Dr. Muñoz-Ortiz, Enrique

The hydrology of scarce-data areas, such as the mountainous area of the Andes, is poorly known mainly owing to the lack of data. Global gridded climatological datasets (GGCDs) are becoming more precise and common, but the utility of these datasets and their applicability to complex hydrological systems are still not yet well determined. In this paper the reliability of a GGCD is evaluated as an alternative source to supply the lacking in situ observations, with the aim of studying the hydrology of a mountainous area in south-central Chile. The GGCDs are found to recover the climate variability in Andean areas, and partially recover the orographic effect caused by the mountains. A finding of practical relevance is that GGCDs could be considered as an adequate source for performing hydrological models and studies under high spatial variability and scarce-data environments such as the Andes.

Different sets of parameters and conceptualizations of a basin can give equally good results in terms of predefined objective functions. Therefore, a need exists to tackle equifinality and quantify the uncertainty bands of a model. In this paper we use the concepts of equifinality, identifiability and uncertainty to propose a simple method aimed at constraining the equifinal parameters and reducing the uncertainty bands of model outputs, and obtaining physically possible and reasonable models. Additionally, the uncertainty of equifinal solutions is quantified to estimate the amount by which output uncertainty can be reduced by knowing how to discard most of the equifinal solutions of a model. As a study case, a conceptual model of the Chillán basin in Chile is carried out. From the study it is concluded that using identifiability analysis makes it possible to constrain equifinal solutions with reduced uncertainty and realistic models, resulting in a framework that can be recommended to practitioners, especially due to the simplicity of the method.