Periods of summertime low flows are often critical for fish. This study quantified the impacts of forest clear-cutting on summertime low flows and fish habitat and how they evolved through time in two snowmelt-dominant headwater catchments in the southern interior of British Columbia, Canada. A paired-catchment analysis was applied to July-September water yield, the number of days each year with flow less than 10% of mean annual discharge, and daily streamflow for each calendar day. The postharvest time series were divided into treatment periods of approximately 6-10 years, which were analysed independently to evaluate how the effects of forestry changed through time. An instream flow assessment using a physical habitat simulation-style approach was used to relate streamflow to the availability of physical habitat for resident rainbow trout. About two decades after the onset of logging and as the extent of logging increased to approximately 50% of the catchments, reductions in daily summertime low flows became more significant for the July-September yield (43%) and for the analysis by calendar day (11-68%). Reductions in summertime low flows were most pronounced in the catchment with the longest postharvest time series. On the basis of the temporal patterns of response, we hypothesize that the delayed reductions in late-summer flow represent the combined effects of a persistent advance in snowmelt timing in combination with at least a partial recovery of transpiration and interception loss from the regenerating forests. These results indicate that asymptotic hydrological recovery as time progresses following logging is not suitable for understanding the impacts of forest harvesting on summertime low flows. Additionally, these reductions in streamflow corresponded to persistent decreases in modelled fish habitat availability that typically ranged from 20% to 50% during the summer low-flow period in one of the catchments, suggesting that forest harvest may have substantial delayed effects on rearing salmonids in headwater streams. K E Y W O R D Sfish, forestry, headwater, hydrology, instream flow assessment, logging, low flows, snowmeltdominant
Paired-catchment studies conducted on small (< 10 km2) rain-dominated catchments revealed that forest harvesting resulted in a period of increased warm-season low flows ranging from less than five years to more than two decades, consistent with the results of stand-level studies and process considerations. Of the five paired-catchment studies in snow-dominated regions, none revealed a statistically significant change in warm-season low flows in the first decade following harvest, although two exhibited non-significant higher flows in August and September and one had lower flows. Two studies, one of rain-dominated catchments and one of snow-dominated catchments, found that summer low flows became more severe (i.e., lower) about two decades or so following harvest. These longer-term results indicate that indices such as equivalent clearcut area, as currently calculated using monotonic recovery curves, may not accurately reflect the nature of post-harvest changes in low flows. Studies focussed on medium to large catchments (tens to thousands of km2 in area) found either no statistically significant relations between warm-season low flows and forest disturbance, or inconsistent responses. Attempts to synthesize existing studies are hampered by the lack of a common low-flow metric among studies, as well as detailed information on post-harvest vegetation changes. Further fieldresearch and process-based modelling is required to help elucidate the underlying processes leading to the results from these paired-catchment studies and to enhance the ability to predict streamflow responses to forest harvesting, especially in the context of a changing climate. KEYWORDS: streamflow; forestry; low flows; fish habitat; hydrologic recovery
Conventional hydraulic-habitat modelling methods are time-consuming to implement.In response to repeated calls for more efficient and practical approaches, researchers have developed a geomorphic instream-flow tool (GIFT) that combines a method to simulate reach-averaged hydraulics at flows less than bankfull and depth and velocity frequency distributions to develop streamflow-fish habitat relationships. This approach requires fewer resources to implement than conventional methods, but it has not been widely adopted because it has been subject to minimal testing and validation. This study evaluates the performance of GIFT by comparing its outputs to empirical measurements and conventional model outputs from eight rivers in western North America. The results of this comparison indicate that the root mean square errors for average depth and velocity were 0.078 m and 0.047 m/s, respectively, and the fit of modelled depth and velocity frequency distributions was satisfactory (index of agreement >0.9) for 11 of 15 surveys for depth and 12 of 15 surveys for velocity.GIFT-derived fish habitat-streamflow relationships peaked at lower flows than benchmark relationships in smaller streams (mean annual discharge [MAD] < 0.15 m 3 /s) and are markedly differed from the benchmark in the largest river (MAD of 87 m 3 /s). GIFT was also paired with a geomorphic regime model to predict the direction of changes in channel morphology and fish habitat following forest harvesting in one watershed. GIFT provides an alternative to conventional modelling approaches for single-thread, gravel-bed rivers with a MAD of around 15 m 3 /s or less. Application of this technique outside of these bounds, or in other regions should proceed with caution, as these scenarios have not been tested.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.