ENGLISH

MOVEMENTS OF A DISTRIBUTED HYDROLOGY MODEL DHSVM

Source:

AND ITS CLIMATOLOGICAL HYDROLOGICAL OFFLINE SIMULATIONAL EXPERIMENTS

WANG Shourong（王守荣），

        National Climate Center, Beijing 100081, China

        HUANG Ronghui（黄荣辉），

        Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100080, China

        DING Yihui（丁一汇），

        National Climate Center, Beijing 100081, China

        LEUNG， L.R., WIGMOSTA, M.S. and VAIL, L. W.

        Pacific Northwest National Laboratory, Richland, Washington 99352, USA

        Received August 25, 2001; revised May 27, 2002

        ABSTRACT

        The advanced distributed hydrology-soil-vegetation model DHSVM, developed by Wigmosta et al. (1994) is introduced from US Pacific Northwest National Laboratory. To apply DHSVM in China for the first time some improvements have been made in terms of the basin characteristics: 1) to change evapotranspiration model, using the improved PenmanMonteith approach in place of the original one; 2) to change the model structure, inserting datasets from 4 stations to grid cells for each river basin, instead of datasets from one or two stations; 3) to develop new hydrology, vegetation and soil parameterization schemes for improving the simulated results, with focus on calculation and adjustment of 11 parameters, such as soil porosity φ, field capacity θfc, leaf area index LAI, stochastic resistance γs, among the total 33 parameters. Then the improved DHSVM is driven by observed datasets for Luanhe River Basin and Sanggan River Basin, respectively. The simulated evapotranspiration (ET), runoff, snow water equivalent, water table, soil moisture and percolation are then gained as DHSVM outputs. The simulated ET shows that the highest peak appears in May or June instead of July or August. This is consistent with the real situations, owing to the improvement of ET model. The simulated runoff process and flood peak are quite consistent with the observed ones. The model efficiency values for Luanhe River and Sanggan River Basins are 0.89 and 0.82, respectively, which shows high simulating ability of the model system for both relatively humid and dry basins.

        Key words: improvements of hydrology model, offline simulation tests, hydrologic modeling efficiency

        Editor-in-Chief: Zhou Xiuji (周秀骥)

        EDITORIAL COMMITTEE OF AMS

        Chairman

        Zhou Xiuji (周秀骥): CAMS

        ViceChairmen

        Ding Yihui (丁一汇): National Climate Center, Beijing 100081, China

        Ji Liren (纪立人)： IAP CAS

        Wang Shaowu (王绍武): DG PU Standing Members et al. 31 altogather.

        此外还聘请了一些国际知名的大气科学家为国外编委。

        Foreign Members

        Anthes, Richard A.: UCAR, Boulder, CO 80307 3000, USA

        Chameides, William L.: School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA 30332 0340, USA

        Lau, William K. M.: NASA, Goddard Space Flight Center, Mail Code 913, Greenbelt, MD 20771, USA

        Liu Shaw C.: Aeronomy Laboratory NOAA/ERL, 325 Broadway, Boulder, CO 80303 3328, USA

        Longhetto, A.: Consiglio Nazionale delle Ricerche Istituto di Cosmo Geofisica, 10133 Torino, Italy

        Serafin, Robert J.: NCAR, Boulder, CO80307-3000, USA

        Tanaka, M.: Upper NCAR,　Boulder, CO 803073000, USA Atmosphere Research Laboratory, Faculty of Science Tohoku University, Sendai, Japan

        Wang Bin: Department of Meteorology, University of Hawaii at Manoa, Honolulu, HI 96822 USA

        Wang Wei-Chyung: Atmospheric Sciences Research Center, State University of New York at Albany, 100 Fuller Road, Albany, NY 12205, USA

        Yasunari T.: Institute of Geoscience, University of Tsukuba, Ibaraki 305, Japan

        Zhang Da-Lin: Dept. of Meteorology 2423 computer& Space Science Bldg Univ. of Maryland College Park, Maryland, 20742-2425, USA

        According to the statistics of nearly thousand of articles published in the past volumes, the percentage of every division of atmospheric sciences can be listed as follows:

        Synoptic Meteorology， 27%

        Analysis of Weather systems，Atmospheric circulation, monsoon and LFO， Tropical meteorology， Typhoon ， Tibetan plateau & polar meteorology， Satellite & Radar meteorology

        Climatology，22%

        Climatological statistics， ENSO & Air-Sea Interation and Climatic Teleconnection， Physical climatology & climate modeling ， Climate change & historical climatology，

        Dynamics & Thermodynamics of the Atmosphere， 18%

        Thermodynamics of the Atmosphere，Dynamics of the Atmosphere，Atmospheric nonlinear dynamics， Atmospheric waves

        Atmospheric Physics，15%

        Atmospheric probing & Equipment， Boundary layer meteorology，Cloud & precipitation physics，Radiation，Atmospheric electricity

        Weather Forecasting & Modification，10%

        Atmospheric modeling，General method & application of NWP，Atmospheric experiment， Weather forecasting using synoptic method, & statistical forecasting， Weather modification

        Atmospheric Chemistry，5%

        Applied Meteorology，3%

        Agricultural meteorology， Marine meteorology

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