大臺北地區歷經數十年大規模防洪工程投入，防護標準已達200年重現期，然而洪氾平原的開發持續推進，顯示都市洪災風險的根源不在工程強度，而在引導土地利用的空間治理邏輯。現有研究雖已充分顯示都市不透水面積增加對逕流的影響，但在政策評估層面，多聚焦於現況風險評估或未來情境推估，較少系統性回溯不同歷史治理選擇在長期都市化過程中所積累的空間水文後果。因而限制了對歷史治水決策所帶來之水文與土地利用影響的深入理解，更使得自然為本解方在流域尺度的實際效益與結構性限制，難以在具有歷史根據的比較框架中獲得量化評估。
鑒於上述研究缺口，本研究以大臺北地區為實證範圍，建構三條具歷史根據的反事實空間治理路徑，探討在開發慣性主導的大都會系統中，管制邏輯對空間與流域水文效益差異，以及自然入滲強化的減洪效益在流域尺度上是否存在結構性邊界條件。本研究以1995至2021年歷史土地利用變遷為基礎，採用反事實分析框架，建構三條具有歷史合理性的假設性發展路徑：情境A為工程導向的現況發展基準；情境B依防洪工程完工後的淹水潛勢深度限制開發；情境C以歷史反覆淹水區位為保全對象，回到工程介入前的地文風險記憶。研究整合土地利用變遷模型與都市洪水風險減緩模型（UFRM），以歷史可觀測軌跡錨定各情境模擬，並於設計暴雨條件下評估不同路徑的逕流保留效益，依歷史洪氾潛勢範圍進行分區比較與空間疊圖分析。
研究結果顯示，在開發總量固定的前提下，治理邏輯本質截然不同的情境B與情境C在流域尺度的逕流保留總量差異僅為0.20%，顯示空間管制的主要效益在於重新配置洪水暴露的空間分布，而非系統性削減流域產流總量，本研究將此現象稱為「空間代償效應」。分區比較進一步顯示，情境C引入自然入滲強化後，是三條路徑中唯一在歷史洪氾範圍內呈現逕流保留淨增加(+2.66%)，然而此效益不足以抵銷開發壓力移轉至洪氾潛勢區外所造成的系統性入滲損失，顯示自然入滲強化的減洪效益存在嚴格的空間邊界條件約束。上述結果整體指出，在高度路徑依賴的大都會系統中，「改變開發區位」而不「調控開發總量」的治理策略，較難在流域尺度上實現洪水風險的明顯降低；若要突破此一結構性制約，洪氾區空間管制與開發總量管控之間的搭配關係，是需要進一步討論的關鍵議題。本研究透過歷史脈絡錨定的反事實比較，提出一套用以評估不同空間治理邏輯之水文後果的分析框架，為大臺北乃至其他高度工程化都市流域的洪水風險治理提供可供參照的實證基礎。

Greater Taipei has invested heavily in flood control for decades and now meets a 200-year-return-period protection standard, but floodplain development continues to grow. This pattern suggests that urban flood risk is not primarily an engineering problem but a spatial governance problem shaped by long-term path dependency.
This study constructs three historically grounded counterfactual governance pathways. It compares their land-use patterns and runoff retention outcomes using CA-Markov land-use simulation and the InVEST Urban Flood Risk Mitigation (UFRM) assessment over 1995–2021.
Cramér's V analysis provides quantitative support for the path dependency identified through a century of engineering-led flood governance in Greater Taipei, confirming that socioeconomic factors drive land use transitions more strongly than terrain factors. Despite different regulatory logics, Scenario B displaces development toward basin-margin forests while Scenario C shifts pressure toward northern agricultural plains, confirming a spatial compensation effect at the land use level. This redistribution reduces global runoff retention by 2.81–3.01%, with only a 0.20% difference between the two governance pathways. Nature-based interventions improve runoff retention within flood zones (+2.66%) but cannot offset the systemic loss outside these zones (−2.68%), and this burden is highly concentrated at the sub-watershed scale, where 8 of 95 sub-watersheds account for 36.9% of the total basin-wide burden and the Zhonghe sub-watershed alone bears 17.7%.
These findings show that spatial governance alone is insufficient to reduce overall flood risk when total development volume stays constant. Effective improvement requires combining spatial regulation with controls on total development intensity and impervious surface area.

