INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 6, No 1, 2015 Copyright by the authors - Licensee IPA- Under Creative Commons license 3.0 Research article ISSN 0976 4380 Sustainable watershed development of the Bandu village (India) watershed using advance geospatial techniques: A case study documenting the importance of Remote Sensing and GIS in developing nations Abhay Prakash 1, Krishnendu Banerjee 2, Bindeshwer Puran 3 1-Bachelor of Technology (2014), Civil Engineering, KIIT University Graduate Trainee at Jharkhand Space Applications Centre (JSAC) 2-B.A. (Hons) (2008), Geography, Barddawan University, Msc. (2010), Remote Sensing and GIS, Vidyasagar University Junior Research Fellow (JRF), Jharkhand Space Applications Centre (JSAC) 3- Project Scientist, Jharkhand Space Applications Centre (JSAC) abhayprakash1991@gmail.com ABSTRACT India being a developing nation lacks the presence of an effective system for the built environment. There is inefficiency in the resource management sector and lack of proper planning has resulted in misuse of resources on a very large scale. In a developing nation like India, the major constraint that had hindered the sustainable usage of resources was the unavailability of state of the art facilities and spatial data and the subsequent processing tools. With the expansion and growth of the nation in the industrial and research front, emphasis is being laid on utilizing resources in an efficient and orderly way and this journal elucidates the significance of spatial data and data processing tools to help create a sustainable built environment. The study of water resources at the watershed scale is widely adopted as an approach to manage, assess and simulate these important natural resources. Watershed studies conducted using a GIS platform have demonstrated that the spatial analysis capabilities of GIS hold the key to improved watershed modeling techniques. The analytical muscle of GIS, combined with readily available digital elevation data, can be used to automate the watershed modeling process and provide a visual representation of the watershed s response to existing conditions and proposed improvement scenarios. In this context the objective of the study is to document the role of GIS and Remote Sensing for the development of the Bandu Watershed, located in Eastern India, in the Paschimi Singhbhum District in the state of Jharkhand. To do so, a merged image from CARTOSAT-1 and LIS-4 Sensor (obtained from the directory at the Jharkhand Space Applications Centre, Government of India) was digitized using ArcGIS and a digital elevation model (DEM) was prepared which gave us the idea of the slope of the region. The subsequent drainage pattern was then chalked out and the Geological Planning Map or the final map was prepared integrating results from all the maps. Keywords: Sustainable watershed development, cartosat-1, lis-4 sensor, DEM, Bandu watershed. 1. Introduction Water is one of the most important form of natural resource. The fact that more than three quarters of the earth s surface is water elucidates its significance to humankind. Therefore, a thorough understanding of it is quintessential for us to enable us to use it in a sustainable way to not only meet the ever expansive resource needs of the present generation but also the future. With the advancement in spatial data acquisition and processing, the task of Submitted on August 2015 published on August 2015 35
harnessing this form of resource has become easier and the subsequent solutions that are developed are more accurate and precise and therefore more efficient in the long run. Watershed development refers to the conservation, regeneration and the judicious use of all the resources - natural (land, water, plants), animals and human - within a particular watershed. Watershed management tries to bring about the best possible balance in the environment between natural resources on the one side, and human and other living beings on the other. Many models were developed for watershed hydrology but the availability of temporal and spatial data was the main constraint that hindered the implementation of these models especially in developing countries. However, the development of Remote Sensing techniques and Geographic Information System (GIS) capabilities has encouraged and improved the expansion use of these models worldwide. In fact, India is one such country which shows that a big evolution in watershed modeling will be made as a result of advances in remote sensing data availability. The specific objective and purpose of modeling Bandu watershed, located in the Eastern region of India, is to set up the adapted model in order to simulate the functioning of the entire basin and therefore predict its response to phenomena and risks it confronts such as erosion, inundations, drought, pollution, etc. To do so, the 3-D Surfacing tool was exploited to prepare the Digital Elevation Model and subsequently a slope map of the region was generated. The Hydrology tool was deemed suitable and was preferred for this