A study of the influence of rainfall datasets' spatial resolution on stream simulation in Chaliyar River Basin, India

Rainfall is a vital input to model watershed hydrology, and the availability of numerous gridded and point-observed rainfall datasets poses a major challenge to the modellers to choose the appropriate data. This study compares three gridded rainfall datasets (i.e., 1° × 1°, 0.5° × 0.5°, and 0.25° ×...

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Veröffentlicht in:Journal of water and climate change 2022-12, Vol.13 (12), p.4234-4254
Hauptverfasser: Senan, Silpa, Thomas, Jobin, Vema, Vamsi Krishna, Jainet, P. J., Nizar, Sinan, Sivan, Shyama, Sudheer, K. P.
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Sprache:eng
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Zusammenfassung:Rainfall is a vital input to model watershed hydrology, and the availability of numerous gridded and point-observed rainfall datasets poses a major challenge to the modellers to choose the appropriate data. This study compares three gridded rainfall datasets (i.e., 1° × 1°, 0.5° × 0.5°, and 0.25° × 0.25°) and point rainfall observations of the India Meteorological Department (IMD) on the simulation of streamflow of a river basin in the southern Western Ghats (India) using the Soil and Water Assessment Tool (SWAT). The results show that the different datasets lead to different optimal model parameter values and consequent water balance components, significantly in groundwater hydrology. The 0.5° × 0.5° and 0.25° × 0.25° datasets result in comparable SWAT model performances (NSE = 0.75 and 0.70, respectively), probably due to the similarity in the rain gauge network density employed for deriving the datasets and also due to the spatial discretization threshold used for sub-watershed delineation. However, the coarser resolution data (1° × 1°) results in poor performance (NSE = 0.21). The study suggests that the choice of rainfall data depends on the spatial resolution of the data and the spatial discretization threshold while compromising the computational requirement vis-à-vis simulation accuracy.
ISSN:2040-2244
2408-9354
DOI:10.2166/wcc.2022.273