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Tracing Crop Water Requirement in the Pumping, Gravitational and Inundation Irrigation Schemes Using Cloud-Based IrriSAT Application |
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| รหัสดีโอไอ | |
| Creator | Paphanin Phutonglom |
| Title | Tracing Crop Water Requirement in the Pumping, Gravitational and Inundation Irrigation Schemes Using Cloud-Based IrriSAT Application |
| Contributor | Areeya Rittima, Yutthana Phankamolsil, Allan Sriratana Tabucanon, Wudhichart Sawangphol, Jidapa Kraisangka, Yutthana Talaluxmana, Varawoot Vudhivanich |
| Publisher | Faculty of Engineeing Naresuan University |
| Publication Year | 2565 |
| Journal Title | Naresuan University Engineering Journal |
| Journal Vol. | 17 |
| Journal No. | 2 |
| Page no. | 28-37 |
| Keyword | Crop Coefficient, Crop Water Requirement, Reference Crop Evapotranspiration, Cloud-Based IrriSAT Application, Normalized Difference Vegetation Index |
| URL Website | https://ph01.tci-thaijo.org/index.php/nuej |
| Website title | https://ph01.tci-thaijo.org/index.php/nuej |
| ISSN | 1905-615x |
| Abstract | Tracing crop coefficient (Kc) at all the stages of crop growth is commonly essential for an accurate estimation of crop water use. This study applied the cloud-based IrriSAT application to trace the dynamic values of crop coefficient in three different sorts of irrigation schemes; pumping, gravitational and inundation irrigation for estimating crop water requirement in the Chao Phraya River Basin (CPYRB), Thailand. Three selected irrigation schemes; Bang Bal (BB), Thabua (TB), and Yom-Nan (YN) representing pumping, gravitational, and inundation irrigation schemes were selected to trace crop coefficient values of in-season and off-season crops and to estimate long-term crop water requirement (ETc) from 2015-2020. The results of dynamic values of Kc-IrriSAT were verified and adjusted with average Kc established by the Royal Irrigation Department (Kc-RID) which were calculated as a function of Kc from field observation for the different types of crops and accumulated area size monitored by the Ged Space Technology Development Agency (GISTDA). The results revealed the similar patterns of average Kc generated by IrriSAT corresponding to the average Kc-RID. After the calibration procedure was successfully done, the correlations between Kc-IrriSAT adjusted and average Kc-RID for BB, TB, and YN irrigation schemes are relatively higher with R2 of 0.8304, 0.8466, and 0.8314, respectively. In addition, it shows the explicit variability on monthly and yearly crop water demands of these three sorts of irrigation schemes when the adjusted Kc-IrriSAT was employed. It would be concluded that cloud-based IrriSAT application can be a very supportive tool in estimating the actual crop water requirement particularly for irrigators to evaluate the current status of irrigation water use and to improve the irrigation efficiency at the field scale. |
