降亚楠,王蕾,魏晓妹,丁星臣.基于SWAT模型的气候变化对泾河径流量的影响[J].农业机械学报,2017,48(2):262-270.
JIANG Ya’nan,WANG Lei,WEI Xiaomei,DING Xingchen.Impacts of Climate Change on Runoff of Jinghe River Based on SWAT Model[J].Transactions of the Chinese Society for Agricultural Machinery,2017,48(2):262-270.
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基于SWAT模型的气候变化对泾河径流量的影响   [下载全文]
Impacts of Climate Change on Runoff of Jinghe River Based on SWAT Model   [Download Pdf][in English]
投稿时间:2016-10-19  修订日期:2017-02-10
DOI:10.6041/j.issn.1000-1298.2017.02.035
中文关键词:  气候变化  泾河流域  SWAT模型  径流量  典型水文年
基金项目:国家自然科学基金项目(51409219、51409222)、水利部公益性行业科研专项(201301016)、西北农林科技大学基本科研业务费项目(2014YB051)和博士科研启动经费项目(2013BSJJ099)
作者单位
降亚楠 西北农林科技大学水利与建筑工程学院 
王蕾 西北农林科技大学水利与建筑工程学院 
魏晓妹 西北农林科技大学水利与建筑工程学院 
丁星臣 东北农业大学水利与土木工程学院 
中文摘要:在收集、处理大量空间及属性数据资料的基础上,构建泾河流域SWAT模型,运用流域出口站张家山水文站点11年的月实测径流量数据对模型进行率定和验证,并以Nash-Sutcliffe系数(Ns)和决定系数(R2)2个指标综合评价模拟效果,率定期及验证期的2个指标值均大于0.7,表明模型对泾河径流量的模拟具有较好的适用性。通过历史降水量数据频率分析计算,选取3个典型水文年作为基准年,并根据前人对HadCM3模式在A2、B2情景下的输出数据作统计降尺度处理得到流域未来3个时段(2020s、2050s和2080s)降水量、气温的变化结果,设定2种未来气候变化情景,并分别输入已验证的SWAT模型,预测未来典型水文年月径流量的变化趋势。结果表明:相比基准年,2种情景下未来3个时段典型水文年年径流量均减小,丰水年在2种情景下的减幅分别为26%~42%和25%~35%,平水年的减幅为23%~37%和21%~25%,枯水年的减幅为23%~38%和20%~31%;2种情景下未来3个时段典型水文年内的月径流量分配趋势与基准年大致相同,且月径流量的变化特征与降水量的变化基本一致,径流量在月峰值处的变化幅度较大,在其他月份变幅较小;A2情景下,3个时段的丰水年月径流量在8月份减幅分别为41%、43%和61%,平水年月径流量在7月份减幅依次为15%、23%和38%,枯水年的月径流量在6月份减幅依次为20%、36%和46%;B2情景下,3个时段的丰水年月径流量在8月份减幅分别为34%、37%和56%,平水年月径流量在7月份减幅依次为15%、23%和38%,而在2月份的径流量分别从17.71m3/s增加到24.93、38.79、63.63m3/s,枯水年的月径流量在6月份减幅依次为24%、31%和28%;2种情景下,丰水年的径流量年内分配不均匀系数从1.06分别减小到0.71和0.74,年内分配不均匀程度降低,而平水年及枯水年的径流量年内分配不均匀系数变化较小;对比2种情景,无论是典型年的年径流量还是各月径流量,其在各时段的变化趋势基本一致,且变幅相差不大。
JIANG Ya’nan  WANG Lei  WEI Xiaomei  DING Xingchen
College of Water Resources and Architectural Engineering, Northwest A&F University,College of Water Resources and Architectural Engineering, Northwest A&F University,College of Water Resources and Architectural Engineering, Northwest A&F University and School of Water Conservancy and Civil Engineering, Northeast Agricultural University
Key Words:climate change  Jinghe watershed  SWAT model  runoff  representative hydrological year
Abstract:When trying to analyze water resources supply and demand balance under climate change for river basin and irrigation district, the annual runoff of river and its monthly distribution in representative hydrological years are necessary and basic data to evaluate the available surface water supply. In order to predict the impacts of future climate change on runoff of Jinghe River, a SWAT model was developed by collecting and processing large amounts of data such as the hydrological, geological and meteorological data. The model was calibrated and validated by using 11 years monthly runoff data from Zhangjiashan hydrological station and evaluated with two targets (the Nash-Sutcliffe coefficient (Ns) and determination coefficient (R2)). Values of Ns and R2 in calibration and validation stages were both greater than 0.7, which meant that the model was capable of simulating runoff responses to climate change. Three representative hydrological years were chosen after analyzing and calculating the precipitation frequency, which were the wet year (25%), normal year (50%) and dry year (75%). Two future climate change scenarios were developed based on previous study, in which precipitation and temperature trends of future three periods (2020s, 2050s and 2080s) in Jinghe River were predicted by statistically downscaling the output data of HadCM3 under A2 and B2 scenarios, and the river annual runoff and its monthly distribution for representative hydrological years in three future periods were forecasted. The results showed that the annual runoff of representative hydrological years in three future periods of both scenarios were decreased, comparing with base years. The changing rates were 26%~42% and 25%~35%, respectively in wet year, 23%~37% and 21%~25% in normal year, 23%~38% and 20%~31% in the dry year. Under both scenarios, the distributions of monthly runoff of representative hydrological years in three future periods had the same trends as base years. And the changing trends of monthly runoff were basically conformed to the tendencies of monthly precipitation in corresponding scenarios and times. The major amplitudes of monthly runoff were appeared in the peak. In scenarios A2 and B2, the changing rates of peak value in three future periods respectively were 41%, 43%, 61% and 34%, 37%, 56% in August of the wet year, 15%, 23%, 38% and 21%, 18%, 31% in July of the normal year, 20%, 36%, 46% and 24%, 31%, 28% in June of the dry year. But the monthly runoff of February in three future periods under scenario B2 was increased from 17.71m3/s to 24.93m3/s, 38.79m3/s and 63.63m3/s, respectively. By calculating the nonuniform coefficient of the runoff annual distribution (Cvy), it was showed that the value of Cvy in wet year was decreased from 1.06 to 0.71 (scenario A2) and 0.74 (scenario B2).

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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