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ThesisItem Open Access MODELLING WATER CONSERVATION FOR CABBAGE PRODUCTION IN SUB–TROPICAL HUMID REGION USING DSSAT–CROPGRO MODEL(G. B. Pant University of Agriculture & Technology, Pantnagar-263145, 2023-02) Anita; Kashyap, P. S.Water management strategies place a considerable priority on water conservation in areas with limited resources of water. Scheduling water applications can help farmers to manage their water in a way that is significantly better. The scheduling of water application deals with applying water at the right time and in the right quantity in order to optimize production and maximize water conservation. In the present study, decision making software DSSAT (Decision Supporting System for Agrotechnology Transfer) CROPGRO model has been employed for cabbage crop to simulate the growth and yield under different scheduling of water applications based on the maximum allowable depletion of available soil water in a sub- tropical humid region . The field experiments were conducted at the Vegetable Research Center (VRC) of G. B. Pant University of Agriculture &Technology, Pantnagar situated in Udham Singh Nagar District of Uttarakhand, India. The experiments were conducted on cabbage crop (Green Coronet) during 2020-2021 and 2021-2022. During the first trial the transplanting of the crop was done in October 2020 and harvested in the month of February, 2021and during the second trial, transplanting was done in November 2021 and harvested in February 2022. The soil profile moisture content of the experimental field was determined using the gravimetric method. The irrigation treatments during cabbage growing experiments consisted of irrigation scheduling based on maximum allowable depletion (MAD) of available soil water (ASW) criteria such as, T1 (15%) indicated that 15% maximum allowable depletion (MAD) of available soil water (ASW), T2 (30%), T3 (45%), T4 (60%) and T5 (75%). No water stress was maintained at the initial stages of the crop development in order to allow the plants to attain healthy growth. Field experiments showed that an irrigation schedule with 45% maximum allowable depletion of available soil water gives the maximum water use efficiency for cabbage crop. It was also found that the scheduling irrigation for cabbage crop, 0-30 cm soil profile to be considered as most of the water was to be found extracted from this layer by the plants.ThesisItem Open Access Effect of soil amendments on runoff, sediment yield, biomass, soil physico-chemical properties and loss of major nutrients from sloping land under natural and simulated rainfall conditions(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2021-06) Kushwaha, Daniel Prakash; Anil KumarIn this research, experimental study was made in three successive trials, viz. first and second trials were conducted under natural rainfall conditions in Mollisols soils of Pantnagar in the foothills of North Western Himalayas during monsoon season of 2018 and 2019, respectively; and the third trial was conducted in simulated rainfall conditions just after completion of natural experiments. During first trial under natural conditions, a pre-determined dose of soil amendments was applied, while in second trial an increased dose of amendments was applied to check their incremental effect. Three soil amendments viz. biochar, anionic PAM and gypsum were used to fix six treatments: control (C); gypsum (G); biochar (B); gypsum and polyacrylamide (G+PAM); biochar and polyacrylamide (B+PAM); and biochar and gypsum (B+G) and each treatment was replicated thrice on plots of size 3m × 3m using randomized block design on uniform land slope of 12%. Hypothesis was whether six treatments could reduce surface runoff, sediment yield, loss of major soil nutrients (N, P and K), and maintain and improve soil physico-chemical properties and above- and below-ground biomass or not? (B+PAM) treatment of second trial, in which biochar was applied @ 1500 g/m2 and PAM was applied @ 4 g/m2, was found to be the best treatment under natural conditions. Therefore, this particular treatment was considered again under simulated rainfall conditions, but this time variable land slopes of 0%, 6%, 12%, 18%, and 24% on plots of size 1m × 3m and variable application rates of amendments along with five simulated rainfall intensities viz. 7.06, 9.07, 11.05, 12.97 and 14.96 cm/h were applied. Trial under simulated rainfall conditions was completed in four consecutive stages, mainly control (no amendments), biochar mixed with soil @ 1000 g/m2, 1500 g/m2 and 2000 g/m2. In each stage, PAM was applied @ 3, 4 and 5 g/m2. Available N-P-K losses, biochar loss, sediment yield and runoff were taken into account in simulated rainfall conditions. In simulated experiment, low dose of anionic PAM as 3 g/m2 (0.03 t/ha) in all conditions and high dose of biochar as 2000 g/m2 (20 t/ha) was found to be acceptable for reduction of runoff, sediment yield and major nutrient losses. In the loss of biochar study, 1500 g/m2 (15 t/ha) was found acceptable instead of high dose 2000 g/m2 (20 t/ha) for reduction of biochar loss. In this study, three reasonable model scenarios of sediment yield, nutrient loss and biochar loss were also developed using the experimental data of both conditions. For these model scenarios, four modeling techniques viz. MLP-ANN, SVM-RKF, SVM-LKF and MLR were used. Under natural conditions, five variables of the best treatment