Abstract:
Pakistan is facing serious climate change issues, particularly vulnerability to
droughts and floods. Droughts are a recurring problem, and studying past droughts can
help in identify high-risk areas. This study addresses deficiencies in current drought
monitoring systems in South Punjab, Pakistan, and aims to improve it using a
straightforward approach that combines meteorological data, multi-indices, remote
sensing, and stochastic modelling. Meteorological parameters, particularly
precipitation and temperature, were investigated for their role in drought occurrence.
Comprehensive drought indices (SPI, RDI, SPEI) were integrated with remote sensing-
based indices (NDVI) for better monitoring. Using the DrinC and R programming,
drought indices were calculated, revealing an inverse relationship between rainfall and
potential evapotranspiration, identifying drought events. Analysis of drought trends
across different sites highlighted severity and variability. SPI and RDI indices showed
high correlation (R=0.99), emphasizing their effectiveness. SPEI results also exhibited
moderate positive correlation with the globally recognized SPEI database. To predict
precipitation and potential evapotranspiration, ARIMA and ETS models were used, and
the results were consistent with past trends in the meteorological drought risk maps.
Results may help in proactive planning against potential drought events. A
comprehensive drought risk classification map, integrating satellite and meteorological
parameters, offered a holistic view of agricultural and meteorological drought risk areas
in South Punjab. The study revealed that majority of South Punjab is at risk of drought
either agricultural or meteorological. Spatial distribution of risk levels indicates the
urgency for targeted interventions in areas facing extreme drought risk. Findings
contribute valuable information for policymakers, meteorological departments, and
relevant ministries to improve preparedness and mitigation strategies, ultimately
strengthening the region's resilience to drought events.
