Observed changes in seasonal drought characteristics and their possible potential drivers over Pakistan

Abstract

Long‐term drought monitoring and its assessment are of great importance for meteorological disaster risk management. The recurrent spells of heat waves and droughts have severely affected the environmental conditions worldwide, including Pakistan. The present work sought to investigate the spatiotemporal changes in drought characteristics over Pakistan during Rabi and Kharif cropping seasons. The role of large‐scale circulation and interannual mode of climate variability is further explored to identify the physical mechanisms associated with droughts in the region. Monthly precipitation and temperature data (1983–2019) from 53 meteorological stations were used to study drought characteristics, using the standardized precipitation evapotranspiration index (SPEI). The nonparametric Mann–Kendall, Sen's Slope, and Sequential Mann–Kendall tests were applied on the drought index to determine the statistical significance and magnitude of the historical trend. The state‐of‐the‐art Bayesian Dynamic Linear model was further used to analyse large‐scale climate drivers of droughts, revealed an increase in drought severity, mostly over arid to semiarid regions for both cropping seasons. While temperature played a significant role in defining droughts over dry and hot seasons, rainfall is influential over the western disturbances influenced region. The analysis of atmospheric circulation patterns revealed that large‐scale changes in wind speed, air temperature, relative humidity, and geopotential height anomalies are the likely drivers of droughts in the region. We found that Niño4, sea surface temperature, and multivariate El Niño‐Southern Oscillation (ENSO4.0) Index are the most influential factors for seasonal droughts across Pakistan. Overall, the findings provide a better understanding of drought‐prone areas in the region, and this information is of potential use for mitigating and managing drought risks.

Observed Changes in Meteorological Drought Events during 1981–2020 over Rwanda, East Africa

“…In some areas, the severity and frequency of droughts can lead to water scarcity conditions, whereas overexploitation of existing water resources can worsen the effects of droughts [85]. Various studies demonstrate that drought is among the most dangerous distractive disaster in the current warming world [86][87][88][89], impacting natural resources such as sustainable water and environment, agriculture, ecology, and biodiversity [79,[90][91][92]. The present study shows that drought occurrences are increasing, which may lead to severe impacts on water resources and agriculture management in a country with a high population density like Rwanda.…”

Spatiotemporal Rainfall Variability and Drought Assessment during Past Five Decades in South Korea Using SPI and SPEI

“…The daily precipitation and temperature datasets were summed to create the monthly and annual datasets. The standardized normalized homogeneity test (SNHT) was used to find the peaks and outliers in the data [49]. During data quality evaluation, it was found that only 2-3% of the data were missing which would not have a substantial impact on the results [49]; however, we still replaced the missing data with the average values of the nearby meteorological stations to maintain the quality [48].…”

“…The standardized normalized homogeneity test (SNHT) was used to find the peaks and outliers in the data [49]. During data quality evaluation, it was found that only 2-3% of the data were missing which would not have a substantial impact on the results [49]; however, we still replaced the missing data with the average values of the nearby meteorological stations to maintain the quality [48]. Next, we calculated the descriptive statistics in XLSAT Adin of Excel software, the details of which are presented in Table 3.…”

Comparison of Multi-Year Reanalysis, Models, and Satellite Remote Sensing Products for Agricultural Drought Monitoring over South Asian Countries

“…The use of such indices is regarded as an ingenious standardized approach based on precipitation scarcity [68]. The SPI is the most important and frequently used index for drought monitoring [15,[70][71][72][73]. This index computes a gamma probability distribution function for a precipitation time series.…”