Articles | Volume 17, issue 10
Hydrol. Earth Syst. Sci., 17, 4143–4158, 2013
https://doi.org/10.5194/hess-17-4143-2013
Hydrol. Earth Syst. Sci., 17, 4143–4158, 2013
https://doi.org/10.5194/hess-17-4143-2013

Research article 24 Oct 2013

Research article | 24 Oct 2013

Distributed hydrologic modeling of a sparsely monitored basin in Sardinia, Italy, through hydrometeorological downscaling

G. Mascaro3,2,1, M. Piras3,2, R. Deidda3,2, and E. R. Vivoni1,4 G. Mascaro et al.
  • 1School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ, USA
  • 2Dipartimento di Ingegneria Civile, Ambientale ed Architettura, Università degli Studi di Cagliari, Cagliari, Italy
  • 3Consorzio Interuniversitario Nazionale per la Fisica delle Atmosfere e delle Idrosfere, Tolentino, Italy
  • 4School of Earth and Space Exploration, Arizona State University, Tempe, AZ, USA

Abstract. The water resources and hydrologic extremes in Mediterranean basins are heavily influenced by climate variability. Modeling these watersheds is difficult due to the complex nature of the hydrologic response as well as the sparseness of hydrometeorological observations. In this work, we present a strategy to calibrate a distributed hydrologic model, known as TIN-based Real-time Integrated Basin Simulator (tRIBS), in the Rio Mannu basin (RMB), a medium-sized watershed (472.5 km2) located in an agricultural area in Sardinia, Italy. In the RMB, precipitation, streamflow and meteorological data were collected within different historical periods and at diverse temporal resolutions. We designed two statistical tools for downscaling precipitation and potential evapotranspiration data to create the hourly, high-resolution forcing for the hydrologic model from daily records. Despite the presence of several sources of uncertainty in the observations and model parameterization, the use of the disaggregated forcing led to good calibration and validation performances for the tRIBS model, when daily discharge observations were available. The methodology proposed here can be also used to disaggregate outputs of climate models and conduct high-resolution hydrologic simulations with the goal of quantifying the impacts of climate change on water resources and the frequency of hydrologic extremes within medium-sized basins.

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