Abstract
Monitoring floods is a major issue in water resources management and risk mitigation, especially in the Global South. Optical and radar observations, even providing a fine spatial resolution, are still limited by cloud cover interaction or insufficient temporal resolution. On the other hand, passive microwave (PMW) sensors collect information on a daily frequency with minor cloud cover interaction, but they have been historically limited in terms of spatial resolution. Here, we evaluate the capability of an enhanced spatial resolution PMW dataset (3.125 km) in monitoring spatio-temporal evolution of flood events, focusing on a major flood event that occurred in October 2005 in Bangladesh. We apply an algorithm aimed to remove the seasonal variability of surface temperature from the PMW timeseries, exploiting the difference in emissivity between dry and water-covered pixels. We assess the capability of the algorithm in capturing flood evolution and extension through the comparison with quantities obtained from optical data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) and water level measurements. We also compare the enhanced product with the historical coarser resolution dataset by means of a variogram-based analysis to evaluate the improvements in terms of spatial representation. Finally, we evaluate the possibility to extract the water fraction within a single pixel by using an Advanced Microwave Scanning Radiometer—Earth Observing System (AMSR-E) emissivity dataset and compare the estimates with MODIS-derived water fractions. Our results show that the enhanced PMW product outperforms the coarser one when compared to flood mapped from optical data based on information content, indicating that it is possible to integrate such a product into the mapping of floods at a global scale on a daily basis.
Highlights
Introduction and Background iationsFlooding is a frequent hydrologic hazard, affecting everyday life and impacting social and economic systems, especially in the Global South
Our results show that the enhanced passive microwave (PMW) product outperforms the coarser one when compared to flood mapped from optical data based on information content, indicating that it is possible to integrate such a product into the mapping of floods at a global scale on a daily basis
We focus on an area in Bangladesh during a major flood event that occurred in October 2005
Summary
Flooding is a frequent hydrologic hazard, affecting everyday life and impacting social and economic systems, especially in the Global South. Structural and non-structural mitigation measurements should be based on proper knowledge of the spatial and temporal evolution of such devastating events. In this regard, the increase in the availability of radar and optical spaceborne data in recent years has allowed monitoring the spatial distribution and temporal evolution of floods with increased accuracy with respect to the previous decades [1–3]. Several major issues need to be addressed for properly capturing the spatio-temporal evolution of floods, especially in regions where in situ measurements and data infrastructures are not well developed and readily available, as in the Global South. While optical data are routinely collected at high spatial (~meters or tens of meters) and temporal (daily) resolutions, the presence of clouds within the acquired
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