DOI: 10.5194/hess-22-2135-2018
Scopus记录号: 2-s2.0-85045309892
论文题名: Large-scale hydrological model river storage and discharge correction using a satellite altimetry-based discharge product
作者: Emery C ; M ; , Paris A ; , Biancamaria S ; , Boone A ; , Calmant S ; , Garambois P ; -A ; , Da Silva J ; S
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2018
卷: 22, 期: 4 起始页码: 2135
结束页码: 2162
语种: 英语
Scopus关键词: Digital storage
; Mean square error
; Rivers
; Soil moisture
; Uncertainty analysis
; Data assimilation techniques
; Ensemble Kalman Filter
; Initial development
; Land surface models
; Large scale hydrological model
; Model uncertainties
; Remotely-sensed observations
; Root mean square errors
; Geodetic satellites
英文摘要: Land surface models (LSMs) are widely used to study the continental part of the water cycle. However, even though their accuracy is increasing, inherent model uncertainties can not be avoided. In the meantime, remotely sensed observations of the continental water cycle variables such as soil moisture, lakes and river elevations are more frequent and accurate. Therefore, those two different types of information can be combined, using data assimilation techniques to reduce a model's uncertainties in its state variables or/and in its input parameters. The objective of this study is to present a data assimilation platform that assimilates into the large-scale ISBA-CTRIP LSM a punctual river discharge product, derived from ENVISAT nadir altimeter water elevation measurements and rating curves, over the whole Amazon basin. To deal with the scale difference between the model and the observation, the study also presents an initial development for a localization treatment that allows one to limit the impact of observations to areas close to the observation and in the same hydrological network. This assimilation platform is based on the ensemble Kalman filter and can correct either the CTRIP river water storage or the discharge. Root mean square error (RMSE) compared to gauge discharges is globally reduced until 21% and at Óbidos, near the outlet, RMSE is reduced by up to 52% compared to ENVISAT-based discharge. Finally, it is shown that localization improves results along the main tributaries. © 2018 Author(s). Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79339
Appears in Collections: 气候变化事实与影响
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作者单位: LEGOS, Université de Toulouse, CNES, CNRS, IRD, UPS, Toulouse, France; GET, Université de Toulouse, UPS, CNRS, IRD, Toulouse, France; LMI OCE IRD/UNB, Campus Darcy Ribeiro, Brasilia, Brazil; Meteo France CNRS, CNRM UMR 3589, Toulouse, France; ICUBE - UMR 7357, Fluid Mechanics Team, INSA, Strasbourg, France; CESTU, Universidade Do Estado Do Amazonas, Manaus, Brazil; JPL, Pasadena, CA, United States; CLS, Ramonville-Saint-Agne, France
Recommended Citation:
Emery C,M,, Paris A,et al. Large-scale hydrological model river storage and discharge correction using a satellite altimetry-based discharge product[J]. Hydrology and Earth System Sciences,2018-01-01,22(4)