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. E N V I R O N M E N T A L C O N C E R N S have increasingly turned in recent years to problems that cannot be solved experimentally. The long-term consequence of intensive forest culture is one such problem. Timber crops typically take from 25 yr to more than 100 yr to mature. Consequently, the effect of repeated harvests could be estimated experimentally only in a study lasting hundreds of years. Even if that approach was practical, it would likely be too late to take corrective action by the time the study’s findings were known. Therefore, of necessity, one must resort to simulations incorporating current understanding of the relevant processes in order to estimate the long-term consequences of current forest management practices. A simulation has both strengths and weaknesses when compared to watershed experiments. Its greatest weakness is that it is a simplification of nature and dependent upon the modeler’s skill in programming natural processes accurately. The strength of a simulation is that it can represent the mean conditions of the area being modeled and that it can explore the effect of a larger spectrum of possible sequences of events. Unlike a watershed experiment, the results of a simulation need not be the victim of the unique series of meteorological events occurring during the study. When considering long-range problems, this is a particularly desirable property. Nonetheless, it must be remembered that measuring the performance of actual watersheds is the only way by which the reasonableness of model assumptions can be tested. Such testing, however, is limited to those conditions to which the watersheds were subjected. The main values of a simulation are not to make numerically accurate evaluations of variables that quantify watershed behavior, but to scale processes and variables in terms of their importance to integrated watershed behavior and to reveal gaps in information on linkages between watershed processes. Both paired-watershed studies and model simulations must be closely linked if cumulative watershed effects are to be understood. A simulation approach is appropriate, quite apart from the time constraints just mentioned, because of the complexity of the forest ecosystem and the uncertainty concerning the spectrum of environmental conditions that would prevail during a period spanning hundreds of years. A Monte Carlo simulation permits the explicit inclusion of estimates of variability and Pacific Southwest Research Station, USDA-FS, 1700 Bayview Drive, Arcata, CA 95521. Received 19 Feb. 1990. *Corresponding author. Published in J. Environ. Qual. 20:36-42 (1991). 36 What follows is a primitive simulation of the changes in stream bed conditions resulting from increased bedload transport associated with three logging strategies. Only the effect of landslide erosion was considered. This limited scope was chosen because the effect of logging on erosion and sedimentation and the resultant damage to fish habitat is an important concern in the coastal environment being modeled. The model is in a continual state of expansion and improvement to more realistically address this and other environmental conflicts. A next important step is to conduct sensitivity analyses on the model inputs and to begin to validate simulation accuracy. ZIEMER ET AL.: WATERSHED EFFECTS & INTENSIVE FOREST MANAGEMENT 37 THE MODELED ENVIRONMENT