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Effect of streamflow measurement error on flood frequency estimation
Journal article   Open access   Peer reviewed

Effect of streamflow measurement error on flood frequency estimation

Nicolas Velasquez and Witold F. Krajewski
Stochastic environmental research and risk assessment, Vol.38(7), pp.2903-2910
07/2024
DOI: 10.1007/s00477-024-02707-1
url
https://doi.org/10.1007/s00477-024-02707-1View
Published (Version of record) Open Access

Abstract

Significant errors often arise when measuring streamflow during high flows and flood events. Such errors conflated by short records of observations may induce bias in the flood frequency estimates, leading to costly engineering design mistakes. This work illustrates how observational (measurement) errors affect the uncertainty of flood frequency estimation. The study used the Bulletin 17 C (US standard) method to estimate flood frequencies of historical peak flows modified to represent the measurement limitations. To perform the modifications, we explored, via Monte Carlo simulation, four hypothetical scenarios that mimic measurement errors, sample size limitations, and their combination. We used a multiplicative noise from a log-normal distribution to simulate the measurement errors and implemented a bootstrap approach to represent the sampling error. Then, we randomly selected M samples from the total N records of the observed peak flows of four gauging stations in Iowa in central USA. The observed data record ranges between 76 and 119 years for watersheds with drainage areas between 500 and 16,000 km2. According to the results, measurement errors lead to more significant differences than sampling limitations. The scenarios exhibited differences with median magnitudes of up to 50%, with some cases reaching differences up to 100% for return periods above 50 years. The results raise a red flag regarding flood frequency estimation that warrants looking for further research on observational errors.
Engineering Mathematics Physical Sciences Technology Engineering, Civil Engineering, Environmental Environmental Sciences Environmental Sciences & Ecology Life Sciences & Biomedicine Science & Technology Statistics & Probability Water Resources

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