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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.
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ThesisItem Open Access STUDY OF GROUND WATER BALANCE AND CARBON EMISSION DUE TO GROUND WATER ABSTRACTION IN RPCAU CAMPUS PUSA(Dr.RPCAU, Pusa, 2021) SINGH, SACHINDRA KUMAR; Chandra, RavishGroundwater is the most preferred water source in various user sectors in India due to its near universal availability, reliability and low capital cost. Groundwater resource estimation is essential for planning and management and distribution of precious ground water resource and gives us insight to allocate groundwater to various sectors like agriculture, water supply, drinking water judiciously. There is an urgent need to study the annual ground water draft, annual ground water recharge to compute the complete evaluation of ground water resource and ground water balance for future possible corrections. Keeping the above things in mind a study in “Study of Ground Water Balance and Carbon Emission due to Groundwater Abstraction in RPCAU Campus Pusa” was undertaken to estimate annual ground water recharge, annual ground water draft, and annual ground water balance for Dr Rajendra Prasad Central Agricultural University Pusa Campus. The study was conducted for three years (2018 to 2020). The GEC norms 1997 was used to estimate annual ground water recharge, annual ground water draft and ground water balance for the study area. This methodology uses the water table fluctuation technique and empirical formula for recharge calculation. The data collected for this investigation were water table fluctuation, annual rainfall, normal rainfall, number of tubewells, brand of tubewells, Power rating of tubewells, tubewell discharge, operating hours and other details of pumping system, hydrology of the area, specific yield, ground water draft, pond area etc. In the present study, the energy consumption and carbon emission through groundwater abstraction in the RPCAU Pusa campus were also studied. The energy required for groundwater abstraction was estimated as per the methodology provide by Rothausen and Conway, 2011. The carbon emission through pumping of groundwater was calculated by using the methodology given by Nelson and Rothausen, 2008.The annual ground water draft used for water supply was found to be 118.2 ha-m, 122.9 ha-m and 111.9 ha-m respectively for the year 2018, 2019 and 2020 and the annual ground water draft used for irrigation water supply was found to be 104.8 ha-m, 105.9 ha-m and 84.6 ha-m respectively for the year 2018, 2019 and 2020 The total annual ground water recharge for the year 2018, 2019 and 2020 was found to be 108.43 ha-m, 140.49 ha-m and 194.1 ha-m respectively. The stage of ground water development for the year 2018, 2019, and 2020 was found to be 205.7 %, 162.9 % and 101.2 % respectively. The energy requirement for municipal water supply was found to be 239186.5 kWh, 243770.2 kWh and 223198.8 kWh respectively for the year 2018, 2019 and 2020. The energy requirement for irrigation water supply was found to be 155571.6 kWh, 157235 kWh, and 125622.05 kWh respectively for the year 2018, 2019, and 2020. The total carbon emission due to ground water pumping was found to be 97.2 ton, 99 ton and 90.7 ton respectively for the year 2018, 2019 and 2020. The total carbon emission due to irrigation water was found to be 63.2 ton, 63.9 ton and 51 ton respectively for the year 2018, 2019 and 2020.ThesisItem Open Access ASSESSMENT OF SURFACE WATER RESOURCE IN SAMASTIPUR DISTRICT OF BIHAR USING RS AND GIS(DRPCAU, PUSA, 2021) G M, RAJESH; Prasad, SudarshanThe study region, Samastipur district of Bihar surrounded by 5 km buffer zone was divided into 67 square grids of 8 km × 8 km spatial resolution using (ArcGIS) software version 10.7.1. The monthly rainfall images (TRMM_3B43) for the period of 20 years from the years of 2000 to 2019 and the monthly dataset of LST (GLDAS_NOAH025_M_EP) products of 0.25o × 0.25o grid size for the period of 21 years from 2000 to 2020 were downloaded and used for analysis. The climatic variables viz. monthly rainfall and LST values were extracted for all grid points (GP-1 to GP-67) using the model builder tool of ArcGIS. Following the recommendation of WMO, the 14 grid points between GP-44 and GP-66 falling under the circumferential coverage of 3000 km2 (radius of 30.90 km) in