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Water ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 207
Author(s):  
Yun-Ju Chen ◽  
Hsuan-Ju Lin ◽  
Jun-Jih Liou ◽  
Chao-Tzuen Cheng ◽  
Yung-Ming Chen

Climate change has exerted a significant global impact in recent years, and extreme weather-related hazards and incidents have become the new normal. For Taiwan in particular, the corresponding increase in disaster risk threatens not only the environment but also the lives, safety, and property of people. This highlights the need to develop a methodology for mapping disaster risk under climate change and delineating those regions that are potentially high-risk areas requiring adaptation to a changing climate in the future. This study provides a framework of flood risk map assessment under the RCP8.5 scenario by using different spatial scales to integrate the projection climate data of high resolution, inundation potential maps, and indicator-based approach at the end of the 21st century in Taiwan. The reference period was 1979–2003, and the future projection period was 2075–2099. High-resolution climate data developed by dynamic downscaling of the MRI-JMA-AGCM model was used to assess extreme rainfall events. The flood risk maps were constructed using two different spatial scales: the township level and the 5 km × 5 km grid. As to hazard-vulnerability(H-V) maps, users can overlay maps of their choice—such as those for land use distribution, district planning, agricultural crop distribution, or industrial distribution. Mapping flood risk under climate change can support better informed decision-making and policy-making processes in planning and preparing to intervene and control flood risks. The elderly population distribution is applied as an exposure indicator in order to guide advance preparation of evacuation plans for high-risk areas. This study found that higher risk areas are distributed mainly in northern and southern parts of Taiwan and the hazard indicators significantly increase in the northern, north-eastern, and southern regions under the RCP8.5 scenario. Moreover, the near-riparian and coastal townships of central and southern Taiwan have higher vulnerability levels. Approximately 14% of townships have a higher risk level of flooding disaster and another 3% of townships will become higher risk. For higher-risk townships, adaptation measures or strategies are suggested to prioritize improving flood preparation and protecting people and property. Such a flood risk map can be a communication tool to effectively inform decision- makers, citizens, and stakeholders about the variability of flood risk under climate change. Such maps enable decision-makers and national spatial planners to compare the relative flood risk of individual townships countrywide in order to determine and prioritize risk adaptation areas for planning spatial development policies.


2022 ◽  
Vol 5 (1) ◽  
pp. 92
Author(s):  
Michael Galetakis ◽  
Vassilios Deligiorgis ◽  
Emmanuel Steiakakis ◽  
Stella Raka ◽  
Marwan Alheib

In this study we present a generic probabilistic risk assessment methodology to evaluate the risk associated with flooding process of a pit. We use the bow-tie analysis to analyze the critical events (we focus on slope failures) and the systemic risk assessment methodology to estimate the risk for the population, for the environment and for the infrastructure. Furthermore, we perform a spatial analysis of the risk by discretizing the affected area into squares, by estimating the risk in each one and finally by creating the risk map. The methodology is implemented by specialized software that has been created in a Matlab environment for the deduction of such risk assessments. The developed methodology was applied in the area of the pit lake Most in Czech Republic.


Water ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 202
Author(s):  
José María Orellana-Macías ◽  
María Jesús Perles Roselló

Groundwater is an essential resource for humans concerning freshwater supply; therefore, preserving and protecting its quality is necessary. Risk assessment, based on hazard, intrinsic vulnerability information and mapping, may be considered as a key aspect of sustainable groundwater management. An approach has been made by combining the Nitrogen Input Hazard Index and the hydrogeological parameters considered in a modified DRASTIC method. A three-level classification has been used to determine the degree of risk, and the thresholds have been established following measurable criteria related to the potential nitrate concentration in groundwater. The second part of the study focused on estimating the socioeconomic impact of groundwater pollution by relating the degree of risk and social vulnerability to groundwater pollution. The method has been tested in the Gallocanta Groundwater Body (Spain). As a result, a risk map and an impact map are provided. The risk map shows that 67% of the study area can be classified as moderate and high-risk areas, corresponding to high hazard sources located in moderate and high vulnerability zones, whereas the impact of groundwater pollution is classified as moderate in the whole groundwater body. The proposed analysis allows comparison between aquifers in different areas and the results required by water authorities to implement control and mitigation measures.


