Hypothetical Failure of the Khassa Chai Dam and Flood Risk Analysis for Kirkuk, Iraq

Many of Iraqi's high-hazard dams lack an Emergency Action Plan, which should include a flood inundation map to show which downstream areas would be flooded if the dams were to fail. This article presents the results of the simulation of a hypothetical 2D dam break for the 58 m high Khassa Chai dam in Kirkuk, Iraq, using HEC-RAS 2D 5.0.7 software. The Khassa Chai dam is situated 7.4 kilometers north of Kirkuk. The simulations revealed that the dam-break flood will affect eight major bridges and the majority of Kirkuk city's metropolitan neighborhoods. Within an hour, the floodwaters will reach the city's center. The flood hazard map revealed that if the Khassa Chai dam fails, many people, vehicles, and structures will be at danger. The findings of this paper can be used to identify evacuation routes and refuge sites as well as build suitable warning systems in order to limit the risk for fatalities if the Khassa Chai dam fails. Moreover, as the effect of modelling bridges downstream of failed dams has not been explored yet, to the knowledge of the authors, eight bridges have been modeled. It was concluded that ignoring bridges in such a large dam break model will not affect the results significantly, which saves the time of data collection and model development.

Dam Break Simulation with HEC-RAS and OpenFOAM

A dam break is a natural disaster that can cause significant property damage and loss of life. It's useful to identify potential flooding areas downstream in the event of a dam break. In this study both HEC-RAS and OpenFOAM are set up to simulate the inundation map downstream of the Dworshak dam in Idaho. Using the same topographical data from satellite observations, similar computational meshes are set up in both HEC-RAS and OpenFOAM. Where possible, identical or similar conditions are set up in HEC-RAS and OpenFOAM to model flooding patterns due to a dam break. The velocity of the water before reaching Ahsahka, the town located at the junction downstream from the dam, is 11.5% slower in HEC-RAS compared to OpenFOAM. The average velocity of water before reaching the end of the computational domain at Big Canyon Creek is about 20% slower in HEC-RAS compared to OpenFOAM. One notable discovery is that the water flow velocity in OpenFOAM appears to depend on the mesh resolution used in the simulation. A significant velocity difference is observed when water flows from one mesh refinement region to another mesh refinement region with a different resolution.

GIS Based Tsunami Risk Assessment

Tsunami is a coastal hazard which occur due to undersea earthquakes, Meteorite falls, volcanic eruptions or even nuclear weapon operations. The tsunami hazard which occurred in December 2004 was generated due to an undersea earthquake 400m west of northern Sumatra and it inundated coastal areas of Indonesia, Sri Lanka, Thailand and India. This hazard became one of the worst disasters in the history resulting in over thirty thousand fatalities and over seventy thousand house damage in Sri Lanka. This study is focused towards creation of GIS based Tsunami risk map for Galle city which was badly hit by the 2004 Tsunami. Tsunami vulnerability was assessed using weighted overlay spatial method with input parameters of population density, sex ratio, age ratio, disability ratio and damaged building ratio. Tsunami hazard map was developed based on tsunami inundation map which was published by Coastal research and design, costal conservation and resource management department with assistant from Disaster management centre using the Cornell Multigrid Coupled Tsunami Model (COMCOT). Vulnerable and hazard maps were analysed and incorporated to develop final risk map using GIS tool. Keywords GIS; Tsunami Inundation Map; Tsunami Risk Map; Vulnerability; Disaster

Inundation Assessment of the 2019 Typhoon Hagibis in Japan Using Multi-Temporal Sentinel-1 Intensity Images

Typhoon Hagibis passed through Japan on October 12, 2019, bringing heavy rainfall over half of Japan. Twelve banks of seven state-managed rivers collapsed, flooding a wide area. Quick and accurate damage proximity maps are helpful for emergency responses and relief activities after such disasters. In this study, we propose a quick analysis procedure to estimate inundations due to Typhoon Hagibis using multi-temporal Sentinel-1 SAR intensity images. The study area was Ibaraki Prefecture, Japan, including two flooded state-managed rivers, Naka and Kuji. First, the completely flooded areas were detected by two traditional methods, the change detection and the thresholding methods. By comparing the results in a part of the affected area with our field survey, the change detection was adopted due to its higher recall accuracy. Then, a new index combining the average value and the standard deviation of the differences was proposed for extracting partially flooded built-up areas. Finally, inundation maps were created by merging the completely and partially flooded areas. The final inundation map was evaluated via comparison with the flooding boundary produced by the Geospatial Information Authority (GSI) and the Ministry of Land, Infrastructure, Transport, and Tourism (MLIT) of Japan. As a result, 74% of the inundated areas were able to be identified successfully using the proposed quick procedure.

