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  • Apr, 2012
    Volume - 32, No. - 1
    ESTIMATING REFERENCE EVAPOTRANSPIRATION USING NEURAL COMPUTING TECHNIQUE
    Seema Chauhan and R. K. Shrivastava

    This paper investigates the potential of artificial neural networks (ANNs) for estimation of reference crop evapotranspiration with climatic data required for Penman-Monteith (P-M) method, to test artificial neural networks (ANNs) for estimating refe...

1969 Dec

Issue (Volume No. 32, Number 1)

ESTIMATING REFERENCE EVAPOTRANSPIRATION USING NEURAL COMPUTING TECHNIQUE

This paper investigates the potential of artificial neural networks (ANNs) for estimation of reference crop evapotranspiration with climatic data required for Penman-Monteith (P-M) method, to test artificial neural networks (ANNs) for estimating reference evapotranspiration (ETo) with limited climatic data (ETo) and compares the performance of ANNs with P-M method. The ANNs are trained to estimate ETo from weekly climate data as input and the Penman-Monteith (P-M) estimate as output. The networks, using varied input combinations of climatic variables have been trained using three backpropagation learning algorithms namely quasi-Newton algorithm, Levenberg-Marquardt algorithm and Backpropagation with variable learning rate. Firstly the networks were trained with weekly climate data (maximum and minimum temperature, maximum and minimum relative humidity, wind speed, and sunshine hours) as input and the P-M estimate as output. Then the networks, using varied input combinations of climatic variables have been trained using the same training algorithms as mentioned above. For each class of inputs, the best ANN architecture for estimation of ETo was selected on the basis of statistical parameters like square estimates of error (SEE) and model efficiency. The analyses suggest that the ETo can be computed from limited climate data using the ANN approach in Mahanadi Reservoir Project (MRP) command area. Further based on the results obtained, it can also be concluded that ANN performed well when the input (first) layer receives the input variables consisting of all quantities that can influence the output.

by Seema Chauhan and R. K. Shrivastava
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1969 Dec

Issue (Volume No. 32, Number 1)

APPLICATION OF ARTIFICIAL NEURAL NETWORK IN PREDICTION OF RESPONSE OF FARMERS? WATER MANAGEMENT DECISIONS ON WHEAT YIELD

Water scarcity is a global problem and the best solution to tackle this problem is to make efficient use of the available water to increase the productivity of the available water resources. It is estimated that nearly 50 percent of potential water saving comes from the water management practices. Water management usually involves decision-making with respect to allocation, scheduling and application of the available water to different crops over an irrigation season so as to get maximum economic returns. A study was carried out in Kaithal irrigation circle for prediction of farmers? decisions on crop yields using Artificial Neural Networks (ANN). Artificial Neural Network models have shown considerable potential for resolving some of the problems related with irrigated agricultural systems, which are complex, non-linear and ill defined. ANNs have shown potential uses in three types of applications in the field of irrigated agriculture including image analysis techniques for identification and classification of agricultural clusters, decision support systems for management, and predictions of various processes. Different ANN algorithms (back-propogation, Levenberg-Marquardt and radial basis function) and architecture were used for prediction of farmers decision on crop yield and it was found that radial basis function with spread constant 0.1 performed better for prediction of wheat and rice yields. It was also found that that ANN algorithm predicted better for both wheat and rice crops in comparison to statistical regression model as obtained coefficient of determination in case of ANN was much higher for (r2 =0.63) than regression model (r2 =0.32).

by M.K. Hardaha , S.S. Chouhan and S.K. Ambast
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  • Apr, 2012
    Volume - 32, No. - 1
    ESTIMATION OF EVAPOTRANSPIRATION FOR WHEAT CROP USING ARTIFICIAL NEURAL NETWORK
    Santosh Ojha and Sita Ram Bhakar

    The study has been undertaken to investigate the utility of artificial neural networks (ANNs) for comparison of daily reference evapotranspiration (ET0) estimated by Penman-Monteith (PM) method and that of estimated by ANNs during growing season of w...

1969 Dec

Issue (Volume No. 32, Number 1)

ESTIMATION OF EVAPOTRANSPIRATION FOR WHEAT CROP USING ARTIFICIAL NEURAL NETWORK

The study has been undertaken to investigate the utility of artificial neural networks (ANNs) for comparison of daily reference evapotranspiration (ET0) estimated by Penman-Monteith (PM) method and that of estimated by ANNs during growing season of wheat crop. Feed forward network has been used for prediction of ET0 using resilient back-propagation method. For the purpose of the study, daily meteorological observations such as minimum and maximum temperature, minimum and maximum relative humidity, wind speed and solar radiation for the period of November 21, 1997 to March 2, 1998 were used as input and ET0 estimated by Penman -Monteith method for growing season of wheat crop as output. The comparisons were made between ANNs estimated ET0 and ET0 estimated using PM method. The correlation coefficient between actual and predicted ET0 during training of ET0 for growing season of wheat crop was found to be 0.990 which was found to be significant at 5 % level. The networks were also used for computation of crop evapotranspiration (ETc). During training of ETc, crop coefficient values estimated by quadratic method have been taken as input to the network along with meteorological parameters and ETc estimated using crop coefficient approach and that of measured by lysimeter as output separately. The crop evapotranspiration estimated by ANNs were compared with ETc estimated by crop coefficient approach and that of evapotranspiration measured by lysimeter. The correlation coefficients during training of ETc of wheat crop were found to be 0.994 and 0.915 respectively which were also found significant at 5 % level. Based on these comparisons, it can be concluded that the ANN models is suitable for prediction of ET0 and ETc

by Santosh Ojha and Sita Ram Bhakar
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  • Apr, 2012
    Volume - 32, No. - 1
    ASSESSMENT OF WATER QUALITY STATUS OF HOLY RIVER KSHIPRA USING WATER QUALITY INDEX
    R.C. Gupta , Ajay K. Gupta and R.K. Shrivastava

    In this paper attempt is being made to assess the water quality of Kshipra, a holy river flowing through Ujjain city. Parameters namely Temperature, pH, Turbidity, Total Solids, Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Phosphate, Ammon...

