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http://dx.doi.org/10.11108/kagis.2020.23.2.053

Analysis of National Stream Drying Phenomena using DrySAT-WFT Model: Focusing on Inflow of Dam and Weir Watersheds in 5 River Basins  

LEE, Yong-Gwan (Dept. of Civil, Environmental and Plant Engineering, Graduate School, Konkuk University)
JUNG, Chung-Gil (Forcast and Control Division, Yeongsan River Flood Control Office)
KIM, Won-Jin (Dept. of Civil, Environmental and Plant Engineering, Graduate School, Konkuk University)
KIM, Seong-Joon (School of Civil and Environmental Engineering, Konkuk University)
Publication Information
Journal of the Korean Association of Geographic Information Studies / v.23, no.2, 2020 , pp. 53-69 More about this Journal
Abstract
The increase of the impermeable area due to industrialization and urban development distorts the hydrological circulation system and cause serious stream drying phenomena. In order to manage this, it is necessary to develop a technology for impact assessment of stream drying phenomena, which enables quantitative evaluation and prediction. In this study, the cause of streamflow reduction was assessed for dam and weir watersheds in the five major river basins of South Korea by using distributed hydrological model DrySAT-WFT (Drying Stream Assessment Tool and Water Flow Tracking) and GIS time series data. For the modeling, the 5 influencing factors of stream drying phenomena (soil erosion, forest growth, road-river disconnection, groundwater use, urban development) were selected and prepared as GIS-based time series spatial data from 1976 to 2015. The DrySAT-WFT was calibrated and validated from 2005 to 2015 at 8 multipurpose dam watershed (Chungju, Soyang, Andong, Imha, Hapcheon, Seomjin river, Juam, and Yongdam) and 4 gauging stations (Osucheon, Mihocheon, Maruek, and Chogang) respectively. The calibration results showed that the coefficient of determination (R2) was 0.76 in average (0.66 to 0.84) and the Nash-Sutcliffe model efficiency was 0.62 in average (0.52 to 0.72). Based on the 2010s (2006~2015) weather condition for the whole period, the streamflow impact was estimated by applying GIS data for each decade (1980s: 1976~1985, 1990s: 1986~1995, 2000s: 1996~2005, 2010s: 2006~2015). The results showed that the 2010s averaged-wet streamflow (Q95) showed decrease of 4.1~6.3%, the 2010s averaged-normal streamflow (Q185) showed decreased of 6.7~9.1% and the 2010s averaged-drought streamflow (Q355) showed decrease of 8.4~10.4% compared to 1980s streamflows respectively on the whole. During 1975~2015, the increase of groundwater use covered 40.5% contribution and the next was forest growth with 29.0% contribution among the 5 influencing factors.
Keywords
DrySAT-WFT; Stream drying influence factors; distributed hydrological model; averaged-wet streamflow (Q95); averaged-normal streamflow (Q185); averaged-drought streamflow (Q355);
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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