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Reconstruction of subgrid scale topographic variability and its effect upon the spatial structure of three dimensional river flow.

By M. A. Casas, S. N. Lane, R. J. Hardy, G. Benito and P. J. Whiting

Abstract

A new approach to describing the associated topography at different scales in computational fluid dynamic applications to gravel bed rivers was developed. Surveyed topographic data were interpolated, using geostatistical methods, into different spatial discretizations, and grain-size data were used with fractal methods to reconstruct the microtopography at scales finer than the measurement (subgrid) scale. The combination of both scales of topography was then used to construct the spatial discretization of a three-dimensional finite volume Computational Fluid Dynamics (CFD) scheme where the topography was included using a mass flux scaling approach. The method was applied and tested on a 15 m stretch of Solfatara Creek, Wyoming, United States, using spatially distributed elevation and grain-size data. Model runs were undertaken for each topography using a steady state solution. This paper evaluates the impact of the model spatial discretization and additional reconstructed-variability upon the spatial structure of predicted three-dimensional flow. The paper shows how microtopography modifies the spatial structure of predicted flow at scales finer than measurement scale in terms of variability whereas the characteristic scale of predicted flow is determined by the CFD scale. Changes in microtopography modify the predicted mean velocity value by 3.6% for a mesh resolution of 5 cm whereas a change in the computational scale modifies model results by 60%. The paper also points out how the spatial variability of predicted velocities is determined by the topographic complexity at different scales of the input topographic model

Publisher: American Geophysical Union
Year: 2010
DOI identifier: 10.1029/2009WR007756
OAI identifier: oai:dro.dur.ac.uk.OAI2:7295
Journal:

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  1. (2000). A conceptual approach for integrating phosphorus and nitrogen management at catchment scales,
  2. (2006). A methodology for integrated economic and environmental analysis of pollution from agriculture,
  3. (2004). A networkindex based version of TOPMODEL for use with high-resolution digital topographic data,
  4. (1994). A quasi-dynamic wetness index for characterizing the spatial distribution of zones of surface saturation and soil water contents,
  5. (2003). A review of erosion and sediment transport models,
  6. (1980). ANSWERS — A model for watershed planning,
  7. (2003). Applying the Patuxent Landscape Unit Model to human dominated ecosystems: The case of agriculture,
  8. (1995). Assessing the performance of the NELUP hyodrological models for river basin planning,
  9. (2001). Assessment of interactions between land use change and carbon and nutrient fluxes in Ecuador,
  10. (1983). Catchment geomorphology and the dynamics of runoff contributing areas,
  11. (2001). Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology,
  12. (1996). Evaluation and management of the impact of land use change on the nitrogen and phosphorus load delivered to surface waters: The export coefficient modelling approach,
  13. Heathwaite (2005), Inadmissible evidence: Knowledge and prediction in land and riverscapes,
  14. (1975). Hydrograph modelling strategies, in Processes in Human and Physical Geography, edited by
  15. (2001). Long-term land use changes in a mesoscale watershed due to socio-economic factors — Effects on landscape structures and functions,
  16. (2003). Making process-based knowledge useable at the operational level: A framework for modelling diffuse pollution from agricultural land,
  17. (2001). Modeling looped ratings in MuskingumCunge routing,
  18. (1994). Modelling of nitrate leaching on a regional scale using a GIS,
  19. (2000). Modelling risk, trade, agricultural and environmental policies to assess trade-offs between water quality and welfare in the hog industry,
  20. (1997). Modelling the hydrologic response of Mediterranean catchments, Prades, Catalonia. The use of distributed models as aids to hypothesis testing,
  21. (1997). Modelling the impact on water quality of land use change in agricultural catchments,
  22. O’Loughlin (2003), The concept of effective length in hillslopes: Assessing the influence of climate and topography on the contributing area of catchments,
  23. (1972). On the assessment of surface heat flux and evaporation using large scale weather parameters,
  24. (2005). On the concept of delivery of sediment and nutrients to stream channels,
  25. (1970). River flow forecasting through conceptual models part I — A discussion of principles,
  26. (2005). River pollution from non-point sources: A new simplified method of assessment,
  27. (2004). Scale appropriate modelling: Representing causeand-effect relationships in nitrate pollution at the catchment scale for the purpose of catchment scale planning,
  28. (2006). Surveillant science: Challenges for the management of rural environments emerging from the new generation diffuse pollution models,
  29. (2007). The concept of hydrological connectivity and its contribution to understanding runoff-dominated geomorphic systems,
  30. (2006). The People and Landscape Model (PALM): Towards full integration of human decision-making and biophysical simulation models,
  31. (2003). The Phosphorus Indicators Tool: A simple model of diffuse P loss from agricultural land to water,
  32. (2009). The potential of digital filtering of generic topographic data for geomorphological research, Earth Surf.
  33. (1999). The use of conventionally and alternatively located buffer zones for the removal of nitrate from diffuse agricultural run-off,
  34. (2003). Threshold values for nature protection areas as indicators for bio-diversity — A regional evaluation of economic and ecological consequences,
  35. (2007). Use of the connectivity of runoff model (CRUM) to investigate the influence of storm characteristics on runoff generation and connectivity in semi-arid areas,
  36. (2004). Variable ‘active’ versus ‘contributing’ areas or periods: A necessary distinction,

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