flat area from MS, Pusa were considered for comparison and validated with ground-based climatic variables measured at MS, Pusa. The graphical technique and statistical techniques like Pearson correlation coefficient (PCC), mean error (ME), root mean square error (RMSE), bias (B), and Percent bias (PB) were used for comparison. Bias in extracted climatic variables was identified and was corrected using linear scaling. The Landsat-8 imageries were used to develop LULC using supervised classification technique in ArcGIS. The accuracy assessment was carried out using visual observation, Google Earth image, mathematical analysis and the kappa coefficient. The validated soil map of the study area was procured from NBSS and LUP, Nagpur, India and reclassified into soil textural classes. The available water capacity (AWC) of the soil was computed based upon the land use, soil texture and rooting depth following the suggestion of Thornthwaite and Mather (1957). The surplus and deficit water for all the grid points area was estimated using computed monthly PET, AET and AS as input parameters. Thematic maps of potential evapotranspiration, actual evapotranspiration and availability of surplus and deficit water over the study area were developed using inverse distance weighted interpolation technique of ArcGIS. The study investigated that estimated PET was progressively increasing from January to June and thereafter gradually decreasing from July to December. PET was found maximum (120.7 mm) for the month June and minimum (5.5 mm) for the month January and similar pattern were observed in case of AET. During the months of July (85.3 mm), August (83.9 mm) and September (81.1 mm), AET and PET were found to be equal. The LULC map depicted the five types of land use feature classes viz. agricultural land, barren land, forest land, settlement and water body in the region. Silt loam, clay loam and clay were observed as major soil textural classes distributed in the study region. The study area undergoes an annual water deficit of 121.2 mm distributed during the months of February to May, November and December whereas, the annual water surplus of 523.8 mm during the months of January, July to September.ThesisItem Open Access Assessment of land use/land cover changes in Samastipur district of Bihar using RS and GIS(DRPCAU, PUSA, 2021) KUMAR, JITENDRA; Sahu, R. K.The assessment and analysis of land use/land cover (LULC) changes are required to identify the land use changes from year to year which plays a critical role in planning and implementation of developmental activities. The present study assesses LULC changes in Samastipur district of Bihar using remote sensing and geographical information system. The inventory map of land resources and water bodies have been prepared using satellite data of the year 2020 and the ground truth data. The LULC maps were prepared using LANDSAT-5 (2000, 2005 and 2010) and LANDSAT-8 (2015 and 2020) images by adopting object based image classification technique. Total five classes of LULC- agriculture land, settlement, natural vegetation, sand/barren land and water-bodies were identified for the present study. Accuracy percentage of the classification was assessed based on the error matrix and kappa coefficient. Assessments of LULC changes were done @ 5 years, @ 10 years and @ 20 years during 2000-2020. The developed inventory map indicated that the total area of Samastipur district is 290000 ha out of which 284689 ha (98.17%) has been occupied by land resources and 5311 ha (1.83%) by water bodies. The results on LULC indicated that the agriculture land coverage increased at high rate during 2000-2005 and 2005-2010; and after that it is increasing at slow rate. The natural vegetation coverage is continuously decreasing during years 2000-2020 while settlement is continuously increasing during this period with notable increase during 2000-2005 and 2015-2020. In the time interval of 10 years (2000-2010), the agriculture land area increased by 22.17% (41295 ha); natural vegetation area decreased by 38.04% (22905 ha); the water-bodies decreased by 46.69% (3683 ha); sand and barren land decreased by 61.27% (16151 ha) and settlement area increased by 15.62% (1444 ha). Over the next 10 years (2010-2020), area covered by agriculture land, settlement, water-bodies and sand and barren land increased by 18320 ha (8.05%), 4093 ha (38.30%), 1105 