Literature review
Jiarui Qi
Word Count: 2093
Literature review on disaster vulnerabilities and managements of coastal flood and rainfall events in Asian tropical and subtropical areas
Introduction
As human civilization developed, population expanded extremely fast. During this process, many problems evolved and on of them is some of the human activities had already seriously affected nature environment, which brought natural disasters like floods and extreme rainfall in coastal areas like south and southeast Asia. On the other hand, while lots of people live densely on the coast, these disasters can seriously affect people’s lives, causing deaths, injuries, and huge amount of economic losses. According to Amartya Sen, the serious consequences caused by natural disasters will slow down the economic growth greatly, which severely restricted the human development and freedom. Looking at the history, it is completely different whether the disaster are faced appropriately. If the government can draw lessons from former disasters, it may help the country resist and prepare for next possible disasters. On the contrary, serious losses will happen repeatedly if the government don’t value the importance of disaster managements. Therefore proper disaster managements like predictions before disasters and ways of recoveries after disasters became urgent questions.
To begin with, the data science methods and datasets used in researches is very important in analyzing disasters. In my annotated bibliography, two passages are about flood and rainfall events. In the first article, the author discussed the Cyclone Ockhi and a torrential rainfall event in south Asia. In order to analyze the cyclone more specifically, the author adopted different data science methods like comparing cyclone Ockhi with other rainfall events, the condition of the cyclone in different dates. Also the author used geospatial data sets like Sea Surface Temperature (SST),Outgoing Longwave Radiation (OLR) and Relative Humidity (RH) to analyze the situation. In the second article, the author researched the mapping of tropical storm-induced flash flood. When it comes to the geospatial data sets, the author used the ESRI file geodatabase to obtain 3732 data samples of 10 factors of floods: LULC( land use and land cover), rainfall, slope, curvature, elevation, aspect, Topographic wetness index, stream, density, soil type, and geology. Having enough information to analyze, the scientists used data science methods like the HE-SysFor model and the EO algorithm to find out the connection and how they can affect the formation of flood out of these 10 factors. To study thoroughly on disaster managements of tropical flood and rainfall events in south and southeast Asia, these methods and data sets are important and will occur frequently.
1.R.S. Mahendra, P.C. Mohanty, H. Bisoyi, T. Srinivasa Kumar, S. Nayak, Assessment and management of coastal multi-hazard vulnerability along the Cuddalore–Villupuram, east coast of India using geospatial techniques, Ocean & Coastal Management, Volume 54, Issue 4, 2011, Pages 302-311, ISSN 0964-5691, https://doi.org/10.1016/j.ocecoaman.2010.12.008. (https://www.sciencedirect.com/science/article/pii/S0964569111000020)
In this passage, the author discussed the multi hazard vulnerability management along the Cuddalore-Villupuram, east coast of Asia. In this coastal area, lots of natural disasters take place: tropical cyclones, sea level rise, floods, coastal erosion, and storm surge along the coast. These various kinds of hazards threaten people’s lives in SW monsoon seasons and cause poverty in coastal areas. During cyclones, sea water causes the inundation of lands and floods in river deltas. In order to deal with the disasters, an important step is to make a Multi-hazard Vulnerability Map to represent the vulnerability, risk, and hazard information together, which can help to manage and access the disasters. However, in such an area with complex systems of different disasters, it is extremely hard for scientists to include all hazard-related information in such a big study area to composite a picture of the disasters of varying magnitude, frequency, and area of effect.
Because if the hazards can be predicted and prepared through warnings and evacuations, the impact will be much smaller. In order to solve this problem, scientists used remote sensing and GIS tools. It is possible to assess vulnerabilities and estimate the inundation of disasters by using parameters like shoreline change rate, sea level change rate, historical storm surges and the high resolution topography. The evacuation routes are generated by imbibing land use, transport, and structural information. I think it proved the usefulness of geo database and geospatial methods in studying complex weathers that can cause disasters.
