scholarly journals Disaster risk assessment for urban areas: A GIS flood risk analysis for Luján City (Argentina)

2019 ◽  
Vol 1 ◽  
pp. 1-2
Author(s):  
Ignacio Agustin Gatti ◽  
Takashi Oguchi

<p><strong>Abstract.</strong> Floods frequently cause disasters worldwide. In Argentina, almost half of disasters are related to floods (Celis &amp; Herzer, 2003). During the period 1944 to 2005, 41 major floods occurred in urban areas in the country (Argentina Red Cross, 2010) with more than 13 million people affected. Luján (34°33′S, 59°07′W) is a city of about 110,000 people, situated 21 m above the mean sea level in a relatively plain area. It suffered from 21 floods between 1967 and 2018 with a result of about 14,600 evacuees and 3 dead people. The main cause of the floods is the overflow of the Luján River, which has an average flow of 5.37&amp;thinsp;m<sup>3</sup>/s (INA, 2007).</p><p> The National Disaster Risk Assessment guidelines (UNDP, 2010; UNSIDR, 2018) outline the use of qualitative or quantitative approaches to determinate the acceptable level of risk. Risk has been associated with a potential loss with different levels of certainty (Crichton, 1999; WMO, 2013), and it could be defined as a combination of hazard, exposure and vulnerability (Akhtar et al, 2018; Behanzin, 2015; Armeneakis et al., 2017; UNISDR, 2017) (Figure 1). If one of those elements is missing, risk is not defined. The hazard is related to the potential danger that the natural phenomenon has, which is inherent to the event itself, and it would be inundation scenarios in this study. Vulnerability has been defined by Cardona et al. (2012) as a propensity or predisposition to be adversely affected. That definition includes the characteristics of a person or a group, and their situation that influences their capacity to anticipate, cope with, resist, and recover from the adverse effects of physical events (Natenzon et al., 2005; González, 2009). The perspectives selected in the present work focus on working with social vulnerability which is linked to socio-economical population conditions and the possibility of these being affected. Spatial distribution of exposure (elements at risk) in proximity to a hazard is a significant factor of disaster risk (UNISDR, 2017). Some researchers (González et al., 1998; Villagrán De León, 2001; Moel et al., 2009) defined “exposure” as what can be affected by a flood such as buildings, land use, and population, the latter of which is a significant factor of disaster risk (UNISDR, 2017). Flood risk maps play an important role in decision-making, planning and implementing flood management options (WMO, 2013).</p><p> Geographical Information Systems (GIS) enable us to perform a spatial analysis of the elements of risk (hazard, vulnerability, and exposure) for Luján City. By creating categories from the selection of some indicators, it is possible to define which area is more likely to be impacted by a flood, which population and which infrastructure are more exposed, and who is more vulnerable. A final flood risk index is created with five categories based on risk values from 0 (lowest) to 1 (highest) (Figure 2).</p><p> Hazard analysis is made by using a 5-m Digital Elevation Model (DEM), rainfall data, land use information, drainage system (sewers and streams) and historical flood maps. Sources of vulnerability and exposure indicators are data from the last National Argentinian Census in the year 2010.</p><p> Although it is impossible to totally eliminate the flood risk, it is possible to mitigate some consequences. Findings from this study illustrate that some areas of higher flood risk coincide with areas of high flood hazard, more exposed, and more vulnerable. This methodology helps to develop disaster risk management strategies for settlements frequently flooded.</p>

2020 ◽  
Vol 24 (5) ◽  
pp. 25-40
Author(s):  
Chonlatid Kittikhun ◽  
Sitang Pilailar ◽  
Suwatana Chittaladakorn ◽  
Eakawat Jhonpadit

