Abstract
Forest harvesting has been shown to effect water quantity and water quality parameters, highlighting the need for comprehensive forest practice rules. Being able to understand and predict these impacts on stream temperature is especially critical where federally threatened or endangered fish species are located. The goal of this research was to predict responses in stream temperature to potential riparian and forest harvest treatments in a maritime, mountainous environment. The Distributed Hydrology Soil Vegetation Model (DHSVM) and River Basin Model (RBM) were calibrated to measured streamflow and stream temperatures in the South Fork of the Caspar Creek Experimental Watersheds during critical summer periods when temperatures are highest and flows are low for hydrologic years 2010–2016. The modeling scenarios evaluated were (1) varying percentages of stream buffer canopy cover, (2) a harvest plan involving incrementally reduced stand densities in gauged sub-watersheds, and (3) an experimental design converting dominant riparian vegetation along set reaches. The model predicted a noticeable rise in stream temperatures beginning when stream buffer canopy cover was reduced to 25 and 0% retention levels. Larger increases in Maximum Weekly Maximum Temperatures (MWMT), compared to Maximum Weekly Average Temperatures (MWAT), occurred across all scenarios. There was essentially no difference in MWAT or MWMT between altering buffers along only fish bearing (Class I) watercourses and altering buffers along all watercourses. For the scenario with stream buffers at 0% retention, MWMTs consistently rose above recommended thermal limits for coho salmon(Oncorhynchus kisutch). Predictions when clearcutting the entire watershed showed less of an effect than simulations with 0% buffer retention, suggesting groundwater inflows mitigate stream temperature rises in the South Fork. The harvest simulation showed a small but consistent increase in MWATs (avg. 0.11°C), and more varied increases in MWMTs (avg. 0.32°C). Sensitivity analyses suggest potentially unrealistic tracking of downstream temperatures, making the vegetation conversion simulations inconclusive. Additional sensitivity analyses suggest tree height and monthly extinction coefficient (a function of leaf area index) were most influential on temperatures in the South Fork, which was consistent with other modeling studies suggesting management focus on tall, dense buffers compared to wider buffer widths.
Highlights
It is commonly accepted that the removal of over-stream tree canopy during forest harvesting increases stream temperatures (Brown and Krygier, 1970; Patric, 1980; Beschta et al, 1987; Lynch and Corbett, 1990; Johnson and Jones, 2000; Carroll et al, 2004; Moore et al, 2005; Wilkerson et al, 2006)
This study aims to better understand the efficacy of California Forest Practice Rules (FPR) streamside buffer regulations at mitigating impacts on stream temperature by using the Distributed Hydrology Soil Vegetation Model (DHSVM) and the River Basin Model (RBM), which take into account many of the aforementioned factors that may contribute to buffer width performance
Calibration of DHSVM focused on maximizing the EREL, a metric that is sensitive to streamflows around the mean value, providing a better indicator of fit of summer lowflow than the Nash Sutcliffe Efficiency (NSE)
Summary
It is commonly accepted that the removal of over-stream tree canopy during forest harvesting increases stream temperatures (Brown and Krygier, 1970; Patric, 1980; Beschta et al, 1987; Lynch and Corbett, 1990; Johnson and Jones, 2000; Carroll et al, 2004; Moore et al, 2005; Wilkerson et al, 2006). Macdonald et al (2003), recorded increases of 4–6◦C 5 years following harvest using 20 and 30 m buffers. Additional factors such as stream orientation (NorthSouth vs East-West), location (latitude and elevation), depth and velocity of flow, hydrologic regime (spatial and temporal variations in the water budget), groundwater and headwater inputs, forest roads, drainage size, geology, and weather are known to play a role in the effectiveness of buffer widths (Larson and Larson, 1996; Moore et al, 2005; Gomi et al, 2006; DeWalle, 2010), making one size fits all guidelines for large areas potentially ineffective
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