Morphometric characterization and hydrological assessments. of River Njoro watershed Using System for Automated

Transcription

1 Copyright by authors under Creative Commons License 3.0 Research article ISSN Morphometric characterization and hydrological assessments of River Njoro watershed Using System for Automated Geoscientific Analysis (SAGA) and Shuttle Radar Topographic Mission (SRTM) digital elevation Model GIS Officer, Gusii Water and Sanitation Company (GWASCO). Research Scholar and Part time Lecturer Department of Natural Resources, Egerton and Kisii University, Kenya Abstract: The growing demand for water from increasing human population and industrialization, along with increasing intensity of quality and quantity challenges as a result of rapid urbanization, call for scientific approaches to water resource management. Drainage basins, catchments and sub catchments are the hydrological units ideally suited for planning purposes focused on conserving land and water resources. For this study, Shuttle Radar Topographic Mission (SRTM) digital elevation data and System for Automated Geoscientific Analysis (SAGA) were used for morphometric analysis. The availability of remote sensing data and enabling GIS platform lend scope for understanding the morphometric properties of the catchment area and surface drainage characteristics of many river basins in different parts of the globe. The aim the study is to assess and understand the morphometric and Terrain characteristics of the Njoro river watershed through the analysis of the linear and the areal aspects. In stream ordering, Strahler s method which is the most commonly used method of stream ordering has been followed for the present study. The linear aspects considered for the study include stream order, stream number, stream length, bifurcation ratio and length ratio while areal aspects include catchment area, drainage density and stream frequency. From the analysis, the total length of River Njoro under the present study was 190 km. The total length of stream segments is maxima under first order streams and this length decreases as the stream order increases. It is also observed that there is a decrease in stream frequency as the stream order increases. It is also noted that, according to available literature, Njoro River catchment area has decreased from the widely quoted 300 Km 2 to approximately 250 Km 2. Key words: Morphometry, Drainage density, Stream orders, Geographic Information System 1. Introduction Water an essential commodity to mankind. Despite drinking purpose, it is an importance source for agricultural and industrial Sector. During the past few decades, the available resource is in decline. Kenya too is heading towards a fresh water crisis. Identification of potential zone ever remains a mystery. Hence geoscientists were adopting various techniques to target groundwater. Amongst high resolution satellite images are increasingly used in groundwater exploration because of their utility in identifying various ground features, which may serve as direct indicators of presence of ground water (Krishanmurthy, et al., 1996; Das et al., 1997; Ravindran and Jayaram, 1997; Pratap, et al., 2000; Sankar, *Corresponding author ( phestosano@gmail.com) Received on September 2015; Accepted on October 2015; Published on November, 2015

2 2002; Bahuguna, et al., 2003; Jagadeeswara Rao, et al., 2004; Ratnakar Dhakate, et al., 2008). Indirect analysis of some directly observable terrain features like geological structures, geomorphology and their hydrologic characteristics using remote sensing enables to target groundwater (Basudeo Rai, et al., 2005; Lokesha, et al., 2005; Samuel Corgne, et al., 2010 ).The geographic information system (GIS) has emerged as a powerful tool in integration and analysis of multi thematic layers in delineating ground water prospect and deficit zones (Carver, 1991; Hoogendoorn Goyal, et al., 1993; Saraf and Chaudhuray, 1998; Goyal, et al., 1999; Rokade, et al., 2007, Thushan Chandrasiri Ekneligoda and HerbertHenkel, 2010). In the present study using satellite data and collateral datasets various surface and subsurface features were interpreted. Based on their potentiality to groundwater, weights were assigned to individual thematic layers and ranks to individual features in each theme. By multiplying both, scores of each feature were derived. Finally using GIS, all the themes were integrated and classified into different classes of groundwater potential zones. 2. Objective The overall objective of the study was to analyze the drainage characteristics and extent of River Njoro watershed using System for Automated Geoscientific Analysis (SAGA) and Shuttle Radar Topographic Mission (SRTM) digital elevation data for better understanding, assessment and management of the Watershed. 3 Methodology and Results 3.1 Study Area River Njoro watershed is located in the rift valley province, Kenya. The watershed covers an area of approximately 300Km 2 at S, E. The river originates from the Eastern Escarpment of the Mau Forest Complex- one of the five major water towers in Kenya and it is about 50Km in length. Figure 1: Study Area 38

3 3.2 The data and tool used GIS and remote sensing techniques are useful tools for watershed analysis and management. Major advantages of Remote sensing and GIS techniques are its rapid access to latest spatial information over a large geographical area including inaccessible areas (Vibhu N. and Kavitha N. 2013), at a relatively economical cost with high degree of precision. For better and elaborate quantitative analysis and study of watershed, terrain data is needed. Digital Elevation Model (DEM) from the Shuttle Radar Topographic Mission (SRTM) of 90m resolution data was used. SRTM digital elevation data provided by The NASA, currently distributed free of charge by USGS, has been processed to fill data voids, and to facilitate its ease of use by a wide group of potential users. The SRTM data is available as 3 arc second (approx. 90m resolution) DEMs, with the reported vertical error to be less than 16m.The data is provided in an effort to promote the use of geospatial science and applications for sustainable development and resource conservation in the developing world System for Automated Geoscientific Analysis (SAGA) was used for this study. SAGA is an open-source digital image processing GIS program capable of processing images in different formats. Figure 2: Methodology 39

