A catastrophe progression approach based index sensitivity analysis model for the multivariate flooding process

Flood mitigation should deal with those most sensitive flooding elements to very efficiently release risks and reduce losses. Present the most concerns of flood control are peak level or peak discharge which, however, may not always be the most sensitive flooding element. Actually, along with human activities and climate change, floods bring threats to bear on human beings appear in not only peak level and peak discharge, but also other elements like maximum 24-h volume and maximum 72-h volume. In this paper, by collecting six key flooding intensity indices (elements), a catastrophe progression approach based sensitivity analysis algorithm model is developed to identify the indices that mostly control over the flood intensity. The indices sensitivity is determined through a selected case study in the Wujiang River, South China, based on half a century of flow record. The model results indicate that there is no evident relationship of interplay among the index sensitivities, but the variability of the index sensitivity is closely related to the index variability and the index sensitivity increases with the decrease of index value. It is found that peak discharge is not the most influential flooding factor as is generally thought in this case. The sensitivity value of the maximum 24-h volume is the greatest influential factor among all the other indices, indicating that this index plays a leading role in the flood threat of the Wujiang River, South China. It is inferred that, for the purpose of flood warning and mitigation, the peak flood discharge is not always the most sensitive and dominant index as opposed to the others, depending on the sensitivity.