Intensive precipitation observation greatly improves hydrological modelling of the poorly gauged high mountain Mabengnong catchment in the Tibetan Plateau | |
Wang, L (Wang, Li)1,2,3; Zhang, F (Zhang, Fan)1,2,3,4; Zhang, HB (Zhang, Hongbo)1,2; Scott, CA (Scott, Christopher A.)5,6; Zeng, C (Zeng, Chen)1,2; Shi, XN (Shi, Xiaonan)1,2 | |
Source Publication | JOURNAL OF HYDROLOGY |
2018 | |
Volume | 556Issue:0Pages:500-509 |
DOI | 10.1016/j.jhydrol.2017.11.039 |
Abstract | Precipitation is one of the most critical inputs for models used to improve understanding of hydrological processes. In high mountain areas, it is challenging to generate a reliable precipitation data set capturing the spatial and temporal heterogeneity due to the harsh climate, extreme terrain and the lack of observations. This study conducts intensive observation of precipitation in the Mabengnong catchment in the southeast of the Tibetan Plateau during July to August 2013. Because precipitation is greatly influenced by altitude, the observed data are used to characterize the precipitation gradient (PG) and hourly distribution (HD), showing that the average PG is 0.10, 0.28 and 0.26 mm/d/100 m and the average duration is around 0.1, 0.8 and 5.2 h for trace, light and moderate rain, respectively. A distributed biosphere hydrological model based on water and energy budgets with improved physical process for snow (WEB-DHMS) is applied to simulate the hydrological processes with gridded precipitation data derived from a lower altitude meteorological station and the PG and HD characterized for the study area. The observed runoff, MODIS/Terra snow cover area (SCA) data, and MODIS/Terra land surface temperature (LST) data are used for model calibration and validation. Runoff, SCA and LST simulations all show reasonable results. Sensitivity analyses illustrate that runoff is largely underestimated without considering PG, indicating that short-term intensive precipitation observation has the potential to greatly improve hydrological modelling of poorly gauged high mountain catchments. (C) 2017 Elsevier B.V. All rights reserved. |
Subject Area | 地理学 |
WOS ID | WOS:000423641300039 |
Language | 英语 |
Indexed By | SCIE |
Keyword | Modis Snow Cover Altitude Relationship Subsurface Stormflow Rainfall Variability Surface Temperature River-basin Validation Runoff Climate Water |
WOS Research Area | Engineering ; Geology ; Water Resources |
WOS Subject | Engineering, Civil ; Geosciences, Multidisciplinary ; Water Resources |
Cooperation Status | 国际 |
ISSN | 0022-1694 |
Department | 环境变化与地表过程重点实验室 |
Publisher | ELSEVIER SCIENCE BV |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://ir.itpcas.ac.cn/handle/131C11/8783 |
Collection | 图书馆 |
Corresponding Author | Zhang, F (Zhang, Fan) |
Affiliation | 1.Chinese Acad Sci, Inst Tibetan Plateau Res, Key Lab Tibetan Environm Changes & Land Surface P, Beijing, Peoples R China; 2.Chinese Acad Sci, Inst Tibetan Plateau Res, Key Lab Alpine Ecol & Biodivers, Beijing, Peoples R China; 3.Univ Chinese Acad Sci, Beijing, Peoples R China; 4.CAS Ctr Excellence Tibetan Plateau Earth Sci, Beijing, Peoples R China; 5.[Scott, Christopher A.] Univ Arizona, Sch Geog & Dev, Tucson, AZ 85719 USA; 6.[Scott, Christopher A.] Univ Arizona, Udall Ctr Studies Publ Policy, Tucson, AZ 85719 USA. |
Recommended Citation GB/T 7714 | Wang, L ,Zhang, F ,Zhang, HB ,et al. Intensive precipitation observation greatly improves hydrological modelling of the poorly gauged high mountain Mabengnong catchment in the Tibetan Plateau[J]. JOURNAL OF HYDROLOGY,2018,556(0):500-509. |
APA | Wang, L ,Zhang, F ,Zhang, HB ,Scott, CA ,Zeng, C ,&Shi, XN .(2018).Intensive precipitation observation greatly improves hydrological modelling of the poorly gauged high mountain Mabengnong catchment in the Tibetan Plateau.JOURNAL OF HYDROLOGY,556(0),500-509. |
MLA | Wang, L ,et al."Intensive precipitation observation greatly improves hydrological modelling of the poorly gauged high mountain Mabengnong catchment in the Tibetan Plateau".JOURNAL OF HYDROLOGY 556.0(2018):500-509. |
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