INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 2, No 3, 2012

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1 INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 2, No 3, 2012 Copyright 2010 All rights reserved Integrated Publishing services Research article ISSN Computation of watershed parameters using Geoinformatics Chandra Bose A.S 1, Viswanadh G.K 2, Giridhar M.V.S.S 3 1- Lecturer, Dept. of Civil Engineering, Govt. Polytechnic, Warangal , India, 2- Professor of Civil Engg and Director of Evaluation, J.N.T.U.H, Hyderabad , India 3- Asst Prof in Center for Water Resources and Addl. Controller of Exams, J N T U Hyderabad, India smilesubhashbose@yahoo.com ABSTRACT The primary objective of this paper is to evaluate watershed parameters using remote sensing and geographic information systems for Kadam watershed which is a part of Middle Godavari (G-5) sub basin of Godavari river basin, India. Preparation of maps such as Contour map, Digital Elevation Model (DEM), Flow direction map, Study area boundary map, Slope map, Aspect map, View shed map, Thiessen polygon network map Soil map and Mandal administrative boundary map have been prepared in GIS environment in order to compute watershed parameters which are useful for various applications of watershed hydrology. The maximum and minimum elevations in the study area from the contour map were found to be 350 m and 160 m respectively. Slope map indicated mild to steep slopes varying from 0 to 28 percent for the study area. The areas of Thiessen polygons namely Bazarhatnoor, Boath, Ichoda, Indervelly, Kadam, Khanapur, Neredigonda and Utnoor have been found to be , , , , , , and sq km respectively. The areas of the soil units viz., 19, 59, 60, 61, 62, 63, 66 and 68 were found to be 15.38, , 17.27, , , , and sq km respectively. Key words: Remote Sensing, GIS, Thiessen polygon, DEM. 1. Introduction Water is indispensable for life and more so for man. Water is a precious natural resource and at the same time complex to manage on account of its dynamic behaviour. Global water resources are finite and are greatly diversified in space and time. Scientific approach is therefore essential to address the issues and challenges for sustainable development of water resources. In this context, watershed approach has proved its efficacy and Watersheds have been considered to be the ideal, logical and scientific hydrologic units for effective and efficient management of Water resources. The watershed based resources management is therefore necessary to plan and conserve the available natural resources. Watershed is the area draining the rainwater into a stream. It can also be explained as a delineated area from which the runoff drains through a common point in the drainage system (Murthy, 2000). Geo-informatics is the discipline of gathering, storing, processing, and delivering of geographic information, or spatially referenced information which includes Geographical Information System, Global Positing System, and Remote Sensing. The Remote sensing and Geographical Information System applications are widely used for thematic mapping of natural resources for planning, development, management, monitoring and also in environmental studies. The integration of remote sensing and conventional data results in decision support system for effective management of land and water resources in a watershed. The benefits Submitted on October 2011 published on February