Flood Risk Index (FRI) is the multi-criteria linked with the factors of vulnerability; exposure, susceptibility, and resilience. In order to establish local FRI, crucial local information have to be accumulated. However, under the limitation of land-use data, particular techniques were applied in this study. CA Markov model was used to analyze the past missing land-use data and, also forecast the future land-use of Pakpanang river basin under conditions of plan and without plan. The ratio changes of forest, agriculture, wetland and water, and urban areas were considered. Then, the result of LULC spatial-temporal changes was then applied to Hec-HMS and Hec-Ras , with Arc GIS extension of Hec-GeoHMS and Hec-GeoRas software, in order to evaluate the flood hydrographs and flood severity in three municipalities corresponding to 100-year return period rainfall. Afterward, the FRI of Pakpanang, Chianyai, and Hua-sai, which ranges from 0 to 1, were evaluated by using the modified FRI equations. It was found that sensitivity analysis in the area of forest on flood depth and inundation areas is incoherent. Nevertheless, without land-use planning, the changes in these three cities cause higher flood risk, where Chianyai is the riskiest as the FRIE is 0.58. Further consideration of FRIE and FRIP proportion that reveals the FRI deviation indicates that to reduce flood risk, Chianyai would need the most resources and highest effort comparison to Pakpanang and Hua-sai.


2021 ◽  
Vol 12 (2) ◽  
pp. 269-291
Author(s):  
Alisa Sahu ◽  
Tushar Bose ◽  
Dipak R. Samal

Urban flooding is growing as a serious development challenge for cities. Urbanization demands the conversion of pervious land to impervious land by pushing the transformation of water bodies, flood plains, wetlands and green spaces into built-up spaces. This affects the hydrological setting of the city’s geographic area. Bhubaneswar, one of the first planned cities of independent India, has expanded rapidly with an increase in the settlement land use cover from 41 km2 to 81 km2 in the last two decades. Non-consideration of disaster risk assessment in the land use plan has placed the city at high disaster risk. Hence, this article explores various avenues for making a flood resilient city through spatial planning. To understand the flood and its consequences, a flood hazard and vulnerability map was prepared by overlaying the existing social and infrastructure networks, and flood risk zones were generated through analytical spatial modelling in GIS. This accounts for the areas in which flood hazards are expected to occur, as well as the area whose socio-economic and infrastructure susceptibility to the disaster is more. The key outcome is to ensure urban development that can work concurrently with nature by integrating disaster risk reduction strategies into land use planning.


2018 ◽  
Vol 38 (11) ◽  
Author(s):  
彭建 PENG Jian ◽  
魏海 WEI Hai ◽  
武文欢 WU Wenhuan ◽  
刘焱序 LIU Yanxu ◽  
王仰麟 WANG Yanglin

Author(s):  
Taowei Chen ◽  
Ling Zhu ◽  
Qiao Xia ◽  
Honglei Deng ◽  
Chen Zhou

Author(s):  
Seyedeh Samaneh Miresmaeeli ◽  
Nafiseh Esmaeili ◽  
Sepideh Sadeghi Ashlaghi ◽  
Zahra Abbasi Dolatabadi

Abstract Background: Exceptional children, like other children, have the right to be educated in a safe environment. Disasters are considered as serious issues regarding safety and security of educational environments. Following disasters, vulnerable groups, especially children with handicaps and disabilities are more likely to be seriously injured. Thus, the present study aimed to evaluate the safety and disaster risk assessment of exceptional schools in Tehran, Iran. Method: The cross-sectional study was conducted in exceptional schools in Tehran, 2018. First, 55 exceptional schools in all grades were selected based on census sampling method and evaluated by using a checklist designed by Tehran Disaster Mitigation and Management Organization (TDMMO) and Ministry of Education in 2015. The data were analyzed using Excel software and statistical descriptive tests. Result: Based on the results, school facilities are worn and have unsafe elevators (least safety: 7.69%), yards (least safety: 9.52%), laboratories (least safety: 16.67%), libraries (least safety: 24.24%), fire extinguishing systems (least safety: 28.99%), and storage rooms and kitchens (least safety: 33.33%) which require immediate considerations. In total, the safety of exceptional schools in this study was 70.13%, which suggests medium-risk level. Conclusion: The educational settings must be reconsidered, along with identifying the risk and safety at school. In addition, a standard should be established for evaluating safety, especially in exceptional schools.


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