Morphometric Analysis of Karadya Micro Watershed: A Case Study of Mandya District
American Journal of Remote Sensing
Volume 6, Issue 1, June 2018, Pages: 15-22
Received: Jan. 16, 2018;
Accepted: Feb. 5, 2018;
Published: Mar. 14, 2018
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Ningaraju Holalu Javarayigowda, Department of Civil Engineering, People’s Education Society College of Engineering, Mandya, India
Ganesh Kumar Shivamogga Basavaraju, Department of Civil Engineering, Sri Dharmasthala Manjunatheshwara Institute of Technology, Ujire, India
Surendra Halasuru Jayaram, Department of Civil Engineering, ATRIA Institute of Technology, Bangalore, India
Water is one of the essential natural resource for the very survival of life becoming a scarce commodity. It is very important to manage this very essential natural resource at micro watershed level for achieving sustainable development. The morphometric analysis plays a vital role in understanding the hydro-geological behavior of drainage basin. Remote sensing and Geographical Information System (GIS) techniques are proven efficient tool for morphometric analysis of a drainage basin throughout the world. Hence, an attempt has been made in this paper to study morphometric parameters of Karadya micro watershed using Geographical information system(GIS) approach. The study reveals that the terrain exhibits dendritic type drainage pattern with highest stream order being third order. The drainage density of watershed is 2.65km-1. The mean bifurcation ratio of the entire basin is 6.73 indicating that the drainage pattern is not much influenced by geological structures. Relief ratio indicates that the discharge capability of these watersheds is very high and the ground water potential is low. Further, the study reveals that GIS techniques proved to be a competent tool in morphometric analysis helps in planning and management of watershed.
Ningaraju Holalu Javarayigowda,
Ganesh Kumar Shivamogga Basavaraju,
Surendra Halasuru Jayaram,
Morphometric Analysis of Karadya Micro Watershed: A Case Study of Mandya District, American Journal of Remote Sensing.
Vol. 6, No. 1,
2018, pp. 15-22.
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