[1] The science of forests and floods is embroiled in conflict and is in urgent need of reevaluation in light of changing climates, insect epidemics, logging, and deforestation worldwide. Here we show how an inappropriate pairing of floods by meteorological input in analysis of covariance (ANCOVA) and analysis of variance (ANOVA), statistical tests used extensively for evaluating the effects of forest harvesting on floods smaller and larger than an average event, leads to incorrect estimates of changes in flood magnitude because neither the tests nor the pairing account for changes in flood frequency. We also illustrate how ANCOVA and ANOVA, originally designed for detecting changes in means, do not account for any forest harvesting induced change in variance and its critical effects on the frequency and magnitude of larger floods. The outcomes of numerous studies, which applied ANCOVA and ANOVA inappropriately, are based on logical fallacies and have contributed to an ever widening disparity between science, public perception, and often land-management policies for decades. We demonstrate how only an approach that pairs floods by similar frequency, well established in other disciplines, can evaluate the effects of forest harvesting on the inextricably linked magnitude and frequency of floods. We call for a reevaluation of past studies and the century-old, preconceived, and indefensible paradigm that shaped our scientific perception of the relation between forests, floods, and the biophysical environment.

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[1] Paired watershed studies have limited researchers wishing to disentangle road and harvesting effects on peak flows or to study management schemes other than the existing scenario. The outcomes of many paired watershed studies examining peak flows have also recently been challenged since only an approach that pairs peak flows by frequency can adequately evaluate the effects of harvesting on peak flows. This study takes advantage of a model that has been developed and extensively tested at a site containing a rich set of internal catchment process observations to examine the isolated and combined effects of roads and harvesting on the peak flow regime of a snow-dominated catchment for return periods of up to 100 years. Contrary to the prevailing perception in forest hydrology, the effects of harvesting are found to increase with return period, which is attributable to the uniqueness of peak flow runoff generation processes in snow-dominated catchments. Planned harvesting (50% harvest area) is found to have a significant effect (9%-25% over control) on peak flows with recurrence intervals ranging 10-100 years. Peak flow frequency increases after harvesting increase with return period, with the largest events (100 year) becoming 5-6.7 times more frequent, and medium-sized events (10 year) becoming 1.7-2 times more frequent. Such changes may have substantial ecological, hydrological, and geomorphological consequences within the watershed and farther downstream. Study findings suggest that peak flow regimes are fairly tolerant to the current level of harvesting in this particular watershed but that further harvesting may affect this element significantly.Citation: Kuraś, P. K., Y. Alila, and M. Weiler (2012), Forest harvesting effects on the magnitude and frequency of peak flows can increase with return period, Water Resour. Res., 48, W01544,

Abstract:Hydrologic models have increasingly been used in forest hydrology to overcome the limitations of paired watershed experiments, where vegetative recovery and natural variability obscure the inferences and conclusions that can be drawn from such studies. Models are also plagued by uncertainty, however, and parameter equifinality is a common concern. Physicallybased, spatially-distributed hydrologic models must therefore be tested with high-quality experimental data describing a multitude of concurrent internal catchment processes under a range of hydrologic regimes. This study takes a novel approach by not only examining the ability of a pre-calibrated model to realistically simulate watershed outlet flows over a four year period, but a multitude of spatially-extensive, internal catchment process observations not previously evaluated, including: continuous groundwater dynamics, instantaneous stream and road network flows, and accumulation and melt period spatial snow distributions. Many hydrologic model evaluations are only on the comparison of predicted and observed discharge at a catchment outlet and remain in the 'infant stage' in terms of model testing. This study, on the other hand, tests the internal spatial predictions of a distributed model with a range of field observations over a wide range of hydroclimatic conditions. Nash-Sutcliffe model efficiency was improved over prior evaluations due to continuing efforts in improving the quality of meteorological data collection. Road and stream network flows were generally well simulated for a range of hydrologic conditions, and snowpack spatial distributions were well simulated for one of two years examined. The spatial variability of groundwater dynamics was effectively simulated, except at locations where strong stream-groundwater interactions exist. Model simulations overall were quite successful in realistically simulating the spatiotemporal variability of internal catchment processes in the watershed, but the premature onset of simulated snowmelt for one of the simulation years has prompted further work in model development.

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