Disaster Mapping and Assessment of Pakistan’s 2022 Mega-Flood Based on Multi-Source Data-Driven Approach

Abstract

Abstract Climate change-induced mega floods have become increasingly frequent worldwide. The rapid mapping and assessment of flood disasters poseurgent challenges for developing countries with poor data facilities or databases. In this study, the characteristics of the 2022 mega-flood in Pakistan were monitored and analyzed based on multi-resources data. The extent of inundation throughout Pakistan and its impact on farmlands, buildings, and roads were mapped using Synthetic Aperture Radar (SAR) remote sensing data processing technology. The results showed that a10-meter resolution flooding map could be achieved using the Google Earth Engine (GEE) platform in a timely manner with reasonable precision. A GIS-based bluespot model was used to evaluate the risk of dam-failure floods. The zone risk distribution map of the dam-failure flood was produced with five risk levels, which contribute to the safety of the key infrastructure for flooding control. The driving forces of snow melting in northern Pakistan induced by heat wavesand disasters was detected using Earth observationsand long-record historical data. Five aspects of flood prevention and control recommendations were characterized, providing a reference for developing countries to cope with flood disasters under worsening climate change conditions.