Hydrology and Earth System Sciences (Jul 2022)

High-resolution satellite products improve hydrological modeling in northern Italy

  • L. Alfieri,
  • F. Avanzi,
  • F. Delogu,
  • S. Gabellani,
  • G. Bruno,
  • L. Campo,
  • A. Libertino,
  • C. Massari,
  • A. Tarpanelli,
  • D. Rains,
  • D. G. Miralles,
  • R. Quast,
  • M. Vreugdenhil,
  • H. Wu,
  • H. Wu,
  • L. Brocca

DOI
https://doi.org/10.5194/hess-26-3921-2022
Journal volume & issue
Vol. 26
pp. 3921 – 3939

Abstract

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Satellite-based Earth observations (EO) are an accurate and reliable data source for atmospheric and environmental science. Their increasing spatial and temporal resolutions, as well as the seamless availability over ungauged regions, make them appealing for hydrological modeling. This work shows recent advances in the use of high-resolution satellite-based EO data in hydrological modeling. In a set of six experiments, the distributed hydrological model Continuum is set up for the Po River basin (Italy) and forced, in turn, by satellite precipitation and evaporation, while satellite-derived soil moisture (SM) and snow depths are ingested into the model structure through a data-assimilation scheme. Further, satellite-based estimates of precipitation, evaporation, and river discharge are used for hydrological model calibration, and results are compared with those based on ground observations. Despite the high density of conventional ground measurements and the strong human influence in the focus region, all satellite products show strong potential for operational hydrological applications, with skillful estimates of river discharge throughout the model domain. Satellite-based evaporation and snow depths marginally improve (by 2 % and 4 %) the mean Kling–Gupta efficiency (KGE) at 27 river gauges, compared to a baseline simulation (KGEmean= 0.51) forced by high-quality conventional data. Precipitation has the largest impact on the model output, though the satellite data on average shows poorer skills compared to conventional data. Interestingly, a model calibration heavily relying on satellite data, as opposed to conventional data, provides a skillful reconstruction of river discharges, paving the way to fully satellite-driven hydrological applications.