Thumbnail Image

Dr. Rajendra Prasad Central Agricultural University, Pusa

In the imperial Gazetteer of India 1878, Pusa was recorded as a government estate of about 1350 acres in Darbhanba. It was acquired by East India Company for running a stud farm to supply better breed of horses mainly for the army. Frequent incidence of glanders disease (swelling of glands), mostly affecting the valuable imported bloodstock made the civil veterinary department to shift the entire stock out of Pusa. A British tobacco concern Beg Sutherland & co. got the estate on lease but it also left in 1897 abandoning the government estate of Pusa. Lord Mayo, The Viceroy and Governor General, had been repeatedly trying to get through his proposal for setting up a directorate general of Agriculture that would take care of the soil and its productivity, formulate newer techniques of cultivation, improve the quality of seeds and livestock and also arrange for imparting agricultural education. The government of India had invited a British expert. Dr. J. A. Voelcker who had submitted as report on the development of Indian agriculture. As a follow-up action, three experts in different fields were appointed for the first time during 1885 to 1895 namely, agricultural chemist (Dr. J. W. Leafer), cryptogamic botanist (Dr. R. A. Butler) and entomologist (Dr. H. Maxwell Lefroy) with headquarters at Dehradun (U.P.) in the forest Research Institute complex. Surprisingly, until now Pusa, which was destined to become the centre of agricultural revolution in the country, was lying as before an abandoned government estate. In 1898. Lord Curzon took over as the viceroy. A widely traveled person and an administrator, he salvaged out the earlier proposal and got London’s approval for the appointment of the inspector General of Agriculture to which the first incumbent Mr. J. Mollison (Dy. Director of Agriculture, Bombay) joined in 1901 with headquarters at Nagpur The then government of Bengal had mooted in 1902 a proposal to the centre for setting up a model cattle farm for improving the dilapidated condition of the livestock at Pusa estate where plenty of land, water and feed would be available, and with Mr. Mollison’s support this was accepted in principle. Around Pusa, there were many British planters and also an indigo research centre Dalsing Sarai (near Pusa). Mr. Mollison’s visits to this mini British kingdom and his strong recommendations. In favour of Pusa as the most ideal place for the Bengal government project obviously caught the attention for the viceroy.

Browse

20225
Reset filters
Subject: Soil and Water Engineering × End date: 2023 × Start date: 2022 × Type: Thesis ×
Reset filters

Search Results

Now showing 1 - 5 of 5
  • Thumbnail Image
    ThesisItemOpen Access
    Study on Water and Nutrient Movement and Root Growth Pattern in Tomato Crop under Drip Irrigation
    (DRPCAU, PUSA, 2022) Kumar, Abhinav; Nirala, S.K.
