Spatiotemporal Characteristics Of Drought Research Articles

Drought Characteristics and Drought-Induced Effects on Vegetation in Sri Lanka

Understanding the spatiotemporal characteristics of drought and its impacts on vegetation is a timely prerequisite to ensuring agricultural, environmental, and socioeconomic sustainability in Sri Lanka. We investigated the drought characteristics (duration, severity, frequency, and intensity) from 1990 to 2020 by using the Standardized Precipitation Evapotranspiration Index (SPEI) at various timescales and the cumulative and lagged effects on vegetation between 2000 and 2020 across the climatic zones of Sri Lanka (Dry, Wet, and Intermediate). SPEI indexes at 1-, 3-, 6-, 12-, and 24-month scales were used to analyze the drought characteristics. Frequent droughts (~13%) were common in all zones, with a concentration in the Dry zone during the last decade. Drought occurrences mostly ranged from moderate to severe in all zones, with extreme events more common in the Dry zone. This research used SPEI and the Standardized Normalized Difference Vegetation Index (SNDVI) at 0 to 24-month scales to analyze the cumulative and lagged effects of drought on vegetation. Cumulated drought effects and vegetation had maximum correlation coefficient values concentrated in the −0.41–0.98 range in Sri Lanka. Cumulated drought effects affected 40% of Dry and 16% of Intermediate zone vegetation within 1–4 months. The maximum correlation between the lagged drought effect and vegetation SNDVI showed coefficient values from −0.31–0.94 across all zones, and the high correlation areas were primarily distributed in Dry and Intermediate zones. Over 60% of the Dry and Intermediate zones had a lagged drought impact within 0 to 1 month, while 52% of the Wet zone experienced it over 11 months. The resulting dominant shorter timescale responses indicate a higher sensitivity of vegetation to drought in Sri Lanka. The findings of this study provide important insights into possible spatiotemporal changes of droughts and their possible impact on vegetation across climate zones.

Analyzing the Spatiotemporal Dynamics of Drought in Shaanxi Province

Drought, as a natural disaster with wide-ranging impacts and long duration, has an adverse effect on the global economy and ecosystems. In this paper, four remote sensing drought indices, namely the Crop Water Stress Index (CWSI), Vegetation Supply Water Index (VSWI), Temperature Vegetation Dryness Index (TVDI), and Normalized Difference Water Index (NDWI), are selected for drought analysis. The correlation analysis is carried out with the self-calibrated Palmer Drought Severity Index (sc-PDSI), and based on the optimal index (CWSI), the spatiotemporal characteristics of drought in Shaanxi Province from 2001 to 2021 were studied by SEN trend analysis, Mann–Kendall test, and a center of gravity migration model. The results show that (1) the CWSI performs best in drought monitoring in Shaanxi Province and is suitable for drought studies in this region. (2) Drought in Shaanxi Province shows a decreasing trend from 2001 to 2021; the main manifestation of this phenomenon is the decrease in the occurrence of severe drought, with severe drought covering less than 10% of the area in 2010 and subsequent years. The most severely affected regions in the province are the northern Loess Plateau region and Guanzhong Plain region. In terms of the overall trend, only 0.21% of the area shows an increase in drought, primarily concentrated in the Guanzhong Plain region and the outskirts of the Qinling–Bashan mountainous region. (3) Drought conditions are generally improving, with the droughts’ center of gravity moving northeastward at a rate of 3.31 km per year. The results of this paper can provide a theoretical basis and a practical reference for drought control and decision-making in Shaanxi Province.

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

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

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.

Refined Identification and Spatiotemporal Characteristics of Drought and Flood Abrupt Alternation Events in the Poyang Lake Basin from 1965 to 2023

This paper utilizes actual observation data from 75 precipitation stations in the Poyang Lake Basin (PLB), combined with the daily scale drought and flood abrupt alternation (DFAA) index, to analyze the occurrences of DFAA in the basin from 1965 to 2023. This includes the frequency and spatiotemporal variation of events, as well as the spatial variation in the intensity of DFAA events. The results indicate that there is no apparent temporal pattern in the frequency and intensity of events in the PLB, with spatial concentration mainly in the Fuhe, Xinjiang, and Raohe river basins. The analysis of a typical drought-to-flood event (DTF) in 1994 and a typical flood-to-drought event (FTD) in 2022 shows that the 1994 event progressed from the northeast to the south, and the prolonged drought following the 2022 event exacerbated the losses caused by the DFAA.

