Meteorological Drought Severity Research Articles

Interactive Changes in Climatic and Hydrological Droughts, Water Quality, and Land Use/Cover of Tajan Watershed, Northern Iran

In response to novel and complex uncertainties, the present research is conducted to characterize the most significant indicators of watershed health including drought, water quality, and vegetation for the Tajan watershed, Mazandaran, Iran. The Standardized Precipitation Index (SPI) and Streamflow Drought Index (SDI) are, respectively, used to quantify the meteorological and hydrological droughts in the present (1993–2020) and future (2023–2050) employing optimistic RCP2.6 and pessimistic RCP8.5 scenarios. To concoct discharge data for the future, IHACRES v1.0 software is used with a Nash–Sutcliffe coefficient (NSE) of 0.48 and a coefficient of determination (R2) of 0.58. Maps of land use and Normalized Difference Vegetation Index (NDVI) are also prepared using Landsat images. Subsequently, the surface water quality is assessed using AqQA v1.1.0 software. The results show the difference in the severity of future meteorological droughts in different stations. In addition, the predominance of non-drought (SDI≥0) or mild drought (−1 ≤ SDI < 0) is indicated for future hydrology. The land use changes show a decrease in rangeland (−5.47%) and an increase in residential land (9.17%). The water quality analysis also indicates an increase in carbonate ions in the watershed outlet. Communicating the relationships between study indicators, which is a big gap in the current watershed management approach, avoids future failures and catastrophes.

The future of droughts in Iran according to CMIP6 projections

ABSTRACT Anthropogenic climate change is exerting immense pressure on water resources in Iran. This study investigates future precipitation and meteorological droughts across the country considering performances of 41 general circulation models (GCMs). The findings indicate a significant increase in long-term average annual precipitation (LAAP) across Iran with an overall north-to-south increasing gradient, particularly in areas prone to extreme events. However, focusing solely on LAAP is misleading. Projected precipitation reveals substantial inter-annual variability, impacting both the severity and duration of meteorological droughts. For instance, 100-year return period droughts are expected to intensify in severity (The Shared Socio-economic Pathway SSP1-2.6: 4–91%, SSP8-5.5: 46–204%) and duration (SSP1-2.6: 19–76%, SSP8-5.5: 40–127%) across most regions, except the Persian Gulf coastal zone, where droughts may become less severe (SSP1-2.6: 23%, SSP8-5.5: 23%) and shorter in duration (SSP1-2.6: 27%, SSP8-5.5: 10%). Additionally, bivariate frequency analysis suggests that major droughts could become significantly more frequent in the future.

Quantifying Meteorological Drought Severity for the Watersheds in Euphrates River Basin, Central Euphrates District, Iraq

Drought is a major natural extreme event that can cause significant damage to water resources. This study investigated the implications of drought for Watersheds in Euphrates River basin in Iraq which includes Hilla, Karbala, Najaf, Diwaniyah, and Najaf.. It was found that had an adverse impact on the study region. Among the most often used drought assessment indices globally are the Standard Precipitation Index (SPI) and its version, the Standard Precipitation and Evapotranspiration Index (SPEI).The study evaluated several probability distribution functions to model rainfall and water balance in Iraq. The Kolmogorov–Smirnov (K–S) test and the Anderson–Darling (A–D) test were used to test the goodness-of-fit for rainfall and water balance. The log-normal distribution was found to be the best fit for rainfall at approximately 40% of the stations considered, while the generalized logistic distribution (genlog) was the best fit for water balance at approximately 80% of the stations considered. The study also found that the extreme droughts in Samwah in 2012 and Diwiniyah in 1999 had the highest severity values of -2.8957 in SPI-12 and SPEI-12, respectively.

