Abstract. The main objective of this study was to calibrate and validate the
eco-hydrological model Soil and Water Assessment Tool (SWAT) with
satellite-based actual evapotranspiration (AET) data from the Global Land
Evaporation Amsterdam Model (GLEAM_v3.0a) and from the Moderate Resolution
Imaging Spectroradiometer Global Evaporation (MOD16) for the Ogun River Basin
(20 292 km2) located in southwestern Nigeria. Three potential
evapotranspiration (PET) equations (Hargreaves, Priestley–Taylor and
Penman–Monteith) were used for the SWAT simulation of AET. The reference
simulations were the three AET variables simulated with SWAT before model
calibration took place. The sequential uncertainty fitting technique (SUFI-2)
was used for the SWAT model sensitivity analysis, calibration, validation and
uncertainty analysis. The GLEAM_v3.0a and MOD16 products were subsequently
used to calibrate the three SWAT-simulated AET variables, thereby obtaining
six calibrations–validations at a monthly timescale. The model performance
for the three SWAT model runs was evaluated for each of the 53 subbasins
against the GLEAM_v3.0a and MOD16 products, which enabled the best model run
with the highest-performing satellite-based AET product to be chosen. A
verification of the simulated AET variable was carried out by (i) comparing
the simulated AET of the calibrated model to GLEAM_v3.0b AET, which is a
product that has different forcing data than the version of GLEAM used for
the calibration, and (ii) assessing the long-term average annual and average
monthly water balances at the outlet of the watershed. Overall, the SWAT
model, composed of the Hargreaves PET equation and calibrated using the
GLEAM_v3.0a data (GS1), performed well for the simulation of AET and
provided a good level of confidence for using the SWAT model as a decision
support tool. The 95 % uncertainty of the SWAT-simulated variable
bracketed most of the satellite-based AET data in each subbasin. A validation
of the simulated soil moisture dynamics for GS1 was carried out using
satellite-retrieved soil moisture data, which revealed good agreement. The
SWAT model (GS1) also captured the seasonal variability of the water balance
components at the outlet of the watershed. This study demonstrated the potential to use remotely sensed
evapotranspiration data for hydrological model calibration and validation in
a sparsely gauged large river basin with reasonable accuracy. The novelty of
the study is the use of these freely available satellite-derived AET
datasets to effectively calibrate and validate an eco-hydrological model for
a data-scarce catchment.
SWAT Model Calibration and Uncertainty Analysis for Streamflow Prediction in the Kunwari River Basin, India, Using Sequential Uncertainty Fitting
