Development of a pan-european Database of Rivers, Lakes and Catchments, in support to the needs of Environmental Policies.

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1 Development of a pan-european Database of Rivers, Lakes and Catchments, in support to the needs of Environmental Policies. Jürgen Vogt, Roberto Colombo, Maria Luisa Paracchini, Pierre Soille, Alfred de Jager Institute for Environment and Sustainability EC Joint Research Centre (JRC) Ispra (Varese), Italy juergen.vogt@jrc.it Abstract The availability of digital data on river networks, lakes and associated catchments and their characteristics is important for the analysis of environmental pressures and their impact on our water resources. Recent policies, such as the Water Framework Directive require the implementation of river and catchment databases for both the development of River Basin Management Plans and for the reporting to the Commission. GIS tools allow for the combined analysis of digital elevation data and terrain parameters in order to derive part of the required information over extended areas. This article presents a new approach making use of medium resolution digital elevation data (250 m grid cell size) and information on climate, vegetation cover, terrain morphology, soils and lithology to derive river networks and catchments for the European continent. Methods to extract channel networks at continental scale normally use a constant threshold for the critical contributing area, independently of widely varying landscape conditions. As a consequence, the resulting drainage network does not reflect the natural variability in drainage density. To overcome this limitation a landscape characterisation is proposed, resulting in a limited number of landscape types reflecting drainage density. For each landscape type the slope-area relationship is then derived from the digital elevation data and the critical contributing area is determined. In the subsequent channel extraction a dedicated critical contributing area threshold is used for each landscape type. In order to comply with the needs of environmental monitoring, lakes and transitional waters are considered during river and catchment mapping. In addition, monitoring stations are accurately positioned on the river reaches and a dedicated algorithm has been developed to overcome problems of automatic river mapping in flat terrain. The described methodology has been developed and tested for the territory of Italy and is now implemented for the pan-european area. Results are validated comparing the derived data with river and catchment data sets from other sources and at varying scales. Good agreement both in terms of river positioning and drainage density could be demonstrated. Proceedings 8 th EC GI & GIS Workshop, July 2002, Dublin Ireland

2 2/10 J. Vogt et al. Introduction One of the main goals of EU environmental policies is to assess and monitor the state of the environment at the continental level. This requires access to large datasets organised in Geographical Information Systems (GIS). With the adoption of the Water Framework Directive (2000/60/EC) the request to use GIS for handling environmental data has assumed a formal role. For the first time, in fact, Member States are explicitly asked to provide data in a GIS compatible format. The need for well-developed and operational European-wide monitoring and reporting systems is obvious. As a consequence, systems for data collection, data harmonisation, and data transfer are requested at different levels. JRC s knowhow on pan-european data handling and management makes it possible to implement rather complex modelling schemes for such extended areas. An example is the case of deriving a pan-european database of drainage networks and catchments. The Catchment Characterisation and Modelling (CCM) activity of JRC s Euro- Landscape project ( is, therefore, developing a pan- European database of drainage networks and catchment boundaries in support of the environmental monitoring activities of the European Environment Agency and DG Environment. The resulting data layers will become part of the Eurostat- GISCO database. Currently, the level of detail of available European river network and catchment data layers ranges from mapping scales of 1:10,000,000 to 1:1,000,000. As a consequence, the use of these data is restricted to small-scale studies, while the need for more detailed assessments (i.e. quantity, quality and trend of water resources, analysis of environmental pressures and impacts) is increasing. The CCM activity, therefore, tries to achieve a mapping scale of 1:250,000 to 1:500,000, using highly automised data processing tools. This allows to cover large areas, to repeat the processing when necessary and to extend the mapping area, if requested. Study Area and Data The area to be covered in this study extends from the Mediterranean to northern Scandinavia and from the Atlantic sea to the Ural mountains. It comprises some 11.2 million square kilometres and is commonly referred to as pan-europe (see Figure 1). Its sheer extent asks for the development of automatic mapping tools. An important constraint to large-area applications is the availability of basic input data. The methodology to be developed, therefore, had to be based on data readily available over all or at least most of the study area. The following data layers were used in the frame of this study: Digital Elevation Models (DEMs), at spatial resolutions varying from 100 to 250 metres and mosaicked in order to cover the EU and Accession Countries; in areas where a medium resolution DEM could not be collected (e.g., Iceland,

