Coastal Disasters Research Articles

Dynamic Changes in Coastal Geomorphology of Shiroda Coasts, using Remote Sensing and GIS: An Approach to Climate Change and Coastal Disaster Risk

The coastline is a unique land feature formed through the interaction between land and sea. It is essential to monitor and detect hotspots and observe spatial and temporal influences of climate change in the coastal environment. Coastal landform changes can be best studied through remote sensing data. This study examines the dynamic changes in the sand spit and associated coastal area of the Shiroda coasts of Sindhudurg district. The Normalized Difference Water Index (NDWI) was used to distinguish land and water and the area was calculated by reclassifying the NDWI index of all images with two classes- land surface of sand spit and water. It was found that the spit area is decreasing seasonally at a dynamic rate. Additionally, geomorphic maps were prepared for the study area and showed disastrous changes in the coastal landforms. It is a need that coastal communities worldwide must address the challenges of coastal flooding and rising sea levels caused by climate change. Climate change is causing uneven rainfall distribution, storms and cyclones, leading to coastal erosion, flooding and landform damage. Additionally, it has a negative impact on the geomorphic features of coastlines.

Increasing compound hazard of landfalling tropical cyclones in China during 1980–2020

AbstractIdentifying the geographical regions where tropical cyclone (TC) activities are changing most is critical for policymakers to develop long‐term strategies for coastal disaster prevention. However, the key concerns for assessing the variation trends of the regional hazard caused by landfalling TCs are limited by data availability in the spatio‐temporal coverage and homogeneity. In this study, based on the high spatio‐temporal resolution ERA5 reanalysis data and a quasi‐Lagrangian approach, we investigate the long‐term variation trend of the compound hazard resulting from wind and precipitation during the landfall of the TCs in the coastal areas of China from 1980 to 2020. Two hotspot areas of TCs hazards are identified, one in the Taiwan Strait and surrounding areas, and the other in the Hainan Island and the northern South China Sea. The observed compound hazard in the former hotspot area shows a noticeable increasing trend over the past 40 years at a rate of 5% per year, while the latter hotspot area displays a robust decreasing trend. This variation pattern of the hazard trend is mainly attributed to the increased frequency of intense TCs (typhoon intensity grade and above) and the northward movement of TC track in China. The number of intense landfalling TCs in southeastern China nearly tripled in 2000–2019 compared to those in 1980–1999. The widespread increase in the compound hazard also suggests a rise in the disaster risk for the middle‐ and high‐latitude coastal regions of China, which require an immediate development and execution of advanced prevention strategies.

EVALUATION OF STORM SURGE BEHAVIOR DUE TO DIFFERENT TYPHOON TRACKS AND WIND SPEEDS ALONG THE COAST OF DAGUPAN CITY, LINGAYEN GULF, PHILIPPINES

Every year, an average of 19.4 typhoons traverse the Philippine Area of Responsibility and the country receives around nine landfalling typhoons. These typhoons can generate storm surges along the coasts and cause inundation of coastal communities. Dagupan City is a low-lying city located along the coast of Lingayen Gulf where 30% of its population live in the coastal barangays. As a coastal community located along the head of the Lingayen Gulf where the bathymetry is shallow, Dagupan city is susceptible to storm surges. This study aims to evaluate the storm surge behavior due to different typhoon tracks and windspeeds along the coast of Dagupan City. To achieve this objective, this study implements numerical simulation of storm surges using the Advanced Circulation (ADCIRC) model. A simple methodology is employed by selecting representative historical typhoons and creating synthetic typhoons by shifting the tracks along the latitude. Simulations of typhoons with different typhoon tracks reveal the critical tracks that give highest storm surges in Dagupan City. Finally, storm surges are simulated for windspeed intensities of 60, 80 and 100 knots which are applied to the identified critical tracks. The results of this study show that shifting the typhoon tracks affects the magnitude of storm surges in Dagupan City. Generally, the tracks that pass near the center of Lingayen Gulf generate the highest storm surge along the coast, however, eastward synthetic tracks near the mouth of the gulf can also potentially produce storm surges in Dagupan City. In addition, it is found that typhoon tracks coming from the West Philippine Sea can generate higher storm surges in Dagupan City compared to tracks from the Pacific Ocean. The highest storm surge generated by the representative historical typhoon is 1 m produced by Typhoon Vicki 1998 while a storm surge of 2 m could be potentially generated along Dagupan City by a typhoon with windspeed of 100 knots. The results of this study can be helpful in predicting storm surges for different typhoon tracks and windspeeds which can be used for coastal disaster preparedness in Dagupan City.

