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

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2021

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Abstract

There are a number of design flood estimation methods routinely used in South Africa. Flood Frequency Analysis (FFA) remains the preferred technique in instances where adequate records of observed data are available. However, in many parts of South Africa, rivers are not gauged for continuous streamflow monitoring. In the case of ungauged catchments, most hydrologists and engineers make use of methods based on deterministic and empirical approaches for design flood estimation. Due to the assumptions and limitations associated with these methods, improved approaches need to be developed for design flood estimation in ungauged catchments. International practice has shown that making use of local information transfer from nearby gauged catchments, also referred to as donor catchments, can improve flood estimation in ungauged catchments. Local information related to model parameters, hydrologic indices, and global uncertainty can be used to compensate for local variations not considered in regional models. The main considerations for implementing such methods are the type of information transferred, selection of suitable donor catchments and density of gauged donor catchments. Approaches for donor catchment selection include physical similarity, spatial proximity and integrated similarity. Some studies have also shown that the use of multiple donor catchments can offer further improvements. Thus, a methodology is proposed and evaluated for using local information from gauged donor catchments to improve the performance of selected deterministic and empirical flood estimation methods widely used in South Africa (Standard Design Flood, Rational Method, Synthetic Unit Hydrograph and HRU 1/71 Empirical Method) in a pilot study at 48 ungauged catchments with information and data provided by the Department of Water and Sanitation. The evaluation criteria used in the study include scatter plots, box and whisker plots of Relative Error and Mean Absolute Relative Error. The results of the study illustrate that, in general, information transfer from a single donor catchment can provide improved design flood estimates when used in conjunction with the existing flood estimation methods. The results also show that the degree of improvement for each of the methods is largely dependent on the approach used for donor catchment selection. When using a single donor catchment, the Standard Design Flood method performed best using the physical similarity approach for the proposed single donor transfer method and the Synthetic Unit Hydrograph method showed the best improvements using the integrated similarity approach, while both the Rational Method and HRU 1/71-Empirical method experienced the most significant improvements using the spatial proximity approach. Even though the best approach for donor catchment selection varied for the different design flood estimation methods, the integrated similarity approach performed consistently well for all methods considered. Similar to the use of single donor catchments, the results obtained from the use of multiple donor catchments also varied for each of the methods used. The optimum number of catchments for the Standard Design Flood and Rational Method was 16 and 4, respectively. However, the Synthetic Unit Hydrograph and HRU 1/71 method did not show any further improvements when using multiple donor catchments. Due to the general improvements and promising results and success of the simple approach used in this study, it is recommended that further refinements of the proposed methodology and approaches to donor catchment selection be considered for future research projects.

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Masters Degree. University KwaZulu- Natal, Durban.

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