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Tracing Crop Water Demand in the Lower Ping River Basin, Thailand Using Cloud–Based Irrisat Application

Author(s): Khin Muyar Kyaw; Arreya Rittima; Yutthana Phankamolsil; Allan Sriratana Tabucanon; Wudhichart Sawangphol; Jidapa Kraisangka; Yutthana Talaluxmana; Varawoot Vudhivanich

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Keywords: Crop coefficient; Reference crop evapotranspiration; Crop Water Demand; IrriSAT; ETo calculator

Abstract: Estimating and tracing actual crop water demands during the growing season are necessarily essential as it can be the basic and useful information for achievement of irrigation water management and reservoir operation practices. The crop water demand (ETcrop) is commonly determined by multiplying the crop coefficient (Kc) and reference crop evapotranspiration (ETo) calculating from meteorological data at the nearby stations. In this study, the planting area and growth stage of crops in the Tortongdang, Wangbua, Wangyang and Nongkhwan Operation and Maintenance Projects, which are located in the Lower Ping River Basin, were tracked and crop coefficient was evaluated using weather based irrigation scheduling (IrriSAT) application for estimation of crop water requirement. IrriSAT provides the satellite images processing of Normalized Difference Vegetation Index (NDVI) of planting area of crop and uses empirical relationship to find Kc. Kc values of season and off–season crops planting in four irrigation area during 2000–2019 were traced by IrriSAT and the results were compared with average Kc–RID values which were calculated as a function of Kc from field observation for the different types of crop and accumulated area of crops monitored by the remote sensing. The results showed the similar patterns of average Kc over the growth stages of crops. However, the Kc values calculated by IrriSAT for four irrigation area were slightly deviated from Kc–RID values in some growing periods. Therefore, calibrating Kc values calculated by IrriSAT was then conducted in this study to estimate actual crop water use and benchmark with the filed observation data. This study also revealed that applying cloud–based IrriSAT could be greatly supportive for irrigators and reservoir operators to enhance the efficiency of irrigation water management.

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Year: 2020

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