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Subject: Soil and Water Engineering × Author: Saran, Bhagwat × End date: 2021 × Start date: 2021 × Type: Thesis ×
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    ThesisItemOpen Access
    Hydrological modelling using SWAT and effect of climate change on rainfall, runoff and sediment yield in the Naula Watershed, Uttarakhand
    (G.B. Pant University of Agriculture and Technology, Pantnagar, District Udham Singh Nagar, Uttarakhand. PIN - 263145, 2021-11) Saran, Bhagwat; Anil Kumar
    Soil and water is one of the most important natural resources for the survival on the earth. Without soil and water the life on the earth is not expected. At present increasing the rate of soil erosion is the matter of serious concern to feed such a huge population. Considering the above facts the present study is undertaken to assess the hydrological behaviour of Naula watershed. In this study the physically based Soil and Water Assessment Tool (SWAT) model was used to simulate the runoff and sediment yield from the Naula watershed of Ranikhet, Uttarakhand, India. The data used for this study was runoff and sediment yield from the year 1980 to 2012, two years of data (1980-1981) were used to warm up of the SWAT model. The calibration was performed using monthly observed data of runoff and sediment yield from the year 1982 to 2002 and that model was validated using same data from 2003 to 2012. The calibration and validation analysis of the model has been carried out at Naula watershed using SWAT-CUP with the algorithm SUFI-2 (Sequential Uncertainty Fitting) for the runoff and sediment yield. The results of monthly Nash-Sutcliffe efficiency (NSE), coefficient of determination (R2), percent bias (PBIAS) and RMSE-observations standard deviation ratio (RSR) were found to be acceptable for both calibration and validation period. The NSE, R2, PBIAS and RMSE for the runoff simulation were found as 0.68, 0.68, -3.3 and 0.56 during calibration period and 0.62, 0.64, -12.8 and 0.76 for the validation respectively. For the simulation of sediment yield using SWAT-CUP, the NSE, R2, PBIAS and RMSE were found as 0.69, 0.73, -1.3 and 0.56 for the calibration period and 0.75, 0.76, -2.6 and 0.51 for the validation period respectively. NDVI and LULC change detection were also analysed in this study. The highest NDVI values were found as 0.64, 0.72 and 0.55 for the year 2000, 2010 and 2020 respectively. In the LULC change detection, the land covered by the agriculture was 13.87 %, mixed forest 1.95 %, shrub land 6.59 %, barren land 0.58 %, fallow land 11.63 %, water body 0.49 % and evergreen forest 64.85 % of the total area for the year of 2000. However, the area of agriculture and forest gradually decrease while the area of barren land and fallow land increase in the year 2000-2010. In the year 2010-2020; the agriculture land and forest land, fallow land decrease and barren land increases twice as compared to previous year. The area of water body increases very less from the year 2000-2020. Climate change was studied by determining the percentage change of rainfall, runoff and sediment yield from the year 2020 to 2052 (33 years) and 2053 to 2085 (33 years) with the base value of 1980 to 2012 (33 years).