A Convolutional Neural Network with Spatial Location Integration for Nearshore Water Depth Inversion.

Nearshore water depth plays a crucial role in scientific research, navigation management, coastal zone protection, and coastal disaster mitigation. This study aims to address the challenge of insufficient feature extraction from remote sensing data in nearshore water depth inversion. To achieve this, a convolutional neural network with spatial location integration (CNN-SLI) is proposed. The CNN-SLI is designed to extract deep features from remote sensing data by considering the spatial dimension. In this approach, the spatial location information of pixels is utilized as two additional channels, which are concatenated with the input feature image. The resulting concatenated image data are then used as the input for the convolutional neural network. Using GF-6 remote sensing images and measured water depth data from electronic nautical charts, a nearshore water depth inversion experiment was conducted in the waters near Nanshan Port. The results of the proposed method were compared with those of the Lyzenga, MLP, and CNN models. The CNN-SLI model demonstrated outstanding performance in water depth inversion, with impressive metrics: an RMSE of 1.34 m, MAE of 0.94 m, and R2 of 0.97. It outperformed all other models in terms of overall inversion accuracy and regression fit. Regardless of the water depth intervals, CNN-SLI consistently achieved the lowest RMSE and MAE values, indicating excellent performance in both shallow and deep waters. Comparative analysis with Kriging confirmed that the CNN-SLI model best matched the interpolated water depth, further establishing its superiority over the Lyzenga, MLP, and CNN models. Notably, in this study area, the CNN-SLI model exhibited significant performance advantages when trained with at least 250 samples, resulting in optimal inversion results. Accuracy evaluation on an independent dataset shows that the CNN-SLI model has better generalization ability than the Lyzenga, MLP, and CNN models under different conditions. These results demonstrate the superiority of CNN-SLI for nearshore water depth inversion and highlight the importance of integrating spatial location information into convolutional neural networks for improved performance.

Dike risk evaluation incorporating the contribution of coastal wetlands: A case study on Chongming Island, China

Due to the increasing risk of coastal disasters and climate change, the traditional gray sea dikes may become unsustainable. Coastal wetlands provide natural protection for shoreline areas and have wave attenuation capacities as green dikes. In this study, we developed a new assessment approach to evaluate comprehensive dike risk for coastal gray-green defense systems, based on the dike characters and the wave attenuation capacity of coastal wetlands for the Chongming Island. The risk assessment system consists of nine indicators of dike constructure standards, dike-top height, land subsidence, wetland vegetation width, wave attenuation capacity of vegetation, mean high water level, storm frequency, rain intensity, and annual rainfall, to determine the dike risk index (RI). The information of dike and meteorological conditions were obtained by carrying out a field survey and referring to construction bulletins and domestic statistical yearbooks. The wave attenuation effect of wetland vegetation was characterized by plant morphology and seasonality. The results indicated that, without the coastal wetland indicators, the RI values of most parts of the dike ring of the island were high. The high-risk regions were mainly located in the south and north shores, consisting of several old dikes that did not meet the constructure standard. The risk level was higher in summer and autumn than in winter and spring, due to seasonal variations (typhoon or storm frequency and intensity). When the coastal wetland indicators were included, the presence of coastal wetland vegetation reduced the dike RI values by an average of 13.6% around the Chongming Island. During the flourishing periods of the vegetation, a high rate of wave attenuation reduced the RI levels considerably. We provide a reliable framework to carry out large-scale and high-resolution dike risk assessment to be applied for wetland vegetation restoration, green dike construction, and risk management in coastal areas.

