Application of geographic weighted regression to establish flood-damage functions reflecting spatial variation

Abstract

Flood damage functions are necessary to ensure comprehensive flood-risk management. This study attempts to establish a residential flood-damage function through interviewing the residents living in the region where flood disasters occur frequently. Keelung River basin, near Taipei Metropolitan in Taiwan was selected as study area. Flood damages are related to the flood depths, which are the most commonly considered factor in previously published work. Ordinary least squares (OLS) regression was used to construct the flood-damage function at the beginning. Analytical results indicate that flood depth is the significant variable, but the spatial pattern of the residuals shows that residuals exhibit spatial autocorrelation. The Geographically Weighted Regression (GWR) Model was then applied to modify the traditional regression model, which cannot capture spatial variations, and to reduce the problem of spatial autocorrelation. The R-square value was found to increase from 0.15 to 0.24, and the spatial autocorrelation in the residuals was no longer evident. A modified OLS model with a dummy variable to capture the spatial autocorrelation pattern was also proposed for future applications. In conclusion, the residential flood damage is determined by flood depth and zone, and the GWR model not only captures the spatial variations of the affecting factors, but also helps to discover the independent variable to modify the traditional regression model.

A Model-Based Flood Hazard Mapping on the Southern Slope of Himalaya

“…A total of 132 km of rural-urban roads and 22 km of highways were inundated during the flood. In summary, this study can support in future planning and decision-making for improved water resources management and development of flood control plans on the southern slope of Himalaya.Therefore, floods are considered as one of the most severe and most frequent water-induced natural disasters, causing major damage to habitat, infrastructures, and properties worldwide-regardless of geographical or hydrological locations-and having direct economic impacts [9][10][11][12][13].Recent floods at the southern slope of Himalaya (e.g., Pakistan, Bangladesh, India, as well as other South Asian Nations) have caused thousands of fatalities, the displacement of millions of people and billions of dollars of damage [14,15]. Other transboundary flood events from 1985 to 2018 have caused the deaths of more than 6000 people and displaced millions in China, Nepal, and India (Table 1).…”

“…Therefore, floods are considered as one of the most severe and most frequent water-induced natural disasters, causing major damage to habitat, infrastructures, and properties worldwide-regardless of geographical or hydrological locations-and having direct economic impacts [9][10][11][12][13].…”

Flood loss modelling with FLF-IT: A new Flood Loss Function for Italian residential structures

“…The results are presented in Table 3, which shows that the results of all iterations with the most likely functional parameters r and Dmax lie within the 95% confidence intervals and the FLF-IT model has an acceptable performance. Results of these validation tests illustrate the importance of model calibration, especially when the water depth is the only hydraulic parameter taken into account (Cammerer et al, 2013;Chang et al, 2008;McBean et al, 1986). In other words, flood damage, being a complicated process, could be dependent on more damage influencing parameters than those considered here (Grahn and Nyberg, 2014;Hasanzadeh Nafari et al, 2016c).…”

Estimation of flood land use/land cover mapping by regional modelling of flood hazard at sub-basin level case study: Marand basin

“…Flood is one of the main global hazards causing massive damages to industries such as agriculture, fisheries, housing, and infrastructures that heavily affects social and economic activities (Chang et al 2008). It occurs after heavy rainfall due to rapid accumulation and the runoff from upstream to downstream.…”