2 associated with the use of GIS in watershed and hydrologic analysis include the improved accuracy, less duplication, easier map storage, more flexibility, ease of data sharing, timeliness, greater efficiency and higher product complexity (Ogden et al., 2000). Nayak and Jaiswal (2003) observed that the conventional hydrologic data are inadequate for the purpose of design and operation of water resources systems. In such cases remote sensing data are of great use for the estimation of relevant hydrological data. RS data can serve as model input for the determination of river catchment characteristics, such as land use /land cover, geomorphology, slope, drainage etc. GIS offers the potential to increase the degree of definition of spatial sub units, in number and in descriptive detail. Vijith (2006) calculated the mean stream length as characteristic related to the drainage network and its associated surfaces for two major upland sub watersheds of Meenachil River in Kerala. The primary objective of this paper is to evaluate watershed parameters using remote sensing and geographic information systems for Kadam watershed which is a part of Middle Godavari (G-5) sub basin of Godavari river basin, India. Preparation of maps such as Contour map, Digital Elevation Model (DEM), Flow direction map, Study area boundary map, Slope map, Aspect map, View shed map, Thiessen polygon network map Soil map and Mandal administrative boundary map have been prepared in GIS environment in order to compute watershed parameters which are useful for various applications of watershed hydrology. 2. Study Area The area selected for present study is Kadam watershed of Middle Godavari (G5) sub basin of Godavari River Basin. The Godavari basin is situated between East longitudes ' to ' and North latitudes ' to ' in the Deccan plateau covering large areas in the States of Maharashtra, Madhya Pradesh, Chattisgarh, Orissa, Karnataka and Andhra Pradesh. The Godavari basin extends over an area of 3, 13, 812 sq.km which is nearly 10% of the total geographical area of the country. Godavari catchment was divided in to eight sub basins. The study area is a part of G-5 sub basin i.e. Middle Godavari sub basin of River Godavari which lies between latitudes and North and longitudes and East. The Middle Godavari sub basin has a catchment area of km 2, which constitutes 11.38% of the total basin area and entirely lies in the State of Andhra Pradesh. In the present study, Middle Godavari sub basin has been considered up to Kadam reservoir only which lies between latitudes and North and longitudes and East. The areal extent of the study area is 2617 km 2, which constitutes 7.4% of the sub basin area. The watershed spreads over twelve mandals viz., Mamda, Kadam, Neredigonda, Jainnor, Boath, Ichchoda, Narnoor, Utnoor, Indervelly, Bazarhatnoor and Sirpur all of which fall under Adilabad district. The climate in the study area is semi arid with an average annual rainfall of 765mm, approximately 50% of which occurs during June. The minimum and maximum temperatures range from 1.8 to 31.5 o C and 7.4 to 43.6 o C respectively. Daily mean relative humidity ranges from 10 to 100%. The highest wind speed 136 km/hr. Agriculture is the main occupation of the people in the sub-basin. Paddy and Red Gram are cultivated in both the seasons. The principal crops that are grown in the region are Paddy, Red gram, Groundnut, Jowar, Ragi, Pulses, Chillies etc. Socio economic Information in the sub-basin has been collected from the Bureau of Economics & Statistics (BES), Khairathabad, Hyderabad, A.P. 3. Data used Daily rainfall data has been collected for a period of 1996 to 2006 from Bureau of Statistics and Economics (BES), Hyderabad. Daily runoff data has also been collected for a period of 1996 to 2006 from Central Water Commission (CWC), Chirag Ali lane, Hyderabad. 771

3 Information regarding soils was extracted from the soil map prepared at a scale of 1:5, 00,000 and supplied by National Bureau of Soil Survey and Land Use, Nagpur. The topographic maps used namely 56 I3, I6, I7, I8, I10, I11, I12, I14, I15 and I16 on a scale of 1:50,000 were collected from Survey of India (SOI), Uppal, Hyderabad. Spatial data in the form of satellite imageries were procured from National Remote Sensing Agency (NRSA). These satellite imageries for both Kharif and Rabi seasons for two years pertain to Indian Remote Sensing Satellite (IRS) P6, Linear Imaging and Self Scanning Sensor (LISS III) with a resolution of 23.5m. 3.1 Methodology In the present study 3D-Analyst tool has been used in Arc GIS 9.2 version to prepare slope map, aspect map, contour map and hillshade map from DEM and the detailed procedure was explained in the following subsections. Arc GIS 3D-Analyst is an ArcGIS extension that provides advanced tools for three dimensional visualization, analysis and surface generation. A better spatial understanding of vector or raster data can use ArcGIS 3D Analyst. Available surface analysis tools include hill shade, slope, aspect, curvature, cut/fill, view shed, line of sight, surface length, surface spot, surface volume, interpolate shape, reclass, slice. Preparation of maps such as Contour map, Digital Elevation Model (DEM), Flow direction map, Study area boundary map, Slope map, Aspect map, View shed map, Thiessen polygon network map Soil map and Mandal administrative boundary map have been discussed. 3.2 Contour map Contours are generated with the help of Survey of India top sheets by digitization. Contour analysis depicts the Topographic undulations. This analysis is used by the survivors to know the steam slope and direction. Contour analysis also depicts weather and oceanic conditions which portray the actual environmental situation. Contours are polylines that connect points of equal value of elevation. The elevation points were prepared from toposheets 56-I 3, I 6, I 7, I 8, I 10, I 11, I 12, I 14, I 15 & I 16 on a scale of 1:50,000 collected from Survey of India (SOI), Hyderabad. The collected toposheets were scanned and registered with tic points and rectified. Further, the rectified maps were projected. All individual projected maps were finally merged as a single layer. The contours were digitized with an interval of 20 m. The contour attribute table contains an elevation attribute for each contour polylines. 3.3 Digital Elevation Models (DEM) A DEM is a raster representation of a continuous surface, usually referring to the surface of the earth. The DEM is used to refer specifically to a regular grid of spot heights. It is the simplest and most common form of digital representation of topography. 3.4 Flow direction map One of the key requirements in deriving hydrologic characteristics of a watershed is the ability to determine the direction of flow from every cell in the raster. This is done with the flow direction function in Arc Map of Arc GIS 9.1 This function takes a surface as input and outputs a raster showing the direction of flow out of each cell. There are eight valid output directions relating to the eight adjacent cells into which flow could travel. The direction of flow is determined by finding the direction of steepest descent or maximum drop from each cell. When a direction of steepest descent is found, the output cell is coded with the value representing that direction. 772

