Grouped Response Units for Distributed Hydrologic Modeling

Kouwen, N.; Soulis, E. D.; Pietroniro, Alain; Donald, J.; Harrington, Robert A.

doi:10.1061/(asce)0733-9496(1993)119:3(289)

Cited by 262 publications

(181 citation statements)

References 11 publications

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“…The Grouped Response Unit (GRU) conceptualization is a lumped approached utilizing a computational unit that consists of one or more fractional land cover characteristics (Kouwen et al, 1993). Specifically, a GRU is a grouping of all areas within an domain with a similar hydrological response (Soulis et al, 2005) regardless of location .…”

Section: The Hydrological and Grouped Response Unitsmentioning

confidence: 99%

“…Each cell thus has associated GRUs and the cell size need not reflect the size of the hydrologic unit being modelled (Cranmer et al, 2001). However, the GRU elements are limited in size to an area that is subject to a uniform hydrological response due to uniform meteorological conditions or where travel times are small compared to the overall basin or the overall meteorological events of interest (Kouwen et al, 1993). The land-cover characteristics of a GRU all contribute to runoff and identical hydrological parameters are used for the same land cover over all elements in the model basin.…”

Section: The Hydrological and Grouped Response Unitsmentioning

confidence: 99%

“…A defining characteristic of the GRUs approach is that each group of GRUs must route water directly to a stream. Hydrological models such as WATFLOOD (Kouwen et al, 1993) and the Modélisation Environmentale Communautaire (MEC)-Surface and Hydrology (MESH) (Pietroniro et al, 2007) model both exploit this concept to decrease model runtime and simplify calculations .…”

Section: The Hydrological and Grouped Response Unitsmentioning

confidence: 99%

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Implications of mountain shading on calculating energy for snowmelt using unstructured triangular meshes

Marsh

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In many parts of the world, the snowmelt energy balance is dominated by net solar shortwave radiation. This is the case in the Canadian Rocky Mountains, where clear skies dominate the winter and spring. In mountainous regions, solar irradiance at the snow surface is not only affected by solar angles, atmospheric transmittance, and the slope and aspect of immediate topography, but also by shadows from surrounding terrain. Many hydrological models do not consider such horizon-shadows. The accumulation of errors in estimating solar irradiance by neglecting horizon-shadows can lead to significant errors in calculating the timing and rate of snowmelt due to the seasonal storage of internal energy in the snowpack.A common approach to representing the landscape is through structured meshes. iii

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Section: The Hydrological and Grouped Response Unitsmentioning

confidence: 99%

Section: The Hydrological and Grouped Response Unitsmentioning

confidence: 99%

Section: The Hydrological and Grouped Response Unitsmentioning

confidence: 99%

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Implications of mountain shading on calculating energy for snowmelt using unstructured triangular meshes

Marsh

Pomeroy

Spiteri

2012

Hydrological Processes

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“…In this case, HRUs lying within one computational element are grouped into a GRU (Kite and Kouwen, 1992). Hydrological processes are modelled identically for each group of HRU, and the responses of each group are weighted and summed to generate a total GRU outflow (Kouwen et al, 1993). The size of the computational element is determined by the resolution of meteorological data or the desired level of detail in model output.…”

Section: Approaches To Hydrological Modellingmentioning

confidence: 99%

Streamflow Modelling: A Primer on Applications, Approaches and Challenges

2012

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This article examines the current practice of streamflow modelling, a field under development for over a century. A sample of the wide range of assessment and planning applications of streamflow models is presented. The diversity in the use of these models is mirrored in the diversity of model complexity, and modelling approaches ranging from empirical to physically based and from lumped to fully distributed are described with examples. Predictions derived from hydrological models are subject to many sources of error; these are discussed along with methods for error minimization or anticipation. Model error is generally quantified using an ensemble of forecasts meant to sample the range of predictive uncertainty. This ensemble can be used to generate reliable probabilistic forecasts of hydrological quantities if all sources of error are accounted for. To date, applications of ensemble methods in streamflow forecasting have typically focused on only one or two error sources. A challenge will be to develop ensemble streamflow forecasts that sample a wider range of predictive uncertainty.

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“…This differs from the REA approach where the element's location will influence its hydrological response. Kouwen et al (1993) described a grouped response unit (GRU) used in a grid square model. The GRU is a grouping of all areas with a similar land cover such that a grid square will contain a number of distinct GRUs.…”

Section: Discretization Of the Watershedmentioning

confidence: 99%

Remote sensing applications in hydrological modelling

Kite¹,

Pietroniro²

1996

Hydrological Sciences Journal

Self Cite

118

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Previous studies have suggested that remotely sensed data should provide major benefits to hydrology and water resources and yet there are few case studies that show practical benefits. One of the reasons for this is the lack of tools to convert remotely sensed data to the type of information useful to water resource systems operators. Hydrological models can play an important role in this translation of data to information. This paper reviews some of the techniques presently used in hydrological models to make use of remotely sensed data and provides a comprehensive reference list. Applications de la télédétection à la modélisation hydrologique Résumé Si de précédentes études on suggéré que les données télédétec-tées pouvaient rendre de grands services à l'hydrologie et à l'étude des ressources en eau, il n'existe que peu d'études de cas mettant en évidence leur intérêt pratique. L'une des causes de cet état de choses est le manque d'outils permettant de traduire les données télédétectées en informations directement utilisables par les gestionnaires des ressources en eau. Les modèles hydrologiques peuvent jouer un grand rôle dans ce processus de transformation de données en informations. Le présent article passe en revue quelques unes des techniques actuellement utilisées en modélisation hydrologique permettant d'utiliser des données télé-détectées et fournit une bibliographie détaillée.

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Grouped Response Units for Distributed Hydrologic Modeling

Cited by 262 publications

References 11 publications

Implications of mountain shading on calculating energy for snowmelt using unstructured triangular meshes

Implications of mountain shading on calculating energy for snowmelt using unstructured triangular meshes

Streamflow Modelling: A Primer on Applications, Approaches and Challenges

Remote sensing applications in hydrological modelling

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