case study because it contained many useful components and functions simulating the watershed processes. Furthermore, its efficiency, compatibility and reliability was confirmed in several regions around the world and this was an opportunity to check its functionality in a developing nation like India. DEM has been tested and used in many regions of Eastern India and also in the Singhbhum District but very few studies were conducted for watershed development. As a matter of fact, in the Eastern region, DEM was never tested or used in large scale basins. Therefore, this study aims to test and evaluate the usefulness and the performance of DEM in the hydrological functioning of large scale basins in the Eastern Zone through the application of this tool to the Bandu Watershed. 2. Description of the study area Case Study of the Bandu Village Area: (Watershed Development- scene in India): Bandu is a small village located in Gudri block of Paschimi Singhbum district, Jharkhand (Highest Extension Top- 22 39' 6.17'' N to 22 41' 45.21'' N and 85 5' 59.24'' E to 85 9' 6.75'' E ) with total 227 families residing. The year could be divided into three major seasons; the winter lasting from November to February, the summer from March to May, and the rainy season from June-October. The westerly winds prevail during the summer seasons. On account of the barrier of hills in the southeast, the atmosphere generally remains dry. The Rainfall is the highest in July and August. The annual average rainfall in the district is about 1422 mm. Monsoon generally breaks in the second week of June. December-January are the coldest months while April-May are the hottest. The Bandu village has a population of 1268 of which 656 are males and 612 are females as per the population census 2011. The livelihood of the population depends upon agriculture and farming which is similar to most of the village districts of India. Of the 698 workers engaged in main work, 660 were cultivators while 13 were agricultural labourer, which illustrates the importance of agriculture in this region, and the need for a sustainable watershed system. The role of Watershed Development in such places is of utmost importance for the families residing in these regions and also for the nation as a major portion of the country s GDP is agriculture based. Government of India is taking several measures to enhance the present system and develop more sustainable solutions for the large of number of regions where such a system does not exists. It is also 36
important to note that such a system will help such regions to develop and not only support their living but to add to the economy of the nation. 3. Methodology Figure 1: Map situation of the Bandu Village and the Bandu watershed 3.1 Land use/ land cover map A merged image of Cartosat-1 and LIS 4 Sensor was digitized with the help of ArcGIS. Different layers were created and digitized which included: 1) Roads 2) Rivers 3) Contours 4) Settlement 5) Wetland 6) Scrubland 7) Mixed Scrub and Wetland 8) Fellow Land 9) Barren Land 10) Agricultural field 11) Forests 3.2 Digital elevation model (DEM) preparation and slope map preparation The contour values were fed while digitizing the contours. A Digital Elevation Model (See Fig.3) was created using the Surfacing tool (3D Surfacing) in ERDAS. The high elevation zones include the Northern, North-Western and Western areas. The South- Eastern zone has a high elevation which falls down acutely as we move towards the Eastern region where the elevation is about 100 meters. 37
Figure 2: Land use/ land cover map The slope map prepared is depicted in Figure4. The slope ranges from 0 degrees (the 'White' areas depicting the flatness of the region having 0 degree slope) to 88 degrees. The Slope Map gives us the idea of the Drainage Basin or the Drainage Patterns subsequently helping us in having a better understanding of the Bandu Watershed. Using the Hydrology Tool from the Arc Toolbox in ArcGIS, following steps were taken: 3.3 Fill sinks This function was used to fill the sinks in a grid. If cells with higher elevation surround a cell, the water is trapped in that cell and cannot flow. The Fill Sinks function was used to modify the elevation value to eliminate these problems. Figure 3: Select Terrain Preprocessing Fill Sinks The input for DEM 'AgreeDEM' was confirmed and the output 'Hydro DEM layer' was created, named by default 'Fil' and upon pressing OK, the 'Fil' layer was added to the map. 38
Figure 4: Input layer 3.4 Flow direction This function was used to compute the flow direction for a given grid. The values in the cells of the flow direction grid indicated the direction of the steepest descent from that cell. Figure 5: Select terrain preprocessing flow direction. The input for Hydro DEM was confirmed as 'Fil' and upon pressing OK, the output 'Flow Direction Grid', named by default 'Fdr' was successfully added to the map. 3.5 Flow accumulation Figure 6: Third hydro input This function was used to compute the flow accumulation grid that contains the accumulated number of cells upstream of a cell, for each cell in the input grid. The input of the Flow Direction Grid was confirmed as 'Fdr' and upon pressing OK, the output 'Flow Accumulation Grid' having a default name of 'Fac' was successfully added to the map. Figure 7: Select terrain preprocessing flow accumulation. 39
