氣候變化對哥倫比亞 Pamplonita 和 Zulia 流域的水流的影響

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范妮莎(Maria Fernanda Vanessa Alvarez Carrascal) 查詢紙本館藏

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國際永續發展碩士在職專班

論文名稱

氣候變化對哥倫比亞 Pamplonita 和 Zulia 流域的水流的影響
(Influence of climate change on streamflow in Pamplonita and Zulia watershed, Colombia.)

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摘要(中)

氣候變遷對水資源乃至於整體社會帶來影響，已是不爭的事實。水資源短缺對經濟、政策、飲食安全、科技以及人民的生活品質造成巨大的影響。本研究採用長期水平衡模式，預測哥倫比亞的潘普洛尼塔與蘇利亞流域，在兩種情境底下的河川流量。這兩種情境代表社會經濟、科技、環境、氣候以及溫室氣體排放的可能狀態。本研究採用的情境設定來源於IPCC第五次評估報告（AR5）所使用之「代表濃度路徑」（RCPs）。其根據未來溫室氣體排放、經濟、政策、科技、機構以及人口統計數據的數種組合，評估2100年的輻射強迫力。此兩種情境用以評估2030年與2050年之間的氣候變遷狀況，其中氣候變遷對於河川流量的影響，在溫度方面，將以五種大氣環流模式（GCMs）進行評估，即CCSm4，GFDL-CM3，MIROC5，MPI-ESM-LR 及 MRI-C6CM3，降水方面則是BCC-CSM，CCSm4，GISS E2-H，GISS-E2-R，MPI ESM 以及 MRI-C6CM3六種。
研究結果顯示溫度呈現上升的趨勢。2050年，溫度將在RCP4.5情況下平均上升2.0±0.6°C，RCP8.5的情況下則為2.8±0.7 °C。另一方面，降水的趨勢並不明顯，然而其平均值仍顯示略為減少：在2050年，RCP4.5的情況下將是-0.23±0.5%，而RCP8.5的結果則呈現為-0.48±0.7%。在整個推估期間內，其預計流量整體呈現降低的趨勢。預料在2050年，流域出口的年平均流量將在RCP4.5的情況下-4.04 ± 2.6%；而在RCP8.5的情況下-7.77± 1.5%。本文研究結果可作為相關區域決策者的評估工具，為未來水資源管理的決策提供參考。

摘要(英)

It is expected that climate change will have an impact on water resources, hence in society. Water scarcity represents a great impact on the economic system, policy, alimentary safe, technology, and population′s life quality. This study uses the Long-term Water Balance to project the streamflow in the Pamplonita and Zulia watersheds in Colombia under two different scenarios. These two scenarios represent how several factors would unfurl in the future, like socioeconomic, technological, environmental, climate, and greenhouse gas emission conditions. The scenarios used in this project come from the 5th IPCC assessment report (AR5), named Representative Concentration Pathway (RCPs), radiative forcing by 2100, due to different combinations of greenhouse gas emission, economic, policy, technological, institutional and demographic futures). These scenarios were used to assess climate change for two periods of time between 2030 and 2050. The impact on the streamflow was evaluated with five GCMs for temperature: namely CCSm4, GFDL-CM3, MIROC5, MPI-ESM-LR and MRI-C6CM3, and six for precipitation: namely BCC-CSM, CCSm4, GISS E2-H, GISS-E2-R, MPI ESM and MRI-C6CM3.
The results indicate an increasing trend for temperature, with an average increase of 2.0±0.6°C under RCP4.5, and 2.8±0.7 °C under RCP8.5 by 2050. On the other hand, precipitation doesn′t present a clear-cut. However, the mean of these presents a slight decrease, -0.23±0.5% under RCP4.5 and -0.48±0.7% under RCP8.5 by 2050. The projected streamflow indicated an overall trend of decreases in all the periods under review. Annual average streamflow has anticipated a decrease of -4.04 ± 2.6% at the outlet of the watershed under RCP4.5 and -7.77± 1.5% under RCP8.5 by 2050. These results serve as a tool for policymakers in the region, as a reference for the future decision on the water resource management in the region.

