Assessment of at‐site design flood estimation methods using an improved event‐based design flood estimation tool

Abstract

Internationally, the occurrence and frequency of floods, along with the uncertainty involved in the estimation thereof, contribute to the practitioners' dilemma to make a single, justifiable decision when various design flood estimation methods are used. This article presents the further development of a Design Flood Estimation Tool (DFET) using Microsoft Visual Basic for Applications to assess the performance of event‐based design flood estimation methods in 48 gauged catchments in South Africa. The improved DFET proved to be an easy‐to‐use software tool for the rapid estimation and assessment of at‐site design floods in both gauged and ungauged catchments. In using a ranking‐based selection procedure, the Soil Conservation Service, Alternative Rational and Catchment Parameter methods provided the best estimates of the at‐site probabilistic flood peaks, while the Standard Design Flood method proved to be the least appropriate. Since the accuracy and uncertainty associated with each design flood method's key input parameters are unknown when applied in ungauged catchments, the incorporation of an ensemble event approach as part of the DFET calculation routines, is recommended. This will ensure that the key input parameters from an expected range of values are used to achieve probability neutrality between input rainfall and estimated runoff.

Evaluation of using local information from donor catchments to improve the performance of selected deterministic and empirical design flood estimation methods in South Africa

“…Their use is thus limited to gauged catchments for which suitable flow records are available at the site of interest, or for catchments where records from adjacent gauged catchments are comparable and may be used (Van Vuuren et al 2013). Deterministic methods estimate the expected runoff from driving and contributing factors such as rainfall, based on the assumption that the RI of the estimated runoff is the same as the RI for the rainfall, while being influenced by catchment characteristic inputs and Model Parameters (MPs) (Gericke 2010). Empirical methods relate peak discharge and derived catchment descriptors in order to establish general regional parameters or at-site quantiles (SANRAL 2013).…”