Dalton Medal Lecture: How far can we go in distributed hydrological modelling?

By Keith Beven. 2001

693 citations recorded by the source corpus.

This paper considers distributed hydrological models in hydrology as an expression of a pragmatic realism. Some of the problems of distributed modelling are discussed including the problem of nonlinearity, the problem of scale, the problem of equifinality, the problem of uniqueness and the problem of uncertainty. A structure for the application of distributed modelling is suggested based on an uncertain or fuzzy landscape space to model space mapping. This is suggested as the basis for an Alternative Blueprint for distributed modelling in the form of an application methodology. This Alternative Blueprint is scientific in that it allows for the formulation of testable hypotheses. It focusses attention on the prior evaluation of models in terms of physical realism and on the value of data in model rejection. Finally, some unresolved questions are outlined that distributed modelling must address in the future together with a vision for distributed modelling as a means of learning about places.

Subfields: Environmental Engineering, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/010795327be64811b2ecfa8c2cf13cb298968381

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Citations in the corpus

Towards an alternative blueprint for a physically based digitally simulated hydrologic response modelling system (2002, methodology): “This methodology has much in common with the Generalised Likelihood Uncertainty Estimation (GLUE) of Beven and Binley (1992, see also Beven et al., 2000; Beven and Freer, 2000b; Beven, 2001).”
On explanatory depth and predictive power (2001, background): “My own view is to view this as more of a problem of rejection (Beven, 2001).”
Weather radar and hydrology (2009, background): “The usefulness of distributed hydrological models has been questioned, mainly due to overparameterization problems, parameter estimation and validation limitations [9,43,8].”
Searching for the Holy Grail of scientific hydrology: Q t =( S, R, Δt ) A as closure (2006, methodology): “Even if we still cannot close the mass balance equations of hydrology by measurement (see Beven, 2001b), we can theorise that hydrological ﬂows must be consistent with the Introduction”
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).”
HESS Opinions : The complementary merits of competing modelling philosophies in hydrology (2017, background): “As already emphasized previously by many authors (e.g. Beven, 1989, 2001, 2006a; Kirchner, 2006; Zehe et al., 2014), these efforts to approach the closure problem in hydrology need to involve both, ways to reliably determine effective model parameters, i.e. the system boundary conditions, that…”
Macropores and water flow in soils revisited (2013, background): “This is not a new insight, it has been known for decades [e.g., Dagan and Bresler, 1983], but with very little effect on modeling practice [see discussion in Beven, 1989, 2001, 2006, 2012].”
A manifesto for the equifinality thesis (2006, methodology): “Model validation is a subject fraught with both practical and philosophical undertones (see Stephenson and Freeze, 1974; Konikow and Bredehoeft, 1992; Oreskes et al., 1994; Anderson and Bates, 2001; Beven, 1993, 2001b, 2002a, b).”
Towards a coherent philosophy for modelling the environment (2002, methodology): “This will be the case even down to quite small grid scales when current measurement techniques are limited to "point" scale measurements (Beven, 2001b).”
Impact of the numbers of observations and calibration parameters on equifinality, model performance, and output and parameter uncertainty (2015, background): “…of equifinality, nonuniqueness, and nonidentifiability of parameters have been discussed for the last three decades in hydrologic modelling (Sorooshian andGupta, 1983; Beven, 1989, 1993, 2001, 2002, and 2006; Beven and Binley, 1992; Gan and Biftu, 1996; Franks et al., 1997; Beven and Freer, 2001).”
Connecting the power-law scaling structure of peak-discharges to spatially variable rainfall and catchment physical properties (2014, background): “There are several main limitations to this approach that range from the approximation of processes which are not yet fully understood (especially subsurface flow dynamics) to the more obvious problems of nonlinearity, scale, equifinality, and uncertainty [2].”
Reconciling theory with observations: elements of a diagnostic approach to model evaluation (2008, methodology): “As we build more realistic and detailed models of environmental processes, we must also develop methods powerful enough to evaluate (test) and correct them (Spear and Hornberger, 1980; Gupta et al., 1998; Beven, 2001; Wagener et al., 2003b; Wagener and Gupta 2005, among others).”
Estimation of a Critical Spatial Discretization Limit for Solving Richards' Equation at Large Scales (2008, methodology): “(2002) and Beven (2001). Th e heterogeneity of the soil material can be taken into account in distributed modeling of water dynamics at larger scales using methods like pedotransfer functions (Wagner et al., 2001) or geostatistical tools (Yeh and Zhang, 1996). However, because of computational limit”
Hydrological modelling of the Chaohe Basin in China: Statistical model formulation and Bayesian inference (2007, background): “This is called the principle of “equifinality” by Beven (2001) and Beven and Freer (2001), but it fits more generally into any Bayesian approach of statistical inference (Gelman et al., 1995).”
Influence of uncertain boundary conditions and model structure on flood inundation predictions. (2006, background): “Empirical results of studies in various fields of environmental modelling (for a summary see [79]) show that many different sets of parameters and model structures can fit evaluation data acceptably well and therefore, it may be impossible to decide between them as useful predictors of the system (t”
Streamflow prediction in ungauged catchments using copula‐based dissimilarity measures (2010, background): “[93] Equifinality of parameter sets has been recognized as one of the common problems affecting the predictability of environmental models in general, and precipitation-runoff models in particular [Beven, 2001].”
Expanding the role of reactive transport models in critical zone processes (2017, methodology): “…originated from numerical weather prediction (Daley, 1991), is another technique that has been used widely in recent decades to address the issue of parameter non-uniqueness or equifinality in atmospheric, geographic, oceanic, and hydrologic sciences (Beven, 2001b; Navon, 2009; Rabier, 2005).”