Flood Hazard and Risk Assessment of Extreme Weather Events Using Synthetic Aperture Radar and Auxiliary Data: A Case Study

Abstract

The Greater Houston metropolitan area has experienced recurring flooding events in the past two decades related to tropical cyclones and heavy inland rainfall. With the projected recurrence of severe weather events, an approach that outlines the susceptibility of different localities within the study area to potential floods based on analyses of the impacts from earlier events would be beneficial. We applied a novel C-band Sentinel-1 Synthetic Aperture Radar (SAR)-based flood detection method to map floodwater distribution following three recent severe weather events with the goal of identifying areas that are prone to future flood hazards. Attempts were made to calibrate and validate the C-band-based results and analyses to compensate for possible sources of error. These included qualitative and quantitative assessments on L-band aerial SAR data, as well as aerial imagery acquired after one of the events. The findings included the following: (1) most urban centers of Harris county, with few exceptions, are not believed to be prone to flooding hazards in contrast to the densely populated areas on the outskirts of Harris county; (2) nearly 44% of the mapped flood-prone areas lie within a 1 km distance of major drainage networks; (3) areas experiencing high subsidence rates have persistently experienced flooding, possibly exacerbated by morphological changes to the land surface induced by subsidence.

Flood Extent Mapping During Hurricane Florence With Repeat‐Pass L‐Band UAVSAR Images

“…In addition, the backscattered signal of the smooth artificial impermeable flat surface, such as that found in urban areas characterized by urban sprawl, also makes it difficult to distinguish from open surface water (Shen, Anagnostou, et al., 2019; Shen, Wang, et al., 2019; Gebremichael et al., 2020). While we only used SAR collected during the flood event, it may be possible to correct this issue if pre‐event data is also available.…”

“…To the best of our knowledge, this is the first study to systematically examine temporal variations in hurricane‐induced riverine floods using UAVSAR. Moreover, there has only been few studies using UAVSAR data to estimate inundation extent after a hurricane event (Denbina et al., 2020; Gebremichael et al., 2020); however, it was based on a single day of data collection after Hurricane Harvey (2017). Thus, for the first time, we demonstrate UAVSAR's capacity to map temporal variations in flood inundation extents using daily time series of flood imagery.…”

Change Detection Techniques with Synthetic Aperture Radar Images: Experiments with Random Forests and Sentinel-1 Observations

“…When decorrelation caused by a specific event is coupled with temporal decorrelation from wind or rain, isolating the two different decorrelation sources becomes challenging. Tracking coherence differences between couples of SAR images has been exploited to study various phenomena (e.g., [103][104][105][106]). Some investigations address the problem of developing proper temporal decorrelation models that can be adopted to discriminate the background changes due to temporal decorrelation from those ascribed to the primary disastrous event.…”

Reservoir-Induced Land Deformation: Case Study from the Grand Ethiopian Renaissance Dam

“…Radar interferometry, for example, is a technique that uses multi-temporal radar images to infer topographic relief as well as subtle topographic changes. This technique has been successfully used to map and measure dam-induced land deformation [25][26][27], aquifer compaction from pumping [28], and land subsidence in urban areas [18,[29][30][31]. The Gravity Recovery and Climate Experiment (GRACE) and its successor, GRACE-Follow On (GRACE-FO), missions were used to derive large-scale land deformation as well as terrestrial water storage anomalies [32][33][34][35].…”