王斌,朱士江,黄金柏,丁星臣,宫兴龙,王贵作.基于全球陆面数据同化系统蒸散量的GSAC模型率定[J].农业机械学报,2018,49(2):232-240.
WANG Bin,ZHU Shijiang,HUANG Jinbai,DING Xingchen,GONG Xinglong,WANG Guizuo.GSAC Model Calibration Based on Evapotranspiration Data from Global Land Data Assimilation System[J].Transactions of the Chinese Society for Agricultural Machinery,2018,49(2):232-240.
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基于全球陆面数据同化系统蒸散量的GSAC模型率定   [下载全文]
GSAC Model Calibration Based on Evapotranspiration Data from Global Land Data Assimilation System   [Download Pdf][in English]
投稿时间:2017-07-08  
DOI:10.6041/j.issn.1000-1298.2018.02.030
中文关键词:  水文模型率定  GSAC模型  GLDAS  蒸散量  呼兰河流域
基金项目:国家重点研发计划项目(2016YFC0400101)、国家自然科学基金项目(51009026、41271046)和农业部农业水资源高效利用重点实验室开放课题项目(2015002)
作者单位
王斌 东北农业大学 
朱士江 三峡大学 
黄金柏 扬州大学 
丁星臣 东北农业大学 
宫兴龙 东北农业大学 
王贵作 水利部发展研究中心 
中文摘要:在识别缺资料流域水文模型参数时,目前常采用的区域化方法存在相似流域间降雨径流关系差别较大、模型参数与流域属性间的相关性不明显、在大范围缺资料地区难于选取参考流域等问题。本文从全球陆面数据同化系统(GLDAS)获取流域蒸散量数据,提出利用GLDAS蒸散量率定GSAC模型的方法。首先,通过合并网格建立GSAC模型模拟的蒸散量与GLDAS蒸散量在时间和空间方面的对应关系;其次,基于纳什效率系数的定义构建了一个模型率定指标,以评价GSAC模型模拟的蒸散量对GLDAS蒸散量的拟合效果;最后,依据GLDAS蒸散量与GSAC模型模拟蒸散量之间的拟合关系率定GSAC模型。呼兰河流域应用结果表明,GLDAS提供的蒸散量能够较好反映流域实际蒸散量的变化情况,为率定GSAC模型提供了一种有效的输入数据;在率定期与验证期,利用GLDAS蒸散量率定的GSAC模型对流量模拟的纳什效率系数分别为0.81和 0.77,与利用流量数据率定的GSAC模型模拟结果相近。
WANG Bin  ZHU Shijiang  HUANG Jinbai  DING Xingchen  GONG Xinglong  WANG Guizuo
Northeast Agricultural University,Three Gorges University,Yangzhou University,Northeast Agricultural University,Northeast Agricultural University and Development Research Center, Ministry of Water Resources
Key Words:hydrological model calibration  grid-based Sacramento model  global land data assimilation system  evapotranspiration  Hulan River Basin
Abstract:Since International Association of Hydrological Science (IAHS) initiated the prediction in ungauged basin (PUB) programe, the regionalization has become a common method for identifying hydrological model parameters in ungauged basins. However, some problems exist in the regionalization method, which was commonly used for parameter identification of hydrological model in ungauged basins, such as different relationships between rainfall and runoff in similar basin, unobvious correlation between hydrological model parameters and basin characteristics, and difficult to select a reference basin in wide range of data-deficient areas, etc. It is significant to study the method of calibrating hydrological model by using the data outside the stream flow. A method was presented to calibrate the parameters of grid-based Sacramento (GSAC) model by using evapotranspiration (ET) data from global land data assimilation system (GLDAS). Firstly, a spatiotemporal-grid corresponding relationship between GLDAS ET and ET simulated by GSAC model was established. Secondly, a evaluation index based on Nash-Sutcliffe efficiency coefficient was constructed to measure the fitting effect between GLDAS ET and ET simulated by GSAC model on 0.25° grid. Finally, validation of GSAC model was carried out based on the GLDAS ET. The results of application in the Hulan River Basin indicated that GLDAS ET can better simulate the actual ET of the Hulan River Basin so that provided a useful input data for calibrating parameters of GSAC;the runoff Nash-Sutcliffe efficiency coefficient of GSAC model calibrated by GLDAS ET were 0.81 and 0.77 in the calibration and validation periods, respectively, and the results were similar to the corresponding values of GSAC model calibrated by runoff data.

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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