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Open AccessArticle

Assessment of Runoff Components Simulated by GLDAS against UNH–GRDC Dataset at Global and Hemispheric Scales

by Meizhao Lv 1,2, Hui Lu 1,3,*, Kun Yang 1,3,4,5, Zhongfeng Xu 2, Meixia Lv 2 and Xiaomeng Huang 1,3
1
Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
2
CAS Key Laboratory of Regional Climate-Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
3
Joint Center for Global Change Studies, Beijing 100875, China
4
CAS Center for Excellence in Tibetan Plateau Earth System, Beijing 100101, China
5
Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
*
Author to whom correspondence should be addressed.
Water 2018, 10(8), 969; https://doi.org/10.3390/w10080969
Received: 13 June 2018 / Revised: 6 July 2018 / Accepted: 23 July 2018 / Published: 24 July 2018
(This article belongs to the Special Issue Catchment Modelling)
The current evaluations of global land data assimilation system (GLDAS) runoff were generally limited to the observation-rich areas. At the global and hemispheric scales, we assessed different runoff components performance of GLDAS (1.0 and 2.1) using the University of New Hampshire and Global Runoff Data Centre (UNH-GRDC) dataset. The results suggest that GLDAS simulations show considerable uncertainties, particularly in partition of surface and subsurface runoffs, in snowmelt runoff modeling, and in capturing the northern peak time. GLDAS1.0-CLM (common land model) produced more surface runoff almost globally; GLDAS-Noah generated more surface runoff over the northern middle-high latitudes and more subsurface runoff in the remaining areas; while the partition in GLDAS1.0-VIC (variable infiltration capacity) is almost opposite to that in Noah. Comparing to GLDAS1.0-Noah, GLDAS2.1-Noah improved the premature snow-melting tendency, but its snowmelt-runoff peak magnitude was excessively high in June and July. The discrepancies in northern primary peak times among precipitation and runoff is partly caused by the combination of rainfall and melting-snow over high-latitude, as well as the very different temporal–spatial distributions for snowmelt runoff simulated by GLDAS models. This paper can provide valuable guidance for GLDAS users, and contribute to the further improvement of hydrological parameterized schemes. View Full-Text
Keywords: runoff component simulation; peak time; snowmelt; global and hemispheric scales; GLDAS runoff component simulation; peak time; snowmelt; global and hemispheric scales; GLDAS
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Lv, M.; Lu, H.; Yang, K.; Xu, Z.; Lv, M.; Huang, X. Assessment of Runoff Components Simulated by GLDAS against UNH–GRDC Dataset at Global and Hemispheric Scales. Water 2018, 10, 969.

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