水資源為全球最為重要的自然資源之一，氣候變遷帶來的溫度及降雨的變化已直接影響水文循環並對水資源運用構成嚴重的威脅，由於地表水短缺，民生、工業及農業需仰賴地下水以滿足用水需求。在臺灣，地下水被視為重要的水資源之一，其使用量約占總用水量的33%，因此地下水的管理至關重要，考量桃園地區的產業結構快速變遷，從傳統的農業和勞力密集型產業轉變為高科技產業，且桃園地區的水資源供給與用水標的也較其他地區多元，故本研究蒐集桃園地區地表高程、土地利用/覆蓋、土壤類型、氣象、水文地質及地下水位等相關資料，結合土壤水文評估模型 Soil and Water Assessment Tool (SWAT)與地下水流數值模型 Groundwater Modeling System (GMS)模擬，探討在TaiESM1氣候模型推估氣候變化下，未來桃園地區受到氣候變遷降雨量變化造成地表逕流與入滲差異，以及對未來地下水水位的影響，研究結果顯示，降雨型態變化與全球氣候模型推估結果相似，豐枯水期差距越來越大，且有豐越豐、枯越枯趨勢，特別是在最嚴重暖化 (SSP5-8.5) 情境下，枯水期降雨量減少最為明顯，至世紀末將減少20.09%；地表入滲量不僅與降雨強度、季節及型態相關，亦受土地利用、土壤特性與空間分布不均等因素影響，加上乾旱事件週期性拉長，可能導致土壤結塊與疏水性，使降雨期間地表逕流增加，同時減少地下水的補注，預測至世紀末最嚴重暖化程度(SSP5-8.5)情境下，降雨量減少24.12~28.29%，地表逕流量山區和沿海地區分別減少33.52%與41.55%，入滲量減少59.78%，山區入滲量約為353 mm，沿海地區入滲量為159 mm，且受氣候變化影響將導致地下水水位低於安全水位，特別是在沿海工業區附近觀測井，至世紀末在最嚴重暖化(SSP5-8.5)情境下低於嚴重下限水位約有14~84%月份，其中多集中在12月至隔年2月，綜上所述，受到全球氣候變異的影響，使得極端氣候事件越來越頻繁進而影響水文平衡，降雨量的減少不僅影響地表水及地下水，因此未來強化水資源的有效利用是不可或缺的，更需以多元化方式開發新水源，例如再生水利用、海水淡化、貯留雨水等，以因應未來氣候變遷水資源短缺之問題，確保民生與工業用水穩定性。

Water resources are among the most crucial natural resources globally. Climate change, through alterations in temperature and precipitation, has directly impacted the hydrological cycle, posing significant threats to the utilization of water resources. Due to surface water shortages, domestic, industrial, and agricultural sectors increasingly rely on groundwater to meet their water needs. In Taiwan, groundwater is considered one of the key water resources, accounting for approximately 33% of the total water usage. Therefore, the management of groundwater is critically important. Considering the rapid transformation of the industrial structure in the Taoyuan area from traditional agriculture and labor-intensive industries to high-tech industries, and the more diverse water supply and usage targets compared to other regions, this study collects relevant data from the Taoyuan area, including surface elevation, land use/cover, soil types, meteorology, hydrogeology, and groundwater levels. This data is integrated with the Soil and Water Assessment Tool (SWAT) and the Groundwater Modeling System (GMS) to simulate the impacts of climate change under the TaiESM1 climate model projections. The study explores the variations in surface runoff and infiltration due to changes in precipitation patterns and their subsequent effects on future groundwater levels in the Taoyuan area.
The results indicate that changes in precipitation patterns are similar to the projections from global climate models, with an increasing disparity between wet and dry seasons, becoming wetter during the wet season and drier during the dry season. Notably, under the fossil-fueled development scenario (SSP5-8.5), the reduction in precipitation during the dry season is the most pronounced, decreasing by 20.09% by the end of the century. Infiltration rates are influenced not only by rainfall intensity, season, and patterns but also by land use, soil characteristics, and spatial distribution. Prolonged drought events could lead to soil compaction and hydrophobicity, increasing surface runoff during rainfall and reducing groundwater recharge. Under the fossil-fueled development scenario (SSP5-8.5), by the end of the century, precipitation is projected to decrease by 24.12-28.29%, surface runoff in mountainous and coastal areas is expected to decrease by 33.52% and 41.55% respectively, and infiltration is predicted to reduce by 59.78%. Infiltration rates in mountainous areas will be around 353 mm and 159 mm in coastal areas. Climate change impacts will cause groundwater levels to drop below safe levels, particularly in observation wells near coastal industrial zones, where, under the fossil-fueled development scenario (SSP5-8.5), groundwater levels are predicted to be below the critical threshold for about 14-84% of the months, predominantly from December to February.
