Application of GAOT to predict irrigation water quality using electrical conductivity mode

• Main Authors: LI, KUO-CHANG, 李國彰
• Other Authors: CHEN, LI
• Format: Others
• Language: zh-TW
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/09728518042252534622

碩士 === 中華大學 === 土木工程學系 === 104 === Irrigated areas of the Taiwan Joint Irrigation Associations at Yunlin do not have any reservoirs to provide backup supplies of water, necessitating the use of primary or secondary return flow for irrigation purposes. However, water quality standards and pollution issues of these water sources are difficult to manage. This study therefore proposed using 2 algorithms of regression analysis and GAOT to assess water quality and conditions of actual irrigation systems in order to establish water quality prediction models based upon upstream canal discharges and downstream return flows. The scope of this study focused upon the 3 work stations of Yinxi, Xiluo, and Jingtong, starting from the Luchangke Canal and its downstream tributaries, covering the discharges at new (and old) Dingbitou, Xiluo, and Gancuo, and finally reaching the Dayilun main channel in order to understand upstream and downstream allocation relationships of the overall irrigation and discharge system. Irrigation water quality data from various monitoring points were used to establish the water quality prediction model and to establish relationships between upstream and downstream water quality along the irrigation and discharge system. Results of scatter plot revealed that GAOT provided better predictions than regression analysis, with correlation coefficients ranging from 0.72 to 0.86. Including real-time water quality monitoring data in the prediction model can help resolve the repeated testing as well as time and labor intensive issues of conventional manual processes.