Figure 8: The input of the Flow Direction Grid The BanduWatershedBoundary.shp shapefile was added to the map and the symbology of Fac was adjusted. Spatial Analyst was used to generate contours of the original DEM so that flow accumulation could be examined relative to the terrain as depicted by contours. 3.6 Stream definition This function was used to compute a stream grid which contains a value of "1" for all the cells in the input flow accumulation grid that have a value greater than the given threshold. All other cells in the Stream Grid contain no data. Select Terrain Preprocessing Stream Definition. The input for the Flow Accumulation Grid was confirmed as 'Fac'. The output is the Stream Grid 'Str' which upon completion is added to the map. 4. Results and discussion Figure 3: DEM Image Depending upon the climatic conditions of the Bandu Village Area as described under section 2, it was assumed that the seepage on either side of the river would be about 100 meters. Keeping this in mind, a River Buffer Map of 100 meters was sketched. 40
Figure 4: Slope Map Figure 5: River Buffer Map (Buffer Zone Width- 100 meters) 41
Figure 6: Maximum Influence Zones This gave us information regarding the maximum influence zones which can be seen in Figure6 which would be favorable for agricultural purposes. Also, integrating the river buffer map with the slope pattern of the region, the flow direction was identified. The Final Map or the Planning Map was created integrating all the parameters which can be seen in Figure7. 4. 1 Hydrologic interpretation from the digital elevation model (DEM) and slope map Definition of Flow Direction (Hydrologic): Water flows in the direction of the steepest Downhill gradient Definition of Flow Direction (GIS): The D8 Method (Greenlee DD, 1987) was used to determine the flow direction. In this method, every pixel is potentially surrounded by eight neighboring pixels. The slope in each of these eight directions may be calculated by taking the difference in elevation indicated by the DEM value at each of these eight neighboring locations and the value at the pixel being examined. This difference in elevation is then divided by the center-to-center distance between these pixels (this distance will be the cellsize in the cardinal directions and the cellsize 2 in each of the diagonal directions). The direction that yields the steepest downhill slope is the inferred direction of water flow. Determination of flow direction at every point throughout a landscape was very helpful as it helped us to infer the drainage areas, flow lengths, and delineate watersheds. 5. Conclusion The GIS-based watershed modeling process began with a digital representation of the ground surface topography, or a digital elevation model (DEM). Using GIS to analyze DEMs, watershed delineation and drainage patterns were prepared with limited manipulation. Through this watershed assessment, we were able to have a draft of the modeling framework 42
along with a fairly detailed knowledge of the drainage patterns and watershed delineation. This study, further showed the role of Remote Sensing and GIS to create, combine, generate and analyze the data for the preparation of a hydrological model of the Bandu Watershed region for sustainable mapping and exploitation of the resources. Acknowledgement Figure 7: Planning Map/Final Map The authors are grateful to the Jharkhand Space Applications Centre, Government of India for providing them with laboratory and satellite data of the study area. They are also thankful to the colleagues at the Jharkhand Space Applications Centre who have helped them at various stages with the preparation of the report and laboratory work. 6. References 1. Bijay Singh and Jimly Dowerah, (2010), Geospatial Mapping of Singhbhum Shear Zone (SSZ) with Respect to Mineral Prospecting, Journal of Geographic Information System, 2, pp 177-184. 2. Greenlee, D.D. (1987), Raster and Vector Processing for scanned linework. Photogrammetric Engineering and Remote Sensing, 53(10), pp 1383-1387 3. Jenson, S.K., and J.O. Domingue. (1988), Extracting Topographic Structure from Digital Elevation Data for Geographic Information System Analysis, Photogrammetric Engineering and Remote Sensing 54(11), pp 1593-1600. 4. Kumar Abhishek, Hydrological Modelling using TOPMODEL in Karso Watershed, https://www.iirs.gov.in/iirs/sites/default/files/studentthesis/kumar_abhishek.pdf 43
5. Singh VP and D. A. Woolhiser, (2002), Mathematical Modeling of Watershed Hydrology, Journal of Hydrologic Engineering, 7(4), pp 70-292. 6. Srinivasa S Vittala, S. Govindaiah, H. Honne Gowda, Digital Elevation Model (DEM) for identification of groundwater prospective zones, Journal of the Indian society of Remote Sensing, September 2006, 34(3), pp 319-324. 44