In conclusion, global climate variability is leading to more frequent extreme weather events, thereby affecting hydrological balance. The reduction in precipitation impacts both surface and groundwater resources. Therefore, enhancing the efficient use of water resources is indispensable in the future. Diverse approaches to developing new water sources, such as recycled water, seawater desalination, and rainwater harvesting, are necessary to address future water shortages due to climate change, ensuring the stability of water supply for domestic and industrial use.

第一章	前言	1
1.1	研究背景	1
1.2	研究架構	3
第二章	文獻回顧	4
2.1	地下水數值模型之應用	4
2.2	地表補注量之推估方法	5
2.3	整合地表水與地下水模型評估氣候變遷對地下水水位之影響	7
第三章	材料與方法	10
3.1	研究區域概述	10
3.2	SWAT水文模型	14
3.2.1	氣象參數蒐集與補遺	17
3.2.2	土地利用與覆蓋資料彙整	21
3.2.3	簡化土壤分類	24
3.2.4	河川水深-流量率定曲線	32
3.3	氣候變遷降雨情境	34
3.4	GMS地下水模型	36
3.5	GMS地下水模型輸入與參數設定	37
3.5.1    水文地質資料收集	37
3.5.2	地下水補注及抽水量估算	38
3.5.3	研究區域概念模型及相關參數	40
3.5.4	GMS地下水模型率定與驗證	44
3.6	地下水安全管理水位	45

第四章	結果與討論	47
4.1	SWAT模型率定與驗證	47
4.2	現在及未來不同SSP情境之地表水循環變化	49
4.2.1	2016-2020年水平衡變化	49
4.2.2	推估未來四種SSP情境水平衡變化	53
4.3	地下水模型率定及驗證結果	59
4.4	氣候變遷對桃園地下水水位影響	62
第五章	結論與建議	70
5.1結論	70
5.2建議	71
參考文獻	72

 
圖目錄
圖1-1、近10年供水情勢枯旱預警	3
圖1-2、研究流程	3
圖3-1、研究區域圖	10
圖3-2、龍潭至觀音之地質剖面圖	12
圖3-3、陽明公園至大園之地質剖面圖	13
圖3-4、SWAT模型模擬水文循環過程示意圖	15
圖3-5、桃園中壢台地區域氣象測站分佈	18
圖3-6、新屋測站與其他氣象測站氣象參數相關性分析	19
圖3-7、南崁溪流域氣象站分佈圖	20
圖3-8、桃園與蘆竹氣象測站氣象參數相關性分析	21
圖3-9、桃園中壢台地土地利用分佈圖	23
圖3-10、土壤質地三角圖(USDA SOIL TEXTURE TRIANGLE)	24
圖3-11、相同土壤質地簡化流程示意圖(以SILTY CLAY為例)	26
圖3-12、SILTY LOAM砂粒比累積面積曲線圖	27
圖3-13、SILTY LOAM各砂粒比所占面積圖	27
圖3-14、SILTY CLAY砂粒比累積面積曲線圖	27
圖3-15、SILTY CLAY各砂粒比所占面積圖	28
圖3-16、SILTY CLAY LOAM砂粒比累積面積曲線圖	28
圖3-17、SILTY CLAY LOAM各砂粒比所占面積圖	28
圖3-18、SANDY LOAM砂粒比累積面積曲線圖	29
圖3-19、SANDY LOAM各砂粒比所占面積圖	29
圖3-20、SANDY CLAY LOAM砂粒比累積面積曲線圖	30
圖3-21、SANDY CLAY LOAM各砂粒比所占面積圖	30
圖3-22、LOAMY SAND砂粒比累積面積曲線圖	30
圖3-23、LOAMY SAND各砂粒比所占面積圖	31
圖3-24、桃園中壢台地區域土壤分佈圖	31
圖3-25、桃園地區水位流量站狀態圖	32
圖3-26、2001-2002年流量水位關係圖	33
圖3-27、南崁溪流域降雨量與流量關係圖	33
圖3-28、桃園中壢台地鑽探井分布圖	38
圖3-29、桃園中壢台地各鄉鎮市區2016~2020年年平均抽水量分佈	39
圖3-30、桃園中壢台地地下水模型邊界條件示意圖	40
圖3-31、桃園中壢台地山區龍潭地下水位與氣象觀測站降雨量變化趨勢	41
圖3-32、桃園中壢台地地下水位高程與地表高程之相關性	41
圖3-33、桃園中壢台地第一含水層水力傳導係數分佈	43
圖3-34、桃園中壢台地第二含水層水力傳導係數分佈	43
圖3-35、桃園中壢台地初始水位分佈圖	44
圖3-36、地下水安全管理水位示意圖	46
圖4-1、SWAT模型南崁溪流子流域劃分	47
圖4-2、南崁溪流域模擬流量及觀測流量率定與驗證之結果	48
圖4-3、桃園中壢台地2016-2020年降雨量、入滲量、及地表逕流量之差異	49
圖4-4、桃園中壢台地區域SWAT模型推估2016~2020年降雨量空間分布圖	50
圖4-5、桃園中壢台地區域SWAT模型推估2016~2020年入滲量空間分布圖	51
圖4-6、桃園中壢台地區域SWAT模型推估2016~2020年地表逕流空間分布圖	52
圖4-7、桃園中壢台地未來近中末世紀不同暖化情境最高溫與最低溫變化量	53
圖4-8、桃園中壢台地未來近中末世紀不同暖化情境豐枯水期降雨量變化	54
圖4-9、桃園中壢台地未來不同暖化情境水平衡變化圖	56
圖4-10、桃園中壢台地未來不同暖化情境降雨量變化空間分布圖	58
圖4-11、桃園中壢台地未來不同暖化情境入滲量變化空間分布圖	58
圖4-12、桃園中壢台地未來不同暖化情境地表逕流變化空間分布圖	58
圖4-13、桃園中壢台地水力傳導係數率定前後分布圖	59
圖4-14、穩態模擬水位與觀測水位率定驗證之結果	59
圖4-15、桃園中壢台地各鄉鎮市區抽水量率定後與工業區分布圖	60
圖4-16、各觀測井暫態模擬水位與觀測水位率定驗證之結果	62
圖4-17、各觀測井未來至世紀末不同暖化情境水位變化	63
圖4-18、各觀測井不同暖化情境於未來三個時期低於於嚴重下限水位之比例	64
圖4-19、近世紀各月份不同暖化情境低於嚴重下限水位之比例	65
圖4-20、世紀中各月份不同暖化情境低於嚴重下限水位之比例	66
圖4-21、世紀末各月份不同暖化情境低於嚴重下限水位之比例	67

 
表目錄
表2-1、常見地下水數值模型優缺點比較表	4
表3-1、SWAT模型模擬表現標準表	17
表3-2、桃園中壢台地區域氣象測站資訊	18
表3-3、國土測繪中心第二級土地利用資料對應SWAT模型分類	22
表3-4、桃園中壢台地及南崁溪流域於SWAT模型土地利用分類及占地面積	23
表3-5、桃園中壢台地土壤相關參數計算及分類結果	25
表3-6、桃園中壢台地區厚度分層表	38
表3-7、桃園中壢台地區各標的地下水取用量	39
表3-8、桃園中壢台地區各測站之水力傳導係數	42
表3-9、各材料比比出水量(SY)與儲水係數(SS)對照表	42
表4-1、南崁溪流域率定參數與各參數最適值	48

1.	Abbaspour, K. C. (2013). SWAT-CUP 2012: SWAT calibration and uncertainty programs–a user manual. Eawag: Dübendorf, Switzerland, 103.
