Scale effect of airborne LiDAR DEM in watershed hydrological analysis and simulation

doi:10.13474/j.cnki.11-2246.2020.0109

Abstract

Abstract: DEM data is the basis for watershed hydrological analysis and simulation. The results of hydrological analysis and simulation have been impacted profoundly by different resolution scale of DEM. Based on the DEM data acquired by airborne LiDAR, the discrepancies resulted from different resolution DEM in slope extraction and hydrological index analysis are analyzed. And the SWAT distributed hydrological model is used to simulate and analyze the hydrological effects of DEM data with different resolutions. The research shows that, with the decrease of the DEM resolution, the slope and the mean SPI reduced, the mean TWI increased. The mean LSF increases first and then decreases, the maximum LSF is at 10 m resolution. The SWAT model simulation results indicate that, with the lower resolution and the smaller value of the slope, TWI becomes larger, evapotranspiration increases, surface runoff depth reduces while the amount of soil leakage and underground runoff is first decrease and then increase, same as LSF, 10 m is the extreme point.

Key words: LiDAR, DEM, scale effect, hydrological analysis, SWAT model

CLC Number:

P237

LAN Jinjing, YU Haiyang, CHEN Lin, MA Huihui, ZHANG Huiyong. Scale effect of airborne LiDAR DEM in watershed hydrological analysis and simulation[J]. Bulletin of Surveying and Mapping, 2020, 0(4): 40-46.

References

[1] REDDY A S, REDDY M J. Evaluating the influence of spatial resolutions of DEM on watershed runoff and sediment yield using SWAT[J]. Journal of Earth System Science, 2015, 124(7):1517-1529.
[2] 刘远, 周买春, 陈芷菁, 等. 基于不同DEM数据源的数字河网提取对比分析——以韩江流域为例[J]. 地理科学, 2012,32(9):1112-1118.
[3] THOMAS I A, JORDAN P, MELLANDER P E, et al. Improving the identification of hydrologically sensitive areas using LiDAR DEMs for the delineation and mitigation of critical source areas of diffuse pollution[J]. Science of the Total Environment, 2016,556(1):276-290.
[4] ZHANG P, LIU R, BAO Y, et al. Uncertainty of SWAT model at different DEM resolutions in a large mountainous watershed[J]. Water Research, 2014, 53(1):132-144.
[5] 陶旸,汤国安,王春,等. DEM地形信息量计算的不确定性研究[J]. 地理科学, 2010,30(3):398-402.
[6] WU S, LI J, HUANG G H. Characterization and evaluation of elevation data uncertainty in water resources modeling with GIS[J]. Water Resour Manage, 2008, 22(8):959-972.
[7] 鲍伟佳,程先富,陈旭东. DEM水平分辨率对流域特征提取的影响分析[J]. 水土保持研究, 2011,18(2):129-132.
[8] SULIMAN A H A, KATIMON A, DARUS I Z M, et al. Topmodel for streamflow simulation of a tropical catchment using different resolutions of ASTER DEM:optimization through response surface methodology[J]. Water Resources Management, 2016, 30(9):3159-3173.
[9] WANG X Y, LIN Q. Effect of DEM mesh size on Ann-AGNPS simulation and slope correction[J]. Environ Monit Assess, 2011,179(1-4):267-277.
[10] DIXON B E J. Resample or not effects of resolution of DEMs in watershed modeling[J]. Hydrol Process, 2009, 23(12):1714-1724.
[11] 于海洋,卢小平,程钢,等. 基于LiDAR数据的流域水系网络提取方法研究[J]. 地理与地理信息科学, 2013,29(1):17-21.
[12] 胡卓玮,李洋,王志恒.基于DEM的四川省低山丘陵区坡度提取不确定性分析[J].山地学报, 2012,30(5):636-640.
[13] 于海洋,罗玲,马慧慧,等. SRTM(1″)DEM在流域水文分析中的适用性研究[J]. 国土资源遥感, 2017,29(2):138-143
[14] SINNATHAMBY S, DOUGLAS-MANKIN K R, CRAIGE C. Field-scale calibration of crop-yield parameters in the soil and water assessment tool (SWAT)[J]. Agricultural Water Management, 2017, 180(2):61-69.
[15] 闫强,廖静娟,沈国状. 近40年乌兰乌拉湖变化的遥感分析与水文模型模拟[J]. 国土资源遥感, 2014,26(1):152-157.
[16] GONG Jianya. Photogrammetry and deep learning[J]. Journal of Geodesy and Geoinformation Science, 2018, 1(1):1-15.