This paper investigates the influence of multi-decadal climatic variability on the temporal evolution of root zone storage capacities (Sr,max) and its implications for streamflow predictions in the Meuse basin. Through a comprehensive analysis of 286 catchments across Europe and the US that are hydro-climatically comparable to the Meuse basin, we construct inter-decadal distributions of past deviations in evaporative ratios (IE) from expected values based on catchment aridity (IA). These distributions of ΔIE were then used to estimate inter-decadal changes in Sr,max and to quantify the associated consequences for streamflow predictions in the Meuse basin. Our findings reveal that, while catchments do not strictly adhere to their specific parametric Budyko curves over time, the deviations in IE are generally very minor, with an average ΔIE=0.01 and an interquartile range (IQR) of −0.01 to 0.03. Consequently, these minor deviations lead to limited inter-decadal changes in Sr,max, mostly ranging between −10 and +21 mm (−5 % to +10 %). When these changes (ΔSr,max) are accounted for in hydrological models, the impact on streamflow predictions in the Meuse basin is found to be marginal, with the most significant shifts in monthly evaporation and streamflow not exceeding 4 % and 12 %, respectively. Our study underscores the utility of parametric Budyko-style equations for first-order estimates of future Sr,max in hydrological models, even in the face of climate change and variability. This research contributes to a more nuanced understanding of hydrological responses to changing climatic conditions and offers valuable insights for future climate impact studies in hydrology.

This paper presents an analysis of future research and development needs to assess the effectiveness of nature-based solutions for climate adaptation in watersheds at scale using hydrological models. Two main questions are addressed: To what extent are hydrological model approaches able to support decision making on nature-based solutions and adaptation, and how well is this hydrological analysis embedded in the broader planning process? To support the research, case studies in Bhutan, Zimbabwe and the Netherlands are presented. The Climate Risk Informed Decision Analysis approach is used to structure the planning process. All three case studies demonstrate how the hydrological system and full landscape of land and water use in watersheds can be simulated to better understand hydrometeorological hazards under current and future climate. Also, simulations of nature-based solutions are demonstrated, which need creativity and profound expert knowledge. In contrast to the assessment of grey infrastructure, no rules or guidance exists for the hydrological assessment of nature-based solutions. Physically-based models are better able to support the understanding of the functioning of the ecohydrological system and, therefore, the effectiveness of adaptation using nature-based solutions. There are however trade-offs between the computational complexity, the computation time and the multiple scenarios and sensitivity analyses of adaptation options needed for climate stress testing. Often there is a lack of monitoring data for verification of model outcomes. Several recommendations on how to improve modelling in an adaptation process are given. In addition, it is recommended to develop and rectify a set of nature-based solutions performance indicators, rules and algorithms to be adopted in models in order to quantify the effectiveness of these solutions.