AWRA 2010 SPRING SPECIALTY CONFERENCE Orlando, FL IMPACT OF PIT REMOVAL METHODS ON DEM DERIVED DRAINAGE LINES IN FLAT REGIONS

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1 AWRA 2010 SPRING SPECIALTY CONFERENCE Orlando, FL March 29-31, 2010 Copyright 2010 AWRA IMPACT OF PIT REMOVAL METHODS ON DEM DERIVED DRAINAGE LINES IN FLAT REGIONS Walter Collischonn, Diogo Costa Buarque, Adriano Rolim da Paz +, Carlos André Bulhões Mendes, Fernando Mainardi Fan * ABSTRACT: Flat surfaces and spurious depressions are common features in raster Digital Elevation Models (DEM) of relatively low relief regions. Different methods have been created to overcome these features when defining flow directions and drainage networks, ranging from breaching to depression filling. The quality of the resulting streamlines is strongly related to the method used to remove pits and depressions, and to overcome flat surfaces. Most of the problems can be solved by imposing known drainage lines on the raster DEM by stream burning or similar techniques. However, in regions where no reliable vector drainage lines are available, the best pit removal method should be used. We used different GIS computer programs with diverse flow direction and pit removal methods, and compared the resulting river networks with drainage lines digitized over well referenced satellite images. The tests were carried out using SRTM DEM of flat regions of the Amazon basin, considering rivers with varying width and slope. In general better results were obtained by methods that breach the DEM at spurious depressions instead of filling the whole depression. Results were also shown to be dependent on river characteristics, such as width and slope. KEY TERMS: pit removal, DEM, Amazon, flow directions INTRODUCTION Modern tools for hydrological analysis of streams and watersheds are more and more based on information derived from Digital Elevation Models (DEM). Several products derived from DEMs can be used as input for distributed hydrological models, such as drainage network, basin delineation and maps of slope and aspect (Burrough and McDonnel, 1998; Johnson, 2009). One of the first steps for deriving hydrological relevant information from DEMs is the definition of flow directions for each cell, from which several attributes can easily be obtained, such as drainage area, watershed divides, river networks, and the length and slope of river reaches. The first methods to define flow directions were described during the 80 s (O Callaghan and Mark, 1984; Mark, 1984; Jenson and Domingue, 1988) and the most important contribution was the assignment of flow directions of one cell according to elevation values of the cell and its neighbors, looking for the direction of the steepest descent, which is now known as the D8 method. During the following years several changes or improvements to the original methods have been proposed, including multi-directional flow (Quinn et al., 1991), the combination of vector information with the raster DEM (Saunders, 1999; Hutchinson, 1989; Soille et al., 2003) and the necessity to avoid parallel drainage lines (Fairfield and Leymarie, 1991). One particular question in this subject that still motivates research is the necessity of defining flow directions in flat regions and depressions (Lindsay and Creed, 2005; Soille et al., 2003; Wang and Liu, 2006; Planchon and Darboux, 2001; Grimaldi et al., 2007). This issue was initially solved using approaches described by Jenson and Domingue (1988) and by Garbrecht and Martz (1997), however it still continues to deserve attention because sometimes results obtained using traditional methods are not completely satisfactory. Another raising question in this subject is computational efficiency of methods to solve the problems imposed by flat areas and depressions (Wang and Liu, 2006; Planchon and Darboux, 2001). This is more important because the spatial resolution of DEMs is growing as new products, as LIDAR, are becoming more used. At the same time the scale of the problems which the water resources community is dealing with is increasing, with attempts to develop hydrological models for continental scale basins using information from SRTM DEM (Collischonn et al., 2007; Paz and Collischonn, 2007). The problem of defining flow directions over DEMs becomes more important when the topography of the region under study shows large floodplains and low slope rivers, as is the case in parts of the Amazon basin. This paper shows a * Respectively, Associate Professor, Graduate Student, Graduate Student, Associate Professor, Student, Federal University of Rio Grande do Sul UFRGS, Institute of Hydraulic Research IPH, Av. Bento Gonçalves, 9500 Agronomia, Porto Alegre-RS, Brazil, CEP , Phone: +55 (51) , collischonn@uol.com.br. + Researcher, EMBRAPA-CNPM, Av. Soldado Passarinho 303, Campinas-SP, Brazil. 1

