Flood damage and loss estimation Research Papers (original) (raw)

Floods are one of the most common and hazardous natural disasters worldwide. In Malaysia, flood is the reason for highest economic damages and loss of human lives as well. Frequency and magnitude of flood is increasing not only because of climate change, but also anthropogenic activities are directly related to it. This study based on a survey where 280 respondents participate who lives in the Temerloh district which is in the midstream zone of Pahang River basin. This paper highlights respondents flood experience and identifies the cause of flood from the view of lay people. Results show that respondents are well known and experienced about the flood and flood related damages. However, their perception about cause of flood was only focused on the natural cause ignoring anthropogenic activities such as land use changes which may reflect the land use change in this area. To identify the land use changes, we also used classified shape file of 2000 and 2010 from Department of Agriculture, Malaysia and used overlay procedure in ArcGIS 10.1.
Within only 10 years, significant land use changes were found which can increase the future flood risk. Policy makers and decision makers should involve the local community in the decision making which may develop their flood risk perception and awareness about sustainable land use.

As a natural hazard, floods can cause significant damage to buildings. Buildings are one of the important components of an economy which are providing the necessary space for human activities. In this regard, any considerable changes to their serviceability affect the living condition of people locally, regionally, and even globally. Thus, building damage analysis forms a crucial part of a flood risk analysis. This review paper provides an insight into flood damage analysis for a building structure and contents: past works, current state, and required improvements. The discussed buildings include residential, commercial, and industrial types. The methods are divided into two main categories: (1) using real data and empirical models, and (2) using what-if analysis and analytical models. Differences in damage analysis of a building structure and its contents are explained in a separate section. Flood factors influencing the damage to a building structure and its contents are presented. How a method considers some of those flood factors is described. Limitations and shortcomings of each method alongside their advantages and strength are discussed. The lack of reliable data for both model construction and validation is one of the main issues with the methods in both categories. Inability to convey uncertainty is the other main issue identified in the literature.

- by Morteza T. Marvi
- •
- Natural Hazards, Risk and Vulnerability - Natural Hazards, Flood Risk, Fragility

A largely undistinguished, former politician who briefly led an extremely minor (territorial) jurisdiction in the outback of Australia a long time ago wants the city of Lismore moved. To higher ground. Where it will cost taxpayers less. You should be careful who you appoint to positions such as Coordinator General of the National Recovery and Resilience Agency. And occupants of these kinds of positions should be especially careful what they say immediately following disasters. Shane Stone has been lambasted for his gross insensitivity after his awful contribution last week: On Friday Stone, the coordinator general of the National Recovery and Resilience Agency, told the Sydney Morning Herald that "the taxpayer and the ratepayer cannot continue to pick up the bill for these huge, catastrophic damage events". "You've got people who want to live among the gum trees-what do you think is going to happen? Their house falls in the river and they say it's the government's fault," Stone reportedly said.

- by Paul Collits
- •
- Retail, Disaster Management, Australian Politics, Natural Disasters

Le changement climatique en Afrique tropicale expose de nombreux établissements ruraux à des précipitations intenses. La dégradation des bassins versants transforme ces précipitations en inondations catastrophiques. Mais les impacts des précipitations intenses dépendent également de l'expansion du bati dans les zones inondables, sur laquelle les connaissances sont encore rares. L'objectif de ce chapitre est de réaliser une évaluation détaillée du risque, qui identifie les biens exposés aux inondations pluviales, estime l'impact et l'efficacité des mesures de réduction du risque. L'évaluation est réalisée dans quatre petites villes du Niger rural en plein essor, qui ont été inondées à plusieurs reprises au cours des dernières années. Les zones inondables suite à des pluies avec période de retour de 3 et 20 ans sont identifiées à l'aide d'un modèle hydrologique bidimensionnel selon que le bassin versant reste dans son état actuel ou est traité avec des mesures de réduction du risque. Les biens exposés sont identifiés par photointerprétation visuelle d'images à très haute résolution et leur valeur de remplacement est estimée. Les mesures de réduction des risques sont identifiées par des discussions avec les communautés. Le risque résiduel et le rapport bénéfice/coût du traitement du risque sont estimés. Le résultat est qu'au cours des 10 dernières années, l'expansion des 4 petites villes est plus rapide dans la zone inondable. Il reste peu de zones sûres pour permettre une expansion future. La cartographie des zones et des éléments exposés aux inondations est donc essentielle pour réduire l'exposition future aux inondations. La rétention d'eau, les toits en tôle ondulée, les barrières anti-inondation, les latrines surélevées et les puits sont des mesures efficaces pour réduire le risque, surtout en cas de précipitations intenses et fréquentes.

- by Maurizio TIEPOLO
- •
- Risk assessment, Citizen Science, Disaster risk reduction, Benefit Cost Analysis

Flood risk assessments in the Global South have increased since the adoption of the United Nations Sendai Framework for Disaster Risk Reduction 2015–2030. However, they often fail to meet disaster risk reduction needs at the local scale, because they typically consider only one hazard (fluvial or pluvial floods). Furthermore, hazard and exposure are considered as stationary conditions, flood-prone assets are rarely identified, risk reduction measures are not identified in detail for specific locations, and the convenience of reducing or accepting risk is not evaluated. This paper describes a flood risk assessment method that is innovative in that it considers three hazard types (backwater, fluvial, and pluvial floods) and multiple risk scenarios; it uses orthophotos generated from images captured by an unmanned aerial vehicle and very high-resolution satellite images, and it involves communities in risk assessment. The method was applied to four rural settlements along the Sirba River, Niger. The assessment identifies the benefit of reducing risk in monetary terms, as well as the intangible benefits that reducing risk could generate, and it detects opportunities that flooding offers for rural development. The method can be replicated in all contexts where decision-making support is needed for flood risk assessment planning.