Return Level Estimation in Spatial Extreme Value Modeling of Bali Sea Currents Velocity using The Smith and Brown-Resnick Max-Stable Process Approach

Bali is the world's second most popular tourist destination in 2023. One of the best tourisms is the beauty of its coasts. Even though it is the best tourism destination, it is not uncommon for disasters to occur in the coastal areas of Bali. One important factor in the occurrence of coastal disasters from waters such as tidal flooding and abrasion is ocean currents. Spatial analysis of sea currents velocity was carried out using the Smith and Brown-Resnick Max-Stable Process Approach. The purpose of this study was to determine parameter estimation and comparison of the results of Spatial Extreme Value modeling with the Smith and Brown-Resnick Max-Stable Process approach, and to determine the Return Level of Bali Sea current velocity for the same period after data testing with the best model. The data used is daily data for the period March 2, 2017 to December 30, 2020. Extreme data selection with Block Maxima uses 14 daily blocks, so there are 100 blocks for each water location. The proportion of training and testing data is 80:20. The training data follows the Generalized Extreme Value distribution and has no pattern trend (stationary). The results of the extremal coefficient measurements ranged from 1.18604 to 1.59485 indicating a fairly strong dependency between locations. The best trend surface model is a model that only has longitude coordinates on the location parameter and latitude on the scale parameter. The estimated value of the spatial parameters of the Smith model tends to be greater than that of the Brown-Resnick model. The Root Mean Square Error and Mean Absolute Percentage Error for the Smith model are 0.15503 and 7.75076%. Meanwhile, the Brown-Resnick model is 0.29576 and 14.12131%. Return Level values for the same period after data testing are classified as strong currents and are respectively 1.20586 m/s, 1.63592 m/s, 1.51322 m/s and 2.13233 m/s for Serangan, Gianyar, Nusa Dua, and Nusa Lembongan Waters. Information on estimated Return Levels is expected to be a consideration that can be used by related agencies such as the Coastal and Marine Resources Management Agency (BPSPL) and the Bali Province Regional Disaster Management Agency (BPBD) as a coastal disaster mitigation effort to make it more effective, efficient and on target.

UTILISING GEOSCIENTIFIC INSIGHTS INTO PAST COASTAL HAZARD EVENTS FOR COASTAL ENGINEERING

People, infrastructure and ecological systems at the coast are vulnerable to several coastal hazards, most of which have, or will, become more serious with changing climate. Climate change is likely to affect rainfall and climate patterns, potentially intensifying and changing seasonal patterns and frequency of storms. Sea-level rise associated with climate change will also impact much of the coastal zone. Despite the threat of coastal disasters, and the projections of increasing hazards under a changing climate, coastal engineering development must continue unabated, leaving many communities at risk of catastrophic losses. For most cities historical events indicate a considerable risk and all coastal communities must live with a certain risk of coastal hazards, but informed coastal engineering can minimize the potential for fatalities and economic loss, and therefore must be undertaken. Here I investigate storms and tsunamis and 1. address the options for obtaining longer records of events and 2. examine the need for incorporating uncertainties of future changes in climate, sea level and and coastal environments.

Mapping The Potential of Mangrove Planting in The Rehabilitation of Coastal Ecosystems Using Drone Technology

Mangroves, as one of the vegetation types that is a natural stronghold from coastal disasters, also function as a shelter and find food for various biota in coastal ecosystems. Therefore, protecting the mangrove ecosystem from degradation is very important. One effort that needs is ecosystem rehabilitation through mangrove planting in coastal environments. To support it, a design was devised using drones and remote-sensing vehicles to assist in making mangrove planting designs. This research was conducted in Jenggalu Estuary, Gading Cempaka District, Bengkulu City. This research aims to study the use of drones in mapping potential mangrove planting areas and designing a mangrove planting plan to rehabilitate coastal ecosystems. In mapping using drones, the height used was 80 meters with 80% overlap, and 2.87 hectares of potential mangrove planting area was obtained. Based on the research results, drones in mapping are very useful in calculating the area of potential mangrove planting areas and designing effective planting plans. There are four scenarios for planting mangroves with a spacing of 0.5 m, 1 m, 2 m, and 3 m, respectively. For a planting area of 2.87 ha, the number of seeds needed is 114,800 planting points for a distance of 0.5 m, 28,700 planting points for a distance of 1 m, 7,175 planting points for a distance of 2 m, and 3,189 planting points for a distance of 3 m