    The research work entitled “Study on Water and Nutrient Movement and Root Growth Pattern in Tomato Crop under Drip Irrigation” was conducted with ten treatments. The treatments comprised with differentreplicationwith different RDF level.Tomato crop of varietyAnsal (Hybrid) was selected for experiment. The field layout was done by using RBD with three replications. The tomato plants planted in experiment field with drip irrigation and fertigation. The water movement at the depth of 0-5 cm varies from 16 -31 %. At depth of 5-10 cm, water content varies from 12 to 26 %. At depth of 10-15 cm, maximum moisture content was found 21 % in treatment T2. At depth of 15-20 cm moisture content 20 % in treatment T2. The results suggest that with drip irrigation, the majority of the nitrates were detected in the layer of soil 0-20 cm, as compared to flood irrigation, where more nitrates leached down 40-50 cm. In treatment T8(60 % RDF+4lph dripper) maximum nitrogen, phosphorous, and potassium content were recorded as 140.90, 92.83, and 169.11 kg ha-1 respectively whereas in T7 (60 % RDF+2lph dripper)), these values were 137.98, 90.41and 167 kg ha-1 at depth of 15-20 cm,0-5 cm,0-5 cm, respectively. In treatment T5(80 % RDF + 4 lph emitter)maximum nitrogen, phosphorous, and potassium content were recorded as 165.54,93.26 and 168.25 kg ha-1 at depth of 15-20 cm, 0-5 cm, 0-5 cm respectively, where as in treatment T4(80 % RDF + 2 lph emitter) found as 155.90, 92.69 and 168.25 kg ha-1 respectively at depth of 15-20 cm,0-5 cm,0-5 cm respectively. Similarly, in treatment T2(100 % RDF + 4 lph emitter)maximum nitrogen, phosphorous, and potassium content were recorded 165.44, 93.12, and 169 kg ha-1 at depth of 15-20 cm,0-5 cm,0-5 cm respectively. In treatment T1(100 % RDF + 2 lph emitter)recorded as 137.98, 90.41and 167 kg ha-1 respectively. Whereas in treatment T3(100 % RDF+6 lph emitter) was 197.81, 97.26, and 180.56 kg ha-1 at depth of 15-20 cm,0-5 cm, 0-5 cm respectively. In flood irrigation maximum nitrogen, phosphorous and potassium contentwas found 277.9, 209.03, and 264 kg ha-1 at depth of 40-50 cm,0-5 cm,10-15 cm respectively. The maximum yield 83.77tons ha-1was recorded in treatment T5(80 % RDF + 4 lph emitter).
  • Thumbnail Image
    ThesisItemOpen Access
    Hydrological Modeling of Burhi Gandak River Catchment, Bihar using HEC-HMS
    (DRPCAU, PUSA, 2022) PAL, SOUVIK; Kumar, Ambrish
    Hydrologic simulation has become essential tools for understanding environment and human influences on river flows and designing ecologically sustainable water management approaches. The present study was carried out in the Burhi Gandak catchment having an area of about 10913.1 sq. km up to Samastipur gauging site (outlet) using SRTM DEM. This flat and elongated watershed had a mains stream of 6th order and experiences less discharge in a short period. The length of overland flow and the constant of channel maintenance had high values, which suggests that the river catchment streams experienced delayed discharges. Due to a high percolation rate, a high chance of groundwater recharge is anticipated on mountainous terrain with a low drainage density (0.57 km-1). In the HEC-HMS, under the loss method, SCS-CN method was chosen, while in the transform method clark’s unit hydrograph and SCS unit hydrograph were chosen. For the flood routing method, the lag method was applied in the HEC-HMS model. The calibration of the model was done with Monsoon data -2020 and the validation was done with Monsoon data - 2021. During the years 2017 and 2020 Waterbodies, flooded vegetation, agricultural land and rangeland increased by 30.02%, 7.96%, 6.88% and 27.7%, respectively. There was a 16.33%, 4.6%, and 21.34% decline in the built-up area, forest land and barren land, respectively. The computed peak discharge was 1683.3, 1910, and 2292 m3/sec and the RMSE was found 0.5 in all cases – calibration, optimization and validation periods, respectively. The NSE value was 0.70, 0.78, and 0.765, the percent bias was 14.01%, 3.74%, and -3.13%, and R2 was 0.77, 0.79, 0.77, respectively for Calibration, optimization and validation. The maximum discharges of five extreme events predicted for monsoon season-2017 were found to be 1.68%, 1.98%, 2.48%, 5.05%, and 4.23% higher for monsoon season-2020, respectively. While the fiveminimum simulated discharges (2020) were higher than the minimum simulated discharge (2017) by 20%, 240%, 225%, 245.16%, and 296.23%, respectively. Due to changes in both land use and land cover during 2017 and 2020, there was an increase in the catchment's flow and a noticeable difference between the discharge in 2017 and 2020. The amount of runoff increased by 18.58% between 2017 and 2020.