1969 Dec

Issue (Volume No. 32, Number 1)

ASSESSMENT OF WATER QUALITY STATUS OF HOLY RIVER KSHIPRA USING WATER QUALITY INDEX

In this paper attempt is being made to assess the water quality of Kshipra, a holy river flowing through Ujjain city. Parameters namely Temperature, pH, Turbidity, Total Solids, Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Phosphate, Ammonia and Fecal Coliform ( F.C.) were determined at important locations of River Khan and Kshipra for summer, monsoon and winter seasons in the year 2010. Assessment was made through Water Quality Index (WQI), a single number representing large quantities of data. US National Sanitation Foundation WQI was calculated for each set of data with and without Phosphate parameter. The results shows that Kshipra River water is of medium to bad quality and Khan River water is the major cause of pollution in Kshipra River. The study also revealed that Kshipra River water is unsuitable even for bathing.

by R.C. Gupta , Ajay K. Gupta and R.K. Shrivastava
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1969 Dec

Issue (Volume No. 32, Number 1)

STATISTICAL ANALYSIS OF SPATIAL PATTERN OF RAINFALL TRENDS IN PARAMBIKUALAM ALIYAR SUB BASIN, TAMIL NADU

This study aims to determine trends in the annual and seasonal total rainfall over Parambikulam Aliyar sub basin of Tamil Nadu using 37 years (1972-2008) monthly rainfall data at four rain-gauge stations (Aliyar Nagar, Pollachi, Vettaikaranpudur and Anamalai). The procedure is based on the nonparametric Mann-Kendall test for the trend and the nonparametric Sen?s method for the magnitude of the trend. Significant positive trend was observed at Anamalai station for annual and North East monsoon rainfall series and significant negative trend has been noticed in the South West monsoon of Vettaikaranpudur. The maximum increase of rainfall out of four stations was experienced by Anamalai in annual rainfall (22.47 mm/year) and maximum reduction was found for Vettaikaranpudur (-6.14 mm/year) in South West monsoon. The presence of trend in annual and seasonal rainfall series determined by Mann-Kendall Z statistics and Sen?s Slope estimator reflected in the linear regression analysis.

by M. Manikandan and D. Tamilmani
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  • Apr, 2012
    Volume - 32, No. - 1
    PERFORMANCE OF MULTIPLE PLUNGING HOLLOW JETS
    Rakesh Gupta , Subodh Ranjan and A. M. Kalra

    The phenomenon of plunging jet entrainment and the resultant aeration has been described by a jet of water plunging into a pool resulting in substantial amounts of air entrainment and oxygenation. The rate of oxygen transfer and oxygen transfer effic...

1969 Dec

Issue (Volume No. 32, Number 1)

PERFORMANCE OF MULTIPLE PLUNGING HOLLOW JETS

The phenomenon of plunging jet entrainment and the resultant aeration has been described by a jet of water plunging into a pool resulting in substantial amounts of air entrainment and oxygenation. The rate of oxygen transfer and oxygen transfer efficiency are the two main parameters which are used for quantifying the performance of an aerator and for comparison of two or more aerators. The present study has been carried out to quantify the performance of 60? curved?shaped single jet aerator, two multiple jet aerators with two and three aerating units for varying discharge ranged from 2.0 l/s to12.5 l/s with uniform jet thicknesses of 20 mm and 25 mm. The performance of single jet aerator is observed to be better for low discharge range only while multiple aerator with two aerating units performed better for higher discharge values. The multiple jet aerator with three aerating units is envisaged to be better for a higher discharge range and a larger water surface area.

by Rakesh Gupta , Subodh Ranjan and A. M. Kalra
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  • Apr, 2012
    Volume - 32, No. - 1
    METEOROLOGICAL DROUGHT ASSESSMENT IN BARAPANI, MEGHALAYA
    Lala I.P. Ray , P.K. Bora , V.Ram , A.K. Singh , R. Singh and S.M. Feroze

    In rain-fed agriculture, rainfall has a crucial role to play for suitable crop planning. Twenty eight years (1983-2010) daily rainfall data has been analysed to find out weekly, monthly, seasonal and yearly meteorological drought occurrence at Barapa...

1969 Dec

Issue (Volume No. 32, Number 1)

METEOROLOGICAL DROUGHT ASSESSMENT IN BARAPANI, MEGHALAYA

In rain-fed agriculture, rainfall has a crucial role to play for suitable crop planning. Twenty eight years (1983-2010) daily rainfall data has been analysed to find out weekly, monthly, seasonal and yearly meteorological drought occurrence at Barapani station of Ri-Bhoi district, Meghalaya. The average annual rainfall of Barapani worked out to be 2,410.40 mm (coming under high rainfall region). The observed frequency of drought was the highest in 28th week in a tune of 11 times; month of December to a tune of about 14 times. Based on rainfall analysis it was found that during 28 years no scanty drought year was experienced. However, there was one moderate drought year which corresponds to the year 1998. Critical dry spells expected to occur during 26th to 28th week of the year.

by Lala I.P. Ray , P.K. Bora , V.Ram , A.K. Singh , R. Singh and S.M. Feroze
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