Missing data representation by perception thresholds in flood flow frequency assessment

Nikola Đokić,Borislava Blagojević,Vladislava Mihailović

doi:10.5937/jaes0-28902

Abstract

Flood flow frequency analysis (FFA) plays one of the key roles in many fields of hydraulic engineering and water resources management. The reliability of FFA results depends on many factors, an obvious one being the reliability of the input data - datasets of the annual peak flow. In practice, however, engineers often encounter the problem of incomplete datasets (missing data, data gaps and/or broken records) which increases the uncertainty of FFA results. In this paper, we perform at-site focused analysis, and we use a complete dataset of annual peak flows from 1931 to 2016 at the hydrologic station Senta of the Tisa (Tisza) river as the reference dataset. From this original dataset we remove some data and thus we obtain 15 new datasets with one continuous gap of different length and/or location. Each dataset we further subject to FFA by using the USACE HEC-SSP Bulletin 17C analysis, where we apply perception thresholds for missing data representation. We vary perception threshold lower bound for all missing flows in one dataset, so that we create 56 variants of the input HEC-SSP datasets. The flood flow quantiles assessed from the datasets with missing data and different perception thresholds we evaluate by two uncertainty measures. The results indicate acceptable flood quantile estimates are obtained, even for larger return periods, by setting a lower perception threshold bound at the value of the highest peak flow in the available - incomplete dataset.

Highlights

Flood frequency analysis (FFA) is an important part of the flood risk management
The flood flow quantiles assessed from the datasets with missing data and different perception thresholds we evaluated through percentage error (PE), and confidence interval width as uncertainty measure, while we observed change in number of detected outliers in the datasets
The results of FFA for the reference dataset are shown in Fig. 4 as screenshot of the Hydraulic Engineering Centre Statistical Software Package (HEC-SSP) output table

Summary

Introduction

Flood frequency analysis (FFA) is an important part of the flood risk management. The FFA result is a set of flood quantiles representing, for example, a 1000-year, 100-year and 50-year flood flow. In the case of gauged catchments, the most common FFA is performed on the datasets comprising annual flow maxima. These datasets often come with missing data, data gaps or broken records. Some analyses concerning gaps in hydrometeorological time series, reveal that a very efficient gap filling of sporadic, single-value gaps, is achieved by the value obtained using only three values of the dataset: the one before, one after the missing value, and the sample mean [2]

Methods

Results

Discussion

Conclusion