Long‐term variability and trends of meteorological droughts in Ukraine

AbstractThe purpose of this research is to identify changes in the spatiotemporal distribution and severity of meteorological droughts in Ukraine between 1946 and 2020. In order to determine the role of precipitation and atmospheric evaporative demand on drought severity, two drought indices were applied for comparative analysis: the standardized precipitation index (SPI) and the standardized evaporation precipitation index (SPEI). Both indices were calculated on 3‐ and 12‐month timescales. The gridded dataset of monthly air temperature and atmospheric precipitation for Ukraine with high spatial resolution (0.1° × 0.1°), developed in the Ukrainian Hydrometeorological Institute, was used. Results of time series analysis of drought indices showed at least 20 episodes, in which more than 25% of the territory of Ukraine was affected by drought of varying intensity. Trends show an increase in drought severity determined mostly by a strong observed increase in the atmospheric evaporative demand. Tendencies towards an increase in the duration and intensity of droughts were observed mainly in the southwestern, central and northern regions of Ukraine. The main cause of the increase was droughts in spring and summer. The temporal analysis of the spatial distribution of areas affected by drought during the identified main drought episodes showed different patterns in drought propagation across the territory of Ukraine.

Spatiotemporal analysis of meteorological drought in El Niño years over Oromia region, Ethiopia

Drought is one of the most common natural disasters globally, having major impacts on environmental, economic, and social conditions and Ethiopia is no exception particularly the Oromia region. In order to evaluate and characterize the meteorological droughts associated with El Niño years over the Oromia region, the satellite data CHIRPS was used. The monthly time series data for the period from 1991 to 2020 was used for temporal and spatial analysis of meteorological drought using standardized precipitation index (SPI) across SPI3, SPI6, SPI9 and SPI12 indices using GeoCLIM, GIS, and Python tools. The results of this study show that meteorological droughts during the El Niño years indicated an increment across weak, moderate, and strong El Niño events over the Oromia region. The dryness was visualized with frequency and duration in time-scale across short-term drought indices in time steps. The time-scale temporal meteorological drought indices in three to twelve months show that the drought indices varied in magnitude, duration, and frequency in meteorological droughts. In general, the meteorological drought severity of correlation for the remaining zones analysis between SPI3 and SPI6, SPI6 and SPI12, and SPI9 and SPI12 indices was dominated by an increment of the correlation values over short to long timescales over the study area.

Determining the response of ecological drought to meteorological and groundwater droughts in Northwest China using a spatio-temporal matching method

Meteorological drought and groundwater drought in ecologically fragile regions may induce ecological drought. Currently, there is no effective method for revealing the response mechanism of ecological drought to meteorological drought and groundwater drought. Taking Northwest China (NWRC) as an example, meteorological drought, groundwater drought and ecological drought were evluated by standardized pricipitation index, standardized groundwater storage anomaly index, and standardized ecological water deficit index, respectively. The spatio-temporal matching method was improved for identifying propagation between three types of drought events. Then, a model of ecological drought characteristics in response to meteorological drought and groundwater drought characteristics was constructed based on the copula function. Finally, the Bayesian model was used to determine the thresholds of meteorological drought and groundwater drought that trigger ecological drought events at different drought levels. The key findings are as follows. (1) A total of 31 pairs of meteorological-groundwater-ecological drought events with a genetic relationship were identified. The ecological drought events with larger severity were caused by the joint effect of meteorological and groundwater drought, and most of them occurred before the 21st century. (2) The optimal response models of the affected area, duration, and intensity of ecological drought events were Gumbel copula driven by the affected area of meteorological drought, the Student t copula driven by the duration of groundwater drought, and the Joe copula driven by the severity of meteorological and ecological drought, respectively. (3) The thresholds and the corresponding curves of meteorological drought and groundwater drought to trigger mild, moderate, severe, and extreme ecological drought events were obtained. Results of this study can provide valuable information for early warning of ecological drought.

