Abstract
This study proposes a general differential split-sample test (GDSST) based on an oriented bootstrap to assess the transferability of conceptual rainfall-runoff models to climatically contrasting periods. Compared to existing benchmark techniques, the GDSST allows a larger number of climatically contrasted discontinuous periods to be sampled, and is computationally more effective than the basic bootstrap to identify the most contrasted periods. When applied to three hydrological models (GR4J, HBV and IHACRES) in five catchments in northern Tunisia, the GDSST provided clear limits of the transferability of the models under changing precipitation (P) and temperature (T) conditions towards drier and hotter conditions. According to the criteria and thresholds retained, approximate limits of model transferability are drawn. The models are roughly transferable for relative changes in precipitation ΔP < (0.08 ΔT − 0.18) with ΔP ∈ [−30%, +80%], and changes in temperature ΔT ∈ [−2 °C, +2 °C]. These transferability limits suggest selecting a past sub-period as close as possible to the future climate to identify calibration parameters, which can be used for hydrological projections. The limits of transferability were then compared to climate projections by eight high-resolution Regional Climate Model (RCM) simulations resulting from the EURO-CORDEX initiative. The RCMs’ precipitation and temperature simulations of the historical period 1970–2000 were first assessed to select the most realistic ones for future projections. A delta-change monthly correction was used to perturb the observed climate series according to climate simulations under two Radiative Concentration Pathway (RCP) scenarios (RCP4.5 and RCP8.5) for one medium-term horizon (2040–2070) and one long-term horizon (2070–2100). The effects of the selected past calibration period on the hydrological projections were then analysed. The RCP 8.5 climate projections fall outside the limits of transferability of all rainfall-runoff models tested. Models calibrated on the whole observed period were found to underestimate the impacts of climate change on runoff by 5%–20% in comparison with models calibrated on sub-periods with mean annual P and T closer to projected climate conditions.