2.	Abbaspour, K. C., Rouholahnejad, E., Vaghefi, S., Srinivasan, R., Yang, H., & Kløve, B. (2015). A continental-scale hydrology and water quality model for Europe: Calibration and uncertainty of a high-resolution large-scale SWAT model. Journal of Hydrology, 524, 733–752. https://doi.org/10.1016/j.jhydrol.2015.03.027
3.	Abd-Elaty, I., Saleh, O. K., Ghanayem, H. M., Zeleňáková, M., & Kuriqi, A. (2022). Numerical assessment of riverbank filtration using gravel back filter to improve water quality in arid regions. Frontiers in Earth Science, 10. https://doi.org/10.3389/feart.2022.1006930
4.	Adhikari, R. K., Mohanasundaram, S., & Shrestha, S. (2020). Impacts of land-use changes on the groundwater recharge in the Ho Chi Minh city, Vietnam. Environmental Research, 185, 109440. https://doi.org/10.1016/j.envres.2020.109440
5.	Arnold, J. G., Srinivasan, R., Muttiah, R. S., & Williams, J. R. (1998). Large Area Hydrologic Modeling and Assessment Part I: Model Development1. JAWRA Journal of the American Water Resources Association, 34(1), 73–89. https://doi.org/10.1111/j.1752-1688.1998.tb05961.x
6.	Barreto-Martin, C., Sierra-Parada, R., Calderón-Rivera, D., Jaramillo-Londono, A., & Mesa-Fernández, D. (2021). Spatio-temporal analysis of the hydrological response to land cover changes in the sub-basin of the Chicú river, Colombia. Heliyon, 7(7), e07358. https://doi.org/10.1016/j.heliyon.2021.e07358
7.	Boonwichai, S., Shrestha, S., Babel, M. S., Weesakul, S., & Datta, A. (2018). Climate change impacts on irrigation water requirement, crop water productivity and rice yield in the Songkhram River Basin, Thailand. Journal of Cleaner Production, 198, 1157–1164. https://doi.org/10.1016/j.jclepro.2018.07.146
8.	Chang, C. H., Harrison, J. F., & Huang, Y. C. (2015). Modeling typhoon-induced alterations on river sediment transport and turbidity based on dynamic landslide inventories: Gaoping River Basin, Taiwan. Water (Switzerland), 7(12), 6910–6930. https://doi.org/10.3390/w7126666
9.	Chang, S. W., Clement, T. P., Simpson, M. J., & Lee, K.-K. (2011). Does sea-level rise have an impact on saltwater intrusion? Advances in Water Resources, 34(10), 1283–1291. https://doi.org/10.1016/j.advwatres.2011.06.006
10.	Chen, C.-S., & Chen, Y.-L. (2003). The Rainfall Characteristics of Taiwan. Monthly Weather Review, 131(7), 1323–1341. https://doi.org/10.1175/1520-0493(2003)131<1323:TRCOT>2.0.CO;2
11.	Crosbie, R. S., McCallum, J. L., Walker, G. R., & Chiew, F. H. S. (2010). Modelling climate-change impacts on groundwater recharge in the Murray-Darling Basin, Australia. Hydrogeology Journal, 18(7), 1639–1656. https://doi.org/10.1007/s10040-010-0625-x
12.	Dang, M.-Q., Wang, S.-J., Fu, C.-C., & Truong, H.-D. (2024). Coastal flowing artesian wells and submarine groundwater discharge driven by tidal variation at TaiCOAST site in Taoyuan, Taiwan. Journal of Hydrology: Regional Studies, 52, 101708. https://doi.org/10.1016/j.ejrh.2024.101708
13.	Domenico, P. A. (1972). Concepts and Models in Groundwater Hydrology. McGraw-Hill.
14.	Dos Santos, F. M., de Souza Pelinson, N., de Oliveira, R. P., & Di Lollo, J. A. (2023). Using the SWAT model to identify erosion prone areas and to estimate soil loss and sediment transport in Mogi Guaçu River basin in Sao Paulo State, Brazil. CATENA, 222, 106872. https://doi.org/10.1016/j.catena.2022.106872
15.	El assaoui, N., Sadok, A., & Merimi, I. (2021). Impacts of climate change on Moroccan’s groundwater resources: State of art and development prospects. Materials Today: Proceedings, 45, 7690–7696. https://doi.org/10.1016/j.matpr.2021.03.220
