多模式预测气候变化及其对雪冰流域径流的影响

doi:10.12118/j.issn.1000–6060.2021.03.23

干旱区地理 ›› 2021, Vol. 44 ›› Issue (3): 807-818.doi: 10.12118/j.issn.1000–6060.2021.03.23

多模式预测气候变化及其对雪冰流域径流的影响

冉思红^1,²(),王晓蕾^2,³,罗毅^2,³()

1.中国科学院新疆生态与地理研究所,荒漠与绿洲生态国家重点实验室,新疆乌鲁木齐 830011
2.中国科学院大学,北京 100049
3.中国科学院地理科学与资源研究所,生态系统网络观测与模拟重点实验室,北京 100049

收稿日期:2020-10-10 修回日期:2021-04-20 出版日期:2021-05-25 发布日期:2021-06-01
通讯作者: 罗毅
作者简介:冉思红（1993-）,女,硕士研究生,主要从事流域水文模拟. E-mail： 18810990976@163.com
基金资助:
中国科学院A类战略性先导科技专项(XDA20060301);国家重点研发计划(2016YFC0501603);国家自然科学基金资助项目(41741025)

Predicting climate change and its impact on runoff in snow-ice basin with multi-climate models

RAN Sihong^1,²(),WANG Xiaolei^2,³,LUO Yi^2,³()

1. State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, Xinjiang, China
2. University of Chinese Academy of Sciences, Beijing 100049, China
3. Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100049, China

Received:2020-10-10 Revised:2021-04-20 Online:2021-05-25 Published:2021-06-01
Contact: Yi LUO

摘要/Abstract

摘要：

冰川覆盖流域的雪冰融水对河川径流有重要的调节作用。气候变化影响雪冰融水过程和数量变化,河川径流过程和径流量相应变化,其程度与流域冰川情况相关。通过利用CMIP5气候模式输出气象数据驱动流域水文模型,模拟研究天山地区3个不同冰川覆盖率河流（库玛拉克河、玛纳斯河、库车河)的径流对气候变化的响应。结果表明：随着未来气温和降水的持续增加,3个流域的雪融水均有增加,冰融水变化受冰川覆盖面积的影响,在各个流域变化不一致。径流变化主要受降水增加和雪冰融水变化的综合影响,在未来情景下各流域径流均有增加,分别增加了5.8%~14.3%（库车河）、2.9%~11.4%（玛纳斯河）、12.9%~47.1%（库玛拉克河）,且冰川覆盖率越大的流域,预估径流不确定性变化区间受冰融水影响越大。预估3个流域的径流、雪冰融水年内分布变化表明,各河流的春季融雪时间提前和融雪量增加使得流域春季径流量较历史时期增大;在夏季,受雪冰融水变化的影响库车河、玛纳斯河夏季径流峰值量减小,而库玛拉克河径流峰值量增加,且预估的各流域夏季径流变化不确定性区间明显大于其它季节。

关键词: 气候变化, 气候模式, 水文模型, 冰川, 径流

Abstract:

The snow-ice melt water in glacier-covered basins plays an essential role in regulating runoff. The impact of climate change on the snow-ice melting process and quantity change, river runoff process and quantity change, which is related to the glacier area in the basin. Using climate models’ meteorological data of CMIP5 driven watershed hydrological model, simulated runoff response to climate change in Tianshan areas (Kumaric River, Manas River, and Kuqa River, Xinjiang, China). The results show that with the temperature and precipitation increasing in the future, three river basins’ snow melt water is both increasing, but ice melt water changes affected by glacier coverage. The change of runoff was mainly affected by the increase in precipitation and the change in snow and ice melt water; the runoff increased by 5.8%-14.3% (Kuqa River), 2.9%-11.4% (Manas River), and 12.9%-47.1% (Kumaric River) under three representative concentration pathways (RCPs). It was estimated that the variation range of runoff uncertainty was affected by ice melting. From the projected intra-annual distribution of runoff, the snow and ice melt of the three basins, the spring runoff of the river basins increased compared with the historical period due to the snow melt time ahead and snow melt volume. In the summer, the peak runoff of the Kuqa River and Manas River decreased due to ice melt water, whereas the peak value of runoff in Kumaric River increased. In addition, the estimated uncertainty range of summer runoff in the study basins in the summer season is significantly larger than those of other seasons.