3 Development of a Pan-European Database of Rivers, Lakes and Catchments 3/10 Russia) data from the HYDRO1K at 1000 m resolution were used (see Figure1). CORINE Land Cover data (Eurostat-GISCO) in grid format with a resolution of 250 meters; in areas where CORINE LC data were not available, they were complemented by IGBP land cover data (1km resolution) and PELCOM data (1 km resolution). Daily meteorological data from the European database of the MARS project, which are available on a 50 km grid for the period (Van der Voet et al. 1994, Terres 2000). Soil data, including information on the geology, from the European Soil Database (ESBSC 1998). Data from the Eurowaternet station network of the EEA (Nixon et al. 1998, Boschet et al. 2000), the Bartholomew river network at 1:1,000,000 scale and detailed river networks for a few sample catchments have been used for validation purposes (Colombo et al. 2001, Vogt et al. 2002a). 100m DEM 250m DEM 1000m DEM (outside AOI) 1000m DEM Kilometers Figure 1: CCM study area and DEM coverage

4 4/10 J. Vogt et al. Drainage Network Extraction at a Continental Scale Landscape Stratification Algorithms for the extraction of drainage channels from DEMs are implemented in many standard GIS systems. In general, these algorithms have problems with handling flat or almost flat terrain and apply a constant threshold for the critical contributing area when determining channel heads. The latter leads to a uniform drainage density over the entire study area. A major challenge in deriving a river network at continental scale, therefore, is to establish a methodology that reflects the natural variability in drainage density and is able to correctly treat flat areas. In order to comply with the first need, a landscape stratification was prepared that reflects the landscape aptitude to develop different drainage densities. The landscape strata, therefore, needed to be based on a combination of environmental factors with a strong influence on channel development. The resulting landscape types are assumed to be homogeneous with respect to drainage density and to exhibit a characteristic relationship between local slope and contributing area. As a consequence, the threshold for the minimum contributing area necessary to start a drainage channel can be varied in space, thus producing different drainage densities for different landscape types. Based on a literature survey, a set of five variables describing climate, relief type, vegetation cover, soil transmissivity, and rock erodibility were selected as the most important factors determining drainage density (see Vogt et al. 2002a and Vogt et al. 2002b for more detailed discussions): Mean annual precipitation ( ) was used as the climate indicator according to Moglen et al. (1998). The influence of the terrain morphology has been considered through the relative relief, defined as the maximum altitude difference in a moving window of 3 by 3 grid cells (Oguchi 1997, Roth et al. 1996). The percentage of surface covered by vegetation was used in the analysis due to its effect on critical shear stress and thus its control on channel initiation (Tucker et al. 1997, Foster et al. 1995). CORINE Land Cover data with a gridcell size of 250 m were reclassified into 14 classes and monthly cover percentages were assigned to each class according to the scheme derived for Europe by Kirkby (1999). As a proxy indicator of saturated soil hydraulic conductivity, soil texture has been chosen as the main soil factor affecting drainage density (e.g., Dietrich et al. 1992, Tucker and Bras 1998). Soil texture was derived from the European soil map (ESBSC 1998). From the European soil map the parent material corresponding to each soil mapping unit was extracted by deriving the dominant lithology. The rock

5 Development of a Pan-European Database of Rivers, Lakes and Catchments 5/10 erodibility was then calculated according to the scale proposed by Gisotti (1983). Through a weighted combination of these variables, a Landscape Drainage Density Index (LDDI) was then derived, which was classified into a few classes. The methodology is described in more detail in Vogt et al. (2002b). LDDI Classes Low Dd High Dd Figure 2: Landscape stratification into six landscape drainage density index (LDDI) classes For each of the LDDI classes the critical contributing area could then be defined on the basis of the relationship between local slope and contributing area. Values for this threshold typically vary between less than ten and a few hundred square kilometres (see Vogt et al. 2002a). River Network Extraction Once the thresholds for the critical contributing area are defined per landscape type, the drainage network can be extracted from the DEM by calculating the flow direction and flow accumulation matrices. This poses the problem of spurious pits interrupting the flow path. This problem has been solved by developing a new

6 6/10 J. Vogt et al. algorithm based on the concepts of morphological image analysis (Soille 1999). More precisely, each pit is suppressed by creating a descending path from it to the nearest point having a lower elevation value. This is achieved by carving, i.e., lowering down, the terrain elevations along the detected path (see Figure 3). A: Original DEM B: Minima Impostion by Carving Figure 3: DEM processing by carving In order to handle the problem of flat areas, the developed algorithm is suitable to an adaptive drainage enforcement, whereby river networks coming from other data sources are imposed to the DEM only in places where the automatic river network extraction deviates substantially from the given networks. Flow directions on truly flat regions are determined by interpolating elevation values so as to create a relief taking into account the general terrain morphology. This interpolation procedure is related to the morphological interpolation of DEMs from elevation contour lines as described by Soille (1991). In addition, priority queue data structures allow for an efficient implementation of the algorithm, which in turn enables the processing of files such as the complete pan-european DEM. Details about the algorithm can be found in Soille (2002). Finally, the landscape stratification is considered during the determination of the channel heads. As a consequence, the derived drainage network reflects the natural variability in drainage density. Lakes and lagoons are taken into account through a specific layer, which is based on CORINE Land Cover (CLC) data as well as other land cover data in areas where CLC data are not available. It is ensured that rivers flow along the centre line of the lakes. The derived drainage network is fully connected and hierarchically structured from the smallest tributary to the largest river flowing into the sea. A view on a subset of the resulting drainage network is shown in Figure 4.