Mangroves Addition as Innovation for Sustainable Tourism

Grand Maerokoco is a tourist site in Semarang, located close to Marina beach. The presence of mangroves in Maerokoco, is expected to protect it from the coastal disaster, as well as to make it as a new attraction. This study assessed the benefits of mangroves addition in Grand Maerokoco according to visitor perception, economic valuation toward mangrove plantation in there, and its ability to reduce noises. Visitor perception could be known by conducting interviews. Economic valuation measurement employed was TCM (Travel Cost Method). Then for determining the ability to reduce noises, a noise measurement using sound level meter was conducted. Based on visitor perception, existence of mangroves in Grand Maerokoco can increase the attraction, increase the number of visitors, make the air cooler and cleaner, reduce the noise, and prevent the entry of coastal floods. The existing noise known at some point of crowds is still below the threshold standards of the EPA (Environmental Protection Agency), caused by mangroves in Maerokoco are high and dense. The potential consumer surplus value per individual per visit is Rp717,792.00. The value indicates the visitors get the benefits of environmental services greater than the cost incurred. For increasing the values, utilizing mangroves for education and agribusiness functions, along with maintenance should be done. 

Assessment of social factors that promote the vulnerability of communities to coastal hazards in the Volta estuary in Ghana

Although vulnerability assessments have been widely conducted along the coast of Ghana, they have not focused on the factors contributing to social vulnerability of households and communities to disaster risks. Using an indicator-based approach, this study examines the social factors that affect the exposure, sensitivity and adaptive capacity of households and communities in the Volta estuary, Ghana. Results indicate that all the communities within the study area were exposed to climate change related hazards. However, two communities, Azizanya in Ada East District and Fuveme in Anloga District, were highly exposed with unweighted indexes of 0.50 and 0.76, respectively. Sensitivity among communities was generally high ranging from 0.00 to 0.87 due to several social factors including low household income, high number of children and aged at home, and lack of social amenities such as roads, health facilities, markets, and schools. The communities recorded high adaptive capacity and were able to withstand the ravages of the ocean and the river system. Households and communities developed various adaptation measures such as relocation to nearby communities or higher grounds, open spaces and packing of their belongings on higher objects such as tables, whiles government actions included occasional dredging and constructions of sea defense structures. An integrated, multi-stakeholder approach involving government, non-governmental community-based organisations, communities, households, and other stakeholders is proposed to design and implement a comprehensive disaster management plan to combat climate change related coastal disasters.

Solitary wave attenuation characteristics of mangroves and multi-parameter prediction model

Mangroves contribute to wave attenuation and improve coastal disaster prevention. Extensive studies have been conducted to explore wave attenuation by mangroves using rigid cylinders. However, few studies have investigated interactions between solitary waves and mangroves with roots. Therefore, laboratory experiments are conducted to investigate wave dissipation along a 1:10 scale Rhizophora mangrove forest under solitary waves, and wave attenuation characteristics are analyzed to highlight the significance of the effects of mangrove roots on wave damping. A numerical model of mangrove with roots is conducted by combining cylinder and porous media, where the trunk is considered as a cylinder and roots are simulated by introducing the resistance source term and porosity effect into the momentum equation. Results show that wave parameters (still water depth and incident wave height) and a vegetation parameter (vegetation submerged projected area) are the dominant variables affecting wave attenuation. In addition, multivariate nonlinear regression, genetic programming, and back propagation (BP) neural network are employed to explore the relationship between the wave attenuation coefficient and other related dimensionless parameters. Results show that the BP model is more accurate in predicting the wave attenuation coefficient as compared with other methods and thus can predict solitary wave attenuation in mangrove forests.

