Terrain Analysis in GIS and Its Significance to Surface Runoff Analysis (A Study of Basawa Community in Sabon Gari L.G.A. of Kaduna State, Nigeria)

E S Scholars www.setscholars.org T Knowledge is Power February 2012 Volume 1, Issue 1 Article #06 IJASETR Research Paper ISSN: 1839-7239 Terrain Analysis in GIS and Its Significance to Surface Runoff Analysis (A Study of Basawa Community in Sabon Gari L.G.A. of Kaduna State, Nigeria) Isioye, O. A 1*, Enebeli, I. 2, Alademomi, S. A. 3, and E. 4 Akomolafe 1,2, 4 Lecturer, Department of Geomatics, Ahmadu Bello University, Nigeria, 3 Lecturer, Department of Surveying and geoinformatics, University of Lagos,Nigeria *Corresponding author s e-mail: lekkyside4u@yahoo.com, oaisioye@abu.edu.ng Abstract The problem of flooding is becoming a global menace which must be tackled seriously as it usually leads to wanton destruction of lives and properties. Basawa Community and its environs are not left out of areas affected by this global phenomenon. This area is usually flooded annually during the raining season due to the poor drainage system existing in the locality. The stagnancy of water during the raining season causes water to flood into homes. This study focuses attention on Digital Terrain Analysis (DTA) of the study area. The effect of this DTA on the surface runoff were analyzed, this was achieved by generating and extracting contour data and planimetric features from a topographic survey and a high resolution satellite image of the area respectively, these information were then used to derive the Digital Elevation Model (DEM) of the area consequently used for surface runoff analysis of the area under investigation. The DEM of the study area was generated in a GIS environment from 3D coordinate data collected using Differential GPS technique (DGPS) and the DEM was analyzed by extracting basic terrain parameters such as slope, aspect, flow direction, flow accumulation, drainage network etc. The Integrated Land and Water Information System (ILWIS) software was used for the generation of the DEM and its analysis. The terrain parameters were further used as input to analyze the surface runoff in the locality. The analysis gave information on ways to curb this recurring flooding by efficient discharge of surface runoff into drainage channels. Finally, ways of safeguarding lives, properties and other valuables in the area from recurring seasonal flooding were proposed. Keywords: Digital Terrain Analysis (DTA), Surface Runoff, Slope, Aspect, Digital Elevation Model (DEM), Flood Isioye, O.A., Enebeli, I., Alademomi, S. A., and E. Akomolafe (2012), Terrain Analysis in GIS and Its Significance to Surface Runoff Analysis (A Study of Basawa Community in Sabon Gari L.G.A. of Kaduna State, Nigeria). IJASETR 1(1): Article #02. Received: 01-01-2012 Accepted: 05-02-2012 Copyright: @ 2012 Isioye et al. This is an open access article distributed under the terms of the Creative Common Attribution 3.0 License. 72

1. INTRODUCTION Natural disasters happen every year and their impact and frequency seem to have greatly increased in recent decades, mostly because of environmental degradation, such as deforestation, intensified land use, and the increasing population. Floods are among the most frequent and costly natural disasters in terms of human and economic loss [1]. These flooding have caused considerable damage to highways, settlement, agriculture and livelihood. While the rains are needed for agriculture, particularly wet rice cultivation, they are also largely responsible for bringing seasonal floods. Among the several types of disasters, flood disaster is a worldwide natural phenomenon especially in a flood-prone area or locality like Basawa barracks and its environs. Typical rainfall, particularly during the month of August each year causes rainwater flooding with devastating effects in Basawa and its environs. Such disaster is increased by the human activities on land such as construction, agriculture, deforestation etc. In Basawa locality, improper planning of their drainage system is the main cause of annual flooding experienced there. This area is flooded every year (Field Survey, 2011). It is expected that accurate mapping of flood hazard areas would improve the planning and sitting of flood protection measures and administration. And also, accurate mapping of flood hazard areas would improve the planning and implementation of flood protection measures and administration. Capabilities for visualizing topography in GIS have evolved from 2D raster maps, contours, and simple 3D meshes in the 1980s to interactive 3D rendered surfaces with shading and color maps draped over the surface that became standard in the 1990s [2]. Recently, several new technologies that combine the flexibility of digital landscape representation with intuitive 3D physical models have emerged. These technologies open new possibilities for user interaction with geospatial data. A prototype tangible geospatial modeling environment in GIS lets users interact with terrain or landscape analysis and simulations using a tangible physical model such as DEM [3]. According to Pradhan [4], Remote Sensing and Geographic Information Systems (GIS) have been embedded in the evaluation of the geo-environmental hazards in recent years. Many research studies have been completed that employ DEM analyzed in a GIS environment as the principal information source in the assessment of hazards/disasters, flooding inclusive. There have been 73