關鍵字(中)

★ 氣候變化
★ 水資源
★ 長期水平衡
★ 哥倫比亞

關鍵字(英)

★ Climate change
★ Water Resources
★ Long-term water balance
★ Colombia

論文目次

Table of Contents
1 Introduction .................................................................................................................... 1
1.1 Objective ............................................................................................................................ 2
1.2 Scope of the study .............................................................................................................. 2
1.3 Motivation .......................................................................................................................... 2
2 Literature Review ........................................................................................................... 3
2.1 Climate change .................................................................................................................. 3
2.2 Climate change impact assessment methodology ........................................................... 4
2.2.1 General Circulation Models (GCMs) ............................................................................................ 4
2.2.2 Hydrological models ..................................................................................................................... 5
2.2.3 Scenarios ....................................................................................................................................... 5
2.3 Previous research .............................................................................................................. 6
3 Study Area ...................................................................................................................... 8
3.1 Climate ............................................................................................................................... 9
3.2 Economy ........................................................................................................................... 10
3.3 Water resources ............................................................................................................... 11
4 Methodology ................................................................................................................. 12
4.1 Data Sources and Pre-processing ................................................................................... 12
4.1.1 GCM’s downscaled data ............................................................................................................. 12
4.1.2 Historical Climate Conditions Data ............................................................................................ 13
4.2 Representative Concentration Pathway ........................................................................ 13
4.3 Long-Term Water Balance ............................................................................................. 13
4.4 Historical Streamflow Computation .............................................................................. 16
4.5 Projected Streamflow Computation .............................................................................. 16
5 Results and Discussion ................................................................................................. 17
5.1 Historical Data ................................................................................................................. 17
5.1.1 Temperature ................................................................................................................................ 17
5.1.2 Precipitation ................................................................................................................................ 21
5.1.3 Streamflow .................................................................................................................................. 25
5.2 Projected Data ................................................................................................................. 28
5.2.1 Temperature ................................................................................................................................ 28
5.2.2 Precipitation ................................................................................................................................ 30
5.2.3 Streamflow .................................................................................................................................. 33
5.3 Streamflow in the dry season ......................................................................................... 35
5.4 RCPs Comparison ........................................................................................................... 38
5.5 Discussion ......................................................................................................................... 39
6 Conclusions and Future Research .............................................................................. 42
7 References ..................................................................................................................... 43
ANNEX A .............................................................................................................................. 48
ANNEX B .............................................................................................................................. 51
ANNEX C .............................................................................................................................. 77
ANNEX E .............................................................................................................................. 83
ANNEX F .............................................................................................................................. 86
ANNEX G ............................................................................................................................ 89
ANNEX H ............................................................................................................................. 92
ANNEX I ............................................................................................................................... 93