viz. rainfall, runoff, sediment yield, biochar loss and nutrients (N, P and K) loss were selected, while under simulated conditions, seven variables viz. rainfall, runoff, sediment yield, biochar loss, nutrients (N, P and K) loss, application rate of amendments, and land slope were selected for the development of model scenarios. On the basis of modeling results under natural and simulated conditions, it was found that SVM-LKF model performed well in comparison to other models in simulating event based data.ThesisItem Open Access Modelling rainfall-runoff using various intelligent computing techniques for Haripura and Baur Dams in Uttarakhand(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2021-07) Dumka, Basant Ballabh; Pravendra KumarWater resources are primary aspects of social, cultural and economic growth of a country. Water conservation is a basic idea for sustainable development of agricultural production, industrialization and high living standards of people. In this study, intelligent computing techniques like artificial neural network (ANN), wavelet coupled ANN (WANN), adaptive neuro-fuzzy inference system (ANFIS), support vector machine (SVM), and nonlinear regression (NLR) were used for rainfall-runoff modelling. The rainfall and runoff data of 20 years duration (1996-2015) for Haripura dam and 8 years duration (2006-2013) for Baur dam were used in this study. These dams are located in Uttarakhand. The data were used for prediction of present day runoff for both of the dams. Gamma test was used to select the best input combination for the development of models. Multilayer perceptron and various activation functions were used for ANN, various wavelet functions were used for WANN, various membership functions were used for ANFIS and radial kernel function was used for SVM techniques. The results showed that the Db-2 WANN model and SVM model were found to be the best among all developed models for Haripura and Baur dams. As the study areas are close to each other, their climatic and meteorological conditions and even soil characteristics are same. Hence both dams are comparable and a common model can be suggested for both Haripura and Baur dams.ThesisItem Open Access Effect of sediment particle characteristics on critical bed shear stress under different channel bed slopes and roughness conditions(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2021-06) Anuradha Kumari; Akhilesh KumarThe condition for incipient motion of sediment particle i.e., critical condition of motion occurs when magnitude of drag force (shear force) exerted by flowing fluid on the sediment particle exceeds the resistance offered by the particle. The analysis of movement of sediment particles along a channel bed has been one of the most challenging problems before the hydraulic engineers for a long time as accurate measurement of flow parameters in a channel at which the incipient motion exactly occurs is a subjective criterion. Sediment transport in gravel-bottomed streams is generally through surface creep as bed load transport due to presence of larger sized particles. Ample research work has been reported on incipient motion to describe the effect of some of these variables considering sediment particles as spherical. However, a very little work is reported in the available literature for non-spherical sediment particles, which is the normal situation in natural streams, where orientation of sediment particles plays a significant role on their incipient motion. Depending on the orientation of a non spherical sediment particle, the surface area of the particle exposed to the flow gets changed and accordingly the entire force dynamics on the sediment particle is altered. This experimental study was conducted in Soil and Water Conservation Engineering Laboratory, College of Technology at Pantnagar with the focus to investigate the effects of sediment particle shape, size, unit weight, orientation and flatness along with channel bed roughness and channel bed slope on the critical bed shear stress. The experiments were conducted by using a rectangular Hydraulic Tilting Flume of 7.0m×0.6m×0.3m size with precise water supply, regulation and measurement systems and can be adjusted a forward slope up to 5%. Incipient conditions for motion of sediment particle were created and observations were recorded analyzed for 252 different combinations. The critical bed shear stress was found to be higher for non- spherical sediment particles as compared to spherical sediment particles of the same nominal diameter and increasing almost linearly with size for all shapes of sediment particles. It was also observed that spherical sediment particles of the same size were having lesser critical bed shear stress as compared to rectangular prismatic sediment particles under similar conditions. As channel bed slope increased from 0.25% to 0.5%, there was almost a 100% increase in critical bed shear stress in case of rectangular prism shaped sediment particles of the same size but about 50% increase was observed in case of spherical and cubical sediment particles under similar situations. Almost a linear increase in critical bed shear stress was observed when the bed roughness height increased from 0mm to 8.000mm for all sized sediment particles at every channel bed slope. It was observed that critical bed shear stress did not change significantly with the change in orientation of the sediment particles, while total shear