Arthur, W. B. (1989). Competing technologies, increasing returns, and lock-in by historical events. Economic Journal, 99(394), 116–131.
Asare, P., Atun, F., & Pfeffer, K. (2024). Spatial multi-criteria analysis for discovering nature-based solutions location for urban flood mitigation in Accra. Applied Spatial Analysis and Policy, 17(1), 207–239.
Azadgar, A., Gańcza, A., Asl, S. R., Salata, S., & Nyka, L. (2025). Optimizing nature-based solutions for urban flood risk mitigation: A multi-objective genetic algorithm approach in Gdańsk, Poland. Science of the Total Environment, 963, 178303.
Aburas, M. M., Ho, Y. M., Ramli, M. F., & Ash'aari, Z. H. (2017). Improving the capability of an integrated CA-Markov model to simulate spatio-temporal urban growth trends using an Analytical Hierarchy Process and Frequency Ratio. International Journal of Applied Earth Observation and Geoinformation, 59, 65–78.
Barredo, J. I., & Engelen, G. (2010). Land use scenario modeling for flood risk mitigation. Sustainability, 2(5), 1327–1344.
Bell, E. J., & Hinojosa, R. C. (1977). Markov analysis of land use change: Continuous time and stationary models. Socio-Economic Planning Sciences, 11(1), 13–17.
Breen, M. J., Kebede, A. S., & König, C. S. (2022). The safe development paradox in flood risk management: A critical review. Sustainability, 14(24), 16955.
Byrne, R. M. J. (2016). Counterfactual thought. Annual Review of Psychology, 67, 135–157.
Camacho Olmedo, M. T., García-Álvarez, D., Gallardo, M., Mas, J. F., Paegelow, M., Castillo-Santiago, M. A., & Molinero-Parejo, R. (2022). Validation of land use cover maps: A guideline. In D. García-Álvarez, M. T. Camacho Olmedo, M. Paegelow, & J. F. Mas (Eds.), Land use cover datasets and validation tools (pp. 35–46).
Catalano, A. J., & Hall, D. M. (2026). Reviewing the levee effect: From theory to practice. Journal of Flood Risk Management, 19(2), e70211.
Chang, H.-S., & Hsu, C.-P. (2025). Levee effect and urban development under climate change: Land-use strategies for managing residual flood risk in Taiwan. In Proceedings of REAL CORP 2025: Urban innovation. To boldly go where no cities have gone before (pp. 687–698). REAL CORP.
Corgo, J., Cruz, S. S., & Conceição, P. (2024). Nature-based solutions in spatial planning and policies for climate change adaptation: A literature review. Ambio, 53(11), 1599–1617.
Croke, J., Fryirs, K., & Thompson, C. (2016). Defining the floodplain in hydrologically-variable settings: Implications for flood risk management. Earth Surface Processes and Landforms, 41(14), 2153–2164.
Dai, K., Shen, S., Cheng, C., & Song, Y. (2023). Integrated evaluation and attribution of urban flood risk mitigation capacity: A case of Zhengzhou, China. Journal of Hydrology: Regional Studies, 50, 101567.
Di Baldassarre, G., Viglione, A., Carr, G., Kuil, L., Salinas, J. L., & Blöschl, G. (2013). Socio-hydrology: Conceptualising human–flood interactions. Hydrology and Earth System Sciences, 17(8), 3295–3303.
Di Baldassarre, G., Sivapalan, M., Rusca, M., Cudennec, C., Garcia, M., Kreibich, H., Konar, M., Mondino, E., Mård, J., Pande, S., Sanderson, M. R., Tian, F., Viglione, A., Wei, J., Wei, Y., Yu, D. J., Srinivasan, V., & Blöschl, G. (2019). Sociohydrology: Scientific challenges in addressing the Sustainable Development Goals. Water Resources Research, 55(8), 6327–6355.
Ding, M., Lin, P., Gao, S., Wang, J., Zeng, Z., Zheng, K., Zhou, X., Yamazaki, D., Gao, Y., & Liu, Y. (2023). Reversal of the levee effect towards sustainable floodplain management. Nature Sustainability, 6(12), 1578–1586.
Esraz-Ul-Zannat, M., Dedekorkut-Howes, A., & Morgan, E. A. (2024). A review of nature-based infrastructures and their effectiveness for urban flood risk mitigation. WIREs Climate Change, 15(5), e889.
