On the evaluation of soil erosion models:Are we doing enough?

Batista, Pedro V.G. and Davies, Jessica and Silva, Marx L.N. and Quinton, John N. (2019) On the evaluation of soil erosion models:Are we doing enough? Earth-Science Reviews, 197. ISSN 0012-8252

[img]
Text (Batista et al 2019 in press)
Batista_et_al_2019_in_press.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (1MB)

Abstract

As any model of real-world phenomena, soil erosion models must be tested against empirical evidence to have their performance evaluated. This is critical to develop knowledge and confidence in model predictions. However, evaluating soil erosion models is complicated due to the uncertainties involved in the estimation of model parameters and measurements of system responses. Here, we undertake a term co-occurrence analysis to investigate how model evaluation is approached in soil erosion research. The analysis illustrates how model testing is often neglected, and how model evaluation topics are segregated from current research interests. We perform a meta-analysis of model performance to understand the mechanisms that influence model predictive accuracy. Results indicate that different models do not systematically outperform each other, and that calibration seems to be the main mechanism of model improvement. We review how soil erosion models have been evaluated at different temporal and spatial scales, focusing on the methods, assumptions, and data used for model testing. We discuss the implications of uncertainty and equifinality in soil erosion models, and implement a case study of uncertainty assessment that enables models to be tested as hypotheses. A comment on the way forward for the evaluation of erosion models is presented, discussing philosophical aspects of hypothesis testing in environmental modelling. We refute the notion that soil erosion models can be validated, and emphasize the necessity of defining fit-for-purpose tests, based on multiple sources of data, that allow for a broad investigation of model usefulness and consistency.

Item Type:
Journal Article
Journal or Publication Title:
Earth-Science Reviews
Additional Information:
This is the author’s version of a work that was accepted for publication in Earth-Science Reviews. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Earth-Science Reviews, 197, 2019 DOI: 10.1016/j.earscirev.2019.102898
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1900
Subjects:
ID Code:
135811
Deposited By:
Deposited On:
01 Aug 2019 08:20
Refereed?:
Yes
Published?:
Published
Last Modified:
22 Sep 2020 04:40