scholarly journals Influence of multi-decadal meteorological variability on the reference evpotranspirtion in hot and humid coastal town of Annamalainagar in Tamil Nadu state

MAUSAM ◽  
2021 ◽  
Vol 71 (1) ◽  
pp. 45-56
Author(s):  
MURUGAPPAN A ◽  
MANIKUMARI N ◽  
MOHAN S
Keyword(s):  
Tamil Nadu ◽  
Reference Evapotranspiration ◽  
Meteorological Parameter ◽  
Vapour Pressure Deficit ◽  
Weather Data ◽  
Net Radiation ◽  
Sunshine Hours ◽  
Daily Weather Data ◽  
Tamil Nadu State ◽  
Decadal Trend

Reference evapotranspiration (ETo) is a key pointer of atmospheric evaporation demand and has been extensively used to describe the hydrological change. In this study, the reference evapotranspiration over the hot and humid town, Annamalainagar, very near to the east coast in Tamilnadu State, India, have been estimated employing the FAO Penman-Monteith (PM) method and the observed daily weather data during 1977-2016. The objective of the present study is two-fold: (i) To identify the multi-decadal trend of the various measured meteorological parameters namely, mean air temperature (Tmean), vapour pressure deficit (VPD), actual sunshine hours (SSH), net radiation (Rn) and wind speed (WS) at the study location and (ii) To identify the main contributing meteorological parameter for the detected decreasing trend in ETo over the multi-decadal period.

scholarly journals Comparison Statistical Rice Yield Prediction with Multiple Weather Parameters

2021 ◽  
pp. 31-38
Author(s):  
T. Thurkkaivel ◽  
G. A. Dheebakaran ◽  
V. Geethalakshmi ◽  
S. G. Patil ◽  
K. Bhuvaneshwari
Keyword(s):  
Bayesian Model ◽  
Tamil Nadu ◽  
Rice Yield ◽  
Model Performance ◽  
Research Centre ◽  
Yield Prediction ◽  
Sunshine Hours ◽  
Tamil Nadu State ◽  
Weather Parameters ◽  
Essential Food

Advance knowledge of harvestable products, especially essential food crops such as rice, wheat, maize, and pulses, would allow policymakers and traders to plan procurement, processing, pricing, marketing, and related infrastructure and procedures. There are many statistical models are being used for the yield prediction with different weather parameter combinations. The performance of these models are dependent on the location’s weather input and its accuracy. In this context, a study was conducted at Agro Climate Research Centre, Tamil Nadu Agricultural University, Coimbatore during Kharif (2020) season to compare the performance of four multivariate weather-based models viz., SMLR, LASSO, ENET and Bayesian models for the rice yield prediction at Tanjore district of Tamil Nadu State with Tmax, Tmin, Mean RH, WS, SSH, EVP and RF.  The results indicated that the R2, RMSE, and nRMSE values of the above models were ranged between 0.54 to 0.79 per cent, 149 to 398 kg/ha, 4.0 to 10.6 per cent, respectively. The study concluded that the Bayesian model was found to be more reliable followed by LASSO and ENET. In addition, it was found that the Bayesian model could perform better even with limited weather parameters and detention of wind speed, sunshine hours and evaporation data would not affect the model performance. It is concluded that Bayesian model may be a better option for rice yield forecasting in Thanjavur districts of Tamil Nadu.

scholarly journals Investigation into the Effects of Climate Change on Reference Evapotranspiration Using the HadCM3 and LARS-WG

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 666 ◽  
Author(s):  
Maryam Bayatvarkeshi ◽  
Binqiao Zhang ◽  
Rojin Fasihi ◽  
Rana Muhammad Adnan ◽  
Ozgur Kisi ◽  
...  
Keyword(s):  
Climate Change ◽  
Reference Evapotranspiration ◽  
Irrigation Scheduling ◽  
Weather Data ◽  
Base Period ◽  
Resources Management ◽  
Weather Information ◽  
Daily Weather Data ◽  
Weather Stations ◽  
A1b Scenario

