Preprints
https://doi.org/10.5194/gmd-2020-399
https://doi.org/10.5194/gmd-2020-399

Submitted as: model description paper 25 Jan 2021

Submitted as: model description paper | 25 Jan 2021

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

Synergy between satellite observations of soil moisture and water storage anomalies for global runoff estimation

Stefania Camici1, Gabriele Giuliani1, Luca Brocca1, Christian Massari1, Angelica Tarpanelli1, Hassan Hashemi Farahani2, Nico Sneeuw2, Marco Restano3, and Jérôme Benveniste4 Stefania Camici et al.
  • 1National Research Council, Research Institute for Geo-Hydrological Protection, Perugia, Italy
  • 2Institute of Geodesy, University of Stuttgart, Geschwister-Scholl-Straße 24D, 70174 Stuttgart, Germany
  • 3SERCO c/o ESA-ESRIN, Largo Galileo Galilei, Frascati, 00044, Italy
  • 4European Space Agency, ESA-ESRIN, Largo Galileo Galilei, Frascati, 00044, Italy

Abstract. This paper presents an innovative approach, STREAM – SaTellite based Runoff Evaluation And Mapping – to derive daily river discharge and runoff estimates from satellite soil moisture, precipitation and terrestrial water storage anomalies observations. Within a very simple model structure, the first two variables (precipitation and soil moisture) are used to estimate the quick-flow river discharge component while the terrestrial water storage anomalies are used for obtaining its complementary part, i.e., the slow-flow river discharge component. The two are then summed up to obtain river discharge and runoff estimates.

The method is tested over the Mississippi river basin for the period 2003–2016 by using Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) rainfall data, European Space Agency Climate Change Initiative (ESA CCI) soil moisture data and Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage data. Despite the model simplicity, relatively high-performance scores are obtained in river discharge simulations, with a Kling-Gupta efficiency index greater than 0.65 both at the outlet and over several inner stations used for model calibration highlighting the high information content of satellite observations on surface processes. Potentially useful for multiple operational and scientific applications (from flood warning systems to the understanding of water cycle), the added-value of the STREAM approach is twofold: 1) a simple modelling framework, potentially suitable for global runoff monitoring, at daily time scale when forced with satellite observations only, 2) increased knowledge on the natural processes, human activities and on their interactions on the land.

Stefania Camici 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 gmd-2020-399', Anonymous Referee #1, 01 Mar 2021
    • AC3: 'Reply on RC1', Stefania Camici, 23 Mar 2021
  • CEC1: 'Comment on gmd-2020-399', Juan Antonio Añel, 03 Mar 2021
  • AC1: 'Comment on gmd-2020-399', Stefania Camici, 08 Mar 2021
    • AC2: 'Reply on AC1', Stefania Camici, 08 Mar 2021
      • EC2: 'DOI and documentation', Andrew Wickert, 22 Mar 2021
        • AC4: 'Reply on EC2', Stefania Camici, 23 Mar 2021
          • EC3: 'Reply on AC4', Andrew Wickert, 23 Mar 2021
  • RC2: 'Comment on gmd-2020-399', Anonymous Referee #2, 22 Mar 2021
    • AC5: 'Reply on RC2', Stefania Camici, 23 Mar 2021
  • EC1: 'Comment on gmd-2020-399', Andrew Wickert, 22 Mar 2021
  • RC3: 'Comment on gmd-2020-399', Anonymous Referee #3, 19 Apr 2021
    • AC6: 'Reply on RC3', Stefania Camici, 30 Apr 2021

Stefania Camici et al.

Stefania Camici et al.

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Short summary
This paper presents an innovative approach, STREAM – SaTellite based Runoff Evaluation And Mapping – to derive daily river discharge and runoff estimates from satellite soil moisture, precipitation and terrestrial water storage anomalies observations. Potentially useful for multiple operational and scientific applications, the added-value of the STREAM approach is the ability to increase knowledge on the natural processes, human activities and on their interactions on the land.