Spatio-Temporal Distribution of Land Use and Groundwater by Multivariate Statistical Analysis in Tainan Area

• Main Authors: HUANG, KUEI-FANG, 黃楏方
• Other Authors: LO, KWONG-FAI ANDREW
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/p2xamg

碩士 === 中國文化大學 === 地學研究所地理組 === 106 === Drought caused by climate change may increase frequency of groundwater use in the southern Taiwan which is the major producer of agricultural products. In order to understand the relationship between land use and groundwater change, this study uses PCA(Principle Component Analysis) to analyze monthly average groundwater level from 2004 to 2013 at Tainan City. Components are analyzed using GWR(Geographically Weighted Regression) to compare land use and to conjecture the driving force of groundwater level change. Results show that the principle components in every aquifer can explain more than 80% of the ratio of the original data. The principle component results (high eigenvalues) of each aquifer are highly correlated with the groundwater level stations, but their correlation decreases with the increase of the number of principal components and the depth of the aquifer. This indicates that in shallow aquifers, the change of groundwater level is obviously directly affected by man-made and natural factors near groundwater stations, while the deep aquifers are affected by other factors. In GWR, the spatial distribution of groundwater level is also different because of different seasons and different land use. Among them, the influence caused by the fourth aquifer forest and aquaculture land is significant. The influence of the aquaculture land in winter coastal areas is most significant. The forest land in summer mountain area has the most obvious influence. Although regression model of seasons and land use types do not exhibit significant meanings, the GWR can still demonstrate groundwater level changes accurately under different time scales. It can also provide important information for groundwater resource management.