Calculating Time-Specific Flux of Runoff Using DEM Considering Storm Sewer Collection Systems
Publication: Journal of Hydrologic Engineering
Volume 22, Issue 2
Abstract
A new technique is proposed for calculating time-specific accumulative flux of surface runoff from a digital elevation model (DEM). The method incorporates ancillary datasets required to determine the depth of effective rainfall and a priori information on surface and underground storm sewer collection systems, permitting grid-based hydrologic analysis using a DEM. The diffusion wave equation is used to analyze temporal changes in surface runoff variables such as flow depth and velocity. Therefore, time-specific accumulative flux of surface runoff for each DEM cell, and for inlets and outfalls of the storm sewer collection systems, can be calculated and used to simulate the propagation of flood waves around storm sewers. The technique was applied to the Sangdong tailings dam in Korea that has both surface drainage and storm sewers. The proposed technique provides better time-specific hydrologic information on watersheds that contain both surface and underground storm sewer collection systems, which is omitted by the EPA’s Storm Water Management Model (SWMM) and the ArcGIS Hydrology toolset.
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Acknowledgments
This work was supported by the Mine Reclamation Technology Development Project funded by the MIRECO, the Brain Korea 21 Project, the Research Institute of Energy and Resources, Seoul National University, and the Basic Science Research Program through the National Research Foundation (NRF) funded by the Ministry of Education (2015R1D1A1A01061290), Korea. The authors thank anonymous reviewers for their critical comments and suggestions, which greatly improved the quality of our manuscript.
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Published In
Journal of Hydrologic Engineering
Volume 22 • Issue 2 • February 2017
Copyright
© 2016 American Society of Civil Engineers.
History
Received: Feb 3, 2016
Accepted: Jul 20, 2016
Published online: Aug 30, 2016
Discussion open until: Jan 30, 2017
Published in print: Feb 1, 2017
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