In the action part, after making the Multi-hazard Vulnerability Map (MHVM), researchers found out many aspects related to disasters using the data of historical storms. Among them I think the most useful one is the estimation of extreme storm surges and return periods. By studying the historic surge records, the scientists have enough data to estimate the non-exceedance probability and maximum surge heights, which are important indexes of storm surges. Except MHVM, scientists also used Quickbird Image to extract data of coastal land use, buildings, and roads. I think these information is extremely important because the risk people have to afford directly relates to the overall construction arrangement. In order to guarantee the safe of coastal residents, it is necessary plan and build the basic infrastructures in carefully and to detect the risk of storm disasters every time. Using these land cover information, the authors can predict the risk of hazards and as a result affect the government to make the proper policy. Possibly in the future, alerts and exquisite weather forecasts will be applied to further decrease the hazard risk of people.
After these researches, I think scientists have already made significant improvements and approaches on disaster managements in the coastal areas. Although the condition of the coastal is complex, using data science information and methods can turn the complexity into data, lowering the difficulty of analyzing.
2.Muhammad Al-Amin Hoque, Naser Ahmed, Biswajeet Pradhan, Sanjoy Roy, Assessment of coastal vulnerability to multi-hazardous events using geospatial techniques along the eastern coast of Bangladesh, Ocean & Coastal Management, Volume 181, 2019, 104898, ISSN 0964-5691, https://doi.org/10.1016/j.ocecoaman.2019.104898. (https://www.sciencedirect.com/science/article/pii/S0964569119301486)
In the eastern coast region of Bangladesh with a 377km-long coastline, under threat of multiple natural disasters like tropical cyclones, floods, coastal erosion and salinity intrusion, each of them with great damage over coastal environment and would likely even lead to future climate change. Facing these problems, scientists set up a target of measuring the vulnerability of hazard of coastal areas to mitigate the influences of disasters.
I think the most important reason why coastal areas are vulnerable to natural disasters is their dense populations and frequent human activities. Regular hazards on the coasts caused huge extensive losses in social and economic ways, making disaster managements extremely important in the process of human development. Bangladesh is the most seriously cyclone affected country in the world. What’s more, it is never an easy task to assess the vulnerability and give corresponding solutions. Different kinds of disasters exist and each of them have different impacts and origins.
The geospatial approach the author mainly used is CVI (coastal vulnerability index). It consists 8 parameters: elevation, slope, geomorphology, shoreline change, sea level rise, mean tide range, bathymetry and storm surge height. Geomorphology is closely related to the historical coastal development, which I think is the most important factor. Because by studying historical data, scientists can find out how did former disasters develop and study their characteristics. After collecting enough data, scientists will be more familiar towards those hazards and might find some patterns how the disaster change through time. This is very useful because although we know lots of geospatial data of the coastal area, we lack the ability to combine them together and see how these factors affect the weather entirely. After studying existing examples, scientists can see how these parameters interact and form a better understanding to the disaster as a whole.
After several researches on those 8 parameters, the CVI results were validated and analyzed, developing a mature CVI map. Proper suggestions of disaster managements were presented, which helped the government officials a lot on their policies.
There are also some limitations of this study. The datasets were not the latest and the images can be taken in higher resolution. Also, the study didn’t consider the effects of saline water and subsidence.
However, to sum up, I think the CVI results are great achievements of scientists and can help to improve the disaster management in coastal areas greatly, ensuring less risks and losses in a wide range.
