Scholarlink

<p>Drought is a multifaceted and challenging natural disaster affecting areas all over the world. It poses recurring and serious challenges to agriculture, livestock, food security, water availability, public health, as well as environmental stability and resilience. Pakistan is one such country that has suffered recurring droughts year after year. This research focuses on examining and forecasting drought trends in three districts of the Bahawalpur division: Bahawalnagar (BHN), Bahawalpur (BHP), and Rahim Yar Khan (RYK). This study aims to evaluate spatial and temporal trends in drought occurrences based on remotely sensed data and climate data over the period 2012–2022. This study estimates drought patterns and analyzes their intensity to improve drought management and mitigation. Remote sensing data are analyzed through the cloud-based Google Earth Engine (GEE) platform to estimate various drought indices. The research applied the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) to calculate the Vegetation Condition Index (VCI), Temperature Condition Index (TCI), and Vegetation Health Index (VHI). The Palmer Drought Severity Index (PDSI) and Normalized Difference Water Index (NDWI) indices further support in determining the intensity of droughts and soil moisture in the study area. Moreover, future temperature forecasts for the areas are formed based on the ARIMA model, executed on the Google Colab platform in Python. The key findings of this research indicate that the years 2012, 2017, and 2022 were classified as drought years with high values of the drought index during the study period. According to the percentage area of VCI, the most severe drought was observed in 2017 (21.82%), followed by 2016 (17.99%) and 2012 (14.44%), respectively. Temperature modeling indicates a rising trend in temperature in both the Bahawalpur (BHP) and Rahim Yar Khan (RYK) districts. The general climate features of the Bahawalpur division depict extreme aridity, sparse vegetation, water shortage, and low population density. The conclusion reveals the challenges of preventing droughts across Pakistan and offers recommendations for policymakers and stakeholders on developing and regulating more effective strategies to reduce future drought events in South Punjab, Pakistan.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Spatial and temporal assessment of drought dynamics in Bahawalpur (Pakistan) using remote sensing and meteorological data

  • 期刊论文

  • 发表日期：

    2025年9月26日

查看全文
  • Muhammad Nasar-u-Minallah,
  • Nusrat Parveen,
  • Muhammad Farrukh Shahzad,
  • Rabia Tabassum

摘要

Drought is a multifaceted and challenging natural disaster affecting areas all over the world. It poses recurring and serious challenges to agriculture, livestock, food security, water availability, public health, as well as environmental stability and resilience. Pakistan is one such country that has suffered recurring droughts year after year. This research focuses on examining and forecasting drought trends in three districts of the Bahawalpur division: Bahawalnagar (BHN), Bahawalpur (BHP), and Rahim Yar Khan (RYK). This study aims to evaluate spatial and temporal trends in drought occurrences based on remotely sensed data and climate data over the period 2012–2022. This study estimates drought patterns and analyzes their intensity to improve drought management and mitigation. Remote sensing data are analyzed through the cloud-based Google Earth Engine (GEE) platform to estimate various drought indices. The research applied the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) to calculate the Vegetation Condition Index (VCI), Temperature Condition Index (TCI), and Vegetation Health Index (VHI). The Palmer Drought Severity Index (PDSI) and Normalized Difference Water Index (NDWI) indices further support in determining the intensity of droughts and soil moisture in the study area. Moreover, future temperature forecasts for the areas are formed based on the ARIMA model, executed on the Google Colab platform in Python. The key findings of this research indicate that the years 2012, 2017, and 2022 were classified as drought years with high values of the drought index during the study period. According to the percentage area of VCI, the most severe drought was observed in 2017 (21.82%), followed by 2016 (17.99%) and 2012 (14.44%), respectively. Temperature modeling indicates a rising trend in temperature in both the Bahawalpur (BHP) and Rahim Yar Khan (RYK) districts. The general climate features of the Bahawalpur division depict extreme aridity, sparse vegetation, water shortage, and low population density. The conclusion reveals the challenges of preventing droughts across Pakistan and offers recommendations for policymakers and stakeholders on developing and regulating more effective strategies to reduce future drought events in South Punjab, Pakistan.