GFDRR. (2017). Land use planning for urban flood risk management. World Bank.
Gashaw, T., Bantider, A., Zeleke, G., Alamirew, T., Jemberu, W., Worqlul, A. W., Dile, Y. T., Bewket, W., Meshesha, D. T., Adem, A. A., & Addisu, S. (2021). Evaluating InVEST model for estimating soil loss and sediment export in data scarce regions of the Abbay (Upper Blue Nile) basin: Implications for land managers. Environmental Challenges, 5, 100381.
Goličnik Marušić, B., Dremel, M., & Ravnikar, Ž. (2023). A frame of understanding to better link nature-based solutions and urban planning. Environmental Science & Policy, 146, 47–56.
Gui, B., Bhardwaj, A., & Sam, L. (2025). Cellular automata models for simulation and prediction of urban land use change: Development and prospects. Artificial Intelligence in Geosciences, 6(2), 100142.
Halmy, M. W. A., Gessler, P. E., Hicke, J. A., & Salem, B. B. (2015). Land use/land cover change detection and prediction in the north-western coastal desert of Egypt using Markov-CA. Applied Geography, 63, 101–112.
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), 3421.
Hamel, P., Guerry, A. D., Polasky, S., Han, B., … & Viguié, V. (2021). Mapping the benefits of nature in cities with the InVEST software. npj Urban Sustainability, 1(1), 25.
Huang, Y., Tian, Z., Ke, Q., Liu, J., Irannezhad, M., Fan, D., Hou, M., & Sun, L. (2020). Nature-based solutions for urban pluvial flood risk management. WIREs Water, 7(3), e1421.
IPCC. (2022). Climate change 2022: Impacts, adaptation and vulnerability. Cambridge University Press.
Itsukushima, R., Ohtsuki, K., & Sato, T. (2024). Significance of land use as a flood control measure: Unveiling the historical and contemporary strategies in the unique case of Kofu basin alluvial fan, Japan. International Journal of Disaster Risk Reduction, 109, 104578.
Kabisch, N., Frantzeskaki, N., & Hansen, R. (2022). Principles for urban nature-based solutions. Ambio, 51(6), 1388–1401.
Kreibich, H., Van Loon, A. F., Schröter, K., Ward, P. J., Mazzoleni, M., Sairam, N., et al. (2022). The challenge of unprecedented floods and droughts in risk management. Nature, 608(7921), 80–86.
Kundzewicz, Z. W., Su, B., Wang, Y., Wang, G., Huang, J., & Jiang, T. (2019). Flood risk in a range of spatial perspectives—from global to local scales. Natural Hazards and Earth System Sciences, 19(7), 1319–1328.
Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174.
Lin, W., Sun, Y., Nijhuis, S., & Wang, Z. (2020). Scenario-based flood risk assessment for urbanizing deltas using future land-use simulation (FLUS): Guangzhou metropolitan area as a case study. Science of the Total Environment, 739, 139899.
Ma, M., & Jin, Y. (2019). What if Beijing had enforced the 1st or 2nd greenbelt? Analyses from an economic perspective. Landscape and Urban Planning, 182, 79–91.
Magliocca, N. R., Dhungana, P., & Sink, C. D. (2023). Review of counterfactual land change modeling for causal inference in land system science. Journal of Land Use Science, 18(1), 1–24.
Matos, F. A., & Roebeling, P. (2022). Modelling impacts of nature-based solutions on surface water quality: A rapid review. Sustainability, 14(12), 7381.
Memarian, H., Balasundram, S. K., Talib, J. B., Teh, B. S., Sood, A. M., & Abbaspour, K. C. (2012). Validation of CA Markov for simulation of land use and cover change in the Langat Basin, Malaysia. Journal of Geographic Information System, 4(6), 542–554.
Mubeen, A., Ruangpan, L., Vojinovic, Z., Sanchez Torrez, A., & Plavšić, J. (2021). Planning and suitability assessment of large-scale nature-based solutions for flood-risk reduction. Water Resources Management, 35(10), 3063–3081.
Nesshöver, C., Assmuth, T., Irvine, K. N., Rusch, G. M., Waylen, K. A., Delbaere, B., Haase, D., Jones-Walters, L., Keune, H., Kovacs, E., Krauze, K., Külvik, M., Rey, F., van Dijk, J., Vistad, O. I., Wilkinson, M. E., & Wittmer, H. (2017). The science, policy and practice of nature-based solutions: An interdisciplinary perspective. Science of the Total Environment, 579, 1215–1227.
