HESS Opinions: Advocating process modeling and de-emphasizing parameter estimation

Bahremand, Abdolreza

doi:10.5194/hessd-12-12377-2015

Cited by 10 publications

(18 citation statements)

References 90 publications

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“…It is therefore desirable and eventually necessary to explore methods to more objectively and rigorously test individual model sub-components against observations (Clark et al, 2011) and/or to assign physical meaning to them a priori (cf. Bahremand, 2016). A potentially effective starting point for the latter is to use observations at the modelling scale to infer information about the functional shape (i.e.…”

Section: (C1) "Top-down Models Have a Poor Physical And Theoretical Bmentioning

confidence: 99%

HESS Opinions: The complementary merits of top-down and bottom-up modelling philosophies in hydrology

Hrachowitz

Clark

2017

Preprint

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Abstract. In hydrology, the two somewhat competing modelling philosophies of bottom-up and top-down approaches are the basis of most process-based models. Differing mostly (1) in their respective degree of detail in resolving the modelling domain and (2) in their respective degree of explicitly treating conservation laws, these two philosophies suffer from similar limitations. Nevertheless, a better understanding of their respective basis (i.e. micro-scale vs. macro-scale) as well as their respective short comings bears the potential of identifying the complementary value of the two philosophies for improving our models. In this manuscript we analyse several frequently communicated beliefs and assumptions to identify, discuss and emphasize the functional similarity of the two modelling philosophies. We argue that deficiencies in model applications largely do not depend on the modelling philosophy but rather on the way a model is implemented. Based on the premises that top-down models can be implemented at any desired degree of detail and that any type of model remains to some degree conceptual we argue that a convergence of the two modelling strategies may hold some value for progressing the development of hydrological models.

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Section: (C1) "Top-down Models Have a Poor Physical And Theoretical Bmentioning

confidence: 99%

HESS Opinions: The complementary merits of top-down and bottom-up modelling philosophies in hydrology

Hrachowitz

Clark

2017

Preprint

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“…In recent decades, a plethora of calibration and optimisation techniques has been developed to optimise the model response by forcing the model parameters to compensate for uncertainties and lack of knowledge (e.g., Beven & Binley, ; Gupta, Sorooshian, & Yapo, ; Moradkhani, Sorooshian, Gupta, & Houser, ). Given their nature, these uncertainties can change in time and space; this is why, as recently stated by Bahremand (), the focus of research should be more on the representation of processes in the model than on parameter optimisation techniques (see also Semenova & Beven, ; Vinogradov, Semenova, & Vinogradova, ).…”

Section: Introductionmentioning

confidence: 99%

Process‐based hydrological modelling: The potential of a bottom‐up approach for runoff predictions in ungauged catchments

Antonetti

Scherrer

Kienzler

et al. 2017

Hydrological Processes

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Conceptual rainfall–runoff models are a valuable tool for predictions in ungauged catchments. However, most of them rely on calibration to determine parameter values. Improving the representation of runoff processes in models is an attractive alternative to calibration. Such an approach requires a straightforward, a priori parameter allocation procedure applicable on a wide range of spatial scales. However, such a procedure has not been developed yet. In this paper, we introduce a process‐based runoff generation module (RGM‐PRO) as a spin‐off of the traditional runoff generation module of the PREVAH hydrological modelling system. RGM‐PRO is able to exploit information from maps of runoff types, which are developed on the basis of field investigations and expert knowledge. It is grid based, and within each grid cell, the process heterogeneity is considered to avoid information loss due to grid resolution. The new module is event based, and initial conditions are assimilated and downscaled from continuous simulations of PREVAH, which are also available for real‐time applications. Four parameter allocation strategies were developed, on the basis of the results of sprinkling experiments on 60‐m2 hillslope plots at several grassland locations in Switzerland, and were tested on five catchments on the Swiss Plateau and Prealps. For the same catchments, simulation results obtained with the best parameter allocation strategy were compared with those obtained with different configurations of the traditional runoff generation module of PREVAH, which was also applied as an event‐based module here. These configurations include a version that avoids calibration, one that transfers calibrated parameters, and one that uses regionalised parameter values. RGM‐PRO simulated heavy events in a more realistic way than the uncalibrated traditional runoff generation module of PREVAH, and, in some instances, it even exceeded the performance of the calibrated traditional one. The use of information on the spatial distribution of runoff types additionally proved to be valuable as a regionalisation technique and showed advantages over the other regionalisation approaches, also in terms of robustness and transferability.

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“…I think of such an approach as being a kind of "white box calibration", and my experiences with the WetSpa model (Bahremand et al, 2005(Bahremand et al, , 2007Bahremand andDe Smedt, 2008, 2010) suggest that it can help to ensure a considerable degree of consistency in both the parameter values and the model behavior. As discussed later in this paper, other no-calibration attempts for physical modeling have been reported using the novel approach of optimality , maximum entropy production , and behavioral modeling under organizing principles .…”

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confidence: 99%

HESS Opinions: Advocating process modeling and de-emphasizing parameter estimation

Bahremand

2016

Hydrol. Earth Syst. Sci.

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Abstract. Since its origins as an engineering discipline, with its widespread use of "black box" (empirical) modeling approaches, hydrology has evolved into a scientific discipline that seeks a more "white box" (physics-based) modeling approach to solving problems such as the description and simulation of the rainfall-runoff responses of a watershed. There has been much recent debate regarding the future of the hydrological sciences, and several publications have voiced opinions on this subject. This opinion paper seeks to comment and expand upon some recent publications that have advocated an increased focus on process-based modeling while de-emphasizing the focus on detailed attention to parameter estimation. In particular, it offers a perspective that emphasizes a more hydraulic (more physics-based and less empirical) approach to development and implementation of hydrological models.

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HESS Opinions: Advocating process modeling and de-emphasizing parameter estimation

Cited by 10 publications

References 90 publications

HESS Opinions: The complementary merits of top-down and bottom-up modelling philosophies in hydrology

HESS Opinions: The complementary merits of top-down and bottom-up modelling philosophies in hydrology

Process‐based hydrological modelling: The potential of a bottom‐up approach for runoff predictions in ungauged catchments

HESS Opinions: Advocating process modeling and de-emphasizing parameter estimation

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