An Artificial Stream Network and Its Application on Exploring the Effect of DEM Resolution on Hydrological Parameters

Conference paper (2018)

Authors

H. Liu OLD Department of GIS Technology
Research Group
Environmental Technology and Design (Architecture and the Built Environment) (TU Delft)
Copyright: © 2018 H. Liu
DOI: https://doi.org/10.1007/978-3-319-78208-9_4
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Published Date

2018

Language

English

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Faculty

Architecture and the Built Environment

Department

Urbanism

Research Group

Environmental Technology and Design

Abstract

Digital elevation models (DEM) are widely used in various distributed
hydrological models. The stream network can be extracted from it so that
runoff routing can be calculated. With the advent of remote sensing and
computing technologies, the computation based on DEM with high
resolution becomes possible. However, there still exist regions with
poor resolution, particularly in developing countries. Previous work
only conducted comparisons between results by implementing hydrological
models for specific basins in the real world and resolutions were only
assigned to several fixed values, such as 30 and 90 m. So, the results
derived were thus not in a general sense. To roughly understand how DEM
resolution influences the hydrologic response, in this paper, first an
artificial stream network of which the principle is originated from
fractal theory is constructed. Then by implementing calculation on such
artificial networks in an iterative way and performing aggregation, the
influence of DEM resolution on several hydrological parameters, namely,
the number of basins, drainage density of all basins, total stream
length, average stream slope and average topographic index used to
assess the spatial distribution of soil saturation of the largest basin
can thus be acquired. It is found that DEMs of low resolution would
reduce drainage density, total stream length and average stream slope,
but would increase topographic index. But the effect is insignificant
regarding the number of basins. In the end, the results of the
simulation as well as the quality of the fractal terrain are validated
by referencing field data.