How does ecosystem adaptation to a changing climate affect catchment Transit Times Distributions

Climate change can considerably control the catchment-scale root zone storage capacity (S_umax) which is a critical factor affecting the moisture exchange between land and atmosphere, hydrological response, and biogeochemical processes in terrestrial hydrological systems. However, direct quantification of the changes of S_umax over long time periods at the catchment-scalehas so far been rare. This is mostly a result that it is difficult to quantify the effect of climate change on parameters of terrestrial hydrological models, which in turn contributes to considerable uncertainties in predictions of the hydrological response under changing climatic conditions. As a consequence, it remains unclear how climate change affects S_umax (e.g., precipitation regime, canopy water demand) and how changes in S_umax may affect partitioning of water fluxes and as a consequence, as well as catchment-scale physical transport of water quality, described by transit and resident time distributions.

The objectives of this study in the upper Neckar river basin in Germany are therefore to provide an analysis of why changes in S_umax can be observed as a result of changing climatic conditions over the past 7 decades and how this further affects hydrological and transport dynamics. More specifically, we test the hypotheses that (1) the changes in water fluxes and storage dynamics over that a 70-year period can be attributed to adaptations of the root zone storage capacity resulting from the changing climate (e.g., precipitation frequency or wetness condition), which affects (2) the shape of travel time distributions and young water fractions, in particular for evaporation fluxes, which are most affected by the climate-induced change S_umax over different periods.The analysis is carried out based on long-term hydrological (1953-2022) and radioactive isotope data (1961-2018), using a distributed hydrological model coupled with StorAge Selection (SAS) functions, which is simultaneously modelling streamflow and tracer dynamics and provides estimates of transit time distributions of different water fluxes and of resident time distributions in different storage components.