Environmental models tend to require increasing computational time and resources as physical process descriptions are improved or new descriptions are incorporated. Many-query applications such as sensitivity analysis or model calibration usually require a large number of model evaluations leading to high computational demand. This often limits the feasibility of rigorous analyses. Here we present a fully automated sequential screening method that selects only informative parameters for a given model output. The method requires a number of model evaluations that is approximately 10 times the number of model parameters. It was tested using the mesoscale hydrologic model mHM in three hydrologically unique European river catchments. It identified around 20 informative parameters out of 52, with different informative parameters in each catchment. The screening method was evaluated with subsequent analyses using all 52 as well as only the informative parameters. Subsequent Sobol's global sensitivity analysis led to almost identical results yet required 40% fewer model evaluations after screening. mHM was calibrated with all and with only informative parameters in the three catchments. Model performances for daily discharge were equally high in both cases with Nash-Sutcliffe efficiencies above 0.82. Calibration using only the informative parameters needed just one third of the number of model evaluations. The universality of the sequential screening method was demonstrated using several general test functions from the literature. We therefore recommend the use of the computationally inexpensive sequential screening method prior to rigorous analyses on complex environmental models.
The study objective is to determine the structure of coordination abilities development in 5 th -7 th grade girls. materials and methods. The participants in the study were 5 th grade girls (n = 20), 6 th grade girls (n = 23), 7 th grade girls (n = 19). The study used the following methods: analysis and collation of scientific and methodological literature, general scientific methods of theoretical level, such as analogy, analysis, synthesis, abstraction, induction, as well as general scientific methods of empirical level: observation, testing, experiment. To evaluate motor preparedness, the study recorded the results of motor tests, body height and weight. The IBM SPSS 20 statistical analysis software was used to process the study materials. A factor analysis was performed, for which the study used principal component analysis with the rotation method: Variamax with Kaiser Normalization. results. The analysis of similarities shows that the most informative tests in the structure of motor preparedness of the 5 th grade girls are the following: test 11 "Evaluation of the ability for vestibular (statokinetic) stability. Running with turns" (.884), test 9 "Static equilibrium evaluation by E. Ya. Bondarevsky's method" (.826), test 6 "Evaluation of the sense of movement speed in sprinting" (.824); of the 6 th grade girls -test 11 "Evaluation of the ability for vestibular (statokinetic) stability. Running with turns" (0.884), test 9 "Static equilibrium evaluation by E. Ya. Bondarevsky's method" (.826), test 6 "Evaluation of the sense of movement speed in sprinting" (.824); of the 7 th grade girls -test 8 "Evaluation of the ability to differentiate movement speed (reproduction accuracy of running speed at 90% intensity of maximum)" (.902), test 11 "Evaluation of the ability for vestibular (statokinetic) stability. Running with turns" (.900), test 1 "30 m running (s)" (.869). conclusions. In the structure of coordination abilities of the 5 th -7 th grade girls, the most informative components are the sense and differentiation of running speed, vestibular stability in exercises that require static and dynamic equilibrium. To carry out pedagogical control of coordination preparedness of 5 th -7 th grade girls, the study recommends using the following tests: test 11 "Evaluation of the ability for vestibular (statokinetic) stability. Running with turns", test 9 "Static equilibrium evaluation by E. Ya. Bondarevsky's method", test 6 "Evaluation of the sense of movement speed in sprinting".
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