Closing the terrestrial water budget from satellite remote sensing

The increasing availability of remote sensing products for all components of the terrestrial water cycle makes it now possible to evaluate the potential of water balance closure purely from remote sensing sources. We take precipitation (P) from the TMPA and CMORPH products, a Penman‐Monteith based evapotranspiration (E) estimate derived from NASA Aqua satellite data and terrestrial water storage change (ΔS) from the GRACE satellite. Their combined ability to close the water budget is evaluated over the Mississippi River basin for 2003–5 by estimating streamflow (Q) as a residual of the water budget and comparing to streamflow measurements. We find that Q is greatly overestimated due mainly to the high bias in P, especially in the summer. Removal of systematic biases in P reduces the error significantly. However, uncertainties in the individual budget components due to simplifications in process algorithms and input data error are generally larger than the measured streamflow.

[1]  Eric F. Wood,et al.  An efficient calibration method for continental‐scale land surface modeling , 2008 .

[2]  Matthew F. McCabe,et al.  Hydrological consistency using multi-sensor remote sensing data for water and energy cycle studies , 2008 .

[3]  Maosheng Zhao,et al.  Development of a global evapotranspiration algorithm based on MODIS and global meteorology data , 2007 .

[4]  P. Bates,et al.  Spatial and temporal complexity of the Amazon flood measured from space , 2007 .

[5]  Y. Hong,et al.  The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales , 2007 .

[6]  E. Wood,et al.  Data Assimilation for Estimating the Terrestrial Water Budget Using a Constrained Ensemble Kalman Filter , 2006 .

[7]  David D. Parrish,et al.  NORTH AMERICAN REGIONAL REANALYSIS , 2006 .

[8]  Matthew F. McCabe,et al.  Modeling Evapotranspiration during SMACEX: Comparing Two Approaches for Local- and Regional-Scale Prediction , 2005 .

[9]  S. Seneviratne,et al.  Basin scale estimates of evapotranspiration using GRACE and other observations , 2004 .

[10]  J. Janowiak,et al.  CMORPH: A Method that Produces Global Precipitation Estimates from Passive Microwave and Infrared Data at High Spatial and Temporal Resolution , 2004 .

[11]  M. Watkins,et al.  The gravity recovery and climate experiment: Mission overview and early results , 2004 .

[12]  J. D. Tarpley,et al.  The multi‐institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system , 2004 .

[13]  Dennis P. Lettenmaier,et al.  Tracking Fresh Water from Space , 2003, Science.

[14]  S. Swenson,et al.  Methods for inferring regional surface‐mass anomalies from Gravity Recovery and Climate Experiment (GRACE) measurements of time‐variable gravity , 2002 .

[15]  F. Bryan,et al.  Time variability of the Earth's gravity field: Hydrological and oceanic effects and their possible detection using GRACE , 1998 .

[16]  Wilfried Brutsaert,et al.  Daytime evaporation and the self-preservation of the evaporative fraction and the Bowen ratio , 1996 .

[17]  J. Monteith.  Evaporation and environment. , 1965, Symposia of the Society for Experimental Biology.