{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T01:48:00Z","timestamp":1776131280985,"version":"3.50.1"},"reference-count":69,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T00:00:00Z","timestamp":1773705600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012111","name":"Norsk Institutt for Vannforskning","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012111","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100011310","name":"Scotland Agriculture and Rural Economy Directorate","doi-asserted-by":"publisher","award":["2022-27"],"award-info":[{"award-number":["2022-27"]}],"id":[{"id":"10.13039\/100011310","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Environmental Modelling &amp; Software"],"published-print":{"date-parts":[[2026,5]]},"DOI":"10.1016\/j.envsoft.2026.106956","type":"journal-article","created":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T16:06:23Z","timestamp":1773763583000},"page":"106956","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Global sensitivity analysis workflows and rankings: A practical comparison for researchers"],"prefix":"10.1016","volume":"200","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1734-5833","authenticated-orcid":false,"given":"Ken B.","family":"Newman","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2737-1739","authenticated-orcid":false,"given":"Shaini","family":"Naha","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4915-8779","authenticated-orcid":false,"given":"Leah A.","family":"Jackson-Blake","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7064-638X","authenticated-orcid":false,"given":"Cairistiona","family":"Topp","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0110-9879","authenticated-orcid":false,"given":"Miriam","family":"Glendell","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0860-6475","authenticated-orcid":false,"given":"Adam","family":"Butler","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.envsoft.2026.106956_b1","series-title":"An Introductory Guide","article-title":"Uncertainty and sensitivity analysis for policy decision making","author":"Azzini","year":"2020"},{"key":"10.1016\/j.envsoft.2026.106956_b2","doi-asserted-by":"crossref","DOI":"10.1016\/j.envsoft.2021.105167","article-title":"Comparison of two sets of Monte Carlo estimators of Sobol\u2019indices","volume":"144","author":"Azzini","year":"2021","journal-title":"Environ. Model. Softw."},{"key":"10.1016\/j.envsoft.2026.106956_b3","series-title":"STICS Soil-Crop Model: Conceptual Framework, Equations and Uses","author":"Beaudoin","year":"2023"},{"issue":"1\u20132","key":"10.1016\/j.envsoft.2026.106956_b4","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.jhydrol.2005.07.007","article-title":"A manifesto for the equifinality thesis","volume":"320","author":"Beven","year":"2006","journal-title":"J. Hydrol."},{"issue":"1","key":"10.1016\/j.envsoft.2026.106956_b5","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1144\/SP408.3","article-title":"The uncertainty cascade in model fusion","volume":"408","author":"Beven","year":"2017","journal-title":"Geol. Soc. Lond. Spec. Publ."},{"key":"10.1016\/j.envsoft.2026.106956_b6","series-title":"Mathematical Statistics: Basic Ideas and Selected Topics, Volumes I-II Package","author":"Bickel","year":"2015"},{"issue":"6","key":"10.1016\/j.envsoft.2026.106956_b7","doi-asserted-by":"crossref","first-page":"771","DOI":"10.1016\/j.ress.2006.04.015","article-title":"A new uncertainty importance measure","volume":"92","author":"Borgonovo","year":"2007","journal-title":"Reliab. Eng. Syst. Saf."},{"issue":"1","key":"10.1016\/j.envsoft.2026.106956_b8","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1007\/s10588-021-09358-5","article-title":"Sensitivity analysis of agent-based models: a new protocol","volume":"28","author":"Borgonovo","year":"2022","journal-title":"Comput. Math. Organ. Theory"},{"issue":"5","key":"10.1016\/j.envsoft.2026.106956_b9","doi-asserted-by":"crossref","first-page":"925","DOI":"10.1111\/rssb.12052","article-title":"Transformations and invariance in the sensitivity analysis of computer experiments","volume":"76","author":"Borgonovo","year":"2014","journal-title":"J. R. Stat. Soc. Ser. B Stat. Methodol."