Investigate the Spatiotemporal Evolution of Drought and Its Interaction with Atmospheric Circulation in the Yellow River Middle Basin

Global warming contributes to an increased frequency and severity of droughts. Drought emerges as a highly prevalent natural calamity, distinguished by its formidable disruptive impact and the capacity to trigger considerable economic setbacks. Understanding the spatiotemporal characteristics of droughts and clarifying the driving role of atmospheric circulation on droughts is vital for agricultural, hydrological, ecological, and socio-economic systems. Leveraging meteorological data from 36 stations in the middle reaches of the Yellow River Basin from 1961 to 2020, we employed the Standardized Precipitation Evapotranspiration Index (SPEI) to calculate drought occurrence. Concurrently, we explored the influence of atmospheric circulation on the SPEI. The findings of our study underscore a concerning trend of worsening drought conditions within the study area. We discovered a significant correlation between the duration and severity of drought (R = 0.83, p < 0.001); longer durations often corresponded to higher levels of severity. Turning our attention to atmospheric dynamics, the Nino Eastern Pacific index (NE) emerged as a critical driver of SPEI dynamics (the contribution of NE to SPEI was 0.22), significantly impacting drought patterns. In conclusion, the study significantly contributes to our comprehension of the evolving drought patterns under the influence of global warming. The findings can provide valuable information for water resource management and drought disaster control.

Unveiling the spatiotemporal impacts of the 2021 Central Asian drought on vegetation: A comprehensive quantitative analysis

In the growing season of 2021, a severe drought occurred in Central Asia impacting various local ecosystems and socio-economic conditions. However, there is limited research on the spatiotemporal characteristics of this drought and its effects on local vegetation. To address this gap, this study utilizes the standardized precipitation evapotranspiration index (SPEI) to quantitatively evaluate the spatiotemporal drought characteristics, and standardized anomalies to assess drought impacts on vegetation greenness and productivity. The drought-induced reduction in vegetation greenness and production was also decomposed into environmental drivers based on a random forest model. Our findings can be summarized as follows: During the 2021 growing season, Central Asia experienced one of the most severe drought events in the past 40 years, with approximately 42.57 % of the region facing record-breaking drought conditions. Abnormally low precipitation (PRE), prolonged high temperatures (TMP) and evapotranspiration also occurred during the drought event. The drought had a significant detrimental effect on vegetation, leading to an approximately 10 % reduction in vegetation greenness and around 13 % in productivity. Soil moisture (SM) was found to be the most critical factor influencing vegetation greenness loss during drought conditions. Leaf Area Index (LAI) and SM emerged as the primary drivers for the reduction of Gross Primary Productivity (GPP) and Solar-Induced Fluorescence (SIF). The antecedent environmental conditions had a significant impact on the decline in vegetation greenness and productivity during the 2021 drought event, accounting for approximately 30 %–35 % and 52–69 % of the respective losses. The findings of this study highlight the importance of taking into account antecedent climate factors when studying the impacts of drought on vegetation.

Spatiotemporal drought characteristics during growing seasons of the winter wheat and summer maize in the North China Plain

The North China plain (NCP) is an important production base for winter wheat and summer maize in China. Severe droughts seriously restrict agricultural production in this region, threatening food security. Based on the standardized precipitation evapotranspiration index (SPEI), this study explored the spatial and temporal drought characteristics during the winter wheat and summer maize growing seasons in the region. The study found that: 1) From 1980 to 2013, the drought trend of the winter wheat growing season in the NCP has intensified, with Huang-Huai Plain agricultural area (HH_P) showing the most significant drought trend. However, the summer maize growing season has become wetter, with the Shandong hilly agricultural and forestry area (SD_Q) showing the most significant wetting trend. 2) After the year 2003, the results from Mann-Kendall trend analysis revealed that the drought trend of HH_P during the winter wheat growing season became particularly pronounced, but the wetting trend of SD_Q and HH_P during the summer maize growing season became more evident. 3) The dominant spatial patterns observed in the NCP during the growing seasons of winter wheat and summer maize were marked by a consistent distribution of drought and wetness conditions. For winter wheat, the southern regions of the foothill plain area of Yanshan and Taihang Mountains (YT_P) and the low-lying plain area of Hebei, Shandong, and Henan (JLY_P) were more sensitive to the changes of drought and wet conditions. For summer maize, SD_Q was more sensitive to the changes of the drought and wet conditions. The results of this study could provide references for the formulation of drought relief strategies of winter wheat and summer maize in the NCP.

