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Ritphring, S.; Somphong, C.; Udo, K., and Kazama, S., 2018. Projections of future beach loss due to sea level rise for sandy beaches along Thailand's coastlines. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 541–545. Coconut Creek (Florida), ISSN 0749-0208. Coastline recession caused by sea level rise due to climate change has become one of the most significant issues worldwide. Thailand's coastlines is also likely to face erosion, especially in the low-lying areas, and its future projection due to sea level rise is necessary. This study compiled a database of beach characteristics, including grain size diameter, beach slope and beach width, to assess the projections of future beach loss along Thailand's coastlines against sea level rise scenarios of the Coupled Model Intercomparison Project Phase 5 (CMIP5) in 2081–2100, relative to a reference period 1986–2005 by using the Bruun rule. Future national beach loss rates were projected to be 45.8% for RCP2.6, 55.0% for RCP4.5, 56.9% for RCP6.0 and 71.8% for RCP8.5. In addition, the rate against the sea level scenarios projected by each CMIP5 model for RCP4.5 ranges from 49.1% for MPI-ESM-LR to 73.4% for MIROC-ESM-CHEM. Based on the current beach situation, sandy beaches in 8 and 23 out of 51 zones will disappear for RCP2.6 and RCP8.5, respectively. These findings will help governors and stakeholders develop adaptation strategies against beach loss due to sea level rise.

Thailand plays a central economic and policy-making role in Southeast Asia. Although climate change adaptation is being mainstreamed in Thailand, a well-organized overview of the impacts of climate change and potential adaptation measures has been unavailable to date. Here we present a comprehensive review of climate-change impact studies that focused on the Thai water sector, based on a literature review of six sub-sectors: riverine hydrology, sediment erosion, coastal erosion, forest hydrology, agricultural hydrology, and urban hydrology. Our review examined the long-term availability of observational data, historical changes, projected changes in key variables, and the availability of economic assessments and their implications for adaptation actions. Although some basic hydrometeorological variables have been well monitored, specific historical changes due to climate change have seldom been detected. Furthermore, although numerous future projections have been proposed, the likely changes due to climate change remain unclear due to a general lack of systematic multi-model and multi-scenario assessments and limited spatiotemporal coverage of the study area. Several gaps in the research were identified, and ten research recommendations are presented. While the information contained herein contributes to state-of-the-art knowledge on the impact of climate change on the water sector in Thailand, it will also benefit other countries on the Indochina Peninsula with a similar climate.

Studies have indicated that submarine landslides played an important role in the 2018 Sulawesi tsunami event, damaging the coast of Palu Bay in addition to the earthquake source. Most of these studies relied on observed coastal subaerial landslides to reproduce tsunamis but could still not fully explain the observational data. Recently, several numerical models included hypothesized submarine landslides that were taken into account to obtain a better explanation of the event. In this study, for the first time, submarine landslides were simulated by applying a numerical model based on Hovland's 3D slope stability analysis for cohesive–frictional soils. To specify landslide volume and location, the model assumed an elliptical slip surface on a vertical slope of 27 m of mesh-divided terrain and evaluated the minimum safety factor in each mesh area based on the surveyed soil property data extracted from the literature. The soil data were assumed as seabed conditions. The landslide output was then substituted into a two-layer numerical model based on a shallow-water equation to simulate tsunami propagation. The tsunamis induced by the submarine landslide that were modeled in this study were combined with the other tsunami components, i.e., coseismal deformation and tsunamis induced by previous literature's observed subaerial coastal collapse, and validated with various post-event field observational data, including tsunami run-up heights and flow depths around the bay, the inundation area around Palu city, waveforms recorded by the Pantoloan tide gauge, and video-inferred waveforms. The model generated several submarine landslides, with lengths of 0.2–2.0 km throughout Palu Bay. The results confirmed the existence of submarine landslide sources in the southern part of the bay and showed agreement with the observed tsunami data, including run-ups and flow depths. Furthermore, the simulated landslides also reproduced the video-inferred waveforms in three out of six locations. Although these calculated submarine landslides still cannot fully explain some of the observed tsunami data, they emphasize the possible submarine landslide locations in southern Palu Bay that should be studied and surveyed in the future.

A recent study suggested that significant beach loss may take place on the coasts of Thailand by the end of the 21st century as per projections of sea-level rise by the Intergovernmental Panel on Climate Change (IPCC). The present study adapts a framework and provides broad estimations for sand volumes and costs required to apply beach nourishment to each coastal zone in Thailand using a technique based on the Bruun rule assumption. Results indicate that a minimum of USD 2981 million (the best scenario) to a maximum of USD 11,409 million (the worst scenario) would be required to maintain all sandy beaches at their present width. Further, the effect of filling particle size on beach nourishment was analyzed in this study. The cost of beach nourishment ranges between USD 1983 and 14,208 million when considering filling particle size diameters of 0.5 and 0.2 mm. A zonal sand volume map for all 51 sandy beach zones in Thailand was created for use as an overview to help decision makers develop a more feasible adaptation plan to deal with the future sea-level rise for Thailand.

Coastal erosion and inundation represent the main impacts of climate change and the consequential sea level rise (SLR) on beaches. The resultant deterioration of coastal habitats and decline in beach tourism revenue has been a primary concern for coastal managers and researchers. Nevertheless, the extent of SLR on beach tourism in Egypt remains relatively unknown. Therefore, this study investigates the relationship between beach width shrinkage due to SLR and the loss in tourist resort revenue. We use the hedonic pricing approach, which combines economic and environmental variables, to determine the environmental impact on beach tourism along 14 km of the coast of Sahl Hasheesh and Makadi Bay, Hurghada, Egypt. The resort revenue depends on the cumulative benefits from the market price of the resort rooms, which is a function of morphological variables and tourism variables. Three regression models (semi-log, double-log, and custom-log) were used to select the most appropriate functional hedonic model. Three coastal slopes were considered (0.03, 0.06, and 0.12) to address the uncertainty in beach width. When 0.06 coastal slope is used, the expected losses in revenue are 84,000, 220,000, and 546,000 USD/day period (representing 3%, 7%, and 18%) for 2030, 2050, and 2100, respectively, considering the lowest scenario representative concentration pathway (RCP2.6); for the worst case (RCP8.5 SLR), the expected losses are 142,000, 369,000, and 897,000 USD/day period (representing 5%, 12%, and 30%) for 2030, 2050, and 2100, respectively.