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Evaluation of soft-computing techniques for pan evaporation estimation

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Title Evaluation of soft-computing techniques for pan evaporation estimation
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Creator AMIT KUMAR
A. SARANGI
D.K. SINGH
I. MANI
K. K. BANDHYOPADHYAY
S. DASH
M. KHANNA
 
Subject Evaporation
Prediction
Neural network
Irrigation scheduling
LSTM network
 
Description Not Available
Estimation of pan evaporation (Epan) can be useful in judicious irrigation scheduling for enhancing agricultural water productivity. The aim of present study was to assess the efficacy of state-of-the-art LSTM and ANN for daily Epan estimation using meteorological data. Besides this, the effect of static time-series (Julian date) as additional input variable was investigated on performance of soft-computing techniques. For this purpose, the models were trained, tested and validated with eight meteorological variables of 37 years by using preceding 1-, 3- and 5- days’ information. Data were partitioned into three groups as training (60%), testing (20%), and validation (20%) components. It was observed that the models performed well (best) with preceding 5-days meteorological information followed by 3-days and 1-day. However, all LSTMs simulated peak value of Epan was more accurate as compared to lower values. Meteorological data with julian date improved the performance of LSTMs (0.75
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Date 2024-03-26T12:30:50Z
2024-03-26T12:30:50Z
2024-03-01
 
Type Research Paper
 
Identifier Kumar, A., Sarangi, A., Singh, D.K., Mani, I., Bandyopadhyay, K. K., Dash, S. and Khanna, M. (2024). Evaluation of soft-computing techniques for pan evaporation estimation. Journal of Agrometeorology, 26(1), 56-62 (NAAS rating: 6.70)
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http://krishi.icar.gov.in/jspui/handle/123456789/81690
 
Language English
 
Relation Not Available;