The amount and intensity of runoff on catchment scale are strongly determinedby the presence of impervious land-cover types, which are the predominant cover types inurbanized areas. This paper examines the impact of different methods for estimatingimpervious surface cover on the prediction of peak discharges, as determined by a fullydistributed rainfall-runoff model (WetSpa), for the upper part of the Woluwe Rivercatchment in the southeastern part of Brussels. The study shows that detailed informationon the spatial distribution of impervious surfaces, as obtained from remotely sensed data,produces substantially different estimates of peak discharges than traditional approachesbased on expert judgment of average imperviousness for different types of urban land use.The study also demonstrates that sub-pixel estimation of imperviousness may be a usefulalternative for more expensive high-resolution mapping for rainfall-runoff modelling atcatchment scale.

The use of hyperspectral (HS) and LiDAR acquisitions has a great potential to enhance mapping and monitoring practices of endangered grasslands habitats, beyond conventional botanical field surveys. In this study we assess the potentiality of recursive feature elimination (RFE) in combination with random forest (RF) classification in extracting the main HS and LiDAR features needed to map selected Natura 2000 grasslands along Polish lowland river valleys, in particular alluvial meadows 6440, lowland hay meadows 6510, and xeric and calcareous grasslands 6120. We developed an automated RFE-RF system capable to combine the potentials of both techniques and applied it to multiple acquisitions. Several LiDAR-based products and different spectral indices (SI) were computed and used as input in the system, with the aim of shedding light on the best-to-use features. Results showed a remarkable increase in classification accuracy when LiDAR and SI products are added to the HS dataset, strengthening in particular the importance of employing LiDAR in combination with HS. Using only the 24 optimal features selection generalized over the three study areas, strongly linked to the highly heterogeneous characteristics of the habitats and landscapes investigated, it was possible to achieve rather high classification results (K around 0.7–0.77 and habitats F1 accuracy around 0.8–0.85), indicating that the selected Natura 2000 meadows and dry grasslands habitats can be automatically mapped by airborne HS and LiDAR data. Similar approaches might be considered for future monitoring activities in the context of habitats protection and conservation.

As recognized in the European Water Framework Directive, groundwater-dependent wetlands and their diverse ecosystems have important functions which need to be protected. The vegetation in such habitats is often dependent on quality, quantity and patterns of river discharge and groundwater-surface water interaction on a local or reach scale. Since groundwater-surface water exchange studies on natural rivers and wetlands with organic soils are scarce, more functional analysis is needed. To this end we combined different field methods including piezometer nests, temperature as tracer and seepage meter measurements. Some of these measurements were used as inputs and/or as validation for the numerical 1-D heat transport model STRIVE. In transient mode the model was used to calculate spatially distributed vertical exchange fluxes from temperature profiles measured at the upper Biebrza River in Poland over a period of nine months. Time series of estimated fluxes and hydraulic head gradients in the hyporheic zone were used to estimate the temporal variability of groundwater-surface water exchange. This paper presents a hierarchical approach for quantifying and interpreting groundwater-surface water interaction in space and time. The results for the upper Biebrza show predominantly upward water fluxes, sections of recharge, however, exist along the reach. The fluxes depend more on hydraulic gradients than on riverbed conductivity. This indicates that the fluvio-plain scale is required for interpreting the exchange fluxes, which are estimated on a local scale. The paper shows that a conceptual framework is necessary for understanding the groundwater-surface water interaction processes, where the exchange fluxes are influenced by local factors like the composition of the riverbed and the position of the measurement on a local scale, and by regional factors like the hydrogeology and topography on a fluvio-plain scale. The hierarchical methodology increases the confidence in the estimated exchange fluxes and improves the process understanding. The accuracy of the measurements and related uncertainties, however, remain challenges for wetland environments. Gaining quantitative information on groundwater-surface water interaction can improve modeling confidence and as a consequence helps to develop effective procedures for management and conservation of valuable groundwater dependent wetlands.