Flood risk assessment for informal settlements

Abstract

The urban informal settlements are particularly vulnerable to flooding events, due to both their generally poor quality of construction and high population density. An integrated approach to the analysis of flooding risk of informal settlements should take into account, and propagate, the many sources of uncertainty affecting the problem, ranging from the characterization of rainfall curve and flooding hazard to the characterization of the vulnerability of the portfolio of buildings. This paper proposes a probabilistic and modular approach for calculating the flooding risk in terms of the mean annual frequency of exceeding a specific limit state for each building within the informal settlement and the expected number of people affected (if the area is not evacuated). The flooding risk in this approach is calculated by the convolution of flooding hazard and flooding fragility for a specified limit state for each structure within the portfolio of buildings. This is achieved by employing the flooding height as an intermediate variable bridging over the fragility and hazard calculations. The focus of this paper is on an ultimate limit state where the life of slum dwellers is endangered by flooding. The fragility is calculated by using a logic tree procedure where several possible combinations of building features/construction details, and their eventual outcome in terms of the necessity to perform structural analysis or the application of nominal threshold flood heights, are taken into account. The logic tree branch probabilities are characterized based on both the orthophoto recognition and the sample in situ building survey. The application of the methodology is presented for Suna, a sub-ward of Dar es Salaam City (Tanzania) in the Msimbazi River basin having a high concentration of informal settlement

Formalizing the Informal: Understanding the Position of Informal Settlements and Slums in Sustainable Urbanization Policies and Strategies in Bandung, Indonesia

“…At a global level, the challenges that residents endure in informal settlements and slums have been well documented [1,20,23,[36][37][38][39][40][41][42]. These can be summarized as follows:…”

“…Spatial patterns of informal settlements reflect the utilization of the edges of rivers and estuaries, accretion lands on ocean and lagoon foreshores, electricity easements, mangrove wetlands, tidal lagoons and swamps (including their location-induced impacts such as flooding), cemeteries, peri-urban "edge" lands, waste disposal sites and land locked traditional "native villages" [12]. While this typology helps us to understand the morphology of informal settlements in the city, it also reinforces that informal settlements and slums emerge and flourish in locations that are at higher risk to climate change and environmental hazards, such as land slips, steep slopes, flood-prone areas and poor drainage [40][41][42] (see Figure 2). In developing countries, it is estimated four out of every ten non-permanent houses are located in areas subject to landslides, flooding and other natural disasters [43], with informal settlements in such areas with non-compliant technical codes and construction increasingly vulnerable to extreme natural events [44].…”

“…In developing countries, it is estimated four out of every ten non-permanent houses are located in areas subject to landslides, flooding and other natural disasters [43], with informal settlements in such areas with non-compliant technical codes and construction increasingly vulnerable to extreme natural events [44]. reinforces that informal settlements and slums emerge and flourish in locations that are at higher risk to climate change and environmental hazards, such as land slips, steep slopes, flood-prone areas and poor drainage [40][41][42] (see Figure 2). In developing countries, it is estimated four out of every ten non-permanent houses are located in areas subject to landslides, flooding and other natural disasters [43], with informal settlements in such areas with non-compliant technical codes and construction increasingly vulnerable to extreme natural events [44].…”

Visk: A Gis-Compatible Platform for Micro-Scale Assessment of Flooding Risk in Urban Areas

“…Figure 14 a: Risk maps in terms of mean annual rate of exceeding the collapse limit state [17] 4 H c is dropped hereafter for brevity.…”

“…De Risi, F. Jalayer, I. Iervolino, G. Manfredi, and S. Carozza Figure 14 b: Risk maps in terms of the annual probability of exceeding the collapse limit state [17] Exposure to risk: VISK estimates the exposure to risk by calculating the total expected loss or the expected number of people affected for all the buildings identified (see Section 2.1) in the case-study area. The expected repair cost (per building or per unit residential area), E[R], can be calculated as a function of the limit state probabilities and by defining the damage state i as the structural state between limit states i and i+1:…”