Hydrological study reveals enhanced runoff simulation accuracy with dense CubeSat sampling in a mountainous watershed, highlighting its value for regional flood forecasting.
Key Points
To evaluate the impact of satellite temporal sampling uncertainty on hydrological runoff simulation in a mountainous watershed using multi-sensor satellite constellations.
Analysed five GPM sensors (GMI, SSMIS, MHS, AMSR2, ATMS) and three TROPICS CubeSats (T3, T5, T6) individually and in multi-sensor combinations over the Ranikhola watershed, India.
Collocated sensor overpass times with IMERG precipitation data to generate rainfall inputs for the lumped HYSIM hydrological model over the 2016–2020 period.
The combined TROPICS configuration (T3–T5–T6) achieved the highest runoff accuracy, with NSE = 0.6983, R² = 0.9568, RMSE = 7.75 m³ s⁻¹, and MAE = 5.62 m s⁻¹.
The sparse two-sensor GMI–SSMIS combination performed poorly, yielding an NSE of −1.7385 and an RMSE of 23.36 m³ s⁻¹.
The TROPICS constellation supplied over 12 overpasses per day, compared to approximately 1 to 2.5 daily overpasses for individual GPM sensors.