Key words: climate change, climate model, hydrological model, glacier, runoff

冉思红,王晓蕾,罗毅. 多模式预测气候变化及其对雪冰流域径流的影响[J]. 干旱区地理, 2021, 44(3): 807-818.

RAN Sihong,WANG Xiaolei,LUO Yi. Predicting climate change and its impact on runoff in snow-ice basin with multi-climate models[J]. Arid Land Geography, 2021, 44(3): 807-818.

图/表 11

图1

表1

表2

表3

CMIP5中39个气候模式基本信息"

模式名称	所属国家	分辨率	情景
ACCESSE1-3	澳大利亚	1.25°×1.88°	RCP4.5、RCP8.5
ACCESSE1-0	澳大利亚	1.25°×1.88°	RCP4.5、RCP8.6
BCC-CSM1-1	中国	2.80°×2.80°	RCP2.6、RCP4.5、RCP8.5
BCC-CSM1-1-m	中国	1.12°×1.25°	RCP2.6、RCP4.5、RCP8.5
BNU-ESM-3	中国	2.80°×2.80°	RCP2.6、RCP4.5、RCP8.5
CanESM2	加拿大	2.80°×2.80°	RCP2.6、RCP4.5、RCP8.5
CCSM4_4	美国	0.94°×1.25°	RCP2.6、RCP4.5、RCP8.5
CESM1-BGC	美国	0.94°×1.25°	RCP4.5、RCP8.5
CESM1-CAM5	美国	0.94°×1.25°	RCP2.6、RCP4.5、RCP8.5
CESM1-WACCM	美国	1.90°×2.50°	RCP2.6、RCP4.5、RCP8.5
CMCC-CESM	意大利	3.75°×3.75°	RCP8.5
CMCC-CM	意大利	0.75°×0.75°	RCP4.5、RCP8.5
CMCC-CMS	意大利	1.86°×1.875°	RCP4.5、RCP8.5
CNRMCM	法国	1.40°×1.40°	RCP2.6、RCP4.5、RCP8.5
CSIRO-Mk3-6-0	澳大利亚	1.88°×1.88°	RCP2.6、RCP4.5、RCP8.5
EC-EARTH	爱尔兰	1.12°×1.25°	RCP2.6、RCP4.5、RCP8.5
FGOALS-g2	中国	2.81°×2.81°	RCP2.6、RCP4.5、RCP8.5
FIO-ESM	中国	2.79°×2.81°	RCP2.6、RCP4.5、RCP8.5
GFDL-CM3	美国	2.00°×2.50°	RCP2.6、RCP4.5、RCP8.5
GFDL-ESM2G	美国	2.00°×2.50°	RCP2.6、RCP4.5、RCP8.5
GFDL-ESM2M	美国	2.00°×2.50°	RCP2.6、RCP4.5、RCP8.5
GISS-E2-H	美国	2.00°×2.50°	RCP2.6、RCP4.5、RCP8.5
GISS-E2-H-cc	美国	2.00°×2.50°	RCP4.5
GISS-E2-R	美国	2.00°×2.50°	RCP2.6、RCP4.5、RCP8.5
GISS-E2-R-cc	美国	2.00°×2.50°	RCP4.5
HadGEM2-AO	韩国	1.25°×1.88°	RCP2.6、RCP4.5、RCP8.5
HadGEM2-CC	英国	1.25°×1.88°	RCP4.5、RCP8.5
HadGEM2-ES	英国	1.25°×1.88°	RCP2.6、RCP4.5、RCP8.5
INMCM4	俄国	1.50°×2.00°	RCP4.5、RCP8.5
IPSL-CM5A-LR	法国	1.86°×3.75°	RCP2.6、RCP4.5、RCP8.5
IPSL-CM5A-MR	法国	1.25°×2.50°	RCP2.6、RCP4.5、RCP8.5
IPSL-CM5B-LR	法国	1.9°×3.75°	RCP4.5、RCP8.5
MIROC5	日本	1.40°×1.40°	RCP2.6、RCP4.5、RCP8.5
MIROC-ESM	日本	2.81°×2.81°	RCP2.6、RCP4.5、RCP8.5
MIROC-ESM-CHEM	日本	2.81°×2.81°	RCP2.6、RCP4.5、RCP8.5
MPI-ESM-LR	德国	1.86°×1.88°	RCP2.6、RCP4.5、RCP8.5
MPI-ESM-MR	德国	1.86°×1.88°	RCP2.6、RCP4.5、RCP8.5
MRI-CGCM3	日本	1.12°×1.13°	RCP2.6、RCP4.5、RCP8.5
NorESM1-M	挪威	1.90°×2.50°	RCP2.6、RCP4.5、RCP8.5

