Capability of ASCAT and ASAR, C-band active microwave sensors, for monitoring of extreme flood and drought events in lower Mekong countries

Kurzfassung

The Mekong River is the longest river in Southeast Asia with a drainage basin of 795,000 km². It rises in the Tibetan highlands and flows through six states, the southeast Chinese province of Yun-Nan, Myanmar, Laos, Thailand, Cambodia and Vietnam. The climate of the Mekong region is influenced by the Southwest and Northeast monsoons. The strong seasonal variation in rainfall leads frequently to extreme flood and drought conditions. Occurrences of large-scale and long-lasting floods alternating with periods of drought and water shortage significantly affect the people living in Mekong watershed and cause severe economic and civil damages. Therefore accurate information on the frequency and the extent of extreme events is critical for preparedness, prevention and management of the disaster. Satellite remote sensing has become valuable for monitoring surface parameters related to floods and droughts by providing comprehensive and multi temporal coverage of large areas. The active microwave sensors have proven to be applicable instruments for monitoring of surface water and soil moisture due to high sensitivity of radar signal to water. One of the major advantages of active sensors is that they can acquire imagery regardless of solar illumination during day and night and unimpeded by cloud cover, with the latter being of special importance during rainy periods, when wetlands are often easier to discriminate but mostly clouded. In this study we use the backscatter and soil moisture information extracted from the C-band Advanced SCATterometer (ASCAT) onboard Metop and the Advanced Synthetic Aperture Radar (ASAR) onboard Envisat to demonstrate the capability of active sensors for monitoring flood and drought events in lower Mekong region. The method is based on anomaly detection and threshold analysis of backscatter and its relative noise for detection of extreme dry, wet and inundated conditions. It is shown that the analysis of ASCAT backscatter noise helps to remove ambiguities in low backscatter domain for discrimination between extremely dry soil and inundated surface. The results show the potential of active sensors for change detection of surface water bodies and monitoring of soil moisture dynamics in the Mekong region which has applications in agriculture, hydrology, and disaster management.