کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6411215 1629923 2015 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Propagation of satellite precipitation uncertainties through a distributed hydrologic model: A case study in the Tocantins-Araguaia basin in Brazil
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات فرآیندهای سطح زمین
پیش نمایش صفحه اول مقاله
Propagation of satellite precipitation uncertainties through a distributed hydrologic model: A case study in the Tocantins-Araguaia basin in Brazil
چکیده انگلیسی


- We generated ensembles of bias corrected satellite rainfall products by raingauges.
- We propagated the errors of satellite estimations using a stochastic model.
- We assessed the performance of our approach in streamflow monitoring in the basin.
- The proposed framework shows high potential for use in hydrological operations.

SummaryThis study investigates the applicability of error corrections to satellite-based precipitation products in streamflow simulations. A three-year time series (2008-2011) is considered across 19 sub-basins of the Tocantins-Araguaia 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 (MHD-INPE) 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.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Hydrology - Volume 527, August 2015, Pages 943-957
نویسندگان
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