Author(s):  
Fereshteh Taromideh ◽  
Ramin Fazloula ◽  
Bahram Choubin ◽  
Alireza Emadi ◽  
Ronny Berndtsson

Urban flood risk mapping is an important tool for the mitigation of flooding in view of human activities and climate change. Many developing countries, however, lack sufficiently detailed data to produce reliable risk maps with existing methods. Thus, improved methods are needed that can improve urban flood risk management in regions with scarce hydrological data. Given this, we estimated the flood risk map for Rasht City (Iran), applying a composition of decision-making and machine learning methods. Flood hazard maps were produced applying six state-of-the-art machine learning algorithms such as: classification and regression trees (CART), random forest (RF), boosted regression trees (BRT), multivariate adaptive regression splines (MARS), multivariate discriminant analysis (MDA), and support vector machine (SVM). Flood conditioning parameters applied in modeling were elevation, slope angle, aspect, rainfall, distance to river (DTR), distance to streets (DTS), soil hydrological group (SHG), curve number (CN), distance to urban drainage (DTUD), urban drainage density (UDD), and land use. In total, 93 flood location points were collected from the regional water company of Gilan province combined with field surveys. We used the Analytic Hierarchy Process (AHP) decision-making tool for creating an urban flood vulnerability map, which is according to population density (PD), dwelling quality (DQ), household income (HI), distance to cultural heritage (DTCH), distance to medical centers and hospitals (DTMCH), and land use. Then, the urban flood risk map was derived according to flood vulnerability and flood hazard maps. Evaluation of models was performed using receiver-operator characteristic curve (ROC), accuracy, probability of detection (POD), false alarm ratio (FAR), and precision. The results indicated that the CART model is most accurate model (AUC = 0.947, accuracy = 0.892, POD = 0.867, FAR = 0.071, and precision = 0.929). The results also demonstrated that DTR, UDD, and DTUD played important roles in flood hazard modeling; whereas, the population density was the most significant parameter in vulnerability mapping. These findings indicated that machine learning methods can improve urban flood risk management significantly in regions with limited hydrological data.


2021 ◽  
Vol 14 (6) ◽  
pp. 3542
Author(s):  
Jéssica Mazutti Penso-Campos ◽  
Eliane Fraga da Silveira ◽  
Eduardo Périco

A pandemia causada pelo coronavírus disparou a possibilidade da crise em diversos segmentos, sobretudo com a adoção do isolamento social, principal ação para o controle da doença infectocontagiosa. O presente estudo justifica-se pela preocupação em relação às tendências do desenvolvimento sustentável no pós-pandemia da COVID-19, no estado do Rio Grande do Sul. A mensuração do grau de sustentabilidade dos municípios segue a tese de que, quanto maior for o grau de sustentabilidade dos municípios, menor o impacto da pandemia, e maiores os recursos para restabelecer o equilíbrio. O objetivo da pesquisa é analisar a distribuição espacial do potencial para a sustentabilidade no pós-pandemia do COVID-19, nos municípios do Rio Grande do Sul, a fim de gerar um mapa de risco sobre os municípios com menor e maior potencial para a sustentabilidade no pós-pandemia. Foi realizada uma análise ecológica, aplicado o instrumento Barômetro da Sustentabilidade, realizada a distribuição e análise espacial, utilizando o cálculo do Índice de Moran. Os resultados apresentam a distribuição e análise espacial do número de casos confirmados, coeficiente de incidência e quantitativo de óbitos pela COVID-19 no Estado. A espacialidade pode explicar o coeficiente de incidência da doença. Foi estimado o potencial para a sustentabilidade e gerado o mapa de risco do potencial para a sustentabilidade, no pós-pandemia do COVID-19, para os municípios do Rio Grande do Sul.   Spatial analysis and distribution of the potential for sustainability in the post-pandemic of COVID-19 in the municipalities of Rio Grande do Sul A B S T R A C TThe pandemic caused by the coronavirus triggered the possibility of the crisis in several segments, especially with the adoption of social isolation, the main action for the control of the infectious disease, therefore, the present study is justified by the concern in relation to the trends of sustainable development in the post-pandemic of COVID-19, in the state of Rio Grande do Sul. Measuring the degree of sustainability of the municipalities follows the thesis that the greater the degree of sustainability of the municipalities, the less the impact of the pandemic, and the greater the resources to restore balance. The objective of the research is to analyze the spatial distribution of the potential for sustainability in the post-pandemic of COVID-19, in the municipalities of Rio Grande do Sul, in order to generate a risk map with less and greater potential for sustainability in the post- pandemic. This study was carried out by means of an ecological analysis and application of the Barometer of sustainability, later the distribution and spatial analysis was carried out by means of the Moran Index. The spatial analysis, performed by calculating the Moran Index, showed significant spatial independence for confirmed cases (I = 0.058; p = 0.024) and deaths (I = 0.032; p = 0.039), and a significant, albeit weak, correlation. for the incidence coefficient (I = 0.234; p = 0.001) of COVID-19. Spatiality does not explain the distribution of cases and deaths. However, when taking into account the population size of the municipalities, in relation to the number of cases, expressed by the incidence coefficient, the spatial aggregation gains merit. The potential for sustainability was estimated and the risk map of the potential for sustainability was generated, in the post-pandemic of COVID-19, for the municipalities of Rio Grande do Sul.Keywords: Moran index; Sustainability Barometer; Sustainability Index; coronavirus; Pandemic.


