Research on the Tsunami Hazard Map linked Tsunami Forecasting

Impacts of rainstorm characteristics on flood inundation mitigation performance of LID measures throughout an urban catchment

Tsunami inundation mapping is the first step in the development of effective evacuation plans for communities at risk. These maps also provide bases for land use planners in communities to reduce risk by locating critical facilities out of the potential tsunami flood plain. The Makran subduction zone, located off the Indian Ocean coasts of Iran and Pakistan, is an important tsunamigenic zone for the region. On the 27th November, 1945, it was the site of a major earthquake with a moment magnitude of 8.1 and killed about 4,000 people. This event is a proof that Makran coastal areas are unsafe since the tsunami is quite probable. The objective of this study was providing tsunami inundation and hazard maps in Chabahar bay which is located in South East of Iran and the northern coast of Oman Sea. Three different source magnitude scenarios along Makran subduction zone are considered and for each scenario, numerical modeling of tsunami propagation is performed using MIKE 21 FM numerical software. Because the Makran subduction zone is very close to the Chabahar bay, unstructured triangular mesh with a higher level of refinement closer to the area of interest was used so that the tsunami was not numerically dissipated. After analyzing the data obtained from the results, inundation maps were produced, and by combining these maps, tsunami hazard map was provided for the bay. Tsunami wave amplification has been observed mainly in the outer coasts of the bay where the uplifted rocky shore experience up to 18 m wave height. Chabahar bay omega form and two eastern and western headlands cause a considerable depreciation in tsunami wave. Longer distance of coasts within the bay is another reason of tsunami depreciation inside the bay. Based on the generated inundation and hazard maps, two flood zones are specified. The first zone associated with no inundation or low inundation on cliffy shores, and the second zone would experience extensive inundation on the coast of kenarak areas, areas with sandy beaches and gentle slope.

Of all natural disasters of the twentieth century, earthquakes caused the largest amount of losses. Although the number of earthquakes remains fairly unchanged, the loss of properties and human lives in recent periods has increased manifolds due to increasing concentration of human population and urbanisation in earthquake-prone areas. Recent improvement in documentations and computational facilities, however, allows for the preparation of seismic microzonation maps of such areas for urban planning and earthquake mitigation purposes. This paper discusses the development of seismic microzonation maps for Banda Aceh which lies close to the Sumatra Subduction Zone and the Sumatran Transform Faults, making the city extremely vulnerable to earthquake hazards. The development of the maps employs Geographic Information Systems (GIS) techniques that make use of several layers of parameters influencing earthquake hazards such as seismological data, faults, tsunami, etc. and site characteristic data such as soil type, groundwater distribution and depth, geological and geophysical data. The seismic microzonation maps incorporate various seismic hazard maps including ground shaking hazard map, liquefaction susceptibility hazard map, landslide potential hazard map, surface faulting hazard map and tsunami hazard map. The final composite map identifies zones with various degrees of hazards which will enable planners to avert hazardous locations during site selection processes, thus reducing losses.

Tsunamis pose a significant threat to the Jailolo coastal area in North Maluku, Indonesia, because of its proximity to the Maluku Sea subduction zone, where seismic activity has historically triggered destructive waves. This study aims to map tsunami hazards in the Jailolo coastal area by integrating the Structure-from-Motion (SfM) photogrammetry method with numerical calculations. The SfM photogrammetry method involves using an unmanned aerial vehicle (UAV) to produce digital elevation model (DEM) data in the form of digital terrain model and digital surface model, as well as orthomosaic data. In addition, tsunami wave propagation simulation modelling was carried out using the Cornell Multi-Grid Coupled Tsunami computational program, with input data including Manning’s coefficient data and fault parameters. The aerial photography resulted in DEMs with a vertical accuracy of LE90 of 0.15 metres and an orthomosaic with a horizontal accuracy of CE90 of 0.5 metres. The tsunami simulation revealed tsunami waves reaching 5.8–17.4 metres, with a hazard zone of approximately 119.31 hectares and an inundation distance of about 700 metres from the coast. The affected areas include settlements, agriculture and mangrove forests. In conclusion, the integration of UAV-based SfM photogrammetry and numerical simulations effectively produces high-precision tsunami hazard maps. Contribution: This study provides a significant contribution to disaster mitigation and evacuation planning by providing an accurate and efficient method for mapping tsunami hazards. The precise data can support decision-making in high-risk coastal areas such as Jailolo.