  • Thumbnail Image
    ThesisItemOpen Access
    Evaluation of infiltration rate on various compaction levels in climate smart villages adopted by RPCAU
    (DRPCAU, PUSA, 2022) DAS, RIMA; Kumar, Ambrish
    The current study entitled "Evaluation of infiltration rate on various compaction levels in climate smart villages adopted by RPCAU" was conducted in the farmer's villages of Samastipur district, Bihar, in the year 2022. In this research, an overall 40 soil samples from different villages were collected for laboratory analysis at 0 to 60 cm soil depth. The soil texture of the study area ranged from loam soil to sandy loam soil to sandy clay loam soil under various cropping systems. The sand, silt, and clay content varied from 47.20 to 65 %, 8.25 to 50 %, and 10 to 40 %, respectively. Bulk density ranged from 1.05 to 1.42 g cm-3. At 0.3 bar suction, FC ranged from 15.10 to 34.58 %, and at 15 bar suction, PWP of soil ranged from 12.33 to 23.41 %. The WHC of soils ranged from 32.09 to 84 %, and OC ranged from 0.15 to 0.89 %, generally decreasing with depth and the percentage of water holding capacity also decreased. A field study was carried out to establish the infiltration rate using an instrument called double-ring infiltrometer. The results showed that the values of initial infiltration rate (mm h-1) for Kalyanpur, Akbarpur, Tira, Rampura, Ladaura, Mirzapur, Basudeopur, Birsingpur, Kabargama, Phulhara were obtained as 12.99, 10.19, 10.11, 5.91, 9.77, 6.79, 6.96, 7.39, 9.73 and 7.13, respectively. Meanwhile, the values of final steady infiltration rate (mm h-1) were 0.18, 0.12, 0.12, 0.12, 0.10, 0.12, 0.12, 0.12, 0.10 and 0.12, respectively. The four infiltration equations, namely, the Green-Ampt equation, Philip equation, Kostiakov equation and Horton equation, were used in this study. The performance evaluation of all developed equations between observed and predicted infiltration rate were analyzed based on the highest values of r ranged from -0.59 to 0.99, R2 ranged from 0.52 to 0.99, and NSE ranged from -28579.30 to 0.99, with WI ranging from 0 to 0.99 and the lowest values of RMSE ranged from 0.1 to 441.08, MAE ranged from 0.08 to 281.43. The results showed that the Green Ampt, Kostiakov, and Philip equations were more appropriate than the Horton equations. The results reveal that Horton's parameters do not fit the conditions for given locations. The average values of penetration resistance for given locations were observed 2067.20, 121290, 1859.68, 1904.32, 109681, 80863, 2432.83, 2196.45, 1524.75 and 1642.65 kPa at 0 to 60 cm depths, respectively. Linear relationship between (weightage mean of PR and constant infiltration rate) shows the value of R2 was 0.45 and significant correlations were obtained. A graphical nomograph was framed to represent three interrelating variables viz. soil texture, final infiltration rate and weighted mean of penetration resistance. A regression analysis was done between infiltration rate as dependent variables and soil parameters as independent variables including soil strength data in developing Pedotransfer Function (PTF). A regression equation had generated to show good relationship between them as R2 = 0.91.
