Data from the publication "Identification of dominant hydrological mechanisms using Bayesian inference, multiple statistical hypothesis testing and flexible models, WRR, doi: 10.1029/2020WR028338"
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Data: Identification of dominant hydrological mechanisms using Bayesian inference, multiple statistical hypothesis testing and flexible models, WRR, doi: 10.1029/2020WR028338 Cristina Prieto; Dmitri Kavetski; Nataliya Le Vine; Cesar Alvarez; Raul Medina !===== ! Purpose: These folders provide data from the publication Prieto et al 2021 ! Prieto C, Kavetski D, Le Vine N, Alvarez C, and Medina R (2021). Identification of dominant hydrological mechanisms using Bayesian inference, multiple statistical hypothesis testing and flexible models, Water Resources Research, doi: 10.1029/2020WR028338 !===== 1. Folder "obs": a) file "c8z1_data_obs.txt": observed hydrological data for the Leizaran catchment b) file "leizaran_mecha_identification.csv": number of bootstraps where a mecha is identified as dominant for the different time periods and significance levels 2. Folder "synthetic": a) folder "reliability_and_power__low_error_med_error_high_error": txt files with the following info: (i) reliability, (ii) power, (iii) true positives, (iv) false positives, and (v) false negatives; for different significance levels, error levels and processes, and across all error levels. Processes are abbreviated as follows: a1 = unsaturated zone, a2 = saturated zone, esoil = evaporation, interf = interflow, perc = percolation, rr = surface runoff, and rout = routing. E.g. file "alpha_r_p_tp_fp_fn_low_error_a1.txt" contains the following information for the lowest error, for the processes in the unsaturated zone: first column = significance level, alpha; second column = reliability, r; third column = power, p; fourth column = number of true positives, tp (out of 50); fifth column = number of false positives, fp (out of 50); sixth column = number of false negatives, fn (out of 50)
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Publication Details
Subfield
Environmental Engineering
Field
Environmental Science
Domain
Physical Sciences
Confidence Score
61%
Source
Open Alex