force acting on the sediment particle changed with orientation in the ratio of their exposed area of non-spherical sediment particles under similar flow and channel roughness conditions. With the increasing flatness ratio, the effect of orientation of sediment particle became an important consideration to determine the magnitude of the total shear force acting on the particle under particular set of conditions. The critical bed shear stress was found to be increasing with the increase in unit weight of the sediment particle at a particular bed slope and roughness height. Relationships between dimensionless critical shear stress ‘θ’ (also called Shields parameter) to the critical particle Reynolds number (Rep) of sediment particles of noncubical and non-spherical shape along with parameters like slope of channel bed and its roughness were developed. Mathematical relationships were developed to determine critical bed shear stress and tested for their estimation efficacy using scatter plots and statistical indices for different combinations of experimental variables. The developed mathematical relationships are likely to provide an effective tool to analyze critical shear stress at incipient conditions.ThesisItem Open Access Efficacy of roots and shoots of napier and lemon grasses to control runoff and sediment outflow under simulated rainfall and overland flow conditions(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2021-02) Tamta, Sushma; Akhilesh KumarIn this study, extensive laboratory experiments were conducted under controlled environment of a laboratory with simulated rainfall and overland flow conditions using a soil filled hydraulic tilting flume as test plot. As per mandate of this study, the effects of root and shoot characteristics of Napier grass and Lemon grass on runoff and sediment outflow at different growth stages with four simulated rainfall intensities of 4.0 cm/h, 6.5 cm/h, 8.3 cm/h and 9.4 cm/h and four overland flow rates of 6.6 l/s/m, 9.0 l/s/m, 10.7 l/s/m and 12.4 l/s/m to observe runoff and sediment outflow at three land slopes of 1%, 2%, and 3% were observed. After each experiment, different morphological characteristics such as Leaf Area Index (LAI), Shoot Length (SL), Number of Leaves (NL), Number of Tillers (NT), Shoot Biomass (SB), Root Density (RD), Root Length (RL), Root Biomass (RB), and Total Biomass (TB) of grasses were measured at Stage-I (90DAP), Stage-II (120DAP) and Stage-III (150DAP) for both crops. Runoff samples were collected for whole plant plot and root plot for various combinations of input variables and in total 936 runoff samples were collected and analyzed to determine sediment concentration and sediment outflow rate. The analysis of findings revealed that Napier grass and Lemon grass were very effective to reduce runoff and sediment outflow and their efficacy increased with the extended growth stage. The reduction in runoff and sediment outflow at stage-I, i.e. 90 DAP, was approximately 56% and 85% for Napier grass, and 52% and 82% respectively for Lemon grass. At stage-II, i.e., 120 DAP, the reduction in runoff and sediment outflow was approximately 68% and 90% for Napier grass, and 59% and 87% respectively for Lemon grass while at stage-III, i.e., 150 DAP, it was observed as 74% and 96% for Napier grass, and 69% and 94% respectively for Lemon grass as compared to bare plot under simulated rainfall conditions.The sediment outflow rate reduction from roots was 9%, 17% and 33% more than the shoots at 90 DAP, 120 DAP and 150 DAP respectively under over land flow conditions. Napier grass with its higher values of above-ground biomass parameters (shoots) and below ground bio mass parameters (roots) as compared to Lemon grass was found to be more effective to reduce runoff and sediment outflow. It was also observed that the contribution of shoots in runoff rate reduction was higher than the roots and maximum reduction was observed at low rainfall intensity. Similarly, root part of the plant has more contribution in sediment outflow rate reduction as compared to shoot part of the plant. The relative contribution of the roots of Napier grass in sediment outflow reduction varied from 61% to 78%, and contribution of shoots was found to be 22-39%. On the other hand, for Lemon grass, the relative contribution of roots in sediment outflow reduction varied from 59% to 78%, and contribution of shoots varied in the range of 22% to 41% under selected rainfall intensities, land slopes and growth stages as compared to whole plant. Mathematical models were established and for runoff and sediment outflow in terms of root and shoot parameters. Developed models were found to be very satisfactory based on the values of various performance indicators.ThesisItem Open Access Stage-discharge sediment modelling using soft computing techniques and prioritization of sub-watersheds of Ghatshila watershed(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2021-02) Manish Kumar; Pravendra KumarSoil and water resources conservation are primary aspect for sustainable development of agricultural production. In this study, soft computing techniques like artificial neural network (ANN), support vector machine (SVM), wavelet based artificial neural network (WANN), wavelet based support vector machine (WSVM) and multilinear regression (MLR) were used for stage-discharge-sediment modelling. The stage, discharge and suspended sediment concentration (SSC) data of 10 years duration (2004-2013) was used for prediction of present day SSC for three sites namely, Adityapur, Jamshedpur and Ghatshila sites of Ghatshila watershed. Gamma test was used to select the best input combination for the development of models. Multilayer perceptron was used for ANN and WANN techniques while linear and radial kernel function were used for SVM and WSVM techniques. The results showed that the WSVM-LF model was found to be the best among all developed models for Adityapur and Ghatshila site while SVM-RF model was found to be the best for Jamshedpur site. Further, prioritization of the sub-watershed based on principal component analysis (PCA) was carried out for Ghatshila watershed. The morphometric analysis of twenty five sub-watersheds of Ghatshila watershed was done based on information obtained from drainage map extracted using remote sensing data and GIS tool. Based on PCA, four principal components namely, texture ratio (T), drainage density (Dd), circulatory ratio (Rc) and stream frequency (Fs) were identified for prioritization. Based on compound factor, SW-15 sub-watershed assigned with rank 1 priority whereas SW-22 sub-watersheds was assigned with rank 25. Therefore, SW-15 sub-watershed can be treated with suitable conservation measures.ThesisItem Open Access Stage-discharge sediment modelling using soft computing techniques and prioritization of sub-watersheds of Ghatshila watershed(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2021-02) Manish Kumar; Pravendra KumarSoil and water resources conservation are primary aspect for sustainable development of agricultural production. In this study, soft computing techniques like artificial neural network (ANN), support vector machine (SVM), wavelet based artificial neural network (WANN), wavelet based support vector machine (WSVM) and multilinear regression (MLR) were used for stage-discharge-sediment modelling. The stage, discharge and suspended sediment concentration (SSC) data of 10 years duration (2004-2013) was used for prediction of present day SSC for three sites namely, Adityapur, Jamshedpur and Ghatshila sites of Ghatshila watershed. Gamma test was used to select the best input combination for the development of models. Multilayer perceptron was used for ANN and WANN techniques while linear and radial kernel function were used for SVM and WSVM techniques. The results showed that the WSVM-LF model was found to be the best among all developed models for Adityapur and Ghatshila site while SVM-RF model was found to be the best for Jamshedpur site. Further, prioritization of the sub-watershed based on principal component analysis (PCA) was carried out for Ghatshila watershed. The morphometric analysis of twenty five sub-watersheds of Ghatshila watershed was done based on information obtained from drainage map extracted using remote sensing data and GIS tool. Based on PCA, four principal components namely, texture ratio (T), drainage density (Dd), circulatory ratio (Rc) and stream frequency (Fs) were identified for prioritization. Based on compound factor, SW-15 sub-watershed assigned with rank 1 priority whereas SW-22 sub-watersheds was assigned with rank 25. Therefore, SW-15 sub-watershed can be treated with suitable conservation measures.ThesisItem Open Access Geospatial technology and soft computing for hydrological modelling of Koyna river basin(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2020-02) Bajirao, Tarate Suryakant; Pravendra KumarConservation of natural resources plays an important role in sustainable development of agriculture. In this study, geospatial technology like remote sensing and geographical information system (GIS) and soft computing techniques like artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), wavelet coupled artificial neural network (WANN) and wavelet coupled adaptive neuro-fuzzy inference system (WANFIS) were employed for hydrological modelling of Koyna river basin, Maharashtra. Different basin characteristics like topography, slope, runoff characteristics etc. were analyzed and different subwatersheds were prioritized to adopt conservation practices to prevent critically degraded area from further erosion. Original rainfall, runoff and suspended sediment concentration (SSC) time series data were decomposed with discrete wavelet transform using different mother wavelets into different multi-frequency sub-signals. Hybrid, WANN and WANFIS models were developed by coupling wavelet transformed data to single ANN and ANFIS, respectively. The performance of the developed models was assessed using qualitative and quantitative performance evaluation criteria. The impact of land use/land cover change on rainfall-runoff transformation was analyzed using natural resource conservation service curve number (NRCSCN) method. Different morphometric parameters indicated young stage of basin topography. Still the soil erosion process is active in nature. It was observed that Coiflet wavelet coupled ANFIS (WANFIS) models performed the best for daily runoff and SSC predictions. Due to spatiotemporal variability of land use/land cover over 13 years, average runoff coefficient increased from 0.41 to 0.43. The performance of data driven models was observed to be satisfactory for daily runoff and SSC predictions. This analysis is useful for decision makers to start natural resources conservation practices on priority basis and it can also be useful to predict daily runoff and SSC of the Koyna river basin.