16.	El-Kadi, A. I., Tillery, S., Whittier, R. B., Hagedorn, B., Mair, A., Ha, K., & Koh, G.-W. (2014). Assessing sustainability of groundwater resources on Jeju Island, South Korea, under climate change, drought, and increased usage. Hydrogeology Journal, 22(3), 625–642. https://doi.org/10.1007/s10040-013-1084-y
17.	Eltarabily, M. G., Abd-Elaty, I., Elbeltagi, A., Zeleňáková, M., & Fathy, I. (2023). Investigating Climate Change Effects on Evapotranspiration and Groundwater Recharge of the Nile Delta Aquifer, Egypt. Water, 15(3), 572. https://doi.org/10.3390/w15030572
18.	Gao, F., Feng, G., Han, M., Dash, P., Jenkins, J., & Liu, C. (2019). Assessment of Surface Water Resources in the Big Sunflower River Watershed Using Coupled SWAT–MODFLOW Model. Water, 11(3), Article 3. https://doi.org/10.3390/w11030528
19.	Gassman, P. W., Sadeghi, A. M., & Srinivasan, R. (2014). Applications of the SWAT Model Special Section: Overview and Insights. Journal of Environmental Quality, 43(1), 1–8. https://doi.org/10.2134/jeq2013.11.0466
20.	Gautam, D., & N. Prajapati, R. (2014). Drawdown and Dynamics of Groundwater Table in Kathmandu Valley, Nepal. The Open Hydrology Journal, 8(1). https://benthamopen.com/ABSTRACT/TOHYDJ-8-17
21.	Ghimire, U., Shrestha, S., Neupane, S., Mohanasundaram, S., & Lorphensri, O. (2021). Climate and land-use change impacts on spatiotemporal variations in groundwater recharge: A case study of the Bangkok Area, Thailand. Science of The Total Environment, 792, 148370. https://doi.org/10.1016/j.scitotenv.2021.148370
22.	Ghosh, D., Mandal, M., Banerjee, M., & Karmakar, M. (2020). Impact of hydro-geological environment on availability of groundwater using analytical hierarchy process (AHP) and geospatial techniques: A study from the upper Kangsabati river basin. Groundwater for Sustainable Development, 11, 100419. https://doi.org/10.1016/j.gsd.2020.100419
23.	Gohar, A. A., Cashman, A., & Ward, F. A. (2019). Managing food and water security in Small Island States: New evidence from economic modelling of climate stressed groundwater resources. Journal of Hydrology, 569, 239–251. https://doi.org/10.1016/j.jhydrol.2018.12.008
24.	Green, T. R., Taniguchi, M., Kooi, H., Gurdak, J. J., Allen, D. M., Hiscock, K. M., Treidel, H., & Aureli, A. (2011). Beneath the surface of global change: Impacts of climate change on groundwater. Journal of Hydrology, 405(3–4), 532–560. https://doi.org/10.1016/j.jhydrol.2011.05.002
25.	Green, T. R. (2016). Linking Climate Change and Groundwater. In A. J. Jakeman, O. Barreteau, R. J. Hunt, J.-D. Rinaudo, & A. Ross (Eds.), Integrated Groundwater Management: Concepts, Approaches and Challenges (pp. 97–141). Springer International Publishing. https://doi.org/10.1007/978-3-319-23576-9_5
26.	Green, W. H., & Ampt, G. A. (1911). Studies on Soil Phyics. The Journal of Agricultural Science, 4(1), 1–24. https://doi.org/10.1017/S0021859600001441
27.	Groundwater Modeling System Introduction, from https://www.aquaveo.com/software/gms-groundwater-modeling-system-introduction
28.	Hamad, R., Balzter, H., & Kolo, K. (2018). Predicting Land Use/Land Cover Changes Using a CA-Markov Model under Two Different Scenarios. Sustainability, 10(10), Article 10. https://doi.org/10.3390/su10103421
29.	Hosseinizadeh, A., Zarei, H., Akhondali, A. M., Seyedkaboli, H., & Farjad, B. (2019). Potential impacts of climate change on groundwater resources: A multi-regional modelling assessment. Journal of Earth System Science, 128(5), 131. https://doi.org/10.1007/s12040-019-1134-5
