气候变化领域集成服务门户(CCPortal): Identifying future climate change and drought detection using CanESM2 in the upper Siem Reap River, Cambodia

CCPortal

DOI	10.1016/j.dynatmoce.2020.101182
	Identifying future climate change and drought detection using CanESM2 in the upper Siem Reap River, Cambodia
	Chim K.; Tunnicliffe J.; Shamseldin A.; Chan K.
发表日期	2020
ISSN	03770265
英文摘要	Cambodia is one of the most vulnerable countries to climate change impacts such as floods and droughts. Study of future climate change and drought conditions in the upper Siem Reap River catchment is vital because this river plays a crucial role in maintaining the Angkor Temple Complex and livelihood of the local population since 12th century. The resolution of climate data from Global Circulation Models (GCM) is too coarse to employ effectively at the watershed scale, and therefore downscaling of the dataset is required. Artificial neural network (ANN) and Statistical Downscaling Model (SDSM) models were applied in this study to downscale precipitation and temperatures from three Representative Concentration Pathways (RCP 2.6, RCP 4.5 and RCP 8.5 scenarios) from Global Climate Model data of the Canadian Earth System Model (CanESM2) on a daily and monthly basis. The Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were adopted to develop criteria for dry and wet conditions in the catchment. Trend detection of climate parameters and drought indices were assessed using the Mann-Kendall test. It was observed that the ANN and SDSM models performed well in downscaling monthly precipitation and temperature, as well as daily temperature, but not daily precipitation. Every scenario indicated that there would be significant warming and decreasing precipitation which contribute to mild drought. The results of this study provide valuable information for decision makers since climate change may potentially impact future water supply of the Angkor Temple Complex (a World Heritage Site). © 2020 Elsevier B.V.
英文关键词	Angkor temple; ANN and SDSM; Drought index; Mann-Kendall; SPI and SPEI; Statistical downscaling
语种	英语
scopus关键词	Catchments; Climate models; Complex networks; Decision making; Drought; Earth (planet); Neural networks; Rivers; Runoff; Stream flow; Water supply; Climate change impact; Climate parameters; Daily precipitations; Dry and wet conditions; Global circulation model; Global climate model; Standardized precipitation index; Statistical downscaling model (SDSM); Climate change
来源期刊	Dynamics of Atmospheres and Oceans
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/178337
作者单位	School of Environment, the University of Auckland, Auckland, 1010, New Zealand; Faculty of Engineering, the University of Auckland, Auckland, 1010, New Zealand; Ministry of Water Resources and Meteorology, Phnom Penh, 12300, Cambodia
推荐引用方式 GB/T 7714	Chim K.,Tunnicliffe J.,Shamseldin A.,et al. Identifying future climate change and drought detection using CanESM2 in the upper Siem Reap River, Cambodia[J],2020.
APA	Chim K.,Tunnicliffe J.,Shamseldin A.,&Chan K..(2020).Identifying future climate change and drought detection using CanESM2 in the upper Siem Reap River, Cambodia.Dynamics of Atmospheres and Oceans.
MLA	Chim K.,et al."Identifying future climate change and drought detection using CanESM2 in the upper Siem Reap River, Cambodia".Dynamics of Atmospheres and Oceans (2020).