- 期刊
以地理加權迴歸分析建立灌溉率與各影響因子之關係
Using Geographically Weighted Regression to Build the Relationship with Irrigation Rate and Effecting Factors
摘要
台灣目前農業用水為用水的大宗，而灌溉用水又佔農業用水之87%，在面對用水不足的壓力下，農業用水成為最大的轉移目標，因此應配合農業用水結構的改變，水稻灌溉用水量需予以合理估算。目前在灌溉用水的估算方面乃採用「灌溉率」的方式計算之，其來源乃是依據工作人員與農民多年工作經驗粗估得知。使用上雖簡便，卻無法由其數值中得知灌溉率與各影響因子間的關係，因此其最大問題為一定值，無法隨各因子變動而調整。故本研究擬以嘉南水利會二期作水田區域為研究對象，藉由空間迴歸找出灌溉率的影響因子，並建立各因子與灌溉率的關係，同時討論各因子在空間上的變化情形。研究結果發現入滲率、溫度、降雨量為其影響因子，而溫度、降雨量其迴歸係數具有空間上顯著的差異。
並列摘要
Agricultural sector in Taiwan holds the biggest share (70%) of water right. About 87% of agricultural water consumption is utilized for irrigation purpose. Water right reallocation becomes a more pressing pressure on agricultural sector because the shortages in water supply comparing to the continuously increasing water demands. An efficient assessment for agricultural water demand is necessary for this regional water reallocation decisions, Irrigation Rate is currently used by Irrigation Association in Taiwan for estimating water demand of paddy farming. These irrigation rates were made up through working experience of the staffs and farmers. Although it is a convenient way for demand assessment, it is difficult to adjust according to the cropping pattern change because the relationships between the Irrigation Rate and related affecting factors are unknown. The Irrigation rate are mainly affected by farm water requirement, as well as the losses in percolation, conveyance and irrigation management practices. This paper introduces the Geographically Weighted Regression to analyze the relationship among irrigation rate and the spatially distributed affecting factor like rainfall, soil and temperature. It is found that the Geographically Weighted Regression does significantly improve the traditional regression and capture the spatial variations of the affecting factors.