Beach Conditions for Guiding the Sandy Beach Management in Phuket, Thailand

Thailand’s current beach management strategies lack integration across sectors, resulting in conflicts of interest and insufficient consideration of diverse beach uses. The complexity of environmental, socio-economic, and coastal disasters challenge policymakers to describe the conditions of sandy beaches, and the most effective coastal management adaptation measures. This study suggests an integrated approach to evaluate beach conditions by incorporating the Urbanization Index, Conservation Index, and Recreation Index. Furthermore, the assessment of beach conditions will include the Threat Index, which consists of erosion rates and shoreline recession caused by sea level rise. The trends index will prioritize beach conditions for appropriate management actions. The study suggests management strategies that aim to preserve the physical and environmental aspects of the beach, while restoring its functionality for ecosystem services by applying engineering structures with beach nourishment. The main purpose of this study is to develop a beach condition that can be used as a guideline for sandy beach management in Thailand. It provides insights and recommendations to policymakers for enhancing the sustainability and resilience of Thailand’s coastal areas in the face of urbanization and climate change.

Wave climate characteristics and effects of tropical cyclones on high wave occurrences in Indonesian waters: Strengthening sea transportation safety management

Tropical cyclones can cause bad weather and high waves that can endanger maritime activities, especially in the waters of Indonesia, which is a maritime country. Understanding ocean wave climate characteristics and the effect of Tropical Cyclones (TCs) on high wave occurrences is important, particularly to ensure the safety of fisheries activities in Indonesian seas. We aim to do so by focusing on Indonesia's 11 Fisheries Management Areas (IFMAs) using descriptive and inferential statistics. Wind and wave data were taken from the European Center for Medium-Range Weather Forecast (ECMWF), namely ECMWF Reanalysis v5 (ERA5) within the range of 42 years (1979–2020), whereas the TC data were from the International Best Track Archive for Climate Stewardship (IBTrACS). We found that significant wave heights (SWHs) in the inner seas are strongly related to monsoonal wind fields. The maximum SWH occurred in northern Indonesian seas during December–February (DJF), while occurring in southern and inner seas between June–August (JJA). The highest extreme SWH and probability of exceedance (PE) for SWH >2 m were found in IFMAs facing the open ocean, such as Malacca Strait, Western Sumatra waters, Southern Java waters, Natuna Sea, Sulawesi Sea, and Northern Papua waters. We found that TCs activity in adjacent Indonesian waters could increase anomalous SWH occurrences. Positive SWH anomalies ranged from 0.1 to 0.4 m and varied depending on TC location and season. TC that forms in the following areas increase the PE for SWH >2 m: (1) Bay of Bengal: Western Sumatra waters (March–May, MAM) around 20%; (2) Western Pacific Ocean: Northern Papua waters (DJF) around 5%; (3) Northeastern Indian Ocean: Western Sumatra waters (DJF) about 3%; and (4) Western and Northern Australian waters: Southern Java waters (DJF) about 20%. The results of this study can serve as an early assessment for investigating wave climate characteristics and identifying the areas in Indonesian waters that are most susceptible to the impact of TCs, particularly in IFMAs. These findings hold significant value for managers and policy authorities, such as the Ministry of Transportation and the Ministry of Marine Affairs and Fisheries of the Republic of Indonesia. They can utilize this information to develop measures aimed at reducing vulnerabilities among marine resource users, specifically fishers, and improving fishing vessel safety. Additionally, these findings can be utilized to enhance advance warnings and forecasts, enabling marine managers to implement strategies that minimize the impact of extreme events and increase resilience in the face of ocean and coastal disasters.

Prediction of wave overtopping discharges at coastal structures using interpretable machine learning

ABSTRACT Appropriate estimation and prediction of wave overtopping discharges are very important in terms of economics, port structure stability, and port operation. In recent years, machine learning (ML) techniques, which predict by finding statistical structures from input/output data using computers, have generated interest. However, as the complexity of ML models increases, interpreting their results becomes increasingly difficult. Interpretation of ML results is an important part in developing an efficient structure design strategy for improved wave overtopping discharge estimation. Therefore, in this study, eight linear/nonlinear ML models were applied to the same data, and a pipeline model for selecting an ML model suitable for data characteristics was developed. In addition, the importance of variables related to the prediction of wave overtopping discharges and their correlations were analyzed by interpretable ML. The research results showed that the extreme gradient boosting model had the highest prediction accuracy and significantly reduced the error. Accordingly, a data-based model can be a new alternative for analyzing the complex physical relationships in the field of coastal engineering and used as a starting point toward structure design and development for coastal disaster prevention.