表3

表4

图2

图3

表5

研究区未来近期和远期39个气候模式集合的气温、降水、径流、冰融水均值较历史时期变化"

情景	变量	库车河				玛纳斯河				库玛拉克河
情景	变量	气温/℃	降水/%	冰融水/%	径流/%	气温/℃	降水/%	冰融水/%	径流/%	气温/℃	降水/%	冰融水/%	径流/%
RCP2.6（近期）	平均值	1.7	4.7	-5.7	6.4	1.5	3.7	25.0	10.1	1.7	3.3	111.8	28.3
	最大值	2.9	23.6	31.2	51.6	2.9	18.1	161.5	41.8	2.6	15.5	212.6	56.2
	最小值	0.6	-10.4	-40.7	-25.7	0.0	-9.7	-43.0	-8.8	0.6	-10.5	4.6	8.2
	标准差	0.6	7.4	15.1	15.0	0.7	5.9	61.9	13.9	0.5	6.1	52.3	13.4
RCP2.6（远期）	平均值	1.8	3.9	-64.6	7.8	1.7	4.7	-37.9	2.9	1.9	3.8	40.5	12.9
	最大值	3.6	28.0	-49.1	72.8	3.1	24.9	12.1	32.8	3.5	17.2	111.5	35.9
	最小值	-0.3	-11.3	-77.1	-23.1	-0.2	-13.2	-51.6	-18.1	-0.2	-9.1	-25.0	-11.1
	标准差	0.8	9.4	7.3	20.5	0.9	7.1	13.6	10.7	0.8	7.0	33.5	11.4
RCP4.5（近期）	平均值	1.6	4.4	-2.1	7.4	1.4	3.8	23.5	9.8	1.7	3.2	121.1	30.5
	最大值	2.7	21.9	26.4	43.2	2.4	17.7	156.5	39.7	2.7	12.9	226.8	62.9
	最小值	-1.3	-9.5	-27.9	-21.2	-0.1	-13.7	-49.0	-7.2	-1.3	-12.0	10.8	6.5
	标准差	0.7	7.0	12.1	14.0	0.6	6.3	58.6	12.6	0.7	5.8	52.2	11.7
RCP4.5（远期）	平均值	3.0	6.3	-60.0	12.4	2.5	5.8	-22.0	6.6	3.0	4.4	103.4	27.0
	最大值	4.9	29.2	-33.3	73.8	4.8	25.4	13.9	40.8	4.9	18.1	154.2	48.0
	最小值	1.1	-12.8	-80.3	-26.8	-0.2	-13.0	-60.8	-12.9	1.1	-12.8	24.0	6.4
	标准差	0.9	8.6	11.4	19.4	1.1	7.6	20.4	11.8	0.9	7.4	31.8	10.1
RCP8.5（近期）	平均值	2.0	4.2	3.4	5.8	1.6	3.7	34.5	11.4	2.0	3.1	142.9	34.8
	最大值	3.1	27.8	33.5	60.3	3.1	21.6	178.3	46.0	3.0	18.3	251.4	67.9
	最小值	0.7	-17.6	-21.3	-23.9	-0.4	-12.3	-47.1	-7.1	0.8	-19.7	33.5	6.8
	标准差	0.5	7.8	12.4	15.1	0.8	6.2	71.3	14.9	0.5	7.0	54.8	13.0
RCP8.5（远期）	平均值	5.2	6.0	-65.1	14.3	4.2	5.9	-0.3	9.8	5.2	2.5	208.2	47.1
	最大值	7.5	40.5	-28.2	120.4	7.7	39.1	77.8	64.7	7.4	27.3	260.0	78.0
	最小值	2.6	-24.7	-88.3	-37.3	-0.1	-19.4	-49.2	-17.4	2.5	-25.3	103.4	25.8
	标准差	1.2	12.6	15.0	29.1	1.9	10.4	37.8	16.4	1.2	10.9	32.5	11.8