  • Thumbnail Image
    ThesisItemOpen Access
    Analysis of Morphometric Characteristics and Land use/Land cover Dynamics of Indravati Catchment Using Geospatial Technique
    (DRPCAU, PUSA, 2022) SINHA, MADHUSUDAN; Suresh, Ram
    The present research work was conducted in the Indravati catchment which is an integral part of Godavari basin. ArcGIS software and Google Earth Engine, a cloud-based platform, were primarily used to determine the morphometric parameters and assess the dynamics of land use and cover change. The study area was first delineated using ArcSWAT tool with SRTM DEM (1-Arc-Global with 30 m resolution) in ArcGIS followed by computation of areal, relief and linear aspects along with all sub-catchments. Three sets of time periods, 2011, 2016, and 2021, were examined using LANDSAT pictures to assess the classification of land use and land cover with changing dynamics. Total six classes- waterbodies, forested areas, agricultural land, built-up areas, barrenland, and rangeland were used in the LULC classification scheme. The supervised classification scheme, Random Forest algorithm was used by the Google Earth Engine to analyse this LULC categorization. Assessment of LULC dynamics were determined by Quantum-GIS using semi-automatic classification plugin. Watershed delineation was accomplished using ArcSWAT, in which maximum and minimum elevation were found as 1361 m and 78 m with total area 40533.24 sq. km. The morphometric parameters were determined for the Indravati catchment and its nine sub-catchments such as drainage related aspects like stream order, drainage density, stream frequency, form factor, circulatory ratio etc were computed. This research showed that the 7th order was the trunk order stream, with 10810 total streams, of which the first four orders contributed 98.77 percent of the streams with a mean bifurcation ratio of 11.792 for the Indravati catchment. For sub-catchments, these parameters were also calculated. The overall accuracy and Kappa statistic for LULC classification were found to be 76.43 % and 70.38 %, 77.05 % % 71.05 % and 83.78 % and 80.16 % for year 2011, 2016 and 2021 respectively. The LULC change dynamics were observed between the years of 2011 and 2021, and it was found that, as a result of industrialization and population growth, the area extent of waterbodies, agricultural land, and rangeland decreased by -35.43 percent, -7.63 percent, and -1.32 percent, respectively, while settlement and barrenland increased by 39.34 and 55.92 percent. Since, there are tropical dense forests in this study area that become more extensive without human intervention, there has been an 8.40 percent (631.959 km2), increase in the area covered by forests. For the time periods 2011-2016, 2016-2021, and 2011-2021, it was observed that the total area of 25788.07 km2, 26844.78 km2, and 26471.19 km2 remained unchanged, whereas the areas of 14054.62 km2, 14737.74 km2, and 13681.78 km2 got considerable changes.
  • Thumbnail Image
    ThesisItemOpen Access
    Study on different Machine Learning Techniques (MLT) in forecasting Crop Water Requirement
    (DRPCAU, PUSA, 2022) Dinkar, Humbare Mrunalini; Bhagat, I. B.
    Crop water requirements must be accurately determined for irrigation scheduling, water resources management, and environmental analysis. There are several locations where different climatic data may not be accessible for its determination. In these circumstances, crop water requirement modelling is a suitable method for predicting crop water requirements. To predict the crop water requirements of rice, wheat, maize, and sugarcane in the Samastipur area of Bihar, Machine Learning Techniques such as Random Forest (RF), Multivariate Adaptive Regression Splines (MARS), Support Vector Machine (SVM) and Multiple Linear Regression (MLR) were utilised in the current study. The Meteorological department of RPCAU, Pusa, Bihar provided the data including relative humidity (maximum and minimum), and temperature (maximum and minimum) while data about solar radiation and wind speed was obtained from Prediction of Worldwide Energy Resources (NASA/POWER) website. For this study, data spanning 20 years (2001–2020) was collected. The FAO-56 Penman-Monteith method and crop coefficient approach were used to determine the water requirement for the selected crops. The Gamma test was utilized for the best input determination. The entire dataset was divided into training (80%) and testing (20%) datasets. The assessment of the models was by the Coefficient of Determination (R2), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Nash-Sutcliffe Efficiency (NSE). It can be inferred that the MLR and MARS models predicted rice crop water requirements finer than they did for other crops. The SVM model accurately predicted the water requirement of the wheat crop compared to other crops. More precisely than other crops, the RF model forecasted the water requirement for sugarcane. For all crops, the overall models' performance-wise rankings were RF, MARS, SVM, and MLR. From the results attained, the RF model beat the other three models throughout training and testing for all crops and can be highly recommended for crop water requirement prediction.