Preprint Article Version 1 This version is not peer-reviewed

Operational Hydrological Modelling of Small Watershed using QPE from Dual-Pol Radar in Brazil

Version 1 : Received: 31 May 2019 / Approved: 4 June 2019 / Online: 4 June 2019 (07:41:17 CEST)

How to cite: Beneti, C.; Calheiros, R.V.; Sorribas, M.; Calvetti, L.; Oliveira, C.; Rozin, N.; Ruviaro, J. Operational Hydrological Modelling of Small Watershed using QPE from Dual-Pol Radar in Brazil. Preprints 2019, 2019060026 (doi: 10.20944/preprints201906.0026.v1). Beneti, C.; Calheiros, R.V.; Sorribas, M.; Calvetti, L.; Oliveira, C.; Rozin, N.; Ruviaro, J. Operational Hydrological Modelling of Small Watershed using QPE from Dual-Pol Radar in Brazil. Preprints 2019, 2019060026 (doi: 10.20944/preprints201906.0026.v1).

Abstract

Among other applications, radar-rainfall (RR) and QPE (Quantitative Precipitation Estimation) based on radar reflectivity, dual polarization variables, and multi-sensor information, provide important information for land surface hydrology, such as flood forecasting. Therefore, we developed a flood alert system using rainfall-runoff model forced with RR and QPE, and tipping-bucket observations to forecast river water levels (using rating-curves). In this study, we used an hourly dataset from an S-Band dual-polarimetric radar with two tropical R(Z) relations based distrometer data, a polarimetric R(Z,ZDR) algorithm from the literature and a multi-sensor approach using radar, satellite and rain gauge. Two hydrological models were used and calibrated using observed discharge time-series. Although our previous studies indicated accurate RR-based simulations, in some cases floods were not detected when using catchment-lumped rainfall derived from multi-sensor QPE. In this study, we advance further in this subject using improved R(Z,ZDR) relations and QPE for the period of 2016-2017 and flood event-based rainfall-runoff calibration. Thus, we focused on the development (and timing) of floods in the Marrecas River can be complex and strongly related to storms spatiotemporal distribution. To explore this aspect, we also perform a first analysis in using RR in rainfall-runoff model with a nested catchment discretization.

Subject Areas

weather radar; quantitative precipitation estimation; remote sensing; hydrological applications

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