The hydrological processes within the catchment are generally influenced by both climate change (CC) and land use/land cover (LULC) change. However, most of the studies are focused on their individual impact on the catchment’s hydrology, while their combined effects have received little attention. This study employs the physically based distributed hydrological model, MIKE SHE, to study the separate and combined effect of climate and LULC change on the hydrology of a mesoscale catchment in the near future (2050s). An Artificial Neural Network–Cellular Automata (ANN-CA) based prediction model was trained to simulate the future LULC map. The future meteorological data under four CC scenarios was obtained from the Royal Netherlands Meteorological Institute (KNMI). The model results showed that the combined effects of CC with LULC changes did not significantly differ from the individual impact of CC on the catchment scale. However, on the local scale, the changes in LULC can significantly influence the variations in groundwater table, soil moisture, and actual evapotranspiration ranging from approximately–6–15%,–9–27%, and–30–10% respectively, depending on the specific change in LULC class and season. In summary, this research provides valuable insights into the complex interactions between LULC changes, CC, and hydrology.

This article presents a methodology for designing and assessing drought-related Nature-Based Solutions (NBS) adaptation strategies on a catchment scale using an integrated hydrological model that simultaneously provides surface water and groundwater results. The Aa of Weerijs catchment, shared between Belgium and the Netherlands, was used for demonstrating the methodology. The model was developed with the MIKE SHE modelling system, using a combination of globally available and local data. Different types of NBS (ditch blocking, infiltration ponds, wetland restoration and heathland restoration) were combined spatially to develop two adaptation strategies with different spatial extents. Their design was based on drought-related Key Performance Indicators (KPIs) linked with water management actions by key stakeholders (bans on water extraction), both on the surface and groundwater. The KPI values were obtained by model simulations under current and future climate conditions, and with the implementation of the two adaptation strategies. The results show that the strategy with a larger spatial extent gives better KPI values, almost eliminating days with no groundwater availability in the downstream part of the catchment, reaching the goal of increased infiltration and groundwater recharge. Additionally, our results show that there is significant accumulation of positive effects from upstream to downstream.