Assessing the impact of meteorological and agricultural drought on maize yields to optimize irrigation in Heilongjiang Province, China

Agriculture is an essential support for social and economic development, most affected by weather and climate. Drought in agriculture significantly threatens food security and social stability. Understanding drought variability in the cultivated land can lay the foundation for crop management. Considering the effects of drought on the actual crop growth process and precise irrigation under limited water resources is a great challenge. In this study, standardized precipitation evapotranspiration index (SPEI) and soil water content were used to study the spatiotemporal characteristics of drought during maize growth in Heilongjiang Province. The distributed AquaCrop model and grey theory were used to study the relationship between irrigation, drought and maize yield at the grid scale, and the current irrigation effect was evaluated by simulating the comparison of crop yield under non-irrigation and irrigated conditions, so as to provide a basis for optimizing the irrigation system in the future. In addition, Future drought trends were also examined using the Mann-Kendall statistical test, Sen's slope, and Hurst index. The results are as follows: (1) Based on remote sensing inversion and distributed AquaCrop model, the relationship between drought and crop yield can be studied at grid scale, which can refine the impact of drought on crop yield in different cells. (2) Irrigation can increase crop yields by at least 20–40% in about 60% of areas in the Heilongjiang Province. (3) In response to the drought characteristics of alternating wet and dry variations or consistent wet and dry variations in different months, inter-regional water transfer can be used to cope with or ensure increased irrigation in drought-prone months (May and June) to achieve water conservation and efficiency. Evaluating the current irrigation effect by simulating crop yield under non-irrigated conditions and crop yield under irrigated conditions can provide a better theoretical basis for optimizing irrigation systems, in order to improve regional crop yields and reduce drought risks.

Changes in spatiotemporal drought characteristics from 1961 to 2017 in northeastern maize-growing regions, China

Changes in spatiotemporal drought characteristics from 1961 to 2017 in northeastern maize-growing regions, China

Spatiotemporal Characteristics of Drought in Northwest China Based on SPEI Analysis

Drought has a direct impact on regional agricultural production, ecological environment, and economic development. The northwest region of China is an important agricultural production area, but it is also one of the most serious areas of water shortage due to drought and little rain. It is of great significance to make full use of agricultural resources to clarify the temporal and spatial distribution characteristics of the drought regime in Northwest China. Based on the Standardized Precipitation Evapotranspiration Index (SPEI), this paper used the methods of Mann–Kendall non-parameter trend, mutation test, and Morlet wavelet analysis to explore the drought characteristics in Northwest China from 1961 to 2017. The results showed that the spatial distribution of SPEI on annual and seasonal scales differed slightly in different regions, but from northwest to southeast, the distribution was generally wetter to drier. The drought intensity (Sij) had a step-like distribution with a range of 1.14–1.98. Based on Sij analysis, the frequency of drought in Northwest China was moderate, followed by extreme drought, severe drought, and light drought. The inter-annual drought station proportion (Pj) ranged from 7.4% to 84.1%. A total of 25, 18, 7, and 5 years of pan-regional drought, regional drought, partial region drought, and local drought occurred, respectively, based on Pj analysis. Moreover, from the whole study period, the regional drought changes tended to cause humidification to different degrees. The results of Morlet wavelet analysis showed that there were multiple time scales of 33–52, 11–19, and 4–7 years of SPEI in the entire time domain, and dry and wet trends occurred. The results of the present research can provide a reference for the efficient utilization of water resources, drought monitoring and early warning, drought prevention, and drought relief in Northwest China.