表5

图4

图5

图6

参考文献 57

[1]	Vaughan G D, Comiso J C, Allison I, et al. Observation: Cryosphere [C] //Climate Change 2013: The Physical Science Basis. New York, USA: Cambridge University Press, 2013: 317-382.
[2]	赵宗慈, 罗勇, 黄建斌. 全球冰川正在迅速消融[J]. 气候变化研究进展, 2015,11(6):440-442.
	[ Zhao Zongci, Luo Yong, Huang Jianbin. Global glaciers are rapidly melting[J]. Advances in Climate Change Research, 2015,11(6):440-442. ]
[3]	Barnett T P, Adam J C, Lettenmaier D P. Potential impacts of a warming climate on water availability in snow-dominated regions[J]. Nature, 2005,438(7066):303-309. pmid: 16292301
[4]	Unger-Shayesteh K, Vorogushyn S, Farinotti D, et al. What do we know about past changes in the water cycle of Central Asian headwaters? A review[J]. Global and Planetary Change, 2013,110:4-25. doi: 10.1016/j.gloplacha.2013.02.004
[5]	Hagg W, Braun L N, Weber M, et al. Runoff modelling in glacierized Central Asian catchments for present-day and future climate[J]. Nordic Hydrology, 2006,37(2):93-105. doi: 10.2166/nh.2006.0008
[6]	陈亚宁, 杨青, 罗毅, 等. 西北干旱区水资源问题研究思考[J]. 干旱区地理, 2012,35(1):1-9.
	[ Chen Yaning, Yang Qing, Luo Yi, et al. Ponder on the issues of water resources in the arid region of northwest China[J]. Arid Land Geography, 2012,35(1):1-9. ]
[7]	Schaner N, Voisin N, Nijssen B, et al. The contribution of glacier melt to streamflow[J]. Environmental Research Letters, 2012,7(3):34029-34036. doi: 10.1088/1748-9326/7/3/034029
[8]	蒙彦聪, 李忠勤, 徐春海, 等. 中国西部冰川小冰期以来的变化——以天山乌鲁木齐河流域为例[J]. 干旱区地理, 2016,39(3):486-494.
	[ Meng Yancong, Li Zhongqin, Xu Chunhai, et al. Glacier change of western China since the little ice age: A case of the Urumqi River Watershed[J]. Arid Land Geography, 2016,39(3):486-494. ]
[9]	王圣杰, 张明军, 李忠勤, 等. 近50年来中国天山冰川面积变化对气候的响应[J]. 地理学报, 2011,66(1):38-46.
	[ Wang Shengjie, Zhang Mingjun, Li Zhongqin, et al. Response of glacier area variation to climate change in Chinese Tianshan Mountains in the past 50 years[J]. Acta Geographica Sinica, 2011,66(1):38-46. ]
[10]	Sorg A, Bolch T, Stoffel M, et al. Climate change impacts on glaciers and runoff in Tien Shan(Central Asia)[J]. Nature Climate Change, 2012,2(10):725. doi: 10.1038/nclimate1592
[11]	刘时银, 丁永建, 张勇, 等. 塔里木河流域冰川变化及其对水资源影响[J]. 地理学报. 2006,61(5):482-490.
	[ Liu Shiyin, Ding Yongjian, Zhang Yong, et al. Impact of the glacial change on water resources in the Tarim River Basin[J]. Acta Geographica Sinica, 2006,61(5):482-490. ]
[12]	Khadka D, Babel M S, Shrestha S, et al. Climate change impact on glacier and snow melt and runoff in Tamakoshi Basin in the Hindu Kush Himalayan (HKH) region[J]. Journal of Hydrology. 2014,511(4):49-60. doi: 10.1016/j.jhydrol.2014.01.005
[13]	陈亚宁, 李稚, 方功焕, 等. 气候变化对中亚天山山区水资源影响研究[J]. 地理学报, 2017,72(1):18-26. doi: 10.11821/dlxb201701002
	[ Chen Yaning, Li Zhi, Fang Gonghuan, et al. Impact of climate change on water resources in the Tianshan Mountians, Central Asia[J]. Acta Geographica Sinica, 2017,72(1):18-26. ] doi: 10.11821/dlxb201701002
[14]	Sorg A, Huss M, Rohrer M, et al. The days of plenty might soon be over in glacierized Central Asian catchments[J]. Environmental Research Letters, 2014,9:10401810, doi: 10.1088/1748-9326/9/10/104018.
