Thu Aug 14, F. Flechtner
• Sorted by Date • Sorted by Last Name of First Author •
Zheng, Dongxue, Zhu, Wenbin, Han, Yan, and Lv, Aifeng, 2025. A novel remote sensing-based calibration and validation method for distributed hydrological modelling in ungauged basins. Journal of Hydrology, 658:133119, doi:10.1016/j.jhydrol.2025.133119.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2025JHyd..65833119Z,
author = {{Zheng}, Dongxue and {Zhu}, Wenbin and {Han}, Yan and {Lv}, Aifeng},
title = "{A novel remote sensing-based calibration and validation method for distributed hydrological modelling in ungauged basins}",
journal = {Journal of Hydrology},
keywords = {Ungauged basin, Hydrology model, Remote sensing, Lake water storage change, Evapotranspiration, Bayesian inference},
year = 2025,
month = sep,
volume = {658},
eid = {133119},
pages = {133119},
abstract = "{Distributed hydrological models allow spatial estimates of the main
components of the water cycle. Consequently, they have been
widely used in various applications. However, in-situ runoff
observations are usually required to calibrate and validate
these models, which largely limits their application in ungauged
or poorly gauged basins. Satellite remote sensing (RS) provides
temporally and spatially continuous data of water-related
information, which makes it hold great potential to improve
hydrological modeling. Against this background, we developed a
novel RS-based calibration and validation method in this study
for distributed hydrological modelling in ungauged basins. This
method was demonstrated with the Soil and Water Assessment Tool
(SWAT) model in Hala Lake basin, a closed watershed in Qinghai
Province of China. The SWAT model was calibrated with RS-based
terrestrial evapotranspiration (ET) products and validated with
the lake water storage change (LWSC) retrieved from multi-
mission satellite data and the basin water storage change
retrieved from the Gravity Recovery and Climate Experiment
(GRACE). The model calibration results demonstrated a Nash-
Sutcliffe Efficiency (NSE) of 0.7 or higher in most sub-basins,
proving the usability of RS products. The simulated ET results
showed good agreement with two RS products, with an R$^{2}$
value of 0.8. Additionally, comparisons with GRACE data further
validated the reliability of this method. This study
demonstrates the significant potential in using multi-source RS
satellite data for calibrating and validating models, as well as
estimating monthly or annual runoff time series in data-scarce
or ungauged basins.}",
doi = {10.1016/j.jhydrol.2025.133119},
adsurl = {https://ui.adsabs.harvard.edu/abs/2025JHyd..65833119Z},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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Thu Aug 14, F. Flechtner