Hydrological modeling of the Silala River basin. 2. Validation of hydrological fluxes with contemporary data

TitleHydrological modeling of the Silala River basin. 2. Validation of hydrological fluxes with contemporary data
AuthorGonzalo Yañez, Francisco Suárez, José Muñoz, Magdalena Lagos
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Recursos Críticos

Year of Publication2023
Journal TitleWIREs Water
Keywords

AbstractA companion paper in this Special Issue reviewed the development of a hydrological model of the Silala River basin, using long-term data (1969–1992) to determine the basin’s water balance and plausible groundwater recharge scenarios. In the context of a remote river basin with limited in situ data, this article reviews the potential of in situ and remotely collected data, available for a relatively short period (2018–2019), to validate various aspects of the hydrological model performance. These include the spatiotemporal evolution of snow cover areal fraction (SCF), actual evapotranspiration (ETa) in the basin’s extensive alluvial deposits, and wetland ETa. The observed SCF dynamics are well represented by the model at annual and monthly timescales, with monthly mean simulated SCF biases between −5.6% and 8%. At daily timescales, the model successfully captures snowstorm occurrence, although there are limitations on snow spatial patterning. Simulated ETa over alluvial deposits agrees with in situ observations during periods of high ETa, although the simulated values underestimate site-specific observations during low ETa periods, due to the presence of lateral subsurface flows. In the wetlands, satellite-based ETa estimates follow the seasonal pattern of in situ observations, but with values ~50% higher than those determined from elevation-corrected eddy-covariance (EC) measurements. Nonetheless, this difference is within the expected precision of the remote sensing method. Although based on a limited period, the validation results are encouraging, and demonstrate the utility of satellite tools and limited period in situ data for watersheds with scarce long-term data.
Doihttps://doi.org/10.1002/wat2.1696 
Corresponding AuthorFrancisco Suárez, fsuarez@ing.puc.cl