},{"key":"10.1016\/j.envsoft.2026.106956_b10","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"10.1016\/j.envsoft.2026.106956_b11","series-title":"Classification and Regression Trees","author":"Breiman","year":"1983"},{"key":"10.1016\/j.envsoft.2026.106956_b12","series-title":"Conceptual Basis, Formalisations and Parameterization of the STICS Crop Model","first-page":"1","author":"Brisson","year":"2009"},{"issue":"6","key":"10.1016\/j.envsoft.2026.106956_b13","doi-asserted-by":"crossref","first-page":"2923","DOI":"10.5194\/hess-21-2923-2017","article-title":"Ensemble reconstruction of spatio-temporal extreme low-flow events in France since 1871","volume":"21","author":"Caillouet","year":"2017","journal-title":"Hydrol. Earth Syst. Sci."},{"issue":"10","key":"10.1016\/j.envsoft.2026.106956_b14","doi-asserted-by":"crossref","first-page":"1509","DOI":"10.1016\/j.envsoft.2006.10.004","article-title":"An effective screening design for sensitivity analysis of large models","volume":"22","author":"Campolongo","year":"2007","journal-title":"Environ. Model. Softw."},{"issue":"1\u20132","key":"10.1016\/j.envsoft.2026.106956_b15","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1016\/j.ecolmodel.2005.10.045","article-title":"The role of sensitivity analysis in ecological modelling","volume":"203","author":"Cariboni","year":"2007","journal-title":"Ecol. Model."},{"key":"10.1016\/j.envsoft.2026.106956_b16","series-title":"European Commission better regulation toolbox","author":"Commission","year":"2023"},{"key":"10.1016\/j.envsoft.2026.106956_b17","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.envsoft.2013.07.009","article-title":"Global sensitivity analysis in wastewater applications: A comprehensive comparison of different methods","volume":"49","author":"Cosenza","year":"2013","journal-title":"Environ. Model. Softw."},{"key":"10.1016\/j.envsoft.2026.106956_b18","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1016\/j.compbiolchem.2012.10.007","article-title":"Parameter sensitivity analysis of stochastic models: Application to catalytic reaction networks","volume":"42","author":"Damiani","year":"2013","journal-title":"Comput. Biol. Chem."},{"key":"10.1016\/j.envsoft.2026.106956_b19","doi-asserted-by":"crossref","DOI":"10.1016\/j.jtbi.2022.111159","article-title":"Multi-method global sensitivity analysis of mathematical models","volume":"546","author":"Dela","year":"2022","journal-title":"J. Theoret. Biol."},{"issue":"14","key":"10.1016\/j.envsoft.2026.106956_b20","article-title":"Multi-objective optimization for Pareto frontier sensitivity analysis in power systems","volume":"16","author":"Giannelos","year":"2024","journal-title":"Sustain. (2071-1050)"},{"key":"10.1016\/j.envsoft.2026.106956_b21","series-title":"Surrogates: Gaussian Process Modeling, Design, and Optimization for the Applied Sciences","author":"Gramacy","year":"2020"},{"key":"10.1016\/j.envsoft.2026.106956_b22","series-title":"Robust Uncertainty Quantification and Scalable Computation for Computer Models with Massive Output","author":"Gu","year":"2016"},{"issue":"11","key":"10.1016\/j.envsoft.2026.106956_b23","doi-asserted-by":"crossref","first-page":"8692","DOI":"10.1029\/2018WR022668","article-title":"Revisiting the basis of sensitivity analysis for dynamical earth system models","volume":"54","author":"Gupta","year":"2018","journal-title":"Water Resour. Res."},{"issue":"3","key":"10.1016\/j.envsoft.2026.106956_b24","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1007\/s10994-021-05946-3","article-title":"Aleatoric and epistemic uncertainty in machine learning: An introduction to concepts and methods","volume":"110","author":"H\u00fcllermeier","year":"2021","journal-title":"Mach. Learn."},{"issue":"7","key":"10.1016\/j.envsoft.2026.106956_b25","doi-asserted-by":"crossref","first-page":"5382","DOI":"10.1002\/2016WR020132","article-title":"Are our dynamic water quality models too complex? A comparison of a new parsimonious phosphorus model, S imply P, and INCA-P","volume":"53","author":"Jackson-Blake","year":"2017","journal-title":"Water Resour. Res."