Integrating hydrology with climate is essential for a better understanding of the impact of present and future climate on hydrological extremes, which may cause frequent flooding, drought, and shortage of water supply. This study assessed the impact of future climate change on the hydrological extremes (peak and low flows) of the Zenne river basin (Belgium). The objectives were to assess how climate change impacts basin-wide extreme flows and to provide a detailed overview of the impacts of four future climate change scenarios compared to the control (baseline) values. The scenarios are high (wet) summer (projects a future with high storm rain in summer), high (wet) winter (predicts a future with high rainfall in winter), mean (considers a future with intermediate climate conditions), and low (dry) (projects a future with low rainfall during winter and summer). These scenarios were projected by using the Climate Change Impact on HYDRological extremes perturbation tool (CCI-HYDR), which was (primarily) developed for Belgium to study climate change. We used the Soil and Water Assessment Tool (SWAT) model to predict the impact of climate change on hydrological extremes by the 2050s (2036–2065) and the 2080s (2066–2095) by perturbing the historical daily data of 1961–1990. We found that the four climate change scenarios show quite different impacts on extreme peak and low flows. The extreme peak flows are expected to increase by as much as 109% under the wet summer scenario, which could increase adverse effects, such as flooding and disturbance of the riverine ecosystem functioning of the river. On the other hand, the low (dry) scenario is projected to cause a significant decrease in both daily extreme peak and low flows, by as much as 169% when compared to the control values, which would cause problems, such as droughts, reduction in agricultural crop productivity, and increase in drinking water and other water use demands. More importantly, larger negative changes in low flows are predicted in the downstream part of the basin where a higher groundwater contribution is expected, indicating the sensitivity of a basin to the impact of climate change may vary spatially and depend on basin characteristic. Overall, an amplified, as well as an earlier, occurrence of hydrological droughts is expected towards the end of this century, suggesting that water resources managers, planners, and decision makers should prepare appropriate mitigation measures for climate change for the Zenne and similar basins.

A tool called WetSpa-Urban was developed to respond to the need for precise runoff estimations in an increasingly urbanized world. WetSpa-Urban links the catchment model WetSpa-Python to the urban drainage model Storm Water Management Model (SWMM). WetSpa-Python is an open-source, fully distributed, process-based model that accurately represents surface hydrological processes but does not simulate hydraulic structures. SWMM is a well-known open-source hydrodynamic tool that calculates pipe flow processes in an accurate manner while runoff is calculated conceptually. Merging these tools along with certain modifications, such as improving the efficiency of surface runoff calculation and simulating flow at the sub-catchment level, makes WetSpa-Urban suitable for event-based and continuous rainfall–runoff modeling for urban areas. WetSpa-Urban was applied to the Watermaelbeek catchment in Brussels, Belgium, which recently experienced rapid urbanization. The model efficiency was evaluated using different statistical methods, such as Nash–Sutcliffe efficiency and model bias. In addition, a statistical investigation, independent of time, was performed by applying the box-cox transformation to the observed and simulated values of the flow peaks. By speeding up the simulation of the hydrological processes, the performance of the surface runoff calculation increased by almost 130%. The evaluation of the simulated 10 minute flow versus the observed flow at the outlet of the catchment for 2015 reached a Nash–Sutcliffe efficiency of 0.86 and a bias equal to 0.06.

We propose a remote-sensing based metric approach to evaluate the hydrological response of highly urbanized areas and apply it to the city of Brussels. The model is set-up using 2 m resolution hyperspectral data. Next, it is upscaled to the city level, using multi-spectral Sentinel-2 data with 20 m resolution. We identify the total impervious area, the vegetation cover and the leaf area index as important metrics to derive a timeseries of spatially distributed net rainfall, runoff and infiltration from rainfall data. For the estimation of the actual evapotranspiration we use the potential evapotranspiration and the available water storage based on the interception, the depression storage and the infiltration. Additionally, we route the runoff to the outlet of selected sub-catchments. An important metric for the routing is the timing to the outlet which is approximated using the total impervious area and the hydrological distance to the outlet. We compare our approach to WetSpa model simulations and reach R ${}^2$ values of 98% for net rainfall, 95% for surface runoff, 99% for infiltration and 97% for cumulative evapotranspiration. The routing in the Watermaelbeek catchment is evaluated with discharge observations and reaches NSE values of 0.89 at a 2 m resolution and 0.88 at a 20 m resolution using an hourly timestep. At the timestep of 10 min and a 20 m resolution the NSE is reduced to 0.76. For the Roodebeek catchment we reach an NSE of 0.73 at a spatial resolution of 20 m and an hourly timestep. The results presented in this paper are optimistic for using spatial and temporal metrics retrieved from remote sensing data to quantify the water balance of urban catchments.