Identification of Coastal Sand Deposits From Tsunamis and Storm Waves Based on Numerical Computations. Issue 7 (9th July 2021)

• Record Type: Journal Article
• Authors: Watanabe, Masashi; Goto, Kazuhisa; Roeber, Volker; Imamura, Fumihiko
• Is Part Of: Journal of geophysical research. Volume 126:Issue 7(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-07-09
• Subjects: identification of tsunami and storm deposits -- sediment transport -- numerical simulation; Geomorphology -- Periodicals; 551.3
• DOI: 10.1029/2021JF006092
• Languages: English
• ISSNs: 2169-9003

Abstract

Abstract: Tsunami and storm deposits can be utilized for estimating inundation zones and recurrence intervals of extreme waves in modern, historic, and prehistoric times. However, the distribution of these deposits is extremely complex and affected by various factors such as the size of the waves, topography, bathymetry, and the supply of sediment and its properties. Here, we use numerical computations to identify the key factors affecting the inundation extent of tsunamis and storm waves, and which subsequently govern the distribution of the corresponding coastal sand deposits. The results demonstrate that the overall topography slope has the most significant impact on the inundation extent of tsunamis and storm waves and subsequently the inland distribution distance of the transported deposits. The existence of onshore sediment sources is crucial for estimating the maximum extent of storm deposits because only a limited amount of sediment is carried inland by the storm waves. In contrast, the presence of onshore sediment sources is less critical for the delineation of the maximum distribution envelope of tsunami deposits compared to other parameters. The parameters that mainly control the sediment deposit volume over land under tsunami and storm wave conditions are the grain size and wave height, respectively. Our computed results are summarized using the Dean number, Shields number, and Iribarren number showing an inter‐connectivity between topography, input wave characteristic, and onshore distributions of both types of deposits. Despite some simplifications, this approach can efficiently lead to an identification and reconstruction of past catastrophic wave events. Key Points: Computational identification of parameters capturing the key processes affecting the distribution of tsunami and storm deposits Storm deposits are generally much smaller by their volume than tsunami deposits. This helps to identify the origin of the deposits Dimensionless numbers show that distributions of sediment deposits can be reconstructed based on wave and topographic conditions