ha (26.27%) and 4558 ha (44.65%) respectively while area covered by natural vegetation decreased by 28076 ha (75.24%). During time interval of 20 years (2000-2020), agriculture land area and settlement area increased by 32% (59615 ha) and 59.91% (5537 ha) respectively while natural vegetation, sand and barren land and water-bodies decreased by 84.66% (50981 ha), 43.98% (11593 ha) and 32.68% (2578 ha) respectively. The analysis of the results indicates that the natural vegetation has decreased at fast rate in the recent years. Therefore, proper attention is required towards stopping of cutting of natural vegetation in the district to save the environment.ThesisItem Open Access Development of drainage plan for waterlogged areas of Darbhanga district using remote sensing and GIS approach(DRPCAU, Pusa, 2020) D, Sudhakar Raj; Bhagat, I. B.In India, rainfall is variable which causes flood and drought frequently. In Bihar, out of 38 districts, 28 districts will become flooded and 15 districts among them will get extremely affected in every consecutive year. Nearly, 73.63% of the geographical area of North Bihar is considered to be prone to floods. Next to flood, congestion in drainage of surface water resulting into water-logging is another major serious problem in the Bihar state. The combined use of remotely-sensed images and GIS based environmental applications in this work is needed for systematic ideas and scientific planning in the Darbhanga district of Bihar. Image processing and water-logged area assessment was done using ArcGIS and eCognition software. The index-based classification method was followed in an ArcGIS software and as a result, various indices such as NDVI, NDWI, MNDWI (Esri), MNDWI (IHS) had been obtained to assess the water-logged portions. Among the various indices used in different months False Colour Composite image, it was found that the month of September (2017) is the best month to indicate, assess and delineate the water-logged areas. Comparison with the other indices, MNDWI was highlighting the water-logged portions in the better way. The object-based classification was carried out in eCognition software which will convert the pixels into objects. The water-logged boundary layer was extracted by using the threshold value of -0.175 in the September month MNDWI raster. The total area subjected to water-logging in the Darbhanga district was found to be 42,282 ha. The area of water-logging was found in the two sub-divisions of the Darbhanga district. The blocks of Darbhanga and Biraul sub-division, holding the water-logging area of 21,899 ha and 20,383 ha respectively. The maximum expected rainfall at 60 per cent, 70 per cent and 80 per cent probability levels were found using Weibull’s formula and 70 percent maximum rainfall of consecutive days was considered for the drainage characteristics which have been analysed with the formula of volume-balance method. The average pan evaporation loss was estimated as 0.385 cm per day. The average percolation loss was found based on the previous research works and considered for analysis of drainage characteristics. The drainage coefficient of consecutive days i.e., 1-,2-,3-,4-,5-,6- and 7- days for the blocks of Darbhanga sub-division was found to be 27.71, 16.93, 12.57, 10.42, 9.19, 8.35 and 1.60 cm per day respectively and for the blocks of Biraul sub-division it was computed as 18.12, 10.94, 8.07, 6.66, 5.85, 5.31 and 4.79 cm per day respectively. The surface drainage plan for the blocks of Darbhanga and Biraul sub-divisions have been expressed by showing the main drain lines and outlets which was based on the comparison of different thematic maps. The useful measures also have been suggested to execute the drainage plan in an active manner.ThesisItem Open Access Standardization of Irrigation and fertigation schedule for Tomato cultivation under soil less media(DRPCAU, Pusa, 2020) Umashanker; Nirala, S. K.The research work entitled “Standardization of Irrigation and Fertigation schedule for Tomato cultivation under Soil Less Media” was conducted with eighteen treatments. The treatments comprised with different soil less media like Cocopeat, Perlite,Vermiculite,Vermicompost and sand along with three levels of RDF and two levels of irrigation. The tomato plants planted in grow bags irrigation and fertigation applied with drip irrigation system. Tomato crop of variety Avinash-2 was