4 3.5 Delineation of sub basin boundary Computation of watershed parameters using Geoinformatics A watershed is the upslope area contributing flow to a given location. Such an area may also be referred to as a basin/catchment/contributing area. A sub basin is simply part of a hierarchy, implying that a given sub basin is part of a larger watershed i.e., a basin. G-5 sub basin was delineated from DEM by computing the flow direction and using it in the watershed function of hydrology tools of Arc Map module in Arc GIS 9.1. The watershed function uses a raster of flow direction to determine contributing area. Flow accumulation threshold or the pour points were used to delineate watersheds. When the threshold is used to define a watershed, the pour points for the watershed will be the junctions of a stream network derived from flow accumulation. Therefore, a flow accumulation raster was specified as well as the minimum number of cells that constitute a stream. When a feature dataset is used to define a watershed, the features identify the pour points. 3.6 Slope map Slope of an area expressed in two ways one is in percentage and another one is in degrees. The slope was divided in to seven classes according to All India Soil and Land Use Survey (AIS & LUS). DEM was converted in to TIN in 3D_Analyst tool. That TIN is used as input for slope map preparation. In the present study slope is calculated in percentage.the Slope function in Arc GIS 9.2 calculates the maximum rate of change between each cell and its neighbors. Every cell in the output raster has a slope value. The lower the slope value indicates the terrain is flatter and the higher the slope value, the steeper the terrain. The output slope raster can be calculated either in percent of slope or degree of slope. 3.7 Aspect map Aspect is the steepest down slope direction from each cell to its neighbors. It can be thought of as direction of slope or the compass direction at hill faces.aspect map is prepared from DEM. Aspect map is prepared in GIS environment. In GIS, 3D_Analyst, surface analysis tool is used for making of Aspect map. Aspect is the direction of the maximum rate of change in the z- value from each cell in a raster surface. Aspect is expressed in positive degrees from 0 to 359.9, measured clockwise from the north. The aspects indicating direction can also be depicted and is important in slope categories where slope is exceeding more than 15%. Cells in the input raster of zero slope are assigned an aspect of -1. If the center cell in the immediate neighborhood (3 x 3 window) is No Data, the output is No Data. If any neighborhood cells are No Data, they are assigned the value of center cell; then the aspect is computed. According to degree of slope the direction of slope categorized into nine classes. Aspect identifies the steepest down slope direction from each cell to its neighbors. The data obtained from the aspect map is used in the fully distributed modeling. 3.8 View shed map View shed identifies the cells in an input raster that can be viewed from one or more observation points. Each cell in the output raster receives a value that indicates how many observer points can be viewed from each location. If one observer point is available, each cell that can see that observer point is given a value of 1. All cells that cannot see the observer point are given a value of Thiessen polygon Map 773