參考文獻

[1] B. C. Bates, Z. W. Kundzewicz, S. Wu, and J. P. Palutikof, “Climate Change and Water.,” Tech. Pap. Intergovermental Panel Clim. Chnage, 2008, Accessed: Feb. 29, 2020. [Online]. Available: https://www.researchgate.net/publication/283720897_Climate_Change_and_Water_Technical_Paper_of_the_Intergovernmental_Panel_on_Climate_Change.
[2] F. R. Rijsberman, “Water scarcity: Fact or fiction?,” Agric. Water Manag., vol. 80, no. 1–3, pp. 5–22, Feb. 2006, doi: 10.1016/j.agwat.2005.07.001.
[3] IPCC, “AR5 Climate Change 2014 - Sythesis Report - Summary for Policymakers.” 2014.
[4] M. Qadir, B. R. Sharma, A. Bruggeman, R. Choukr-Allah, and F. Karajeh, “Non-conventional water resources and opportunities for water augmentation to achieve food security in water scarce countries,” Agric. Water Manag., vol. 87, no. 1, pp. 2–22, Jan. 2007, doi: 10.1016/j.agwat.2006.03.018.
[5] S. B. Roy, L. Chen, E. H. Girvetz, E. P. Maurer, W. B. Mills, and T. M. Grieb, “Projecting Water Withdrawal and Supply for Future Decades in the U.S. under Climate Change Scenarios,” Environ. Sci. Technol., vol. 46, no. 5, pp. 2545–2556, Mar. 2012, doi: 10.1021/es2030774.
[6] IPCC, “AR4 Climate Change 2007: Synthesis Report,” 2007. https://www.ipcc.ch/report/ar4/syr/ (accessed Feb. 22, 2020).
[7] L. J. Mata et al., “Latin America. Climate Change 2001, Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on Climate Change,” Intergovermental Panel Clim. Change, 2001.
[8] C. Costa-Posada, “Adaptation to Climate Change in Colombia,” Rev. Ing., p. 8, 2007.
[9] J. D. Pabón, “El cambio climático global y su manifestación en Colombia,” Cuad. Geogr. Rev. Colomb. Geogr., vol. 0, no. 12, Art. no. 12, Jan. 2003.
[10] D. Alzate, E. Rojas, J. Mosquera, and J. Ramon, “Cambio Climático y Variabilidad Climática Para El Periodo 1981-2010 En Las Cuencas De Los Ríos Zulia y Pamplonita, Norte de Santander – Colombia,” Luna Azul, no. 40, Jan. 2015, doi: 10.17151/luaz.2015.40.10.
[11] M. C. García, A. P. Botero, F. A. B. Quiroga, and E. A. Robles, “Variabilidad climática, cambio climático y el recurso hídrico en Colombia,” Rev. Ing., vol. 36, pp. 60–64, 2012.
[12] A. F. Hurtado and O. J. Mesa, “Climate Change and Space-time Variability Of The Precipitatioj In Colombia,” Rev. EIA, vol. 12, no. 24, pp. 131–150, 2015.
[13] IDEAM, “National Water Study.” 2010.
[14] J. Ramirez-Villegas, M. Salazar, A. Jarvis, and C. E. Navarro-Racines, “A way forward on adaptation to climate change in Colombian agriculture: perspectives towards 2050,” Clim. Change, vol. 115, no. 3, pp. 611–628, Dec. 2012, doi: 10.1007/s10584-012-0500-y.
[15] D. Ruiz-Carrascal et al., “On the assessment of likely near-term changes in climate extremes in the densely-populated Magdalena-Cauca water shed, Colombia,” 2019.
44
[16] E. O. Ojeda B., “Informe Nacional Sobre La Gestion del Agua en Colombia. Recursos Hídricos, Agua Potable y Saneamiento.” Comision Economica Para Latino America y el Caribe, 2000.
[17] DANE, “Censo Nacional de Poblacion y Vivienda - ¿Dónde Estamos?,” 2018. https://sitios.dane.gov.co/cnpv/#!/donde_estamos (accessed Mar. 06, 2020).
[18] CORPONOR, “Plan de ordenación y manejo de la cuenca hidrográfica del río Zulia,” 2010, [Online]. Available: http://corponor.gov.co/publica_recursos/pomca/zulia/POMCH_COMPLETO-RIO_ZULIA.pdf.
[19] CORPONOR, “Plan de ordenación y manejo de la cuenca hidrografica del rio Pamplonita.” 2010, [Online]. Available: https://pdfs.semanticscholar.org/ca9e/005ea3eed7b2aa4b3a91c8a4da421754bbc6.pdf.
[20] IPCC, “Glossary — Global Warming of 1.5 oC,” 2019. https://www.ipcc.ch/sr15/chapter/glossary/ (accessed Feb. 29, 2020).