many studies on flood susceptibility mapping using remote sensing data and GIS tools [4], [5], [6], [7], and [8]. This study is aimed at using GIS to analyze terrain and check its significance to surface runoff in the study area so as to curb the recurring annual rainwater flooding caused by bad runoff drainage in the locality. It focuses on the use of contour data and planimetric features generated and extracted from a topographic survey and a high resolution satellite imagery of the area respectively to derive a Digital Elevation Model (DEM) for terrain and surface runoff analysis in Basawa Barracks and its environs in a GIS software environment. This derived DEM was used as terrain inputs for performing spatial analysis and obtaining derivative products. The generated DEM was used to analyze the terrain and then used to mark out drainage patterns of the study area using a combination of GIS software namely ILWIS Open 3.7 and Surfer 9 (and its extension tools). A high resolution IKONOS satellite imagery of the study area was used to extract the existing drainage in the locality by digitizing these drainage channels and other planimetric features. In marking out the drainage pattern, topographic attributes such as slope, aspect, flow direction and flow accumulation were considered as factors affecting the flow of surface runoff. 1.1 STUDY AREA The study area includes parcels of land between the Basawa Military barracks and Hayin Dogo Civilian settlement. Geographically, the community lies between latitudes 11 09 N and 1111 N and between longitudes 7 40 E and 7 41 E, covering a total area of about 371.91 Hectares. The whole study area is a suburb of Sabon Gari Local Government Area of Zaria; a city in Kaduna State, Nigeria. The topography is composed of plains and valleys with elevations ranging from 644m to 680m above the local datum [9]. This part of Basawa is characterized by a built-up area, sparse tree cover, farmlands and a stream that runs through its middle as depicted in Figures 1(a) and (b). 74

Figure 1a: IKONOS satellite imagery of the study area (Source: Centre for Remote sensing and GIS of The Nigerian space Agency) Figure 1b: Digitized map of the study area 2.0 MATERIALS AND METHODOLOGY 2.1 PROCEDURES AND METHODS OF DATA ACQUISITION A reconnaissance survey was carried out prior to the commencement of the study. This site reconnaissance was completed during the planning stage. It was a very good idea to walk through the study site so as to inspect it, consider, select and mark suitable instrument stations. From the field reconnaissance, a reconnaissance diagram was drawn indicating features and the points which had been selected for the traverse survey and subsequent instrument stations. This reconnaissance diagram served as a visual guide during office-planning for the execution of the task. The primary data sources include all data (coordinate data) collected from the traverse survey of the survey site using both the GPS and the total station. Other primary data sources include the height data collected by the Real-time kinematic survey method using the Sokkia Stratus Differential GPS (DGPS) which were eventually used to generate the Digital Elevation Model (DEM) of the study area. The secondary data source includes the satellite imagery of the study area. 75