Land Use/Land Cover Optimized SAR Coherence Analysis for Rapid Coastal Disaster Monitoring: The Impact of the Emma Storm in Southern Spain

The high exposure of coastal areas worldwide to natural and anthropogenic disasters emphasizes the relevance of disaster management processes that ensure a prompt damage detection and identification of affected areas. This paper aimed to develop a novel approach for disaster monitoring in coastal areas using SAR data. The method was based on an interferometric coherence difference analysis of Sentinel 1 data. To calibrate and validate the method, the Emma Storm, a severe coastal storm that affected the southwest coast of the Iberian Peninsula in 2018, was chosen as a case study. A coastal land use/land cover method optimization by optical and UAV field data resulted in an overall improvement of about 20% in the identification of disaster-affected areas by reducing false alarms by up to 33%. Finally, the method achieved hit and false alarm rates of about 80% and 20%, respectively, leading to the identification of approximately 30% (7000 ha) of the study area as being affected by the storm. Marshes and vegetated dunes were the most significantly impacted covers. In addition, SAR data enabled the impact assessment with a time lag of 2 days, contrasting the 25-day delay of optical data. The proposed method stands out as a valuable tool for regional-scale coastal disaster monitoring. In addition, it can be automated and operated at a low cost, making it a valuable tool for decision-making support.

Experimental Investigations Using Computer Vision for Debris Motion Generated by Solitary Waves

A tsunami created by the momentary release of a large amount of energy accumulated in the ocean crust destroys coastal structures and generates considerable debris, posing a serious threat to coastal communities. Hence, understanding the movement characteristics of drifting attributed to tsunamis for coastal disaster prevention is necessary. In this study, a color-based Debris mOtion Tracking (DOT) model is developed to understand the behavioral characteristics of drifting caused by solitary waves. The behavioral characteristics of drifting are analyzed quantitatively based on the weight of the debris, scale of solitary waves, and revetment type, which have not been considered previously. The DOT model tracks the drifting behavior more accurately than the existing commercial programs. In a laboratory experiment, the kinetic energy, and maximum debris velocity increase with an increase in the magnitude of solitary waves. An analysis of the drifting characteristics based on revetment type reveals that the initial acceleration of drifting in the wave absorbing revetment (WAR) is higher than that in the vertical revetment (VR). Velocities of vertical and horizontal flow develop in VR and WAR, respectively, and thus the momentum flux acted more strongly. Further, overtopping the wave characteristics based on the revetment type determines the drifting behavior.

An investigation on the effects of increasing maximum wind speed of tropical cyclones on the return periods of water levels in the sea area of the Yangtze River Delta

This paper investigates the impact of increasing maximum wind speed of tropical cyclones on the return periods of water levels in the sea area of the Yangtze River Delta. To conduct this study, a series of numerical experiments are performed using historical tropical cyclones that impacted the Yangtze River Delta from 1949 to 2019. The aim is to analyze the effects of global climate change on extreme water levels and the corresponding return periods. To obtain the historical water levels in the sea areas of the Yangtze River Delta, a storm surge model is driven by the selected tropical cyclones. The simulated astronomical tidal levels during the same period are also used. The extreme water levels of different return periods are then calculated. The maximum wind speeds of the selected tropical cyclones are increased by 11% according to the expected amount of increase under global climate change. The extreme water levels of different return periods under this scenario are calculated with the same procedure. The results of the study show that the impact of increasing maximum wind speed of tropical cyclones on the increases of extreme water levels and the decrease of return periods is more significant in the inner area of the estuaries than in the outer areas. Moreover, the responses of the extreme water levels and the corresponding return periods in the Yangtze River Estuary and the Hangzhou Bay show different characteristics. The results of this study provide significant reference value for the management of future coastal disaster prevention and mitigation in the Yangtze River Delta. Furthermore, the methodology used in this study can be applied in other estuaries to investigate the potential impacts of changes in climate and hydrology factors on extreme water levels and the corresponding return periods.

