长江流域参照蒸发量时空变化趋势分析
Trends Analysis on Spatiotemporal Characteristics of Reference Evaporation in the Yangtze River Basin

DOI: 10.12677/JWRR.2015.46065, PP. 522-529

Keywords: 气候变化，长江流域，统计降尺度，参照蒸发蒸腾量
Climate Change, Yangtze River Basin, Statistical Down-Scaling Model, Reference Evaporation

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Abstract:

根据长江流域134个气象站1961-2010年逐日气象资料，基于Penman-Monteith法计算参照蒸发量，选取NECP再分析数据，采用SDSM (the Statistical Down-Scaling Model)方法，进行长江流域未来参照蒸发量的降尺度研究。研究表明：1) SDSM方法对参照蒸发量能较准确的模拟，检验期的确定性系数可达93%以上；2) 1961~2010年长江流域的蒸发蒸腾量呈下降趋势，显著下降的站点集中在长江中下游区域、长江流域北部的区域；3) Rcp45与Rcp85气候情景下，长江流域未来2011~2099年的参照蒸发量呈上升趋势，且Rcp85情景下的参照蒸发量增加的幅度大于Rcp45。
Based on 134 hydro-meteorological gauges in the Yangtze River basin 1961-2010 daily meteorological data, the reference evaporation was calculated by using the Penman-Monteith method. To predict the future change of the reference evaporation, SDSM (the Statistical Down-Scaling Model) method was used to downscale the outputs of GCMs, which was firstly trained by utilizing the NECP reanalysis data. Results show that: 1) SDSM reference evaporation method performed better in simulating the reference evapo-ration as to the high simulation deterministic coefficient (0.93) in the testing period; 2) 1961-2010 annual reference evaporation in the Yangtze River basin decreased significantly; decreasing sites concentrated in the lower reaches, the middle stream and the north of the Yangtze River basin; 3) under Rcp45 and Rcp85 climate scenarios, reference evaporation of the Yangtze River basin will increase in 2011 - 2099 years, and the rate of increase of reference evaporation under Rcp85 scenarios is greater than Rcp45.

References

[1]	肖义, 唐少华, 陈华, 等. 气候变化对湘江流域降水气温和蒸发的影响变化预测[J]. 水资源研究, 2013, 2(1): 70-75. XIAO Yi, TANG Shaohua, CHEN Hua, et al. Climate change impact on hydro-climate variables in the Xiangjiang basin. Journal of Water Resources Research, 2013, 2(1): 70-75. (in Chinese)
[2]	左德鹏, 徐宗学, 李景玉, 刘兆飞. 气候变化情景下渭河流域潜在蒸散量时空变化特征[J]. 水科学进展, 2011, 22(4): 455-461. ZUO Depeng, XU Zongxue, LI Jingyu and LIU Zhaofei. Spatiotemporal characteristics of potential evapotranspiration in Weihe River basin under future climate change. Advances in Water Science, 2011, 22(4): 455-461. (in Chinese)
[3]	褚健婷, 夏军, 许崇育. SDSM模型在海河流域统计降尺度研究中的适用性分析[J]. 资源科学, 2008, 30(12): 1825-1832. CHU Jianting, XIA Jun and XU Chongyu. Suitability analysis of SDSM model in the Haihe River basin. Resources Science, 2008, 30(12): 1825-1832. (in Chinese)
[4]	向田恬, 陈华, 郭家力, 等. 气候变化对嘉陵江流域降水变化影响分析[J]. 南水北调与水利科技, 2010, 8(1): 75-77. XIANG Tiantian, CHEN Hua, GUO Jiali, et al. Impact of climate change on prediction of precipitation in Jialing River of the upper Yangtze River basin. South-to-North Water Transfers and Water Science & Technology, 2010, 8(1): 75-77. (in Chi-nese)
[5]	王丽娜. 统计降尺度方法对黄河上游流域气象要素模拟分析[J]. 水资源与水工程学报, 2015, 2: 114-118. WANG Lina. Simulation analysis of meteorological element by statistical downscaling method in Yellow River basin. Journal of Water Resources and Water Engineering, 2015, 2: 114-118. (in Chinese)
[6]	IPCC. METZ, B., DAVIDSON, O. R., BOSCH, P. R., DAVE, R., MEYER, L. A., Eds. Climate change 2007: Mitigation. Contribution of working group III to the 4th assessment report of the intergovernmental panel on climate change. Cambridge, New York: Cambridge University Press, 2007.
[7]	郝振纯, 杨荣榕, 陈新美, 陈玺, 梁之豪, 达娃顿珠. 1960~2011年长江流域潜在蒸发量的时空变化特征[J]. 冰川冻土, 2013, 35(2): 408-419. HAO Zhenchun, YANG Rongrong, CHEN Xinmei, CHEN Xi, LIANG Zhihao and DAWA Dunzhu. Tempo-spatial pattern of the potential evaporation in the Yangtze River catchment for the period 1960-2011. Journal of Glaciology and Geocryology, 2013, 35(2): 408-419. (in Chinese)
[8]	邢万秋, 王卫光, 邵全喜, 杨慧, 彭世彰, 余钟波, 杨涛. 未来气候情景下海河流域参考蒸发蒸腾量预估[J]. 应用基础与工程科学学报, 2014, 2: 239-251. XING Wanqiu, WANG Weiguang, SHAO Quanxi, YANG Hui, PENG Shizhang, YU Zhongbo and YANG Tao. Projection of future reference evapotranspiration change across the Haihe River basin. Journal of Basic Science and Engineering, 2014, 2: 239-251. (in Chinese)
[9]	WILBY, R. L., WIGLEY, T. M. L. Downscaling general circulation model output: A review of methods and limitations. Progress in Physical Geography, 1997, 21(4): 530-548. http://dx.doi.org/10.1177/030913339702100403
[10]	DA SILVA, V. P. R. On climate variability in Northeast of Brazil. Journal of Arid Environment, 2004, 58(4): 575-596. http://dx.doi.org/10.1016/j.jaridenv.2003.12.002
[11]	MANN, H. B. Nonparametric tests against trend. Econometrica, 1945, 13(3): 245-259. http://dx.doi.org/10.2307/1907187
[12]	KENDALL, M. G. Rank correlation methods. London: Griffin, 1975.
[13]	WILBY, R. L., HAY, L. E. and LEAVESLEY, G. H. A comparison of downscaled and raw GCM output: Implications for climate change scenarios in the SanJuan River basin, Colorado. Journal of Hydrology, 1999, 225(1-2): 67-91. http://dx.doi.org/10.1016/S0022-1694(99)00136-5
[14]	WILBY, R. L., DAWSON, C. W. and BARROW, E. M. SDSM—A decision support tool for the assessment of regional climate change impacts. Environmental Modelling & Software, 2002, 17(2): 147-159. http://dx.doi.org/10.1016/S1364-8152(01)00060-3
[15]	WILBY, R. L., TOMLINSON, O. J. and DAWSON, C. W. Mul-ti2site simulation of precipitation by conditional resampling. Climate Research, 2003, 23(3): 183-194. http://dx.doi.org/10.3354/cr023183

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