7 Development of a Pan-European Database of Rivers, Lakes and Catchments 7/10 Figure 4: Example of the resulting river network for the Iberian peninsula with major catchments delineated and Eurowaternet stations positioned. Drainage Basin Delineation and Station Positioning Basins and sub-basins are then delineated according to the surface morphology. A further correction is introduced in the case of sub-basins intersecting lakes. These are recalculated so that the outlet of each basin lies along the lake perimeter (Figure 5). Tests showed that the overestimation of subcatchment areas without this correction can be as large as 10%. In order to position the Eurowaternet stations on the river network, a specific algorithm has been developed that optimises the station position along the derived river reaches and calculates the area of the drainage basin upstream of each station. The results show that for the continental part of the study area (excluding UK, Ireland, Iceland and Scandinavia) 83% of the stations drain a surface that is estimated within a 15% error of the official values given by the EEA member states.

8 8/10 J. Vogt et al. A: Not Considering Lakes B: Considering Lake Perimeter Figure 5: Considering lake perimeters when computing 1 st order catchments Data Validation A first validation of the dataset is carried out through (a) checking data topology and coherency, and (b) against independent data sets. With respect to (a) the most important data requirements are that the river network is fully connected, that connectivity is maintained through lakes, that lakes are represented by closed polygons, and that consistency exists between the different layers (i.e., rivers, lakes, coast and catchment boundaries and in some cases political boundaries). Data validation against independent data sets is performed using existing European and national datasets, as well as a few large-scale datasets for selected drainage basins. The validation is implemented in two ways: (a) through the assessment of the position of the river reaches by overlaying them to the reference datasets and evaluating their correspondence through buffers of varying size; and (b) through the comparison of the calculated size of a sample of river basins with the officially reported size in the Eurowaternet database (more than 3000 basins). First results of this validation have shown that the river network is of high quality and corresponds to a mapping scale of roughly 1:500,000. More information on the validation procedure can be found in Vogt et al. (2002a) and Colombo et al. (2001).

9 Development of a Pan-European Database of Rivers, Lakes and Catchments 9/10 Conclusions and Outlook The methodology presented in this paper allows for the derivation of high quality pan-european datasets on river networks, lakes and associated catchments. By including a landscape stratification, the developed algorithm allows to retrieve drainage networks reproducing the natural variation in drainage density. It has further been implemented with a fast and reliable algorithm based on the concepts of morphological image analysis. The speed of this algorithm allows for repeated calculations even for large areas such as the entire European continent. This is a major asset for implementing corrections after further validation steps. In the current version, the LDDI is subdivided in only a few classes for practical reasons of deriving the critical contributing area. Further improvements of the methodology are, therefore, expected through the use of more drainage density classes or the implementation of a continuous LDDI. Based on the underlying data on climate, vegetation cover, terrain, soils and geology, a first set of characteristics will be calculated for each catchment in the hierarchical system. These can serve for further analysis and in some cases as proxy pressure indicators. In the near future the set of characteristics will be extended with more detailed data, given specific consideration to the calculation of a set of pressure indicators for the monitoring activities of the European Environment Agency (EEA) and to the calculation of agri-environmental indicators. As a final step, a coding system will be introduced. This coding system will provide a unique identifier for each river reach, lake and drainage basin. The coding system will follow the recommendations given by the European Working Group on GIS under the Common Implementation Strategy for the Water Framework Directive 1. As a result of this Working Group, a Guidance Document on GIS issues under the Water Framework Directive will be published in early A first version of the described River and Catchment GIS, including a first set of catchment characteristics and a coding system, will be finalised by the end of the year It is expected to become part of the Eurostat-GISCO reference database in References BOSCHET, A.F., V. DE PAEPE, T.J. LACK (2000): Inland waters. Annual topic update.- European Environment Agency, Topic Report 1/2000, Luxembourg (Office for Official Publications of the European Communities) 30p. COLOMBO, R., J.V. VOGT, F. BERTOLO (2001): Deriving drainage networks and catchment boundaries at the European scale. A new approach combining Digital Elevation Data and environmental characteristics.- Office for Official Publications of the European Communities, Luxembourg, EUR EN,. 58 p. DIETRICH, W.E., C.J. WILSON, D.R. MONTGOMERY, J. McKEAN, R. BAUER (1992): Erosion thresholds and land surface morphology.- Geology 20:

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