30.	Huang, W.-R., Liu, P.-Y., & Hsu, J. (2021). Multiple timescale assessment of wet season precipitation estimation over Taiwan using the PERSIANN family products. International Journal of Applied Earth Observation and Geoinformation, 103, 102521. https://doi.org/10.1016/j.jag.2021.102521
31.	Hutchins, M. G., Abesser, C., Prudhomme, C., Elliott, J. A., Bloomfield, J. P., Mansour, M. M., & Hitt, O. E. (2018). Combined impacts of future land-use and climate stressors on water resources and quality in groundwater and surface waterbodies of the upper Thames river basin, UK. Science of The Total Environment, 631–632, 962–986. https://doi.org/10.1016/j.scitotenv.2018.03.052
32.	IPCC, 2014: Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and L.A. Meyer (eds.)]. IPCC, Geneva, Switzerland, 151 pp.
33.	Karki, R., Srivastava, P., Kalin, L., Mitra, S., & Singh, S. (2021). Assessment of impact in groundwater levels and stream-aquifer interaction due to increased groundwater withdrawal in the lower Apalachicola-Chattahoochee-Flint (ACF) River Basin using MODFLOW. Journal of Hydrology: Regional Studies, 34, 100802. https://doi.org/10.1016/j.ejrh.2021.100802
34.	Lam, Q. D., Meon, G., & Pätsch, M. (2021). Coupled modelling approach to assess effects of climate change on a coastal groundwater system. Groundwater for Sustainable Development, 14, 100633. https://doi.org/10.1016/j.gsd.2021.100633
35.	Lemieux, J.-M., Hassaoui, J., Molson, J., Therrien, R., Therrien, P., Chouteau, M., & Ouellet, M. (2015). Simulating the impact of climate change on the groundwater resources of the Magdalen Islands, Québec, Canada. Journal of Hydrology: Regional Studies, 3, 400–423. https://doi.org/10.1016/j.ejrh.2015.02.011
36.	Li, F., Feng, P., Zhang, W., & Zhang, T. (2013). An Integrated Groundwater Management Mode Based on Control Indexes of Groundwater Quantity and Level. Water Resources Management, 27(9), 3273–3292. https://doi.org/10.1007/s11269-013-0346-8
37.	Li, S.-Y., Miao, L.-J., Jiang, Z.-H., Wang, G.-J., Gnyawali, K. R., Zhang, J., Zhang, H., Fang, K., He, Y., & Li, C. (2020b). Projected drought conditions in Northwest China with CMIP6 models under combined SSPs and RCPs for 2015–2099. Advances in Climate Change Research, 11(3), 210–217. https://doi.org/10.1016/j.accre.2020.09.003
38.	Loucks, D. P., & van Beek, E. (2017). Water Resources Planning and Management: An Overview. In D. P. Loucks & E. van Beek (Eds.), Water Resource Systems Planning and Management: An Introduction to Methods, Models, and Applications (pp. 1–49). Springer International Publishing. https://doi.org/10.1007/978-3-319-44234-1_1
39.	Lu, C.-M., & Chiang, L.-C. (2019). Assessment of Sediment Transport Functions with the Modified SWAT-Twn Model for a Taiwanese Small Mountainous Watershed. Water, 11(9), Article 9. https://doi.org/10.3390/w11091749
40.	McDonald, M. G., & Harbaugh, A. W. (1988). A modular three-dimensional finite-difference ground-water flow model. In Techniques of Water-Resources Investigations (06-A1). U.S. G.P.O.,. https://doi.org/10.3133/twri06A1
41.	Ministry for the Environment, & Stats NZ. (2020). Our atmosphere and climate 2020. Ministry for the Environment & Stats NZ. https://www.mfe.govt.nz/publications/environmental-reporting/our-atmosphere-and-climate-2020
