globalchange  > 气候变化事实与影响
DOI: 10.5194/hess-21-4861-2017
Scopus记录号: 2-s2.0-85030529960
论文题名:
Parameter optimisation for a better representation of drought by LSMs: Inverse modelling vs. sequential data assimilation
作者: Dewaele H; , Munier S; , Albergel C; , Planque C; , Laanaia N; , Carrer D; , Calvet J; -C
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2017
卷: 21, 期:9
起始页码: 4861
结束页码: 4878
语种: 英语
Scopus关键词: Rain ; Uncertainty analysis ; Above ground biomass ; Available water contents ; Complex methods ; Interannual variability ; Inverse modelling ; Land data assimilation systems ; Land surface models ; Parameter optimisation ; Inverse problems ; aboveground biomass ; agricultural land ; annual variation ; crop yield ; data assimilation ; drought ; experimental study ; feasibility study ; inverse analysis ; land surface ; leaf area index ; optimization ; parameterization ; rainfed agriculture ; soil water ; time series analysis ; water content ; France
英文摘要: Soil maximum available water content (MaxAWC) is a key parameter in land surface models (LSMs). However, being difficult to measure, this parameter is usually uncertain. This study assesses the feasibility of using a 15-year (1999-2013) time series of satellite-derived low-resolution observations of leaf area index (LAI) to estimate MaxAWC for rainfed croplands over France. LAI interannual variability is simulated using the CO2-responsive version of the Interactions between Soil, Biosphere and Atmosphere (ISBA) LSM for various values of MaxAWC. Optimal value is then selected by using (1) a simple inverse modelling technique, comparing simulated and observed LAI and (2) a more complex method consisting in integrating observed LAI in ISBA through a land data assimilation system (LDAS) and minimising LAI analysis increments. The evaluation of the MaxAWC estimates from both methods is done using simulated annual maximum above-ground biomass (Bag) and straw cereal grain yield (GY) values from the Agreste French agricultural statistics portal, for 45 administrative units presenting a high proportion of straw cereals. Significant correlations (p valueg 0.01) between Bag and GY are found for up to 36 and 53% of the administrative units for the inverse modelling and LDAS tuning methods, respectively. It is found that the LDAS tuning experiment gives more realistic values of MaxAWC and maximum Bag than the inverse modelling experiment. Using undisaggregated LAI observations leads to an underestimation of MaxAWC and maximum Bag in both experiments. Median annual maximum values of disaggregated LAI observations are found to correlate very well with MaxAWC. © 2017 Author(s).
Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79045
Appears in Collections:气候变化事实与影响

Files in This Item:

There are no files associated with this item.


作者单位: CNRM, UMR3589, Météo-France, CNRS, Toulouse, France

Recommended Citation:
Dewaele H,, Munier S,, Albergel C,et al. Parameter optimisation for a better representation of drought by LSMs: Inverse modelling vs. sequential data assimilation[J]. Hydrology and Earth System Sciences,2017-01-01,21(9)
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[Dewaele H]'s Articles
[, Munier S]'s Articles
[, Albergel C]'s Articles
百度学术
Similar articles in Baidu Scholar
[Dewaele H]'s Articles
[, Munier S]'s Articles
[, Albergel C]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[Dewaele H]‘s Articles
[, Munier S]‘s Articles
[, Albergel C]‘s Articles
Related Copyright Policies
Null
收藏/分享
所有评论 (0)
暂无评论
 

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.