To realize the aim of this study, software such as ILWIS Open version 3.7, Microsoft Excel, Sokkia Link and Sokkia Spectrum Survey v4.00 were used. The basic instruments used in the acquisition of field data include: Sokkia Set510 Series Total Station and Sokkia Stratus Differential GPS Receivers. A method for creating and quantitatively analyzing virtual environment by using a DEM as the base for the terrain is employed in this study. The process of quantitatively describing terrain is known as Digital Terrain Analysis (DTA), this approach is well documented in [10]. Common synonyms are geomorphological analysis, landform parameterization and surface analysis. DTA is a set of techniques used to derive terrain parameters such as slope, aspect, flow direction, flow accumulation, catchment area, profile curvature etc. The following sub-section gives briefs into how some of these terrain parameters were generated for the study. 2.2 DEM CREATION AND TERRAIN ANALYSIS IN ILWIS In order to create and analyze the DEM, a number of maps were created in the GIS software (ILWIS). Each map was created by the following procedure as stated below. Point mapping In order to create the point map, the 3-D coordinates of all points collected in the field (study area) were arranged in three columns in an ILWIS table and a forth column was created for the points IDs. This table was then converted into a point map with reference to the coordinate system created in Universal Traverse Mercator (UTM) system. A point map is a data object used to store spatial geographic information which consists of points defined by their planimetric coordinates. Point Interpolation The created point map was used as input to create an interpolated point map using the Kriging point interpolation technique with the ordinary kriging type method. The output map was a DEM. A Fill Sink map was also created using the point interpolation map as input. The Fill sinks operation removes local depressions from a DEM by replacing these local depressions by flat areas in the output DEM. 76

DEM Creation The Kriging-interpolated point map was filtered using the filter command to create a 2-D DEM. This DEM was visually enhanced for better visualization using the DEM visualization command in the operation tree. 2.3 TERRAIN PROCESSING AND ANALYSIS With the DEM now created, the terrain processing of the DEM was then done. This involves creating terrain-parameter maps using the DEM hydro-processing menu/command in ILWIS. Flow Direction Map The filled DEM was then used to calculate the flow direction map using standard D-8 algorithm [11]. Flow direction is calculated for every central pixel of input blocks of 3 by 3 pixels, each time comparing the value of the central pixel with the value of its 8 neighbours. The output map contains flow directions as N, NE, NW, S, SE, SW, E and W. The steepest slope method was used for this study to find the steepest downhill slope of a central pixel to one of its 8 neighbour pixels and assign to flow directions. Flow Accumulation Map The processed flow direction was then used as base map for calculating the flow accumulation map of the study area. The flow accumulation map contains cumulative hydrologic flow values that represent the number of input pixels which contribute any water to any outlet. The operation was used to find the drainage pattern of the terrain. Drainage Network Ordering Map The flow direction and flow accumulation maps were used to extract the drainage pattern in the locality. The Drainage network ordering operation examines all drainage lines in the drainage network extraction map, finds the nodes where two or more streams meet, and assigns a unique ID to each stream in between these nodes, as well as to the streams that only have a single node. The Drainage network ordering operation finds individual streams within a drainage network and 77

assigns a unique ID to each stream. The operation delivered an output raster map, an output segment map and an output attribute table. Drainage Network Extraction Map The flow accumulation map was used as input to create a Drainage Extraction Map. The Drainage Network Extraction operation extracts a basic drainage network. Flow length map A flow length map was created using the flow length to outlet command. It takes the flow direction and drainage network ordering map as input. Catchment Extraction and Catchment Merging Maps The drainage network ordering, the flow accumulation, the flow direction maps and the created DEM were all used to extract the catchments of the drainage network and to merge the catchments. The Catchment Extraction operation constructs catchments; a catchment was calculated for each stream found in the output map of the Drainage Network Ordering operation. The Catchment merge operation is able to merge adjacent catchments, as found by the Catchment extraction operation. New catchments were created on the basis of the Drainage network ordering map and its attribute table (see Figure 2). 3.0 RESULTS AND ANALYSIS 3.1 RESULTS During the course of this study, spot height data were collected to produce a Digital Elevation Model (DEM) on which a terrain analysis was performed to see its significance to surface runoff so as to check the recurring flooding of the area under investigation. Using a DGPS in kinematic mode, all data collected were 3-dimensional i.e. in Easting, Northing and Height. Figure (3) shows the point map created using the height data from which the DEM of the study area was created. 78

