scholarly journals Assessing pre-monsoon and monsoon rainfall change signal with future projection over Gangetic West Bengal

MAUSAM ◽  
2021 ◽  
Vol 72 (3) ◽  
pp. 545-552
Author(s):  
PRAMITI KUMAR CHAKRABORTY ◽  
LALU DAS
Keyword(s):  
West Bengal ◽  
Monsoon Rainfall ◽  
India Meteorological Department ◽  
Rainfall Data ◽  
Dominant Factor ◽  
Analysis Model ◽  
Moderate Amount ◽  
Future Scenario ◽  
Crop Planning ◽  
Stake Holder

Monsoon rainfall is the dominant factor that determines the success or failure of agriculture in general. Gangetic West Bengal is not any exception. Monsoon rainfall has immense importance for growing kharif rice in this region. Whereas pre-monsoon rainfall helps farmers for proper crop planning like choosing variety etc. So assessing a long (1901-2005) and short (1961-2005 and 1991-2005) period rainfall data, its comparison with different models and construction of future scenario have utmost importance. For this purpose, rainfall data from nine selected station of India Meteorological Department were collected and subjected to trend analysis. Model outputs were compared with the observed station data. Results showed an overall negative trend of pre-monsoon rainfall during 1901-2005. However, increasing trend in monsoon rainfall was noticed during the same period. In future scenario, monsoon rainfall indicates a nominal increase (~6%) whereas pre-monsoon rainfall increases in moderate amount (~11%). So, from the study it may be said that in near future farmers and crop planner should give more importance in pre-monsoon rainfall for better crop planning and other stake holder activities.

scholarly journals Statistical analysis of monsoon rainfall distribution over West Bengal, India

MAUSAM ◽  
2021 ◽  
Vol 61 (4) ◽  
pp. 487-498
Author(s):  
AVIK GHOSH DASTIDAR ◽  
SARBARI GHOSH ◽  
U. K. DE ◽  
S. K. GHOSH
Keyword(s):  
Time Series ◽  
Statistical Analysis ◽  
West Bengal ◽  
Monsoon Rainfall ◽  
Daily Rainfall ◽  
India Meteorological Department ◽  
Seasonal Rainfall ◽  
Rainfall Distribution ◽  
Rainfall Characteristics ◽  
Plain Region

Seasonal, monthly and daily rainfall characteristics of meteorological sub-divisions of Sub Himalayan West Bengal (SHWB) and Gangetic West Bengal (GWB) have been studied using rainfall data of 23 stations of India Meteorological Department (IMD) over the state of West Bengal. The two subdivisions have distinctive characteristics, though two stations lying in the plain region of SHWB have behaviour more alike the stations of GWB.  Krishnagar is a station with least seasonal rainfall in the entire state. Kurtosis and Skewness of the seasonal rainfall distribution have been studied and found that, for most of the stations they lie within reasonable limits. From the time series analysis, it is found that the seasonal rainfall has no trend.     

Forecasting of Summer Monsoon Rainfall over Gangetic West Bengal, India Utilising Intrinsic Mode Functions, Linear and Neural Regression

2020 ◽  
Vol 12 (1) ◽  
pp. 60-69 ◽  
Author(s):  
Pijush Basak
Keyword(s):  
Neural Network ◽  
West Bengal ◽  
Monsoon Rainfall ◽  
Linear Part ◽  
Intrinsic Mode Functions ◽  
Quasi Biennial Oscillation ◽  
Nonlinear Part ◽  
South West ◽  
South West Monsoon ◽  
West Monsoon

The South West Monsoon rainfall data of the meteorological subdivision number 6 of India enclosing Gangetic West Bengal is shown to be decomposable into eight empirical time series, namely Intrinsic Mode Functions. This leads one to identify the first empirical mode as a nonlinear part and the remaining modes as the linear part of the data. The nonlinear part is modeled with the technique Neural Network based Generalized Regression Neural Network model technique whereas the linear part is sensibly modeled through simple regression method. The different Intrinsic modes as verified are well connected with relevant atmospheric features, namely, El Nino, Quasi-biennial Oscillation, Sunspot cycle and others. It is observed that the proposed model explains around 75% of inter annual variability (IAV) of the rainfall series of Gangetic West Bengal. The model is efficient in statistical forecasting of South West Monsoon rainfall in the region as verified from independent part of the real data. The statistical forecasts of SWM rainfall for GWB for the years 2012 and 2013 are108.71 cm and 126.21 cm respectively, where as corresponding to the actual rainfall of 93.19 cm 115.20 cm respectively which are within one standard deviation of mean rainfall.