4 3.3 Linear aspect Stream order In quantitative analysis of watershed, Stream ordering is the first step as it expresses the hierarchical relationship between stream connectivity, their segments and the discharge arising from contributing catchments. According to Andy and Jessica (2008), Stream systems have been classified according to their relative position within a stream network in order to help us understand, discuss, and explore similarities and differences between them. Stream order is an important characteristic of stream systems because it can be related to drainage area and stream size (Andy W. and Jessica L. D., 2008). It is also important because it can be related to the expected ecological function of a stream system. There are different methods of stream classification, example, morphological. According to this system, the stream is identified by the average size of bed material (sand-bed, gravel-bed, bedrock) or by physical setting and land use (mountain stream, meadow stream, urban channel, etc.). Schumm s system is another classification method, where streams are classified into erosion, transport, and deposition, which was helpful in beginning to understand the sediment transport behavior of a stream. According to estimation of stream orders, 89 streams were identified under the 1 st order, 23 streams under 2 nd order, 5 streams under 3 rd order and 1 stream under 4 th order '0"E 35 55'0"E 36 0'0"E 36 5'0"E 0 20'0"S 0 20'0"S 0 25'0"S Ü 0 25'0"S 0 30'0"S Legend '0"S 0 35'0"S Km 0 35'0"S 35 50'0"E 35 55'0"E 36 0'0"E 36 5'0"E Figure 2: Stream Order Stream number (Nu) According to Kuldeep P. and Upasana P. (2011), the total of order wise stream segments is known as stream number. 40

5 Table 1: Stream number (Nu) 1 st Order 2 nd Order 3 rd Order 4 th Order 1024/ /23 245/5 323/ Stream Length ratio (R 1) The cumulative mean lengths of stream segments of each of the successive orders in a catchment tend closely to approximate a direct geometric series in which the first term is the mean length of streams of the first order (Nishant V. et al 2013; Horton 1945). Stream length Ratio (Rl) helps in identifying the geographical location of Hydro Electric P0wer stations (HEPs) and its calculated by the following formulae; (Rl) = Lu/Lu-1 (Rl) = Nu-1 / Nu Where (Rl) = stream length ratio, Nu = length of an order, and Nu-1 = length in the next higher order. Table 2: Length Ratio (R 1) Stream Length Ratio (R 1) Mean Stream Length Ratio 2 nd order/ 1 st order 3 rd order/ 2 nd order 4 th order/ 3 rd order Bifurcation Ratio (R b) According to Horton (1945), Bifurcation Ratio is the number of streams in a low order to the number of streams in the next high order, bifurcation means dividing in two, and is given by; Rb= Table 3: Bifurcation Ratio (R b) Bifurcation Ratio (R b) Mean Bifurcation Ratio (R b) 1 st order / 2 nd order 2 nd order / 3 rd order 3 rd order /4 th order/ The average Rb for Njoro river watershed system is approximately Bifurcation ratios normally range between 2 and 5 and tend to be larger for more elongated basin (Beaumont, 1975; Nancy D. et al. 1992). According to Strahler (1964), the geological structure does not distort the drainage pattern if the Bifurcation Ratio (Rb) values stand between 3.0 and 5.0 for a catchment. In our study area, these values stood to be 3.87 under 1 st and 2 nd order streams, 4.6 under 2 nd and 3 rd order, and 5 under 3 rd and 4 th order. 41

6 3.4 Aerial aspect Catchment area The catchment area is another important parameter like the length of the stream drainage. Schumm (1956) established an interesting relation between the total watershed areas and the total stream lengths, which are supported by the contributing areas. According to the present study, the catchment area covers approximately 250 square kilometer, indicating a reduction or shrinking of the Njoro watershed Drainage Density (D) This is a primary feature of any drainage basin, determined by dividing the total length of all stream channels in the basin by the area of the basin (Robert W. Christopherson 2011). Drainage density is inversely related to permeability of the terrain, and higher the drainage density the lesser the permeability of the terrain (Muthukrishnan et al 2013). The number and length of channels in a given area reflect the landscape s regional geology and topography. It is calculated; D = Lu /A, Where Lu = Total stream length of all orders, and A = Drainage Area (km) Table 4: Drainage Density (D) Total length of 1 st Order (Km) Total length of 2 nd Order (Km) Total length of 3 rd Order (Km) Total length of 4 th Order (Km) Total Stream Length (Km) where D = Lu /A, D = /200, D = Km/Km 2 The drainage density (D) of Njoro river catchment area is Km km/km 2 indicating high drainage density. The high drainage density indicates low permeable sub-soil and relatively poor or less vegetative cover and high relief (Nag, 1998). However, under the present case, the former is most prominent Stream frequency (Fs) Stream frequency is the number of stream segments per unit area (Horton, 1932; 1945), and it is calculated by the following formulae; (Fs) = Nu/A 42

