic Approach for Drought Characterization Using Trivariate and Pairwise Copula Construction (PCC) Model

Under variable climatic conditions, the conventional Standardized Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) are inadequate for predicting extreme drought characteristics. Non-stationary Standardized Precipitation Index (NSPI) and Non-stationary Reconnaissance Drought Index (NRDI) are, therefore, developed by fitting non-stationary distributions. The Generalized Additive Model in Location, Scale and Shape (GAMLSS) framework, with time varying location parameters considering the external covariates, is used to fit the non-stationary distributions. Multivariate ENSO Index (MEI), Southern Oscillation Index (SOI), Sea Surface Temperature (SST), and Indian Ocean Dipole (IOD) are considered as external covariates for the non-stationary drought assessment. The performances of stationary and non-stationary models are compared. The study also concentrated on the trivariate and the Pairwise Copula Construction (PCC) models to estimate the drought return periods. The comparison of two copula models revealed that the PCC model performed better than the trivariate Student’s t copula model. The recurrence intervals arrived at for the drought events are different for trivariate copula model and PCC model. This study showed that non-stationary drought indices will be helpful in the accurate estimate of the drought characteristics under the changing climatic scenario.

Spatiotemporal evolution and the driving factors of meteorological drought in the Hun-Taizi River basin, NE China

Abstract The evolution of meteorological drought under global warming is of great significance to drought risk management. Meanwhile, driving factors that influence hydrological factors and water cycle processes play an important role in meteorological drought risk assessment. The Hun-Taizi River basin (HTRB) is a region seriously troubled by drought in China. Therefore, we reveal the evolution characteristics of meteorological drought and its driving factors. First, the standardized precipitation index (SPI) was adopted to characterize the evolution characteristics of meteorological drought. Meanwhile, copula functions with the highest goodness of fit were established to calculate the return period of meteorological drought. Then, the relationships between the SPI and the climatic phenomena were reflected by the cross-wavelet transform method to reveal the driving factors of meteorological drought. The results showed that (1) the meteorological drought of the HTRB varied greatly in different periods, and drought aggravated during spring and autumn; (2) the meteorological drought in the western, northwestern and southeastern regions of the HTRB was characterized by high frequency, short duration and low severity, while that in the other regions was characterized by low frequency, long duration and high severity; (3) the co-occurrence return periods of mild, moderate and severe drought were 1.9, 4.7 and 32.8 years and the joint return periods were 1.5, 3.0 and 9.3 years, respectively; (4) solar activity (sunspot), El Niño Southern Oscillation (ENSO) and Arctic Oscillation (AO) were strongly correlated with drought evolution in the HTRB.