},{"issue":"10\u201311","key":"10.1016\/j.envsoft.2026.106956_b26","doi-asserted-by":"crossref","first-page":"1126","DOI":"10.1016\/j.ress.2005.11.047","article-title":"Sensitivity analysis in presence of model uncertainty and correlated inputs","volume":"91","author":"Jacques","year":"2006","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"10.1016\/j.envsoft.2026.106956_b27","series-title":"An Introduction to Statistical Learning: With Applications in R","author":"James","year":"2021"},{"key":"10.1016\/j.envsoft.2026.106956_b28","series-title":"Predictability and Nonlinear Modelling in Natural Sciences and Economics","first-page":"334","article-title":"Monte Carlo estimation of uncertainty contributions from several independent multivariate sources","author":"Jansen","year":"1994"},{"issue":"10","key":"10.1016\/j.envsoft.2026.106956_b29","doi-asserted-by":"crossref","first-page":"4323","DOI":"10.5194\/hess-23-4323-2019","article-title":"Inherent benchmark or not? Comparing Nash\u2013Sutcliffe and Kling\u2013Gupta efficiency scores","volume":"23","author":"Knoben","year":"2019","journal-title":"Hydrol. Earth Syst. Sci."},{"issue":"7","key":"10.1016\/j.envsoft.2026.106956_b30","doi-asserted-by":"crossref","first-page":"1135","DOI":"10.1016\/j.ress.2008.05.006","article-title":"Monte Carlo evaluation of derivative-based global sensitivity measures","volume":"94","author":"Kucherenko","year":"2009","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"10.1016\/j.envsoft.2026.106956_b31","series-title":"Monte Carlo and Quasi-Monte Carlo Methods: MCQMC, Leuven, Belgium, April 2014","first-page":"455","article-title":"Derivative-based global sensitivity measures and their link with Sobol\u2019sensitivity indices","author":"Kucherenko","year":"2016"},{"issue":"1","key":"10.1016\/j.envsoft.2026.106956_b32","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1029\/1998WR900018","article-title":"Evaluating the use of \u201cgoodness-of-fit\u201d measures in hydrologic and hydroclimatic model validation","volume":"35","author":"Legates","year":"1999","journal-title":"Water Resour. Res."},{"issue":"6","key":"10.1016\/j.envsoft.2026.106956_b33","doi-asserted-by":"crossref","first-page":"597","DOI":"10.1061\/(ASCE)1084-0699(2006)11:6(597)","article-title":"Evaluation of the Nash\u2013Sutcliffe efficiency index","volume":"11","author":"McCuen","year":"2006","journal-title":"J. Hydrol. Eng."},{"issue":"2","key":"10.1016\/j.envsoft.2026.106956_b34","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1080\/00401706.1991.10484804","article-title":"Factorial sampling plans for preliminary computational experiments","volume":"33","author":"Morris","year":"1991","journal-title":"Technometrics"},{"key":"10.1016\/j.envsoft.2026.106956_b35","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.ecolmodel.2016.09.008","article-title":"Sensitivity analysis of a sensitivity analysis: We are likely overlooking the impact of distributional assumptions","volume":"340","author":"Paleari","year":"2016","journal-title":"Ecol. Model."},{"key":"10.1016\/j.envsoft.2026.106956_b36","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1016\/j.envsoft.2016.02.008","article-title":"Sensitivity analysis of environmental models: A systematic review with practical workflow","volume":"79","author":"Pianosi","year":"2016","journal-title":"Environ. Model. Softw."},{"key":"10.1016\/j.envsoft.2026.106956_b37","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.envsoft.2015.01.004","article-title":"A simple and efficient method for global sensitivity analysis based on cumulative distribution functions","volume":"67","author":"Pianosi","year":"2015","journal-title":"Environ. Model. Softw."},{"issue":"22","key":"10.1016\/j.envsoft.2026.106956_b38","doi-asserted-by":"crossref","first-page":"3991","DOI":"10.1002\/hyp.10968","article-title":"Understanding the time-varying importance of different uncertainty sources in hydrological modelling using global sensitivity analysis","volume":"30","author":"Pianosi","year":"2016","journal-title":"Hydrol. Process."},{"issue":"1\u20132","key":"10.1016\/j.envsoft.2026.106956_b39","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.jhydrol.2011.09.034","article-title":"A downward structural sensitivity analysis of hydrological models to improve low-flow simulation","volume":"411","author":"Pushpalatha","year":"2011","journal-title":"J. Hydrol."},{"issue":"2","key":"10.1016\/j.envsoft.2026.106956_b40","doi-asserted-by":"crossref","DOI":"10.1615\/Int.J.UncertaintyQuantification.2021038133","article-title":"A comprehensive comparison of total-order estimators for global sensitivity analysis","volume":"12","author":"Puy","year":"2022","journal-title":"Int. J. Uncertain. Quantif."