| Abstract: | The accuracy and sufficiency of precipitation data play a key role in environmental
research and hydrological models. They have a significant effect on the simulation results of
hydrological models; therefore, reliable hydrological simulation in data-scarce areas is a challenging
task. Advanced techniques can be utilized to improve the accuracy of satellite-derived rainfall
data, which can be used to overcome the problem of data scarcity. Our study aims to (1) assess the
accuracy of different satellite precipitation products such as Tropical Rainfall Measuring Mission
(TRMM 3B42 V7), Precipitation Estimation from Remotely Sensed Information using Artificial
Neural Networks (PERSIANN), PERSIANN-Climate Data Record (PERSIANN-CDR), and China
Meteorological Assimilation Driving Datasets for the SWAT Model (CMADS) by comparing them
with gauged rainfall data; and (2) apply them for runoff simulations for the Han River Basin in South
Korea using the SWAT model. Based on the statistical measures, that is, the proportion correct (PC),
the probability of detection (POD), the frequency bias index (FBI), the index of agreement (IOA),
the root-mean-square-error (RMSE), the mean absolute error (MAE), the coefficient of determination
(R2), and the bias, the rainfall data of the TRMM and CMADS show a better accuracy than those of
PERSIANN and PERSIANN-CDR when compared to rain gauge measurements. The TRMM and
CMADS data capture the spatial rainfall patterns in mountainous areas as well. The streamflow
simulated by the SWAT model using ground-based rainfall data agrees well with the observed
streamflow with an average Nash-Sutcliffe efficiency (NSE) of 0.68. The four satellite rainfall products
were used as inputs in the SWAT model for streamflow simulation and the results were compared.
The average R2, NSE, and percent bias (PBIAS) show that hydrological models using TRMM (R2 = 0.54,
NSE = 0.49, PBIAS = [-52.70–28.30%]) and CMADS (R2 = 0.44, NSE = 0.42, PBIAS = [-29.30–41.80%])
data perform better than those utilizing PERSIANN (R2 = 0.29, NSE = 0.13, PBIAS = [38.10–83.20%])
and PERSIANN-CDR (R2 = 0.25, NSE = 0.16, PBIAS = [12.70–71.20%]) data. Overall, the results
of this study are satisfactory, given that rainfall data obtained from TRMM and CMADS can be
used to simulate the streamflow of the Han River Basin with acceptable accuracy. Based on these
results, TRMM and CMADS rainfall data play important roles in hydrological simulations and
water resource management in the Han River Basin and in other regions with similar climate and
topographical characteristics. |