The roles of natural and human disturbances in forest soil erosion.

Elliot, William J.; Owens, Philip N.; Collins, A. J.

doi:10.1079/9780851990507.0177

Cited by 4 publications

(4 citation statements)

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“…This suite of runs is typical of those recommended for a fuel management analysis (Elliot, 2006;Elliot and Robichaud, 2006). Average annual results from a single hillslope, and from a typical watershed, are presented in Table 1.…”

Section: Tmdlsmentioning

confidence: 99%

“…Human induced forest disturbances include thinning, prescribed fire, and the road network (Elliot 2006). This paper will focus on the first two, although sediment from the road network may well exceed sediment from the hillslope disturbances in some watersheds.…”

Section: Erosion From Forest Activitiesmentioning

confidence: 99%

“…The alternative approach suggested by Elliot (2006) and Elliot and Robichaud (2006) for evaluating the watershed effects of fuel management is to consider average annual values for individual hillslopes rather than TMDLs. These authors suggest that because the nature of the climate in the year following a disturbance is unknown, the best approach is to consider a number of different years and then use the average for those years.…”

Section: Average Annual Sediment Deliverymentioning

confidence: 99%

“…There are several ways to incorporate this information into a "background" estimation. One method proposed by Elliot (2006) is to average the gross hillslope erosion (42 t ha -1 ) over the fire return interval. In this example, with a 150-year fire return interval, that would mean adding an additional 0.28 t ha -1 y -1 to the undisturbed forest erosion rate, leading to a "background" value of 3.1 t ha -1 y -1 .…”

Section: Background Erosion Ratesmentioning

confidence: 99%

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Predicting Background and Risk-based Sedimentation for Forest Watershed TMDLs

Elliot¹

2007

Watershed Management to Meet Water Quality Standards and TMDLS (Total Maximum Daily Load) Proceedings of the 10-14 March 2007,

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Abstract. The Water Erosion Prediction Project (WEPP) model is a physically-based soil erosion tool INTRODUCTIONIn many forested watersheds, managers carry out fuel reduction activities, such as thinning and prescribed fire, to reduce the likelihood or severity of a wildfire. These management activities may cause increased hillslope erosion, and increased sediment yields from watersheds the year following the treatment. Watershed managers need to estimate erosion as part of their planning activities. In some cases, this estimate may need to be a Total Maximum Daily Load (TMDL) of sediment associated with a treatment.Water quality regulations frequently base the quality of our surface water on the TMDL of a pollutant. This practice has evolved from early regulation of industrial polluters who had the ability to increase or decrease the flows of polluted effluents into our nation's surface water. This approach to regulation was well suited to industrial enterprises, and allowed them to set goals to balance the cost of treatment versus the quantity of effluent that they could discharge.Although not ideal, the TMDL approach was subsequently applied to agriculture. Pollution from sediments from agriculture are not generated from a single point, but are dispersed across the landscape and generally described as "nonpoint source pollution." The TMDL approach assumed that a manager would be able to develop farming practices that would limit daily sediment generation. Typically, the Universal Soil Loss Equation (USLE) aided in developing management plans, even though it is an average annual technology. The TMDL approach stretched the validity of the USLE technology. This extrapolation was acceptable because of agency and public familiarity with the USLE. Another assumption dealt with management practices and assumed the same level of disturbances every season, or in some cases, in every rotation sequence.A more recent erosion prediction technology is the Water Erosion Prediction Project (WEPP) model (Laflen et al., 1997). WEPP was developed to replace the USLE. WEPP estimates average annual erosion after simulating a number of years with each year containing a number of storms. The daily weather file that drives WEPP is generated stochastically, and has a similar statistical distribution to that observed on nearby weather stations. In recent years, there have been numerous suggestions to apply the WEPP technology to predicting sediment TMDLs (Conroy et al., 2003;Elliot, 2002).The "average annual erosion" approach does not lend itself to management of wildlands, such as forests and rangelands. In these ecosystems, erosion is relatively low to non-existent when the site is not disturbed. Wildlands are disturbance-driven ecosystems, and occasionally, a wildfire will occur during a dry year, or landslides during a wet season. In nature, these disturbances dominate the erosion processes. Years with large runoff events dominate sediment delivery at a watershed scale. Human disturbances can also increase runoff and erosion, incl...

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Section: Tmdlsmentioning

confidence: 99%

Section: Erosion From Forest Activitiesmentioning

confidence: 99%

Section: Average Annual Sediment Deliverymentioning

confidence: 99%

Section: Background Erosion Ratesmentioning

confidence: 99%

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