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Forest operations, extreme flooding events, and considerations for hydrologic modeling in the Appalachians - A review

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FOREST ECOLOGY AND MANAGEMENT
卷 242, 期 2-3, 页码 77-98

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DOI: 10.1016/j.foreco.2007.01.051

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best management practices; forest operations; flooding; watershed management; hydrologic modeling

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The connection between forests and water resources is well established, but the relationships among controlling factors are only partly understood. Concern over the effects of forestry operations, particularly harvesting, on extreme flooding events is a recurrent issue in forest and watershed management. Due to the complexity of the system, and the cost of installing large-scale hydrologic studies, data are usually limited. Therefore, hydrologic models are employed to evaluate specific land use issues during extreme conditions. Our objectives were to review literature regarding: (1) relevant forest hydrology concepts, (2) the effects of silviculture and forest operations on peak discharges and flood yields, and (3) the suitability of existing modeling approaches for assessing these effects on extreme peak discharges. Numerous studies have shown that the effects of forest operations on streamflow vary, and that the influence of vegetation, soils, and land use on streamflow generation diminishes as larger volumes of water are introduced to the system. The most significant impact forest operations might have on extreme flows is by routing via poorly located and designed road networks. Extreme events appear to have different hydrologic controls than lower-flow events, and that sharp thresholds may exist between these paradigms. There are a large number of hydrologic models currently available that have been developed for a wide variety of applications. Issues such as uncertainty, overparameterization, extrapolation of flood data, and logistic issues limit the use of hydrologic models for evaluating the specific controls and outcome of land-use change on extreme peak discharges. (C) 2007 Elsevier B.V. All rights reserved.

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