This paper provides a systematic review and practical workflow for Sensitivity Analysis (SA) in environmental modelling. It aims to clarify terminology, classify SA methods, and offer practical guidelines for their application. The review discusses the purpose and scope of SA, its relationship with uncertainty analysis, model calibration, diagnostic evaluation, dominant controls analysis, and robust decision-making. It also addresses the use of emulators in SA and presents a classification system of SA methods based on computational complexity and purpose. The paper outlines a workflow for applying SA, including key choices and considerations at each step. It emphasizes the importance of SA in understanding model behaviour, identifying influential factors, and supporting decision-making under uncertainty. The review highlights the need for a systematic approach to SA, with a focus on practical applications and best practices in environmental modelling. The paper is intended for a broad audience, including researchers and practitioners, and aims to stimulate discussion on good practices and future research directions in SA.This paper provides a systematic review and practical workflow for Sensitivity Analysis (SA) in environmental modelling. It aims to clarify terminology, classify SA methods, and offer practical guidelines for their application. The review discusses the purpose and scope of SA, its relationship with uncertainty analysis, model calibration, diagnostic evaluation, dominant controls analysis, and robust decision-making. It also addresses the use of emulators in SA and presents a classification system of SA methods based on computational complexity and purpose. The paper outlines a workflow for applying SA, including key choices and considerations at each step. It emphasizes the importance of SA in understanding model behaviour, identifying influential factors, and supporting decision-making under uncertainty. The review highlights the need for a systematic approach to SA, with a focus on practical applications and best practices in environmental modelling. The paper is intended for a broad audience, including researchers and practitioners, and aims to stimulate discussion on good practices and future research directions in SA.