[1]祁雪姣,杨 颖,韩传楠,等.气候变化对长江源区地表径流的影响[J].南京师大学报(自然科学版),2022,45(04):81-90.[doi:10.3969/j.issn.1001-4616.2022.04.012]
　Qi Xuejiao,Yang Ying,Han Chuannan,et al.Effect of Climate Change on Surface Runoff in the Source Area of the Yangtze River[J].Journal of Nanjing Normal University(Natural Science Edition),2022,45(04):81-90.[doi:10.3969/j.issn.1001-4616.2022.04.012]
点击复制

气候变化对长江源区地表径流的影响()
分享到：

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

卷:
第45卷
期数:
2022年04期
页码:
81-90
栏目:
生态学
出版日期:
2022-12-15

文章信息/Info

Title:
Effect of Climate Change on Surface Runoff in the Source Area of the Yangtze River
文章编号:
1001-4616(2022)04-0081-10
作者:
祁雪姣1; 杨 颖1; 韩传楠1; 李健明1; 李佳君1; 刘增辉1; 李梦媛2; 张秀芝2; 包文金2; 卢素锦1; 何 奕1; 李悦娇1; 陈斯亮1; 曾宣淯1
(1.青海大学生态环境工程学院,青海 西宁 810016)
(2.青海大学农牧学院,青海 西宁 810016)
Author(s):
Qi Xuejiao1; Yang Ying1; Han Chuannan1; Li Jianming1; Li Jiajun1; Liu Zenghui1; Li Mengyuan2; Zhang Xiuzhi2; Bao Wenjin2; Lu Sujin1; He Yi1; Li Y
(1.College of Ecological and Environmental Engineering,Qinghai University,Xi'ning 810016,China)
(2.College of Agriculture and Animal Husbandry,Qinghai University,Xi'ning 810016,China)
关键词:
长江源区; 气候变化; 地表径流; CMIP5; RCPS; SWAT模型
Keywords:
the source area of the Yangtze River; climate change; surface runoff; CMIP5; RCPS; SWAT model
分类号:
P467; P333.1
DOI:
10.3969/j.issn.1001-4616.2022.04.012
文献标志码:
A
摘要:
研究气候变化对长江源区地表径流的影响,为长江源区水资源开发与保护提供依据. 基于1980—2021年地表径流数据,运用线性回归法对地表径流年际、年内变化趋势进行分析,运用CMIP5模型中的21种模式的模拟结果,结合RCPS的三种气候情景(RCP2.6、RCP4.5、RCP8.5)并耦合SWAT模型下,预测未来(2022—2100年)长江源区地表径流的变化趋势. 结果表明:1980—2021年地表径流年际变化较大,在2009年年际径流最大,总体呈现上升趋势; 3—7月地表径流量上升,7—12月径流量逐渐下降,12—3月径流量平稳. 除1980—1982年、1983—1985年降水量与径流量相关性不显著外,其余年份均呈显著状态(P<0.05). 用建立好的SWAT模型在长江源区进行模拟,率定期的决定系数为0.81,模拟径流量与实测径流量误差为6.44%,验证期的决定系数为 0.86,误差为4.60%,模拟数值符合度较高,SWAT模型在长江源区较为适用. 三种气候情景下,地表径流的年际变化较大,总体呈现下降趋势; RCP2.6情景下,2048年径流量最大; RCP4.5情景下,2035年径流量最大; RCP8.5情景下,2036年径流量最大. 三种气候情景下,地表径流年内变化较大,且年内分配不均匀,3—8月径流量上升,8—12月径流量下降,12—3月保持平稳; RCP4.5中径流变化最大,RCP8.5中径流变化最小. 未来气候情景下,长江源区径流量将下降,加强水资源保护迫在眉睫.
Abstract:
The impact of climate change on surface runoff in the source area of the Yangtze River is studied to provide a basis for water resources development and protection in the source area of the Yangtze River. Based on the surface runoff data from 1980 to 2021,the linear regression method is used to analyze the inter- and intra-annual trends of surface runoff,and the simulation results of 21 models in the CMIP5 model are used to predict the future(2022-2100)trends of surface runoff in the Yangtze source area River under three climate scenarios(RCP2.6,RCP4.5,RCP8.5)of RCPS and coupled with the SWAT model. The results show that the interannual variation of surface runoff from 1980 to 2021 is large,and the interannual runoff is the largest in 2009,with an overall increasing trend,the surface runoff increases from March to July,decreases gradually from July to December,and is stable from December to March. The correlation between precipitation and runoff was significant(P<0.05)in all years except for 1980-1982 and 1983-1985,correlation was not significant. The established SWAT model was used to simulate in the source area of the Yangtze River. The coefficient of determination for the rate period was 0.81,the error between the simulated runoff and the measured runoff was 6.44%,and the coefficient of determination for the verification period was 0.86 and the error was 4.60% higher,the SWAT model is more applicable in the source area of the Yangtze River. Under the three climate scenarios,the interannual variability of surface runoff is large,and the overall trend is decreasing,the maximum runoff is in 2048 under RCP2.6,2035 under RCP4.5,and 2036 under RCP8.5. Under the three climate scenarios,surface runoff varies greatly within the year and is unevenly distributed within the year,with runoff increasing from March to August,decreasing from August to December,and remaining stable from December to March; runoff varies the most in RCP4.5 and the least in RCP8.5. Under the future climate scenario,the runoff in the source area of the Yangtze River will decrease,and it is urgent to strengthen water conservation.

