SESAME: Finding Ways Of Promoting SME Adaptation To Flood Risk

Small and medium-sized companies and other enterprises (SMEs) around the world are exposed to flood risk and many of the 4.5 million in the UK are at risk. As SMEs represent almost half of total business turnover in the UK, their protection is a vital part of the drive for greater climate change resilience. However, few have measures in place to ensure the continuity of their activities during a flood and its aftermath. The SESAME project aims to develop tools that encourage businesses to discover ways of becoming more resilient to floods and to appreciate how much better off they will be once they have adapted to the ongoing risk. By taking some of the mystery out of flooding and flood risk, it aims to make it susceptible to the same business acumen that enables the UK’s SMEs to deal with the many other challenges they face. In this paper we will report on the different aspects of the research in the project Understanding behaviour Changing behaviour Modelling impacts Economic impacts Through the above the project will advise government, local authorities and other public bodies on how to improve their responses to floods and will enable them to recommend ways to improve the guidelines provided to SMEs in flood risk areas.

Meteomap: Generation Of Meteorological Variables For Distributed Physically-Based Hydrological Modeling

Distributed energy and water balance models require time-series surfaces of the meteorological variables involved in hydrological processes. Most of the hydrological GIS-based models apply simple interpolation techniques to extrapolate the point scale values registered at weather stations at a watershed scale. In mountainous areas, where the monitoring network ineffectively covers the complex terrain heterogeneity, simple geostatistical methods for spatial interpolation are not always representative enough, and algorithms that explicitly or implicitly account for the features creating strong local gradients in the meteorological variables must be applied. Originally developed as a meteorological pre-processing tool for a complete hydrological model (WiMMed), MeteoMap has become an independent software. The individual interpolation algorithms used to approximate the spatial distribution of each meteorological variable were carefully selected taking into account both, the specific variable being mapped, and the common lack of input data from Mediterranean mountainous areas. They include corrections with height for both rainfall and temperature (Herrero et al., 2007), and topographic corrections for solar radiation (Aguilar et al., 2010). MeteoMap is a GIS-based freeware upon registration. Input data include weather station records and topographic data and the output consists of tables and maps of the meteorological variables at hourly, daily, predefined rainfall event duration or annual scales. It offers its own pre and post-processing tools, including video outlook, map printing and the possibility of exporting the maps to images or ASCII ArcGIS formats. This study presents the friendly user interface of the software and shows some case studies with applications to hydrological modeling.