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Forest Road Decommissioning Policies Determined using Deterministic and Stochastic Dynamic Programming
Abstract
Extensive timber harvesting and the accompanying road construction in the Pacific Northwest region have decreased the quality of fish-bearing streams. The decommissioning of abandoned forest roads increases stream quality by decreasing erosion and downstream sedimentation. Road removal treatments have been performed in many locations. However, the management of these treatments has been generally site-specific, with little investigation of how the treatments will affect the entire watershed. Land managers have a need to design a watershed wide management policy to reduce sedimentation, while maintaining overall costs within a reasonable limit. Identifying the trade-offs of the costs of different treatment policies associated with net reduction of sediment can be quantified. This work further develops optimization approaches to manage road decommissioning projects. Previous work in deterministic dynamic programming and genetic algorithmes did not incorporate the uncertainty of the effectiveness of the road treatments. Stochastic dynamic programming is used to determine the road treatment policy that maximizes the expected sediment saved. This approach is used to determine a policy for the Lost Man Creek Watershed in Northern California containing 691 road segments and road crossings. The model determines the optimal treatment level for each road segment and road crossing while considering a budgetary constraint.
... Both models performed better than either a policy of minimal erosion control treatments applied uniformly across the landscape, or a policy of maximum treatment on roads near streams. The models can be extended to include other considerations; for example, by weighting locations that are susceptible to debris torrents or adjacent to critical habitat, by modelling changes in runoff pathways on forest road networks (Croke et al., 2005) or by incorporating the uncertainty of the effectiveness of road treatments through stochastic dynamic programming (Baker et al., 2004). ...
Many anadromous fisheries streams in the Pacific Northwest have been damaged by various land use activities, including timber harvest and road construction. Unpaved forest roads can cause erosion and downstream sedimentation damage in anadromous fish-bearing streams. Although road decommissioning and road upgrading activities have been conducted on many of these roads, these activities have usually been implemented and evaluated on a site-specific basis without the benefit of a watershed perspective. Land managers still struggle with designing the most effective road treatment plan to minimize erosion while keeping costs reasonable across a large land base. Trade-offs between costs of different levels of treatment and the net effect on reducing sediment risks to streams need to be quantified. For example, which problems should be treated first, and by what treatment method? Is it better to fix one large problem or 100 small problems? If sediment reduction to anadromous fish-bearing streams is the desired outcome of road treatment activities, a more rigorous evaluation of risks and optimization of treatments is needed. Two approaches, Dynamic Programming (DP) and Genetic Algorithms (GA), were successfully used to determine the most effective treatment levels for roads and stream crossings in a pilot study basin with approximately 200 road segments and stream crossings and in an actual watershed with approximately 600 road segments and crossings. The optimization models determine the treatment levels for roads and crossings that maximize the total sediment saved within a watershed while maintaining the total treatment cost within the specified budget. The optimization models import GIS data on roads and crossings and export the optimal treatment level for each road and crossing to the GIS watershed model.
... Both models performed better than either a policy of minimal erosion control treatments applied uniformly across the landscape, or a policy of maximum treatment on roads near streams. The models can be extended to include other considerations; for example, by weighting locations that are susceptible to debris torrents or adjacent to critical habitat, by modelling changes in runoff pathways on forest road networks (Croke et al., 2005) or by incorporating the uncertainty of the effectiveness of road treatments through stochastic dynamic programming (Baker et al., 2004). ...
Many forested steeplands in the western United States display a legacy of disturbances due to timber harvest, mining or wildfires, for example. Such disturbances have caused accelerated hillslope erosion, leading to increased sedimentation in fish-bearing streams. Several restoration techniques have been implemented to address these problems in mountain catchments, many of which involve the removal of abandoned roads and re-establishing drainage networks across road prisms. With limited restoration funds to be applied across large catchments, land managers are faced with deciding which areas and problems should be treated first, and by which technique, in order to design the most effective and cost-effective sediment reduction strategy. Currently most restoration is conducted on a site-specific scale according to uniform treatment policies. To create catchment-scale policies for restoration, we developed two optimization models – dynamic programming and genetic algorithms – to determine the most cost-effective treatment level for roads and stream crossings in a pilot study basin with approximately 700 road segments and crossings. These models considered the trade-offs between the cost and effectiveness of different restoration strategies to minimize the predicted erosion from all forest roads within a catchment, while meeting a specified budget constraint. The optimal sediment reduction strategies developed by these models performed much better than two strategies of uniform erosion control which are commonly applied to road erosion problems by land managers, with sediment savings increased by an additional 48 to 80 per cent. These optimization models can be used to formulate the most cost-effective restoration policy for sediment reduction on a catchment scale. Thus, cost savings can be applied to further restoration work within the catchment. Nevertheless, the models are based on erosion rates measured on past restoration sites, and need to be updated as additional monitoring studies evaluate long-term basin response to erosion control treatments. Copyright © 2006 John Wiley & Sons, Ltd.
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