5 The Thiessen tool can proportionally divide and distribute point coverage into regions known as Thiessen polygon network in GIS environment. The Thiessen polygons were constructed as follows: Points of rain gauge station were located in the toposheets, For these points Triangulated Irregular Network (TIN) has been developed. The perpendicular bisectors for each triangle edge are generated, forming the edges of the Thiessen polygons. The locations at which the bisectors intersect determine the locations of the Thiessen polygon vertices. Thiessen polygons are built to generate polygon topology. The locations of the points are used as the label points for the Thiessen polygons Extraction of digitized soil map The soil map was collected from National Bureau of Soil Survey and Land Use, Nagpur which was prepared on a scale of 1:5,00,000. The collected soil maps were scanned and registered with tic points and rectified. Further, the rectified maps were projected. All individual projected maps were finally merged as a single layer. Later, the delineated study area map of sub basin was overlaid on projected soil map and finally, soil map pertaining to the study area was thus extracted in GIS environment. Boundaries of different soil textures were digitized in ARC/INFO and the polygons representing soil classes were assigned different colors for reorganization of hydrologic soil groups. Now, the already prepared Thiessen polygon coverage was overlaid on the extracted soil map of the study area to bring out sub areas in the soil map and to classify soil types in the study area of the Middle Godavari sub basin in GIS environment Mandal administrative map The study area falls entirely in Adilabad district of Andhra Pradesh, India. Mandal boundaries in Adilabad district were digitized, registered, rectified, projected and also merged. 4. Results and Discussion Watershed parameters corresponding to the study area were evaluated using Arc GIS 9.2. Kadam watershed was delineated based on the contour map prepared in GIS environment. Preparation of Digital Elevation Model (DEM) map, slope map, aspect map, Hill shade map, View shed map, Flow direction map, Flow accumulation map and soil map was carried out in GIS environment. The contour map was prepared using Arc Map of Arc GIS 9.1 and shown in Figure 1. The maximum and minimum elevations in the study area from the contour map were found to be 350 m and 160 m respectively. The Digital Elevation model for the study area was generated from the contour map using Surface Analysis tool of Spatial Analyst in Arc Map as shown in Figure 2. Flow direction raster map was prepared from ARC Map of Arc GIS 9.1 in Hydrology tools as shown in Figure 3. The study area boundary has been delineated in GIS environment as presented in Figure 4. The total area under the study is sq.km. The perimeter of the study area boundary has been found to be km. The Figure 5 shows the slope of the terrain in the Kaddam watershed. Slope map indicated mild to steep slopes varying from 0 to 28 percent for the study area. In present study, aspect map is prepared from DEM and presented in Figure 6. View shed map has been developed from DEM using Arc Map of Arc GIS 9.1 in 3D analyst as shown in Figure 7. The view shed map can be used for flood mapping of the study area. 774

6 Computation of watershed parameters using Geoinformatics Figure 1: Contour map 775

7 Figure 2: DEM map 776

8 Computation of watershed parameters using Geoinformatics Figure 3: Flow direction Map 777

9 Figure 4: Study area boundary map 778

10 Figure 5: Slope map 779

11 Figure 6: Aspect map 780

12 Figure 7: Viewshed map 781

13 Figure 8: Thiessen Polygon map Figure 9: Soil map 782

14 Figure 10: Mandal Administrative Boundary Map Table 1: Areas of Thiessen polygons of the study area S.No Thiessen polygon Area in sq Kms % in area 1 Bazarhatnoor Boath Ichoda Indervelly Kadam Khanapur Neredigonda Utnoor Total Sl No Map Unit Description Table 2: Soil types description in the study area Fine Mixed typic haplustalfs Clayey skeletal, Mixed (paralithic) Ustorthents. Clayey skeletal, Mixed (paralithic) Ustorthents. Loamy Mixed (lithic) Ustorthents. Drainage Moderately deep, well drained clayey soils with high AWC on Gently sloping lands, Moderately eroded Shallow well drained,gravelly clay soils with Low AWC on Gently sloping upper side slopes with Gravelly surface, severely eroded Shallow well drained,gravelly clay soils with Low AWC on Gently sloping summits with stony surface, severely eroded Very Shallow well drained Loamy soils with Low AWC on Moderately sloping lower side slopes with gravelly surface, severely eroded 783

15 Clayey Mixed (lithic) Ustorthents. Clayey Monmorillonitic (lithic) Ustorthents. Fine, Monmorillonitic (Calcareous) typic haplusterts Very Fine, Monmorillonitic (Calcareous) typic haplusterts Very Shallow well drained clayey soils with very Low AWC on Gently sloping upper side slopes with gravelly surface, severely eroded Shallow well drained clayey soils with Low AWC on moderately sloping summits with stony surface, severely eroded Deep, Moderately well Drained,Cracking clay Calcareous soils with very high AWC, On Gently sloping Valleys, Salinity Patches Very Deep, moderately Well Drained,Cracking clay Calcareous soils with very high AWC, On Very Gently sloping Valleys, Salinity Patches Table 3: Areas of Different soil types of the study area Sl.No Soil unit Area in sq kms % area Reservoir Total % Table 4: Watershed drainage parameters of the study area Sl. No Parameters Values 1 Catchment area of the Basin 2651 sq.km 2 Maximum Length of the Basin km 3 Perimeter of the Basin km 4 Max. Length of the stream in the Basin km 5 Total length of the stream segments in the Basin km 6 Total number of stream segments in the basin Mean length of the streams in the Basin km 8 Elevation of the basin at the outlet 160 m 9 Elevation of the Basin at highest point 660 m The Thiessen polygon network coverage was prepared for eight rain gauge stations viz., Bazarhatnoor, Boath, Ichoda, Indervelly, Kadam, Khanapur, Neredigonda and Utnoor located in the study area as shown in Figure 8. Area of each Thiessen Polygon has been calculated 784

