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Frequency and intensity of extreme weather events are immensely changing throughout the world. This study aims to give insight into the changing climatic patterns leading to severe flood and drought conditions in the interior of Punjab province of Pakistan and devise adaptation strategies for risk governance. Landsat TM 30 m imagery was processed for flood analysis, while for drought analysis, Land Surface Temperature, Normalized Difference Vegetation Index (NDVI), and Temperature Vegetation Dryness Index (TVDI) were calculated from MODIS (MOD11A2 and MOD13A2) imageries. A questionnaire-based survey was conducted to prepare a management plan based on views of experts and local communities. The main regions affected by extreme events (flood and drought) in interior Punjab were Bahawalpur, Faisalabad, Mianwali, Multan, Sargodha, and Rahim Yar Khan. Supervised classification shows flooding in the Mianwali district during August 2010, and TVDI values show that drought prevailed during the year 2000 in the Bahawalpur district. Annual precipitation showed a significant trend in Sargodha and Mianwali with the magnitude of 6.95 mm/year and 2.97 mm/year, respectively. However, SPI moves to positive in the case of all studied districts except Sargodha where temperature change is 0.6 °C. Climatic analysis and survey show that the people of districts, i.e., Faisalabad, Mianwali, Multan, and Sargodha, were more affected by floods, whereas the people of districts, i.e., Bahawalpur and Rahim Yar Khan, were affected by both flood and drought. Adaptation strategies suggest that the flood water should be conserved which can help farmers in irrigation throughout the year. [ABSTRACT FROM AUTHOR]

Flooding is among the most catastrophic and common natural events. It not only endangers human lives, their livelihoods, and possessions but also devastates the nation’s economy. Increased flooding is an inevitable consequence of climate change. Hence, Identification of flood suspectable hotspots is vital for flood risk management along with disaster handling. The primary objective of this research is to use a frequency ratio model to classify flood-prone zones in two provinces of Pakistan. The flood inventory map was developed using 230 flood location points in Northern Sindh and Southern Punjab. Aspect, profile curvature, elevation, slope, normalized difference vegetation index (NDVI), normalized difference soil index (NDSI), distance from the road, distance from the river, land use/land cover (LULC) and rainfall were among the ten (10) determining factors. The data were randomly divided into two distinct datasets, with 70% flood points (161) used for inventory formulation and the other 30% (69 flood points) for result validation. The flood vulnerability map was categorized into five different zones ranging from very low (19.73%) to very high (20.37%) susceptibility range. The area under the receiver operating characteristic curve (ROC) and area under curve (AUC) was used to demonstrate the prediction result that yielded a reasonable score of 77.4%. The study suggested that in comparison to other studied districts, Jacobabad is the most prone region with acute vulnerability and constrained resilience. The presented data can serve as a source for tracking, assessing, and predicting potential flood activity in the area and could be beneficial for planners and decision-makers involved in early disaster response planning within the country. [ABSTRACT FROM AUTHOR]