3D FEA Modeling of Hard Turning

2002 ◽  
Vol 124 (2) ◽  
pp. 189-199 ◽  
Author(s):  
Y. B. Guo ◽  
C. R. Liu
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Geometric Model ◽  
Friction Model ◽  
Dominant Factor ◽  
Analysis Model ◽  
Element Analysis ◽  
Plastic Properties ◽  
Fea Model ◽  
Model Predictions

A practical explicit 3D finite element analysis model has been developed and implemented to analyze turning hardened AISI 52100 steels using a PCBN cutting tool. The finite element analysis incorporated the thermo-elastic-plastic properties of the work material in machining. An improved friction model has been proposed to characterize tool-chip interaction with the friction coefficient and shear flow stresses determined by force calibration and material tests, respectively. A geometric model has been established to simulate a 3D turning. FEA Model predictions have reasonable accuracy for chip geometry, forces, residual stresses, and cutting temperatures. FEA model sensitivity analysis indicates that the prediction is consistent using a suitable magnitude of material failure strain for chip separation, the simulation gives reasonable results using the experimentally determined material properties, the proposed friction model is valid and the sticking region on the tool-chip interface is a dominant factor of model predictions.

Trend analysis and ARIMA modelling of pre-monsoon rainfall data for western India

2013 ◽  
Vol 345 (1) ◽  
pp. 22-27 ◽  
Author(s):  
Priya Narayanan ◽  
Ashoke Basistha ◽  
Sumana Sarkar ◽  
Sachdeva Kamna
Keyword(s):  
Trend Analysis ◽  
Monsoon Rainfall ◽  
Rainfall Data ◽  
Western India

scholarly journals Recent models for long range forecasting of Southwest monsoon rainfall in India

MAUSAM ◽  
2021 ◽  
Vol 43 (3) ◽  
pp. 239-248
Author(s):  
V. THAPLIYAL ◽  
S. M. KULSHRESTHA
Keyword(s):  
Long Range ◽  
Monsoon Rainfall ◽  
India Meteorological Department ◽  
Scientific Work ◽  
Southwest Monsoon ◽  
Scientific Basis ◽  
Seasonal Forecasts ◽  
Dynamic Stochastic ◽  
The Times ◽  
Southwest Monsoon Rainfall

India has a long tradition of scientific work or, long range forecasting of the southwest monsoon ever since the times of Blanford and Walker In the early Parts of this century, the recent decades have witnessed increased research in regard to the development of new long range forecast models in the India Meteorological Department which have, given correct long range (seasonal) forecasts of southwest monsoon rainfall, over the country as a whole, during, the successive four year~, 1988 to 1991, Presently, four models namely, Para-metric Power Regression, Dynamic Stochastic Transfer and Improved Multiple Regression models are being used for formulating the seasonal forecast of monsoon rainfall over the country as a whole, The forecast is issued in two stages, In the first stage a tentative inference which is qualitative in nature is issued before the middle of April based mainly on the Parametric model which utilizes signals from 16 regional and global parameters that are related to land, ocean and atmospheric forcing and show physical linkages with monsoon. In the second stage, a firm quantitative forecast is issued towards the end of the May and is based on the remaining three models mentioned above, although higher weight age is given to the Power Regression Model which has shown encouraging performance during the last four years. In this paper, these recently developed models and the scientific basis underlying these are discussed, Data on validation of these Operational models, used for the long range  forecast during the past four years (1988-91) are also presented.

scholarly journals ANALISIS FAKTOR – FAKTOR BAURAN PEMASARAN TERHADAP KEPUTUSAN PEMBELIAN DAGING AYAM DI PASAR SWALAYAN FRESH MART BAHU KECAMATAN MALALAYANG KOTA MANADO

ZOOTEC ◽  
2020 ◽  
Vol 40 (2) ◽  
pp. 503
Author(s):  
Randy Taroreh ◽  
M L Rundengan ◽  
J K.J Kalangi ◽  
F N.S Oroh
Keyword(s):  
Marketing Strategy ◽  
Food Product ◽  
Dominant Factor ◽  
Meat Color ◽  
Analysis Model ◽  
Broiler Meat ◽  
Factors Affecting ◽  
Purchasing Decision ◽  
Factors Analysis ◽  
Method Analysis

