[1]赵琳林,孙美平,*,等.天山北坡奎屯河流域径流模拟及对气候变化的敏感性分析[J].山地学报,2018,(05):722-730.[doi:10.16089/j.cnki.1008-2786.000368]
 ZHAO Linlin,SUN Meiping,SUN Hao,et al.Discharge Simulation and Sensitivity to Climate Change of the Kuytun River Basin on the North Slope of Tianshan Mountains, China[J].Mountain Research,2018,(05):722-730.[doi:10.16089/j.cnki.1008-2786.000368]
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天山北坡奎屯河流域径流模拟及对气候变化的敏感性分析()
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《山地学报》[ISSN:1008-2186/CN:51-1516]

卷:
期数:
2018年05期
页码:
722-730
栏目:
山地环境
出版日期:
2018-09-30

文章信息/Info

Title:
Discharge Simulation and Sensitivity to Climate Change of the Kuytun River Basin on the North Slope of Tianshan Mountains, China
文章编号:
1008-2786-(2018)5-722-09
作者:
赵琳林1孙美平1 2 *孙 皓1巩宁刚1闫露霞1
1.西北师范大学 地理与环境科学学院, 兰州 730070; 2.中国科学院西北生态环境资源研究院 冰冻圈科学国家重点实验室,兰州 730000
Author(s):
ZHAO Linlin1 SUN Meiping1 2 SUN Hao1 GONG Ninggang1 YAN Luxia1
1.College of Geography and Environment Sciences, Northwest Normal University, Lanzhou 730070, China; 2.State Key Laboratory of Cryosphere Sciences, Northwest Institute of Eco-Environment and Resources, CAS, Lanzhou 730000, China
关键词:
月径流模拟 敏感性分析 冰川储量 BP人工神经网络 奎屯河流域
Keywords:
monthly discharge simulation sensitivity analysis glacier volume BP artificial neural network Kuytun River Basin
分类号:
P933
DOI:
10.16089/j.cnki.1008-2786.000368
文献标志码:
A
摘要:
利用乌苏气象站和将军庙水文站1964-2009年气象与水文数据,将月径流分为消融期和非消融期进行研究,并结合第一和第二次冰川编目数据以及1979-2009年分辨率为0.1°×0.1°的CMFD数据,基于BP人工神经网络模型对新疆天山北麓奎屯河流域消融期月径流进行模拟及气候变化的敏感性分析,结果表明:(1)奎屯河流域年径流量总体呈上升趋势,消融期径流增速与年径流增速十分接近,非消融期径流变化不甚显著。(2)通过对比分析,发现将气温、降水、日照时数、风速和相对湿度等五种气象要素作为输入的神经网络模型性能最佳。根据两次冰川编目的冰川储量变化值确定的5-7-1结构的BP人工神经网络模拟结果较好,可用于奎屯河流域径流模拟。(3)奎屯河流域消融期径流对气温、降水和日照时数的敏感性较高,对相对湿度和风速的敏感性较低,除风速其他四个要素对径流均起促进作用。降水不变,气温升高0.5℃、1℃和2℃时,径流分别较2000-2009年消融期月径流平均值增加4.62%、9.13%和18.30%; 气温不变,降水增加10%时,径流将增加9.78%。气温和降水同时作用时,径流增加幅度明显高于仅气温或仅降水作用下的情景。
Abstract:
The discharges during the ablation and non-ablation periods of the Kuytun River Basin were analyzed by using the meteorological data from Usu Meteorological Station and hydrological data from Jiangjunmiao Hydrological Station during 1964-2009.Combined with the data from the First and Second Chinese Glacier Inventories and the China Meteorological Forcing Dataset(CMFD)with the resolution of 0.1°×0.1°, the discharge during ablation period was simulated using the BP artificial neural network, and the sensitivity analysis of climate change was examined.The results showed that:(1)The annual discharge from the Kuytun River Basin presented an generally increasing trend.The trend magnitude of discharge during ablation period was close to the annual value.There was no significant trend during the non-ablation period.(2)The comparative analysis indicated that the BP artificial neural network model showed a best performance when the five meteorological elements(air temperature, precipitation amount, sunshine duration, wind speed and relative humidity)were applied as input data.The best structure of BP artificial neural network model was 5-7-1, which was determined by the change of glacier volume of the First and Second Chinese Glacier Inventories.(3)The air temperature, precipitation amount, sunshine duration and relative humidity during the ablation period of the Kuytun River Basin all played important roles in promoting discharge, but the wind speed was the opposite.The discharge was more sensitive to air temperature, precipitation amount and sunshine duration.The discharge will rise by 4.62%, 9.13% and 18.30% relative to the mean value during 2000-2009, when precipitation amount remains stable and air temperature rises by 0.5 ℃, 1 ℃ and 2 ℃, respectively.When air temperature keeps constant and precipitation amount rises by 10%, the discharge will rise by 9.78%.When air temperature and precipitation amount change simultaneously, the increase of discharge will be significantly higher than that if only air temperature or precipitation amount changes.

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备注/Memo

备注/Memo:
收稿日期(Received date):2018-04-05; 改回日期(Accepted date): 2018-09-20
基金项目(Foundation item):国家自然科学基金项目(41561016); 中国博士后科学基金(2015M572619); 西北师范大学创新团队项目:冰冻圈变化(NWNU-LKQN-14-4)资助。 [National Natural Science Foundation of China(41561016); China Postdoctoral Science Foundation(2015M572619); Innovative Team Project of Northwest Normal University: Changes of Cryosphere(NWNU-LKQN-14-4)]
作者简介(Biography):赵琳林(1994-),女,黑龙江齐齐哈尔人,硕士研究生,研究方向为寒旱区水文与气候变化。[ZHAO Linlin(1994-), female, born in Qiqihaer, Heilongjiang province, M.Sc.candidate, research on hydrology and climate change in cold and arid regions] E-mail:geozhao1994@163.com
*通讯作者(Corresponding author):孙美平(1982-),女,辽宁沈阳人,博士,副教授,主要从事寒区旱区气候变化及水文过程方面研究。[SUN Meiping(1982-), female, boin in Shenyang, Liaoning province, Ph.D., associate professor, specialized in climate change and hydrological processes in cold and arid regions] E-mail:sunmeiping1982@163.com
更新日期/Last Update: 2018-11-30