The southern part of Java Island is susceptible to tsunamis as its role as a subduction zone between Indo-Australian and Eurasian plates. On July 17, 2006, a tsunami struck Java's south coast triggered by an earthquake and affected more than 300 km of shoreline, as well as claimed more than 730 casualties. It is important to assess the risk in the southern part of Java. This research aims to analyze tsunami risk assessments on public facilities in the southern part of Bantul Regency, Yogyakarta. The Tsunami hazard map was created by using tsunami modeling from BMKG. Public facilities footprint such as health facilities, religious facilities and school were derived from data provided by Open Street Map (OSM). The Papathoma Tsunami Vulnerability Assessment (PTVA) model, specifically developed to estimate the relative vulnerability of buildings to tsunami hazards, is used to generate a building vulnerability map. A geographic information system (GIS) was utilized to calculate and visualize the hazard, vulnerability, and risk map. A total of 394 buildings were analyzed with the results that public facilities in three sub-districts, namely Srandakan, Sanden and Kretek, had varying levels of building vulnerability ranging from minor, moderate, average and high with RVI values ranging from 1.5 to 3.4. Additionally, tsunami risk assessment of public facilities indicates that buildings within Bantul Regency are categorized as having very high, high, moderate, or low levels of building risk.

Since the mid-1980s, there has been accumulating geologic evidence of large local tsunamis generated by earthquakes along the Cascadia subduction zone off the Pacific Northwest. Information from recent geophysical and geological investigations constrains the potential rupture-zone geometry and average repeat time of interplate thrust earthquakes. Based on this information, tsunami hazard maps have been prepared for coastal communities in the Pacific Northwest using sophisticated numerical models to simulate tsunami propagation and inundation. In this study, sources of uncertainty in tsunami hazard calculations are described and a probabilistic hazard analysis for tsunamis, similar to probabilistic seismic hazard analysis (PSHA), is outlined. Though probabilistic tsunami hazard analysis (PTHA) shares many similarities with PSHA, there are specific issues unique to tsunami hazards that need to be accounted for in the probability calculations. For example, the possibility of rupture along splay faults from the Cascadia interplate thrust have a large effect on tsunami generation, but a relatively small impact on peak ground accelerations onshore. The largest sources of uncertainty include the average slip and downdip extent of rupture. Also, it is demonstrated that significant variations in nearshore tsunami amplitude are caused by uncertainty in slip distribution patterns. Correct identification of uncertainties related to tsunami generation and propagation is critical in performing the probability calculations. PTHA has the potential to provide an improved technique for evaluating local tsunami hazards in the Pacific Northwest and elsewhere.

Understanding the impacts of tsunamis, especially in terms of damage and losses, is important for disaster mitigation and management. The aim of this study is to present our estimations of the potential losses from tsunami damage on Okinawa Island. We combine the use of a tsunami hazard map and our proposed economic loss model to estimate the potential losses that would be sustained by Okinawa Island in the event of a tsunami. First, to produce the tsunami hazard map, we calculated tsunami flow characteristics using the mathematical model TUNAMI-N2 and incorporating 6 earthquake fault scenarios around the study area. The earthquake scenarios are based on historical records along the Ryukyu Trench and the Okinawa. The resulting inundation map is overlaid with economic land use type and topography maps to identify vulnerable regions, which are then employed to compute potential economic losses. Second, we used our proposed economic model for this study area to calculate the potential losses that would be sustained in these vulnerable regions. Our economic model extends the multi-regional-input-output (MRIO) model, where the economic values of industrial sectors are scaled to correlate with land use and topography types (coastal and inland areas) to calculate losses through the Chenery–Moses estimation method. Direct losses can be estimated from the total input of the MRIO table, while indirect losses are computed from the direct losses and interaction parameter of the MRIO table. The interaction parameter is formed by linear programming and calculated using the Leontief methodology. Our results show that the maximum total damaged area under the 6 earthquake scenarios is approximately 30 km2. Inundation ranging from 2.0 to 5.0 m in depth covers the largest area of approximately 10 km2 and is followed by areas with inundation depths of 1.0–2.0 m and >5.0 m. Our findings show that direct losses will occur, while indirect losses are only approximately 56% that of direct losses. This approach could be applied to other areas and tsunami scenarios, which will aid disaster management and adaptation policies.

