Preprints
https://doi.org/10.5194/hess-2021-104
https://doi.org/10.5194/hess-2021-104

  09 Mar 2021

09 Mar 2021

Review status: this preprint is currently under review for the journal HESS.

Information content of soil hydrology in the Amazon as informed by GRACE

Elias C. Massoud, A. Anthony Bloom, Marcos Longo, John T. Reager, Paul A. Levine, and John R. Worden Elias C. Massoud et al.
  • Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA

Abstract. The seasonal-to-decadal terrestrial water balance on river basin scales depends on a number of well-characterized but uncertain soil physical processes, including soil moisture, plant available water, rooting depth, and recharge to lower soil layers. Reducing uncertainties in these quantities using observations is a key step towards improving the data fidelity and skill of land surface models. In this study, we quantitatively characterize the capability of Gravity Recovery and Climate Experiment (NASA-GRACE) measurements – a key constraint on Total Water Storage (TWS) – to inform and constrain these processes. We use a reduced complexity physically-based model capable of simulating the hydrologic cycle, and we apply Bayesian inference on the model parameters using a Markov Chain Monte Carlo (MCMC) algorithm, to minimize mismatches between model simulated and GRACE-observed TWS anomalies. Based on the prior and posterior model parameter distributions, we further quantify information gain with regards to terrestrial water states, associated fluxes and time-invariant process parameters. We show that the data-constrained terrestrial water storage model is capable of capturing basic physics of the hydrologic cycle for a watershed in the western Amazon during the period of January 2003 through December 2012, with an r2 of 0.96 and RMSE of 46.93 mm between observed and simulated TWS. Furthermore, we show a reduction of uncertainty in many of the parameters and state variables, ranging from a 2 % reduction in uncertainty for the porosity parameter to an 85 % reduction for the rooting depth parameter. The annual and interannual variability of the system are also simulated accurately, with the model simulations capturing the impacts of the 2005–2006 and 2010–2011 South America droughts. The results shown here suggest the potential of using gravimetric observations of TWS to identify and constrain key parameters in soil hydrologic models.

Elias C. Massoud et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-104', Anonymous Referee #1, 11 Apr 2021
    • AC1: 'Reply on RC1', Elias Massoud, 24 Jun 2021
  • RC2: 'Comment on hess-2021-104', Anonymous Referee #2, 17 May 2021
    • AC2: 'Reply on RC2', Elias Massoud, 24 Jun 2021

Elias C. Massoud et al.

Elias C. Massoud et al.

Viewed

Total article views: 656 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
475 170 11 656 33 2 5
  • HTML: 475
  • PDF: 170
  • XML: 11
  • Total: 656
  • Supplement: 33
  • BibTeX: 2
  • EndNote: 5
Views and downloads (calculated since 09 Mar 2021)
Cumulative views and downloads (calculated since 09 Mar 2021)

Viewed (geographical distribution)

Total article views: 517 (including HTML, PDF, and XML) Thereof 517 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 16 Oct 2021
Download
Short summary
The water balance on river basin scales depends on a number of soil physical processes. Gaining information on these quantities using observations is a key step towards improving the skill of land surface hydrology models. In this study, we use data from the Gravity Recovery and Climate Experiment (NASA-GRACE) to inform and constrain these hydrologic processes. We show that our model is able to simulate the land hydrologic cycle for a watershed in the Amazon from January 2003 to December 2012.