Towards a coherent philosophy for modelling the environment

By Keith Beven. Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, 2002

425 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Environmental Engineering, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/fa45a2726b8559ddc0d315e238ff2c6854d50670

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Citations in the corpus

Modelling guidelinesterminology and guiding principles (2004, background): “As Beven [9] argues we need to distinguish between”
GLUE: 20 years on (2014, background): “As a paper, however, it had to do more than comment and made the suggestion that future work in this area should try to assess the uncertainty associated with the predictions of distributed models (refer also to Beven, 2001, 2002a,2002b).”
Modelling everything everywhere: a new approach to decision-making for water management under uncertainty (2012, background): “Models can be treated as hypotheses about how the catchment system functions (Beven, 2002, 2009, 2010).”
Searching for the Holy Grail of scientific hydrology: Q t =( S, R, Δt ) A as closure (2006, methodology): “…is possible at all) would be the deﬁning act of scientiﬁc hydrology (it would not be the end of scientiﬁc hydrology as there would still be some interesting problems associated with applying that solution to di ﬀ erent applications in di ﬀ erent places, see, for example, Beven, 2000, 2002).”
Confidence, uncertainty and decision-support relevance in climate predictions (2007, background): “It is a well known and widely discussed statistical problem that computer models of natural systems are inadequate (Oreskes et al. 1994; Kennedy & O’Hagan 2001; Bevan 2002; Chatfield 2002, 2003; Smith 2002) in the sense that they cannot be isomorphic to the real system.”
Facets of uncertainty: epistemic uncertainty, non-stationarity, likelihood, hypothesis testing, and communication (2016, background): “Even these more complex cases, however, are what I have called ideal cases in the past (e.g. Beven 2002, 2006a).”
Uncertainty in the environmental modelling process - A framework and guidance (2007, methodology): “Uncertainty assessment of model simulations is therefore important, when models are used to support water management decisions (Beven and Binley, 1992; Beven, 2002; Pahl-Wostl, 2002; Jakeman and Letcher, 2003; Refsgaard and Henriksen, 2004; Pahl-Wostl, 2007; Vandenberghe et al., 2007).”
A framework for dealing with uncertainty due to model structure error (2004, methodology): “Furthermore, as the selected conceptual models can never cover all possibilities, but instead cover limited range, it is important to emphasise that the overall uncertainty of model predictions cannot be assessed in an absolute sense, only in a conditional or relative sense [7,31].”
Nonparametric direct mapping of rainfall‐runoff relationships: An alternative approach to data analysis and modeling? (2004, methodology): “The recourse to input and output data for parameter estimation appears as unavoidable for presently available models [Beven, 2000, 2002].”
Information content and complexity of simulated soil water fluxes (2006, background): “A comprehensive contemplation on the non-uniqueness of modeling in environmental sciences was recently presented by Beven (2002, 2003).”
Hybrid fuzzy and optimal modeling for water quality evaluation (2007, background): “[4] The importance of uncertainty in the water quality area is widely recognized and documented [e.g., Beck, 1987; Van der Perk, 1997; Beven and Freer, 2001; Beven, 2002; Vrugt et al., 2002; Harris and Heathwaite, 2005; Zheng and Keller, 2006].”
What makes Darwinian hydrology "Darwinian"? Asking a different kind of question about landscapes (2014, background): “Consider the historical watershed evolution as a trajectory in “landscape space”, with ach point along this trajectory mapping to a behavioral subset of the “model space” of the system at a point in time (Beven, 2002).”