Journal of Water and Climate Change (Dec 2022)

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

  • Silpa Senan,
  • Jobin Thomas,
  • Vamsi Krishna Vema,
  • P. J. Jainet,
  • Sinan Nizar,
  • Shyama Sivan,
  • K. P. Sudheer

DOI
https://doi.org/10.2166/wcc.2022.273
Journal volume & issue
Vol. 13, no. 12
pp. 4234 – 4254

Abstract

Read online

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. HIGHLIGHTS The effects of various IMD gridded rainfall datasets and point rainfall observations on the simulation of streamflow of a river basin of the southern Western Ghats (India) was assessed.; The optimal parameter values for 1° × 1° rainfall data are far deviated from the point observation data.; The 0.25° × 0.25° and 0.5° × 0.5° have better model performances compared to 1° × 1° and point observations.;

Keywords