Modeling the Cumulative Watershed Effects of Forest Management Strategies

There is increasing concern over the possibility of adverse cumulative watershed effects from intensive forest management. It is impractical to address many aspects of the problem experimentally because to do so would require studying large watersheds for 100 yr or more. One such aspect is the long-term effect of forest management strategies on erosion and sedimentation and the resultant damage to fish habitat. Is dispersing activities in time and space an effective way to minimize cumulative sedimentation effects? To address this problem, Monte Carlo simulations were conducted on four hypothetical 10 000-ha fifth-order forested watersheds: one watershed was left undisturbed, one was completely clearcut and roaded in 10 yr, with cutting starting at the head of the watershed and progressing toward the mouth, another was cut at the rate of 1% each year beginning at the watershed’s mouth and progressing upstream, and another was cut at a rate of 1% each year, with individual cut areas being widely dispersed throughout the watershed. These cutting patterns were repeated in succeeding centuries, rebuilding one-third of the road network every 100 yr. The parameters governing the simulations were based on recent data from coastal Oregon and northwestern California, Mass wasting, the most important source of sediment in that environment, was the only hillslope process modeled. The simulation results suggest that (i) the greatest differences between management strategies appeared in the first 100 yr and were related primarily to the rate of treatment. By the second 100 yr, when all watersheds had been treated, the principal difference between logging strategies was the timing of impacts. (ii) Dispersing harvest units did not significantly reduce cumulative effects. (iii) The frequency of bed elevation changes between 1 and 4 cm is dramatically increased by logging. uncertainty in a model. These properties are essential for the characterization of meteorological inputs and can be used to account for uncertainty in hydrologic and geomorphic parameters. Paired-watershed experiments are frequently used to investigate the effects of land use on hydrologic processes. Normally the results of paired-watershed experiments are assumed to be more real than those obtained from computer simulations. That assumption should be scrutinized a little more carefully. Paired-watershed experiments record the natural interplay of all the relevant processes. They do so, however, at one location during a relatively short period of time. Therefore, statistical inferences of such studies apply only to the study watersheds and only to the conditions operating during the study periods. All else is extrapolation based on professional judgement, not statistical inference.