气候变化对水文季节性迁移的影响:以水库汛期分期和极值降水为例
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摘要
气候变化影响下水利工程的可靠设计和安全运行是广大决策者、研究者和公众共同关注的热点问题。以清江流域为研究对象,首先采用模糊集合分析法对不同温室气体排放情景(A2、A1B和B1)下的逐日降水资料进行汛期分期,再通过广义极值分布(GEV)函数对各分期的极值降水序列进行频率分析。结果表明,降水季节性迁移直接影响汛期分期;3种排放情景下未来各时段(2011—2030年、2046—2065年和2080—2099年)的主汛期较基准期均推迟且有缩短趋势。对于极值降水量级,未来情景下明显小于基准期,且这种差距随着重现期的增大而增大;主汛期明显大于前汛期和后汛期,且在时段之间的差异明显大于排放情景之间的差异。
Under the influence of climate change the reliable design and safe operation of hydraulic engineering has become a hot issue for decision makers, researchers and the public. Taking the Qingjiang River Basin as the research target, and using fuzzy set analysis method to classify the daily rainfall data generated under different greenhouse emission scenarios(e.g., A2, A1 B and B1), the extreme precipitation series were simulated by generalized extreme value distribution(GEV) function. The results show that climate change has changed the precipitation structure, and its seasonal shift directly affects the flood season division. Under the three emission scenarios, the main flood season in the future will be postponed and shortened compared with the baseline period.The extreme precipitation in the future(e.g., 2011-2030, 2046-2065 and 2080-2099) is less than the baseline period, and this difference increases with the increase of the return period. The extreme precipitation in the main flood season is notably larger than that in the pre-flood season and post flood season. For extreme precipitation,the differences between periods are remarkably greater than those of emission scenarios.
Under the influence of climate change the reliable design and safe operation of hydraulic engineering has become a hot issue for decision makers, researchers and the public. Taking the Qingjiang River Basin as the research target, and using fuzzy set analysis method to classify the daily rainfall data generated under different greenhouse emission scenarios(e.g., A2, A1 B and B1), the extreme precipitation series were simulated by generalized extreme value distribution(GEV) function. The results show that climate change has changed the precipitation structure, and its seasonal shift directly affects the flood season division. Under the three emission scenarios, the main flood season in the future will be postponed and shortened compared with the baseline period.The extreme precipitation in the future(e.g., 2011-2030, 2046-2065 and 2080-2099) is less than the baseline period, and this difference increases with the increase of the return period. The extreme precipitation in the main flood season is notably larger than that in the pre-flood season and post flood season. For extreme precipitation,the differences between periods are remarkably greater than those of emission scenarios.
引文
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[15]李浩,周义仁.气候变化对汛期分期的影响研究[J].水力发电,2018, 44(6):22-26
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[21]张徐杰,林盛吉,马冲,等. HadCM3模式下钱塘江流域设计暴雨估算[J].水文, 2013, 33(1):21-26
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[23]陈守煜.从研究汛期描述论水文系统模糊集分析的方法论[J].水科学进展, 1995, 6(2):133-138