2 comparison of results obtained by five methods of pit removing and flow direction definition in terms of the quality of derived drainage lines of rivers in the Brazilian Amazon. BACKGROUND One of the main challenges for defining flow directions over raster grids is the presence of pits, depressions or sinks, which are formed by one cell or a group of adjacent cells that are surrounded by cells with higher elevation. Unfortunately all DEMs, independent of the way they were generated, seem to have those pits, and their area may cover up to 5% of the total DEM area (Tarboton et al., 1991). Historically, pits or depressions are one of the major problems in hydrological applications of DEMs, because they hinder flow routing (Rieger, 1998). Ideally, actual and artificial pits should be distinguished (Lindsay and Creed, 2006), however it is common practice to assume that all depressions are artifacts, i.e. pits are formed by errors in the development of the DEM, due to limited horizontal/vertical resolutions, operator error or interpolation error. The first proposed method for removing pits of a DEM consisted of applying a low-pass filter, such as a moving average (Mark, 1984), but this method does not guarantee that all pits are removed and it can add new pits in narrow valleys (Grimaldi et al., 2007). Other methods try to reduce the presence of pits by pre-conditioning the DEM using vector drainage line information, an operation that could be performed during the interpolation or creation of the grid DEM (Hutchinson, 1989), but the most common method is to change the DEM using drainage stream burning (Saunders, 1999; Maidment, 2002). This method can only be applied where vector hydrography data is available in a scale that is compatible with the DEM data, and it does not completely eliminate the presence of pits in the reconditioned DEM. The most popular methods to deal with pits in DEMs try to eliminate them from the elevation grid by adjusting the grid values so as to insure that there is at least one downslope direction for each cell in the grid. The adjustment can be obtained by increasing the elevation of the cells inside the pit ( pit filling or depression filling ), by reducing the elevation of cells on the pit border ( carving or breaching ), or by a combination of the two. The pit filling procedure consists of simply increasing the elevation of the cells within a pit until a way out can be found, which is repeated iteratively until all depressions are filled up, and no cells exist within the DEM without a hydrologically connected downstream cell. This method is implemented, for instance, in the ESRI ArcGIS tool Fill, following the Jenson and Domingue (1988) algorithm. A different approach has been proposed by Planchon and Darboux (2001), whose algorithm first inundates the whole surface represented by the DEM, by assigning a high surface water level to all cells and then drains the excess water from each cell. It has been implemented in the freeware Terrain Analysis System software (Lindsay, 2005). Jones (2002) described a method to remove depressions from a DEM by applying a priority-first-search algorithm (PFS) to find an outlet for a pit and then adjust the elevations of the cells along the way from within the depression to the outlet. The adjustment is a variable decrease in elevation, the same way in the breaching method proposed by Martz and Garbrecht (1998), but it is not limited to one or two cells, as in the case of the algorithm proposed by those authors. THE PROBLEM OF DEFINING DRAINAGE LINES FROM DEM IN THE AMAZON The issues raised and results obtained and discussed in this paper came out from an effort to apply the large-scale hydrological model MGB-IPH (Collischonn et al., 2007) to the Amazon basin (Paiva, 2009; Paiva et al., 2009) using preprocessing procedures such as ArcHydro tools (Maidment, 2002). The Amazon is the world s largest river basin, and parts of it show a very shallow relief. Covering the whole Amazon, the best available topography information in the region is the DEM derived by the Shuttle Radar Topography Mission, with a horizontal resolution of about 90 m, and with an elevation resolution of 1 m (Farr et al., 2007). Due to its nature, SRTM DEM actually gives the elevation of the vegetation instead of the terrain itself, and artifacts arise in partially deforested regions (Valeriano et al., 2006). Nevertheless, it is recognized that SRTM information for this region is generally better than DEMs produced by interpolation of contour lines from 1:100,000 maps (Santos et al., 2006). No reliable vector hydrography layers are available that could be used to improve the DEM by preconditioning methods such as stream burning, except for some of the largest rivers. The best available digitized vector drainage lines that we found were the layers provided by Brazil s National Water Agency (ANA), which were obtained from 1:1,000,000 scale maps. Therefore the Amazon poses a huge challenge in terms of the usual methods used to generate hydrologically relevant information from the DEM: huge amounts of data (approximately 40,000 columns and 31,000 rows from SRTM 90 m DEM); large relatively flat areas; available DEM with recognized problems. METHODS We obtained drainage lines of main rivers in two test areas in the Amazon basin by applying the following sequence of procedures that is typical of DEM analysis in water resources engineering (Johnson, 2009): remove sinks; define flow directions upstream to downstream; accumulate flow; define streams or drainage lines. 2

