Abstract
Coastal hazards, such as a tsunamis and storm surges, are a critical threat to coastal communities that lead to significant loss of lives and properties. To mitigate their impact, event-driven water level changes should be properly monitored. A tide gauge is one of the conventional water level measurement sensors. Still, alternative measurement systems can be needed to compensate for the role of tide gauge for contingency (e.g., broken and absence, etc.). Global Navigation Satellite System (GNSS) is an emerging water level measurement sensor that processes multipath signals reflected by the water surface that is referred to as GNSS-Reflectometry (GNSS-R). In this study, we adopted the GNSS-R technique to monitor tsunamis and storm surges by analyzing event-driven water level changes. To detect the extreme change of water level, enhanced GNSS-R data processing methods were applied which included the utilization of multi-band GNSS signals, determination of optimal processing window, and Kalman filtering for height rate determination. The impact of coastal hazards on water level retrievals was assessed by computing the confidence level of retrieval (CLR) that was computed based on probability of dominant peak representing the roughness of the water surface. The proposed approach was validated by two tsunami events, induced by 2012 Haida Gwaii earthquake and 2015 Chile earthquake, and two storm surge events, induced by 2017 Hurricane Harvey and occurred in Alaska in 2019. The proposed method successfully retrieved the water levels during the storm surge in both cases with the high correlation coefficients with the nearby tide gauge, 0.944, 0.933, 0.987, and 0.957, respectively. In addition, CLRs of four events are distinctive to the type of coastal events. It is confirmed that the tsunami causes the CLR deduction, while for the storm surges, GNSS-R keep high CLR during the event. These results are possibly used as an indicator of each event in terms of storm surge level and tsunami arrival time. This study shows that the proposed approach of GNSS-R based water level retrieval is feasible to monitor coastal hazards that are tsunamis and storm surges, and it can be a promising tool for investigating the coastal hazards to mitigate their impact and for a better decision making.
Highlights
Extreme waves such as tsunamis and storm surges have severely damaged coastal communities, including casualties and property losses
The average confidence level of retrieval (CLR) increased from 16.625 before the storm surge to 18.328 during the storm surge (00:00 February 12 to 12:00 February 13). These results show that this storm surge did not cause the performance degradation of the Global Navigation Satellite System (GNSS)-R based tide gauge, so the previously identified discrepancy with the tide gauge result from the long distance between the two sensors
The present study showed the feasibility of GNSS-R for monitoring tsunamis and storm surges
Summary
Extreme waves such as tsunamis and storm surges have severely damaged coastal communities, including casualties and property losses. The various countermeasures could not have protected the coastal communities perfectly every time For this reason, the monitoring techniques have been developed for early warning and post-event analysis. The tide gauge observations can be used to warn other coastal communities where the tsunami takes more time to reach. Storm surges accompanied by a storm cause an abnormal sea-level rise induced by wind stress and sea-surface pressure gradient [9] These cause critical inundation to coastal areas. GNSS-R detects the distance between a GNSS antenna and the water surface through a remote sensing technique that allows indirect measurements of water level variations over time.
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