Hydrologic and suspended sediment effects of forest roads using field and DHSVM modelling studies

Abstract

Forest road hydrologic and surface erosion effects were evaluated using a two-step approach in South Fork Caspar Creek: (1) road runoff and suspended sediment measurements and (2) use of the Distributed Hydrology Soil Vegetation Model (DHSVM) to examine road scenarios at the watershed scale. Statistical evaluation showed the best multiple linear regression (MLR) model to predict Log10 suspended sediment load (SSL) was from road runoff event peak flow and cube root of maximum turbidity combined with road characteristics of either cutslope cover or road surface type. MLR using road dimensions and event precipitation, without runoff or turbidity, suggested the best model to predict Log10 SSL used road length times slope squared (LS2), road surface type, and cutslope area. DHSVM simulations for three different road drainage scenarios for two road networks were used to evaluate hydrologic and suspended sediment effects. The 2018 road network represented road networks placed high on slopes away from watercourses and a pre-1974 road network lower on the hillslopes with high numbers of watercourse crossings and streamside roads. Forest harvest of South Fork Caspar Creek (SFC) was predicted by DHSVM to increase storm peak flows by 1.5% to 11% relative to pre-harvest, no-road peak flows. The 2018 road network, with 13% of road length adjacent to watercourses, was predicted to make < 2% increase in peak flows. In contrast, the pre-1974 road network scenario, with 58% of road length adjacent to watercourses, was predicted to increase peak flows as much as 46%. There were low levels of suspended sediment contributions, 23–86 kg/ha/yr, predicted from the 2018 road network scenario with few road watercourse crossings. The pre-1974 road network was predicted to contribute 347 – 2158 kg/ha/yr, depending on road drainage scenario.