42.	Mittelstet, A. r., Storm, D. e., & Fox, G. a. (2017). Testing of the Modified Streambank Erosion and Instream Phosphorus Routines for the SWAT Model. JAWRA Journal of the American Water Resources Association, 53(1), 101–114. https://doi.org/10.1111/1752-1688.12485
43.	Morris, D. A., & Johnson, A. I. (1967). Summary of hydrologic and physical properties of rock and soil materials, as analyzed by the hydrologic laboratory of the U.S. Geological Survey, 1948-60. In Water Supply Paper (1839-D). U.S. Government Printing Office. https://doi.org/10.3133/wsp1839D
44.	Moriasi, D. N., Gitau, M. W., Pai, N., & Daggupati, P. (2015). Hydrologic and Water Quality Models: Performance Measures and Evaluation Criteria. Transactions of the ASABE, 58, 1763–1785.
45.	Mourot, F. M., Westerhoff, R. S., White, P. A., & Cameron, S. G. (2022). Climate change and New Zealand’s groundwater resources: A methodology to support adaptation. Journal of Hydrology: Regional Studies, 40, 101053. https://doi.org/10.1016/j.ejrh.2022.101053
46.	Otkin, J. A., Anderson, M. C., Hain, C., Svoboda, M., Johnson, D., Mueller, R., Tadesse, T., Wardlow, B., & Brown, J. (2016). Assessing the evolution of soil moisture and vegetation conditions during the 2012 United States flash drought. Agricultural and Forest Meteorology, 218–219, 230–242. https://doi.org/10.1016/j.agrformet.2015.12.065
47.	Otkin, J. A., Svoboda, M., Hunt, E. D., Ford, T. W., Anderson, M. C., Hain, C., & Basara, J. B. (2018). Flash Droughts: A Review and Assessment of the Challenges Imposed by Rapid-Onset Droughts in the United States. Bulletin of the American Meteorological Society, 99(5), 911–919. https://doi.org/10.1175/BAMS-D-17-0149.1
48.	Oude Essink, G.H.P., van Baaren, E.S., de Louw, P.G.B., 2010. Effects of climate change on coastal groundwater systems: a modeling study in The Netherlands. Water Resour. Res. 46, W00F04. https://doi.org/10.1029/2009WR008719.
49.	Our atmosphere and climate 2020. (2020, October 1). Ministry for the Environment. https://environment.govt.nz/publications/our-atmosphere-and-climate-2020/
50.	Pan, Y., Gong, H., ZHou, D., Li, X., & Nakagoshi, N. (2011). Impact of land use change on groundwater recharge in Guishui River Basin, China. Chinese Geographical Science, 21(6), 734–743. https://doi.org/10.1007/s11769-011-0508-7
51.	Pendergrass, A. G., Meehl, G. A., Pulwarty, R., Hobbins, M., Hoell, A., AghaKouchak, A., Bonfils, C. J. W., Gallant, A. J. E., Hoerling, M., Hoffmann, D., Kaatz, L., Lehner, F., Llewellyn, D., Mote, P., Neale, R. B., Overpeck, J. T., Sheffield, A., Stahl, K., Svoboda, M., … Woodhouse, C. A. (2020). Flash droughts present a new challenge for subseasonal-to-seasonal prediction. Nature Climate Change, 10(3), 191–199. https://doi.org/10.1038/s41558-020-0709-0
52.	Pisinaras, V., Paraskevas, C., & Panagopoulos, A. (2021). Investigating the Effects of Agricultural Water Management in a Mediterranean Coastal Aquifer under Current and Projected Climate Conditions. Water, 13(1), 108. https://doi.org/10.3390/w13010108
53.	Ponpang-Nga, P., & Techamahasaranont, J. (2016). Effects of climate and land use changes on water balance in upstream in the Chao Phraya River basin, Thailand. Agriculture and Natural Resources, 50(4), 310–320. https://doi.org/10.1016/j.anres.2016.10.005
54.	Purjenaie, A., Moradi, M., Noruzi, A., & Majidi, A. (2012). Prediction of Aquifer Drawdown Using MODFLOW Mathematical Model (Case Study: Sarze Rezvan Plain, Iran). Geosciences, 2(5), 112–116.
