东江流域分布式降水径流模拟研究
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摘要
基于东江博罗站上游区域的数字高程模型(DEM)数据,提取了数字河网水系与流域边界,构建了基于DEM的分布式水文模型DDRM(DEM-based Distributed Rainfall-Runoff Model)并模拟了博罗站1980—2005年降水径流过程。采用Nash效率系数、径流深相对误差对DDRM模型的径流模拟效果进行了评价,并与新安江模型的模拟效果进行对比分析。结果表明:DDRM模型和新安江模型在东江流域降水径流模拟中均取得了较好的模拟效果。整体而言,两个模型的模拟效果相当;在洪水量级模拟方面,DDRM模型优于新安江模型。与新安江模型相比,DDRM模型具有结构简单、参数较少的优点,且能模拟径流量的空间分布。
Based on the digital elevation model( DEM) data from the Boluo upstream region in Dongjiang Basin, the river network was extracted, and the basin boundary was delineated. A DEM-based distributed rainfall-runoff model( DDRM) was built to simulate the streamflow series of Boluo gauge during the period between 1980 and 2005. The simulation performance of DDRM was compared to that of the Xin anjiang model( XAJ) in terms of the Nash-Schutcliffe coefficient of efficiency and the relative error of runoff depth.The results show that both DDRM and XAJ can achieve a satisfactory simulation performance. DDRM shows similar simulation performance with XAJ with regards to the Nash-Schutcliffe coefficient of efficiency and advantages in simulating peak flow over XAJ. Compared to XAJ, DDRM is simpler in structure, more parsimonious in parameters, and able to simulate the spatial distribution of runoff.
Based on the digital elevation model( DEM) data from the Boluo upstream region in Dongjiang Basin, the river network was extracted, and the basin boundary was delineated. A DEM-based distributed rainfall-runoff model( DDRM) was built to simulate the streamflow series of Boluo gauge during the period between 1980 and 2005. The simulation performance of DDRM was compared to that of the Xin anjiang model( XAJ) in terms of the Nash-Schutcliffe coefficient of efficiency and the relative error of runoff depth.The results show that both DDRM and XAJ can achieve a satisfactory simulation performance. DDRM shows similar simulation performance with XAJ with regards to the Nash-Schutcliffe coefficient of efficiency and advantages in simulating peak flow over XAJ. Compared to XAJ, DDRM is simpler in structure, more parsimonious in parameters, and able to simulate the spatial distribution of runoff.
引文
[1]徐宗学.水文模型[M].北京:科学出版社,2009.
[2]熊立华,郭生练.分布式流域水文模型[M].北京:中国水利水电出版社,2004.
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[4]龙海峰,熊立华,万民.基于DEM的分布式水文模型在清江流域的应用[J].长江流域资源与环境,2012,21(1):71-78.
[5]万民,熊立华,董磊华.飞来峡流域基于栅格DEM的分布式水文模拟[J].武汉大学学报(工学版),2010,43(5):549-553.
[6]XIONG L,YANG H,ZENG L. Evaluating Consistency between the Remotely Sensed Soil Moisture and the Hydrological Model-Simulated Soil Moisture in the Qujiang Catchment of China[J]. Water,2018,10(3):291.
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[10]何艳虎,陈晓宏,林凯荣,等.东江流域近50年旱涝时空演变特征[J].地理科学,2014(11):1391-1398.
[11]杨宏伟. GIS支持下的东江典型流域径流变化研究[D].南京:南京大学,2009.
[12]万民,熊立华,卫晓婧.数字高程模型预处理方法的研究进展[J].水文,2008,28(5):11-17.
[13]熊立华,郭生练.基于DEM的数字河网生成方法的探讨[J].长江科学院院报,2003,20(4):14-17.
[14]熊立华,万民.基于数字高程模型的河道分级与节点编码[J].长江科学院院报,2007,24(1):23-26.
[15]熊立华,郭生练,KDNNOR K M O.利用DEM提取地貌指数的方法述评[J].水科学进展,2002(06):775-780.
[16]解河海,黄国如.地形指数若干计算方法探讨[J].河海大学学报(自然科学版),2006,34(1):46-50.
[17]SHEPARD D. A two-dimensional interpolation function for irregularly-spaced data[C]. Proceedings of the 1968 23rd ACM national conference,1968:517-524.
[18]BLANEY H F,CRIDDLE W D. Determining water requirements in irrigated areas from climatological and irrigation data[M]. Washington,1950.
[19]DUAN Q,SOROOSHIAN S,GUPTA V. Effective and efficient global optimization for conceptual rainfall-runoff models[J]. Water Resources Research,1992,28(4):1015-1031.
[20]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.
[2]熊立华,郭生练.分布式流域水文模型[M].北京:中国水利水电出版社,2004.
[3]熊立华,郭生练,田向荣.基于DEM的分布式流域水文模型及应用[J].水科学进展,2004,15(4):517-520.
[4]龙海峰,熊立华,万民.基于DEM的分布式水文模型在清江流域的应用[J].长江流域资源与环境,2012,21(1):71-78.
[5]万民,熊立华,董磊华.飞来峡流域基于栅格DEM的分布式水文模拟[J].武汉大学学报(工学版),2010,43(5):549-553.
[6]XIONG L,YANG H,ZENG L. Evaluating Consistency between the Remotely Sensed Soil Moisture and the Hydrological Model-Simulated Soil Moisture in the Qujiang Catchment of China[J]. Water,2018,10(3):291.
[7]赵人俊.流域水文模拟:新安江模型与陕北模型[M].北京:水利电力出版社,1984.
[8]BEVEN K J. Distributed Hydrological Modeling:Application of the TOPMODEL Concept[M]. New York:John Wiley&Sons Limited,1997.
[9]涂新军,陈晓宏,张强,等.东江径流年内分配特征及影响因素贡献分解[J].水科学进展,2012(04):493-501.
[10]何艳虎,陈晓宏,林凯荣,等.东江流域近50年旱涝时空演变特征[J].地理科学,2014(11):1391-1398.
[11]杨宏伟. GIS支持下的东江典型流域径流变化研究[D].南京:南京大学,2009.
[12]万民,熊立华,卫晓婧.数字高程模型预处理方法的研究进展[J].水文,2008,28(5):11-17.
[13]熊立华,郭生练.基于DEM的数字河网生成方法的探讨[J].长江科学院院报,2003,20(4):14-17.
[14]熊立华,万民.基于数字高程模型的河道分级与节点编码[J].长江科学院院报,2007,24(1):23-26.
[15]熊立华,郭生练,KDNNOR K M O.利用DEM提取地貌指数的方法述评[J].水科学进展,2002(06):775-780.
[16]解河海,黄国如.地形指数若干计算方法探讨[J].河海大学学报(自然科学版),2006,34(1):46-50.
[17]SHEPARD D. A two-dimensional interpolation function for irregularly-spaced data[C]. Proceedings of the 1968 23rd ACM national conference,1968:517-524.
[18]BLANEY H F,CRIDDLE W D. Determining water requirements in irrigated areas from climatological and irrigation data[M]. Washington,1950.
[19]DUAN Q,SOROOSHIAN S,GUPTA V. Effective and efficient global optimization for conceptual rainfall-runoff models[J]. Water Resources Research,1992,28(4):1015-1031.
[20]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.