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Discussion papers
https://doi.org/10.5194/hess-2019-75
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2019-75
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 01 Mar 2019

Research article | 01 Mar 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Hydrology and Earth System Sciences (HESS).

Using nowcasting technique and data assimilation in a meteorological model to improve very short range hydrological forecasts

Maria Laura Poletti1, Francesco Silvestro1, Silvio Davolio2, Flavio Pignone1, and Nicola Rebora1 Maria Laura Poletti et al.
  • 1CIMA Research Foundation
  • 2ISAC-CNR

Abstract. Forecasting flash floods with anticipation of some hours is still a challenge especially in environments made by a collection of small catchments. Hydrometeorological forecasting systems generally allow to predict the possibility of having very intense rainfall events on quite large areas with good performances even with 12–24 hours of anticipation. However, they are not able to predict exactly rainfall location if we consider portions of territory of 10 to 103 km2 as order of magnitude. The scope of this work is to exploit both observations and modeling sources to improve the discharge prediction in small catchments with time horizon of 2–8 hours.

The models used to achieve the goal are essentially three i) a probabilistic rainfall nowcasting model able to extrapolate the rainfall evolution from observations; ii) a non hydrostatic high-resolution numerical weather prediction (NWP) model; iii) a distributed hydrological model able to provide a streamflow prediction in each pixel of the studied domain. These tools are used, together with radar observations, in a synergistic way, exploiting the information of each element in order to complement each other: observations are used in a frequently updated data assimilation framework to drive the NWP system, whose output is in turn used to improve the information in input to a nowcasting technique; finally nowcasting and NWP outputs are blended, generating an ensemble of rainfall scenarios used to feed the hydrological model and produce a prediction in terms of streamflow.

The flood prediction system is applied to three major events occurred on Liguria Region (Italy) first to produce a standard analysis on predefined basin control sections, then using a distributed approach that exploit the capabilities of the employed hydrological model. The results obtained for these three analyzed events show that the use of the present approach is promising. Even if not in all the cases, the blending technique clearly enhances the prediction capacity of the hydrological nowcasting chain with respect to the use of input coming only from the nowcasting technique; moreover, a worsening of the performance is rarely observed and it is nevertheless ascribable to the critical transition between the nowcasting and the NWP model rainfall field.

Maria Laura Poletti et al.
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Status: open (until 26 Apr 2019)
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Maria Laura Poletti et al.
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Short summary
In this work a probabilistic rainfall nowcasting model, a non hydrostatic high-resolution numerical weather prediction (NWP) model corrected with data assimilation and a distributed hydrological model are used, together with radar observations to implement an hydrological nowcasting chain. This chain is used to obtain a useful discharge prediction in small catchments with time horizon of 2–8 hours.
In this work a probabilistic rainfall nowcasting model, a non hydrostatic high-resolution...
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