selected for experiment. The field layout done by using CRD with three replications. The seasonal crop water requirement of tomato plants in soilless media in grow bages cultivation varies from 12.72 to 15.90 cm under irrigation level 80% and 100% Etc.The best growing media was foundCocopeat + Perlite + Vermicompost (3:1:1). The composite effect of growing media, irrigation and fertigation on vegetative growth and yield parameters (fruit length, fruit diameter, numbers of fruit per plant, fruit weight, yield per plant) was found better in treatment M1I2F1 (Cocopeat + Perlite + Vermicompost + 0.80 ETc + 125 % RDF). The maximum average vegetative growth was recorded as 102.12 cm, fruit length 5.55 cm, maximum diameter 5.29 cm, average numbers of fruit per plant 63.73, average fruit weight 90.82 g, and maximum yield 5.23 kg per plant was recorded. However, the minimum yield was (2.88 Kg) under M1F3I2 treatment. The B: C ratio of 3.12 and maximum net income of Rs 211211/- per 1000 m2 in treatment M1I2F1 and minimum B: C ratio of 1.46 in treatment M1F3I2 (control).ThesisItem Open Access Drought assessment and impact of land use land cover change on surface water extent of Bihar using remote sensing and GIS(Dr. Rajendra Prasad Central Agricultural University, Pusa, Samastipur, 2019) Bhawana; Prasad, SudarshanThe captured satellite datasets using advanced techniques such as remote sensing (RS) and its processing to extract the information using geographic information system (GIS) have been used for detection of droughts and its mapping for the Bihar state. Meteorological droughts over various places of Bihar during monsoon season were identified using standard precipitation index (SPI) through software for SPI computation. The daily rainfall estimates of time duration of 67 years from 1951 to 2017 extracted from satellite datasets viz. Asian Precipitation Highly Resolved Observational Data Integration towards evaluation of water resources (APHRODITE) of duration 47 years from 1951 to 1997 and Tropical Rainfall Measuring Mission (TRMM) of duration 20 years from 1998 to 2017 were used for the purpose. The whole area of the state was divided into total number of 301 grid points of 0.25° × 0.25° resolutions and monthly time series of rainfall (mm) estimates were obtained for each grid points from daily rainfall estimates obtained from TRMM and APHRODITE. These datasets of monthly time series were validated with rainfall data of monthly time series of 20 years duration from 1998 to 2017 observed at rain gauge station, Pusa using statistical techniques Thus, spatio-temporal maps of SPI based meteorological drought were developed for the years 2000 to 2017 for the area under study. Vegetation condition index (VCI) estimated through MODIS NDVI products obtained from USGS Earth Explorer for Bihar state were composited for Kharif and Rabi season from year 2000 to 2017. Spatio-temporal maps of NDVI and VCI for Kharif as well as Rabi season were developed based on vegetation indices for the years from 2000 to 2017. Using LANDSAT-5 (TM) and LANDSAT-8 (OLI/TIRS) imageries unsupervised image classification was performed. The Land use-land cover maps were generated for the years 2008 and 2018 with six feature classes namely agricultural land, settlement, vegetation, waste land, water body and sand were identified. Analysis of SPI revealed that the year 2006 experienced moderate dry conditions in the districts like Kishanganj, Araria, Purnea, Katihar and Gopalganj. In the year 2013 districts like West Champaran, Saran, Gopalganj Sheohar, Vaishali, Muzaffarpur and Samastipur faced moderately dry conditions repeating the trend in 2016. In all the years from 2000-2017 majority of the study area experienced mild drought. However, in case of 2007, almost all the districts of the study area having the extreme wet condition because of high rainfall during monsoon season. The temporal variation of NDVI in the year from 2000 to 2017 showed that most of the south-western districts of the state noticed the low value of NDVI ranging from 0.2 to 0.4 during Kharif season of almost all years. During the wet year of 2007, the high value of NDVI (>0.5) was noticed in almost every district except Samatipur, Darbhanga and Khagaria which experienced highly wet condition. During entire period of analysis lush vegetation with high value NDVI of more than 0.6 was noticed except for Banka and