},{"key":"10.1016\/j.envsoft.2026.106956_b41","series-title":"R: A Language and Environment for Statistical Computing","author":"R Core Team","year":"2024"},{"key":"10.1016\/j.envsoft.2026.106956_b42","series-title":"Agent-Based and Individual-Based Modeling: A Practical Introduction","author":"Railsback","year":"2019"},{"issue":"1","key":"10.1016\/j.envsoft.2026.106956_b43","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1002\/2015WR017558","article-title":"A new framework for comprehensive, robust, and efficient global sensitivity analysis: 1. Theory","volume":"52","author":"Razavi","year":"2016","journal-title":"Water Resour. Res."},{"key":"10.1016\/j.envsoft.2026.106956_b44","doi-asserted-by":"crossref","DOI":"10.1016\/j.envsoft.2020.104954","article-title":"The future of sensitivity analysis: An essential discipline for systems modeling and policy support","volume":"137","author":"Razavi","year":"2021","journal-title":"Environ. Model. Softw."},{"issue":"2","key":"10.1016\/j.envsoft.2026.106956_b45","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1016\/S0010-4655(02)00280-1","article-title":"Making best use of model evaluations to compute sensitivity indices","volume":"145","author":"Saltelli","year":"2002","journal-title":"Comput. Phys. Comm."},{"issue":"3","key":"10.1016\/j.envsoft.2026.106956_b46","doi-asserted-by":"crossref","first-page":"579","DOI":"10.1111\/0272-4332.00040","article-title":"Sensitivity analysis for importance assessment","volume":"22","author":"Saltelli","year":"2002","journal-title":"Risk Anal."},{"key":"10.1016\/j.envsoft.2026.106956_b47","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.envsoft.2019.01.012","article-title":"Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices","volume":"114","author":"Saltelli","year":"2019","journal-title":"Environ. Model. Softw."},{"key":"10.1016\/j.envsoft.2026.106956_b48","series-title":"Five ways to ensure that models serve society: a manifesto","author":"Saltelli","year":"2020"},{"key":"10.1016\/j.envsoft.2026.106956_b49","series-title":"Sensitivity Analysis","first-page":"80","author":"Saltelli","year":"2000"},{"key":"10.1016\/j.envsoft.2026.106956_b50","series-title":"Global Sensitivity Analysis: The Primer","author":"Saltelli","year":"2008"},{"key":"10.1016\/j.envsoft.2026.106956_b51","first-page":"377","article-title":"Sensitivity analysis as an ingredient of modeling","author":"Saltelli","year":"2000","journal-title":"Statist. Sci."},{"key":"10.1016\/j.envsoft.2026.106956_b52","series-title":"The Design and Analysis of Computer Experiments","author":"Santner","year":"2018"},{"issue":"20","key":"10.1016\/j.envsoft.2026.106956_b53","doi-asserted-by":"crossref","first-page":"17231","DOI":"10.1007\/s00521-022-07372-5","article-title":"New hybrid GR6J-wavelet-based genetic algorithm-artificial neural network (GR6j-WGANN) conceptual-data-driven model approaches for daily rainfall\u2013runoff modelling","volume":"34","author":"Sezen","year":"2022","journal-title":"Neural Comput. Appl."},{"key":"10.1016\/j.envsoft.2026.106956_b54","first-page":"407","article-title":"Sensitivity estimates for nonlinear mathematical models","volume":"1","author":"Sobo\u013a","year":"1993","journal-title":"Math. Model. Comput. Exp."},{"issue":"10","key":"10.1016\/j.envsoft.2026.106956_b55","doi-asserted-by":"crossref","first-page":"3009","DOI":"10.1016\/j.matcom.2009.01.023","article-title":"Derivative based global sensitivity measures and their link with global sensitivity indices","volume":"79","author":"Sobol","year":"2009","journal-title":"Math. Comput. Simulation"},{"key":"10.1016\/j.envsoft.2026.106956_b56","doi-asserted-by":"crossref","first-page":"739","DOI":"10.1016\/j.jhydrol.2015.02.013","article-title":"Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications","volume":"523","author":"Song","year":"2015","journal-title":"J. Hydrol."},{"issue":"2","key":"10.1016\/j.envsoft.2026.106956_b57","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1080\/00401706.1987.10488205","article-title":"Large sample properties of simulations using Latin hypercube sampling","volume":"29","author":"Stein","year":"1987","journal-title":"Technometrics"},{"key":"10.1016\/j.envsoft.2026.106956_b58","doi-asserted-by":"crossref","DOI":"10.1016\/j.envsoft.2024.105977","article-title":"An annotated timeline of sensitivity analysis","volume":"174","author":"Tarantola","year":"2024","journal-title":"Environ. Model. Softw."