This study evaluates the effect of climate change on reference evapotranspiration (ET0), which is one of the most important variables in water resources management and irrigation scheduling. For this purpose, daily weather data of 30 Iranian weather stations from 1981 and 2010 were used. The HadCM3 statistical model was applied to report the output subscale of LARS-WG and to predict the weather information by A1B, A2, and B1 scenarios in three periods: 2011–2045, 2046–2079, and 2080–2113. The ET0 values were estimated by the Ref-ET software. The results indicated that the ET0 will rise from 2011 to 2113 approximately in all stations under three scenarios. The ET0 changes percentages in the A1B scenario during three periods from 2011 to 2113 were found to be 0.98%, 5.18%, and 12.17% compared to base period, respectively, while for the B1 scenario, they were calculated as 0.67%, 4.07%, and 6.61% and for the A2 scenario, they were observed as 0.59%, 5.35%, and 9.38%, respectively. Thus, the highest increase of the ET0 will happen from 2080 to 2113 under the A1B scenario; however, the lowest will occur between 2046 and 2079 under the B1 scenario. Furthermore, the assessment of uncertainty in the ET0 calculated by the different scenarios showed that the ET0 predicted under the A2 scenario was more reliable than the others. The spatial distribution of the ET0 showed that the highest ET0 amount in all scenarios belonged to the southeast and the west of the studied area. The most noticeable point of the results was that the ET0 differs from one scenario to another and from a period to another.

Estimation of Evapotranspiration using the Modified Hargreaves Equation by Genetic Algorithm

2020 ◽  
Author(s):  
Deokhwan Kim
Keyword(s):  
Genetic Algorithm ◽  
Developing Countries ◽  
Correction Factor ◽  
Historical Data ◽  
Reference Evapotranspiration ◽  
Weather Data ◽  
Correction Coefficient ◽  
Test Bed ◽  
True Value ◽  
Daily Weather Data

<p>In this study, the Hargreaves monthly correction factor is presented to estimate the reference evapotranspiration. For the analysis, I used daily weather data from 1989 to 2018, at 67 meteorological stations located throughout the Korean peninsula.</p><p>A large number of more or less empirical methods have been developed over the last 50 years by numerous scientists and specialists worldwide to estimate evapotranspiration from different climatic variables. The FAO Penman-Monteith method is recommended as the sole ETo method for determining reference evapotranspiration. However, the Penman-Monteith method has the disadvantage of inputting a lot of weather data. In addition, there is a lack of meteorological data when using old historical data or as a test bed for developing countries.</p><p>In the case of the Hargreaves method, the reference evapotranspiration can be estimated only if the latitude, maximum and minimum temperatures of the meteorological station are known. However, the accuracy of the results is not as good as that of the Penman-monteith method. Thus, using the genetic algorithm method suggested the monthly correction factor of the Hargreaves method each station. The reference evapotranspiration amount calculated by Penman-Monteith was set as the true value, and the learning period of genetic algorithm was set from 1989 to 2013, and the validation period was set from 2014 to 2018.</p><p>In order to verify the model efficiency, the root mean square error decreased and the correlation coefficient increased when the monthly correction coefficient was applied to the reference evapotranspiration calculated by the Hargreaves method.</p><p>It is very important to estimate the reference evapotranspiration amount in order to develop the water long-term plan.</p><p>With the development of measuring equipment and technological capabilities, it is now possible to simulate the state of nature as if it were real, but many problems arise when using historical data or analyzing developing countries.</p><p>If the monthly correction coefficient suggested in this study is applied, it is possible to estimate the standard evaporation amount with a more approximate value.</p><p> </p><p>Acknowledgements</p><p> This research is supported by the Research Program (20200041-001) of Korea Institute of Civil Engineering & Building Technology </p>

scholarly journals Estimating hourly reference evapotranspiration from limited weather data by sequentially adaptive RBF network

2011 ◽  
Vol 9 (3) ◽  
pp. 473-480 ◽  
Author(s):  
Slavisa Trajkovic
Keyword(s):  
Heat Flux ◽  
Air Temperature ◽  
Reference Evapotranspiration ◽  
Soil Heat Flux ◽  
Weather Data ◽  
Canopy Resistance ◽  
Net Radiation ◽  
Rbf Networks ◽  
Rbf Network ◽  
Two Parameters

This study investigates the utility of adaptive Radial Basis Function (RBF) networks for estimating hourly grass reference evapotranspiration (ET0) from limited weather data. Nineteen days of micrometeorological and lysimeter data collected at half-hour intervals during 1962-63 and 1966-67 in the Campbell Tract research site in Davis, California were used in this study. Ten randomly chosen days (234 patterns) were selected for the RBF networks training. Two sequentially adaptive RBF networks with different number of inputs (ANNTR and ANNTHR) and two Penman-Monteith equations with different canopy resistance values (PM42 and PM70) were tested against hourly lysimeter data from remaining nine days (200 patterns). The ANNTR requires only two parameters (air temperature and net radiation) as inputs. Air temperature, humidity, net radiation and soil heat flux were used as inputs in the ANNTHR. PM equations use air temperature, humidity, wind speed, net radiation and soil heat flux density as inputs. The results reveal that ANNTR and PM42 were generally the best in estimating hourly ET0. The ANNTHR performed less well, but the results were acceptable for estimating ET0. These results are of significant practical use because the RBF network with air temperature and net radiation as inputs could be used to estimate hourly ET0 at Davis, California.

