Abstract:Mathematical modelling is a well-accepted framework to evaluate the effects of wetlands on stream flow and watershed hydrology in general. Although the integration of wetland modules into a distributed hydrological model represents a costeffective way to make this assessment, the added value brought by landscape-specific modules to a model's ability to replicate basic hydrograph characteristics remains unclear. The objectives of this paper were the following: (i) to present the adaptation of PHYSITEL (a geographic information system) to parameterize isolated and riparian wetlands; (ii) to describe the integration of specific isolated wetland and riparian wetland modules into HYDROTEL, a distributed hydrological model; and (iii) to evaluate the performance of the updated modelling platform with respect to the capacity of replicating various hydrograph characteristics. To achieve this, two sets of simulations were performed (with and without wetland modules), and the added value was assessed at three river segments of the Becancour River watershed, Quebec, Canada, using six general goodness-of-fit indicators and 14 water flow criteria. A sensitivity analysis of the wetland module parameters was performed to characterize their impact on stream flows of the modelled watershed. Results of this study indicate the following: (i) integration of specific wetland modules can slightly increase the capacity of HYDROTEL to replicate basic hydrograph characteristics; and (ii) the updated modelling platform allows for the explicit assessment of the impact of wetlands (e.g. typology and location) on watershed hydrology.
Background Biomechanical and clinical parameters contribute very closely to functional evaluations of the knee joint. To better understand knee osteoarthritis joint function, the association between a set of knee biomechanical data and a set of clinical parameters of an osteoarthritis population (OA) is investigated in this study. Methods The biomechanical data used here are a set of characteristics derived from 3D knee kinematic patterns: flexion/extension, abduction/adduction, and tibial internal/external rotation measurements, all determined during gait recording. The clinical parameters include a KOOS questionnaire and the patient’s demographic characteristics. Canonical correlation analysis (CCA) is used (1) to evaluate the multivariate relationship between biomechanical data and clinical parameter sets, and (2) to cluster the most correlated parameters. Multivariate models were created within the identified clusters to determine the effect of each parameter’s subset on the other. The analyses were performed on a large database containing 166 OA patients. Results The CCA results showed meaningful correlations that gave rise to three different clusters. Multivariate linear models were found explaining the subjective clinical parameters by evaluating the biomechanical data contained within each cluster. Conclusion The results showed that a multivariate analysis of the clinical symptoms and the biomechanical characteristics of knee joint function allowed a better understanding of their relationships.
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