Jamui districts which experienced moderately dry condition in almost every year from 2000 to 2017. Spatio-temporal maps with varying VCI, showed the moderate to no drought conditions in the study area. In the year 2000, extremely good vegetation condition was observed decreasing in each year especially in the year 2005 in which almost entire area experienced low value of VCI ranging from 0.5 to 0.2 indicating fair vegetation condition. During Rabi season districts like Banka and Jamui show consistent poor vegetation condition in the years from 2000 to 2016. Analysis of Land use-land cover map for the years 2008 and 2018 depicted that there was drastic change in most of the feature classes. The water body shrinked to 2.13 % with areal loss of water body by 35.74 km2.ThesisItem Open Access Impact assessment of change in land use land cover and rainfall pattern on soil erosion potential of Irga river catchment (Jharkhand) using remote sensing and GIS techniques(Dr. Rajendra Prasad Central Agricultural University, Pusa, Samastipur, 2019) Yadav, Shankar; Sahu, R.K.Soil erosion is a major form of land degradation and has been recognized as a severe environmental problem. The present study was conducted in Irga catchment situated in Giridih district of Jharkhand. Image processing and soil erosion assessment is done using eCognition and ArcGIS softwares. The land use land cover map of 1997, 2007 and 2017 were prepared using LANDSAT images by object-based image classification technique having better accuracy than traditional pixel based image classification. The Land use land cover maps were classified into six classes viz. agricultural land, settlement, vegetation, waste land, water body and river. Using RUSLE integrated with RS and GIS, soil erosion map was prepared for the study area. For preparing soil erosion map, R factor was derived from TRMM rainfall data of ten years (2008 to 2017), K factor from DSMW prepared by UN FAO and LS factor from SRTM DEM. The C and P factor values were assigned according to LULC map based on reviewed works. The overall accuracy of classified images are computed to be 88%, 83% and 91 % while kappa coefficients are found to be 0.8455, 0.7706 and 0.8796 for year 1997, 2007 and 2017 respectively. The results indicate that waste land greatly reduced and converted into settlement and agricultural land. In application of RUSLE model for Irga catchment, R factor varied from 499.834 to 538.049 MJ mm h-1 ha-1 yr-1and K factor varied from 0.0159 to 0.0191 t ha h ha-1 MJ-1 mm-1 for year 2017. The generated LS factor map of the study area showed that it varied from 0.03 to 41.09. C and P factor varied from 0 to 1. The estimated value of soil loss from the catchment varies from 0 to 36.1185 t /ha/yr with mean value as 0.2814 t/ha/yr. The results indicate that the study area has very slight and slight erosion class. Further, using 10 year rainfall data of 1998 to 2007 and LULC map of 2007, the soil erosion potential map for the year 2007 was also generated. The value of soil loss varies from 0 to 44.2149 t/ha/yr for this year with mean value as 0.3057 t/ha/yr. The mean value of the soil erosion potential has decreased by 8.6049 % over the period of 10 years (2007-2017) which reveals that the changes in LULC and rainfall pattern greatly affect the soil erosion potential. The results of the present study also reveal that object-based image classification technique gives higher accuracy for image classification as compared to pixel-based classification. Further, integrated use of RUSLE with RS and GIS technique is effective and powerful tool for estimation of soil erosion.ThesisItem Open Access Effect of Fertigation and Plastic Mulching on Capsicum cultivation under Polyhouse(Dr. Rajendra Prasad Central Agricultural University, Pusa (Samastipur), 2018) Kumari, Sadhani; Nirala, S. K.The research work entitled “Effect of Fertigation and Plastic Mulching on Capsicum cultivation under Polyhouse” was carried out under eighteen treatments with three level of irrigation, three level of fertigation with plastic mulch and without plastic mulch with three replications. Indra variety of capsicum was selected for experiment. The field layout design was done by using Randomized Block Design (RBD). The monthly crop water requirements was computed for the months of October, November, December, January, February, March and April, it was found as 2.17 cm, 