Calibration of a large-scale hydrological model using satellite-based soil moisture and evapotranspiration products
A considerable number of river basins around the world lack sufficient ground observations of hydro-meteorological data for effective water resources assessment and management. Several approaches can be developed to increase the quality and availability of data in these poorly gauged or ungauged...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2017-06-01
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Series: | Hydrology and Earth System Sciences |
Online Access: | https://www.hydrol-earth-syst-sci.net/21/3125/2017/hess-21-3125-2017.pdf |
Summary: | A considerable number of river basins around the world lack sufficient ground
observations of hydro-meteorological data for effective water resources
assessment and management. Several approaches can be developed to increase
the quality and availability of data in these poorly gauged or ungauged river
basins; among them, the use of Earth observations products has recently
become promising. Earth observations of various environmental variables can
be used potentially to increase knowledge about the hydrological processes in
the basin and to improve streamflow model estimates, via assimilation or
calibration. The present study aims to calibrate the large-scale hydrological model PCRaster GLOBal Water Balance
(PCR-GLOBWB) using satellite-based products of evapotranspiration and
soil moisture for the Moroccan Oum er Rbia River basin. Daily simulations at
a spatial resolution of 5 × 5 arcmin are performed with
varying parameters values for the 32-year period 1979–2010. Five different
calibration scenarios are inter-compared: (i) reference scenario using the
hydrological model with the standard parameterization, (ii) calibration using
in situ-observed discharge time series, (iii) calibration using the Global
Land Evaporation Amsterdam Model (GLEAM) actual evapotranspiration time
series, (iv) calibration using ESA Climate Change Initiative (CCI) surface
soil moisture time series and (v) step-wise calibration using GLEAM actual
evapotranspiration and ESA CCI surface soil moisture time series. The impact
on discharge estimates of precipitation in comparison with model parameters
calibration is investigated using three global precipitation products,
including ERA-Interim (EI), WATCH Forcing methodology applied to ERA-Interim reanalysis data (WFDEI) and Multi-Source
Weighted-Ensemble Precipitation data by merging gauge, satellite and
reanalysis data (MSWEP).
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Results show that GLEAM evapotranspiration and ESA CCI soil moisture may be
used for model calibration resulting in reasonable discharge estimates (NSE
values from 0.5 to 0.75), although better model performance is achieved when
the model is calibrated with in situ streamflow observations. Independent
calibration based on only evapotranspiration or soil moisture observations
improves model predictions to a lesser extent. Precipitation input affects
discharge estimates more than calibrating model parameters. The use of WFDEI
precipitation leads to the lowest model performances. Apart from the in situ
discharge calibration scenario, the highest discharge improvement is obtained
when EI and MSWEP precipitation products are used in combination with a
step-wise calibration approach based on evapotranspiration and soil moisture
observations. This study opens up the possibility of using globally available
Earth observations and reanalysis products of precipitation,
evapotranspiration and soil moisture in large-scale hydrological models to
estimate discharge at a river basin scale. |
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ISSN: | 1027-5606 1607-7938 |