Questioning the use of ensembles versus individual climate model generated flows in future peak flood predictions: Plausibility and implications

Abstract

Abstract Accurate estimation of design floods is necessary for developing effective flood‐management strategies. Climate change (CC) studies on floods generally consider alterations in mean runoff using ensembles compared to a base period. In this study, we examined the plausibility and implications of applying individual climate model‐generated flows versus their ensembles to estimate peak floods (magnitude and timing of occurrence), using Budhigandaki River Basin of Nepal as a case study. Annual maximum one‐day floods were derived for four future climate scenario projections (cold‐dry, cold‐wet, warm‐wet, and warm‐dry) from simulated daily flow series. Future floods of six return periods estimated for the individual climate scenarios were compared with their “Ensemble” (combiner for the ensemble series is the arithmetic mean of daily floods), “Average,” and ‘Baseline.” Results showed that magnitudes of the flood peaks are such that those estimated using “Ensemble” < “Average” < individual series. We conclude that ensemble series should not be used for flood estimation because of the averaging effect. Designers should consider at the least the “Average” instead of the “Ensemble” series while designing climate‐resilient flood structures. Furthermore, the occurrences of flood peaks are likely to be confined within the monsoon season for the “Ensemble” but spread out in the other months for the individual climate scenarios. This could have direct implications on the availability and mobilization of resources as well as the need for a year‐round operational early warning system for flood risk management.

Keywords

• average
• climate change
• ensemble
• flood
• frequency
• timing of occurrence