Nithila Devi, N., Ganapathy, A., Silva, A. F. R., Vorogushyn, S., Apel, H., Kreibich, H., Oostwegel, L. J. N., Kuiry, S. N., & Sairam, N. (2025). Lost water bodies and a flooded city: Counterfactual scenarios of the extreme Chennai flood highlight the potential of nature-based solutions. Urban Climate, 61, 102454.
Netherlands Delta Programme (2025). Towards a new balance in the living environment: Room to live with water. Ministry of Infrastructure and Water Management, the Netherlands.
OECD. (2020). Nature-based solutions for adapting to water-related climate risks (OECD Environment Policy Papers, No. 21). OECD Publishing.
Pauleit, S., Hansen, R., Rall, E. L., Rolf, W., & van Lierop, M. (2020). Green infrastructure for the city of the future: Perspectives from Europe. Urban@it, 2, 1–11..
Pierson, P. (2000). Increasing returns, path dependence, and the study of politics. American Political Science Review, 94(2), 251–267.
Pontius, R. G., Jr., & Malanson, J. (2005). Comparison of the structure and accuracy of two land change models. International Journal of Geographical Information Science, 19(2), 243–265.
Pontius, R. G., Jr., Boersma, W., Castella, J. C., Clarke, K., de Nijs, T., Dietzel, C., et al. (2008). Comparing the input, output, and validation maps for several models of land change. The Annals of Regional Science, 42(1), 11–37.
Pontius, R. G., Varga, O. G., Singh, S. K., & Szabó, S. (2021). Intensity analysis and the Figure of Merit’s components for assessment of a Cellular Automata–Markov land change model. Ecological Indicators, 121, 107016.
Quagliolo, C., Roebeling, P., Matos, F., Pezzoli, A., & Comino, E. (2023). Pluvial flood adaptation using nature-based solutions: An integrated biophysical-economic assessment. Science of the Total Environment, 902, 166202.
Rentschler, J., Avner, P., Marconcini, M., Su, R., Strano, E., Vousdoukas, M., & Hallegatte, S. (2023). Global evidence of rapid urban growth in flood zones since 1985. Nature, 622(7981), 87–92.
Ridolfi, E., Lucantonio, M., Di Baldassarre, G., Moccia, B., Napolitano, F., & Russo, F. (2025). The interplay between the urban development of Rome (Italy) and the Tiber River floods: A review of two millennia of socio-hydrological history. Ambio, 54(2), 198–210.
Roese, N. J. (1997). Counterfactual thinking. Psychological Bulletin, 121(1), 133–148.
Rubin, D. B. (1974). Estimating causal effects of treatments in randomized and nonrandomized studies. Journal of Educational Psychology, 66(5), 688–701.
Ruangpan, L., Vojinovic, Z., Di Sabatino, S., Leo, L. S., Capobianco, V., Oen, A. M. P., McClain, M. E., & Lopez-Gunn, E. (2020). Nature-based solutions for hydro-meteorological risk reduction: A state-of-the-art review of the research area. Natural Hazards and Earth System Sciences, 20(1), 243–270.
Sanchez, G. M., Lawrimore, M. A., Petrasova, A., Vogler, J. B., Collins, E. L., Petras, V., Harper, T., Butzler, E. J., & Meentemeyer, R. K. (2024). The safe development paradox of the United States regulatory floodplain. PLOS ONE, 19(12), e0311718.
Sang, L., Zhang, C., Yang, J., Zhu, D., & Yun, W. (2011). Simulation of land use spatial pattern of towns and villages based on CA–Markov model. Mathematical and Computer Modelling, 54(3–4), 938–943.
Seebauer, S., Thaler, T., Hanger-Kopp, S., & Schinko, T. (2023). How path dependency manifests in flood risk management: Observations from four decades in the Ennstal and Aist catchments in Austria. Regional Environmental Change, 23(1), 31.
Sivapalan, M., Savenije, H. H. G., & Blöschl, G. (2012). Socio-hydrology: A new science of people and water. Hydrological Processes, 26(8), 1270–1276.
Srinivasan, V. (2015). Reimagining the past: Use of counterfactual trajectories in socio-hydrological modelling—the case of Chennai, India. Hydrology and Earth System Sciences, 19(2), 785–801.
