Improving distributed runoff prediction in urbanized catchments with remote sensing based estimates of impervious surface cover

The amount and intensity of runoff on catchment scale are strongly determined by the presence of impervious land-cover types, which are the predominant cover types in urbanized areas. This paper examines the impact of different methods for estimating impervious surface cover on the prediction of peak discharges, as determined by a fully distributed rainfall-runoff model (WetSpa), for the upper part of the Woluwe River catchment in the southeastern part of Brussels. The study shows that detailed information on the spatial distribution of impervious surfaces, as obtained from remotely sensed data, produces substantially different estimates of peak discharges than traditional approaches based 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 useful alternative for more expensive high-resolution mapping for rainfall-runoff modelling at catchment scale

A hierarchical approach on groundwater-surface water interaction in wetlands along the upper Biebrza River, Poland

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 groundwatersurface water interaction can improve modeling confidence and as a consequence helps to develop effective procedures for management and conservation of valuable groundwater dependent wetlands

Wetlands in flux: looking for the drivers in a central European case

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Improved distributed runoff modelling of urbanised catchments by integration of multi-resolution remote sensing

The runoff amount and intensity on catchment scale is strongly related to the spatial distribution of impervious area cover, which is the predominant cover type in urbanized area. This can only be taken effectively into account when a fullydistributed hydrological model is used. In this paper we investigate the assessment of imperviousness by a multiresolution remote sensing technique. The remote sensing approach uses a classified high resolution (HR) Ikonos image that covers part of the research area to train a neural network based sub-pixel classification model that estimates impervious surface cover proportions within the pixels of a medium-resolution (MR) Landsat ETM+ image that covers the entire area. The GIS based distributed WetSpa model was used for studying the influence of different imperviousness scenarios on runoff generation with an hourly time step. It shows that estimates of imperviousness derived from satellite data may strongly improve those made by experts, as well as the necessity of application of fully-distributed grid-based hydrological models for urban runoff simulation.Book subtitle: SENSING AND UNDERSTANDING OUR PLANETstatus: publishe

Continuous Daily Evapotranspiration with Optical Spaceborne Observations at Sub-Kilometre Spatial Resolution

Evapotranspiration (ET) is a key parameter in the description of the energy and water fluxes over land. Continuous and spatially detailed ET simulations are thus required for a number of scientific and management-related purposes. These conditions are determined by the modelling approach and the composition of the forcing dataset. This study aimed at simulating daily ET in a diversity of climate and land cover conditions at a spatial resolution of ∼1 km and higher. The modelling approach was based on the algorithm driving the ET product developed and set in operations in the framework of the Satellite Application Facility on Land Surface Analysis programme (LSA-SAF). The implemented algorithm allowed the ingestion of biophysical parameters derived from SPOT-V and PROBA-V observations developed by the Copernicus Global Land Programme, as well as other model parameters at a similar spatial resolution. The model was tested at an ∼1 km spatial resolution in over 40 sites located in different climate and land cover contexts. The implementation at ∼300 m was tested in the upper Biebrza basin, in Poland. The simulations correlated well with the validation dataset (r2 > 0.75 in 80% of sites) and exhibited root mean squared values lower than 1 mm/day in 80% of the cases. The results also pointed to the need for refining the accuracy of soil moisture data sources, especially in dry areas. The results showed the ability of the modelling approach and the SPOT-V/PROBA-V missions to support the generation of long ET time series. They also opened the gate to incorporate Sentinel-3 in ET continuous modelling

A Critical Evaluation on the Role of Aerodynamic and Canopy–Surface Conductance Parameterization in SEB and SVAT Models for Simulating Evapotranspiration: A Case Study in the Upper Biebrza National Park Wetland in Poland

Evapotranspiration (ET) estimation through the surface energy balance (SEB) and soil-vegetation-atmosphere-transfer (SVAT) models are uncertain due to the empirical parameterizations of the aerodynamic and canopy-substrate conductances (gA and gS) for heat and water vapor transfers. This study critically assessed the impact of conductance parameterizations on ET simulation using three structurally different SEB and SVAT models for an ecologically important North-Eastern European wetland, Upper Biebrza National Park (UBNP) in two consecutive years 2015 and 2016. A pronounced ET underestimation (mean bias −0.48 to −0.68 mm day−1) in SEBS (Surface Energy Balance System) was associated with an overestimation of gA due to uncertain parameterization of momentum roughness length and bare soil’s excess resistance to heat transfer (kB−1) under low vegetation cover. The systematic ET overestimation (0.65⁻0.80 mm day−1) in SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes) was attributed to the overestimation of both the conductances. Conductance parameterizations in SEBS and SCOPE appeared to be very sensitive to the general ecohydrological conditions, with a tendency of overestimating gA (gS) under humid (arid) conditions. Low ET bias in the analytical STIC (Surface Temperature Initiated Closure) model as compared to SEBS/SCOPE indicated the critical need for calibration-free conductance parameterizations for improved ET estimation

Modelling nutrient load changes from fertilizer application scenarios in six catchments around the Baltic sea

The main environmental stressor of the Baltic Sea is elevated riverine nutrient loads, mainly originating from diffuse agricultural sources. Agricultural practices, intensities, and nutrient losses vary across the Baltic Sea drainage basin (1.75 × 106 km2 , 14 countries and 85 million inhabitants). Six “Soil and Water Assessment Tool” (SWAT) models were set up for catchments representing the major agricultural systems, and covering the different climate gradients in the Baltic Sea drainage basin. Four fertilizer application scenarios were run for each catchment to evaluate the sensitivity of changed fertilizer applications. Increasing sensitivity was found for catchments with an increasing proportion of agricultural land use and increased amounts of applied fertilizers. A change in chemical fertilizer use of ±20% was found to affect watershed NO3-N loads between zero effect and ±13%, while a change in manure application of ±20% affected watershed NO3-N loads between zero effect and −6% to +7%.publishedVersio

Combined LiDAR and hyperspectral imagery to characterize the response of riparian communities to water availability: insights for climate change impact assessment

International audienceRecent developments in remote-sensing enable a continuous monitoring of riparian vegetation, a task that was traditionally reliant on resource-consuming field campaigns and is key for river management policies. Over the Ain River (France), a simultaneous acquisition of high-resolution hyperspectral and LiDAR data was conducted through EUFAR-funded HYMOSENS2 airborne campaign in order to assess the potential of such technologies for characterizing the ecological condition of the riparian corridor. The coupling of these datasets with in-field sampling of vegetation plots and complementary LiDAR data from other airborne campaigns was used to determine the environmental conditions (e.g., depth to water and overbank sedimentation over a 7 year period) and riparian vegetation structural characteristics of each sampled plot through LiDAR-derived parameters. An empirical growth model was established by linking the structural characteristics of the vegetation to its age, for each plot. Deviations to this model and variations in canopy height within a plot were found to be correlated to geomorphic indicators of connectivity such as overbank sedimentation or the depth to water. This hydrological disconnection of the vegetation which affects both plant growth and species distribution can be identified with hyperspectral data at the levels of the plot and of individual tree crowns through leaf water content. This research shows the applicability of multiple sources of airborne-sensed data for the monitoring of vegetation health in a riverine environment and the identification of water-driven stress and competition, which is a growing concern in a context of climate change