Spatiotemporal characterization of droughts and vegetation response in Northwest Africa from 1981 to 2020

Drought has become one of the most devastating natural risks of agricultural production and the environment in almost all climate regions. Thus, understanding the spatiotemporal characteristics of drought and its associated impacts is crucial in drought early warning management and adaptation efforts. In this study, we used the 3-month Standardized Precipitation Index (SPI-3) obtained from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) to investigate the space–time characteristics of drought conditions. Also, this study examined the impact of the SPI-based drought on vegetation health conditions using the Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) time-series data from 1981 to 2020. The results revealed that the region experiences drought primarily between July and September, with the most prolonged drought events lasting up to five months. Morocco suffered from more frequent droughts than other countries in the region. The Mann-Kendall test showed that the trend of drought became drier over the last decade, whereas the period from 1981 to 2010 witnessed either wetting or no trends. This study also found that the response of crops and grasslands showed higher correlation with the SPI-3 and that the response of vegetation to droughts was higher during the dry season. The findings of this study provide useful information to support local and regional drought planning and adaptation programs and enhance the understanding of drought development in the region.

Drought in Shanxi Province Based on Remote Sensing Drought Index Analysis of Spatial and Temporal Variation Characteristics

Drought is a natural disaster with long duration and which causes great harm. Studying the characteristics of drought evolution in Shanxi Province can grasp the regularity of drought occurrence and provide a basis for drought prevention and resistance. This study utilizes MODIS products to analyze and quantify the extent of drought in a specific area. The study calculates several indices, including the Crop Water Stress Index (CWSI), Vegetation Supply Water Index (VSWI), and Temperature Vegetation Dryness Index (TVDI), using variables such as the Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), Evapotranspiration (ET), and Potential Evapotranspiration (PET). Additionally, three drought indices are analyzed for correlation with the self-calibrated Palmer Drought Severity Index (sc-PDSI), and the most suitable drought index is selected through validation with typical drought events. Finally, the selected indices are used to investigate the spatiotemporal characteristics of drought in the study area from 2001 to 2020. The results show: (1) CWSI and sc-PDSI have a strong correlation both in terms of time and spatial analysis. Furthermore, CWSI has been shown to be more effective in monitoring significant drought events. (2) The multi-year mean values of CWSI range from 0.71 to 0.85, with a significant degree of spatial heterogeneity. In the study area, the percentage of the area affected by different levels of drought is in the following order: moderate drought > severe drought > mild drought > no drought. (3) The trend of CWSI changes shows that the drought situation in Shanxi Province has been alleviated from 2001 to 2020, and the overall spatial distribution indicates that the degree of drought alleviation in the southern region is greater than that in the northern region. The turning point from drought to wetness in the study area was in 2011, showing the overall characteristic of “dry in the north and wet in the south”.

Spatiotemporal Characteristics and Hazard Assessments of Maize (Zea mays L.) Drought and Waterlogging: A Case Study in Songliao Plain of China

The Songliao Plain is the largest maize (Zea mays L.) cropland area in China and, thus, is most influenced by water stress. To mitigate the adverse impact of water stress on maize yield and quality, various agricultural irrigation strategies have been implemented. Based on land surface temperature and an enhanced vegetation index, this study constructed the temperature vegetation dryness index (TVDI) and combined the Hurst index and Sen trend to analyze the spatiotemporal characteristics of drought and waterlogging. From the correlation between TVDI and gross primary productivity, the weight coefficients of different growth cycles of maize were derived to determine the drought and waterlogging stresses on maize in Songliao Plain for 2000–2020. The drought hazard on the western side of Songliao Plain was high in the west and low in the east, whereas the waterlogging hazard was high in the east. Waterlogging likely persisted according to the spatiotemporal trends and patterns of drought and waterlogging. During the second growth cycle, maize was most severely affected by water stress. There was a spatial heterogeneity in the severity of the hazards and the stress degree of maize. For the reason that precipitation in the study area was concentrated between mid-late July and early August, maize was susceptible to drought stress during the first two growth stages. Irrigation concentrated in the early and middle stages of maize growth and development in the western part of the Songliao Plain reduced the drought stress-induced damage. Spatiotemporally-detected drought and waterlogging couplings and hazards for maize in the Songliao Plain for 2000–2020 provide actionable insights into the prevention and mitigation of such disasters and the implementation of water-saving irrigation practices at the regional scale.

