Erosion modelling for land management in the Tahoe basin, USA: scaling from plots to forest catchments

Grismer, Mark E.

doi:10.1080/02626667.2012.685170

Cited by 15 publications

(17 citation statements)

References 45 publications

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“…The familiar Manning's equation for broad shallow flow of depth 'h' takes the form Q " p1{nqh 1.667 S 0.5 (4) where S is the slope equivalent in concept to the angle θ in Figure 1. Then, the Manning's mean flow velocity is given by u m " p1{nqh 0.667 S 0.5 (5) Note that in Equation (3), the mean flow velocity is proportional to the flow depth squared and directly to the slope, whereas under turbulent flow assumptions (Equation (5)), the mean velocity is proportional to the flow depth to the 2/3rd power and the square root of the slope. This difference between Equations (3) and (5) also plays out in the formulation of the water storage as a function of depth, or celerity (c = BQ B h ), as in the kinematic-wave equation often applied in hydrologic modeling [42].…”

Section: Theory-laminar and Turbulent Overland Flow Equationsmentioning

confidence: 99%

“…This project originated from an effort to relate observed field simulated runoff rates from Rainfall [40] and Runoff Simulators to model-predicted values so as to better infer soil properties associated with hillslope soils restoration efforts and estimation of watershed sediment loading rates [5]. Such modeling effort was hampered by the inability to a priori predict when surface runoff generation would result from infiltration excess, rather than saturation excess (more readily simulated when available soil water storage is filled).…”

Section: Research Hypotheses and Objectivesmentioning

confidence: 99%

“…Clarification of this distinction is critical towards assessing subsurface-surface hydrologic connectivity [3] within the watershed as well as estimation of flow travel times to streams and the surface shear stresses (overland flow velocities, or stream power) associated with erosion rates. Field observations from hundreds of rainfall/runoff simulations and during storm events in the northern Sierra Nevada and coastal CA watersheds have indicated that when near surface soils are unsaturated, overland flow generation only occurs on compacted soils (e.g., roads and landings) and only occasionally from less disturbed or restored forest soils [4][5][6][7][8][9]. In the less disturbed or restored soils, rainfall (even at rainfall rates of 100 mm/h) or snowmelt surface onflows (e.g., [10]) become subsurface interflows that may appear as seeps downslope at low gradient areas, creek banks, or roadside ditches.…”

Section: Introductionmentioning

confidence: 99%

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Surface Runoff in Watershed Modeling—Turbulent or Laminar Flows?

Grismer¹

2016

Hydrology

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Determination of overland sheet flow depths, velocities and celerities across the hillslope in watershed modeling is important towards estimation of surface storage, travel times to streams and soil detachment rates. It requires careful characterization of the flow processes. Similarly, determination of the temporal variation of hillslope-riparian-stream hydrologic connectivity requires estimation of the shallow subsurface soil hydraulic conductivity and soil-water retention (i.e., drainable porosities) parameters. Field rainfall and runoff simulation studies provide considerable information and insight into these processes; in particular, that sheet flows are likely laminar and that shallow hydraulic conductivities and storage can be determined from the plot studies. Here, using a 1 m by 2 m long runoff simulation flume, we found that for overland flow rates per unit width of roughly 30-60 mm 2 /s and bedslopes of 10%-66% with varying sand roughness depths that all flow depths were predicted by laminar flow equations alone and that equivalent Manning's n values were depth dependent and quite small relative to those used in watershed modeling studies. Even for overland flow rates greater than those typically measured or modeled and using Manning's n values of 0.30-0.35, often assumed in physical watershed model applications for relatively smooth surface conditions, the laminar flow velocities were 4-5 times greater, while the laminar flow depths were 4-5 times smaller. This observation suggests that travel times, surface storage volumes and surface shear stresses associated with erosion across the landscape would be poorly predicted using turbulent flow assumptions. Filling the flume with fine sand and conducting runoff studies, we were unable to produce sheet flow, but found that subsurface flows were onflow rate, soil depth and slope dependent and drainable porosities were only soil depth and slope dependent. Moreover, both the sand hydraulic conductivity and drainable porosities could be readily determined from measured capillary pressure displacement pressure head and assumption of pore-size distributions (i.e., Brooks-Corey lambda values of 2-3).

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Section: Theory-laminar and Turbulent Overland Flow Equationsmentioning

confidence: 99%

Section: Research Hypotheses and Objectivesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Surface Runoff in Watershed Modeling—Turbulent or Laminar Flows?

Grismer¹

2016

Hydrology

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“…capable of predicting these rates, from less-disturbed forest and rangeland soils (Grismer 2012). Meyer (1988) contended that simulated rainfall results only give relative, rather than absolute, erosion data, and that to correlate the simulation results to that of natural events, data from similar plots subject to long-term natural rainfall events must be available for comparison (Hamed et al 2002).…”

Section: Rainfall Simulator Designsmentioning

confidence: 99%

Standards vary in studies using rainfall simulators to evaluate erosion

Grismer¹

2012

Cal Ag

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Rainfall simulators are often employed to measure erosion rates, in order to estimate stream loading of sediment and nutrients in California foothill watersheds. The rainfall simulator enables the precise application of artificial rain with controlled drop sizes, intensity and duration. In addition to rain factors such as drop energy and intensity, several soil-and cover-related factors affect erosion rates. While computational models have evolved to quantify erosion based on field measurements taken by rainfall simulators, there has not been a consensus on the methodology to be deployed , especially in forested and remote landscapes. In addition, it is challenging to apply study results from small plots to entire watersheds. To guide future fieldwork on sediment loading to water bodies, we review key concerns related to rainfall simulator studies.

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“…Those empirical and physically-based models have been applied in catchment-scale erosion studies with varying degrees of success (e.g. Finney et al, 1993;Summer and Walling, 2002;Larsen and MacDonald, 2007;Kim et al, 2007;Grismer, 2012;Wieprecht et al, 2013;Ramsankaran et al, 2013).…”

mentioning

confidence: 98%