DOI: 10.1175/JCLI-D-11-00300.1
Scopus记录号: 2-s2.0-84862109275
论文题名: Multisource estimation of long-term terrestrial water budget for major global river basins
作者: Pan M. ; Sahoo A.K. ; Troy T.J. ; Vinukollu R.K. ; Sheffield J. ; Wood A.E.F.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2012
卷: 25, 期: 9 起始页码: 3191
结束页码: 3206
语种: 英语
Scopus关键词: Calibration procedure
; Climate variability
; Data assimilation techniques
; Data merging
; Data sets
; Data source
; Estimation process
; Global datasets
; Global scale
; Hydrologic cycles
; In-situ observations
; Integrated assessment
; Kalman filter technique
; Land surface models
; Long term records
; Model physics
; Multisources
; Network density
; River basins
; Specific location
; Systematic method
; Trend analysis
; Water balance
; Water budget
; Climate change
; Error analysis
; Estimation
; Kalman filters
; Merging
; Remote sensing
; Sensor networks
; Water resources
; Water supply
; Budget control
; climate change
; climate variation
; error analysis
; estimation method
; hydrological cycle
; Kalman filter
; river basin
; water budget
; water resource
英文摘要: A systematic method is proposed to optimally combine estimates of the terrestrial water budget from different data sources and to enforce the water balance constraint using data assimilation techniques. The method is applied to create global long-term records of the terrestrial water budget by merging a number of global datasets including in situ observations, remote sensing retrievals, land surface model simulations, and global reanalyses. The estimation process has three steps. First, a conventional analysis on the errors and biases in different data sources is conducted based on existing validation/error studies and other information such as sensor network density, model physics, and calibration procedures. Then, the data merging process combines different estimates so that biases and errors from different data sources can be compensated to the greatest extent and the merged estimates have the best possible confidence. Finally, water balance errors are resolved using the constrained Kalman filter technique. The procedure is applied to 32 globally distributed major basins for 1984-2006. The authors believe that the resulting global water budget estimates can be used as a baseline dataset for large-scale diagnostic studies, for example, integrated assessment of basin water resources, trend analysis and attribution, and climate change studies. The global scale of the analysis presents significant challenges in carrying out the error analysis for each water budget variable. For some variables (e.g., evapotranspiration) the assumptions underpinning the error analysis lack supporting quantitative analysis and, thus, may not hold for specific locations. Nevertheless, the merging and water balance constraining technique can be applied to many problems. © 2012 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/52432
Appears in Collections: 气候变化事实与影响
There are no files associated with this item.
作者单位: Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, United States
Recommended Citation:
Pan M.,Sahoo A.K.,Troy T.J.,et al. Multisource estimation of long-term terrestrial water budget for major global river basins[J]. Journal of Climate,2012-01-01,25(9)