Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Assessment of Metals Loading in an Acid Mine Drainage Watershed

Authors
Pak, GijungJung, MinjaeKim, HwansukMallari, Kristine Joy B.Chung, GunhuiKim, SungpyoKim, YoungOa, SeongwookYoon, Jaeyoung
Issue Date
Mar-2016
Publisher
SPRINGER HEIDELBERG
Keywords
Hydrology; Metals; WARMF model
Citation
MINE WATER AND THE ENVIRONMENT, v.35, no.1, pp.44 - 54
Indexed
SCIE
SCOPUS
Journal Title
MINE WATER AND THE ENVIRONMENT
Volume
35
Number
1
Start Page
44
End Page
54
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/89442
DOI
10.1007/s10230-015-0336-6
ISSN
1025-9112
Abstract
Watershed-scale modeling can be useful in identifying the main environmental factors and the physical mechanisms responsible for acid mine drainage (AMD) formation, attenuation, and impacts. Since flow rates and water quality of the AMD and receiving streams are related to the rainfall-runoff relationship and associated contaminant dissolution, we thought that hydrologic analysis of the mined area and surrounding drainage basin should be the starting point in documenting the source and fate of AMD contaminants. Further modeling of AMD pollutants could then be performed in terms of metal concentrations and loading at the watershed scale. In this study, monitoring was conducted in the Geopung mine watershed; the watershed analysis risk management framework (WARMF) model was used to evaluate the effect of AMD contributions to downstream metal concentrations. The hydrologic model of the basin was calibrated and verified with rainfall and streamflow data, and the water quality model was calibrated for the dissolved concentrations of metals (Cd, Cu, Zn, and Pb), using discharge data gathered in 2009. There was a strong correlation (r = 0.93) between the observed and simulated runoff values plus high Nash-Sutcliffe model efficiency (NSE = 0.89) and low average percent difference between predicted and measured values (%Diff = 0.46). Subsequent model validation using data gathered in 2010 also showed good agreement (%Diff = 9.76; NSE = 0.77; r = 0.91) between the observed and simulated values. For the metals, the model was calibrated using data from 2010; the correlation between the observed and simulated values was quite good (r = 0.80-0.41).
Files in This Item
There are no files associated with this item.
Appears in
Collections
Graduate School > Department of Environmental Engineering > 1. Journal Articles
College of Science and Technology > Department of Environmental Engineering > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Kim, Young photo

Kim, Young
College of Science and Technology (Department of Environmental Engineering)
Read more

Altmetrics

Total Views & Downloads

BROWSE