Dynamic Characteristics of Meteorological Drought and Its Impact on Vegetation in an Arid and Semi-Arid Region

Under the background of global climate warming, meteorological drought disasters have become increasingly frequent. Different vegetation types exhibit varying responses to drought, thus, exploring the heterogeneity of the impact of meteorological drought on vegetation is particularly important. In this study, we focused on Inner Mongolia (IM) as the research area and employed Standardized Precipitation Evapotranspiration Index (SPEI) and Vegetation Health Index (VHI) as meteorological drought and vegetation indices, respectively. The Breaks for Additive Seasons and Trend algorithm (BFAST) was utilized to reveal the dynamic characteristics of both meteorological drought and vegetation changes. Additionally, the Pixel-Based Trend Identification Method (PTIM) was employed to identify the trends of meteorological drought and vegetation during spring, summer, autumn, and the growing season. Subsequently, we analyzed the correlation between meteorological drought and vegetation growth. Finally, the response of vegetation growth to various climate factors was explored using the standardized multivariate linear regression method. The results indicated that: (1) During the study period, both SPEI and VHI exhibited a type of interrupted decrease. The meteorological drought was aggravated and the vegetation growth was decreased. (2) Deserts and grasslands exhibited higher sensitivity to meteorological drought compared to forests. The strongest correlation between SPEI-3 and VHI was observed in desert and grassland regions. In forest areas, the strongest correlation was found between SPEI-6 and VHI. (3) The r between severity of meteorological drought and status of vegetation growth was 0.898 (p < 0.01). Vegetation exhibits a more pronounced response to short-term meteorological drought events. (4) Evapotranspiration is the primary climatic driving factor in the IM. The findings of this study provide valuable insights for the rational utilization of water resources, the formulation of effective irrigation and replenishment policies, and the mitigation of the adverse impacts of meteorological drought disasters on vegetation growth in the IM.

Spatio‐temporal risk analysis of agriculture and meteorological droughts in rainfed Potohar, Pakistan, using remote sensing and geospatial techniques

AbstractDroughts of various types are considered as a major threat to rainfed agriculture, because agricultural production is dependent on the spatio‐temporal distribution of rainfall. The rainfed regions of Pakistan, such as Potohar, have experienced several instances of drought since 2000. The most drought‐affected staple crop of the region is wheat, which ultimately affects regional food security. In this study, we examine the agricultural and the meteorological droughts in the Potohar region during 2000–2020, to create a drought risk map. This region comprises four districts, namely Attock, Chakwal, Jhelum and Rawalpindi. First, the agricultural and meteorological drought severity maps were created using rainfall data (meteorological data) and vegetation indices for three different periods (i.e., drought year, moderate drought year and normal year). The agricultural drought patterns and intensity were identified and evaluated using the MODIS products MOD09A1 and MOD11A2, while the meteorological droughts were identified using CHRIPS rainfall data. Afterwards, a combined drought risk map was generated by integrating the agricultural and meteorological adrought severity maps using a weighted overlay analysis. This drought risk map showed that Attock and Rawalpindi were expeiencing slight to no drought conditions, whereas the southwestern and central parts of Chakwal showed moderate drought conditions. Similarly, the western parts of Jhelum faced moderate drought conditions. Thus, the combined drought risk map may be a useful guide for decision makers in the local and provincial government. Using this map, they can identify adaptation practices in the drought‐prone areas of this region for enhancing agricultural productivity.

A generalized framework for quantifying and monitoring the severity of meteorological drought

The current study proposes a new framework for quantifying and monitoring the severity of meteorological drought. The proposed framework consists of three phases. The first phase of the framework uses K-component Gaussian Mixture Distribution (GMD) in the computation. The second phase is mainly based on the dissimilarity matrix-based clustering using C-index and Monte Carlo Feature-based Selection (MCFS) method. The third phase uses the Markov chain, transition probabilities and a non-homogeneous Poisson process under the Bayesian estimation. The Relative Importance (RI) values are used to choose appropriate stations. The Deviance Information Criteria (DIC) is used to check model suitability, and Root Mean Square Error (RMSE) is utilized for determining model performance. The proposed framework is validated to the 52 meteorological stations in Pakistan for 49 years from 1968 to 2016. Moreover, the outcomes of the current analysis provide insight to quantify and monitor meteorological drought comprehensively and accurately.