[15]	Gan R, Luo Y, Zuo Q, et al. Effects of projected climate change on the glacier and runoff generation in the Naryn River Basin, Central Asia[J]. Journal of Hydrology, 2015,523:240-251. doi: 10.1016/j.jhydrol.2015.01.057
[16]	张宜清. 气候变化对中国天山雨雪冰产流过程的影响[D]. 北京: 中国科学院大学, 2016.
	[ Zhang Yiqing. The impact of climate change on runoff generation and streamflow in the Tianshan Mountains, China[D]. Beijing: The University of Chinese Academy of Sciences, 2016. ]
[17]	Lutz A F, Ter Maat H W, Biemans H, et al. Selecting representative climate models for climate change impact studies: An advanced envelope-based selection approach[J]. International Journal of Climatology, 2016,36(12):3988-4005. doi: 10.1002/joc.4608
[18]	Woldemeskel F M, Sharma A, Sivakumar B, et al. A framework to quantify GCM uncertainties for use in impact assessment studies[J]. Journal of Hydrology, 2014,519:1453-1465. doi: 10.1016/j.jhydrol.2014.09.025
[19]	Immerzeel W W, van Beek L P H, Konz M, et al. Hydrological response to climate change in a glacierized catchment in the Himalayas[J]. Climatic Change, 2012,110(3-4):721-736. pmid: 26005229
[20]	Zhang Y, Luo Y, Sun L, et al. Using glacier area ratio to quantify effects of melt water on runoff[J]. Journal of Hydrology, 2016,538:269-277. doi: 10.1016/j.jhydrol.2016.04.026
[21]	Ma C, Sun L, Liu S, et al. Impact of climate change on the streamflow in the glacierized Chu River Basin, Central Asia[J]. Journal of Arid Land, 2015,7(4):501-513. doi: 10.1007/s40333-015-0041-0
[22]	Su F, Zhang L, Ou T, et al. Hydrological response to future climate changes for the major upstream river basins in the Tibetan Plateau[J]. Global and Planetary Change, 2016,136:82-95. doi: 10.1016/j.gloplacha.2015.10.012
[23]	Peel M C, Srikanthan R, Mcmahon T A, et al. Approximating uncertainty of annual runoff and reservoir yield using stochastic replicates of global climate model data[J]. Hydrology and Earth System Sciences, 2015,19(4):1615-1639. doi: 10.5194/hess-19-1615-2015
[24]	Bosshard T, Kotlarski S, Zappa M, et al. Hydrological climate-impact projections for the Rhine River: GCM-RCM uncertainty and separate temperature and precipitation effects[J]. Journal of Hydrometeorology, 2014,15(2):697-713. doi: 10.1175/JHM-D-12-098.1
[25]	Vetter T, Huang S, Aich V, et al. Multi-model climate impact assessment and intercomparison for three large-scale river basins on three continents[J]. Earth System Dynamics, 2015,6(1):17-43. doi: 10.5194/esd-6-17-2015
[26]	Xu H, Taylor R G, Xu Y. Quantifying uncertainty in the impacts of climate change on river discharge in sub-catchments of the Yangtze and Yellow River Basins, China[J]. Hydrology and Earth System Sciences, 2011,15(1):333-344. doi: 10.5194/hess-15-333-2011
[27]	Immerzeel W W, van Beek L P H, Bierkens M F P. Climate change will affect the Asian water towers[J]. Science, 2010,328(5984):1382-1385. doi: 10.1126/science.1183188
[28]	王国亚, 沈永平, 苏宏超, 等. 1956—2006年阿克苏河径流变化及其对区域水资源安全的可能影响[J]. 冰川冻土, 2008,30(4):562-568.
	[ Wang Guoya, Shen Yongping, Su Hongchao, et al. Runoff changes in Aksu River Basin during 1956—2006 and their impacts on water availability for Tarim River[J]. Journal of Glaciology and Geocryology, 2008,30(4):562-568. ]
[29]	沈永平, 王国亚, 丁永建, 等. 1957—2006年天山萨雷扎兹库玛拉克河流域冰川物质平衡变化及其对河流水资源的影响[J]. 冰川冻土, 2009,31(5):792-800.
