Damage caused by flood events is expected to increase in the coming decades driven by increased land use pressures and climate change impacts. The insurance sector needs accurate and efficient loss adjustment methodologies for flood events. These can include remote sensing approaches that enable the rapid estimation of (i) damage caused to property as well as (ii) the number of affected properties. Approaches based on traditional remote sensing methods have limitations associated with low-cloud cover presence, oblique viewing angles, and the resolution of the geomatic products obtained. Unmanned aerial vehicles (UAVs) are emerging as a potential tool for post-event assessment and provide a means of overcoming the limitations listed above. This paper presents a UAV-based loss-adjustment framework for the estimation of direct tangible losses to residential properties affected by flooding. For that purpose, features indicating damage to property were mapped from UAV imagery collected after the Desmond storm (5 and 6 December 2015) over Cockermouth (Cumbria, UK). Results showed that the proposed framework provided an accuracy of 84% in the detection of direct tangible losses compared with on-the-ground household-by-household assessment approaches. Results also demonstrated the importance of pluvial and, from eye witness reports, lateral flow flooding, with a total of 168 properties identified as flooded falling outside the fluvial flood extent. The direct tangible losses associated with these additional properties amounted to as high as £3.6 million. The damage-reducing benefits of resistance measures were also calculated and amounted to around £4 million. Differences in direct tangible losses estimated using the proposed UAV approach and the more classic loss-adjustment methods relying on the fluvial flood extent was around £1 million—the UAV approach providing the higher estimate. Overall, the study showed that the proposed UAV approach could make a significant contribution to improving the estimation of the costs associated with urban flooding, and responses to flooding events, at national and international levels.

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.

<p>Pluvial (surface water) flooding is often the cause of significant flood damage in urban areas. However, pluvial flooding is often overlooked in catchments which are historically known for fluvial floods. In this study, we present a conceptual remote sensing-based integrated approach to enhance current practice in the estimation of flood extent and damage and characterise the spatial distribution of pluvial and fluvial flooding. Cockermouth, a small town in England which is highly prone to flooding, was selected as a study site and the flood event caused by storm Desmond in 2015 (5-6/12/2015) was selected for this study. A high-resolution digital elevation model (DEM) was produced from a composite digital surface model (DSM) and a digital terrain model (DTM) obtained from the Environment Agency. Using this DEM, a 2D flood model was developed in HEC-RAS (v5) 2D for the study site. Simulations were carried out with and without pluvial flooding. Calibrated models were then used to compare the fluvial and combined (pluvial and fluvial) flood damage areas for different land-use types. The number of residential properties affected by fluvial and combined flooding was compared using a combination of modelled results and data collected from Unmanned Areal System (UAS). As far as the authors are aware, this is the first time remote sensing data, hydrological modelling and flood damage data at property level have been combined to differentiate between the flood extents and damage caused by fluvial and pluvial flooding in the same event. Results show that the contribution of pluvial flooding should not be ignored even in a catchment where fluvial flooding is the major cause of the flood damages. Although the additional 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 affected properties by 25%. In addition, it increased the flood depths in a number of properties that were identified as being affected by fluvial flooding, in some cases by more than 50%. These findings show the importance of taking pluvial flooding into consideration in flood management practices. Further, most of the data used in this study were obtained via remote sensing methods, including UASs. This demonstrates the merit of developing a remote sensing-based framework to enhance current practice in the estimation of flood extent and damage.</p>

<p align="justify">The recent droughts and unprecedented floods in Central Europe have revealed our vulnerability to extreme weather events. Besides climate change as a driver of more frequent and intensifying extreme events, demographic change and socio-economic development exacerbate severe impacts. International frameworks for disaster risk reduction (DRR) and climate change adaptation (e.g. Sendai framework for DRR, EU Strategy on adaptation to climate change) acknowledge the critical need for integrating risk governance, communication and operational mechanisms for coping with extreme climate events throughout the entire Disaster Risk Management cycle.</p> <p align="justify">DIRECTED aspires to foster disaster-resilient European societies by expanding our capabilities to communicate, utilise and exchange state-of-the-art data, information and knowledge between different actors. The project strives to boost the integration, accessibility and interoperability of models, facilitating knowledge sharing and improving dialogue and cooperation on all levels of Disaster Risk Management cycle. Four regional and municipal Real World Labs in the Capital Region of Denmark, the Danube Region, Emilia Romagna Region, Italy and the Rhine-Erft District, Germany, are at the centre of the bottom-up, value-driven co-development approach. The Real World Labs ensure the project continuously and actively involves key stakeholders in the development process and address topical problems of multi-hazard risk management and climate change adaptation to maximise the impacts of the DIRECTED project. Key to supporting interoperability will be the establishment of the DATA-FABRIC, an innovative, federated cloud platform that enables secure, flexible, discovery and sharing of all structured and unstructured data. DIRECTED is committed to promote the power of open data and open science in all of its research efforts.</p> <p align="justify">Through an interdisciplinary approach that brings together natural and social scientists, with data experts, local stakeholders as well as first and second responders DIRECTED builds lasting real world partnerships and leverages synergies for Disaster Risk Reduction and Climate Change Adaptation efforts in Europe.</p>

<p>New catastrophe and disaster risk data, tools and services can often include complex science and algorithms that offer profoundly important information on understanding risk or can inform climate adaption. However, if few people know about or understand how and in what context to use these tools, they remain on the databases of academic institutions and in scientific journals across the world. How many tools that could transform the world’s understanding of risk and ways to adapt to that risk already exist or are currently under development? The answer is likely to be in the hundreds. But, how many of those tools have ever been used beyond one or two scientific case studies? The answer is likely to be, in most cases, very few.</p><p> </p><p>Academic institutions often administer barriers on access to their data and tools through institutional data management and by specifically implementing non-commercial use licensing in the dissemination of tools once scientific studies are completed. In addition, very commonly, insufficient thought is put to the exploitation strategies of these tools. The gaps in understanding and trust between academia and the needs of business sometimes feel insurmountable on both sides. Is ‘custom’ defying reason in the face of the climate change crisis and the need for rapid systems transformation globally?</p><p> </p><p>The Oasis family, offers new approaches around transparency, collaboration, dissemination and exploitation and the encouragement of intereoperability by providing platforms that allow for comparative approaches to scientific data and tools.</p><p> </p><p>Firstly, "OASIS LMF is an open source platform for developing, deploying and executing catastrophe models to enable the “plug and play” of hazard and vulnerability modules (along with exposure and insurance policy terms) by way of a set of data standards that describe a model. It has been built in collaboration with the insurance industry (https://oasislmf.org/)." Oasis Palmtree offers support to enable access to this system.</p><p> </p><p>Secondly, Oasis Hub, has designed science innovation approaches to bringing tools and data to wider, diverse audiences in collaboration with scientific institutions. We discuss "OASIS Hub, as a global window and conduit to free and commercial environmental, catastrophe and risk data, tools and services (https://oasishub.co/) as an example of a new innovation approach.</p>