3 The following five different methods of pit removal and flow direction definition have been tested: (a) Jenson and Domingue method as implemented in TAS; (b) Planchon and Darboux method as implemented in TAS; (c) Jenson and Domingue method as implemented in ArcGIS; (d) PFS method as implemented in Idrisi Kilimanjaro version; (e) Jenson and Domingue method with a random factor to avoid parallel drainage lines as implemented by Paz et al. (2006). Two test areas were chosen within the Purus river sub-basin to apply the methods (Figure 1). The two regions are in relatively flat regions since no significant differences are expected between the methods in high relief areas. The first test region comprises a SRTM 90 m DEM with 1392 columns and 426 rows in which there is a 484 km long reach of the Purus river (Figure 2a). This river is one of the most important tributaries of the Amazon, with a drainage area of about 376,000 km 2, and shows a very sinuous planform, with very sharp bends and width about 300 m. The second test region is a SRTM 90 m DEM with 1092 columns and 948 rows, which comprises a 450 km long reach of the Ituxi river, a tributary of the Purus, and whose drainage area is about 45,000 km 2. The relief of both test areas is quite similar, but the Ituxi river is much narrower (about 100 m). The drainage lines for the main rivers of both DEMs derived by the different methods were compared to drainage lines manually digitized following the centerline of the rivers over well georeferenced Landsat ETM images using ArcGIS. These digitized lines were assumed to be correct and the method suggested by Matos (2001) was applied to quantify the closeness between DEM-derived and actual drainage lines. Following this method, the two lines being compared are overlaid and polygons are created where the lines define closed regions (Figure 2a). The sum of these polygons areas is considered to be inversely related to the agreement between the two lines. The resulting area is further divided by the length of the actual drainage line, giving in an average error in meters. We also used a slightly modified version of such method, in which a buffer was created around the actual drainage lines, and the polygon areas within the buffer were not added to the total area (Figure 2b). The distance to calculate the buffer was considered to be the same as the river width. -80W -70W -60W -50W -40W -30W 10N 10N 69W 68W 67W 66W 65W 64W 63W 62W 0 0 6S 6S -10S -20S -30S -10S -20S -30S 7S 8S 9S Purus River Ituxi River 7S 8S 9S -40S -50S -80W -70W Legend -40S Purus River Basin Amazon River Basin Brazil -50S South America -60W -50W -40W -30W 10S 69W 68W 67W 66W 65W km Figure 1: Region of tests of the pit removal methods, close to the confluence of the rivers Ituxi and Purus, one of the major tributaries of the Amazon which flows through low relief completely forested areas. 64W 63W 62W 10S Figure 2: (a) Example of the method to quantify closeness between derived (dotted black) and actual drainage lines (grey continuous) by measuring the area of the polygons defined by the intersection of both lines (grey areas); (b) The same of (a), but considering the modified method which disregards the polygon areas within the buffer (grey continuous wide). 3

4 RESULTS For the Purus river (the main river that flows within the first test area), comparisons between actual and calculated drainages using ArcGIS and using PFS algorithm, which is mostly based on breaching than on filling of depressions, seem to give very good results, and the same is valid for the other methods (Table 1). In terms of area between calculated and actual lines and the derived average error, average errors of 61 to 87 m were obtained. There is a slight advantage of the programs that use the Jenson and Domingue (1988) method. These general good results for the Purus river seem to be related to the relatively large width of the river, which is close to 300 m, and therefore encompasses more or less three cells of the SRTM 90 m DEM. Because the elevation measured by the SRTM surveying is actually the elevation of the vegetation cover and not the elevation of the terrain, and because river margins are covered with forests, this river is well defined in the SRTM DEM, and the derived drainage is excellent, despite of the difficulties imposed by the low slope and flat relief. Table 1: Polygon areas (km 2 ) and average errors (m) created by intersection of actual and automatically derived drainage lines using different pit removal methods. Purus river (test area 1) Ituxi river (test area 2) Method Area between lines (km 2 ) Average error (m) Area between lines excluding buffer (km 2 ) Area between lines (km 2 ) Average error (m) Area between lines excluding buffer (km 2 ) PFS - IDRISI Planchon e Darboux TAS Jenson e Domingue TAS Jenson e Domingue ArcGIS Jenson e Domingue D8fa In the second test area (Ituxi river) there is a clear advantage of the PFS method implemented in Idrisi. This method resulted in an area of 16 km 2 between lines, while all the other methods show areas close to two times larger. This river is narrower than the Purus and its width encompasses only a single DEM cell. Therefore, any elevation error along the main river gives rise to a blockage, and an obstacle to the flow. The region upstream any blockage gives rise to a depression, which has to be removed. The resulting drainage line is strongly related to the way this depression is removed. In general, it becomes clear that there are several points of bad agreement between the calculated and actual drainage lines (Figure 3). Figure 3: Comparison of the actual drainage line of the Ituxi river (continuous grey line) with the automatically derived drainage line using different methods: (a) PFS algorithm using Idrisi Kilimanjaro; (b) Planchon and Darboux using TAS; (c) Jenson and Domingue using TAS; (d) Jenson and Domingue using ArcGIS; (e) Jenson and Domingue using Paz et al. (2006) program; (f) the best available vector drainage line from ANA is shown for comparison. 4

