气候变化领域集成服务门户(CCPortal): Projection of runoff and sediment yield under coordinated climate change and urbanization scenarios in Doam dam watershed; Korea

CCPortal

DOI	10.2166/wcc.2016.068
	Projection of runoff and sediment yield under coordinated climate change and urbanization scenarios in Doam dam watershed; Korea
	Kim Y.D.; Kim J.M.; Kang B.
发表日期	2017
ISSN	20402244
起始页码	235
结束页码	253
卷号	8 期号:2
英文摘要	A hydro-environmental model chain in the Doam dam basin, Korea, was developed for an impact assessment under the Intergovernmental Panel on Climate Change’s A1B scenario. The feasible downscaling scheme composed of an artificial neural network (ANN) and non-stationary quantile mapping was applied to the GCM (Global Climate Model) output. The impacts under climate and land use change scenarios were examined and projected using the Soil and Water Assessment Tool (SWAT) model. The daily SWAT model was calibrated and validated for 2003–2004 and 2006–2008, respectively. Meanwhile the monthly SS (suspended solids) was calibrated and validated for 1999–2001 and 2007–2009, respectively. The simulation results illustrated that under the assumption of 1–5% urbanization of the forest area, the hydrologic impact is relatively negligible and the climate change impacts are dominant over the urbanization impacts. Additionally the partial impacts of land use changes were analyzed under five different scenarios: partial change of forest to urban (PCFUr), to bare field, to grassland, to upland crop (PCFUp), and to agriculture (PCFA). The analysis of the runoff change shows the highest rate of increase, 73.57% in April, for the PCFUp scenario. The second and third highest rate increases, 37.83% and 31.45% in May, occurred under the PCFA and PCFUr scenarios, respectively. © IWA Publishing 2017.
英文关键词	ANN; Climate change; Land use change; Regional Climate Model (RCM); Sediment yield; SWAT
语种	英语
scopus关键词	Calibration; Climate models; Forestry; Land use; Neural networks; Runoff; Climate change impact; Intergovernmental panel on climate changes; Land-use change; Regional climate modeling (RCM); Runoff and sediment yields; Sediment yields; Soil and water assessment tool; SWAT; Climate change; artificial neural network; climate change; climate modeling; land use change; regional climate; runoff; sediment yield; soil and water assessment tool; urbanization; Korea
来源期刊	Journal of Water and Climate Change
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/148111
作者单位	Department of Environmental Engineering, Nakdong River Environmental Research Center, Inje University, Inje-ro 197, Gimhae-si, Gyeongsangnam-do, South Korea; Water Resources Research Center, K-water Convergence Institute, 125, Yuseong-daero 1689, beon-gil, Yuseong-gu, Daejeon, South Korea; Department of Civil & Environmental Engineering, Dankook University, Jukjeon-ro 152, Suji-gu, Yongin-si, Gyeonggi-do, South Korea
推荐引用方式 GB/T 7714	Kim Y.D.,Kim J.M.,Kang B.. Projection of runoff and sediment yield under coordinated climate change and urbanization scenarios in Doam dam watershed; Korea[J],2017,8(2).
APA	Kim Y.D.,Kim J.M.,&Kang B..(2017).Projection of runoff and sediment yield under coordinated climate change and urbanization scenarios in Doam dam watershed; Korea.Journal of Water and Climate Change,8(2).
MLA	Kim Y.D.,et al."Projection of runoff and sediment yield under coordinated climate change and urbanization scenarios in Doam dam watershed; Korea".Journal of Water and Climate Change 8.2(2017).