参考文献/References:

[1]张建云,王国庆,刘九夫,等. 国内外关于气候变化对水的影响的研究进展[J]. 人民长江,2009,40(8):39-41.
[2]魏瑞江,王鑫. 气候适宜度国内外研究进展及展望[J]. 地球科学进展,2019,34(6):584-595.
[3]鄢继尧,赵媛. 近三十年我国生态脆弱区研究热点与展望[J]. 南京师大学报(自然科学版),2020,43(4):74-85.
[4]ZHANG Y,XU X,LIAO Z,et al. Response of surface runoff to land use and land cover change and its impact on Daihai Lake shrinkage in Inner Mongolia,China[J]. Theoretical and applied climatology,2021,144(8):1-15.
[5]简季,潘佩芬,胡运海. 国内外气候变化对水文影响的研究进展[C]//第二届“测绘科学前沿技术论坛”论文精选. 长春,吉林:测绘出版社,2010.
[6]NIGEL W. Climate change and global water resources:SRES emissions and socioeco nomic scenarios[J]. Global environmental change,2004,14(1):31-52.
[7]张强,张存杰,白虎志,等. 西北地区气候变化新动态及对干旱环境的影响——总体暖干化,局部出现暖湿迹象[J]. 干旱气象,2010,28(1):1-7.
[8]QIN Y H,SUN X,LI B F,et al. A nonlinear hybrid model to assess the impacts of climate variability and human activities on runoff at different time scales[J]. Stochastic environmental research and risk assessment,2021,35(9):1917-1929.
[9]陈桂亚,DEREK C. 气候变化对嘉陵江流域水资源量的影响分析[J]. 水资源研究,2006,27(1):25-30.
[10]范广洲,吕世华,程国栋. 气候变化对滦河流域水资源影响的水文模式模拟(Ⅱ)模拟结果分析[J]. 高原气象,2001,20(3):302-310.
[11]秦大河. 中国气候与环境演变[J]. 文明,2005(12):10-11.
[12]周莉,兰明才. 21世纪前期长江中下游极端降水预估及不确定性分析[J]. 气象学报,2018,76(1):47-61.
[13]韩乐琼,韩哲,李双林. 不同代表性浓度路径(RCPs)下21世纪长江中下游强降水预估[J]. 大气科学学报,2014,37(5):529-540.
[14]杨永兴. 国际湿地科学研究的主要特点、进展与展望[J]. 地理科学进展,2002(2):111-120.
[15]王英斌. 全球湿地消失速度加剧[J]. 世界文化,2019(2):61.
[16]MENZEL L,BÜRGER G. Climate change scenarios and runoff response in the Mulde catchment(Southern Elbe,Germany)[J]. Elsevier B.V.,2002,267(1):53-64.
[17]CAMERA C,BRUGGEMAN A,ZITTIS G,et al. Simulation of extreme rainfall and streamflow events in small Mediterranean watersheds with a one-way-coupled atmospheri-hydrologic modelling system[J]. Natural hazards and earth system sciences,2020,20(10):2791-2810.
[18]KIBII J K,KIPKORIR E C,KOSGEI J R. Application of Soil and Water Assessment Tool(SWAT)to evaluate the impact of land use and climate variability on the Kaptagat Catchment River discharge[J]. Sustainability,2021,13(4):1802-1802.
[19]PANDEY V P,BHAUBANJAR S,BHARATI,et al. Hydrological response of Chamelia watershed in Mahakali Basin to climate change[J]. Science of the total environment,2018,650(1):365-383.
[20]谭丽丽,黄峰,乔学瑾,等. TRMM在海河流域南系的降水估算精度评价及其对SWAT模型的适用性[J]. 农业工程学报,2020,36(6):11.
[21]王国庆,金君良,鲍振鑫,等. 气候变化对华北粮食主产区水资源的影响及适应对策[J]. 中国生态农业学报,2014,22(8):898-903.
[22]占车生,宁理科,邹靖,等. 陆面水文—气候耦合模拟研究进展[J]. 地理学报,2018,73(5):893-905.
[23]宋小园. 气候变化和人类活动影响下锡林河流域水文过程响应研究[D]. 内蒙古:内蒙古农业大学,2016.
[24]郑巍斐,杨肖丽,程雪蓉,等. 基于CMIP5和VIC模型的长江上游主要水文过程变化趋势预测[J]. 水文,2018,38(6):48-53.
