Name
Abstract | ||
|---|---|---|
Hydrological models are usually calibrated against observed streamflow (Q(obs)), which is not applicable for ungauged river basins. A few studies have exploited remotely sensed evapotranspiration (ETRS) for model calibration but their effectiveness on streamflow simulation remains uncertain. This paper investigates the use of ETRS in the hydrological calibration of a widely used land surface model coupled with a source-sink routing scheme and global optimization algorithm for 28 natural river basins. A baseline simulation is a setup based on the latest model developments and inputs. Sensitive parameters are determined for Q(obs) and ETRS-based model calibrations, respectively, through comprehensive sensitivity tests. The ETRS-based model calibration results in a mean Kling-Gupta Efficiency (KGE) value of 0.54 for streamflow simulation; 61% of the river basins have KGE > 0.5 in the validation period, which is consistent with the calibration period and provides a significant improvement over the baseline. Compared to Q(obs), the ETRS calibration produces better or similar streamflow simulations in 29% of the basins, while further significant improvements are achieved when either better ET or precipitation observations are used. Furthermore, the model results show better or similar performance in 68% of the basins and outperform the baseline simulations in 90% of the river basins using model parameters from the best ETRS calibration runs. This study confirms that with reasonable precipitation input, the ETRS-based spatially distributed calibration can efficiently tune parameters for better ET and streamflow simulations. The application of ETRS for global scale hydrological model calibration promises even better streamflow accuracy as the satellite-based ETRS observations continue to improve. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.3390/rs12030428 | REMOTE SENSING |
Keywords | Field | DocType |
hydrological model,calibration,remote sensing,evapotranspiration,ungauged river basins | Satellite,Remote sensing,Geology,Evapotranspiration,Calibration | Journal |
Volume | Issue | Citations |
12 | 3 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lulu Jiang | 1 | 0 | 0.34 |
| Huan Wu | 2 | 0 | 1.35 |
| Jing Tao | 3 | 0 | 0.34 |
| John S. Kimball | 4 | 490 | 50.16 |
| Lorenzo Alfieri | 5 | 0 | 0.34 |
| Xiuwan Chen | 6 | 33 | 18.04 |