Predicting streamflow in a changing climate poses significant challenges for traditional hydrological models. Static parameter sets result from model calibrations over historical data that increasingly encounter the non-stationary impacts on the hydrological system. Endeavouring toward non-stationary model parameters by incorporating time-adaptive ecosystem-scale root zone storage parameters shows promise for modelling systems under change. The ongoing CATAPUC project aims to further develop, refine, and implement this adaptive modelling approach. This paper continues to build upon this body of work by investigating the evidence for land cover change impacts on root zone storage capacity, focusing specifically on uncertainties in the evaporative balance. Combining long-term hydrometeorological data from the primary study area, the Meuse basin, with the large-sample CAMELS datasets (GB and US) analyses were performed across 283 catchments. Applying the vector operations from Velde et al. (2014) and Jaramillo et al. (2018) to decadal changes within the Budyko framework, we separate climate-related evaporative changes. We isolated the residual component of evaporative change, which is the unknown component affecting parameter estimations. Our findings indicate that this residual component is twice as prominent in evaporative change as the climate component. The aim is to test if land cover changes have contributed significantly to the residual component of evaporative change. A multi-scale approach to land cover change analysis is adopted to bridge the data gap from 1984 to 2019. Implementing ensemble machine-learning methods on Landsat imagery with Google Earth Engine, we develop annual timeseries of (30m) high-resolution multi-class data for this period with accuracies up to 86% for 117 catchments (Meuse and GB). Resulting land cover change estimates suggest that Meuse Basin urbanisation rates may have been significantly underestimated for this period. The Meuse Basin over the most recent 20-year period is found to deviate anomalously in actual evaporation compared with the large sample. A distinct spatial pattern reveals a concentration of deviations in the east of the basin. Calculated by Tempel (2023), the anomaly in the basin corresponds with a relative median error in root zone storage capacity change of −14%. Low flow analysis is performed to remove the possibility that deviations are affected by anomalous contribution to streamflow from additional subsurface flow. We observed that the increase in low flow variability over the same period exhibits a spatial pattern similar to the Meuse Basin anomaly. We found no meaningful causal relationships linking multi-scale interdecadal changes in forest, agriculture, and urban land classes to the observed deviations in the large sample datasets. The implication of this study is that land cover change is likely not a significant driver of evaporative changes, specifically, errors, throughout the record available.

Hydrological models are commonly used to predict future streamflow. However, the assumption of stationary model parameters obtained through calibration on past conditions may not accurately represent non-stationarity in hydrological system characteristics. Evidence suggests that vegetation adapts its root zone storage capacity in response to changing climate, emphasizing the need to account for non-stationarity in hydrological models. This study examines the effects of long-term climate variability on root zone storage capacity and its consequences on hydrological response. By using the method of Fu (1981), we determine whether the root zone storage capacity has significantly changed and evaluate the sensitivity of hydrological model predictions to these changes. We explain the changes in root zone storage capacity and evaporation using various climate indicators. For two large sample datasets CAMELS GB and CAMELS USA, we confirm that the Fu method can be used with the same omega parameter when transitioning from one decade to the next, indicating small differences in root zone storage capacity. However, for hydrometeorological data from the Meuse basin in Northwest Europe, we observe a trend where the actual evaporation is smaller than expected. This suggests that caution should be exercised when applying the Fu-method. In four different scenarios, we have implemented historical changes in evaporation as altered root zone storage capacity in the wflow flextopo model. The scenarios based on the evaporation trends observed in the Meuse data, result in less evaporation during the summer months (May, June, July) within a range of 0 to -22%, and an increase in streamflow during the autumn months (September, October, November) between 0 and +48%. On the other hand, the scenarios based on evaporation trends observed in all combined data (Meuse, CAMELS GB, CAMELS USA) result in changes around zero of evaporation during summer months between -7% and +5%, and of streamflow in autumn months between -11% and +10%. This study represents a step towards a more reliable and robust estimation of root zone storage capacity in hydrological modelling, thereby enhancing our ability to predict future streamflow.