Conservation equations governing hillslope responses: Exploring the physical basis of water balance

Reggiani, P.; Sivapalan, Murugesu; Hassanizadeh, S. Majid

doi:10.1029/2000wr900066

Cited by 133 publications

(145 citation statements)

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“…New concepts for process-based models have been put forward in recent years, but more testing is required to assess whether previous limitations of physically-based models have yet been overcome (e.g. Reggiani et al 1998Reggiani et al , 1999Reggiani et al , 2000Reggiani et al , 2001Panday & Huyakorn 2004;Qu & Duffy 2007;Kollet & Maxwell 2006, 2008.…”

Section: Introductionmentioning

confidence: 99%

Advances in the identification and evaluation of complex environmental systems models

Wagener

Reed

Werkhoven

et al. 2009

Journal of Hydroinformatics

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Advances in our ability to model complex environmental systems are currently driven by at least four needs: (1) the need for the inclusion of uncertainty in monitoring, modelling and decisionmaking; (2) the need to provide environmental predictions everywhere; (3) the need to predict the impacts of environmental change; and (4) the need to adaptively evolve observation networks to better resolve environmental systems and embrace sensing innovations. Satisfying these needs will require improved theory, improved models and improved frameworks for making and evaluating predictions. All of these improvements should result in the long-term evolution and improvement of observation systems. In the context of this paper we discuss current bottlenecks and opportunities for advancing environmental modelling with and without local observations of system response. More realistic representations of real-world thresholds, nonlinearities and feedbacks motivates the use of more complex models as well as the consequent need for more rigorous evaluations of model performance. In the case of gauged systems, we find that global sensitivity analysis provides a widely underused tool for evaluating models' assumptions and estimating the information content of data. In the case of ungauged systems, including the modelling of environmental change impacts, we propose that the definition of constraints on the expected system response provides a promising way forward. Examples of our own work are included to support the conclusions of this discussion paper. Overall, we conclude that an important bottleneck currently limiting environmental predictions lies in how our model evaluation and identification approaches are extracting, using and evolving the information available for environmental systems at the watershed scale.

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Section: Introductionmentioning

confidence: 99%

Advances in the identification and evaluation of complex environmental systems models

Wagener

Reed

Werkhoven

et al. 2009

Journal of Hydroinformatics

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“…Models based on the Darcy-Richards equation and Manning equation might claim to have a physical foundation, but the empirical ''physics'' on which they are based is clearly not universally applicable [see, for example, Beven and Germann, 2013;Beven, 2013]. In principle, of course, we can have deductive physically based models derived from principles of conservation of mass, energy, and momentum (as in the Representative Elementary Watershed ''REW'' framework of Reggiani et al [2000Reggiani et al [ , 2001) and simplifications of the Navier-Stokes equations [e.g., Neuman, 1977]. In both cases, except for some special cases, the auxiliary and boundary conditions required to have a working model at useful scales will reintroduce an inductive element.…”

Section: Model Structuresmentioning

confidence: 99%

A guide to good practice in modeling semantics for authors and referees

Beven

Young

2013

Water Resources Research

106

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[1] This opinion piece makes some suggestions about guidelines for modeling semantics that can be referred to by authors and referees. We discuss descriptions of model structures, different forms of simulation and prediction, descriptions of different sources of uncertainty in modeling practice, the language of model validation, and concepts of predictability and fitness-for-purpose. While not expecting universal agreement on these suggestions, given the loose usage of words in the literature, we hope that the discussion of the issues involved will at least give pause for thought and encourage good practice in model development and applications.Citation: Beven, K., and P. Young (2013), A guide to good practice in modeling semantics for authors and referees, Water Resour.

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“…Most scaling work to date has built on the representative elementary area (REA) concept Fan and Bras, 1995), and extensions to the representative elementary watersheds (REW) introduced by Reggiani et al (1998Reggiani et al ( , 1999Reggiani et al ( , 2000Reggiani et al ( , 2001) -the REA-REW concept seeks to define physically meaningful control volumes for which it is possible to obtain simpler descriptions of the rainfall-runoff process (i.e., simpler than those on the point scale). An alternative, but related, concept is the representative hillslope (RH; Berne et al, 2005;Hazenberg et al, 2015).…”

Section: Scaling and Similarity Hypothesesmentioning

confidence: 99%

“…As asserted by Dooge (1986), "within the physical sciences and the Earth sciences there is and can be no universal model for water movement." Despite numerous attempts at integrating local models across soils (e.g., Kim et al, 1997), hillslopes , and watersheds (e.g., Reggiani et al, 1998Reggiani et al, , 1999Reggiani et al, , 2000Reggiani et al, , 2001, universal laws in hydrology and the required closure relations remain elusive because the physics are likely scale-dependent (e.g., Bierkens, 1996) and the data required to test these hypotheses are either not readily available or not easily synthesized, or, even worse, would never be observable (Beven, 2006). Further, computational advances have enabled so-called "hyperresolution" or, using an alternative term that is not necessarily equivalent, "hillslope-resolving" modeling (e.g., Chaney et al, 2016;Wood et al, 2011); but as noted in the discussion between Beven and Cloke (2012) and Wood et al (2012), and later discussed in Beven et al (2015), the ability to provide meaningful information from hillslope-resolving models is limited both by a lack of tested parameterizations on a given model scale as well as by lack of data for model evaluation (e.g., Melsen et al, 2016a).…”

Section: Introductionmentioning

confidence: 99%

Scaling, similarity, and the fourth paradigm for hydrology

Peters‐Lidard

Clark

Samaniego

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. In this synthesis paper addressing hydrologic scaling and similarity, we posit that roadblocks in the search for universal laws of hydrology are hindered by our focus on computational simulation (the third paradigm) and assert that it is time for hydrology to embrace a fourth paradigm of dataintensive science. Advances in information-based hydrologic science, coupled with an explosion of hydrologic data and advances in parameter estimation and modeling, have laid the foundation for a data-driven framework for scrutinizing hydrological scaling and similarity hypotheses. We summarize important scaling and similarity concepts (hypotheses) that require testing; describe a mutual information framework for testing these hypotheses; describe boundary condition, state, flux, and parameter data requirements across scales to support testing these hypotheses; and discuss some challenges to overcome while pursuing the fourth hydrological paradigm. We call upon the hydrologic sciences community to develop a focused effort towards adopting the fourth paradigm and apply this to outstanding challenges in scaling and similarity.

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Conservation equations governing hillslope responses: Exploring the physical basis of water balance

Cited by 133 publications

References 14 publications

Advances in the identification and evaluation of complex environmental systems models

Advances in the identification and evaluation of complex environmental systems models

A guide to good practice in modeling semantics for authors and referees

Scaling, similarity, and the fourth paradigm for hydrology

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