Non-parametric severity-duration-frequency analysis of drought based on satellite-based product and model fusion techniques.

Climate change has increased the severity and frequency of droughts over the last decades. To alleviate the adverse impacts of droughts, an effective planning and management framework requires high-resolution spatiotemporal data. TRMM multi-satellite precipitation analysis (TMPA) dataset provides sufficient accuracy with fine spatio-temporal resolution. However, it only covers a short temporal span, which limits its applicability for drought studies. This paper presents a methodology for efficient and accurate temporal extension of TMPA using four artificial intelligence (AI)-based models. To improve AI-based model precipitation estimations, fusion techniques including Orness, Orlike, and genetic algorithm (GA)-based weighting methods were employed. Results show that fusion approaches provide more accurate estimates of precipitation. Different timescales of n-SPI time series and drought spatial maps were prepared to visually evaluate the performance of long-term TMPA (LT-TMPA) alongside statistical error indices. The results confirm that this dataset is effective for meteorological drought monitoring over southern Iran. Finally, drought risk assessment was carried out to determine the spatiotemporal characteristics of droughts through severity-duration-frequency (SDF) contour maps. In contrast to the traditional SDF curves, SDF contour maps provide a superior understanding of drought for policymakers since they preserve spatial information.

Spatiotemporal Characteristics of Droughts and Floods in Shandong Province, China and Their Relationship with Food Loss

Spatiotemporal Characteristics of Droughts and Floods in Shandong Province, China and Their Relationship with Food Loss

Spatiotemporal Characteristics of Meteorological Drought and Wetness Events across the Coastal Savannah Agroecological Zone of Ghana

Drought and wetness events have become common due to global warming, warranting the need for continuous analysis and monitoring of drought and wet events to safeguard people’s livelihoods. In this study, the Standardized Precipitation Evapotranspiration Index (SPEI) was utilized to analyze the spatiotemporal characteristics of drought and wetness events in the coastal Savannah agroecological zone from 1981 to 2021. Climate data from 14 locations across the zone were used to characterize drought and wetness events at the 3 and 12 month timescales. Except for September 1995 and November 2002, when changepoints occurred, the results revealed the homogeneous nature of temperature and rainfall in the zone. More drought events were observed in the dry and minor seasons, while the wet season had more wetness events under both the SPEI-3 and SPEI-12 timescales. The results also showed that, while moderate-to-severe drought events were common for most years, extreme drought events were more typical in the 1980s and 1990s than in the 2000s under both the SPEI-3 and SPEI-12. Furthermore, the 2000s saw more moderate-to-severe wetness events than the 1980s and 1990s, while the greatest number of extreme wetness events occurred in 1987, followed by 1997 and 2021 under the SPEI-3, and a few moderate-to-extreme wetness events occurred in 1987, 1991, 1997–1998, 2012–2013, 2018, and 2020–2021 under the SPEI-12. Under the SPEI-12, only extreme drought events showed a significant positive trend with a small magnitude of change. On the spatial scale, drought and wetness events occurred more frequently in the Central and Volta regions than in the Greater Accra region; however, the intensity and duration of the events were stronger and lasted longer in the Greater Accra and Central regions than in the Volta region. The regular monitoring of drought and wetness events is required to protect the livelihoods of people in the zone.

Tracking the influence of drought events on winter wheat using long-term gross primary production and yield in the Wei River Basin, China