[21] C. J. Vörösmarty, P. Green, J. Salisbury, and R. B. Lammers, “Global Water Resources: Vulnerability from Climate Change and Population Growth,” Science, vol. 289, no. 5477, pp. 284–288, Jul. 2000, doi: 10.1126/science.289.5477.284.
[22] R. H. Moss et al., “The next generation of scenarios for climate change research and assessment | Nature,” 2010. https://www.nature.com/articles/nature08823 (accessed Sep. 20, 2019).
[23] J. F. Feenstra, I. Burton, J. B. Smith, and R. S. J. Tol, Handbook on Methods for Climate Change Impact Assessment and Adaptation Strategies. United Nation Environmental Programme, 1998.
[24] W. L. Gates et al., “Climate models - evaluation. In Climate Change 1992: The Supplementary Report to the IPCC Scientific Assessment.,” Camb. Univ. Press, 1996.
[25] IPCC, “Guidance on the use of data,” 1998. https://www.ipcc-data.org/guidelines/pages/gcm_guide.html (accessed Mar. 03, 2020).
[26] IPCC, “Evaluation of Climate Models — IPCC,” 2014. https://www.ipcc.ch/report/ar5/wg1/evaluation-of-climate-models/ (accessed Mar. 06, 2020).
[27] A. Gaur and S. P. Simonovic, “Chapter 4 - Introduction to Physical Scaling: A Model Aimed to Bridge the Gap Between Statistical and Dynamic Downscaling Approaches,” in Trends and Changes in Hydroclimatic Variables, R. Teegavarapu, Ed. Elsevier, 2019, pp. 199–273.
[28] S. H. Pour, S. Shahid, E.-S. Chung, and X.-J. Wang, “Model output statistics downscaling using support vector machine for the projection of spatial and temporal changes in rainfall of Bangladesh,” Atmospheric Res., vol. 213, pp. 149–162, Nov. 2018, doi: 10.1016/j.atmosres.2018.06.006.
[29] A. Shaukat et al., “Assessment of climate extremes in future projections downscaled by multiple statistical downscaling methods over Pakistan,” Atmospheric Res., vol. 222, pp. 114–133, 2019, doi: 10.1016/j.atmosres.2019.02.009.
[30] J. Evans, J. McGregor, and K. McGuffie, “Chapter 9 - Future Regional Climates,” in The Future of the World’s Climate (Second Edition), A. Henderson-Sellers and K. McGuffie, Eds. Boston: Elsevier, 2012, pp. 223–250.
[31] C. Navarro-Racines, J. Tarapues, P. Thornton, A. Jarvis, and J. Ramirez-Villegas, “High-resolution and bias-corrected CMIP5 projections for climate change impact assessments,” Sci. Data, vol. 7, no. 1, p. 7, Dec. 2020, doi: 10.1038/s41597-019-0343-8.
[32] F. Giorgi and L. O. Mearns, “Introduction to special section: Regional Climate Modeling Revisited,” J. Geophys. Res. Atmospheres, vol. 104, no. D6, pp. 6335–6352, 1999, doi: 10.1029/98JD02072.
[33] S. K. Jalota, B. B. Vashisht, S. Sharma, and S. Kaur, “Chapter 2 - Climate Change Projections,” in Understanding Climate Change Impacts on Crop Productivity and Water Balance, S. K. Jalota, B. B. Vashisht, S. Sharma, and S. Kaur, Eds. Academic Press, 2018, pp. 55–86.
[34] L. R. Leung, Y. Qian, X. Bian, W. M. Washington, J. Han, and J. O. Roads, “Mid-Century Ensemble Regional Climate Change Scenarios for the Western United States,” Clim. Change, vol. 62, no. 1, pp. 75–113, Jan. 2004, doi: 10.1023/B:CLIM.0000013692.50640.55.
[35] H. Wheater, S. Sorooshian, and K. D. Sharma, Hydrological Modelling in Arid and Semi-Arid Areas. Cambridge University Press, 2007.
[36] G. K. Devia, B. P. Ganasri, and G. S. Dwarakish, “A Review on Hydrological Models,” Aquat. Procedia, vol. 4, pp. 1001–1007, Jan. 2015, doi: 10.1016/j.aqpro.2015.02.126.
[37] IPCC, “Socio-Economic Data and Scenarios,” 2019. https://sedac.ciesin.columbia.edu/ddc/ar5_scenario_process/RCPs.html (accessed Mar. 04, 2020).
[38] B. Felzer and P. Heard, “Precipitation differences among GCMs used for the U.S. National Assesment,” J. Am. Water Resour. Assoc., vol. 35, pp. 1327–1339, 1999.
