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<p>Drought, a recurring natural phenomenon, poses significant challenges to water resource management and agricultural sustainability worldwide. This study examines meteorological drought characteristics in Punjab province, Pakistan, during 1991–2022 using the standardized precipitation index (SPI) and reconnaissance drought index (RDI). Drought severity was classified based on SPI and RDI thresholds (mild, moderate, severe, and extreme), enabling a systematic assessment across temporal scales. Statistical measures, including correlation (R) and Root Mean Square Error (RMSE), were employed to evaluate the consistency and accuracy of the indices. Various drought periods were identified across 3, 6, 9 and 12-month timeframes, confirming the presence of both short-term and long-term drought conditions. Extreme drought years in 1997 and 2002, severe drought in 1991, 2000, 2001, and 2005, and milder drought periods in 1993, 1999, and 2004 were identified. Strong correlations (R = 0.84–1) and low RMSE (0.03–0.085) values between SPI and RDI indices indicate their effectiveness in assessing long-term drought conditions. District-level analysis highlighted regional variability, where southern and central districts—such as Bahawal Nagar, Bahawal Pur, Multan, Muzaffargarh, Rajanpur, RYK, and Vehari—are more prone to drought due to consistently high maximum temperatures, limited rainfall, and elevated evaporation rates. Historical temperature and rainfall data from NASA Power were utilized, although limitations in spatial resolution and coverage were acknowledged. The novelty of this study lies in its combined application of SPI and RDI at multiple temporal scales with district-level resolution, providing region-specific insights for drought monitoring. The findings offer practical implications for developing localized drought management strategies and support broader climate change adaptation efforts in semi-arid regions. Future research should explore integrating additional datasets or satellite imagery for enhanced analysis, as well as incorporating socio-economic factors to better capture community vulnerability and resilience.</p>

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Statistical analysis of long-term climate variability and drought trends: a case study of Punjab province, Pakistan

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  • 发表日期：

    2026年1月31日

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  • Shoukat Ali Shah,
  • Songtao Ai,
  • Tahira Khurshid

摘要

Drought, a recurring natural phenomenon, poses significant challenges to water resource management and agricultural sustainability worldwide. This study examines meteorological drought characteristics in Punjab province, Pakistan, during 1991–2022 using the standardized precipitation index (SPI) and reconnaissance drought index (RDI). Drought severity was classified based on SPI and RDI thresholds (mild, moderate, severe, and extreme), enabling a systematic assessment across temporal scales. Statistical measures, including correlation (R) and Root Mean Square Error (RMSE), were employed to evaluate the consistency and accuracy of the indices. Various drought periods were identified across 3, 6, 9 and 12-month timeframes, confirming the presence of both short-term and long-term drought conditions. Extreme drought years in 1997 and 2002, severe drought in 1991, 2000, 2001, and 2005, and milder drought periods in 1993, 1999, and 2004 were identified. Strong correlations (R = 0.84–1) and low RMSE (0.03–0.085) values between SPI and RDI indices indicate their effectiveness in assessing long-term drought conditions. District-level analysis highlighted regional variability, where southern and central districts—such as Bahawal Nagar, Bahawal Pur, Multan, Muzaffargarh, Rajanpur, RYK, and Vehari—are more prone to drought due to consistently high maximum temperatures, limited rainfall, and elevated evaporation rates. Historical temperature and rainfall data from NASA Power were utilized, although limitations in spatial resolution and coverage were acknowledged. The novelty of this study lies in its combined application of SPI and RDI at multiple temporal scales with district-level resolution, providing region-specific insights for drought monitoring. The findings offer practical implications for developing localized drought management strategies and support broader climate change adaptation efforts in semi-arid regions. Future research should explore integrating additional datasets or satellite imagery for enhanced analysis, as well as incorporating socio-economic factors to better capture community vulnerability and resilience.