Surface runoff estimation in urban areas via remotely sensed greenery and composite curve number

Traditionally, flood risk maps used by city officials and water resource managers for urban planning, by engineers for adequate flood defence infrastructure design, or by insurers and re-insurers for estimating financial risk exposure are the result of modelling flood hazard of rivers and their associated floodplain lands at different return periods. Often, any of these stakeholders would use the 1:100 return period of fluvial hazard to plan accordingly. 

However, with the climate crises signals clearly present during recent flood disasters, and especially with the 2021 Europe floods, water managers, cities and the financial risk sector are now starting to plan differently and are recognizing the need not only for better and more frequently updated flood risk analysis, particularly in urban areas, but also need to consider pluvial and flash floods that can happen in any part of a river basin and oftentimes take place in headwater areas or off the main river floodplains. Flash flooding greatly impacts urban areas where the storm drainage infrastructure is becoming largely insufficient due to the increasing duration and higher frequency of extreme intense rainstorms. Therefore, model simulations of flood hazard that account for these rather unprecedented types of extremely destructive events are required, and those need to be integrating the newest data from all types of sensors. At the same time, we observe that sustainable, nature-based solutions are now sought after because these solutions offer an inviting alternative to ever changing flood risk, particularly under the present and future climate crisis.  

It is stipulated that increasing healthy urban vegetation cover could reduce this risk and is a form of a nature-based solution for urban areas. Here we combine existing methods from the literature and develop a methodology relating  time-series of satellite-based vegetation maps, topography and soil permeability to estimate excess runoff from intense precipitation. The runoff coefficient is mapped through the use of a composite curve number method.. The method of looking at  the partition between rainfall and runoff is highly correlated to change in land use, and thus changes in vegetation cover. Relying on the NDVI index for green vegetation mapping, the methodology is able to capture the differences in the hydrological response even for seasonal or canopy integrity changes. Looking at different vegetation cover scenarios therefore allows the creation of different runoff responses, and therefore a possible reduction in flood risk.In this paper, we present initial results of this flood risk analysis, the goal of which is to produce runoff change maps at city, urban neighbourhood or city post code level using different scenarios in rainfall amounts from design storms coupled with existing or planned urban vegetation cover scenarios.