A Remote Sensing Based Integrated Approach to Quantify the Impact of Fluvial and Pluvial Flooding in an Urban Catchment

Abstract

Pluvial (surface water) flooding is often the cause of significant flood damage in urbanareas. However, pluvial flooding is often overlooked in catchments which are historically knownfor fluvial floods. In this study, we present a conceptual remote sensing based integrated approachto enhance current practice in the estimation of flood extent and damage and characterise the spatialdistribution of pluvial and fluvial flooding. Cockermouth, a town which is highly prone to flooding,was selected as a study site. The flood event caused by named storm Desmond in 2015 (5-6/12/2015)was selected for this study. A high resolution digital elevation model (DEM) was produced from acomposite digital surface model (DSM) and a digital terrain model (DTM) obtained from theEnvironment Agency. Using this DEM, a 2D flood model was developed in HEC-RAS (v5) 2D forthe study site. Simulations were carried out with and without pluvial flooding. Calibrated modelswere then used to compare the fluvial and combined (pluvial and fluvial) flood damage areas fordifferent land use types. The number of residential properties affected by both fluvial and combinedflooding was compared using a combination of modelled results and data collected from UnmannedAircraft Systems (UAS). As far as the authors are aware, this is the first time that remote sensingdata, hydrological modelling and flood damage data at a property level have been combined todifferentiate between the extent of flooding and damage caused by fluvial and pluvial flooding inthe same event. Results show that the contribution of pluvial flooding should not be ignored, evenin a catchment where fluvial flooding is the major cause of the flood damages. Although theadditional flood depths caused by the pluvial contribution were lower than the fluvial flood depths,the affected area is still significant. Pluvial flooding increased the overall number of affectedproperties by 25%. In addition, it increased the flood depths in a number of properties that wereidentified as being affected by fluvial flooding, in some cases by more than 50%. These findingsshow the importance of taking pluvial flooding into consideration in flood management practices.Further, most of the data used in this study was obtained via remote sensing methods, includingUAS. This demonstrates the merit of developing a remote sensing based framework to enhancecurrent practices in the estimation of both flood extent and damage.