[39] P. G. Hess, D. S. Battisti, and P. J. Rasch, “Maintenance of the Intertropical Convergence Zones and the Large-Scale Tropical Circulation on a Water-covered Earth,” J. Atmospheric Sci., vol. 50, no. 5, pp. 691–713, Mar. 1993, doi: 10.1175/1520-0469(1993)050<0691:MOTICZ>2.0.CO;2.
[40] C. I. of H. IDEAM Meteorology and Environmental Studies, “IDEAM - ArcGIS Web Application- Weather Sation Data,” 2018. http://dhime.ideam.gov.co/atencionciudadano/ (accessed Sep. 20, 2019).
[41] DANE, “Empleo y desempleo,” 2019. https://www.dane.gov.co/index.php/estadisticas-por-tema/mercado-laboral/empleo-y-desempleo (accessed Mar. 20, 2020).
[42] A. Garcia, “Cúcuta, víctima de la crisis de Venezuela al otro lado de la frontera,” Infobae, 2019. https://www.infobae.com/america/colombia/2019/03/09/cucuta-victima-de-la-crisis-de-venezuela-al-otro-lado-de-la-frontera/ (accessed Feb. 28, 2020).
[43] R. P. on C. C. CCAFS Agriculture and Food Security, “Data - CCAFS Climate,” 2015. http://www.ccafs-climate.org/data_spatial_downscaling/ (accessed Sep. 20, 2019).
[44] WorldClim, “WorldClim - Global Climate Data | WorldClim Version 1,” 2019. https://www.worldclim.org/version1 (accessed Sep. 20, 2019).
[45] R. J. Blakeslee, “Lightning Imaging Sensor (LIS) on TRMM Science Data.” NASA Global Hydrology Resource Center DAAC, 1998, doi: 10.5067/lis/lis/data201.
[46] R. G. Barry, “Mountain Weather and Climate,” Cambridge Core, Jul. 2008. /core/books/mountain-weather-and-climate/AB88E7CA8DE0FD36123922EBBCBF3B1E (accessed Mar. 22, 2020).
[47] D. M. Livingstone, A. F. Lotter, and I. R. Walkery, “The Decrease in Summer Surface Water Temperature with Altitude in Swiss Alpine Lakes: A Comparison with Air Temperature Lapse Rates,” Arct. Antarct. Alp. Res., vol. 31, no. 4, pp. 341–352, Nov. 1999, doi: 10.1080/15230430.1999.12003319.
[48] R. C. Tabony, “The variation of surface temperature with altitude,” Meteorol. Mag., vol. 114, pp. 37–48, 1985.
[49] S. Manabe, “Climate and the ocean circulation,” Mon. Weather Rev., vol. 97, no. 11, pp. 739–774, Nov. 1969, doi: 10.1175/1520-0493(1969)097<0739:CATOC>2.3.CO;2.
[50] J. C. Schaake, “From climate to flow.,” Clim. Change US Water Resour., pp. 177–206, 1990.
[51] Poveda Germán et al., “Linking Long-Term Water Balances and Statistical Scaling to Estimate River Flows along the Drainage Network of Colombia,” J. Hydrol. Eng., vol. 12, no. 1, pp. 4–13, Jan. 2007, doi: 10.1061/(ASCE)1084-0699(2007)12:1(4).
[52] IDEAM, “Estudio Nacional del Agua 2010.” 2010.
[53] A. Kleidon and S. Schymanski, “Thermodynamics and optimality of the water budget on land: A review,” Geophys. Res. Lett., vol. 35, no. 20, 2008, doi: 10.1029/2008GL035393.
[54] C. Lorenz and H. Kunstmann, “The Hydrological Cycle in Three State-of-the-Art Reanalyses: Intercomparison and Performance Analysis,” J. Hydrometeorol., vol. 13, no. 5, pp. 1397–1420, Apr. 2012, doi: 10.1175/JHM-D-11-088.1.
[55] S. Seneviratne, P. Viterbo, D. Lüthi, and C. Schär, “Inferring changes in terrestrial water storage using ERA-40 reanalysis data: The Mississippi River basin.,” 2003. .
[56] C. W. Thornthwaite, “AN APPROACH TOWARDS A RATIONAL CLASSIFICATION OF CLIMATE,” 1948, doi: 10.1097/00010694-194807000-00007.
[57] M. I. Budyko and D. H. Miller, Climate and Life, Volume 18 - 1st Edition. Academic Press Inc., 1974.
[58] K. Fraedrich, “A Parsimonious Stochastic Water Reservoir: Schreiber’s 1904 Equation,” J. Hydrometeorol., vol. 11, no. 2, pp. 575–578, Oct. 2009, doi: 10.1175/2009JHM1179.1.