<title>Abstract</title> The Lesser Sunda Islands (comprising Bali, West Nusa Tenggara, and East Nusa Tenggara) are situated between three seismic sources: the subduction zone, the fold-thrust back (FTB), and the back-arc thrust fault system in the north. The combined activity of these three sources makes the region highly vulnerable to tsunami hazards. The high population density in coastal areas and the presence of critical infrastructure in this region increase the urgency of conducting a tsunami hazard assessment. This study aims to analyze the tsunami hazard using a Probabilistic Tsunami Hazard Assessment (PTHA) based on a Green’s function approach, derived from simulations of the Shallow Water Equation (SWE). A total of 10,120 tsunami scenarios were developed from 9 fault sources using the stochastic slip distribution based on the Von Karman correlation function. All faults were divided into 108 subfaults to estimate the response of the tsunami wave at 255 observation points. The locations with the highest frequency per year for waves exceeding 1 m include Jembrana and Buleleng, northern and southern Sumbawa, as well as Sikka and west Manggarai. The tsunami hazard maps indicate that for a return period (RP) of 2475 years, more than 57% of the locations experience tsunami waves exceeding 3 m, with maximum heights reaching over 11 m. For the return period of 475 years, the rate is more than 0.4%, and for the return period of 72 years, there’s no location where the tsunami wave height exceeds 3 meters. The faults from the Bali subduction zone, the Sumbawa thrust, the Flores thrust, and the Timor FTB are the dominant contributors to the tsunami hazard in 20 strategic locations.

The present study aims to assess the Tsunami hazard in Palu due to the future Tsunamigenic event in terms of near-shore and far-field Tsunami runup, inundation height, and Tsunami arrival time along the coast of Palu. A numerical model is developed to simulate propagation and inundation in the study area. Four scenarios are conducted, which consists of the Tsunamigenic earthquake and aerial subsidence as an approach for mimicking hypothetical potential landslide. The outcome from simulation such as inundation height each grid points then calculated with building footprint stored data – derivation data from the terrain model to develop a Tsunami hazard map. Preliminary Tsunami Hazard Map is made to classify the Tsunami hazard level by existing classification added with estimated building impacted and arrival time ashore on each village in Palu City administrative region.

Tsunamis pose a considerable risk to life and property along the shorelines of the Hawaiian Islands. To help mitigate this risk, the federal emergency management agency (FEMA) has included tsunami runup mapping on coastal flood hazard maps in the County of Hawaii. In 2007, the U.S. Army Corps of Engineers (USACE) collected high-resolution airborne bathymetric and topographic LiDAR data along the Hawaiian Island coasts. Recently, FEMA funded a study to update the tsunami runup mapping for the City of Hilo, which was previously completed with topographic data collected in the late 1970s. Because the tsunami analysis is dependent on topographic characteristics, a re-delineation of the existing runup elevations onto the new terrain data would not be accurate. This paper includes a description of the updated tsunami runup analysis, a comparison between the old and new results, and details on some of the unique challenges that arose from incorporating high resolution data and results into existing coastal flood hazard maps.

Flooding is a major natural hazard in many parts of the world, and its frequency and magnitude are projected to increase with global warming. With increased concern over ongoing climate change, more detailed and precise information about climate-change risks is required for formulating local-scale countermeasures. However, the impacts of biases in climate-model outputs on river-flood simulation have not been fully evaluated, and thus evaluation of future flood risks using hazard maps (high-resolution spatial distribution maps of inundation depths) has not been achieved. Therefore, this study examined methods for constructing future-flood-hazard maps and discussed their validity. Specifically, we compared the runoff-correction method that corrects for bias in general-circulation-model (GCM) runoff using the monthly climatology of reanalysis runoff with the lookup method, which uses the GCM simulation results without bias correction to calculate changes in the return period, and depends on the reanalysis simulation to determine absolute flood depths. The results imply that the runoff-correction method may produce significantly different hazard maps compared to those based on reanalysis of runoff data. We found that in some cases, bias correction did not perform as expected for extreme values associated with the hazard map, even under the historical climate, as the bias of extreme values differed from that of the mean value. we found that the direction of the change in future hazard (increase or decrease) obtained using the runoff-correction method relative to the reference reanalysis-based hazard map may be inconsistent with the changes projected by the GCMs in some cases. On the other hand, we confirmed that the lookup method can produce future-hazard maps that are consistent with the changes in flood risk projected by the GCMs, indicating the possibility of obtaining reasonable inundation-area distribution. The results imply that the lookup method is more suitable for future-flood hazard-map construction than the runoff-correction method. The lookup method also has the advantage of facilitating research on efficient construction of future-climate hazard maps, as it allows for improvement of the reanalysis hazard map through upgrading of the model and separate estimation of changes due to climate change. We discuss future changes in inundation areas and the affected population within the inundation area. Using the lookup method, the total population living in modeled inundation areas with flood magnitudes exceeding the 100-year return period under a future climate would be around 1.8 billion. In the assessment of future climate risks, we found that an affected population of around 0.5 billion may be missed if the historical hazard map is used as an alternative to constructing future-hazard maps and only frequency changes are considered. These results imply that in global flood-risk studies, future-hazard maps are important for proper estimation of climate-change risks, rather than assessing solely changes in the frequency of occurrence of a given flood intensity.