Proposing a new framework for analyzing the severity of meteorological drought

The quantitative description of meteorological drought from various geographical locations and indicators is crucial for early drought warning to avoid its negative impacts. Therefore, the current study proposes a new framework to comprehensively accumulate spatial and temporal information for meteorological drought from various stations and drought indicators (indices). The proposed framework is based on two major components such as the Monthly-based Monte Carlo Feature Selection (MMCFS,) and Monthly-based Joint Index Weights (MJIW). Besides, three commonly used SDI are jointly assessed to quantify drought for selected geographical locations. Moreover, the current study uses the monthly data from six meteorological stations in the northern region for 47 years (1971-2017) for calculating SDI values. The outcomes of the current research explicitly accumulate regional spatiotemporal information for meteorological drought. In addition, results may serve as an early warning to the effective management of water resources to avoid negative drought impacts in Pakistan.

Possible Future Climate Change Impacts on the Meteorological and Hydrological Drought Characteristics in the Jinghe River Basin, China

Revealing the impact of future climate change on the characteristics and evolutionary patterns of meteorological and hydrological droughts and exploring the joint distribution characteristics of their drought characteristics are essential for drought early warning in the basin. In this study, we considered the Jinghe River Basin in the Loess Plateau as the research object. The standardized precipitation index (SPI) and standardized runoff index (SRI) series were used to represent meteorological drought and hydrological drought with monthly runoff generated by the SWAT model. In addition, the evolution laws of the JRB in the future based on Copula functions are discussed. The results showed that: (1) the meteorological drought and hydrological drought of the JRB displayed complex periodic change trends of drought and flood succession, and the evolution laws of meteorological drought and hydrological drought under different spatiotemporal scales and different scenario differ significantly. (2) In terms of the spatial range, the JRB meteorological and hydrological drought duration and severity gradually increased along with the increase in the time scale. (3) Based on the joint distribution model of the Copula function, the future meteorological drought situation in the JRB will be alleviated when compared with the historical period on the seasonal scale, but the hydrological drought situation is more serious. The findings can help policy-makers explore the correlation between meteorological drought and hydrological drought in the background of future climate change, as well as the early warning of hydrological drought.

Assessment of Meteorological and Agricultural Drought Analysis in Kırklareli province

The Global warming in the world cause to the climate change in this century. Agriculture is one of the sectors that can be most affected by climate change. Agricultural production is affected by precipitation and temperature variables. Due to the changes in these two parameters, the increase in the temperatures and the changes in the amount of precipitation in parallel with this disrupt the ecological balance and bring along the problems of desertification and drought. Agricultural production is highly dependent on meteorological factors in Thrace region. For this reason, it is expected that changes in climatic factors will affect the agriculture of the region positively or negatively. The aim of this study is to determine the frequency and severity of meteorological and agricultural drought with two indexes between 1963-2019 years in Kırklareli province. Standardized Precipitation Evapotranspiration Index (SPEI) was used to determine monthly, seasonal, six monthly and annual agricultural drought. According to annual agricultural drought results, it was calculated ten years mild arid (1969, 1985, 1986, 1990, 1991, 1992, 1993, 2011, 2016, and 2019), five years moderate arid (1983, 1989, 1996, 2008, and 2015), one year severe arid (1994), and two years extreme arid (2000 and 2001). Another drought index which is Standardized Precipitation Index (SPI) was used to determine meteorological drought. According to annual meteorological drought results, Eight years mild arid (1964, 1969, 1982, 1985, 1986, 1990, 1991, and 2011), seven years moderate arid (1983, 1989, 1992, 1993, 1994, 1996, and 2008), and two years extreme arid (2000, 2001) was figured out. According to linear correlation analysis, a good correlation was obtained for SPI and SPEI values, between annual, six monthly (Spring-Summer), and three monthly only winter and spring periods (R2=0.871, R2=0.901, R2=0.974, and R2=0.919), respectively. In the 57-year observation period; 18 years were determined as the arid year with SPEI index and 67% of these total arid years (12 arid years) occurred and 17 years were determined as the arid year with SPI index and 76% of these total arid years (13 arid years) occurred, between 1982 and 2002 years. The SPEI drought index which use precipitation, temperature and evapotranspiration data could give much good results to policy makers in drought mitigation policies in terms of giving results that are more accurate in agricultural production and drought assessments.