[59] ESRI, “Performing cross-validation and validation—Help | Documentación,” 2019. https://desktop.arcgis.com/es/arcmap/latest/extensions/geostatistical-analyst/performing-cross-validation-and-validation.htm#GUID-7460E552-DAF6-4D04-8247-8B5866D7B06D (accessed Jul. 16, 2020).
[60] IPCC, “Summary for Policymakers — Global Warming of 1.5 oC,” 2018. https://www.ipcc.ch/sr15/chapter/spm/ (accessed Feb. 22, 2020).
[61] N. W. Arnell, “Global warming, river flows and water resources.,” Glob. Warm. River Flows Water Resour., 1996, Accessed: Feb. 22, 2020. [Online]. Available: https://www.cabdirect.org/cabdirect/abstract/19971903551.
[62] K. E. Trenberth, “Changes in precipitation with climate change,” Clim. Res., vol. 47, no. 1–2, pp. 123–138, Mar. 2011, doi: 10.3354/cr00953.
[63] M. G. Bosilovich, J. Chen, F. R. Robertson, and R. F. Adler, “Evaluation of Global Precipitation in Reanalyses,” J. Appl. Meteorol. Climatol., vol. 47, no. 9, pp. 2279–2299, Sep. 2008, doi: 10.1175/2008JAMC1921.1.
[64] S. P. de Szoeke and S.-P. Xie, “The Tropical Eastern Pacific Seasonal Cycle: Assessment of Errors and Mechanisms in IPCC AR4 Coupled Ocean–Atmosphere General Circulation Models,” J. Clim., vol. 21, no. 11, pp. 2573–2590, Jun. 2008, doi: 10.1175/2007JCLI1975.1.
[65] IPCC, “AR4 Climate Change 2007: The Physical Science Basis.” Cambridge University Press, 2007, Accessed: Apr. 13, 2020. [Online]. Available: https://www.ipcc.ch/report/ar4/wg1/.
[66] B. G. Liepert and M. Previdi, “Do Models and Observations Disagree on the Rainfall Response to Global Warming?,” J. Clim., vol. 22, no. 11, pp. 3156–3166, Jun. 2009, doi: 10.1175/2008JCLI2472.1.
[67] D. J. Lorenz and E. T. DeWeaver, “The Response of the Extratropical Hydrological Cycle to Global Warming,” J. Clim., vol. 20, no. 14, pp. 3470–3484, Jul. 2007, doi: 10.1175/JCLI4192.1.
[68] G.-Y. Yang and J. Slingo, “The Diurnal Cycle in the Tropics,” Mon. WEATHER Rev., vol. 129, p. 18, 2001.
[69] I. Richter and C. R. Mechoso, “Orographic Influences on Subtropical Stratocumulus,” J. Atmospheric Sci., vol. 63, no. 10, pp. 2585–2601, Oct. 2006, doi: 10.1175/JAS3756.1.
[70] H. Xu, Y. Wang, and S.-P. Xie, “Effects of the Andes on Eastern Pacific Climate: A Regional Atmospheric Model Study,” J. Clim., vol. 17, no. 3, pp. 589–602, Feb. 2004, doi: 10.1175/1520-0442(2004)017<0589:EOTAOE>2.0.CO;2.
[71] D. a Stainforth, M. r Allen, E. r Tredger, and L. a Smith, “Confidence, uncertainty and decision-support relevance in climate predictions,” Philos. Trans. R. Soc. Math. Phys. Eng. Sci., vol. 365, no. 1857, pp. 2145–2161, Aug. 2007, doi: 10.1098/rsta.2007.2074.
[72] J. D. Herman, J. D. Quinn, S. Steinchneider, M. Giuliani, and S. Fletcher, “Climate Adaptation as a Control Problem: Review and Perspectiveson Dynamic Water Resources Planning Under Uncertainty,” Water Resour. Res., vol. 56, no. e24389, 2020, Accessed: Feb. 19, 2020. [Online]. Available: https://doi.org/10.1029/2019WR025502.
[73] Fletcher Sarah M., Miotti Marco, Swaminathan Jaichander, Klemun Magdalena M., Strzepek Kenneth, and Siddiqi Afreen, “Water Supply Infrastructure Planning: Decision-Making Framework to Classify Multiple Uncertainties and Evaluate Flexible Design,” J. Water Resour. Plan. Manag., vol. 143, no. 10, p. 04017061, Oct. 2017, doi: 10.1061/(ASCE)WR.1943-5452.0000823.
[74] F. L. Paton, H. R. Maier, and G. C. Dandy, “Including adaptation and mitigation responses to climate change in a multiobjective evolutionary algorithm framework for urban water supply systems incorporating GHG emissions,” Water Resour. Res., vol. 50, no. 8, pp. 6285–6304, 2014, doi: 10.1002/2013WR015195.

指導教授

吳瑞賢(Ray-Shyan Wu)

審核日期

2020-7-20

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