[24]陈守煜.工程水文水资源系统模糊集合分析理论与实践[M].大连:大连理工大学出版社, 1998
[25]舒章康,刘冀,董晓华,等.基于模糊集合分析的汛期分期降雨极值分布研究[J].水力发电学报, 2017, 36(7):55-64
[26]陈守煜.基于可变模糊集的辩证法三大规律数学定理及其应用[J].大连理工大学学报, 2010, 50(5):838-844
[27]胡宜昌.中国不同强度降水时空变化特征[J].气象科技进展, 2013(3):59-66
[28]刘攀,郭生练,李玮,等.变点分析方法在隔河岩水库汛期分期中的应用[J].长江科学院院报, 2007(1):8-11
[29]马永胜,黄强,王义民,等.基于模糊集理论的石泉水库分期汛限水位确定[J].水电能源科学, 2008(3):47-49
[30]林壬萍,周天军.参加CMIP5计划的四个中国模式模拟的东亚地区降水结构特征及未来变化[J].大气科学, 2015, 39(2):338-356
[31]刘向培,王汉杰,何明元.应用统计降尺度方法预估江淮流域未来降水[J].水科学进展, 2012, 23(1):29-37
[2]Marengo J A, Cavalcanti I F A, Satyamurty P, et al. Assessment of regional seasonal rainfall predictability using the CPTEC/COLA atmospheric GCM[J]. Climate Dynamics, 2003, 21(5-6):459-475
[3]孔锋,方佳毅,刘凡,等. 1951—2012年中国降水集中度和集中期的时空格局[J].北京师范大学学报:自然科学版, 2015(4):404-411
[4]李东龙,王文圣,李跃清.中国主要江河年径流变化特性分析[J].水电能源科学, 2011(11):1-5
[5]姜洋.基于集中度的大伙房水库汛期分期探讨[J].水利水电技术,2016, 47(5):119-123
[6]陈璐,郭生练,张洪刚,等.长江上游干支流洪水遭遇分析[J].水科学进展, 2011, 22(3):323-330
[7]张利平,杜鸿,夏军,等.气候变化下极端水文事件的研究进展[J].地理科学进展, 2011,30(11):1370-1379
[8]Matti B, Dahlke H E, Dieppois B, et al. Flood seasonality across Scandinavia:evidence of a shifting hydrograph?[J]. Hydrological Processes, 2017, 31(24):4354-4370
[9]Vormoor K, Lawrence D, Heistermann M, et al. Hydrological model parameter(in)stability:implications for the assessment of climate change impacts on flood seasonality[J]. Orbit, 2014, 33(7):477
[10]Vormoor K, Lawrence D, Heistermann M, et al. Climate change impacts on the seasonality and generation processes off loods:projections and uncertainties for catchments with mixed snowmelt/rainfall regimes[J]. Hydrology and Earth System Sciences Discussions,2015, 19(2):913-931
[11]陈海山,范苏丹,张新华.中国近50a极端降水事件变化特征的季节性差异[J].大气科学学报, 2009, 32(6):744-751
[12]王金星,张建云,李岩,等.近50年来中国六大流域径流年内分配变化趋势[J].水科学进展, 2008, 19(5):656-661
[13]顾西辉,张强,刘剑宇,等.新疆塔里木河流域洪水过程集聚性及低频气候影响[J].水科学进展, 2016, 27(4):501-511
[14]蒋海艳,莫崇勋,韦逗逗,等.水库汛期分期研究综述[J].水利水电科技进展, 2012, 32(3):75-80
[15]李浩,周义仁.气候变化对汛期分期的影响研究[J].水力发电,2018, 44(6):22-26
[16]莫崇勋,阮俞理,莫桂燕,等.水文变异对水库汛期分期及汛限水位确定的影响[J].水利水电技术, 2018(2):1-7
[17]董思言,高学杰.长期气候变化:IPCC第五次评估报告解读[J].气候变化研究进展, 2014, 10(1):56-59
[18]Richardson C W, Wright D A. WGEN:a model for generating daily weather variables[J]. Agricultural Research Service, 1984, 97-118
[19] Semenov M, Brooks R, Barrow E, et al. Comparison of the WGEN and LARS-WG stochastic weather generators for diverse climates[J].Climate Research, 1998, 10(2):95-107
[20]祝薄丽,郭家力,郭靖,等.基于多模式耦合的赣江流域设计暴雨估算[J].人民长江, 2016, 47(13):6-11
[21]张徐杰,林盛吉,马冲,等. HadCM3模式下钱塘江流域设计暴雨估算[J].水文, 2013, 33(1):21-26
[22]许士国,陈守煜.水文分期描述的模糊统计方法[J].大连理工大学学报, 1990, 30(5):585-598
[23]陈守煜.从研究汛期描述论水文系统模糊集分析的方法论[J].水科学进展, 1995, 6(2):133-138
[24]陈守煜.工程水文水资源系统模糊集合分析理论与实践[M].大连:大连理工大学出版社, 1998
[25]舒章康,刘冀,董晓华,等.基于模糊集合分析的汛期分期降雨极值分布研究[J].水力发电学报, 2017, 36(7):55-64
[26]陈守煜.基于可变模糊集的辩证法三大规律数学定理及其应用[J].大连理工大学学报, 2010, 50(5):838-844
[27]胡宜昌.中国不同强度降水时空变化特征[J].气象科技进展, 2013(3):59-66
[28]刘攀,郭生练,李玮,等.变点分析方法在隔河岩水库汛期分期中的应用[J].长江科学院院报, 2007(1):8-11
[29]马永胜,黄强,王义民,等.基于模糊集理论的石泉水库分期汛限水位确定[J].水电能源科学, 2008(3):47-49
[30]林壬萍,周天军.参加CMIP5计划的四个中国模式模拟的东亚地区降水结构特征及未来变化[J].大气科学, 2015, 39(2):338-356
[31]刘向培,王汉杰,何明元.应用统计降尺度方法预估江淮流域未来降水[J].水科学进展, 2012, 23(1):29-37