首页关于本刊影响因子及获奖投稿须知订阅及广告专辑与专题学术会议绿色发表通道优秀论文 
孟现勇,王浩,雷晓辉,蔡思宇.基于CMDAS驱动SWAT模式的精博河流域水文相关分量模拟、验证及分析.生态学报,2017,37(21):7114~7127 本文二维码信息
二维码(扫一下试试看!)
基于CMDAS驱动SWAT模式的精博河流域水文相关分量模拟、验证及分析
Simulation, validation, and analysis of the Hydrological components of Jing and Bo River Basin based on the SWAT model driven by CMADS
投稿时间:2016-08-23  
DOI: 10.5846/stxb201608231719
关键词CMADS  SWAT  精博河流域  地表分量
Key WordsCMADS  SWAT  Jing and Bo River Basin  surface component
基金项目"南水北调中线干线工程应急运行集散控制技术研究与示范"(2015BAB07B03);国家973计划课题(2013CB036406);北京市科技计划课题(Z141100006014049);2016年度流域水循环模拟与调控国家重点实验室代表性成果培育课题(2016CG05)
作者单位E-mail
孟现勇 中国水利水电科学研究院 流域水循环模拟与调控国家重点实验室, 北京 100038  
王浩 中国水利水电科学研究院 流域水循环模拟与调控国家重点实验室, 北京 100038 wanghao@iwhr.com 
雷晓辉 中国水利水电科学研究院 流域水循环模拟与调控国家重点实验室, 北京 100038  
蔡思宇 中国水利水电科学研究院 流域水循环模拟与调控国家重点实验室, 北京 100038  
摘要点击次数 94
全文下载次数 35
摘要:
利用大气和水文模型定量描述陆表相关变量变化规律一直是大气科学和水文学界的研究热点。然而,由于我国西部地区站点匮乏,传统气象观测站点已不能满足大尺度地表分量高精度模拟分析的需求。建立SWAT模型中国大气同化驱动数据集 (China Meteorological Assimilation Driving Datasets for the SWAT model, CMADS) 驱动SWAT(Soil and Water Assessment Tool) 模型(简称为CMADS+SWAT 模式),选取传统气象站点稀缺的新疆精博河流域为靶区,完成流域各地表分量 (如土壤湿度、雪深、融雪) 校准、验证及其时空关系提取与分析。分析发现:CMADS数据集可很好地驱动、率定SWAT模式完成本地化工作。其中,CMADS+SWAT模式在月尺度上总体NSE效率系数均在0.659-0.942,日尺度也均在0.526-0.815。对流域内土壤湿度和融雪过程进行相关分析发现:精博河流域土壤湿度在年内3-4月份达到其第一次峰值,主要贡献来自于流域内高山融雪现象;融雪期结束后,流域降水量增加,伴随气温上升等现象导致土壤温度呈现波动态势,至10月中旬冷空气过境产生较大降水(雪),最终使土壤水转变为冻土,直至次年接近融雪期,土壤水再次增加直到融雪过程结束。一方面证明CMADS+SWAT模式可有效提高SWAT水文模型在我国西北干旱区(站点稀缺区域)的表现能力,另一方面理清了精博河流域相关地表分量(土壤湿度、蒸发等)时空演变规律。本研究对我国大气水文学科发展将起到一定的科学促进作用。
Abstract:
Describing the changing rules of land surface variables by using meteorological and hydrological models has always been a research hotspot in the fields of atmospheric and hydrological science. However, due to the scarcity of weather stations in West China, traditional weather stations cannot satisfy the requirements of high precision simulation of large scale land surface components. Using the Jing and Bo River Basin in Xinjiang as a research area, the present study used the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) to drive the Soil and Water Assessment Tool (SWAT) model, and then completed calibration, verification, and time-space relation analysis of each land surface component (such as soil moisture content, snow depth, and snow melt). Our analysis showed that the CMADS dataset can drive and calibrate the SWAT mode land complete localization work in Jin and Bo River Basin. The NSE efficiency coefficients of the SWAT model driven by the CMADS dataset were generally controlled between 0.659 and 0.942 at the monthly scale, and were also controlled between 0.526 and 0.815 at the daily scale. Furthermore, our analysis indicated that the soil moisture content would reach a high level for the first time between March and April each year, which is mainly caused by snow melting in the high mountains. However, when snow melting finished, due to an increase in precipitation and temperature, soil temperature fluctuated until the middle of October, when cold air brought considerable precipitation and snow. Finally, soil water was transformed into frozen soil until the snow melting period in the following year. Thereafter, soil water would increase again until the end of the snow melting period. On one hand, this study verified that the CMADS+SWAT mode can enhance the performance ability of the SWAT model in the arid areas of northwestern China, which lacks weather stations. On the other hand, the study provided a scientific explanation for time-space changing rules of land surface components (such as soil moisture and evaporation) in the Jing and Bo River Basin. The findings of this research will play a certain role in promoting the development of China's meteorological and hydrological sciences.
HTML 查看全文   查看/发表评论  下载PDF阅读器

您是本站第 65581716 位访问者

Copyright © 2005-2019   京ICP备06018880号
地址:北京海淀区双清路18号
  邮编:100085    电话:010-62941099
  E-mail : shengtaixuebao@rcees.ac.cn
本系统由北京勤云科技发展有限公司提供技术支持