Sensitivity of flood damage estimation to spatial resolution

Komolafe, Akinola Adesuji; Herath, Srikantha; Avtar, Ram

doi:10.1111/jfr3.12224

Cited by 23 publications

(16 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Saksena and Merwade () resampled high‐resolution LiDAR DEMs to DEMs of lower resolution and found a relationship between errors arising from DEM properties to fluvial flood inundation maps. Komolafe et al () investigated the sensitivity of spatial resolution of the flood inundation map to damage estimation and concluded that the underestimation or overestimation of damage is dependent on the data integration approach. They did not take the DEM resolution effects into account and only resampled the 50‐m inundation map obtained in previous studies to coarser resolutions.…”

Section: Introductionmentioning

confidence: 99%

DEM Resolution Effects on Coastal Flood Vulnerability Assessment: Deterministic and Probabilistic Approach

Fereshtehpour

Karamouz

2018

Water Resources Research

View full text Add to dashboard Cite

Flood modeling is highly influenced by topography data set. Lower resolution digital elevation models (DEMs) are usually used because of their availability and less computational burden when they are used in modeling applications. However, low accuracy of these DEMs yields to even lower accuracy in flood risk analysis through spatial modeling. This study aims to explore the DEM resolution effects on coastal flood risk assessments. For this purpose, deterministic and probabilistic approaches are employed for flood inundation modeling utilizing hydrologically connected bathtub method. High‐resolution light detection and ranging (LiDAR) DEM is considered as the most accurate data from which different resolution maps are obtained using resampling techniques. This is incorporated into an error analysis framework along with U.S. Geological Survey (USGS) National Elevation Dataset (NED) DEMs. The probabilistic framework is developed by simulating the spatial variability of elevation errors compared to LiDAR DEM through a Monte Carlo‐based method called sequential Gaussian simulation. The proposed methodology is applied to the lower Manhattan in New York City. By integrating the flood model into the developed framework, flood inundation probability at each grid cells is obtained. Furthermore, using the concept of accuracy‐efficiency tradeoffs, a framework for selecting a suitable spatial resolution for probabilistic flood risk assessment has been suggested. The results show that by exercising a range of options presented in this paper, a broader insight into mapping resolution can be provided, improving flood assessment, evacuation zones, and mitigation plans depending upon the data availability in a region.

show abstract

Section: Introductionmentioning

confidence: 99%

DEM Resolution Effects on Coastal Flood Vulnerability Assessment: Deterministic and Probabilistic Approach

Fereshtehpour

Karamouz

2018

Water Resources Research

View full text Add to dashboard Cite

show abstract

“…In summary, the loss differences reached 7.8% and 11.2% during two events when compared with the 1-m and 10-m resolutions. Spatial resolutions used in the assessment had a direct impact on the potential flood heights [21]. However, the flood loss evaluation was often restricted due to the lack of dense observation data [22].…”

Section: Flood Loss Comparison Using Different Resolutionsmentioning

confidence: 99%

Residential Flood Loss Assessment and Risk Mapping from High-Resolution Simulation

Afifi

Chu

Kuo

et al. 2019

Water

View full text Add to dashboard Cite

Since the patterns of residential buildings in the urban area are small-sized and dispersed, this study proposes a high-resolution flood loss and risk assessment model to analyze the direct loss and risk impacts caused by floods. The flood inundation simulation with a fine digital elevation model (DEM) provides detailed estimations of flood-inundated areas and their corresponding inundation depths during the 2016 Typhoon Megi and 2017 Typhoon Haitang. The flood loss assessment identifies the impacts of both events on residential areas. The depth-damage table from surveys in the impacted area was applied. Results indicated that the flood simulation with the depth-damage table is an effective way to assess the direct loss of a flood disaster. The study also showed the effects of spatial resolution on the residential loss. The results indicated that the low-resolution model easily caused the estimated error of loss in dispersed residential areas when compared with the high-resolution model. The analytic hierarchy process (AHP), as a multi-criteria decision-making method, was used to identify the weight factor for each vulnerability factor. The flood-vulnerable area was mapped using natural and social vulnerability factors, such as high-resolution DEM, distance to river, distance to fire station, and population density. Eventually, the flood risk map was derived from the vulnerability and flood hazard maps to present the risk level of the flood disaster in the residential areas.

show abstract

“…Elevation errors are thus transferred first to a hydrodynamic model in terms of flood depth errors, and then to damage model errors (Koivumäki et al, 2010). Differences in simulated flood depths are also observed for different DTMs resolutions and sources (Bhuyian & Kalyanapu, 2017;Komolafe, Herath, & Avtar, 2015;Krebs, Kokkonen, Valtanen, Setälä, & Koivusalo, 2014;Sanders, 2007).…”

Section: Introductionmentioning

confidence: 99%

Effects of digital terrain model uncertainties on high‐resolution urban flood damage assessment

Arrighi

Campo

2019

J Flood Risk Management

View full text Add to dashboard Cite

This work investigates the impact of high‐resolution digital terrain model (DTM) uncertainties on the estimation of urban flood losses. Starting from a Light Detection And Ranging (LiDAR)‐derived DTM of an urban area, four digital terrain representations (raw data, building footprints filled, buildings as waterproof blocks, and different elevation data merged) are used to generate a computational mesh to run a 2D flood model for three inundation scenarios, differing in flood volumes. The most detailed DTM is obtained by merging the DTM with elevation points based on a two‐step optimal interpolation algorithm. A flood damage model based on stage‐damage curves is used to estimate monetary losses to structures at the building scale. Flood maps and flood losses are then compared for each terrain representation. The application of the method to an Italian urban district shows that (a) a significant mismatch between manually surveyed elevation points and DTM can be observed, (b) different sources of elevation data can be merged to obtain an optimal representation of the terrain, (c) in dense urban settlements, important differences in flood extent and losses (up to 180%) occur depending on terrain representation. Considerations on time effort required by the increasing detail of the DTM and on the transferability of the results are presented.

show abstract

Sensitivity of flood damage estimation to spatial resolution

Cited by 23 publications

References 21 publications

DEM Resolution Effects on Coastal Flood Vulnerability Assessment: Deterministic and Probabilistic Approach

DEM Resolution Effects on Coastal Flood Vulnerability Assessment: Deterministic and Probabilistic Approach

Residential Flood Loss Assessment and Risk Mapping from High-Resolution Simulation

Effects of digital terrain model uncertainties on high‐resolution urban flood damage assessment

Contact Info

Product

Resources

About