Predicting short term flood risks
Two models for estimating the short term risk of a flood exceeding some critical flow, which take account of the season and prevailing conditions have recently been published. The model proposed by Ettrick (1986) is based on conditional probability distributions, while Smith and Karr (1986) relate the rate of exceedence of the critical level of interest to relevant covariates. Both models are fitted to a 1000 year synthetic data set, to compare the results with empirically derived immediate and 30 day ahead risk estimates. After some modifications to the Smith and Karr model, both models demonstrate reasonable accuracy. A second comparison is then made using summer data from a U.K. catchment. The results demonstrate the sensitivity of the risk to the prevailing conditions at the beginning of the period of interest. The assumptions, data requirements and accuracy of the models are compared and discussed. The Ettrick model is chosen for further consideration, given that this model is based on a precipitation threshold, whilst the Smith and Karr model is based on a flow threshold, and the data record is longer for the former. The Ettrick model is then applied to two other U.K. catchments to give all year flood risk estimates. These cover the immediate, 7 day and 30 day ahead time periods. For the immediate flow risk estimates, the importance of snow on the catchment to the levels of flood risk is highlighted. In the case of the 7 day ahead estimates, the significance of the snow is reduced. Given this latter result, the 30 day ahead estimates are not conditional on snow, but still highlight a strong seasonality in the flood risk. Application of the Ettrick model is shown to imply the variable source area concept of runoff production. This may not be the dominant runoff production mechanism on certain catchments, and as such, restricts applicability of the Ettrick model.