Impact Assessment of Agro-Meteorological Drought Using Geo-Spatial Techniques. A Case Study of Southeastern Sindh-Pakistan

Saira Batool; Syed Amer Mahmood; Jahanzeb Qureshi; Amer Masood; Maryam Muhammad Ali; Zainab Tahir

Authors

Saira Batool Centre for Integrated Mountain Research University of Punjab Lahore
Syed Amer Mahmood Department of Space Science, University of Punjab Lahore
Jahanzeb Qureshi Department of Space Science, University of Punjab Lahore
Amer Masood Department of Space Science, University of Punjab Lahore
Maryam Muhammad Ali Department of Space Science, University of Punjab Lahore
Zainab Tahir Department of Space Science, University of Punjab Lahore

Keywords:

Climate change, Cardiac Products, SPI, Remote sensing, NDVI, LST, SMI, Geospatial techniques

Abstract

The frequency of droughts is increasing as global temperatures rise. To effectively monitor drought conditions, it is crucial to use the appropriate index. In this study, the Standardized Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) were applied to evaluate droughts. The tool "DrinC" was used to calculate the RDI for 3-, 6-, and 12-month periods (Oct-Dec, Oct-March, and Oct-Sept) from 1981 to 2020. RDI values between -1.0 and -2.5 indicated moderate to extreme droughts across all districts. The RDI for 3, 6, and 12 months highlighted significant drought years, including 1984, 1992, 1994, 2010, 2011, 2015, and 2019, showing reduced productivity during these periods. Dry conditions were prevalent at most stations between 1981 and 2020. In South-Eastern Sindh, Pakistan, this study also assessed changes in Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), and Soil Moisture Index (SMI) over the last four decades (1981-2020). Satellite data analysis showed that NDVI peaked in 1988 (+0.53) and hit its lowest in 2021 (+0.48). Similarly, SMI ranged from +1.1 in 1988 to +0.98 in 2021, while LST increased from 35.1°C in 1988 to 53.4°C in 2021. A negative correlation between SPI and RDI was observed through linear regression, confirming the effectiveness of both indices in assessing drought severity. These findings can inform the development of drought preparedness plans, helping to mitigate the impact of drought on various economic sectors.

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