},{"issue":"1","key":"10.1016\/j.envsoft.2026.106956_b59","doi-asserted-by":"crossref","first-page":"5","DOI":"10.18564\/jasss.2857","article-title":"Which sensitivity analysis method should I use for my agent-based model?","volume":"19","author":"Ten Broeke","year":"2016","journal-title":"J. Artif. Soc. Soc. Simul."},{"key":"10.1016\/j.envsoft.2026.106956_b60","series-title":"Rpart: Recursive partitioning and regression trees (p. 4.1. 24)[Dataset]","author":"Therneau","year":"2023"},{"key":"10.1016\/j.envsoft.2026.106956_b61","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.earscirev.2019.04.006","article-title":"What has Global Sensitivity Analysis ever done for us? A systematic review to support scientific advancement and to inform policy-making in earth system modelling","volume":"194","author":"Wagener","year":"2019","journal-title":"Earth-Sci. Rev."},{"key":"10.1016\/j.envsoft.2026.106956_b62","doi-asserted-by":"crossref","DOI":"10.1016\/j.envsoft.2021.105206","article-title":"The chaos in calibrating crop models: Lessons learned from a multi-model calibration exercise","volume":"145","author":"Wallach","year":"2021","journal-title":"Environ. Model. Softw."},{"issue":"5\u20136","key":"10.1016\/j.envsoft.2026.106956_b63","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1051\/agro:19980501","article-title":"STICS: a generic model for the simulation of crops and their water and nitrogen balances. I. Theory and parameterization applied to wheat and corn","volume":"18","author":"Brisson","year":"1998","journal-title":"Agronomie"},{"key":"10.1016\/j.envsoft.2026.106956_b64","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.envsoft.2017.05.002","article-title":"The suite of lumped GR hydrological models in an R package","volume":"94","author":"Coron","year":"2017","journal-title":"Environ. Model. Softw."},{"issue":"2","key":"10.1016\/j.envsoft.2026.106956_b65","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1002\/gdj3.78","article-title":"HadUK-Grid\u2014A new UK dataset of gridded climate observations","volume":"6","author":"Hollis","year":"2019","journal-title":"Geosci. Data J."},{"issue":"2","key":"10.1016\/j.envsoft.2026.106956_b66","doi-asserted-by":"crossref","first-page":"282","DOI":"10.1093\/bioinformatics\/btaa662","article-title":"treeheatr: an R package for interpretable decision tree visualizations","volume":"37","author":"Le","year":"2021","journal-title":"Bioinformatics"},{"key":"10.1016\/j.envsoft.2026.106956_b67","series-title":"Hydrologie Appliqu\u00e9e aux Petits Bassins Ruraux","author":"Michel","year":"1987"},{"issue":"2","key":"10.1016\/j.envsoft.2026.106956_b68","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1175\/1520-0493(1972)100<0081:OTAOSH>2.3.CO;2","article-title":"On the assessment of surface heat flux and evaporation using large-scale parameters","volume":"100","author":"Priestley","year":"1972","journal-title":"Mon. Weather Rev."},{"key":"10.1016\/j.envsoft.2026.106956_b69","series-title":"Global sensitivity analysis for choosing the main soil parameters of a crop model to be determined","author":"Varella","year":"2012"}],"container-title":["Environmental Modelling &amp; Software"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1364815226001039?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1364815226001039?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T01:00:24Z","timestamp":1776128424000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1364815226001039"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5]]},"references-count":69,"alternative-id":["S1364815226001039"],"URL":"https:\/\/doi.org\/10.1016\/j.envsoft.2026.106956","relation":{},"ISSN":["1364-8152"],"issn-type":[{"value":"1364-8152","type":"print"}],"subject":[],"published":{"date-parts":[[2026,5]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Global sensitivity analysis workflows and rankings: A practical comparison for researchers","name":"articletitle","label":"Article Title"},{"value":"Environmental Modelling & Software","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.envsoft.2026.106956","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"106956"}}