Status: this discussion paper is a preprint. It has been under review for the journal Hydrology and Earth System Sciences (HESS). The manuscript was not accepted for further review after discussion.
An advanced distributed automated extraction of drainage network model on high-resolution DEM
Y. Mao,A. Ye,J. Xu,F. Ma,X. Deng,C. Miao,W. Gong,and Z. Di
Abstract. A high-resolution and high-accuracy drainage network map is a prerequisite for simulating the water cycle in land surface hydrological models. The objective of this study was to develop a new automated extraction of drainage network model, which can get high-precision continuous drainage network on high-resolution DEM (Digital Elevation Model). The high-resolution DEM need too much computer resources to extract drainage network. The conventional GIS method often can not complete to calculate on high-resolution DEM of big basins, because the number of grids is too large. In order to decrease the computation time, an advanced distributed automated extraction of drainage network model (Adam) was proposed in the study. The Adam model has two features: (1) searching upward from outlet of basin instead of sink filling, (2) dividing sub-basins on low-resolution DEM, and then extracting drainage network on sub-basins of high-resolution DEM.
The case study used elevation data of the Shuttle Radar Topography Mission (SRTM) at 3 arc-second resolution in Zhujiang River basin, China. The results show Adam model can dramatically reduce the computation time. The extracting drainage network was continuous and more accurate than HydroSHEDS (Hydrological data and maps based on Shuttle Elevation Derivatives at multiple Scales).
Received: 02 Jun 2014 – Discussion started: 03 Jul 2014
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State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, and Joint Center for Global Change Studies, Beijing, 100875, China
State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, and Joint Center for Global Change Studies, Beijing, 100875, China
J. Xu
State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, and Joint Center for Global Change Studies, Beijing, 100875, China
F. Ma
State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, and Joint Center for Global Change Studies, Beijing, 100875, China
X. Deng
State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, and Joint Center for Global Change Studies, Beijing, 100875, China
C. Miao
State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, and Joint Center for Global Change Studies, Beijing, 100875, China
State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, and Joint Center for Global Change Studies, Beijing, 100875, China
Z. Di
State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, and Joint Center for Global Change Studies, Beijing, 100875, China