@Article{FalckMagTomVilDin:2015:CaStTo,
author = "Falck, Aline Schneider and Maggioni, Viviana and Tomasella, Javier
and Vila, Daniel Alejandro and Diniz, F{\'a}bio Luiz Rodrigues",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {} and
{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)}",
title = "Propagation of satellite precipitation uncertainties through a
distributed hydrologic model: a case study in the
Tocantins-Araguaia basin in Brazil",
journal = "Journal of Hydrology",
year = "2015",
volume = "527",
pages = "943--957",
keywords = "Tropical basin, Streamflow ensemble, Satellite rainfall,
Uncertainties precipitation.",
abstract = "This study investigates the applicability of error corrections to
satellite-based precipitation products in streamflow simulations.
A three-year time series (20082011) is considered across 19
sub-basins of the TocantinsAraguaia basin (764,000 km2), located
in the center-north region of Brazil. A raingauge network (24 h
accumulation) of approximately 300 collection points (~1 gauge
every 2500 km2) is used as reference for evaluating the following
four satellite rainfall products: the Tropical Rainfall Measuring
Mission real-time 3B42 product (3B42RT), the Climate Prediction
Center morphing technique (CMORPH), the Global Satellite Mapping
of Precipitation (GSMaP), and the NOAA Hydroestimator (HYDRO-E).
Ensemble streamflow simulations, for both dry and rainy seasons,
are obtained by forcing the Distributed Hydrological Model
developed by the Brazilian National Institute for Space Research
(MHDINPE) with the satellite rainfall products, corrected using a
two-dimensional stochastic satellite rainfall error model
(SREM2D). The ensemble simulations are evaluated using streamflow
output derived by forcing the model with reference rainfall gauge
data. SREM2D is able to correct for errors in the satellite
precipitation data by pushing the modeled streamflow ensemble
closer to the reference river discharge, when compared to the
simulations forced with uncorrected rainfall input. Ensemble
streamflow error statistics (MAE and RMSE) show a decreasing trend
as a function of the catchment area for all satellite products,
but the rainfall-to-streamflow error propagation does not show any
dependence on the basin size.",
doi = "10.1016/j.jhydrol.2015.05.042",
url = "http://dx.doi.org/10.1016/j.jhydrol.2015.05.042",
issn = "0022-1694",
language = "en",
urlaccessdate = "27 abr. 2024"
}