Block-level Drought Assessment using Rainfall and Remote sensing Data

<p>Drought is a disastrous natural phenomenon. It is generally viewed as a sustained and regionally extensive occurrence of below average natural water availability either in the form of rainfall, river runoff or groundwater. Drought is defined based on different factors and generally assessed in meteorological, hydrological and agricultural contexts. Efficient management of drought over an area or catchment depends mainly on its correct assessment. In this study, Meteorological drought severity assessment was carried out based on the frequency analysis of IMD method producing Meteorological Drought Severity Index (MDSI). Agricultural drought severity assessment was carried out by developing an Agricultural Drought Severity Index (ADSI), which involves crop land and fallow land estimation, delineated from remote sensing data using NDVI analysis. The methodology was applied for Samba season (major crop season) of Palar Sub-basin encompassing Vellore (a chronic drought prone district), located in the North-East part of Tamil Nadu State, India. Block-wise drought severity maps were generated using geospatial environment to understand the drought severity status of the area. It is observed that 70% of the blocks in the study area were affected by moderate and severe droughts, which needs drought proofing measures.</p>

Integrated drought monitoring and assessment using multi-sensor and multi-temporal earth observation datasets: a case study of two agriculture-dominated states of India.

In the current scenario of climate change, there has been a substantial increase in the frequency and severity of drought events. Therefore, it is necessary to investigate spatio-temporal characteristics of different drought events to plan for water resource utilization. The present study aims to assess and quantify the impact of meteorological, hydrological, and agricultural drought events from 2001 to 2017 over two large states of India (i.e., Maharashtra and Madhya Pradesh) using multi-temporal earth observation data at a finer resolution of 1km. Drought indices including Standardized Precipitation Index (SPI), Standardized Water level Index (SWI), and Vegetation Health Index (VHI) were derived from precipitation, groundwater level, vegetation indices, and land surface temperature data respectively to map the spatial extent and severity of meteorological, hydrological, and agricultural drought. Assessment of individual drought indices was carried out to understand the effect of these drought events separately on the study area. Area vulnerable with multiple droughts in the region was identified by integrating multiple drought indices to derive a composite drought map. This included the locations that are hotspots in terms of the occurrence of drought events of different types. The spatial pattern captured in the composite drought map indicates that most of the study areas are prone to drought events varying from mild to extreme severity. Madhya Pradesh is more prone to meteorological and agricultural drought events compared to hydrological drought. Maharashtra state is prone to three types of drought with agricultural drought being the dominant one. This study provides an opportunity to investigate and understand the drought phenomenon in a comprehensive manner at comparatively finer spatial resolution.

A copula model to identify the risk of river water temperature stress for meteorological drought

Drought is a natural phenomenon that can occur in all climatic zones, and is persistent and regionally widespread. Extreme drought caused by climate change can have serious consequences for freshwater ecosystems, which can have significant social and economic impacts. In this study, the effect of meteorological drought on river water temperature was analyzed probabilistically in order to identify the risk of river water temperature stress experienced by the aquatic ecosystem when a meteorological drought occurs. Meteorological drought is divided into a situation in which moisture is insufficiently supplied from the atmosphere and a situation in which the atmosphere requires excessive moisture from the earth's surface. Using the copula theory, a joint probabilistic model between the river water temperature and each meteorological drought caused by two causes is proposed. In order to consider the propagation time from meteorological drought to river water temperature, the optimal time-scale meteorological drought index is adopted through correlation analysis between the meteorological drought index calculated at various time-scales and the river water temperature. The optimal copula function of the drought index and river water temperature is determined using AIC analysis. Using the proposed model, a risk map is drawn for the river water temperature stress experienced by the aquatic ecosystem under the user-defined meteorological drought severity. The risk map identifies the stream sections where the river water temperature is relatively more sensitive to meteorological drought. The identified stream sections appear differently depending on the cause of the meteorological drought, the region, and the season.