55.	Sahoo, S., Sil, I., Dhar, A., Debsarkar, A., Das, P., & Kar, A. (2018). Future scenarios of land-use suitability modeling for agricultural sustainability in a river basin. Journal of Cleaner Production, 205, 313–328. https://doi.org/10.1016/j.jclepro.2018.09.099
56.	Samper, J., Li, Y., & Pisani, B. (2015). An evaluation of climate change impacts on groundwater flow in the Plana de La Galera and Tortosa alluvial aquifers (Spain). Environmental Earth Sciences, 73(6), 2595–2608. https://doi.org/10.1007/s12665-014-3734-3
57.	Scanlon, B. R., Reedy, R. C., Faunt, C. C., Pool, D., & Uhlman, K. (2016). Enhancing drought resilience with conjunctive use and managed aquifer recharge in California and Arizona. Environmental Research Letters, 11(3), 035013. https://doi.org/10.1088/1748-9326/11/3/035013
58.	Service, U. S. S. C. (1972). SCS National Engineering Handbook, Section 4: Hydrology. The Service.
59.	Shahid, S., Alamgir, M., Wang, X., & Eslamian, S. (2017). Climate Change Impacts on and Adaptation to Groundwater (pp. 108–120).
60.	Shrestha, S., Bach, T. V., & Pandey, V. P. (2016). Climate change impacts on groundwater resources in Mekong Delta under representative concentration pathways (RCPs) scenarios. Environmental Science & Policy, 61, 1–13. https://doi.org/10.1016/j.envsci.2016.03.010
61.	Sixth Assessment Report—IPCC, from https://www.ipcc.ch/assessment-report/ar6/
62.	Supari, Tangang, F., Juneng, L., Cruz, F., Chung, J. X., Ngai, S. T., Salimun, E., Mohd, M. S. F., Santisirisomboon, J., Singhruck, P., PhanVan, T., Ngo-Duc, T., Narisma, G., Aldrian, E., Gunawan, D., & Sopaheluwakan, A. (2020). Multi-model projections of precipitation extremes in Southeast Asia based on CORDEX-Southeast Asia simulations. Environmental Research, 184, 109350. https://doi.org/10.1016/j.envres.2020.109350
63.	Tariq, A., & Shu, H. (2020). CA-Markov Chain Analysis of Seasonal Land Surface Temperature and Land Use Land Cover Change Using Optical Multi-Temporal Satellite Data of Faisalabad, Pakistan. Remote Sensing, 12(20), Article 20. https://doi.org/10.3390/rs12203402
64.	Tizora, P., Roux, A. le, Mans, G., & Cooper, A. K. (2018). Adapting the Dyna-CLUE model for simulating land use and land cover change in the Western Cape Province. South African Journal of Geomatics, 7(2), Article 2. https://doi.org/10.4314/sajg.v7i2.7
65.	Treidel, H., Martin-Bordes, J. L., & Gurdak, J. J. (2012). Climate Change Effects on Groundwater Resources: A Global Synthesis of Findings and Recommendations. CRC Press.
66.	Natural Resources Conservation Service, from USDA Website: https://www.nrcs.usda.gov/
67.	USGS, 2020. Ice, Snow, and Glaciers and the Water Cycle. August. Retrieved from USGS Website: https://www.usgs.gov/special-topic/water-science-school/science/ice -snow-and-glaciers-and-water-cycle?qt-science_center_objects=0#qt-science_cente r_objects.