	[ Shen Yongping, Wang Guoya, Ding Yongjian, et al. Changes in glacier mass balance in eatershed of Sary Jaz-Kumarik Rivers of Tianshan Mountains in 1957—2006 and their impact on water resources and trend to end of the 21^th century[J]. Journal of Glaciology and Geocryology, 2009,31(5):792-800. ]
[30]	叶柏生, 丁永建, 刘潮海. 不同规模山谷冰川及其径流对气候变化的响应过程[J]. 冰川冻土, 2001,23(2):103-110.
	[ Ye Baisheng, Ding Yongjian, Liu Chaohai. Response of valley glaciers in various size and their runoff to climate change[J]. Journal of Glaciology and Geocryology, 2001,23(2):103-110. ]
[31]	高前兆, 王润, Ernst Giese. 气候变化对塔里木河来自天山的地表径流影响[J]. 冰川冻土, 2008,30(1):1-11.
	[ Gao Qianzhao, Wang Run, Ernst Giese. Impact of climate change on surface runoff of Tarim River originating from the south slopes of the Tianshan Mountains[J]. Journal of Glaciology and Geocryology, 2008,30(1):1-11. ]
[32]	Luo Y, Arnold J, Liu S, et al. Inclusion of glacier processes for distributed hydrological modeling at basin scale with application to a watershed in Tianshan Mountains, northwest China[J]. Journal of Hydrology, 2013,477:72-85. doi: 10.1016/j.jhydrol.2012.11.005
[33]	Aizen V B, Aizen E M, Melack J M, et al. Climatic and hydrologic changes in the Tien Shan, Central Asia[J]. Journal of Climate, 1997,10(6):1393-1404. doi: 10.1175/1520-0442(1997)010<1393:CAHCIT>2.0.CO;2
[34]	Guo W, Liu S, Xu J, et al. The second Chinese glacier inventory: Data, methods and results[J]. Journal of Glaciology, 2015,61(226):357-372. doi: 10.3189/2015JoG14J209
[35]	Aizen V B, Kuzmichenok V A, Surazakov A B, et al. Glacier changes in the Tien Shan as determined from topographic and remotely sensed data[J]. Global and Planetary Change, 2007,56(3-4):328-340. doi: 10.1016/j.gloplacha.2006.07.016
[36]	Yatagai A, Kamiguchi K, Arakawa O, et al. APHRODITE: Constructing a long-term daily gridded precipitation dataset for Asia based on a dense network of rain gauges[J]. Bulletin of the American Meteorological Society, 2012,93(9):1401-1415. doi: 10.1175/BAMS-D-11-00122.1
[37]	Sheffield J, Goteti G, Wood E F. Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling[J]. Journal of Climate, 2006,19(13):3088-3111. doi: 10.1175/JCLI3790.1
[38]	Lutz A F, Immerzeel W W, Shrestha A B, et al. Consistent increase in high Asia’s runoff due to increasing glacier melt and precipitation[J]. Nature Climate Change, 2014,4(7):587-592. doi: 10.1038/nclimate2237
[39]	李兰海, 尚明, 张敏生, 等. APHRODITE降水数据驱动的融雪径流模拟[J]. 水科学进展, 2014,25(1):53-59.
	[ Li Lanhai, Shang Ming, Zhang Minsheng, et al. Snowmelt runoff simulation driven by APHRODITE precipitation dataset[J]. Advances in Water Science, 2014,25:53-59. ]
[40]	Lutz A F, Immerzeel W W, Gobiet A, et al. Comparison of climate change signals in CMIP3 and CMIP5 multi-model ensembles and implications for Central Asian glaciers[J]. Hydrology and Earth System Sciences, 2013,17(9):3661-3677. doi: 10.5194/hess-17-3661-2013
[41]	Wang X, Sun L, Zhang Y, et al. Rationalization of altitudinal precipitation profiles in a data-scarce glacierized watershed simulation in the Karakoram[J]. Water, 2016,8(5):186. doi: 10.3390/w8050186
[42]	王晓蕾, 孙林, 张宜清, 等. 用分布式水文模型识别流域冰川融水对径流的贡献——以天山库玛拉克河为例[J]. 资源科学, 2015,37(3):475-484.
