1. PAVITHRA C J - Ph.D Scholar, Department of Civil Engineering, Visvesvaraya Technological University, Belagavi,
2. Dr. BALAKRISHNA H B - Professor and Head, Bangalore Institute of Technology, Bengaluru, Karnataka, India.
Water is a vital element for life to sustain on the earth. The changing climate and weather have their impact on water resources. Floods and droughts are to be prevented, controlled and managed. The increasing population and urbanization are causing water stress in burgeoning cities like Bengaluru. Hence, it is absolutely essential for sustainable utilization and governance of existing water resources. Runoff is a very important hydrologic variable in water resources applications and its quantification helps to achieve water sustenance. The SCS-CN model is a very popular and proven method for estimating surface runoff and the same has been employed in the present study. Runoff estimations in three Valley systems of Hebbal, Kormangala-Challaghatta and Vrishabhavathi were carried out using the rainfall data collected from DES and KSNDMC for the years from 1991 to 2020. . In the Hebbal Valley, the highest runoff of 536.45mm was recorded during 2005 and the least runoff of 141.70mm was observed during 2003. The Hebbal Valley has an average runoff coefficient of 0.36 calculated for the past thirty year data (1991-2020). In the KC Valley, the highest runoff of 560.61mm was observed during 1998 and the least runoff of 69.54mm was observed during 1994. The KC Valley has an average runoff coefficient of 0.33 calculated for the past thirty year data (1991-2020). In Vrishabhavathi Valley, the highest runoff of 542.48 mm was observed during 2017 and the least runoff of 68.21mm was observed during 2002. Vrishabhavathi Valley has an average runoff coefficient of 0.32 when calculated with the past thirty years data (1991-2020). More runoff can be observed during the months of September (Monsoon), October (Post-Monsoon) and December (Post-Monsoon) in all the three Valley systems. We observed a positive linear correlation between the rainfall and runoff within the Valley systems with values of correlation coefficient ranging between 0.73 -0.9. Thus, runoff calculations using the SCS-CN method give us a more reliable output for average conditions. This study can be used as input data for mapping of flood-prone zones within these valleys and also to govern the water conservation needs and its management.
GIS, KSNDMC, Rainfall, Runoff, Runoff coefficient, SCS-CN Method, Valley