Estimation of reference evapotranspiration using Aquacrop model for agro-climatic conditions of Madhya Pradesh

2017 ◽  
Vol 51 (06) ◽  
Author(s):  
Deepika Yadav ◽  
M. K. Awasthi ◽  
R. K. Nema
Keyword(s):  
Temporal Variability ◽  
Reference Evapotranspiration ◽  
Madhya Pradesh ◽  
Weather Data ◽  
Accurate Estimation ◽  
Spatial And Temporal Variability ◽  
Statistical Parameters ◽  
Climatic Zones ◽  
Aquacrop Model ◽  
Daily Weather Data

Accurate estimation of evapotranspiration is necessary step for better management and allocation of water resources. The United Nations Food and Agriculture Organization (FAO) adopted the Penman Moneith method as a global standard to estimate reference crop evapotranspiration (ETo). The study aimed to estimate FAO P-M reference evapotranspiration for different district of five agro climatic zones of Madhya Pradesh state by using Aquacrop model. Daily weather data including maximum and minimum temperature, precipitation, relative humidity, wind speed and solar radiation were collected for the period of 1979 to 2013 which were used as input data in Aquacrop. Several statistical parameters were used for characterizing the spatial and temporal variability of ETo. The average monthly ETo was found maximum in month of May (10.67 mm day-1) in all district of different agro climatic zones for the average period considered for the study and also for each years, whereas average minimum ETo was estimated in month of December (3.23 mm day-1) in Kymore Plateau and August (2.44 mm day-1) in Satpura Plateau. The mean daily reference evapotranspiration ranges from 4 mm day-1 to 10 mm day-1 for all districts. From the statistical analysis it was found that spatial variability of ETo lower than the temporal variability. It means the bigger differentiation of ETo in the years than in the space.

A Study on Job Satisfaction among Tamil Nadu State Transport Corporation (TNSTC) Employees at Tiruvarur Branch

GIS Business ◽  
2019 ◽  
Vol 14 (6) ◽  
pp. 230-242
Author(s):  
M. Ganesan, K ◽  
K. Veerakumar ◽  
N. R Vembu ◽  
Dr. M. K Durgamani ◽  
Dr. Renuka
Keyword(s):  
Job Satisfaction ◽  
Job Stress ◽  
Tamil Nadu ◽  
Heavy Traffic ◽  
Road Transportation ◽  
The Road ◽  
Tamil Nadu State ◽  
On The Road ◽  
Day By Day ◽  
Labour Turnover

Job satisfaction is an important factor for employees working in formal and informal sector. The job is small or big, permanent or temporary, risky or non-risky, job satisfaction is important. It is the mental feeling which drives the employees to excel. Job satisfaction is a combination of psychological, physiological and environmental circumstances. A satisfied employee is a contented and happy human being. The labour turnover depends upon job satisfaction. Even highly paid employees quit the job when they are not satisfied with the job. Road transportation in Tamilnadu is growing day by day. Job stress in the road transportation is very high due to increase in number of vehicle playing on the road and heavy traffic. The drivers and conductors working in public transport corporation are suffering from high job stress. If drivers and conductors are not satisfied with their job which leads to mental stresses and affects the productivity and also creates accidents. In this present study the researchers made an attempt to study the level of job satisfaction among the drivers and conductors who are working in the Tamilnadu State Transport Corporation (TNSTC). The study reveals the expectations of drivers and conductors working in TNSTC with regards to the attributes like salary, promotion and fringe benefits etc., are satisfactory and not detrimental. 

scholarly journals Distribution and incidence of viruses in Irish seed potato crops

2015 ◽  
Vol 54 (2) ◽  
pp. 98-106 ◽  
Author(s):  
F. Hutton ◽  
J.H. Spink ◽  
D. Griffin ◽  
S. Kildea ◽  
D. Bonner ◽  
...  
Keyword(s):  
Potato Virus ◽  
Significant Proportion ◽  
Potato Production ◽  
Weather Data ◽  
Management Approach ◽  
Potato Seed ◽  
Virus Diseases ◽  
Aphid Control ◽  
Daily Weather Data ◽  
Potato Crops

