2014
DOI: 10.1007/s00267-014-0251-9
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A Method for Spatially Explicit Representation of Sub-watershed Sediment Yield, Southern California, USA

Abstract: We present here a method to integrate geologic, topographic, and land-cover data in a geographic information system to provide a fine-scale, spatially explicit prediction of sediment yield to support management applications. The method is fundamentally qualitative but can be quantified using preexisting sediment-yield data, where available, to verify predictions using other independent data sets. In the 674-km(2) Sespe Creek watershed of southern California, 30 unique "geomorphic landscape units" (GLUs, define… Show more

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Cited by 9 publications
(13 citation statements)
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“…; Booth et al . ). Conversely, channels in regions of intrinsically low watershed sediment delivery (e.g.…”
Section: Watershed Differences and Urban Channel Evolutionmentioning
confidence: 97%
“…; Booth et al . ). Conversely, channels in regions of intrinsically low watershed sediment delivery (e.g.…”
Section: Watershed Differences and Urban Channel Evolutionmentioning
confidence: 97%
“…Extrapolation of hillslope erosion process to areas under canopy and not field‐accessible was based on ‘geomorphic landscape units’ (GLUs, Booth et al ., ), a representative area approach similar to ‘response units’ in hydrology (Wolock et al ., ; Beighley et al ., ). Land cover, lithology and hillslope steepness were combined at the scale of their respective minimum resolution (i.e.…”
Section: Methodsmentioning
confidence: 99%
“…Episodic mass wasting sources in decadal sediment supply can be estimated through a more detailed sediment budget approach (e.g., Reid and Dunne, 1996), or more simply by increasing the sediment yield in active mass wasting areas based on regional literature values. For example, two similar studies (GMA, 2007;Bigelow et al, 2012b) used digitized maps of active earthflows and local literature values of earthflow rates to appropriately increase the sediment yield estimates at these discrete locations within the watersheds. This approach in part accounts for differences in lithologic erosion rates across the basin, as higher sediment yields from earthflows often occur in specific formations that produce clay-rich soils (e.g., Keefer and Johnson, 1983).…”
Section: Adjustments and Considerationsmentioning
confidence: 99%
“…For example, the Universal Soil Loss Equation (USLE) (Wischmeier and Smith, 1978), the revised USLE (RUSLE) (Renard et al, 1997), and similar approaches (e.g., Booth et al, 2014) simply use a generic reduction (C-factor) based on classes of vegetation cover (e.g., crop type, forest, scrub, etc.) to adjust erosion predictions over vast areas regardless of the individual size of vegetation within the categories.…”
Section: Modifying Erosion Potential By Vegetationmentioning
confidence: 99%
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