Spatiotemporal climate variability and trends in UNESCO designated Cultural Landscapes of Konso, Ethiopia

ABSTRACT Understanding spatiotemporal patterns of climate variability and trends is essential to designing context-specific adaptation and mitigation interventions for climate change impacts. To this end, this paper examines the 1983–2016 rainfall and temperature variability and trends using merged satellite-gauge station data in the UNESCO designated Cultural Landscapes of Konso, Ethiopia. We have employed a non-parametric Mann-Kendall test to analyze rainfall and temperature trends, whereas the coefficient of variation (CV) has been used for variability analysis. The distribution and severity of meteorological droughts were mapped using the Standardized Precipitation Index (SPI). Our findings revealed an increase in annual and summer (Kiremt) season rainfall by 3.16 mm and 0.42 mm per year, respectively. However, rainfall in the spring (Belg) season decreased by 1.12 mm per year. Our findings also showed a substantial spatiotemporal variability in drought events due to variations in rainfall and topography. Consequently, the observed increase in frequency and the spatial extent of drought pose potential threats to rainfed farming, which gradually exposes smallholders to food insecurity and socioeconomic vulnerability. Therefore, agroecological-based local adaptation and mitigation interventions to climate variability are needed to enhance the resilience of smallholder farmers and ensure the continuity of the Konso cultural landscapes.

Reassessing the frequency and severity of meteorological drought considering non-stationarity and copula-based bivariate probability

Drought is a multifaceted natural phenomenon with diverse spatial and temporal characteristics and significant environmental, social, and economic effects. The utility of conventional drought indices based on the assumption of stationarity is questionable due to the advent of rapid environmental change. We proposed a non-stationary standardized precipitation index (SPINS) to reassess the nature of meteorological drought. Precipitation observations from eight rain gauge stations for 1961–2017 in South Korea were fitted to a non-stationary gamma distribution using a generalized additive model in location, scale, and shape algorithm. Drought duration and severity were identified by SPINS and joint and conditional return periods were estimated using copula-based bivariate probabilities. The results show that average drought duration, severity, and frequency obtained from SPINS were more severe than those produced by a conventional standardized precipitation index (SPIC). The average inter-arrival time was 41.46 months and 39.86 months for SPIC and SPINS, respectively, at the Seoul station. The joint return periods of observed drought event from March 2008 to June 2008 with a duration of 4 months and a severity of 4.8 were 10.4 and 6.4 years for the SPIC and SPINS, respectively, at the Seoul station. We conclude that return periods calculated using the SPINS are more reliable than those calculated by the SPIC. These findings should prove helpful in drought management and risk assessment under a changing environment as effective management requires prior knowledge of events.

Assessment of drought using standard precipitation index in Prakasam district Andhra Pradesh, India

This paper discusses a method for calculating the severity of meteorological droughts based on historical precipitation data as the primary criterion Monthly precipitation data from 1970 to 2020 were used to obtain Standardized Precipitation Index (SPI) values for Prakasam district, Andhra Pradesh. SPI has the ability to analyse the drought at various time scales and for a variety of applications. SPI is calculated at various time scales (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 etc. months). Time scales of one, two, and three months are effective for agriculture, while time scales of six, nine, and twelve months are useful for hydrology. A drought event occurs any time the SPI is continuously negative and reaches an intensity of -1.0 or less. The event ends when the SPI becomes positive. Each drought event, therefore, has a duration defined by its beginning and end, and an intensity for each month that the event continues. The annual SPI for Prakasam district was calculated from 1970 to 2020 to show the frequency of occurrence of dry and wet conditions. Temporal SPI graphs show that the maximum SPI value (extreme drought) occurred in the year 2018 in that year, the SPI value was -2.6. Furthermore, in severe and extreme drought years, SPI values indicated only moderate dryness rather than extreme dryness, with SPI values never falling below -2.5.Severe and moderate drought occurred in 1984, 2002 and 2014. Drought patterns were evaluated, yielding many interesting results on the variability of drought occurrence in the region. The study's findings are relevant to climate change studies in order to understand historical patterns and build future scenarios of drought occurrences.

