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20213
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Subject: Soil and Water Engineering × 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).
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    ThesisItemOpen Access
    Effect of temporally distributed rainfall patterns on runoff-sediment outflow from lands under sorghum and urad crops and with furrow treatment
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2021-02) Atul Prakash; Akhilesh Kumar
    In this study, laboratory experiments were conducted to assess the effect of temporally distributed rainfall patterns namely, Uniform rainfall distribution pattern (URDP), Advanced rainfall distribution pattern (ARDP), Delayed rainfall distribution pattern (DRDP) and Intermediate rainfall distribution pattern (IRDP) considering Sorghum and Urad crop lands and also lands treated with along the slope furrow and across the slope furrow on total runoff, average runoff rate, average sediment concentration and average sediment outflow rate under at selected land slopes. The observations were also analyzed to assess the efficacy of above soil biomass and below soil biomass of these cropping systems on runoff and sediment outflow. This study was conducted on experimental plots using artificially generated rainfall with the help of a rainfall simulation system of 3 m × 1 m size. Rainfall distribution pattern were created by using simulated rainfall and the simulator was operated for 30 minutes to provide a total rainfall of 4.4 cm depth. A comparison of observed values of runoff rate and sediment concentration for whole plant plot and below soil bio mass plot clearly revealed that the for whole plant plot, the lowest runoff rate occurred for URDP while the lowest value of sediment concentration was found in case IRDP at 4% land slope. For 8% land slope, the maximum average runoff rate and sediment concentration rate were observed in case of IRDP. This study clearly revealed that in case of below soil mass plot, the minimum value of runoff was observed in case of URDP and maximum was for ARDP at 4% land slope while at 8% land slope the minimum value of runoff was observed in case of IRDP and maximum was for URDP. Similarly, the minimum average sediment concentration in this case was observed as 1236.66 PPM in case of DRDP and the maximum value of sediment concentration was observed as 1483.33 PPM in case of URDP at 4% land slope. At 8% land slope, the minimum and maximum values of runoff were observed in case of IRDP & URDP rainfall pattern while the minimum and maximum values of sediment concentration were observed in case of DRDP and ARDP rainfall pattern respectively. The observations and analysis of the findings clearly indicated that in case of runoff, plot with below soil bio mass provided better reduction as compared to above soil bio mass plot for every rainfall distribution pattern. In case of sediment, however, the situation was not that clear as in case of IRDP and DRDP below soil bio mass plot provided better reduction in sediment concentration but n case of IRDP and ARDP, above soil bio mass plots had an edge over below soil bio mass plot in sediment outflow control. Observed values of total runoff indicated that the highest runoff rate occurred in case of land without any treatment under URDP while the lowest runoff rate occurred in case of lands treated with across the slope. It was also observed that the runoff rate got reduced by more than 50 in case of lands treated with across the slope as compared to lands without any treatment under every rainfall distribution pattern. It was also seen that the across the slope furrow treatment produced lesser runoff rate by 25.925%, 20.833%, 18.309% and 17.46% as compared to along the slope furrow treatment at 4% land slope under URDP, ARDP, DRDP and IRDP respectively.
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    ThesisItemOpen Access
    Comparative assessment of different geostatistical approaches for spatial interpolation of annual rainfall
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2021-02) Verma, Shikha; Singh, Praveen Vikram
    Rainfall is an essential component and acts as primary input for hydrological modelling. The availability of reliable data is necessarily important to obtain the maximum benefit from hydrological analysis. The rainfall in rajasthan is so irregular and unpredictable spatially as well as temporally. The measurement of rainfall is very important however it is not practically possible to measure at each and every point. In such situations, rainfall measurements are typically available at a finite number of rain gauges therefore, determination of rainfall at various ungauged stations needs spatial interpolation to assess the spatial variability of the region. The analysis was done over annual rainfall of rajasthan having 253 raingauging stations for a period of 40 years (1980–2019). The present study was an attempt to analyze and compare the performance of different geostatistical spatial interpolation techniques, univariate, Ordinary Kriging (OK), and multivariate, Simple Co-kriging (SCK) and Ordinary Co-kriging (OCK), to interpolate the annual rainfall. In both the techniques, spherical, circular and Gaussian models were used to find the best-fitted semivariogram for rainfall prediction purpose. The nugget-sill ratio was determined for all the nine models to decide the best fit model. The statistical analysis of nugget-sill ratio for univariate and multivariate geostatistical analysis revealed that the ordinary kriging (OK-Circular) and ordinary cokriging (OCK-Spherical) was followed the least standard deviation as 0.1121 and 0.1051, respectively in the dataset. The cross-validation results were depicted the overall comparative evaluation of the selected models in which OCK-Spherical outperformed over OK-Circular by the consideration of different statistical parameters. For OK-Circular, the value of ME, RMSE, MSDE, RMSSDE and ASE were found to be 0.6525, 210.1545, 0.0035, 1.0306 and 204.4955 and for the validation of ordinary co-kriging OCK-Spherical these statistical parameter values were found as 0.3221, 210.3274, 0.0023, 1.0367 and 203.6121, respectively. Finally, the study concluded that the incorporation of elevation as a secondary variable with rainfall, increases the accuracy of estimation of spatial continuity of rainfall at ungauged locations irrespective of its correlation with the rainfall. However, both the selected models performed well for the study area. Statistically, OCK-Spherical worked better than OK-Circular method of interpolation.