1.8 cm, 1.24 cm, 0.93 cm, 3.36cm, 7.13cm and 9.0cm, respectively. Overall, in terms of the total depth of water requirement of capsicum during the entire crop period was estimated to be 25.63cm. The composite effect of irrigation, fertigation and mulching on vegetative growth, number of branches, yield parameter (number of fruit per plant, fruit weight, yield per plant) and quality of fruit(diameter of fruit, length of fruit) was found to be better in treatment T2(I1F1M1, i.e.,120 % RDF with 100% WR through drip with plastic mulch). The maximum diameter of capsicum fruit was recorded 8.37 cm, length of capsicum fruit11.72 cm, maximum number of fruits per plant 12.5, height fruit weight 168.00 gram, height yield (kg/plant)2.44 kg and height yield 93.74 t/ha in treatment T2. The maximum water use efficiency was found in treatment 62.49 (kg/ha-cm) and fertilizer use efficiency was found 101.67 in treatment T2.The maximum benefit cost ratio was estimated to the tune of 2.99 in treatment T2 followed by 2.21 in treatment T4.ThesisItem Open Access Performance Evaluation of FAO-AquaCrop Model for Maize crop in Eastern Part of Indo-Gangetic Plain(Dr. Rajendra Prasad Central Agricultural University, Pusa (Samastipur), 2018) Kumar, Vicky; Chandra, Ravishhe present study was undertaken to study the response of different level of irrigation on crop growth, yield, biomass and water use efficiency of Rabi maize under North Bihar condition. A further field investigation was also undertaken to evaluate of FAO-AquaCrop model for Rabi maize under different level of furrow irrigation at experimental field of AICRP on Irrigation Water Management, Dr. RPCAU, Pusa (Samastipur), Bihar. Crop growth, yield, biomass and water use were measured under different treatments. The AquaCrop model was used to simulate Rabi maize yield and biomass under full deficit irrigation and rainfed treatments. Evaluation of AquaCrop model was accomplished using the observed values from field experiment during 4th Nov. 2016 to 13th April 2017 for Rabi maize. The biometric parameters like plant height, stem diameter, number of leaves and canopy spread were significantly superior in treatment T1(control/full irrigation) compared to other deficit irrigation and rainfed treatments. The biometric parameters like plant height, stem diameter, number of leaves and canopy spread for treatment T1(control/full irrigation) was 179.80 cm, 29.90 mm, 12 and 87.70 cm respectively. Rabi maize yield was highest for treatment T1 with a value of 11.12 t/ha, followed by treatment T2 (75% of CI) with a value of 10.98 t/ha and lowest for treatment T4 (Rainfed) with a value of 3.35 t/ha. Biomass was highest for treatment T1 (CI) with a value of 24.92 t/ha, followed by treatment T2 (75% of CI) with a value of 24.65 t/ha and lowest treatment T4 (Rainfed) with the value of 7.931 t/ha. The crop yield and biomass were significantly higher for treatment T1 (control/full irrigation) compared to other treatments. The water use efficiency of Rabi maize yield decreased with increase in irrigation level for all treatments of furrow irrigation. Water use efficiency was highest for treatment T3 with a value of 310 kg/ha-cm followed by treatment T2 with a value of 303 kg/ha-cm. The water use efficiency was significantly higher treatment T3 (50% of CI) compared to other treatments. The adapted values of canopy growth coefficient and canopy decline coefficient were 15.4% day-1 and 9.5% day-1 respectively for Rabi maize. The days of emergence, sowing to flowering, senescence and maturity were 6, 60, 142 and 161 days respectively. The adopted values of water productivity (WP) were obtained as 30.7 g m-2. The harvest index was obtained as 48%. The AquaCrop model evaluated for grain yield and biomass under different irrigation levels resulted in prediction error ranging from 2.25% to 9.59% and 2.44% to 11.84% respectively. The AquaCrop model was evaluated for simulation of grain yield and biomass of Rabi maize for all treatment with the prediction statistics 0.971 < E < 0.988, 0.221 < RMSE < 0.731, 0.987 < R2 < 0.997 and 0.421 < MAE < 0.806 t ha-1. The AquaCrop model predictions for grain yield and biomass of Rabi maize were in line with the observed data corroborated with E and R2 values approaching one. The AquaCrop model was more accurate in predicting the maize yield under full and 75% of CI as compared to the rainfed and 50% of CI.