3.Guanghui Wang, Yijun Liu, Hongbing Wang, Xueying Wang, A comprehensive risk analysis of coastal zones in China, Estuarine, Coastal and Shelf Science, Volume 140, 2014, Pages 22-31, ISSN 0272-7714, https://doi.org/10.1016/j.ecss.2013.12.019. (https://www.sciencedirect.com/science/article/pii/S027277141300543X)
China has a coastal line with a length of 30 thousand kilometers. There are many big cities locate on the coast: Shanghai, Shenzhen, Hong Kong, etc. In the late 1900s, the economy in coastal cities developed remarkably fast, which is one of the main reasons of the growth of China’s national strength. Although the frequency of hazards in China’s coast might be less than other countries in southeast Asia, the potential economic loss once disasters take place is very severe because of the large amount of cities and their dense populations. Therefore, it is very important to pay attention to possible disasters along the coast.
The main goal for the authors was to build a evaluation index system of multi-disaster vulnerabilities. After setting the goal, a hierarchy of the index system was formed, including 5 criteria to achieve the final comprehensive risk assessment of coastal zones, with 3 factors under each criterion. These factors covered information in both environmental and humanity fields. I think the total of 15 factors and 5 indexes is very rigorous but at the same time very challenging because it is hard to gather and compare such a great amount of data. However, scientists used the Delphi method to construct the system and Analytic Hierarchy Process to weigh those factors. To collect information, scientists used the geospatial data set of China City Statistical, Ocean and Marine Statistical Yearbook. In the process of assessing vulnerabilities, scientists divided all factors into positive and negative indices and analyzed them by using mathematical formulas. When it comes to the comprehensive risk assessment, scientists only used the mechanism of the method of Risk Matrices, leading to more precise results.
After using proper geospatial methods and datasets, scientists disintegrated the complex natural and human living system on the coast into small factors and both made comparison between them and analyzed their data independently. This ingenious separation and combination of data solved lots of problems and accelerated the research process greatly.
There are also some limitations in this research. Since data in statistical yearbooks are official figures that lack civil statistics, the final result will have a tiny inaccuracy. Some inaccessible data will also affect the result. Therefore, although the system is surely a great work, it can be advanced in the future.
4.Mohanty, P.C., Panditrao, S., Mahendra, R.S. et al. Geospatial Assessment of Flood Hazard Along the Tamil Nadu Coast. J Indian Soc Remote Sens 47, 1657–1669 (2019). https://doi.org/10.1007/s12524-019-01012-7
The average precipitation of the rainy seasons in low-lying areas in India is very exaggerate. Due to climate change, the frequency and intensity of heavy precipitation event is still increasing, leading to many natural disasters like floods. In the densely populated Tamil Nadu Coast in southeast India, floods and extreme rainfall can bring devastating effects to local residents’ lives and national economy.
In order to fully study the flood events’ impacts on coastal areas, scientists have to collect information in two kinds of areas: the inundation or flooding area and the built-up area. In the inundation or flooding area, the disasters have greater impacts on natural environment because of the seriousness. In the built-up areas, the disasters have great affect on people’s lives and economy even if the disaster is not very severe.
To extract information in the flooding area, scientists used the Sentinel-1 SAR method. 4 steps are used and finally generations of flood maps are developed. When it comes to the built-up area, Landsat-8, OLI was used to process the built-up area inundation. While combining information of the flood map and the built-up inundation, the flooding risk in built-up areas can be estimated, and it is the same at village level.
By properly using data science methods and information, the authors established exact models to learn the specific condition of seriously affected areas on the coast. The flood risks and flood maps can help the local government make policies aiming at reducing losses.
Summary
While accessing disaster vulnerabilities, it is extremely convenient to use datasets and geospatial data science methods. It is fast for the computers to process the huge amount of data, select useful ones and find potential patterns between them. All over the world history, we noticed that more and more natural disasters can be forecast and prepared. During and after disasters, we are not that nervous and can always make proper responses and reduce losses to the maximum extent. These improvements, showing that human can better deal with the nature, promoted human development greatly. However, apart from disaster managements, we must also pay attention to take care of the nature environment. The best disaster management is not to prepare for disaster and lower the losses, but to reduce the amount of disasters by preserving nature. It is necessary for us the push these two processes at the same time.