Benefits of Beach Erosion Control on the East Coast of Korea

Lee, J.S. and Chang, J.-I., 2023. Benefits of beach erosion control on the east coast of Korea. Journal of Coastal Research, 39(2), 347–353. Charlotte (North Carolina), ISSN 0749-0208. Coastal erosion control projects bring various benefits to people, such as reducing damage from coastal disasters, reducing erosion and flooding damage, and providing water-friendly spaces. Nevertheless, it is difficult to evaluate a project because there are few analyses of the economic impact of the project. Thus, this study aims to estimate the benefits of coastal erosion control and maintenance projects using people's willingness to pay (WTP). In particular, information on the effectiveness of a project for relatively unknown coastal regions is lacking. Therefore, this study targeted the Yeongrang coast in Gangwon-do, located on the east coast of Korea. The annual WTP per household was estimated to be approximately KRW 1999 (USD 1.81). The benefit–cost ratio based on this was estimated to be approximately 2.98, which is considered to be a sufficiently large benefit compared with the cost of the project. The findings of this study can be used as the basis for decision making regarding coastal erosion control policies for similar case areas.

The External, Internal Factor and Ecosystem Services to Support Mangrove Rehabilitation Planning in North Coast of Jakarta

The mangrove ecosystem on North Coast of Jakarta has many services and function both of ecology, social and economic function and services, including the tidal flooding reduction, land subsidence reduction, pollution reduction, ecotourism and others. However, the mangrove ecosystem in North Coast of Jakarta Mangroves are being badly damaged, so require effort and activity to rehabilitate. This research aimed to develop rehabilitation strategy of mangrove ecosystem in North Coast of Jakarta to reduce coastal disaster and to support ecosystem services. The methods of this research used IFAS, EFAS analysis and Buchard analysis. The results showed that the ecosystem services of mangrove ecosystem were are ecotourism, conservation, wildlife reserves, reduction of tidal flooding, abrasion and accretion, reduction of intrusion, reduction of land subsidence, economic income, fishing and fishpond activities, pond activities, and social benefits. The strategy of mangrove rehabilitation was weakness-opportunity strategy (minimalizing weakness, taking advantage of opportunities, and avoid threats. The strategies of mangrove rehabilitation plaaning were mangrove rehabilitation, mangrove revitalization, support creative economy, developing greenbelt, increasing human resources and developing blue carbon

Relationship between depositional environments and preservabilities of Holocene tsunami deposits on the Hidaka coast, Hokkaido, Japan

Rising sea levels and associated coastal topography changes are expected to increase coastal vulnerability to tsunamis. Reliable records of the periodicity of the most damaging tsunamis, with recurrence intervals of several centuries, are often incomplete. To understand the likelihood of coastal disasters that would be worsened by sea-level rise, as well as their possible occurrence leading to the actual extent of inland inundation, it is useful to examine the geological record of the mid-Holocene highstand periods to supplement the written archives. However, the formation and preservation potential of event layers depends heavily on the depositional environment resulting from coastal evolutions. This study attempted to reconstruct the depositional environment changes using diatom and chemical analyses on the Hidaka coast of Hokkaido, Japan, to examine the preservation of event layer archives.Following field investigations, we found three sand layers formed by extreme waves from field investigations. The relationship between the depositional environment and the timing of the event layer formation over the past 7000 years along the central Hidaka coast indicates that supratidal to freshwater marsh environments are the most suitable for preserving tsunami deposits in this region. Since sand layers in the distant areas from wave sources were not well preserved in upland (as at elevations above marsh environment) and saltmarsh environments, the time windows of preservation were very limited depending on the depositional environments with relative sea-level changes. On the other hand, in areas closer to the Kuril Trench, sand layers were preserved not very sensitive to the depositional environment, suggesting that the event archive length is related to the magnitude of tsunamis.