Figure (4) depicts the topography of the study area by contour lines with a maximum value of 681m and a minimum value of 644m. These values are clearly labeled on the contour lines. Figure 2: Catchment map of the study area overlaid with the network ordering map Figure (5) shows a 2-D depression-less DEM of the study area (i.e. a sink-free DEM). The key/legend shows the height values in metres ranging from 657m to 680m. These are depicted in variation of colours. Figure (6) shows 3-D colour shaded elevation model of the study area which truly depicts the terrain of the area. This map, as shown below, clearly shows the stream which flows through the study area. The Flow direction map is shown in Figure (7). It shows the flow direction from each cell to its steepest down-slope neighbour. Flow direction is calculated for every central pixel of input blocks of 3 by 3 pixels, each time comparing the value of the central pixel with the value of its 8 79

neighbours. The map contains flow directions as N (to the North), NE (to the North East) etc. The algorithm used is called the D-8 algorithm in ILWIS. Figure (8) shows the flow accumulation map generated from the flow direction map. Figure 3: A point map of a part of Basawa (Barracks and its environ) 80

Figure 4: Contour map of the study area Figure 5: 2-D DEM generated by interpolating the point map of the study area 81

Figure 6: Showing a colour shaded 3-D DEM of the study area Figure 7: Flow direction map of the study area 82

Figure 8: Flow accumulation map of the study area In Figure (9), the aspect map is shown in degrees. This map was generated using a script command/algorithm in ILIWIS software. This was further used to generate the classified aspect map of the study area shown in Figure (10). Figure (11) depicts the slope map of the study area in percentages to which was used to generate the classified slope map of the area according to the steepness of the slope. The classified slope map is shown below in Figure (12). Stream Figure 9: Aspect map of the study area 83

Stream Figure 10: Classified aspect map of the study area Stream Figure 11: Slope map of the study area in percentage 84

Stream Figure 12: Classified slope map of the study area 3.2 ANALYSIS 3.2.1 DRAINAGE PATTERN ANALYSIS From the drainage network ordering map extracted from the Digital Elevation Model (DEM), the area appears to have a dendritic drainage pattern. This is illustrated in Figure (13) below. The legend shows the downstream elevation of each drainage segment. Downstream elevation is the elevation, as extracted from the DEM, at the position of the XY-coordinate of the end of a stream segment (down-flow). A dendritic drainage pattern is the most common form and looks like the branching pattern of tree roots. It develops in regions underlain by homogeneous material. That is, the subsurface geology has a similar resistance to weathering so there is no apparent control over the direction the tributaries take. Tributaries are joining larger streams at acute angle (less than 90 degrees). This is true as seen in the drainage lines as they flow into the stream in the locality. 85

3.2.2 ANALYSIS OF FLOW DIRECTION Figure 13: Drainage network pattern of the study area From Table (1), the number of pixels shows that flow eastwards is highest. This means that most of the surface runoff will tend to flow eastwards on the left across the stream and flow west on the right side across the stream. This calls for the construction of drainage channels that will slope towards the east of the study area. Surface water will also tend to flow south eastwards as 139008 pixels with an area of 556032m 2 flows in that direction which is also towards the east, though southwards. This is the direction in which the stream in the locality flows. The total pixels area is 3704056m 2 with 926014 pixels. Table 1: Statistics of Flow Direction Map Data ASPECT CLASS North North East East South East South South West West North West No. of pixels 94360 116332 204354 139008 119486 97292 97601 57581 Area(m2) 377440 465328 817416 556032 477944 389168 390404 230324 % Area 10.15 12.51 21.98 14.95 12.85 10.46 10.5 6.19 86