Reliable information on building stock and its vulnerability is important for understanding societal exposure to floods. Unfortunately, developing countries have less access to and availability of this information. Therefore, calculations for flood damage assessments have to use the scarce information available, often aggregated on a national or district level. This study aims to improve current assessments of flood damage by extracting individual building characteristics and estimate damage based on the buildings' vulnerability. We carry out an object-based image analysis (OBIA) of high-resolution (11 cm ground sample distance) unmanned aerial vehicle (UAV) imagery to outline building footprints. We then use a support vector machine learning algorithm to classify the delineated buildings. We combine this information with local depth-damage curves to estimate the economic damage for three villages affected by the 2019 January river floods in the southern Shire Basin in Malawi and compare this to a conventional, pixel-based approach using aggregated land use to denote exposure. The flood extent is obtained from satellite imagery (Sentinel-1) and corresponding water depths determined by combining this with elevation data. The results show that OBIA results in building footprints much closer to OpenStreetMap data, in which the pixel-based approach tends to overestimate. Correspondingly, the estimated total damage from the OBIA is lower (EUR 10 140) compared to the pixel-based approach (EUR 15 782). A sensitivity analysis illustrates that uncertainty in the derived damage curves is larger than in the hazard or exposure data. This research highlights the potential for detailed and local damage assessments using UAV imagery to determine exposure and vulnerability in flood damage and risk assessments in data-poor regions.

- by Marc van den Homberg
- •
- Geology, Flood damage and loss estimation

The use of high resolution ground-based light detection and ranging (LiDAR) datasets provides spatial density and vertical precision for obtaining highly accurate Digital Surface Models (DSMs). As a result, the reliability of flood damage analysis has improved significantly, owing to the increased accuracy of hydrodynamic models. In addition, considerable error reduction has been achieved in the estimation of first floor elevation, which is a critical parameter for determining structural and content damages in buildings. However, as with any discrete measurement technique, LiDAR data contain object space ambiguities, especially in urban areas where the presence of buildings and the floodplain gives rise to a highly complex landscape that is largely corrected by using ancillary information based on the addition of breaklines to a triangulated irregular network (TIN). The present study provides a methodological approach for assessing uncertainty regarding first floor elevation. This is based on: (i) generation an urban TIN from LiDAR data with a density of 0.5 points¨m´2 , complemented with the river bathymetry obtained from a field survey with a density of 0.3 points¨m´2. The TIN was subsequently improved by adding breaklines and was finally transformed to a raster with a spatial resolution of 2 m; (ii) implementation of a two-dimensional (2D) hydrodynamic model based on the 500-year flood return period. The high resolution DSM obtained in the previous step, facilitated addressing the modelling, since it represented suitable urban features influencing hydraulics (e.g., streets and buildings); and (iii) determination of first floor elevation uncertainty within the 500-year flood zone by performing Monte Carlo simulations based on geostatistics and 1997 control elevation points in order to assess error. Deviations in first floor elevation (average: 0.56 m and standard deviation: 0.33 m) show that this parameter has to be neatly characterized in order to obtain reliable assessments of flood damage assessments and implement realistic risk management.

- by Jose Bodoque
- •
- LiDAR, Flood damage and loss estimation

Flood risk reduction at the local scale requires knowledge of the settlements which are most exposed to floods, and those where the existing measures are insufficient to handle the threats. The knowledge on spatial dynamics of the flooded human settlements is limited, especially that of the smaller ones, such as the settlements in the sub-Saharan Africa. The dataset on 122 flooded settlements in the Dosso Region (Niger) offers information on: the built-up area and the number of buildings with corrugated iron roofs in 2004, 2012, and 2019 (average dates), the type of human settlements (city, rural town, village, or hamlet), the flood dates and the number of buildings collapsed between 2011 and 2019. The data on the built-up area and the number of buildings with corrugated iron roofs were extracted by visual photointerpretation from very high-resolution images accessible through Google Earth Pro. The information on the settlement category was obtained from the Human Settlements National Directory (French acronym, ReNaLoc) published by the National Institute of Statistics of Niger. The dates of floods and the data on the number of collapsed buildings were obtained from the open access national database on flooding, known by the French acronym, BDINA. These data can be reused to build a geodatabase for flood risk reduction and to draft the municipal and regional development plans. Their potential reuse allows for the identification of settlements undergoing the most rapid physical expansion, built-up area in a flood-prone zone, and settlements that require protection and flood risk reduction policies. Additionally, the dataset can also be used to verify the accuracy of the built-up area obtained from the satellite images with coarse resolution and for comparisons with other regions in Niger and in sub-Saharan Africa.

- by Maurizio TIEPOLO
- •
- West Africa, Built Environment, Small country towns, Rural Settlement

Floods are one of the most common natural disasters worldwide. In Malaysia, floods cause significant economic damage and loss of human life. The frequency and magnitude of floods are increasing due to climate change and related anthropogenic activities. This study surveyed 280 respondents living in the Temerloh district which is in the midstream zone of the Pahang River Basin. This paper highlights their flood experience and identifies the cause of floods from the view of lay people. Results show that respondents are experienced in flood and flood-related damages. However, their perception of the causes of floods focused on natural causes while ignoring anthropogenic activities such as land use changes. To identify the land use changes, we used a classified shapefile for the years 2000 and 2010 from the Department of Agriculture, Malaysia and used overlay procedure in ArcGIS 10.1. Within the ten years, significant land use changes took place which could increase future flood risks. ...

- by Nor Diana Mohd Idris
- •
- Geography, Epistemology of the Social Sciences, Land Use Change, Flood Risk