The Wei River Basin (WRB) is the main winter wheat-producing area in Northwest China and plays a pivotal role in national food security and economic development. Drought is the main agro-meteorological disaster affecting winter wheat yield in this region, and the accurate assessment of the drought impacts on crop growth and yield is an important part of maintaining food security. However, commonly used assessment methods, such as correlation analysis and crop model simulation, have some limitations. In this study, based on standardized precipitation evapotranspiration index (SPEI) at multiple time scales, gross primary production (GPP) and yield data from 1990 to 2018, sensitivity analysis, Pearson correlation, and superposed epoch analysis (SEA) were used to analyze the spatiotemporal characteristics of drought in the WRB and its influence on winter wheat growth and quantitatively assess the impact of drought at different levels on winter wheat yield. The results were as follows: 1) Overall, the WRB was in a dry state with a drying trend during 1990–2018, and the droughts in spring, summer, and winter were the main driving forces of annual drought that seriously threatened the growth and yield of winter wheat, especially in spring (March–May), which is the key growth period of winter wheat. 2) The average annual GPP of winter wheat in the WRB showed a significant upward trend of 0.465 · 10a−1, and the central part of the WRB was the region where winter wheat GPP had higher sensitivity to drought. In general, winter wheat GPP during the growing season was most sensitive to SPEI-3, indicating that seasonal water deficits had the greatest impact on winter wheat growth. 3) The yield reduction of winter wheat caused by drought presented a spatial distribution that is heavy in the north and light in the south, and as the drought grade increased, the winter wheat yield decreased more significantly, even in irrigated areas. Therefore, relevant government departments still need to strengthen the risk management of agricultural droughts in the WRB and formulate reasonable policies to maintain food security.

Multisource data-based integrated drought monitoring index: Model development and application

In this study, we proposed a new integrated remote sensing drought monitoring indices, i.e. Multiple Remote Sensing Drought Index integrated by Principal Component Analysis (PSDI), Multiple Remote Sensing Drought Index integrated by multiple linear regression (MRSDI) and Multiple Remote Sensing drought index integrated by gradient boosting method (GBMDI), based on the Precipitation Condition Index (PCI), Temperature Condition Index (TCI), Vegetation Condition Index (VCI), and Soil Moisture Condition Index (SMCI). The monitoring performance of PSDI, MRSDI and GBMDI was compared and verified based on the real-world observed droughts during 2002 to 2016. We also evidenced drought monitoring performance of the PSDI MRSDI and GBMDI by comparison between PSDI, MRSDI, GBMDI and SPEI, SPI and PDSI based on the in situ observed meteorological data. We found that the spatiotemporal characteristics of droughts monitored by the PSDI, MRSDI and GBMDI were generally in good agreement with those by the SPI and SPEI. The GBMDI performs better than PSDI and MRSDI in describing drought processes and spatial patterns of droughts of different drought intensities. Comparison between the real-world observed drought-affected croplands and those monitored by PSDI, MRSDI and GBMDI indicated better drought monitoring performance of GBMDI than PSDI and MRSDI in monitoring droughts across widespread drought-affected regions. Besides, the trend of GBMDI is in good agreement with standardized crop yield. Therefore GBMDI should be the first choice in drought monitoring practice. The GBMDI developed in this study can help to provide an alternative drought monitoring index for large-scale drought monitoring across China and also in other regions of the globe.

Spatiotemporal Characteristics of Drought in Central Asia from 1981 to 2020

Drought is a meteorological phenomenon that threatens ecosystems, agricultural production, and living conditions. Central Asia is highly vulnerable to drought due to its special geographic location, water resource shortages, and extreme weather conditions, and poor management of water resources and reliance on irrigated agriculture exacerbate the effects of drought. In this study, the latest version of the Global Land Data Assimilation System was employed to calculate the Standardized Precipitation Evapotranspiration Index at different time scales during the period from 1981 to 2020. The varimax Rotated Empirical Orthogonal Function was applied for subregional delineation of drought patterns in Central Asia, and various methods were employed for a comparative analysis of the spatiotemporal characteristics of drought in these Central Asian subregions. The results show that drought patterns vary considerably in the Central Asian subregions. Over the past 40 years, alternating wet and dry conditions occurred in Central Asia. North Kazakhstan experienced more drought events with lower severity. East and west differences appear after 2001, the west becoming drier and the east becoming wetter. Some regions near lakes, such as Balkhash, Issyk-Kul, and the Aral Sea, suffer from droughts of long duration and high severity. In the Tianshan region, droughts in the northern slopes occur more frequently, with shorter durations and higher intensity and peaks. Northwestern China and western Mongolia have extensive agricultural land and grasslands with highly fragile ecosystems that have become progressively drier since 2001.