A holistic monitoring approach for water quality BMP and Forest Watershed Risk assessment

Abstract

The use of water quality BMPs during forest harvesting reduces potential impacts to water quality, and previous monitoring work has documented high levels of BMP use. However, the utility of past monitoring efforts for water management is limited, because monitoring estimates are provided at large scales and lacking situational context conducive to local management. Here we present a framework for holistic monitoring at the watershed scale that incorporates estimates of BMP implementation with forest disturbance metrics and watershed characteristics to qualitatively evaluate the risk of forestry activities impacting water quality in a given watershed. Using three case study watersheds in Minnesota, USA, we demonstrate that forest disturbance patterns and BMP implementation are variable across watersheds, and the implications of these differences for water quality are dependent on the physical characteristics of a watershed such as stream density, soil properties, and topography. An implicit assumption in our assessment is that risks of water quality degradation are greatest with lower levels of BMP implementation and where forest disturbance is concentrated in time and space. The monitoring approach is being used in Minnesota to guide adaptive management at the watershed scale to preemptively address water quality risks associated with forestry activities.