Performance evaluation of global hydrological models in six large Pan-Arctic watersheds

doi:10.1007/s10584-020-02892-2

	Performance evaluation of global hydrological models in six large Pan-Arctic watersheds
	Gaedeke, Anne 11; Krysanova, Valentina 11; Aryal, Aashutosh 11; Chang, Jinfeng 1,2,12; Grillakis, Manolis 3,4; Hanasaki, Naota 5; Koutroulis, Aristeidis 3; Pokhrel, Yadu 6; Satoh, Yusuke 1,5; Schaphoff, Sibyll 11
刊名	CLIMATIC CHANGE
	2020-11-24
页码	23
关键词	Global Water Models Model performance Model evaluation Arctic watersheds Boruta feature selection
ISSN号	0165-0009
DOI	10.1007/s10584-020-02892-2
通讯作者	Gaedeke, Anne(a.gaedeke@gmail.com)
英文摘要	Global Water Models (GWMs), which include Global Hydrological, Land Surface, and Dynamic Global Vegetation Models, present valuable tools for quantifying climate change impacts on hydrological processes in the data scarce high latitudes. Here we performed a systematic model performance evaluation in six major Pan-Arctic watersheds for different hydrological indicators (monthly and seasonal discharge, extremes, trends (or lack of), and snow water equivalent (SWE)) via a novel Aggregated Performance Index (API) that is based on commonly used statistical evaluation metrics. The machine learning Boruta feature selection algorithm was used to evaluate the explanatory power of the API attributes. Our results show that the majority of the nine GWMs included in the study exhibit considerable difficulties in realistically representing Pan-Arctic hydrological processes. Average API(discharge) (monthly and seasonal discharge) over nine GWMs is > 50% only in the Kolyma basin (55%), as low as 30% in the Yukon basin and averaged over all watersheds API(discharge) is 43%. WATERGAP2 and MATSIRO present the highest (API(discharge) > 55%) while ORCHIDEE and JULES-W1 the lowest (API(discharge) <= 25%) performing GWMs over all watersheds. For the high and low flows, average API(extreme) is 35% and 26%, respectively, and over six GWMs API(SWE) is 57%. The Boruta algorithm suggests that using different observation-based climate data sets does not influence the total score of the APIs in all watersheds. Ultimately, only satisfactory to good performing GWMs that effectively represent cold-region hydrological processes (including snow-related processes, permafrost) should be included in multi-model climate change impact assessments in Pan-Arctic watersheds.
资助项目	Projekt DEAL
WOS关键词	LAND-SURFACE MODEL ; PART 1 ; RUNOFF ; ENVIRONMENT ; LATITUDES ; ACCURACY ; LEVEL ; JULES ; MASS
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
语种	英语
出版者	SPRINGER
WOS记录号	WOS:000592141800001
资助机构	Projekt DEAL
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/156711]
专题	中国科学院地理科学与资源研究所
通讯作者	Gaedeke, Anne
作者单位	1.Int Inst Appl Syst Anal IIASA, Schlosspl 1, A-2361 Laxenburg, Austria 2.Zhejiang Univ, Coll Environm & Resource Sci, Hangzhou 310058, Peoples R China 3.Tech Univ Crete, Sch Environm Engn, Khania 73100, Greece 4.Fdn Res & Technol Hellas, Inst Mediterranean Studies, Lab Geophys Remote Sensing & Archaeoenvironm, Rethimnon 74100, Greece 5.Natl Inst Environm Studies, 16-2 Onogawa, Tsukuba, Ibaraki 3058506, Japan 6.Michigan State Univ, Dept Civil & Environm Engn, E Lansing, MI 48824 USA 7.Goethe Univ Frankfurt, Inst Phys Geog, D-60438 Frankfurt, Germany 8.Senckenberg Leibniz Biodivers & Climate Res Ctr S, D-60325 Frankfurt, Germany 9.Helmholtz Zentrum Geesthacht, Inst Coastal Res, D-21502 Geesthacht, Germany 10.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China
推荐引用方式 GB/T 7714	Gaedeke, Anne,Krysanova, Valentina,Aryal, Aashutosh,et al. Performance evaluation of global hydrological models in six large Pan-Arctic watersheds[J]. CLIMATIC CHANGE,2020:23.
APA	Gaedeke, Anne.,Krysanova, Valentina.,Aryal, Aashutosh.,Chang, Jinfeng.,Grillakis, Manolis.,...&Thonicke, Kirsten.(2020).Performance evaluation of global hydrological models in six large Pan-Arctic watersheds.CLIMATIC CHANGE,23.
MLA	Gaedeke, Anne,et al."Performance evaluation of global hydrological models in six large Pan-Arctic watersheds".CLIMATIC CHANGE (2020):23.