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多源DEM数据在山区流域河网提取中的对比

Comparison of Multi-source DEM Data in River Network Extraction in Mountain Watershed

  • 摘要: 针对何种DEM数据更适合山区流域的河网提取,选择长江上游与珠江上游的山区流域,以ALOS 12.5 m DEM、ASTER 30 m GDEM与SRTM 90 m DEM为基础数据,基于Arcpy提取研究区域河网,通过河网套合差、Arc Hydro Tools对提取结果进行修正与评价,探讨山区流域最佳集水面积阈值的选择与地形特征对数字河网提取的影响。结果表明:(1)分辨率为12.5 m的ALOS DEM河网套合差最小,能更真实地反映山区流域的水系发育程度;(2)通过Arc Hydro Tools修正DEM数据,3种DEM的河网套合差均减小,可明显提高河网的提取精度;(3)基于均值变点分析法确定研究区最佳集水面积阈值,ALOS DEM的最佳集水面积阈值为20 000,ASTER GDEM与SRTM DEM为500;(4)大起伏山地有利于河网的提取,ALOS DEM提取效果最佳。因此,经过修正的ALOS DEM提取流域水系效果最佳,成果可为山区流域提取水系提供一定的参考和借鉴。

     

    Abstract: To determine which DEM data are more suitable for river network extraction in mountainous river basins, this paper selects mountainous river basins in the upper reaches of Yangtze River and Pearl River, including the Liqiu River Basin, the Zagunao River Basin, the Heshui River Basin, the Gantangjiang River Basin, and the Lijiang River Basin above the Darongjiang River Hydrological Station, and uses ALOS 12.5 m DEM, ASTER 30 m GDEM and SRTM 90 m DEM as the base data. The extraction of the river network in the study area is based on Arcpy, and the extraction results are corrected and evaluated by the river network ensemble difference and Arc Hydro Tools to explore the influence of the selection of the optimal catchment area threshold and topographic features on the extraction of the digital river network in mountainous watersheds. The results show that:(1) ALOS DEM with 12.5 m resolution has the smallest river network ensemble difference, which can reflect the degree of water system development in the mountainous watersheds more realistically, and the river network ensemble differences of ALOS DEM in the Liqiu River Basin, the Zagunao River Basin, the Heshui River Basin, the Gantangjiang River Basin and the Lijiang River Basin above the Darongjiang River Hydrological Station are 0.380%, 0.275%, 0.312%, 1.374% and 0.873%.(2) By correcting the DEM data with Arc Hydro Tools, the river network ensemble differences of the three DEMs are reduced, which can significantly improve the extraction accuracy of the river network, and the extraction effect of ALOS DEM before and after correction is optimal and applicable to different river basins. The SRTM 90 m DEM is still better than the ASTER 30 m GDEM in the upper Li River Basin and the Li River Basin after correction, while the accuracy of the ASTER 30 m GDEM is higher in the Zaguzhong River Basin, the Heshui River Basin and the Gantang River Basin after correction;(3) the coefficient of determination of the SRTM DEM is 0.930 2 in the upper Li River(the Li River basin above the Da Sol River Hydrological Station), and the coefficient of determination of the ALOS DEM in the Zaguzhong River Basin is 0.985 4. The coefficient of determination for the rest of the conditions is more than 0.99, which indicates that the correlation is good.Based on the mean-variable point analysis method to determine the best catchment area threshold for the study area, the best catchment area threshold is 20 000 for ALOS DEM and 500 for ASTER GDEM and SRTM DEM;(4) The large undulating hills are favorable for river network extraction, and the DEM correction converts some watersheds into large undulating hills favorable for river network extraction, and the ALOS DEM has the best extraction effect. Therefore, the modified ALOS DEM extracts the watershed water system with the best effect, and the results can provide some reference for the extraction of water system in mountainous watersheds.

     

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