Emulation techniques for the reduction and sensitivity analysis of complex environmental models

Emulation (also denoted as metamodelling in the literature) is an important and expanding area of research and represents one of the major advances in the study of complex mathematical models, with applications ranging from model reduction to sensitivity analysis. Despite the stunning increase in computing power over recent decades, computational limitations remain a major barrier to the effective and systematic use of large-scale, process-based simulation models in rational environmental decision-making. Whereas complex models may provide clear advantages when the goal of the modelling exercise is to enhance our understanding of the natural processes, they introduce problems of model identifiability caused by over-parameterization and suffer from high computational burden when used in management and planning problems, i.e. when they are combined with optimization routines. Therefore, a combination of techniques for complex model reduction with procedures for data assimilation and learning-based control could help to bridge the gap between science and the operational use of models for decision-making. Furthermore sensitivity analysis is a well known and established tool for evaluating robustness of model based results in management and planning, and is often performed in tandem with emulation. Indeed, emulators provide an efficient means for doing a sensitivity analysis for large and expensive models.This thematic issue aims at providing a guide and reference for modellers in choosing appropriate emulation modelling approaches and understanding their features. Tools and applications of sensitivity analysis in the context of environmental modelling are also addressed, which is a typical complement of emulation in most applications. We hope that this thematic issue provides a useful benchmark in the academic literature for this important and expanding area of research, and will create an opportunity for dialogue between methodological and user-focused research.