Evaluation of daily gridded meteorological datasets for hydrological modeling in data-sparse basins of the largest lake in Southeast Asia

Abstract

Study region: Tonle Sap Lake (TSL) Basin in Cambodia. Study focus: The development and application of hydrological models for data-sparse basins are hindered by the limited hydro-meteorological data. Although gridded meteorological products are alternatively considered in many studies, the validation of the products with limited point observations overlooks the original spatiotemporal characteristics, thus leading to a selection of datasets with high uncertainty. Here, we evaluated seven gridded meteorological datasets of rainfall and air temperature covering the data-sparse Tonle Sap Lake Basin by employing the statistical approach based on the bilinear-interpolation method and hydrological approach using the SWAT model, which ensures the reliable estimates of streamflow and evapotranspiration. New hydrological insights for the region: The results of the statistical approach indicate that APHRODITE, ERA5, TRMM and IMERG-based precipitation and CPC and SA-OBS-based air temperature performed comparably well (R ≥ 0.75) with the gauged data. However, ERA5-based streamflow performed relatively poor, while SWAT driven by APHRODITE underestimated satellite-based evapotranspiration, indicating the underestimation of basin-wide precipitation by APHRODITE. Although TRMM and IMERG provide more reliable estimation of streamflow and evapotranspiration, slightly better performance and a higher spatial resolution of IMERG dataset suggest that IMERG precipitation is superior for basin-wide hydrological modeling and impact assessment. These findings showed that statistical comparisons with gauge-data and hydrological evaluation of streamflow are not enough to justify the reliability of each gridded dataset.

Keywords

• The Tonle Sap Lake Basin
• Gridded datasets
• Streamflow
• Evapotranspiration
• SWAT model