	[ Wang Xiaolei, Sun Lin, Zhang Yiqing, et al. Estimation of glacier melt contribution to streamflow using a distributed hydrologic model for the Kumaric River, Tien Shan[J]. Resources Science, 2015,37(3):475-484. ]
[43]	Arnold J G, Allen P M, Bernhardt G. A comprehensive surface-groundwater flow model[J]. Journal of Hydrology, 1993,142(1-4):47-69. doi: 10.1016/0022-1694(93)90004-S
[44]	Nash J E, Sutcliffe J V. River flow forecasting through conceptual models part I: A discussion of principles[J]. Journal of Hydrology, 1970,10(3):282-290. doi: 10.1016/0022-1694(70)90255-6
[45]	Moriasi D N, Arnold J G, Van Liew M W, et al. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations[J]. Transaction of the ASABE, 2007,50(3):885-900.
[46]	Masson D, Knutti R. Spatial-scale dependence of climate model performance in the CMIP3 ensemble[J]. Journal of Climate, 2009,24(11):2680-2692. doi: 10.1175/2011JCLI3513.1
[47]	Wilby R L, Charles S P, Zorita E, et al. Guidelines for use of climate scenarios developed from statistical downscaling methods[J]. Supporting Material of the Intergovernmental Panel on Climate Change, available from the DDC of IPCC TGCIA, 2004,24(27):119-120.
[48]	Arnell N W. Climate change and water resources in Britain[J]. Climate Change, 1998,39(1):83-110. doi: 10.1023/A:1005339412565
[49]	刘潮海, 施雅风, 王宗太, 等. 中国冰川资源及其分布特征——中国冰川目录编制完成[J]. 冰川冻土, 2000,22(2):106-112.
	[ Liu Chaohai, Shi Yafeng, Wang Zongtai, et al. Glacier resources and their distributive characteristics in China: A review on Chinese glacier inventory[J]. Journal of Glaciolgy and Geocryology, 2000,22(2):106-112. ]
[50]	张艳武, 张莉, 徐影. CMIP5模式对中国地区气温模拟能力评估与预估[J]. 气候变化研究进展, 2016,12(1):10-19.
	[ Zhang Yanwu, Zhang Li, Xu Ying. Simulations and projections of the surface air temperature in China by CMIP5 models[J]. Advances in Climate Change Research, 2016,12(1):10-19. ]
[51]	Tianjun Z, Fengfei S, Xiaolong C. Historical evolution of global and regional surface air temperature simulated by FGOALS-s2 and FGOALS-g2: How reliable are the model results[J]. Advances in Atmospheric Sciences, 2013,30(3):638-657. doi: 10.1007/s00376-013-2205-1
[52]	Kong Y, Pang Z. Evaluating the sensitivity of glacier rivers to climate change based on hydrograph separation of discharge[J]. Journal of Hydrology, 2012, 434-435:121-129. doi: 10.1016/j.jhydrol.2012.02.029
[53]	Kaldybayev A, Chen Y, Issanova G, et al. Runoff response to the glacier shrinkage in the Karatal River Basin, Kazakhstan[J]. Arabian Journal of Geosciences, 2016,9(3):208. doi: 10.1007/s12517-015-2106-y
[54]	Semenova O, Beven K. Barriers to progress in distributed hydrological modelling[J]. Hydrological Processes, 2015,29(8):2074-2078. doi: 10.1002/hyp.v29.8
[55]	Kay A L, Davies H N, Bell V A, et al. Comparison of uncertainty sources for climate change impacts: Flood frequency in England[J]. Climatic Change, 2009,92(1):41-63. doi: 10.1007/s10584-008-9471-4
[56]	Haque M M, Rahman A, Hagare D, et al. Estimation of catchment yield and associated uncertainties due to climate change in a mountainous catchment in Australia[J]. Hydrological Processes, 2015,29(19):4339-4349. doi: 10.1002/hyp.10492
[57]	Luo Y, Wang X, Piao S, et al. Contrasting streamflow regimes induced by melting glaciers across the Tien Shan-Pamir-north Karakoram[J]. Sentific Report, 2018,8:16470, doi: 10.1038/s41598-018-34829-2.