3.2.3 SLOPE ANALYSIS The ILWIS GIS software was used to generate a slope map using a command script which was further used to classify the output slope map. The slope was classified into five classes based on slope in percentage as suggested by the ILWIS help file. The classification were as follows: Flat (0-2%), Gentle slope (2-8%), Sloppy (8-16%), Steep slope (16-30%), Extreme slope (> 30%). The slope maps show the steepness of the slopes irrespective of the direction of the slope. Based on the classified slope map of the study area, and as seen in Table (2), a large portion of the area is flat, accounting for 228.60 hectares of the total land area of 371.91 hectares. This is about 61.46% of the total land area. Only 99.16 hectares slopes gently which is 26.66% of the total area. The steep slope has a total area of 7.86 hectares of land accounting for only 2.11% of the area. These steep slopes are seen very close to the stream as depicted by the classified slope map. The flat areas have the maximum value while extreme slopes are very minimal. This analysis can be interpreted to mean that the flooding in the locality is mainly due to the flatness of a greater portion of the terrain. Ideally, this will prevent the flow of surface water during rains. There will be a good flow in areas close to the stream within the study area. Table 2: Statistics of Classified Slope Map Data ASPECT CLASS Flat Gentle Slope Slopy Steep Slope Extreme Slope No. of pixels 571497 247909 78583 19639 12142 Area(m2) 2285988 991636 314332 78556 48568 % Area 61.46 26.66 8.45 2.11 1.31 As shown below in Figure (14), the existing drainage map in the residential quarters (digitized from the satellite imagery of the area) of Basawa barrack was overlaid on the classified slope map. The figure shows that the buildings are situated in the north-eastern part on the map, an area in which the predominant slope is flat. Gentle slopes are also seen to be common in this area. The existing drainage channels open up into these flat slope and gentle slope areas. This means that the area will be flooded by surface runoff since the drainage channels cannot drain the surface 87

water (which flows into them) efficiently due to flat and gentle slopes in the locality. Surface water can hardly flow off land during rains as the area is flat. This analysis can be interpreted to mean that the flooding is largely due to the inability of surface runoff to flow off the land. Figure 14: Digitized map of the study area overlaid on the classified slope map 3.1.4 ASPECT ANALYSIS The aspect map of the study area was also generated by running a script in the ILWIS command pane. The aspect map was generated both in degrees and in percentage. The aspect map was also classified into nine logical aspect classes based on the ILWIS guide (east, north, southeast, south, southwest, etc). The map was classified into 8 different directions at 45 0 intervals. Taking into account the steepness of the slopes in the region, aspect (Slope face) could have important information on the causes of flooding in a locality. 88

From Table (3); with surface runoff on the terrain, a total area of 28.61 Hectares containing the surface runoff will direct the water to flow eastwards. This is the direction in which the maximum volume of the runoff will flow. 33353 pixels define this area. 23.47 hectares defined by 58687 pixels will enable surface runoff to flow westwards. This account for 16.38% of the total land area, all surface runoff in areas defined by the pixel values shown above will flow westwards. 14.8% and 13.9% of the total surface area will drain surface water southwards and south-westwards respectively. 6.2% (8.89 Hectares) of the total area will drain water north-westwards. Therefore, every flow that is south-westwards, southwards, north-westwards, north-eastwards and southeastwards will eventually flow into channels flowing westwards after being collected into catchment areas and will eventually drain into the stream. The direction in which the stream will flow will aid these channels to discharge into it. A total of 358383 pixels define the total area of 143.35 hectares defining the terrain aspect. Thus, all discharge in these directions will flow towards the stream into which all the excess surface water will drain. Table 3: Statistics for Classified Aspect Map Data ASPECT CLASS North North East East South East South South West West North West North 2 No. of pixels 33353 33262 71529 35500 53156 49856 58687 22236 804 Area(m2) 133412 133048 286116 142000 212624 199424 234748 88944 3216 % Area 9.31 9.28 19.96 9.91 14.83 13.91 16.38 6.20 0.22 4.0 CONCLUSION AND R ECOMMENDATIONS 4.1 CONCLUSION The devastating impacts of floods on local community residents around Basawa barracks has been an enduring concern for these residents. Flooding is the major hazard recurring in the locality and this study has shown that this flooding is largely due to poor drainage channel and the flatness of slope in the residential quarters of the study area. The advancement in computer-aided and spacebased technology such as Geographic Information Systems (GIS) and remote sensing has proved very useful in studying the causes of floods and flood-mapping by performing digital terrain 89

