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20225
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Subject: Agricultural Meteorology × End date: 2022 × Start date: 2022 × Type: Thesis × Thesis Type: M.Sc ×
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Now showing 1 - 5 of 5
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    ThesisItemOpen Access
    Quantification of evapotranspiration using EEFLUX tool and comparison by empirical methods in maize (Zea mays L.)
    (Punjab Agricultural University, Ludhiana, 2022) Deepan R; Som Pal Singh
    Evapotranspiration (ET) is one of the most important parameter in agriculture and to water management and irrigation requirement. Under the present scenario of Climate change and Global warming, importance of ET measurement and its validation assumes a great significance. There are various techniques used to estimate actual measurement of ET in the field condition. However, researchers have developed state of the art instrument to measure it in the field condition and instruments of varying accuracy are available. The instrument can measure point value of ET for being placed at particular location in the field and therefore the spatial accuracy of the data is bound to reduce to a certain extent. On the other hand, the empirical estimation of ET has its own limitation owing to the requirement of huge data set to estimate the ET to near accuracy. Google EEFlux is a web-based tool which utilizes the satellite-based information to provide the ET rate on spatio-temporal scale. Therefore, an effort has been put forth to estimate ET using the Google EEFlux for maize crop. The ET has been estimated using the Google EEFlux for maize crop sown in the field experiment at the Research Farm, Department of Climate Change and Agricultural Meteorology, PAU during the kharif season of 2020-21. The ET was also computed using Penman’s equation geeSEBAL, NRSC-NHP, Cropwat 8.0 and FAO Ref-ET calculator for PMH-1 and PMH-2 varieties of maize during the same period grown under three sowing environments. The relationships were developed between ET (Google EEFlux), ET (geeSEBAL), ET(NRSCNHP) and ET (FAO-ETo calculator). The relationships indicated a significant association between the ET obtained by both these methods. The data generated can help the researchers to fine tune treatments and also to reorient the irrigation and management research programs.
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    ThesisItemEmbargo
    Assessing climatic and environmental implications of crop residue burning in Punjab using ground observations and satellite remote sensing
    (Punjab Agricultural University, Ludhiana, 2022) Yashi Singh; Kingra, P.K.
    The study entitled, “Assessing climatic and environmental implications of crop residue burning in Punjab using ground observations and satellite remote sensing” was conducted at the Department of Climate Change and Agricultural Meteorology, PAU, Ludhiana and Punjab Remote Sensing Centre, Ludhiana. Variability in meteorological variables (temperature, relative humidity, wind speed and sunshine hours), gases (NO2, SO2 and O3) and aerosols (PM2.5 and PM10) in wheat (March-May) and rice harvesting season (September-November) from 2017-21 was analyzed. In addition to this fire events data was collected through remote sensing (from VIIRS) for the same period. In Punjab, maximum burning points were observed in central region followed by south west region and north-east region. In central region, highest fire counts during wheat harvesting period were observed in 2019 (11602) and lowest in 2021 (7104), whereas for rice harvesting period they were highest in 2021 (40960) and lowest in 2019 (22548). Significant influence of crop residue burning was observed on the concentration of particulate matter in air as it increased drastically during crop harvesting period. During wheat harvesting season, Ludhiana experienced highest concentration of PM2.5 (85.66±26.49 µg/m3 ) and PM10 (160 ±43.49 µg/m3 ) during May 2018, whereas concentration of SO2 (15.54±4.24 µg/m3 ) and O3 (40.12±6.70 µg/m3 ) was observed highest in May 2019 and during rice harvesting season, Ludhiana experienced highest concentration of PM2.5 (140.83±49.37 µg/m3 ) and PM10 (305±97.45 µg/m3 ) during November 2017, whereas concentration of SO2 was observed highest (23.50±13.20 µg/m3 ) during 2018. However highest concentration of NO2 (47.12±15.33 µg/m3 ) was observed in October 2018 and of O3 (32.19±8.91) was observed in October 2020. Particulate matter (PM2.5 and PM10) depicted strong positive correlation with fire counts in all the agroclimatic regions of Punjab in the harvesting period of wheat and rice whereas somewhat variable relation was observed for NO2 and SO2. Mean temperature during November was found to be positively correlated while relative humidity and sunshine hours were observed to have negative correlation with fire events for most of the wheat and rice harvesting period. The results of the study indicated that crop residue burning is specifically responsible for increasing the amount of particulate matter in air which can have severe health implications.
