Abstract: In this study surface runoff was estimated using the USDA Soil Conservation Service curve number (SCS-CN) method in Maharuwa micro-watershed. The total geographical area of the micro-watershed is 1028.00 ha, located between 830 54’ 29’’ to 820 54’ 32” North latitude and 250 64’ 44” to 250 55’ 38” East longitude which is situated at Maharuwa village of Ambedkar Nagar district, Uttar Pradesh. A total of 11yearrainfall event were selected between the years 2010 and 2020 for the study. Antecedent moisture content (AMC) was calculated by taking preceding five days rainfall events which gave three conditions AMC I, AMC II and AMC III. Weighted Curve Number for the entire selected micro-watershed was calculated based on site information of the watershed by land use land cover classification using ArcGIS and found to be 82.905 for AMC II. The CN values corresponding to AMC I and AMC III were 68.011 and 91.907 respectively. The runoff for each storm events was estimated using Curve Number method and it is found that among the selected year events maximum rainfall occurred in year 2013 giving runoff value of 162.27 mm and minimum rainfall occurred in year 2015 with runoff value of 49.15 mm. Runoff volume of the Maharuwa micro-watershed for each year events were also calculated, and maximum runoff volume was1668208.616 m3found in year 2013 and minimum runoff volume was505326.247 m3in year2015. By using previous year runoff values, prediction of runoff for next five year was also done. The prediction of runoff was done using Forecast tool available in Excel 2016 (FORECAST.ETS). It was found that the maximum runoff was expected in the year 2025 and minimum runoff was expected in year 2023. From the present study it was concluded that the SCS-CN method gives significant values of runoff, with the R2 value of 0.8514. The predicted values from the study could be useful for design of soil and water conservation structures and also useful for preparation for the next Storm event.
Index Terms – runoff, SCS-CN method, potential maximum retention, rainfall, AMC and micro-watershed.
| DOI: 10.17148/IARJSET.2022.9807