Storm Surge Awareness and Intended Evacuation in Low-Lying Areas of Tokyo City

Japan is a country that is normally considered to be well protected against storm surges, with the population aware of the potential consequences of such events. However, the inundation caused by typhoon Jebi in 2018 at Osaka Bay has highlighted that there is a significant risk of flooding in many areas. In the present paper the authors conducted questionnaire surveys with the aim to gauge the level of storm surge awareness and intended evacuation behaviour of the population of low-lying areas of Tokyo City. The results indicate that respondents have a high awareness regarding storm surges, but lower actual knowledge about the risk in their area and the evacuation plan. Respondents who have higher risk awareness about storm surges often had participated in evacuation drills, and those who knew about the inundation map tend to indicate that they would perform long-distance evacuation. It was also found that respondents who are in their 30s have lower awareness than other age groups. Keywords: storm surge; awareness; natural hazards; Japan; intended evacuation behaviour

Case study: mapping the tsunami-hazard zone in the Pasir Jambak sub-district, in Padang, Indonesia

A tsunami hazard is an adverse event that causes damage to properties and loss of life. The problem in assessing a tsunami risk zone for a small area is significant, as available tsunami inundation zone data does not give detailed information for tsunami inundation and run-up in every nested grid. Hence, this study aims to establish a tsunami risk map in the Pasir Jambak sub-district, Padang, Indonesia. The map was carried out in every nested grid point of the area and on a large scale (1:5,000). The TUNAMI N3 program was used for the simulation of the tsunami inundation. A tsunami assessment was made through simulations in nine scenarios of fault parameter data for Sipora block earthquakes. The result of the study provides a tsunami inundation map. Furthermore, this tsunami inundation map can be used for communities, local authorities, government, and others for many studies, and decision-makers can come up with mitigation plans for a small study area.

Statistical Analysis of Building Damage from the 2013 Super Typhoon Haiyan and its Storm Surge in the Philippines

In November 2013, Super Typhoon Haiyan (Yolanda) hit the Philippines. It caused heavy loss of lives and extensive damages to buildings and infrastructure. When collapsed buildings are focused on, it is interesting to find that these buildings did not collapse for the same reasons after the landfall of the typhoon and storm surge. The objective of this study is to develop a statistical model for building damage due to Super Typhoon Haiyan and its storm surge. The data were collected in collaboration with Tanauan Municipality, the Philippines. The data for the inundation map were obtained by field surveys conducted on-site to determine the cause of the damages inferred from satellite data. The maximum wind speed was derived from the Holland parametric hurricane model based on the Japan Meteorological Agency (JMA) typhoon track data and the inundation depth of storm surge was calculated using the MIKE model. Multinomial logistic regression was used to develop a model to identify the significant factors influencing the damage to buildings. The result of this work is expected to be used to prepare urban plans for preventing damage from future storms.

A METHOD TO GENERATE FLOOD MAPS IN 3D USING DEM AND DEEP LEARNING

High-resolution remote sensing imagery has been increasingly used for flood applications. Different methods have been proposed for flood extent mapping from creating water index to image classification from high-resolution data. Among these methods, deep learning methods have shown promising results for flood extent extraction; however, these two-dimensional (2D) image classification methods cannot directly provide water level measurements. This paper presents an integrated approach to extract the flood extent in three-dimensional (3D) from UAV data by integrating 2D deep learning-based flood map and 3D cloud point extracted from a Structure from Motion (SFM) method. We fine-tuned a pretrained Visual Geometry Group 16 (VGG-16) based fully convolutional model to create a 2D inundation map. The 2D classified map was overlaid on the SfM-based 3D point cloud to create a 3D flood map. The floodwater depth was estimated by subtracting a pre-flood Digital Elevation Model (DEM) from the SfM-based DEM. The results show that the proposed method is efficient in creating a 3D flood extent map to support emergency response and recovery activates during a flood event.