Journal
ENVIRONMENTAL MODELLING & SOFTWARE
Volume 119, Issue -, Pages 418-432Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.envsoft.2019.07.007
Keywords
Identifiability; Response surface; Non-uniqueness; Derivative based methods; Hessian; Emulation; Uncertainty
Categories
Funding
- Academy of Finland [305471]
- Emil Aaltonen Foundation funded project 'eat-less-water'
- U.S. Department of Energy's National Nuclear Security Administration [DE-NA-0003525]
Ask authors/readers for more resources
Identifiability is a fundamental concept in parameter estimation, and therefore key to the large majority of environmental modeling applications. Parameter identifiability analysis assesses whether it is theoretically possible to estimate unique parameter values from data, given the quantities measured, conditions present in the forcing data, model structure (and objective function), and properties of errors in the model and observations. In other words, it tackles the problem of whether the right type of data is available to estimate the desired parameter values. Identifiability analysis is therefore an essential technique that should be adopted more routinely in practice, alongside complementary methods such as uncertainty analysis and evaluation of model performance. This article provides an introductory overview to the topic. We recommend that any modeling study should document whether a model is non-identifiable, the source of potential non-identifiability, and how this affects intended project outcomes.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available