[25]朱海涛. 长江源区长序列径流变化规律及其与气象要素的关系分析[J]. 中国农学通报,2019,35(22):123-129.
[26]孙永寿,段水强. 近年来青海三江源区河川径流变化特征及趋势分析[J]. 水资源与水工程学报,2015,26(1):52-57.
[27]李林,戴升,申红艳,等. 长江源区地表水资源对气候变化的响应及趋势预测[J]. 地理学报,2012,67(7):941-950.
[28]陈进. 长江源区水循环机理探讨[J]. 长江科学院院报,2013,30(4):1-5.
[29]陈进,黄薇. 水资源与长江的生态环境[M]. 北京:中国水利水电出版社,2008.
[30]梁川,侯小波,潘妮. 长江源高寒区域降水和径流时空变化规律分析[J]. 南水北调与水利科技,2011,9(1):53-59.
[31]范晓梅. 长江源区植被覆盖变化对高寒草甸蒸散的影响及作物系数的确定[D]. 兰州:兰州大学,2011.
[32]刘光生. 长江源多年冻土区沼泽及高寒草甸水热过程及其对气候变化的响应[D]. 兰州:兰州大学,2009.
[33]李峰,胡铁松,黄华金. SWAT模型的原理、结构及其应用研究[J]. 中国农村水利水电,2008(3):24-28.
[34]刘梅. 我国东部地区气候变化模拟预测与典型流域水文水质响应研究[D]. 杭州:浙江大学,2015.
[35]何旭强. 基于SWAT模型的黑河上游径流量模拟及其对气候变化的影响[D]. 兰州:西北师范大学,2013.
[36]李慧,靳晟,雷晓云,等. SWAT模型参数敏感性分析与自动率定的重要性研究—以玛纳斯河径流模拟为例[J]. 水资源与水工程学报,2010,21(1):79-82.
[37]ABBASPOUR K C,VEJDANI M,HAGHIGHAT S. SWAT-CUP calibration and uncertainty programs for SWAT[J]. Modsi international congress on modelling & simulation land water&environmental management integrated system for sustainability,2007,364(3):1603-1609.
[38]万浩,董晓华,彭涛,等. 基于SWAT模型和SUFI-2算法的黄柏河东支流域径流模拟研究[J]. 中国农村水利水电,2018(12):94-100.
[39]任泉,蔡新婷,马文惠. 新疆达坂城地区52a来气温和降水变化特征分析[J]. 干旱区资源与环境,2011,25(10):116-121.
[40]宋晓猛,张建云,占车生,等. 水文模型参数敏感性分析方法评述[J]. 水利水电科技进展,2015,35(6):105-112.
[41]徐会军,陈洋波,李昼阳,等. 基于LH-OAT分布式水文模型参数敏感性分析[J]. 人民长江,2012,43(7):19-23.
[42]孙永寿,段水强,李燕,等. 近年来青海三江源区河川径流变化特征及趋势分析[J]. 水资源与水工程学报,2015,26(1):52-57.
[43]罗玉,秦宁生,周斌,等. 1961—2016年长江源区径流量变化规律[J]. 水土保持研究,2019,26(5):123-128.
[44]朱延龙,陈进,陈广才. 长江源区近32年径流变化及影响因素分析[J]. 长江科学院院报,2011,28(6):1-4.
[45]王菊英,丘玉俐. 长江源年径流量变化趋势分析[J]. 水利水电快报,2008,29(S1):62-64.
[46]程志刚,刘晓东,范广洲,等. 21世纪长江黄河源区径流量变化情势分析[J]. 长江流域资源与环境,2010,19(11):1333-1339.
[47]俞烜,申宿慧,杨舒媛,等. 长江源区径流演变特征及其预测[J]. 水电能源科学,2008(3):14-16.
[48]李硕. GIS和遥感辅助下流域模拟的空间离散化与参数化研究与应用[D]. 南京:南京师范大学,2002.
[49]张永勇,张士锋,翟晓燕,等. 三江源区径流演变及其对气候变化的响应[J]. 地理学报,2012,67(1):71-82.
[50]VERONIKA E,SANDRINE B,MEEHL G A,et al. Overview of the coupled model intercomparison project phase 6(CMIP6)experimental design and organization[J]. Geoscientific model development,2016,9(5):1937-1958.
[51]陈活泼,孙建奇,林文青,等. CMIP6和CMIP5模式对极端气候的模拟比较[J]. Science bulletin,2020,(17):1415-1418.
[52]ZHU H H,JIANG Z H,LI J,et al. Does CMIP6 inspire more confidence in simulating climate extremes over China?[J]. Advances in atmospheric sciences,2020,37(10):1119-1132.
[53]王予,李惠心,王会军,等. CMIP6全球气候模式对中国极端降水模拟能力的评估及其与CMIP5的比较[J]. 气象学报,2021,79(3):369-386.

备注/Memo

备注/Memo:
收稿日期:2022-04-12.
基金项目:国家自然科学基金地区基金项目(31760147)、青海省科技厅项目(2021-ZJ-926).
通讯作者:卢素锦,教授,研究方向:修复生态学研究. E-mail:lusujin88@163.com
更新日期/Last Update: 2022-12-15