5 We observed that part of these errors are not really relevant, because over relatively long reaches the lines are very close together and automatically derived lines are within the actual width of the existing river. Therefore we applied the modified version of the quantification method, in which areas within the buffer around the river were not taken into account. It can be seen that all pit removal methods are equally good in the case of the Purus river. However, for the Ituxi river there is a very clear advantage of the PFS method, with only 2 km 2 of area between the drainage lines, while other methods give a difference of more than 12 km 2. The visual comparison provided by Figure 3 also shows that the drainage calculated for the Ituxi river with PFS Idrisi is in perfect agreement with the actual drainage line, while all the other methods tend to follow the main river but deviate from the actual path line at most of the river meanders. These meander cuts tend to form a much shorter river than the actual one. Also shown in this Figure are the best available digitized vector drainage lines. In this case the vector hydrography does not agree well with the actual drainage line of the Ituxi river. This means that any DEM conditioning method such as stream burning would enforce a wrong drainage line on the DEM, giving worse results than would be obtained by the best available automatic method (PFS Idrisi). The advantage of the PFS algorithm implemented in Idrisi seems to be related to the fact that, unlike the other methods, it does not fill depressions. The PFS method breaches the depression outlets, by reducing the elevation of a few cells that block the river, thus changing the elevation of only a few cells while preserving the information contained in the original DEM upstream of the blockage. The pit filling methods, on the other hand, increase the elevation of all cells located upstream of a blockage. Depending on the elevation of the depression outlet, the whole region of the river can be transformed in a flat area, where flow directions are set more or less arbitrarily, as the information contained in the original DEM is partially lost. The comparison we conducted does not allow for a complete assessment of the differences in computational efficiency between the methods, since the algorithms were implemented by different programmers, in different computer languages, and because the DEMs of both test areas are relatively small. However it is interesting to note that the PFS Idrisi method was among the methods giving the fastest results and that for the same program (TAS) the pit filling method of Planchon and Darboux (2001) resulted in significant less processing time (18% faster for Purus river and 57% for Ituxi river ) than the method of Jenson and Domingue s (1988). CONCLUSIONS We have shown that there are clear differences of resulting drainage lines between methods of pit removal. Methods based on depression filling seem to generate large flat areas, where part of the information of the original DEM is lost. As a consequence of this loss, erroneous drainage lines are created, which are generally shorter than the actual ones, because several meanders are cut. This is the case of the Jenson and Domingue (1988) method, which is the most popular method and is used in widespread software as ArcGIS and its ArcHydro set of Tools. On the other hand, methods based on pit removal by breaching or carving, as the PFS method implemented in Idrisi Kilimanjaro, only change the elevation of a few cells, preserving most of the information contained in the original DEM. This finding is in accordance with the suggestions by Jones (2002), Rieger (1998) and Martz and Garbrecht (1998). If we consider only pit removal methods based on depression filling, as Jenson and Domingue (1988) and Planchon and Darboux (2001), no important differences in resulting drainage lines can be found. The correct positioning of links between rivers was not assessed in this study, but it is expected that this important product is also strongly dependent on the pit removal method that is used. Although we could not prove it, we expect that the PFS pit-removal method gives the best results in terms of positioning of channel links, because the DEM is less affected. The findings presented here and by other authors suggest that pit removal algorithms currently used in some of the most popular GIS packages are at the same time less effective and less efficient than other methods that are also simple and that introduce less arbitrary changes to the original DEM. Finally, it is worth to stress that the importance of errors in the definition of drainage lines should not be underestimated. 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