Towards a comprehensive assessment of model structural adequacy

Abstract

[1] The past decade has seen significant progress in characterizing uncertainty in environmental systems models, through statistical treatment of incomplete knowledge regarding parameters, model structure, and observational data. Attention has now turned to the issue of model structural adequacy (MSA, a term we prefer over model structure "error"). In reviewing philosophical perspectives from the groundwater, unsaturated zone, terrestrial hydrometeorology, and surface water communities about how to model the terrestrial hydrosphere, we identify several areas where different subcommunities can learn from each other. In this paper, we (a) propose a consistent and systematic "unifying conceptual framework" consisting of five formal steps for comprehensive assessment of MSA; (b) discuss the need for a pluralistic definition of adequacy; (c) investigate how MSA has been addressed in the literature; and (d) identify four important issues that require detailed attention-structured model evaluation, diagnosis of epistemic cause, attention to appropriate model complexity, and a multihypothesis approach to inference. We believe that there exists tremendous scope to collectively improve the scientific fidelity of our models and that the proposed framework can help to overcome barriers to communication. By doing so, we can make better progress toward addressing the question "How can we use data to detect, characterize, and resolve model structural inadequacies?"

Improving the representation of hydrologic processes in Earth System Models

“…This requires four main elements: (1) synthetic test problems; (2) process-based model evaluation, making extensive use of multivariate and multiscale data from research basins; (3) evaluating the interplay between predictive accuracy, computational efficiency, and transferability; and (4) understanding the information content in data and models, in order to improve how land models use the data that are available to them. We will discuss each of these elements in the following sections, building on the existing literature on benchmarking of hydrologic and land models [Abramowitz et al, 2008;Gupta et al, 2008;Blyth et al, 2011;Clark et al, 2011;Abramowitz, 2012;Gupta et al, 2012;Luo et al, 2012;Maxwell et al, 2014;Nearing and Gupta, 2014].…”

“…This issue relates to our expectations of model performance. Specifically, we ask the following related questions: how do we define a ''good'' model, and can we define meaningful benchmarks to evaluate the extent to which the model contains useful information [Kirchner et al, 1996;Schaefli and Gupta, 2007;Abramowitz et al, 2008;Blyth et al, 2011;Gupta et al, 2012;Nearing and Gupta, 2014].…”

Ecohydrological particle model based on representative domains

“…The water particles move realistically in the conjugated domains under the tested conditions. Also the mimicry of irrigation experiment based on directly measurable parameters corroborates the proposed model framework with regard to 15 structural adequacy (Gupta et al, 2012;Gupta and Nearing, 2014) and the intended objectives. Further testing should explore the model capabilities under various macropore settings in heterogeneous soils.…”

HESS Opinions: The complementary merits of competing modelling philosophies in hydrology

“…McGlynn et al, 2004) and modellers (e.g. Gupta et al, 2012) to describe the understanding of the system. When viewed as abstract conceptual understanding, the "conceptual" model refers to all models, regardless of complexity, since all models are necessarily an abstract depiction of nature.…”

“…Beven and Westerberg, 2011;Renard et al, 2011;Beven, 2013;McMillan et al, 2012;Kauffeldt et al, 2013;McMillan and Westerberg, 2015;Coxon et al, 2015) and insufficient model evaluation and testing (cf. Klemeš, 1986;Wagener, 2003;Clark et al, 2008;Gupta et al, 2008Gupta et al, , 2012Andréassian et al, 2009), models then often experience substantial performance decreases when used to predict the hydrological response for time periods they were not calibrated for (e.g. Seibert, 2003;Refsgaard and Henriksen, 2004;Kirchner, 2006;Coron et al, 2012;Gharari et al, 2013).…”