7 Table 5: Stream frequency Fs Segments of 1 st Order 89 Segments of 2 nd Order 35 Segments of 3 rd Order 5 Segments of 4 th Order 1 Total Segments 130 where Fs = 130/200, Fs = The stream frequency value of Njoro River the catchment is 0.65streams/km 2. Stream frequency is directly related to drainage density. The direct relationship is due to rainfall, relief, and infiltration rate, initial resistivity of terrain to erosion and total drainage area of the basin (Nishant V. et al. 2013), the value of Fs indicates poor stream networks and high values indicate denser networks in the catchment area. 4. Conclusion The Overall result from the study in the analysis of watershed and morphometric parameters demonstrates that GIS/remote sensing based approach is more appropriate and efficient than the conventional methods in understanding morphometric parameters and their influence on soils, landforms and eroded land characteristics in a river catchment. Through the approach, it is possible to explore the relationship between the drainage morphometry and properties of landforms and the analysis of different morphometric parameters. Drainage density and stream frequency from the result are more useful criteria for the morphometric classification of drainage system and pattern in Njoro River catchment. Acknowledgement I would like to express my sincere thanks to the Dean Faculty of Environment and Resources Development, Dr. Gilbert Obwoyere and the Chairman of the Department, Natural Resources Management, Dr. Benard Kirui, both from Egerton University, Kenya for their support and positive criticism. I cannot forget to sincerely thank Dr. Luca Ongaro of Istituto Agronomico per l'oltremare/ University of Florence, Italy for always being ready to answer my question about GIS during my master s study. I would also wish to extend my appreciation to the United State Geological Survey (USGS) for availing the topographic data free of charge to be used worldwide for research and development. 5. References 1. Abhijit M. Zende, Nagarajan R., Atal K.R. (2014). Analysis of surface runoff from Yerala River Basin using SCS-CN and GIS, International journal of Geomatics and Geosciences, 4(3), Andy Ward and Jessica L. D Ambrosio (2008). Stream Classification, Ohio State University, 43

8 Agriculture and Natural Resources Fact sheet, AEX Beaumont, P. (1975). Hydrology, in River Ecology (Ed. B. A.), pp. 1-38, Blakwell Scientific, Oxford. 4. Clarke, J.I. (1966). Morphometry from Maps, Essays in Geomorphology. Elsevier Publ. Co., New York, pp Horton R.E., (1932). Drainage basin characteristics, Trans. Amer. Geophys. Union, 13, Horton R.E., (1945). Erosional development of streams and their drainage basins: Hydrophysical approach to quantitative morphology, Bulletin of Geological Society of America, 5, pp Kishor C, Panigrahi B. and Paul J.C., (2014). Morphometric analysis of Kharlikani watershed in Odisha, India using spatial information technology, International Journal of Geomatics and Geosciences, 4(4), Kuldeep Pareta and Upasana Pareta (2011). Quantitative Morphometric Analysis of a Watershed of Yamuna Basin India using ASTER (DEM) Data and GIS, International journal of Geomatics and Geosciences, 2(1), McColl, C. and Aggett, G., (2006). Land-use forecasting and hydrologic model integration for improved land-use decision support, Journal of Environmental Management, 84(4), pp Moore, I. D., Gessler, P.E., Nielsen, G.A., Petersen, G.A (1993). Terrain attributes: estimation methods and scale effects, In Jakeman, A.J.; Beck, M.B.; McAleer, M. Modelling Change in Environmental Systems. London: Wiley. p Muthukrishnan, Manoj K. S. and Banukumar K., (2013). Drainage Morphometry Evaluation for Kodavanar sub basin to understand the Interrelationships in Morphological Systems and in Process-Response Systems, International journal of Geomatics and Geosciences, 3(4), Nancy D. Gordon Thomas A. McMahon Brian L. Finlayson (1992); Stream Hydrology, An Introduction for Ecologist. New York: J. Willey. 13. Nag S.K., (1998). Morphometric analysis using remote sensing techniques in the Chaka sub basin, Purulia district, West Bengal, Journal of Indian Society of Remote Sensing, 26(12), pp Nishant Vaidya, Jagdish Chandra Kuniyal and Rohit Chauhan (2013). Morphometric analysis using Geographic Information System (GIS) for sustainable development of hydropower projects in the lower Satluj river catchment in Himachal Pradesh, India, International journal of Geomatics and Geosciences, 3(3), Robert W. Christopherson (2011). Geosystems: an introduction to physical geography, 8th Ed. 16. Schumm, S.A (1956). Evolution of Drainage Systems & Slopes in Badlands at Perth Anboy, New Jersey, Bulletin of the Geological Society of America, 67, pp Schumm, S. (1977). The fluvial system, New York: J. Willey. 18. Vibhu Nayar and Kavitha Natarajan, (2013). Quantitative Morphometric analysis of Kosasthalaiyar sub basin (Chennai basin) using remote sensing (SRTM) data and GIS techniques, International Journal of Geomatics and Geosciences, 4(1),