Manuela I. Brunner

Flood type specific construction of synthetic design hydrographs

Accurate estimates of flood peaks, corresponding volumes, and hydrographs are required to design safe and cost-effective hydraulic structures. In this paper, we propose a statistical approach for the estimation of the design variables peak and volume by constructing synthetic design hydrographs for different flood types such as flash-floods, short-rain floods, long-rain floods, and rain-on-snow floods. Our approach relies on the fitting of probability density functions to observed flood hydrographs of a certain flood type and accounts for the dependence between peak discharge and flood volume. It makes use of the statistical information contained in the data and retains the process information of the flood type. The method was tested based on data from 39 mesoscale catchments in Switzerland and provides catchment specific and flood type specific synthetic design hydrographs for all of these catchments. We demonstrate that flood type specific synthetic design hydrographs are meaningful in flood-risk management when combined with knowledge on the seasonality and the frequency of different flood types.

Uncertainty assessment of synthetic design hydrographs for gauged and ungauged catchments

Design hydrographs described by peak discharge, hydrograph volume, and hydrograph shapeare essential for engineering tasks involving storage. Such design hydrographs are inherently uncertain asare classical flood estimates focusing on peak discharge only. Various sources of uncertainty contribute tothe total uncertainty of synthetic design hydrographs for gauged and ungauged catchments. These com-prise model uncertainties, sampling uncertainty, and uncertainty due to the choice of a regionalizationmethod. A quantification of the uncertainties associated with flood estimates is essential for reliable deci-sion making and allows for the identification of important uncertainty sources. We therefore propose anuncertainty assessment framework for the quantification of the uncertainty associated with synthetic designhydrographs. The framework is based on bootstrap simulations and consists of three levels of complexity.On the first level, we assess the uncertainty due to individual uncertainty sources. On the second level, wequantify the total uncertainty of design hydrographs for gauged catchments and the total uncertainty ofregionalizing them to ungauged catchments but independently from the construction uncertainty. On thethird level, we assess the coupled uncertainty of synthetic design hydrographs in ungauged catchments,jointly considering construction and regionalization uncertainty. We find that the most important sources ofuncertainty in design hydrograph construction are the record length and the choice of the flood samplingstrategy. The total uncertainty of design hydrographs in ungauged catchments depends on the catchmentproperties and is not negligible in our case.

Synthetic design hydrographs for ungauged catchments: a comparison of regionalization methods

Design flood estimates for a given return period are required in both gauged and ungauged catchments for hydraulic design and risk assessments. Contrary to classical design estimates, synthetic design hydrographs provide not only information on the peak magnitude of events but also on the corresponding hydrograph volumes together with the hydrograph shapes. In this study, we tested different regionalization approaches to transfer parameters of synthetic design hydrographs from gauged to ungauged catchments. These approaches include classical regionalization methods such as linear regression techniques, spatial methods, and methods based on the formation of homogeneous regions. In addition to these classical approaches, we tested nonlinear regression models not commonly used in hydrological regionalization studies, such as random forest, bagging, and boosting. We found that parameters related to the magnitude of the design event can be regionalized well using both linear and nonlinear regression techniques using catchment area, length of the main channel, maximum precipitation intensity, and relief energy as explanatory variables. The hydrograph shape, however, was found to be more difficult to regionalize due to its high variability within a catchment. Such variability might be better represented by looking at flood-type specific synthetic design hydrographs.

Bivariate analysis of floods in climate impact assessments

Climate impact studies regarding floods usually focus on peak discharges and a bivariate assessment of peak discharges and hydrograph volumes is not commonly included. A joint consideration of peak discharges and hydrograph volumes, however, is crucial when assessing flood risks for current and future climate conditions. Here, we present a methodology to develop synthetic design hydrographs for future climate conditions that jointly consider peak discharges and hydrograph volumes. First, change factors are derived based on a regional climate model and are applied to observed precipitation and temperature time series. Second, the modified time series are fed into a calibrated hydrological model to simulate runoff time series for future conditions. Third, these time series are used to construct synthetic design hydrographs. The bivariate flood frequency analysis used in the construction of synthetic design hydrographs takes into account the dependence between peak discharges and hydrograph volumes, and represents the shape of the hydrograph. The latter is modeled using a probability density function while the dependence between the design variables peak discharge and hydrograph volume is modeled using a copula. We applied this approach to a set of eight mountainous catchments in Switzerland to construct catchment-specific and season-specific design hydrographs for a control and three scenario climates. Our work demonstrates that projected climate changes have an impact not only on peak discharges but also on hydrograph volumes and on hydrograph shapes both at an annual and at a seasonal scale. These changes are not necessarily proportional which implies that climate impact assessments on future floods should consider more flood characteristics than just flood peaks.