Modelling surface water flood risk using coupled numerical and physical modelling techniques

Abstract:

Surface water (pluvial) flooding occurs due to intense precipitation events where rainfall cannot infiltrate into the sub-surface or drain via storm water systems. The perceived risk appears to have increased in recent years with pluvial flood events seeming more severe and frequent within the UK. Surface water flood risk currently accounts for one third of all UK flood risk, with approximately two million people living in urban areas being at risk of a 1 in 200 year flood event. Surface water flooding research often focuses upon using 1D, 2D or 1D-2D coupled numerical modelling techniques to understand the extent, depth and severity of actual or hypothetical flood scenarios. Although much research has been conducted using numerical modelling, field data available for model calibration and validation is limited due to the complexities associated with data collection in surface water flood conditions. Ultimately, the data which numerical models are based upon is often erroneous and inconclusive. Physical models offer an alternative and innovative environment to collect data within. A controlled, closed system allows independent variables to be altered individually to investigate cause and effect relationships. Despite this, physical modelling approaches are seldom used in surface water flooding research. Scaled laboratory experiments using a 9m², two-tiered physical model consisting of: (i) a mist nozzle type rainfall simulator able to simulate a range of rainfall intensities similar to those observed within the United Kingdom, and; (ii) a fully interchangeable, scaled plot surface have been conducted to investigate and quantify the influence of factors such as slope, impermeability, building density/configuration and storm dynamics on overland flow and rainfall-runoff patterns within a range of terrestrial surface conditions. Results obtained within the physical modelling environment will be compared with numerical modelling results using FloodMap (Yu & Lane, 2006) to evaluate the extent to which data collected can be used to inform and support current flood modelling strategies.