Author(s):  
A. E. Akay ◽  
A. Erdoğan

Abstract. Large forest lands are damaged every year due to wild fires in Turkey. Prompt detection and rapid intervention is the key factors of firefighting activities. To be well prepared for the wildfires, it is crucial to determine the fire sensitive areas and then to locate fire extinguishing structures such as fire lookout towers and the firefighting headquarters by consideration these areas. The accuracy of the fire risk maps plays important role in the effectiveness of the fire management strategies and decisions. In this paper, the accuracy of a fire risk map, which was developed by GIS techniques integrated with Multi-Criteria Decision Analysis (MCDA), was evaluated based on the previous fire incidence in the study area. Analytic Hierarchy Process (AHP) method was used to generate fire risk map based on topographic features and forest vegetation structures. Then, total of 19 forest fires recorded in the study area in last 50 years were evaluated to validate the risk map. It was found that 23.81% of the area was subject to extreme risk, while 25.81% was of high risk. The results indicated that about 42.10% of the fire events fell into the forested areas with extreme fire risk, while 31,58% were in the high fire risk. Thus, the fire risk map developed by using the GIS-based MCDA can be an effective way for accurate estimation of the fire sensitive areas.


2021 ◽  
pp. 24-67
Author(s):  
Ba Le Huy ◽  
Hoan Nguyen Xuan ◽  
Thanh Le Minh

2021 ◽  
Vol 1 (2) ◽  
pp. 78-84
Author(s):  
Raden Theodorus Soepraptomo ◽  
Fitri Hapsari ◽  
Teddy Wijaya

Placenta accreta is one of the emergency conditions and has resulted in increased mortality and morbidity of pregnant women due to the massive obstetric hemorrhage. Placenta accreta can lead to secondary complications including coagulopathy, multisystem organ failure, acute respiratory distress syndrome, need for repeat surgery, and death. Assessment by anesthesia should be carried out as early as possible before surgery to reduce or even eliminate morbidity and mortality. In this report, we present the case of a patient with total placenta previa and high-risk MAP score with a transverse lie fetal position. The various anesthetic treatments and transfusion strategies are discussed with a multidisciplinary approach to delivery.


Author(s):  
Arshad Ali

Climate change has put the planet earth on high risk due to flash, riverine flooding and droughts. Unprecedented frequent flooding, hurricanes, droughts and heavy snowfalls can be witnessed in the past few decades. Now no country can declare itself safe from the negative impacts of changing climate. To reduce the risk of potential damages, vulnerability and risk assessment can give a clear picture of a particular region regarding a specific hazard. It will help the administration to address those areas which are highly at risk due to a certain hazard so as to minimize collateral damages in future. In Khyber Pukhtoonkhwa, Nowshera was one of the most affected districts. It has destroyed building stock, livestock and crops in most parts of the district. To minimize these losses in future, this research has been carried out to assess the current condition of building stock in Nowshera Cantt and Nowshera City area. This research explores in detail the building stock vulnerability and associated risk. This research has found that the flood reoccurrence time period is 7 years for zone 1and 7. While other zones 2, 3,4,5,6,8 and 9 have 81 years of reoccurrence time period. Based on the physical vulnerability, this research found that there are five types of buildings in the study area. Vulnerability of Type 1 to 5 are varying  from strong to weak according to its  structures having RCC roof, strong walls, plain concrete / tiles floor. Flood risk map has been produced on the basis of flood frequency and typology of high frequency structures in that particular area. The research explicitly shows different areas in risk map according to the level of risk i.e. from low to high risk zones.  This research has found that binding material is the major factor in structural damages in the study area.


2021 ◽  
Vol 7 (11) ◽  
pp. 106979-106990
Author(s):  
Clayton Assis Da Silva ◽  
Maria Luiza Araújo De Farias ◽  
Antonio Romão Alves Da Silva Filho ◽  
Isabel De Cássia Marcelino Da Silva ◽  
José Floro De Arruda Neto ◽  
...  
Keyword(s):  
Risk Map ◽  

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