Integrating stormwater management and stream restoration strategies for greater water quality benefits.

Urbanization alters the delivery of water and sediment to receiving streams, often leading to channel erosion and enlargement, which increases loading of sediment and nutrients, degrades habitat, and harms sensitive biota. Stormwater control measures (SCMs) are constructed in an attempt to mitigate some of these effects. In addition, stream restoration practices such as bank stabilization are increasingly promoted as a means of improving water quality by reducing downstream sediment and pollutant loading. Each unique combination of SCMs and stream restoration practices results in a novel hydrologic regime and set of geomorphic characteristics that interact to determine stream condition, but in practice, implementation is rarely coordinated due to funding and other constraints. In this study, we examine links between watershed-scale implementation of SCMs and stream restoration in Big Dry Creek, a suburban watershed in the Front Range of northern Colorado. We combine continuous hydrologic model simulations of watershed-scale response to SCM design scenarios with channel evolution modeling to examine interactions between stormwater management and stream restoration strategies for reducing loading of sediment and adsorbed phosphorus from channel erosion. Modeling results indicate that integrated design of SCMs and stream restoration interventions can result in synergistic reductions in pollutant loading. Not only do piecemeal and disunited approaches to stormwater management and stream restoration miss these synergistic benefits, they make restoration projects more prone to failure, wasting valuable resources for pollutant reduction. We conclude with a set of recommendations for integrated planning of SCMs and stream restoration to simultaneously achieve water quality and channel protection goals.

The role of warm, dry summers and variation in snowpack on phytoplankton dynamics in mountain lakes.

Climate change is altering biogeochemical, metabolic, and ecological functions in lakes across the globe. Historically, mountain lakes in temperate regions have been unproductive because of brief ice-free seasons, a snowmelt-driven hydrograph, cold temperatures, and steep topography with low vegetation and soil cover. We tested the relative importance of winter and summer weather, watershed characteristics, and water chemistry as drivers of phytoplankton dynamics. Using boosted regression tree models for 28 mountain lakes in Colorado, we examined regional, intraseasonal, and interannual drivers of variability in chlorophyll a as a proxy for lake phytoplankton. Phytoplankton biomass was inversely related to the maximum snow water equivalent (SWE) of the previous winter, as others have found. However, even in years with average SWE, summer precipitation extremes and warming enhanced phytoplankton biomass. Peak seasonal phytoplankton biomass coincided with the warmest water temperatures and lowest nitrogen-to-phosphorus ratios. Although links between snowpack, lake temperature, nutrients, and organic-matter dynamics are increasingly recognized as critical drivers of change in high-elevation lakes, our results highlight the additional influence of summer conditions on lake productivity in response to ongoing changes in climate. Continued changes in the timing, type, and magnitude of precipitation in combination with other global-change drivers (e.g., nutrient deposition) will affect production in mountain lakes, potentially shifting these historically oligotrophic lakes toward new ecosystem states. Ultimately, a deeper understanding of these drivers and pattern at multiple scales will allow us to anticipate ecological consequences of global change better.

Quantifying pollutant loading from channel sources: Watershed-scale application of the River Erosion Model.

Phosphorus and fine sediment pollution are primary causes of water quality degradation. Streambank erosion is a potentially significant source of fine sediment and particulate phosphorus to watersheds, but it remains difficult to quantify the magnitude of this loading. A new, easily applied, watershed scale model was used to simulate the potential for future phosphorus and sediment loading from channel erosion in two watersheds: Big Dry Creek, Colorado and Lick Creek, North Carolina. The projected magnitude of loading for phosphorus is about an order of magnitude higher in Big Dry Creek compared to Lick Creek (∼280 kg/yr and ∼50 kg/yr, respectively), while sediment loading results are similar (∼950 ton/yr). In both watersheds, model results suggest that channel erosion will not contribute a significant amount of phosphorus to the watershed (∼1-4% of historic watershed total from all pollutant sources) but will contribute a large amount of sediment (30-100% of historic watershed total). Uncertainty in these estimates is high, but quantifying confidence in model projections is important for understanding and using model results. Importantly, modeling shows no decrease in loading over the 40-year model time frame in either watershed, suggesting that the channels are not adjusting to a new stable state and erosion will continue to be a pollutant source. Lick Creek model results are sensitive to upstream sediment supply while Big Dry Creek's are not, reinforcing the importance of considering alterations to both the hydrologic and sediment regimes when analyzing potential channel changes - at least in vertically active channels. This new modeling approach is useful for estimating historic and future phosphorus and sediment loading from channel erosion, an important first step in effective management to improve water quality.