地球科学进展 ›› 2005, Vol. 20 ›› Issue (5): 499 -504. doi: 10.11867/j.issn.1001-8166.2005.05.0499

研究论文 上一篇    下一篇

DEM空间分辨率的初步分析
郝振纯 1;池宸星 1;王 玲 2;王跃奎 1   
  1. 1.河海大学水文水资源与水利工程科学国家重点实验室,江苏 南京 210098;2.黄河水文水资源科学研究所,河南 郑州 450004
  • 收稿日期:2004-02-24 修回日期:2004-09-10 出版日期:2005-05-25
  • 通讯作者: 郝振纯
  • 基金资助:

    国家自然科学基金重点项目“黄河流域典型支流水循环机理研究”(编号:50239050);治黄专项“黄土高原典型支流小理河流域产流特性变化研究”(编号:2003Z01)资助.

A PRELIMINARY ANALYSIS OF DEM SPACE DATA RESOLUTION

HAO Zhenchun 1; CHI Chenxing 1; WANG Ling 2;WANG Yuekui 1   

  1. (1.State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China; 2.Yellow River Hydrology and Water Resources Institute, Zhengzhou 450004,China)
  • Received:2004-02-24 Revised:2004-09-10 Online:2005-05-25 Published:2005-05-25

分布式模型的输入及其参数具有时空变异性,模型的校正也依赖于网格单元的大小,因此需要确定适当的空间分辨率来描述和控制空间变化。随着分辨率的不同,DEM的精度以及由此提取的流域特征值(如高程、坡度、地形指数、河网长度)在统计特性上也会随之变化。对50 m分辨率的DEM平均取样获得150~950 m的9组DEM,对不同分辨率下提取的流域特征值进行了统计分析,并采用信息熵度量不同分辨率的信息量。

Distributed hydrological model is used to explain the effect of information (such as terrain, soil, vegetation and climate) on every points of the study basin. The inputs and parameters of distributed hydrological model change with space and time. The model's calibration depends on the resolution of grid. In order to describe and control the space change, it is important to make sure right resolution. Distributed hydrological modeling is base on the watershed characteristics extracted from digital elevation model (DEM). Watershed characteristics extracted from different DEM resolution will be statistically different. This paper statistically analyses the watershed character values (such as elevation, gradient, length of watershed network, topographic index) extracted from various resolutions. The concept of entropy has been considered a promising method in this study as it quantitatively measures the information produced by an object (watershed). Large entropy means plenty of information. We find that the coarser the resolution is, the more smoother the terrain is. Mostly, with the DEM grid size increasing, maximal elevation and various of elevation decrease, average elevation and minimal elevation increases; maximal gradient and average gradient and various of gradient decrease; maximal topographic index and various of topographic index decrease; minimal topographic index and average of topographic index increases; length of watershed network decreases. This shows the smoothness effect of resample. With the DEM grid size increasing, entropy becomes smaller and smaller. This means DEM with coarser resolution has less information. Decrease of information is in consistent with change of watershed character values. We compare the relative change of average gradient with relative change of entropy. We find that they have approximately exponential relation. The smoothness of terrain may slower the conflux, but decrease of length of watershed network will shorten conflux time, some analyses of their effects on the velocity of flow have been done.

中图分类号: 

[1] Wang Zhonggen, Liu Changming, Wu Xianfeng. A review of the studies on distributed hydrological model based on DEM[J]. Journal of Natural Resources, 2003, 18(2):168-173. [王中根, 刘昌明, 吴险峰. 基于DEM的分布式水文模型研究综述[J].自然资源学报, 2003, 18(2):168-173.]
[2] Tang Guoan, Zhao Mudan, Li Tianwen, et al. Modeling slope uncertainty derived from DEMs in Loess Plateau[J]. Acta Geographica Sinica, 2003, 58(6):824-830. [汤国安,赵牡丹,李天文,等. DEM提取黄土高原地面坡度的不确定性[J].地理学报, 2003, 58(6):824-830.]
[3] Zhang Yong, Tang Guoan, Peng Qi. A mathematical simulation of DEM terrain representation error—A case study in the Loess Hill-gully areas of China [J]. Journal of Mountain Science, 2003, 21(2):252-256. [张勇, 汤国安, 彭奇. 数字高程模型地形描述误差的量化模拟——以黄土丘陵沟壑区的实验为例[J]. 山地学报, 2003, 21(2):252-256.]
[4] Chen Rensheng, Kang Ersi, Yang Jianping. Application of Topmodel to simulate runoff from Heihe mainstream mountainous basin[J]. Journal of Desert Research, 2003, 23(4):428-434. [陈仁升, 康尔泗, 杨建平,等. Topmodel模型在黑河干流出山径流模拟中的应用[J]. 中国沙漠, 2003, 23(4):428-434.] 
[5] Georges-Marie Saulnier. Digital elevation analysis for distributed hydrological modeling: Reducing scale dependence in effective hydraulic conductivity value[J]. Water Resources Research, 1997, 33(9): 2 097-2 101.
[6] David M Wolock,Curtis V Price. Effects of digital elevation model map scale and data resolution on a topography-based watershed model[J].Water Resources Research, 1994, 30(11): 3 041-3 052.
[7] Baxter E Vieux. Distributed Hydrologic Modeling Using GIS[M]. Netherlands: Kluwer Academic Publishers, 2001.
[8] Wang Junde. Statistic of Hydrology[M]. Nanjing: Hehai Unversity Press,1993.[王俊德. 水文统计[M] .南京:河海大学出版社, 1993.]
[9] Hou Ruzhen, Zheng Kesheng. A theoretical study of raingauge network evaluation using information entropy[J]. Journal of Taiwan Water Conservancy, 2003,51(2):10-20. [侯如真, 郑克声. 讯息熵应用于雨量站网评估之理论探讨[J]. 台湾水利, 2003, 51(2):10-20.]
[10] Chen Zhihua, Ding Guoping. Entropy-based approach to remove  redundant monitoring wells in regional-scale groundwater system in Hebei plain, China[J].Earth Science—Journal of China University of Geosciences,2001,26(5):517-523.[陈植华, 丁国平. 应用信息熵方法对区域地下水观测网的优化研究[J]. 中国地质大学学报, 2001 , 26(5):517-523.]
[11] Wang Dong, Zhu Yuansheng. Principle of maximum entropy and its application in hydrology and water resources[J]. Advances in Water Science, 2001, 12(3):424-430.[王栋, 朱元甡. 最大熵原理在水文水资源科学中的应用[J]. 水科学进展, 2001, 12(3): 424-430.]
[12] Zhang Jiguo, Liu Xinren. Information entropy analysis on nonuniformity of precipitation distribution in time-space, I, basic concept and data analysis[J]. Advances in Water Science, 2000, 11(2):133-137.[张继国, 刘新仁. 降水时空分布不均匀性的信息熵分析(I)——基本概念与数据分析[J].水科学进展, 2000, 11(2): 133-137.]
[13] Nilgun B Harmancioglu, Necdet Alpaslan. Water quality monitoring network design:A problem of multi-objective decision making[J]. Water Resources Bulletin,  1992,  28(1): 179-192.
[14] Sevinc Ozkul,Nilgun B Harmnaciou, Vijay P Singh. Entropy-based assessment of water quality monitoring networks[J].Journal of Hydrologic Engineering,  2000,  5(1): 90-100.
[15] Zhang Xuewen. Entropy of physical field and iIts self-minish[J]. Journal of Natural, 1986, 9(11):847-850.[张学文. 物理场的熵及其自发减小现象[J]. 自然杂志, 1986, 9(11):847-850.]

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