Ashish V. Sonawane Murtaza Hasan Deepak Singh


Study was conducted to derive operational model for a farm pond of 3000 cubic meter capacity at Center for protected cultivation technology (CPCT), Indian Agricultural Research Institute, New Delhi, India which was the important source of irrigation water of the farm of the area 10 ha. The Neuro-Fuzzy approach was used to develop the operational model and to derive operational rules for proper irrigation scheduling of the horticultural crops grown at CPCT. Based upon the inputs like crop water requirement, evaporation losses and farm pond inflow the model predicting outflow of the reservoir was developed. The developed model was having high accuracy and predictability when tested statistically. The coefficient of determination (R2) was found to be 0.96, whereas the model efficiency (E) was 0.97 which shows the high reliability of the model. The operating rules which were of ‘If-Then’ form were also developed which would lead to better management of the farm pond system and would also improve the irrigation scheduling at CPCT farm, IARI, New Delhi.


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Farm pond, Irrigation scheduling, Neuro-Fuzzy, Operational rules

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Sonawane, A. V., Hasan, M., & Singh, D. (2016). Development of farm pond operational modeling using Neuro-Fuzzy technique. Journal of Applied and Natural Science, 8(2), 730-735. https://doi.org/10.31018/jans.v8i2.866
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