ANALYSIS OF MARKETING MIXED FACTORS ON BROILER MEAT PURCHASING DECISION AT   PRESHMART SUPER STORE BAHU, MALALAYANG DISTRICT OF MANADO CITY. Broiler meats were categorized into popular high nutrient food product to supply protein needs of human being. The activities applied by the super store to overcome the high competition supplying consumers were to define the marketing strategy. A certain important strategy was mixed marketing. Strategy of mixed marketing was only applied to obtain the satisfaction wanted by consumers. The objective of this study was to evaluate factors affecting consumers to decide their decision on broiler meat purchasing at the fresh-mart super store Bahu, Mando.  A total of hundred purchasers were chosen to be samples using accidental sampling method. Analysis was done by SPSS program for Windows version 23. Data were analyzed by factors analysis model, continued by multiple regression to define the effects of factors of mixed marketing on purchasing decision by consumers. The factors affecting purchasing decision by consumers were meat color (X1), reached price (X2), strategic location (X3), and advertising material (X4). The dominant factor affecting purchasing decision was meat color (X1) with the highest regression coefficient of 0.725.

scholarly journals Prospect of double cropping of rainfed rice in West Bengal

MAUSAM ◽  
2021 ◽  
Vol 49 (1) ◽  
pp. 121-126
Author(s):  
H. P. DAS ◽  
S. V. DATAR
Keyword(s):  
Markov Chain ◽  
West Bengal ◽  
Monsoon Season ◽  
Growing Season ◽  
Threshold Value ◽  
Rainfall Data ◽  
Ranking Method ◽  
Growing Period ◽  
Rainfed Rice ◽  
Double Cropping

The prospect of double cropping of rain fed rice in West Bengal has been studied in two agroecological conditions (Canning, located in coastal saline region and Nagri, located in Red lateritic region) by identifying growing season through the analysis of rainfall data. The rainfall data of these locations have been analysed for dry and wet weeks by assuming a dry threshold value of 20 mm per week. Wet and dry weeks have been subjected to Markov Chain probability analysis and periods of ideal sowing have been determined. Rainfall data has also been accumulated from 1st  week (1- 7 Jan) onwards, and 52nd week (24- 31 Dec) backwards and by subjecting it to ranking method, growth periods of dry and wet crops have been determined. The study reveals that generally from 24th to 37th week (11 Jun-16 Sep) the probability of getting wet weeks exceeds 15% and probability of two consecutive dry weeks is negligible from 20th to 38th week (14 May - 23 September) for both the statistics. It is also found that harvesting two rice crops of shorter duration is feasible during the growing period covering pre-monsoon and monsoon season.

scholarly journals Dynamic crop planning for enhancing crop productivity in Mymensingh district

2014 ◽  
Vol 11 (2) ◽  
pp. 313-320 ◽  
Author(s):  
T Akter ◽  
MSU Talukder ◽  
MH Rahman ◽  
MNN Mazumder
Keyword(s):  
Water Balance ◽  
Crop Production ◽  
Potential Evapotranspiration ◽  
Crop Productivity ◽  
Rainfall Data ◽  
Maximum Rainfall ◽  
Crop Planning ◽  
Rainfall Analysis ◽  
Land Preparation ◽  
Rainy Days

A study was carried out to analyze the rainfall data for crop planning in rainfed regions,, Probability analysis of rainfall offers a better scope for predicting the minimum assured rainfall to help in crop planning. The 75% probability of rainfall occurrence was proposed as an index of dependable rainfall for crop production. Considering this in view, 25 years (1981-2005) of rainfall data of Mymensingh district have been analyzed in greater details covering probability aspects. Assured rainfall analysis, probability of potential evapotranspiration, water-balance approach and actual evapotranspiration were found quite effective to assess the water availability period for crop planning under rainfed condition. It was found that maximum rainfall occurred in July and minimum in December. The numbers of rainy days per year at 75% probability were 128 days. In the month of July and August numbers of rainy days were 20 and in December, it reduced to zero. The highest potential evapotranspiration was obtained in April (4.6 mm/day) and the lowest in January (2.4 mm/day).It was observed that April to October is the rainfall excess (rainfall>PET) and November to March is the deficit period (PET>rainfall). Climatic water balance revealed the possibility of water harvesting during May to October. It may be concluded that probabilistic rainfall data and number of rainy days, would be quite helpful for crop planning. It provides useful information like land preparation, planting, transplanting, intercultural operations, harvesting, threshing, drying and other cropping practices. This would go a long way in crop planning at farmers and at policy making level. DOI: http://dx.doi.org/10.3329/jbau.v11i2.19935 J. Bangladesh Agril. Univ. 11(2): 313-320, 2013

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