GHOMESHI M
Articles written in Journal of Earth System Science
Volume 129 All articles Published: 27 September 2020 Article ID 0201 Research Article
KHOSHCHEHREH M GHOMESHI M SHAHBAZI A
Accurate estimation of the precipitation characteristics, including the value, temporal pattern, and spatial distribution, plays a significant role in the input uncertainty reduction for rainfall-runoff models. In many basins, the improper spatial distribution of rain gauge stations or their limited historical recorded data causes many challenges, especially in heterogeneous catchments which due to the impact of the drastic geographical alterations on the rainfall distribution pattern, the cover of the ground stations cannot estimate the actual precipitation rate. This challenge can be potentially solved by adopting rainfall products as alternative or complementary data sources. In this research, three rainfall products (PERSIANN-CCS, CMORPH and ERA-Interim), were compared against rain gauge stations for calibration of a daily conceptual lumped rainfall-runoff model (CRFM) in a data-scarce and heterogeneous basin located in southwestern Iran. The results indicated that ERA-Interim has the best performance among other datasets. Better performance of this dataset compared to the
$\bf{Highlights}$
$\bullet$ Three rainfall products (PERSIANN-CCS, CMORPH and ERA-Interim), were compared against rain gauge stations for calibration of a daily conceptual lumped rainfall-runoff model in a data-scarce and heterogeneous basin located in southwestern Iran
$\bullet$ ERA-Interim has the best performance among other datasets and suggests a better estimation of the basin average as well as the temporal pattern of precipitation
$\bullet$ The performance of satellite-based data of CMORPH and PERSIANN-CCS is not acceptable in simulating the daily flow
$\bullet$ The performance of all datasets significantly reduces in spring
$\bullet$ All datasets were shown to perform better in simulating the flow in terms of the transition from dry to wet periods, rather than wet to dry periods
Volume 129, 2020
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