河流	水文站	流域面积/km²	冰川情况		高程/m			气候特征
河流	水文站	流域面积/km²	面积/km²	覆盖率/%	平均	最低	最高	气温/°C	降水/mm
库玛拉克河	协和拉	12990	2725	21.0	3732	1434	7070	10.8	130.0
玛纳斯河	肯斯瓦特	5163	493	9.5	3252	846	5145	7.2	215.0
库车河	兰干	2912	15	0.5	2575	1271	4488	11.4	66.5

NSE	PBIAS/%	结果评价
NSE≤0.50	PBIAS>±25	不满意
0.50<NSE≤0.65	±15<PBIAS≤±25	满意
0.65<NSE≤0.75	±10<PBIAS≤±15	好
0.75<NSE≤1	PBIAS<±10	非常好

河流	水文站	月模拟				多年平均径流量/10⁸ m³
		NSE		PBIAS		率定期		验证期
		率定期	验证期	率定期	验证期	实测值	模拟值	实测值	模拟值
库玛拉克河	协和拉	0.66	0.85	1.55	4.08	45.50	44.80	47.30	50.00
玛纳斯河	肯斯瓦特	0.88	0.87	-0.65	-4.45	12.36	12.04	11.43	12.05
库车河	兰干	0.63	0.63	6.65	-2.08	2.97	3.03	3.59	3.50

多模式预测气候变化及其对雪冰流域径流的影响

Predicting climate change and its impact on runoff in snow-ice basin with multi-climate models

RichHTML

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

图/表 11

参考文献 57

相关文章 15

Metrics

本文评价

推荐阅读 0

[1]	隋露, 闫志明, 李开放, 何佩恩, 马英杰, 张汝萃. 人类活动及气候变化影响下伊犁河谷生境质量预测研究[J]. 干旱区地理, 2024, 47(1): 104-116.
[2]	田昊玮, 陈伏龙, 龙爱华, 刘静, 海洋. 博尔塔拉河源流区径流对气候变化的响应及预测[J]. 干旱区地理, 2023, 46(9): 1432-1442.
[3]	魏英楠, 马龙, 孙柏林, 张晶. 基于红皮云杉（Picea koraiensis）重建大兴安岭南麓历史径流量[J]. 干旱区地理, 2023, 46(8): 1269-1278.
[4]	艾丽亚, 王永芳, 郭恩亮, 银山, 顾锡羚. 基于GEE的大青山国家级自然保护区NDVI变化及影响因素分析[J]. 干旱区地理, 2023, 46(8): 1279-1290.
[5]	成硕, 李艳忠, 星寅聪, 于志国, 王渊刚, 黄曼捷. 遥感降水产品对黄河源区水文干旱特征的模拟性能分析[J]. 干旱区地理, 2023, 46(7): 1063-1072.
[6]	杨雪雯, 王宁练, 梁倩, 陈安安. 近60 a天山北坡冰川变化研究[J]. 干旱区地理, 2023, 46(7): 1073-1083.
[7]	高晓宇, 郝海超, 张雪琪, 陈亚宁. 中国西北干旱区植被水分利用效率变化对气象要素的响应——以新疆为例[J]. 干旱区地理, 2023, 46(7): 1111-1120.
[8]	顾朝林, 苏鹤放, 顾江, 高喆, 陈乐琳, 郭力. 论地球科学的新时代[J]. 干旱区地理, 2023, 46(7): 1176-1195.
[9]	陈淑君,许国昌,吕志平,马铭悦,李晗羽,朱玉岩. 中国植被覆盖度时空演变及其对气候变化和城市化的响应[J]. 干旱区地理, 2023, 46(5): 742-752.
[10]	李娜,武永利,赵桂香,钱锦霞,李芬,赵海英,韩普. 近60 a山西省极端气温事件的年际变化及其对区域增暖的响应[J]. 干旱区地理, 2023, 46(3): 337-348.
[11]	任涛涛,李双双,段克勤,何锦屏. 黄土高原热浪型和缺水型骤旱时空变化特征及其影响因素[J]. 干旱区地理, 2023, 46(3): 360-370.
[12]	晋子振, 秦翔, 赵求东, 李延召, 刘宇硕, 陈记祖, 王利辉, 王强. 祁连山西段老虎沟流域消融季径流变化特征研究[J]. 干旱区地理, 2023, 46(2): 178-190.
[13]	冀琴, 张翠兰, 丁悦凯, 曹香芹, 梁文莉. 基于多源遥感数据的珠峰自然保护区冰川监测研究[J]. 干旱区地理, 2023, 46(10): 1591-1601.
[14]	刘鑫, 亢燕铭, 辛渝, 陈勇航, 周海江, 秦汉, 何清, 王智敏. RegCM4.6两种积云参数化方案在东亚模拟结果的评估[J]. 干旱区地理, 2023, 46(1): 23-35.
[15]	丁悦凯, 刘睿, 张翠兰, 童丽媛, 董军. 喜马拉雅地区叶如藏布流域冰川和冰湖变化遥感监测研究[J]. 干旱区地理, 2022, 45(6): 1870-1880.