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    ThesisItemEmbargo
    Applicability of medium range weather forecast in respect to growth and yield attributes of wheat in south-west Punjab
    (Punjab Agricultural University, Ludhiana, 2022) Tirath Singh; Raj Kumar Pal
    The current study evaluates the predictability of wheat production using forecast scenarios that were gathered from the IMD in order to evaluate the potential of the wheat season weather forecast. CERES-Wheat model was used to estimate crop phenology and wheat yield. In this regard, the experiment was carried out in a split-plot design at Punjab Agricultural University (PAU), Regional Research Station, Bathinda (30°36'09" N, 74°28'55" E) during the rabi season of 2021 with three replications. The main plot treatments included five sowing dates viz., October 25, November 04, November 14, November 24 and December 04 with four sub-plot treatments of variety which were HD 3086, PBW 725, HD 2967, PBW 658. All the cultural practices were followed as per the package of practices of Punjab Agricultural University except the experimental treatments. Model validation showed that simulated emergence, anthesis and maturity were deviated over observed by 1-3 days, 1-8 days, and 1-20 days, respectively, whereas anthesis, maturity, and yield were overestimated. Additionally, the simulated wheat yield differed from the observed yield by 0.5 to 12 per cent. Phenology and yield were found to have greater RMSE values, wider deviations between simulated and actual values, and less connection with delayed sowing. For the wheat growing season (2013–2021), rainfall, Tmax, and Tmin weather forecast were employed, which wereto assess the likelihood of wheat production at various sowing periods. The medium-range weather forecast and the actual weather data closely matched each other for wheat phenology and yield. The annual fluctuation in observed wheat yield as well as treatment-wise variations were more or less effectively reflected by the daily medium-range weather forecast data. The research's conclusions are very useful for making decisions in the study region, determining when to sow wheat and other agricultural inputs, and developing long-term plans for other agricultural chores.
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    ThesisItemEmbargo
    Evaluation of medium range weather forecast for the prediction of phenology and yield of cotton in southwestern region of Punjab
    (Punjab Agricultural University, Ludhiana, 2022) Sanyam; Pal, Raj Kumar
    In order to assess the potential of the forecast during cotton season, the current study examines the predictability of cotton productivity using value-added medium-range forecast scenarios using CROPGRO-cotton model. In this regard, experiment was carried out at Punjab Agricultural University (PAU) Regional Research Station, Bathinda, (30°58‟N, 74°18‟E) during the kharif 2021. The experiments were laid out with Bt cotton hybrid RCH 776 and RCH 773 and Non-Bt was F2228 and LH2108 and sown at five dates i.e. April 25, May 05, May 15, May 25 and June 04 in split-plot design with three replications. Model validation using actual weather data showed underestimation in respect of emergence and almost overestimation for anthesis, maturity and yield having deviation over observed by 1-3 days, 1-6 days, 1-22 days and 0.5 – 12%, respectively. Moreover, medium range weather forecast during experimental period followed the similar trend and indicated deviation by 1-3 days (emergence), 1-7 days (anthesis), 1-16 days (maturity) and 0. 1– 10.33% (seed cotton yield). Deviation in simulated value over observed was found increased for phenology and yield having higher value of RMSE and lesser correlation with delayed sowing. To assess the prospect of cotton productivity at different sowing time, cotton growing period forecast (Premonsoon and monsoon) of Rainfall, maximum temperature and minimum temperature were used during 2013-2021. Medium range weather forecast showed close agreement with the observed weather data for phenology and yield of cotton. The daily medium range weather forecast data showed more or less significant efficiency to capture year-to-year as well as treatment-wise variability in observed cotton yield. The results of the study are very useful for taking decisions in the study region, for selection of appropriate time for sowing of cotton as well as other input management and farm activities well in advance.
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    ThesisItemOpen Access
    Impact analysis of precipitation and groundwater behaviour in Punjab by using stochastic model technique
    (Punjab Agricultural University, Ludhiana, 2022) Arpna; Gill, K. K.
    Agriculture in India is mostly rainfed and is greatly influenced by summer monsoon. It contributes about 75 % of the total rainfall. The historical data of rainfall (1951-2018) and groundwater (1998-2018) for different zones of Punjab viz. Sub-mountain undulating zone, Undulating plain zone, Central plain zone, Western plain zone and Western zone were collected from the Meteorological Department, New Delhi and Department of Soil & Water Engineering, PAU, Ludhiana, respectively. The data of area and productivity of major crops of Punjab viz. rice, wheat, maize, cotton and mustard were collected from Statistical Abstract of Punjab. Rainfall Anomaly Index revealed that maximum dry and wet years during 19512018 has been observed in Hoshiarpur (37 years) and SAS Nagar (32 years), respectively. The extreme rainfall events during the last 2 decades (2001-10 and 2011-18) showed decreasing trend as compared to the previous decades (except Amritsar, Bathinda, Patiala, SAS Nagar and Tarn Taran). Mann-kendall test exhibited the decreasing trend of rainfall in the month of January, July, August, October and increasing trend of rainfall in the month of February, April, May, June, September, November has been noticed in most of the districts. Decade wise rainy days showed the decreasing trend during annual period and post monsoon rainy days, whereas monsoon and pre monsoon rainy days presented the increasing trend from the last few decades. The groundwater table showed significant decrease in groundwater level depth in all the districts except Mukatsar district. Standard Groundwater Level Index (SGI) exhibited that non drought years from 1998 to 2018 observed as highest at SAS Nagar and drought year were highest at Kapurthala. Relationship between groundwater, area and productivity of the major cropping system revealed that productivity of the cropping system has been increased with the decline in water table while the area under major cropping system have been deceased except rice-wheat cropping system.