Observed meteorological drought trends in Bangladesh identified with the Effective Drought Index (EDI)

Countries dependent on small-scale agriculture, such as Bangladesh, can be vulnerable to the effects of climate change and variability. Changes in the occurrence and severity of drought are an important part of this issue and form the subject of this paper. We examined the characteristics of meteorological drought occurrence and severity using the Effective Drought Index (EDI), including the drought events, drought chronology, onset and ending of drought, consecutive drought spells, drought frequency, intensity and severity, using North-Bengal of Bangladesh as a case study. The rainfall and temperature dataset of the Bangladesh Meteorological Department (BMD) for the study region throughout 1979–2018 is utilised. The trends of drought are detected by using the Mann-Kendall test and Sen Slope estimation. We evaluated the performance of EDI using the Standardized Precipitation Index (SPI), historical drought records and rice production. This study finds that seasonal and annual droughts have become more frequent over the period studied in all seasons except the pre-monsoon. In addition, the largest decrease in seasonal EDI is found in the monsoon, both in the Teesta floodplain and Barind tract regions. In the decades prior to the late 2000s, a drought spell typically starts between March and May (±15 days) and ends with the monsoonal rainfall in June/July. In the years since the late 2000s, monsoon and post-monsoon droughts spells have significantly increased. Overall, the peak intensity of droughts are higher in the Barind tract than in the Teesta floodplain, and the frequency and severity of moderate to severe drought are increasing significantly in the Barind tract. The drought frequency has increased by at least 10% in North Bengal of Bangladesh over the periods of 1979–2018. Though EDI is strongly correlated with the SPI index, our analysis shows that, surprisingly, rice production is actually decoupled from meteorological drought (as identified by the EDI and SPI). Hence, this research suggests that there are other significant influences on rice yield beyond meteorological drivers. This could include effects from differing irrigation infrastructure, technology and management strategies in the study regions. Challenges to agricultural production may be exacerbated in coming years, should the identified increasing meteorological drought trends continue. Data AvailabilityThe data that support the findings of this study are available on request from the corresponding author.

Identification of future meteorological drought hotspots over Indian region: A study based on NEX‐GDDP data

AbstractThe present study aims to answer the following two research questions using the future outputs from 19 GCMs of the novel NASA Earth Exchange Global Daily Downscaled Projections (NEX‐GDDP) under two Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios. (a) What will be the possible variability of future meteorological drought properties during the 21st century? (b) What will be the possible influence of temperature in modulating the drought properties? In order to answer the above questions, five different drought properties namely frequency, severity, duration, peak, and areal spread are analysed for future (2022–2099) using two meteorological drought indices such as Standardized Precipitation Index (SPI) and Standardized Precipitation‐Evapotranspiration Index (SPEI) for short (3‐month scale) and long (12‐month scale) term drought conditions. The essential outcomes from the study indicate a warming and wetting climate over Maharashtra during the 21st century. With an increase in monthly precipitation, severity and duration of future meteorological droughts are likely to decrease in long‐term drought condition. Conversely, in the short‐term condition, the properties are expected to increase. The drought properties like peak and areal spread are expected to increase for both short and long‐term drought conditions in most of the regions. Temperature plays a vital role in modulating the meteorological droughts, and the present study notices the same in most of the cases in all the drought properties, especially in drought severity, duration, and peak. All the division are identified as hotspot regions during the mid and later part of the 21st century for short‐term drought condition. The number of hotspot regions decreases in long‐term drought condition as compared to short‐term drought condition.