Streamflow prediction in ungauged basins through geomorphology-based hydrograph transposition

Abstract

Geomorphology-based rainfall–runoff models are particularly helpful for predicting hydrology in ungauged basins. The robustness, generality and flexibility of the modelling approach make it able to deal with a wide variety of processes, events and scales. It allows a rainfall–runoff transfer function to be estimated for any basin without needing to measure discharge. The aim of this study is to transpose hydrological observations from gauged to ungauged basins to predict streamflow hydrographs. It considers pairs of nested and neighbouring basins, the first one providing information for the second ungauged one. A time-series of the donor basin's discharge is deconvoluted by inverting its geomorphology-based transfer function to assess the time-series of net rainfall. The latter is then transposed to the receiver basin, where it is convoluted with the reciever basin's transfer function to predict the hydrograph therein. The methodology was implemented with virtual and real rainfall–runoff events on a set of basins in temperate Brittany, France. Different time scales and spatial configurations were tested. Goodness-of-fit of model predictions varied by basin pair. High prediction accuracy was observed when transposing hydrographs between nested basins differing greatly in size. Several ways to improve the approach are identified by relaxing simplifying assumptions.