Hydrological modelling has undergone constant growth with the increase in information processing capabilities. Hydrological models have traditionally been used to study the effects of climate change on management and land-use changes and for water resources planning, among other purposes. The aim of this study was to determine and analyse the advantages of the HBV and HYMOD models, which are commonly used in hydrology on daily and monthly time scales. A regional sensitivity analysis was used to compare the processes that take on greater importance at different time scales in the two models. As a result, it was found that quick precipitation–runoff processes prove to be better represented in the HBV model, while slow, time-aggregated processes are better represented by the HYMOD model. This study confirms that both models are adequate for rain-dominated basins, such as those of the study area. Additionally, the HBV model proved to be more robust in comparison to HYMOD.

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.

Choosing a model that suitably represents the characteristics of a watershed to simulate low flows is crucial, especially in watersheds whose main source of baseflow generation depends on groundwater storage and release. The goal of this investigation is to study the performance and representativeness of storage-release process modeling, considering aspects such as the topography and geology of the modeled watershed through regional sensitivity analysis, in order to improve low-flow prediction. To this end, four groundwater storage-release structures in various watersheds with different geological (fractured and sedimentary rock) and topographic domains (steep and gentle slopes) were analyzed. The results suggest that the two-reservoir structure with three runoff responses is suitable (better) for simulating low flows in watersheds with fractured geological characteristics and rugged or steep topography. The results also indicate that a one-reservoir model can be adequate for predicting low flows in watersheds with a sedimentary influence or flat topography.

The use of unmanned aerial vehicles (UAVs) is steadily increasing due to their capacity to capture terrain elevation data with remarkable precision and cost-effectiveness. Nonetheless, their application for estimating water surface elevations and submerged terrain, such as channel bathymetry, remains constrained. Consequently, the development of a digital terrain model that relies on UAV data during low-water periods assumes a more extensive dry channel surface area, thus alleviating the information gap regarding submerged terrain. The objective of this brief report is to validate a hydraulic model for flood calculation. To this end, a 1D steady-state hydrological model of the Ñuble River based on a UAV survey in the low-water period of 2016 was constructed in HEC-RAS v.5.0.3 and compared to water surface elevation observations of the flood on 24 June 2023. The model tends to overestimate the flood, but the errors are considered tolerable for flood calculation (on average, a 10.6% depth error was obtained for a 30-year return period flood); therefore, the hydraulic model derived from remote sensing seems to be an effective alternative for the construction of hydraulic models for flood studies.

Depending on the purpose of the study, aggregated hydrological models are preferred over distributed models because they provide acceptable results in terms of precision and are easy to run, especially in data scarcity scenarios. To obtain acceptable results in terms of hydrological process representativeness, it is necessary to understand and assess the models. In this study, the relative importance of the parameters of the Hydrologiska Byråns Vattenbalansavdelning (HBV) model is analyzed using sensitivity analysis to detect if the simulated processes represent the predominant hydrological processes at watershed scale. As a case study, four watersheds with different hydrological regimes (glacial and pluvial) and therefore different dominant processes are analyzed. The results show that in the case of the rivers with a glacial regime, the model performance depends highly on the snow module parameters, while in the case of the rivers with a pluvial regime, the model is sensitive to the soil and evapotranspiration modules. The results are directly related to the hydrological regime, which indicates that the HBV model, complemented by sensitivity analysis, is capable of both detecting and representing hydrological processes at watershed scale.