Preprints
https://doi.org/10.5194/hess-2023-214
https://doi.org/10.5194/hess-2023-214
07 Sep 2023
 | 07 Sep 2023
Status: this preprint is currently under review for the journal HESS.

On the combined use of rain gauges and GPM IMERG satellite rainfall products: testing cellular automata-based interpolation methodology on the Tanaro river basin in Italy

Annalina Lombardi, Barbara Tomassetti, Valentina Colaiuda, Ludovico Di Antonio, Paolo Tuccella, Mario Montopoli, Giovanni Ravazzani, Frank Silvio Marzano, Raffaele Lidori, and Giulia Panegrossi

Abstract. The uncertainty of hydrological forecasts is strongly related to the uncertainty of the rainfall field due to the nonlinear relationship between the spatio-temporal pattern of rainfall and runoff. Rain gauges are typically considered as reference data to rebuild precipitation fields. However, due to the density and the distribution variability of the raingauge network, the rebuilding of the precipitation field can be affected by severe errors which compromise the hydrological simulation output. On the other hand, retrievals obtained from remote sensing observations provide spatially resolved precipitation fields improving their representativeness. In this regard, this paper aims to investigate the impact of using the merged rainfall fields from the rain gauge Italian rainfall network and the NASA Global Precipitation Measurement (GPM) IMERG precipitation product on the hydrological simulation performance. In particular, one aspect is to highlight the benefits of applying the Cellular Automata algorithm to pre-process input data in order to merge them and reconstruct an improved version of the precipitation field.

The cellular automata approach is evaluated in the Tanaro River Basin, one of the tributaries of the Po River in Italy. As this site is characterized by the coexistence of a variety of natural morphologies, from mountain to alluvial environments, as well as the presence of significant civil and industrial settlements, it makes it a suitable case study to apply the proposed approach. The latter has been applied over three different flood events occurred from November to December 2014.

The results confirm that the use of merged gauge-satellite data using the Cellular Automata algorithm improves the performance of the hydrological simulation, as also confirmed by the statistical analysis performed for seventeen selected quality scores.

Annalina Lombardi, Barbara Tomassetti, Valentina Colaiuda, Ludovico Di Antonio, Paolo Tuccella, Mario Montopoli, Giovanni Ravazzani, Frank Silvio Marzano, Raffaele Lidori, and Giulia Panegrossi

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-2023-214', Anonymous Referee #1, 09 Oct 2023
    • AC1: 'Reply on RC1', Annalina Lombardi, 27 Nov 2023
  • RC2: 'Comment on hess-2023-214', Anonymous Referee #2, 11 Oct 2023
    • AC2: 'Reply on RC2', Annalina Lombardi, 27 Nov 2023
Annalina Lombardi, Barbara Tomassetti, Valentina Colaiuda, Ludovico Di Antonio, Paolo Tuccella, Mario Montopoli, Giovanni Ravazzani, Frank Silvio Marzano, Raffaele Lidori, and Giulia Panegrossi
Annalina Lombardi, Barbara Tomassetti, Valentina Colaiuda, Ludovico Di Antonio, Paolo Tuccella, Mario Montopoli, Giovanni Ravazzani, Frank Silvio Marzano, Raffaele Lidori, and Giulia Panegrossi

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Short summary
The accurate estimation of precipitation and its spatial variability within a watershed is crucial for reliable discharge simulations. The study is the first detailed analysis of the potential usage of the Cellular Automata technique to merge different rainfall data inputs to hydrological models. This work shows an improvement in the performance of hydrological simulations when satellite and rain gauge data are merged.