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2004 - 200972010 - 201912
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Subject: Soil and Water Engineering × End date: 2019 × Type: Thesis × Thesis Type: M.Tech. ×
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Now showing 1 - 9 of 19
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    ThesisItemOpen Access
    GIUH models based on uniform and non uniform stream flow velocities
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2006-07) Behera, Ramakanta; Akhilesh Kumar
    The present study was carried out with the objective to develop mathematical models for Geomorphologic Instantaneous Unit Hydrograph by considering uniform stream flow velocity as well spatial distributed (non uniform) stream flow velocity along the stream network. In this approach, a unifying synthesis of the hydrological response of a catchment to surface runoff is attempted by deriving equations of general characteristics which express IUH as a function of Horton‟s numbers i.e. area ratio (RA), bifurcation ratio (RB) length ratio (RL), an internal scale parameter (LW) denoting the length of the highest order stream; and the peak velocity of the stream flow (v). In the present study, these geomorphologic properties of the watershed were determined by using Horton‟s stream order laws. GIUH model formulation was attempted considering the uniform and non uniform stream flow velocities in the watershed network. In case of uniform flow velocity, the stream flow is assumed to be constant throughout the watershed network and the flow velocity was determined from the geomorphological quantities of the network and the intensity of the effective rainfall, while in case of variable velocity model the flow velocity was considered to vary according to the slope pattern of the network of various order of streams. The conceived models were developed by using the geomorphological and hydrological data of a small hilly watershed known as “Arki watershed” comprising an area of 2460 ha in Solan district of Himachal Pradesh (India). The performance of both the models viz., GIUH with uniform and non uniform flow velocities has been evaluated for the study area considering sixteen storm events by employing various statistical error indices. Based on qualitative and quantitative comparison it was observed that both the GIUH models based on uniform and non uniform flow velocities are applicable for the study area. However, on the basis of the calculated values of statistical indices it was found that the GIUH-UV model performed better in comparison to the GIUH-VV model except in the computation of peak rate of runoff where the GIUH-VV was found to be better performing than GIUH-UV model.
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    ThesisItemOpen Access
    Optimization of spatial allocation of agricultural activities for a Himalayan watershed: an application of multi-objective programming approach
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2006-08) Joshi, Digvijay; Singh, J.K.
    In the present study, an attempt has been made to develop the optimal land use model by using multi-objective programming technique with the basic objectives viz. to minimize the soil loss and maximize net return from the Chorgaliya watershed based on resource constraints such as land availability, water availability, labour opportunities FYM availability and fodder availability. All the relevant data and information to develop the model were collected and were synthesized as per the requirement of the model. The Universal Soil Loss Equation (USLE) was used to determine the soil loss from different land use activities. Having determined the soil loss coefficients, the other coefficients such as water coefficient, labour coefficient, FYM coefficient and fodder coefficient were also estimated and were incorporated to develop the model. In order to make model socially acceptable, economically viable and ecologically conducive to the inhabitants of the watershed, three alternative plans, viz. Plan I: Existing cropping pattern and livestock status with the restriction on crops preferred by farmers, Plan II. Existing cropping pattern and livestock status with the restriction on orchards and Plan III. Existing cropping pattern with the restriction on the food grains were developed. All these alternative plans were compared with the existing land use pattern in the Chorgalia watershed. Among all the alternative plans, the Plan II was found to generate maximum net return to the farmers and the least amount of soil loss from the study area.
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    ThesisItemOpen Access
    Runoff estimation from a small watershed using GIUH approach in a GIS environment
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2005-07) Nema, Manish Kumar; Singh, J.K.
    The conventional techniques of derivation of unit hydrographs require historical rainfall- runoff data. In a developing country like India, the most of the small watersheds are still ungauged; hence adequate runoff data are not generally available. For such type of catchments tedious procedure of regionalization of model parameters are sought. The research in the field of fluvial geomorphology of the problems facing the hydrologist today, in this regard the concept of geomorphologic instantaneous unit hydrograph (GIUH) has been introduced. Wherein the characteristics of instantaneous unit hydrograph are related to the geomorphological and climatic characteristics of the watershed. The major advantage of this approach is that this linking of geomorphologic parameters with the hydrologic characteristics of the watershed can lead to a simple and useful procedure to simulate the hydrologic behavior of various catchments, particularly ungauged ones. In the present study the geomorphologic characteristics of Kothuwatari watershed, a sub-watershed of upper Damodar Valley, Hazaribagh, Jharkhand, India have been estimated from the toposheets 72H/7 and 72H/8 by using the GIS software ILWIS 3.0. The GIUH based Clark and Nash models have been used for the simulation of nine storm events. The direct surface runoff (DSRO) hydrographs derived by both the models have been compared with the observed DSRO hydrographs. The performance of the models for the study area has been evaluated by employing performance indices viz., (i) absolute relative error, (ii) Absolute percentage deviation in peak flow rates, (iii) coefficient of efficiency, (iv) absolute average error, (v) root mean square error and (vi) average error in volume. The results of the study showed that both the developed models provide a reasonably good estimate of direct surface runoff based on these performance indices. However it was difficult to conclude that which model performs better for the study area as based on percentage absolute deviation in peak and average error in volume, the GIUH based Clark model was found better while based on rest of the indices the GIUH based Nash model was found better.
