Abstract
Assessment of Irrigation performance is considered an important management tool to implement, monitor, and evaluate activities for water delivery systems. An ideal or reference irrigation is one that delivers the necessary water for the entire area at the proper time and in the proper amount with the fewest losses feasible. This study presented the use of actual evapotranspiration -based performance indicators for the Evaluation of irrigation performance of a Belan canal irrigated area in Prayagraj. This research aims to quantify the crops produced there require water to the area and assessed the irrigated areas. The actual evapotranspiration (ETa) was measured using the meteorological data collected from the station Using actual evapotranspiration the Delivery performance ratio, Depleted fraction, Relative evapotranspiration, Crop water deficit, and Field application ratio was calculated. The temporal variation of the irrigated area, there is water stress was successfully demonstrated for every performance metric. Water stress is indicated by the Delivery performance ratio for four months of the growing period (August, September, October, and January). With the exception of November to February, the Relative Evapotranspiration shows water stress for virtually the whole irrigation period. Despite the fact that the same two months’ worth of December and January as that of Relative evapotranspiration are given by the Crop Water Deficit, which likewise indicated water stress for the most of the time period and also for another two months March and April. As a whole, the execution of the system was not ideal and requires maintenance and proper supply as per the water requirements. Water User Association is highly recommended in this condition.
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Mishra, V., Denis, D., Mishra, H., Kumar, M. (2023). Assessing Irrigation Performance of a Canal Command Area Using Space and Ground Observation. A Case Study of Belan Canal, Prayagraj. In: Ramdane-Cherif, A., Singh, T.P., Tomar, R., Choudhury, T., Um, JS. (eds) Machine Intelligence and Data Science Applications. MIDAS 2022. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-99-1620-7_38
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