Performance evaluation of global hydrological models in six large Pan-Arctic watersheds
文献类型：期刊论文
| 作者 | Gaedeke, Anne1; Krysanova, Valentina1; Aryal, Aashutosh1; Chang, Jinfeng3,4,5; Grillakis, Manolis6,7; Hanasaki, Naota8; Koutroulis, Aristeidis6; Pokhrel, Yadu2; Satoh, Yusuke4,8; Schaphoff, Sibyll1 |
| 刊名 | CLIMATIC CHANGE
 |
| 出版日期 | 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. |
| WOS关键词 | LAND-SURFACE MODEL ; PART 1 ; RUNOFF ; ENVIRONMENT ; LATITUDES ; ACCURACY ; LEVEL ; JULES ; MASS |
| 资助项目 | Projekt DEAL |
| WOS研究方向 | Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences |
| 语种 | 英语 |
| WOS记录号 | WOS:000592141800001 |
| 出版者 | SPRINGER |
| 资助机构 | Projekt DEAL |
| 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.Leibniz Assoc, Potsdam Inst Climate Impact Res, D-14412 Potsdam, Germany 2.Michigan State Univ, Dept Civil & Environm Engn, E Lansing, MI 48824 USA 3.Univ Paris Saclay, UVSQ, CEA, CNRS,LSCE,IPSL,Lab Sci Climat & Environm, F-91191 Gif Sur Yvette, France 4.Int Inst Appl Syst Anal IIASA, Schlosspl 1, A-2361 Laxenburg, Austria 5.Zhejiang Univ, Coll Environm & Resource Sci, Hangzhou 310058, Peoples R China 6.Tech Univ Crete, Sch Environm Engn, Khania 73100, Greece 7.Fdn Res & Technol Hellas, Inst Mediterranean Studies, Lab Geophys Remote Sensing & Archaeoenvironm, Rethimnon 74100, Greece 8.Natl Inst Environm Studies, 16-2 Onogawa, Tsukuba, Ibaraki 3058506, Japan 9.Goethe Univ Frankfurt, Inst Phys Geog, D-60438 Frankfurt, Germany 10.Senckenberg Leibniz Biodivers & Climate Res Ctr S, D-60325 Frankfurt, Germany |
| 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. |
入库方式： OAI收割
来源：地理科学与资源研究所
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