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    ThesisItemOpen Access
    Runoff prediction from Gaula river using Heuristic approaches
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2019-07) Bhatt, Gaurav; Pravendra Kumar
    Runoff is the most complex and important elements of hydrologic cycle which needs to be understood well and is to be predicted in a very efficient manner. Runoff prediction is very important for countries which are very much prone to floods in a short period of time. It can cause various famines and diseases if not controlled in a proper way. Considering these facts, a study has been carried out to assess the daily monsoon runoff prediction from Gaula river, Kathgodam, Nainital, Uttarakhand, India. The daily monsoon meteorological data of 11 years (1st June, 2008 to 30th Sept, 2018) were collected from Gaula barrage located at Kathgodam, Nainital, Uttarakhand, India. In the present study, multilayer perceptron artificial neural network (MLP-ANN) and Wavelet based artificial neural network (WANN) techniques were used to predict the daily monsoon runoff. The daily data for monsoon period (1st June to 30th September) of years 2008-2015 and 2016-2018 were used to train and test the models respectively. The lags were decided on the basis of Minitab statistical approach and all the possible input combinations were put to back-propagation algorithm and tan sigmoid activation function for training and testing of models. The performance of the models was evaluated qualitatively by visual observations and quantitatively using various performance indices viz. RMSE, correlation coefficient, coefficient of efficiency and Willmott index. The WANN model performed better than the MLP-ANN model.
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    ThesisItemOpen Access
    Spatio-temporal rainfall analysis of Uttarakhand
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2019-05) Rana, Saroj; Kashyap, P.S.
    Analysis of rainfall and rainy days are important issues for all mountainous states of India due to their varying topography and extreme rainfall events are the reason for quick surface runoff which is dangerous for safety of large structures and other natural resources. In this study, spatial and temporal variability and trend of rainfall and rainy days was analyzed for Uttarakhand sate. Long-term characteristics of rainfall and rainy days were checked using statistical parameters. Mean, coefficient of variation, standard deviation and skewness in the rainfall and rainy days time series were checked on the seasonal and annual basis. Lag-1 serial autocorrelation using student’s t-test confirmed the randomness in the time series data and on the basis of t-test, Mann-Kendall (MMK) test and modified Mann-Kendall (MK) test has been used to analyze the trend in rainfall and rainy days data of all districts of Uttarakhand. Theil-Sen’s slope estimator method has been used to determine the magnitude of trend change and the percentage change over the study period. The change point in the trend and beginning of the change was detected using Sequential Mann-Kendall (SQMK) test. The inverse distance weighting (IDW) technique of interpolation in QGIS 3.4 has been used for detecting the spatial variability and trend in rainfall and rainy days time-series. A moderate variation in annual rainfall and rainy days and high variation in seasonal rainfall and rainy days was observed in Uttarakhand. Both significant and non significant increasing and decreasing trends was obtained from the results depending upon the districts. A decreasing trend of rainfall and rainy days concentration was also observed in most of the districts on seasonal as well as annual basis. The analysis manifested the high spatial and temporal variability due to diverse precipitation-generating mechanisms and the need for an improved monitoring network.
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    ThesisItemOpen Access
    Hydrological characterization of Nagavali river basin under varying land use scenario
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2019-05) Naik, Bijayalaxmi; Kashyap, P.S.
    Soil and water are the two contrary sides of a coin that need to be monitored for watershed management point of view. In the present scenario with increase in population, a huge demand for water as well as land space is raising as a big question mark. Taking this issue into account, the impact on hydrological parameters due to change in land use & land cover has been studied in Nagavali River Basin of Odisha covering a total area of 9510 km2. SWAT is a semi distributed, continuous, deterministic hydrological model which was utilized for determining the changes on hydrological components due to variation in land use for specific years within the desired study area. During the total process the watershed was delineated to 29 subbasins with 249 HRUs. The developed SWAT model was calibrated for 11 years (2000-2010) and validated for 3 years (2011-2013) using SUFI-2 algorithm using SWAT-CUP. NSE and R2 for calibration were 0.91 in both cases where as in validation it was 0.79 and 0.96 respectively. The change in hydrological components due to land use scenarios was studied for five years i.e. 1985, 1995, 2005, 2015 and 2018. Evapotranspiration, precipitation, streamflow, lateral flow and groundwater contribution to stream were the five hydrological parameters that were considered for each year for the ongoing study. Evapotranspiration, precipitation and lateral flow were resulted maximum variation over the years.
