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Data: An exploration of Bayesian identification of dominant hydrological mechanisms in ungauged catchments

Abstract: Purpose: These folders provide data from the paper submitted to wrr "An exploration of Bayesian identification of dominant hydrological mechanisms in ungauged catchments", 2021WR030705

1. Folder "exp1_2" : a) file "zreg_exp1.csv": regionalized flow indices principal components for the 16 "target" catchments.- b) file "zobs_exp1_2.csv": "observations" based flow indices principal components in the 92 catchments (for each "target" catchment the reamining 91 are used as "donor" catchments).- c) folder "z_sim_hydro_model": simulated flow indices principal componets derived from simulations provided by the ensembple of hydrological models FUSE. 2. Folder "fid_r_summary": .- a) file "overall": fraction of identifications and reliability for each experiment accross catchments and processes.- b) file "fid_r_exp3_4_accross_catch.xlsx": excel file with the following information accross the 16 target catchents and replicates per process: (i) true positives, (ii) false positives, (iii) false negatives, (iv) fraction of identifications, and (v) reliability; for different dispersion factors

Repositorio: Zenodo

 Año de publicación: 2021

 DOI: 10.5281/zenodo.5774699

 Citación completa: Prieto, C., Le Vine, N., Kavetski, D., Fenicia, F., Scheidegger, A. & Vitolo. C. (2021). Data: An exploration of Bayesian identification of dominant hydrological mechanisms in ungauged catchments. [Dataset]. (Version 1). Zenodo. https://doi.org/10.5281/zenodo.5774699

Autoría

LE VINE, NATALIYA

KAVETSKI, DMITRI

FENICIA, FABRIZIO

SCHEIDEGGER, ANDREAS

VITOLO, CLAUDIA