New Approach to Estimate Extreme Flooding Using Continuous Synthetic Simulation Supported by Regional Precipitation and Non-Systematic Flood Data

Carles Beneyto,Félix Francés,José Ángel Aranda,Gerardo Benito

doi:10.3390/w12113174

Abstract

Stochastic weather generators combined with hydrological models have been proposed for continuous synthetic simulation to estimate return periods of extreme floods. Yet, this approach relies upon the length and spatial distribution of the precipitation input data series, which often are scarce, especially in arid and semiarid regions. In this work, we present a new approach for the estimation of extreme floods based on the continuous synthetic simulation method supported with inputs of (a) a regional study of extreme precipitation to improve the calibration of the weather generator (GWEX), and (b) non-systematic flood information (i.e., historical information and/or palaeoflood records) for the validation of the generated discharges with a fully distributed hydrological model (TETIS). The results showed that this complementary information of extremes allowed for a more accurate implementation of both the weather generator and the hydrological model. This, in turn, improved the flood quantile estimates, especially for those associated with return periods higher than 50 years but also for higher quantiles (up to approximately 500 years). Therefore, it has been proved that continuous synthetic simulation studies focused on the estimation of extreme floods should incorporate a generalized representation of regional extreme rainfall and/or non-systematic flood data, particularly in regions with scarce hydrometeorological records.

Highlights

Accurate estimates of extreme and rare floods have been a fundamental problem in flood hydrology since pioneer work by Foster [1], and it is still present among the scientific and engineering communities in numerous papers and reports
The methodology consisted of four steps: (1) application of a weather generator for simulating daily precipitation and temperatures with an additional calibration of the parameters related to the extremes using a regional annual maximum rainfall study to deal with the limited length of precipitation records; (2) implementation at a daily and sub-daily scale of a fully-distributed hydrological model that can cope with the spatial variability of rainfall and catchment characteristics; (3) simulation of daily flows of the synthetic rainfall dataset in the fully distributed rainfall-runoff model; (4) comparison of the performance flood analysis from observed and synthetic flood series; and (5) incorporation
The following paragraphs describe the implementation of the hydrological model at both the daily scale and 5-min temporal resolutions

Summary

Introduction

Accurate estimates of extreme and rare floods have been a fundamental problem in flood hydrology since pioneer work by Foster [1], and it is still present among the scientific and engineering communities in numerous papers and reports. Traditional flood studies (e.g., for the design of sensitive infrastructures) were based in either flood frequency analysis (FFA) for gauged basins or deterministic procedures, mainly based on the design storm, for ungauged basins. This latter approach draws from the premise that return periods of concurrent rainfall and peak discharge are assumed to be the same and that the design flood of a given return period can be estimated based on a single rainfall duration that generates the highest peak discharge (see the classical Chow et al [8] or the Flood Estimation Handbook [9]). The procedure involves the generation of synthetic discharge data series obtained from a stochastic weather generator (WG)

Objectives

Methods

Results

Discussion

Conclusion