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    ThesisItemOpen Access
    Comparison of MLP-ANN and W-ANN for SPI forecasting to assess meteorological drought
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2019-07) Amit Kumar; Singh, Pravin Vikram
    The accurate assessment of drought is an essential component for effective water resource management planning to mitigate adverse consequences of drought. The Standardized Precipitation Index (SPI) is a widely used index to characterize meteorological drought on a varying time scale. Information about Standardized Precipitation Index (SPI) at a place is vital for the assessment of drought. In this study, an approach to forecast Standardized Precipitation Index (SPI) has been attempted to assess meteorological drought in drought prone area of the country at different time scales. This approach involved application of Multi-Layer Perceptron Artificial Neural Networks (MLP-ANN) and Wavelet Artificial Neural Network (W-ANN) to generate Standardized Precipitation Index values for different scales and denoted as, SPI-1, SPI-3, SPI-6, SPI-9, SPI-12 and SPI-24. To generate SPI values using these two models, the data set of Prabhani district in the state of Maharashtra was considered. The total data set of calculated values of SPI during 1971 to 2014 at various time scales was divided into three sets; (i) a training set, consisting of first 36 years data from January, 1971 to December, 2006; and (ii) a testing set, consisting of 4 years data from January, 2007 to December, 2010; and (ⅲ) a validation set, consisting of remaining 4 years data from January, 2011 to December 2014 for both the approaches. The SPI values at previous six-month lag were used to forecast current month SPI values and gamma test was used to decide the best combination of inputs for SPI forecasting. Both MLP-ANN and W-ANN models trained with the Levenberg Marquardt (LM) back propagation algorithm were developed using single hidden layer. The Root Mean Square Error (RMSE), Correlation Coefficient (r) and Coefficient of Efficiency (CE) statistical indices were adopted to evaluate the performance of these models. The SPI values generated by using best developed MLP-ANN and W-ANN models were compared with calculated values of SPI. The forecasted results indicate that for SPI-1, the performance of both MLP-ANN and WANN models was not satisfactory, however, MLP-ANN based model performed better than W-ANN model. For SPI-3, 6 and 9, the performance of W-ANN model was found to be better than MLP-ANN based model. In case of SPI-12 hand SPI-24, both the models were found to be performing satisfactorily, however, WANN model has a little bit edge over MLP-ANN. Interestingly, it was observed that the performance of both these models was found to be improving with increasing SPI time scale.
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    ThesisItemOpen Access
    Monthly rainfall modelling using Artificial Neural Network for Almora
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2019-07) Rawat, Devendra Singh; Devendra Kumar
    Artificial Neural Networks model using different inputs were developed for monthly rainfall modelling of Almora. The 70% of monthly rainfall data from 1964 to 2018 was used for calibration and 30% for validation. Different topologies of models were constructed with change in number of hidden layers, processing elements and activation functions. The numbers of hidden layers varied from 1 to 3 and numbers of neurons from 1 to 10. Log-Sigmoid Axon & Tanh Axon transfer functions with back propagation algorithm and Levenberg-Marquardt learning rule were used. The performance of the models was evaluated qualitatively using rainfall time series graphs and scatter plots and quantitatively by employing Correlation coefficient, Root mean square error, Coefficient of efficiency, Integral square error and Pbias indices. The models having higher value of Coefficient of efficiency, Correlation coefficient and lower values of Root mean square error, Integral square error and Pbias were considered to be the best fit model. Based on the selected criteria, the performance of ANN model with 6-8-8-1 architecture with Log-SigmoidAxon transfer function with back propagation and Levenberg-Marquardt learning rule having past 1, 2, 3, 4, 5 and 6 months rainfall as inputs was found better than the other models.
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    ThesisItemOpen Access
    Spatio-temporal water spread mapping of various lakes in Nainital district of Uttarakhand using GIS and satellite data
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2019-05) Deoli, Vaibhav; Deepak Kumar
    Surface water has been using regularly for drinking purpose as well as for agriculture, domestics and industrials uses. Hence, identification and mapping of waterbodies may be important to estimation of water quantity, changes detection, flood estimation and so on. In this study, mapping of water spread areas of Nainital Lake, Bhimtal Lake, Sattal Lake and Naukuchiatal Lakes have been studied. All lakes are situated in Nainital District of Uttarakhand State of India. To study the water spread areas for duration of 17 years from 2001-02 to 2017-18 of these lakes, Landsat-8 OLI and Landsat-7 ETM satellites have been used. To calculating areas of the studied lakes, each study year has been divided into three periods such as October to February, March to June and July to October. Water spread areas of all lakes have been calculated based on the 4 water indices namely NDWI, MNDWI, WRI and NDVI. To know the performance of these water indices and accuracy analysis physically GPS survey of all lakes has been conducted. Based on this GPS survey, WRI has been determined most accurate water index and based on this correct areas of all lakes has been calculated. To know the trend in water spread areas, Mann-Kendall test has been used to know the trend and San’s slope estimator test has been used to calculating magnitude of trend and percentage changes in water spread areas of all studied lakes. The depth of the lakes has been measured also at 10 different location for each lake and based on these 10 depths average depth of all lakes has been determined in pre-monsoon season of year 2019. After knowing the depths and areas of all lakes volume of water for all lakes has been calculated. This type of study, may be very helpful in state like Uttarakhand where physical mapping is difficult due to tough topography.