Shoyama, K. (2021). Assessment of Land-Use Scenarios at a National Scale Using Intensity Analysis and Figure of Merit Components, 10(4), 379.
UNISDR. (2009). UNISDR terminology for disaster risk reduction. United Nations International Strategy for Disaster Reduction.
Verburg, P. H., Schot, P. P., Dijst, M. J., & Veldkamp, A. (2004). Land use change modelling: Current practice and research priorities. GeoJournal, 61(4), 309–324.
Wang, C., Huang, S., & Wang, J. (2022). Spatio-temporal dynamic evolution and simulation of dike-pond landscape and ecosystem service value based on MCE-CA-Markov: A case study of Shunde, Foshan. Forests, 13(8), 1241.
Wang, H.-W., Castillo Castro, D. S., & Chen, G.-W. (2024). Managing residual flood risk: Lessons learned from experiences in Taiwan. Progress in Disaster Science, 23, 100337.
Wang, L., Cui, S., Li, Y., Huang, H., Manandhar, B., Nitivattananon, V., Fang, X., & Huang, W. (2022). A review of the flood management: From flood control to flood resilience. Heliyon, 8(11), e11763.
White, G. F. (1958). Changes in urban occupance of flood plains in the United States. University of Chicago.
Zhao, H., Gu, T., Tang, J., Gong, Z., & Zhao, P. (2023). Urban flood risk differentiation under land use scenario simulation. iScience, 26(4), 106479.
中文文獻
江浩弘、江莉琦、盧至美（2024）。應用 InVEST 模型評估土地利用變遷對生態系服務之影響－以蘭陽溪為例。載於台灣農業工程學會（編），113年農業工程研討會論文集（頁153–160）。
戴寶村（2011）。淡水河系與北臺灣的發展。國圖通訊，89，4–7。
毛孫京澤、吳沛袀等（2022）。〈台灣花園城市的消逝與變遷〉，ArcGIS StoryMaps，2022年6月25日。取自：Esri StoryMaps 網站（最後瀏覽日期：2026年5月28日）
王鏗惠（2003）。台北衛星城市變遷之研究─以戰後永和為例。﹝碩士論文。淡江大學﹞臺灣博碩士論文知識加值系統。
王筱雯、郭純園（2024年7月29日）。25座滯洪池承蓄近500萬噸洪水，為什麼凱米來襲高雄還是淹水？CSR@天下。
永和市公所。(1986)。永和市志。國家圖書館臺灣記憶系統（資料來源：國家圖書館 臺灣記憶 https://tm.ncl.edu.tw/）
顧雅文、李宗信、簡佑丞（2025）。島都之河：匯流與共生，淡水河與臺北的百年互動。春山出版。
邱薏潔（2024）。氣候變遷與都市發展對洪災危害度之空間區位影響探討―以臺北市為例。國立成功大學都市計劃學系。
林煒舒（2024）。一九一一，台北全滅：台灣百年治水事業的起點及你不可不知的重大水利故事。網路與書出版。
秦寂梅（2022）。沿海高風險區後撤性調適策略對洪災風險變遷之影響—以嘉義縣東石鄉與布袋鎮為。國立成功大學都市計劃學系。
周魁一（2004）。防洪減災觀念的理論進展——災害雙重屬性概念及其科學哲學基礎。自然災害學報。
徐敏純（2018）。堤防效應下之水災風險變遷與風險認知研究。國立成功大學都市計劃學系。
張學聖、徐敏純（2021）。堤防效應下之水災風險變遷與風險認知研究。都市與計劃，48(2)。
莊家維（2005）。近代淡水聚落的空間構成與變遷：從五口通商到日治時期。國立成功大學建築學系。
許晃雄、王嘉琪、陳正達、李明旭、詹士樑（2024）。國家氣候變遷科學報告2024：現象、衝擊與調適。國家科學及技術委員會、環境部。
黃珩婷、王志弘（2016）。哪一種自然才算數？新店溪河濱菜園的解離與重組。臺灣社會學刊，59，29–91。
經濟部水利署水利規劃試驗所（2020）。出流管制手冊。
環境部（2023）。國家氣候變遷調適行動計畫（112–115年）。
臺北廳（1905）。《臺北廳第一統計書》。臺北：臺灣總督府。取自臺灣法實證日治時期資料庫（臺灣大學法律學院）（2025年12月1日查詢）。