<strong class="journal-contentHeaderColor">Abstract.</strong> Flooding is a major natural hazard in many parts of the world, and its frequency and magnitude are projected to increase with global warming. With increased concern over ongoing climate change, more detailed and precise information about climate-change risks is required for formulating local-scale countermeasures. However, the impacts of biases in climate-model outputs on river-flood simulation have not been fully evaluated, and thus evaluation of future flood risks using hazard maps (high-resolution spatial distribution maps of inundation depths) has not been achieved. Therefore, this study examined methods for constructing future-flood-hazard maps and discussed their validity. Specifically, we compared the runoff-correction method that corrects for bias in general-circulation-model (GCM) runoff using the monthly climatology of reanalysis runoff with the lookup method, which uses the GCM simulation results without bias correction to calculate changes in the return period, and depends on the reanalysis simulation to determine absolute flood depths. The results imply that the runoff-correction method may produce significantly different hazard maps compared to those based on reanalysis of runoff data. We found that in some cases, bias correction did not perform as expected for extreme values associated with the hazard map, even under the historical climate, as the bias of extreme values differed from that of the mean value. we found that the direction of the change in future hazard (increase or decrease) obtained using the runoff-correction method relative to the reference reanalysis-based hazard map may be inconsistent with the changes projected by the GCMs in some cases. On the other hand, we confirmed that the lookup method can produce future-hazard maps that are consistent with the changes in flood risk projected by the GCMs, indicating the possibility of obtaining reasonable inundation-area distribution. The results imply that the lookup method is more suitable for future-flood hazard-map construction than the runoff-correction method. The lookup method also has the advantage of facilitating research on efficient construction of future-climate hazard maps, as it allows for improvement of the reanalysis hazard map through upgrading of the model and separate estimation of changes due to climate change. We discuss future changes in inundation areas and the affected population within the inundation area. Using the lookup method, the total population living in modeled inundation areas with flood magnitudes exceeding the 100-year return period under a future climate would be around 1.8 billion. In the assessment of future climate risks, we found that an affected population of around 0.5 billion may be missed if the historical hazard map is used as an alternative to constructing future-hazard maps and only frequency changes are considered. These results imply that in global flood-risk studies, future-hazard maps are important for proper estimation of climate-change risks, rather than assessing solely changes in the frequency of occurrence of a given flood intensity.

Study on urban flood simulation based on a novel model of SWTM coupling D8 flow direction and backflow effect

Annual fluvial and pluvial floods happened in Lower Ping River Basin, Thailand. A flood hazard assessment approach was performed in the present study to evaluate flood impacts. The coupled 1D-2D hydrodynamic (HD) modeling package was applied for different return periods to investigate and classify the flood hazards. The 1D hydrodynamic model was calibrated for flood year 2011 at discharge and water level stations. The 2D hydrodynamic model was calibrated using observed flood map. Flood hazards were categorized based on critical flood depths for flooding scenarios of 2-, 5-, 10-, 25-, 50-, and 100-year return periods. The results showed that 28.8% of the total basin area (2423.8 km2) was flooded during the 100-year return period, and the maximum flood inundation area was observed in Kamphaengphet and Nakhon Sawan provinces. Mostly, the flooded area under each return period was categorized under high hazard, followed by low and medium, and the least area was classified under a very high hazard level. More than 40% of sub-districts’ area of Kamphaengphet and Nakhon Sawan provinces were flooded, which is located along the Ping River, while less than 20% sub-districts’ area was flooded in Tak Province. The government and local stakeholders need to consider structural and nonstructural measures to reduce flood impacts in three provinces, and priority-based areal flood management approaches should be considered during the implementation of flood mitigation measures.

Global climate change and rapid urbanization have caused increases in urban floods. Urban flood risk assessment is a vital method for preventing and controlling such disasters. This paper takes the central region of Cangzhou city in Hebei Province as an example. Detailed topographical information, such as the buildings and roads in the study area, was extracted from GF-2 data. By coupling the two models, the SWMM and MIKE21, the spatial distribution of the inundation region, and the water depth in the study area under different return periods, were simulated in detail. The results showed that, for the different return periods, the inundation region was generally consistent. However, there was a large increase in the mean inundation depth within a 10-to-30-year return period, and the increase in the maximum inundation depth and inundation area remained steady. The comprehensive runoff coefficient in all of the scenarios exceeded 0.8, indicating that the drainage system in the study area is insufficient and has a higher flood risk. The flood risk of the study area was evaluated based on the damage curve, which was obtained from field investigations. The results demonstrate that the loss per unit area was less than CNY 250/m2 in each return period in the majority of the damaged areas. Additionally, the total loss was mainly influenced by the damaged area, but, in commercial areas, the total loss was highly sensitive to the inundation depth.