analysis on the DEM of flood-prone areas and developing measures that can be useful to the local communities as well. This explains what was carried out during the course of this study. This study has demonstrated the capabilities of the Geographic and Information System (GIS) software: ILWIS to be used for the extraction of these terrain parameters and the analysis of the terrain. There is a need for a proper drainage in the study area (Basawa barracks and its environs) to curb recurring flooding. The aspect and slope maps of this area extracted from the DEM of the same area can aid in this regard. From the analysis carried out on the DEM using the terrain parameters, it was realized that the flooding always experienced in the area during the raining season is largely due to the flatness of most part of the terrain especially the residential area. The result of the analysis shows that 61% of the land area is relatively flat, which is considered the reason for the flooding as surface runoff cannot be accurately discharged because these flat areas are surrounded by rising terrain which prevents the water from draining out. 4.2 RECOMMENDATIONS Based on the analysis carried out on the terrain, the following recommendations are made: 1. Flooding is a natural phenomenon and its complete control requires concise and effective efforts. However, the magnitude of flooding and its impact can be reduced to a certain extent through development and effective implementation of land-use zoning guidelines and building codes and standards. Building codes and guidelines when strictly adhered to can reduce the risk of flooding. 2. Based on the analysis made on the DEM of the study area in the course of this study, further studies should be carried out to see how excess surface water which is drained can be harnessed for other uses such as irrigation in the same locality as there are farmlands in the surrounding, especially close to the stream. 3. Local residents have realized the importance of a flood preparedness plan incorporating components of watershed conservation and drainage management through proper land-use guidelines, income-generating activities, early warning system, and creation of flood 90

awareness. Therefore government and local authorities should devise and implement such programmes that will increase the people s awareness and proper dissemination of information should be established. 4. Environmental planning should incorporate the use of DEMs for housing layouts to mitigate against disaster such as flood. The accurate hydrological analysis of DEM will aid proper planning so as to avoid flood-risk areas for residential settlement. Terrain parameters such as slope, aspect, flow direction etc are of great use in this respect. 5. The capability of residents to respond to hazards and their resilience against them is poor in terms of their physical assets, economic and financial conditions, human development, and the technical capability of infrastructure. However, these residents are willing to participate in and contribute to flood-hazard mitigation and management if given the chance. Government and local authorities should make efforts to tap this sentiment through developing and strengthening local community-based sensitizing and campaign institutions. REFERENCES [1] O. A. Isioye, Towards the Development of a National Geo-Database Framework for Managing Climate Related Risks in Nigeria, A paper presented at AvH Kolleg International Conference on climate change, at the University of Ibadan, Nigeria, 11-15 October 2011. [2] Z. Li, Q. Zhu and C. Gold, Digital Terrain Modeling: Principles and methodology, CRC Press: Boca Raton, FL, 323pp, 2005 [3] United States Geological Survey (USGS). (2001). Digital Elevation Models: USGS DEM Model Information, http://rmmcweb.cr.usgs.gov/elevation/, March 15, 2010. [4] B. Pradhan, Flood Susceptibility Mapping and Risk Area Delineation Using Logistic Regression, GIS and Remote Sensing, http://www.spatialhydology.com/journal/paperfall2009, August 13, 2010. [5] G. Luis and L. B. Rafael, A Distributed Model for Real-Time Flood forecasting using Digital Elevation Models, Journal of Hydrology, vol.167, issues 1-4, pp.279-306, 1993. [6] B. Gumbo, N. Munyamba, G. Thole and H. G. Hubert, Coupling of Digital Elevation Model and Rainfall-Runoff Model in Storm Drainage Network Design, Paper presented at 2nd WARFSA/WaterNet Symposium: Integrated Water Resources Management: Theory, Practice, Cases, Cape Town. pp 4-11, 2001. 91

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