Abstract Virus diseases are of key importance in potato production and in particular for the production of disease-free potato seed. However, there is little known about the frequency and distribution of potato virus diseases in Ireland. Despite a large number of samples being tested each year, the data has never been collated either within or across years. Information from all known potato virus testing carried out in the years 2006–2012 by the Department of Agriculture Food and Marine was collated to give an indication of the distribution and incidence of potato virus in Ireland. It was found that there was significant variation between regions, varieties, years and seed classes. A definition of daily weather data suitable for aphid flight was developed, which accounted for a significant proportion of the variation in virus incidence between years. This use of weather data to predict virus risk could be developed to form the basis of an integrated pest management approach for aphid control in Irish potato crops.

scholarly journals Maternal Vitamin B12 Status and Risk of Cleft Lip and Cleft Palate Birth Defects in Tamil Nadu State, India

2021 ◽  
Vol 58 (5) ◽  
pp. 567-576
Author(s):  
Ronald G. Munger ◽  
Rajarajeswari Kuppuswamy ◽  
Jyotsna Murthy ◽  
Kalpana Balakrishnan ◽  
Gurusamy Thangavel ◽  
...  
Keyword(s):  
Cleft Palate ◽  
Tamil Nadu ◽  
Cleft Lip ◽  
Maternal Nutrition ◽  
Case Control ◽  
Vitamin B ◽  
Plasma Vitamin ◽  
Maternal Vitamin ◽  
Increased Risk ◽  
Tamil Nadu State

Background and Objective: The causal role of maternal nutrition in orofacial clefts is uncertain. We tested hypotheses that low maternal vitamin B12 and low folate status are each associated with an increased risk of isolated cleft lip with or without cleft palate (CL±P) in a case–control study in Tamil Nadu state, India. Methods: Case-mothers of CL±P children (n = 47) and control-mothers of unaffected children (n = 50) were recruited an average of 1.4 years after birth of the index child and plasma vitamin B12, methylmalonic acid (MMA), total homocysteine (tHcy), and folate were measured at that time. Logistic regression analyses estimated associations between nutrient biomarkers and case–control status. Results: Odds ratios (ORs) contrasting biomarker levels showed associations between case-mothers and low versus high plasma vitamin B12 (OR = 2.48, 95% CI, 1.02-6.01) and high versus low plasma MMA, an indicator of poor B12 status (OR = 3.65 95% CI, 1.21-11.05). Case–control status was not consistently associated with folate or tHcy levels. Low vitamin B12 status, when defined by a combination of both plasma vitamin B12 and MMA levels, had an even stronger association with case-mothers (OR = 6.54, 95% CI, 1.33-32.09). Conclusions: Mothers of CL±P children in southern India were 6.5 times more likely to have poor vitamin B12 status, defined by multiple biomarkers, compared to control-mothers. Further studies in populations with diverse nutritional backgrounds are required to determine whether poor maternal vitamin B12 or folate levels or their interactions are causally related to CL±P.

scholarly journals A method for simulating risk profiles of wheat yield in data-sparse conditions

2021 ◽  
pp. 1-12
Author(s):  
G. Bracho-Mujica ◽  
P.T. Hayman ◽  
V.O. Sadras ◽  
B. Ostendorf
Keyword(s):  
Reference Site ◽  
Climate Impacts ◽  
Weather Data ◽  
Climate Data ◽  
High Quality ◽  
Risk Profiles ◽  
Record Length ◽  
Daily Weather Data ◽  
Study Sites

Abstract Process-based crop models are a robust approach to assess climate impacts on crop productivity and long-term viability of cropping systems. However, these models require high-quality climate data that cannot always be met. To overcome this issue, the current research tested a simple method for scaling daily data and extrapolating long-term risk profiles of modelled crop yields. An extreme situation was tested, in which high-quality weather data was only available at one single location (reference site: Snowtown, South Australia, 33.78°S, 138.21°E), and limited weather data was available for 49 study sites within the Australian grain belt (spanning from 26.67 to 38.02°S of latitude, and 115.44 to 151.85°E of longitude). Daily weather data were perturbed with a delta factor calculated as the difference between averaged climate data from the reference site and the study sites. Risk profiles were built using a step-wise combination of adjustments from the most simple (adjusted series of precipitation only) to the most detailed (adjusted series of precipitation, temperatures and solar radiation), and a variable record length (from 10 to 100 years). The simplest adjustment and shortest record length produced bias of modelled yield grain risk profiles between −10 and 10% in 41% of the sites, which increased to 86% of the study sites with the most detailed adjustment and longest record (100 years). Results indicate that the quality of the extrapolation of risk profiles was more sensitive to the number of adjustments applied rather than the record length per se.

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