16 from the attribute table of Thiessen Polygon Network map and presented in Table 1. The areas of Thiessen polygons namely Bazarhatnoor, Boath, Ichoda, Indervelly, Kadam, Khanapur, Neredigonda and Utnoor have been found to be , , , , , , and sq km respectively. The percentage of area of coverage of the study area for these polygon areas were calculated and found to be 9.81, 13.05, 10.66, 11.45, 8.08, 16.09, and 19.25respectively. Maximum Thiessen polygon area of sq km is observed for Utnoor Thiessen polygon and a minimum Thiessen polygon area of sq km is observed for Kadam Thiessen polygon. In semi distributed conceptual rainfall-runoff modeling, these Thiessen polygon network areas may be treated as sub areas forming the basis for semi distributed approach and accordingly runoff can be calculated. Soil map has been prepared in GIS environment. From the soil map, different soil units viz.,19, 59, 60, 61, 62, 63, 66 and 68 covered the study area and their description is narrated in Table 2. The areas of these corresponding units have been calculated and tabulated in Table 3. The areas of the soil units viz., 19, 59, 60, 61, 62, 63, 66 and 68 were found to be 15.38, , 17.27, , , , and sq km respectively. The soil unit 63 indicating the type i.e., Clayey Monmorillonitic (lithic) Ustorthents is found to be predominant in the study area covering % of the study area. Figure 9 depicts the classification of soils in each sub area. The study area boundary was overlaid on merged Mandal map to extract Mandal administrative boundaries in the study area as shown in Figure 10. Watershed drainage parameters of the study area have been presented in Table Conclusions All the hydrological parameters which are spatially and temporally variable were found to be more accurately estimated through Geo-informatics. The study clearly demonstrated that interactive integration of spatial and non-spatial data in GIS environment provides a powerful tool for various applications in watershed hydrology. Manual computation in order to compute these watershed parameters is not only tedious and error prone but also time consuming. The computation and analysis of the parameters of the watershed indicate the greater efficiency and accuracy of using GIS compared to manual methods. Present study demonstrated that GIS is found to be flexible and is relatively easy to apply on large study areas enabling gathering of all data and information in a common data base for spatial analysis and watershed characterization. Wide scope of applying Geoinformatics has been presented in the present work. It is clear from the analysis that Geoinformatics aids in obtaining useful information about the watershed in a short time and in an economic way. Extracting watershed parameters at micro level using RS and GIS can augment the conventional methods to a great extent for hydrological studies. 6. References 1. Jenson, S.K., (1991), Applications of Hydrologic Information Automatically Extracted from Digital Elevation Models. Published in: Terrain Analysis and Distributed Modeling in Hydrology, edited by K.J. Beven and I.D. Moore. John Wiley and Sons, Kirkby, M.J., (1993), Network Hydrology and Geomorphology. Published in: Channel Network Hydrology, edited by K. Beven and M.J. Kirkby. John Wiley and Sons. 3. Maidment, D.R., (1996), GIS and Hydrologic Modeling an Assessment of Progress. 785

17 4. Murthy, J.V.S., (2000), A Text book of Watershed management in India, Wiley Eastern Limited. 5. Nayak. T.R., and Jaiswal. R.K., (2003), Rainfall-runoff modeling using satellite data and GIS for Bedas river in Madya Pradesh, Indian Institute of Engineers (India) Journal, 84, May, pp Ogden, F.L., Garbrecht, J., DeBarry, P.A., and Johnson, L.E., (2001) GIS and distributed watershed models-ii: Modules, Interfaces and Models. J. Hydrologic Engineering, ACSE, 6(6), pp Vijith H and Sathesh R., (2006), GIS based morphometric analysis of two major upland watersheds of Meenachil River in Kerala. 786

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