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Title: Quantitative generalizations for catchment sediment yield following forest logging

Author: Bathurst, James C.; Iroumé, Andrés;

Date: 2014

Source: Water Resources Research. 50(11): 8383-8402.

Publication Series: Scientific Journal (JRNL)

Description: Published data for temperate forests across the world are analyzed to investigate the potential for generalized quantitative expressions of catchment sediment yield impact in the years immediately following logging. Such generalizations would be useful in a variety of forestry and engineering tasks and would aid the spread of knowledge amongst both relevant professionals and new students. Data were assembled for paired catchment studies (51 catchments including 16 controls) that enabled the postlogging sediment yield impact to be compared with both the prelogging period and an undisturbed control catchment, using a specially defined relative response factor. Three categories of impact were derived: low-moderate, high, and very high, defined by specific ranges in the maximum value of the relative response factor. The maximum increase in specific sediment yield (in t km22 yr21) following logging is 1 order of magnitude above the control sediment yield at both the annual and storm event scales, at least under normal circumstances of Best Management Practice. There is no apparent relationship between sediment yield and the proportion of catchment logged, at least at the general scale. A cumulative probability distribution for the year in which the maximum postlogging sediment yield occurs, shows the majority of cases falling in the first 2 years. These generalizations refer to the broad response to logging as a function of ground disturbance, for example, by logging technique, roads, and burning. Although limited to order of magnitude quantification, they provide a basis for first estimates and for a general appreciation of an impact problem.

Publication Notes:

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Bathurst, James C.; Iroumé, Andrés. 2014. Quantitative generalizations for catchment sediment yield following forest logging. Water Resources Research. 50(11): 8383-8402.

 


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