68.	Webb, M. D., & Howard, K. W. F. (2011). Modeling the transient response of saline intrusion to rising sea-levels. Ground Water, 49(4), 560–569. https://doi.org/10.1111/j.1745-6584.2010.00758.x
69.	Winkler, K., Fuchs, R., Rounsevell, M., & Herold, M. (2021). Global land use changes are four times greater than previously estimated. Nature Communications, 12(1). Scopus. https://doi.org/10.1038/s41467-021-22702-2
70.	World development report 2010 : development and climate change (English). World development report Washington, D.C. : World Bank Group. http://documents.worldbank.org/curated/en/201001468159913657/World-development-report-2010-development-and-climate-change
71.	Yifru, B. A., Chung, I.-M., Kim, M.-G., & Chang, S. W. (2020). Assessment of Groundwater Recharge in Agro-Urban Watersheds Using Integrated SWAT-MODFLOW Model. Sustainability, 12(16), Article 16. https://doi.org/10.3390/su12166593
72.	Yifru, B. A., Chung, I.-M., Kim, M.-G., & Chang, S. W. (2021). Assessing the Effect of Land/Use Land Cover and Climate Change on Water Yield and Groundwater Recharge in East African Rift Valley using Integrated Model. Journal of Hydrology: Regional Studies, 37, 100926. https://doi.org/10.1016/j.ejrh.2021.100926
73.	Zamanirad, M., Sedghi, H., Sarraf, A., Saremi, A., & Rezaee, P. (2018). Potential impacts of climate change on groundwater levels on the Kerdi-Shirazi plain, Iran. Environmental Earth Sciences, 77(11), 415. https://doi.org/10.1007/s12665-018-7585-1
74.	大氣科學研究與應用資料庫:
https://asrad.pccu.edu.tw/dbar/
75.	經濟部水利署全球資訊網
https://www.wra.gov.tw/Default.aspx
76.	經濟部水利署水權資訊網:
https://wr.wra.gov.tw/WRTInfoFrontEnd/
77.	經濟部中央地質調查所地質雲加值應用平臺:
http://www.geologycloud.tw/map/hydro
78.	吳益裕、林啓峰、劉瓊玲、溫志超、林建利 (2021)。地下水管理水位之演進與運用。土木水利，48(6)。
79.	李振誥、余進利、陳志忠、陳榮華 (1998)。彰化地區淺層地表土壤入滲行為之研究。台灣水利，46(2)，12–22。
80.	林時猷 (2003)。以地下水位之區位相關性輔助濁水溪沖積扇地下水模擬之參數決定(碩士論文)。逢甲大學土木及水利工程所。
81.	桃園市政府水務局，109年桃園市智慧下水管理推動計畫，2020。
82.	桃園市政府水務局，110年桃園市智慧下水管理推動計畫，2021。
83.	氣候變遷災害風險調適平台:
https://dra.ncdr.nat.gov.tw/
84.	內政部國土測繪中心國土測繪圖資:
https://whgis-nlsc.moi.gov.tw/Opendata/Files.aspx
85.	陳希軍 (2013)。台中盆地地下水流數值模式之建立(碩士論文)。國立臺灣大學土木工程學研究所。
86.	陳尉平、李振誥、陳進發 (2000)。由河川流量資料與流量歷線推估中部地區地下水補注量。中國鑛冶工程學會會刊，44(3)，97–110。
87.	陳進發、李振誥、陳尉平 (1999)。應用未飽和層水平衡理論估計彰化地區地下水補注量之研究。臺灣水利，47(185)，54-66。
88.	黃品鈞 (2022)。桃園台地地下水數值模擬及管理水位之探討。中原大學土木工程學系。
89.	經濟部水利署，桃園地區地面地下水聯合管理整合模式評估與建構報告書，2007。
90.	經濟部水利署，臺灣地區地下水觀測網整體計畫成果彙編，2006。
91.	經濟部水利署水利規劃試驗所，地下水防災緊急備援井網規劃-桃園地區，2017。
92.	經濟部水利署北區水資源局，桃園地區防災緊急備援井工程規劃及基本設計報告，2021。
93.	壽克堅 & 潘家祺 (2020)。考慮極端氣候之台中盆地地下水位分析，氣候變遷與永續發展，第18屆大地工程學術研究討論會論文集。
94.	臺灣水文地質資訊系統:
https://hydro.geologycloud.tw/map
95.	臺灣氣候變遷推估資訊與調適知識平台，臺灣氣候變遷推估與資訊平台計畫，2016。
96.	臺灣氣候變遷推估資訊與調適知識平台:
https://tccip.ncdr.nat.gov.tw/login.aspx#!
97.	蔡清研 (2007)。濁水溪沖積扇整合模式下之MODFLOW地下水模擬研究(碩士論文)。國立中正大學地震研究所暨應用地球物理研究所。
98.	歷線分析—地層下陷監測資訊整合平台:
https://landsubsidence.wra.gov.tw/water_new/GwAnalysis/HydrographIndex/
99.	謝壎煌 (2009)。供水系統開發與管理調配之研究-以彰化地區為例(博士論文) 。國立成功大學資源工程學系。
100.	農業部農業試驗所土壤資料供應查詢平台:
https://tssurgo.tari.gov.tw/Tssurgo/
101.	經濟部水利署水文年報:
https://gweb.wra.gov.tw/wrhygis/ebooks/getebook.asp
102.	內政部20公尺網格數值地形模型資料
https://www.tgos.tw/MDE/MetaData/CRUD/ViewMetaData?GUID=74c6a7b7-1816-499c-bb60-89246065390f&VIEW_TYPE=only&SOURCE=1