The primary objectives of this study were to address how stream temperature is influenced by (1) spatial variability in energy exchanges, (2) reach-scale stream-subsurface water interactions and (3) the net radiation dynamics associated with standing dead riparian vegetation. Stream temperature, riparian microclimate, and hydrology were characterized for a 1.5 km reach of Fishtrap Creek, located north of Kamloops, British Columbia. Within-reach air temperature and humidity variability was small, while wind speed, net radiation and surface-subsurface interactions exhibited considerable spatially variability. The field data were used to drive a deterministic energy budget model to predict stream temperature. The model was evaluated against measured stream temperature and performed well. The model indicated that the spatially complex hydrology was a significant control on the observed stream temperature patterns. A modelling exercise using three canopy cover scenarios revealed that post-disturbance standing dead trees reduce daytime net radiation reaching the stream surface by one third compared to complete vegetation removal. However, standing dead trees doubled daytime net radiation reaching the stream compared to pre-wildfire conditions. The results of this study have highlighted the need to account for the spatial variability of energy exchange processes, specifically net radiation and surface-subsurface water interactions, when understanding and predicting stream thermal regimes.

The primary objectives of this study were to address how stream temperature is influenced by (1) spatial variability in energy exchanges, (2) reach-scale stream-subsurface water interactions and (3) the net radiation dynamics associated with standing dead riparian vegetation. Stream temperature, riparian microclimate, and hydrology were characterized for a 1.5 km reach of Fishtrap Creek, located north of Kamloops, British Columbia. Within-reach air temperature and humidity variability was small, while wind speed, net radiation and surface-subsurface interactions exhibited considerable spatially variability. The field data were used to drive a deterministic energy budget model to predict stream temperature. The model was evaluated against measured stream temperature and performed well. The model indicated that the spatially complex hydrology was a significant control on the observed stream temperature patterns. A modelling exercise using three canopy cover scenarios revealed that post-disturbance standing dead trees reduce daytime net radiation reaching the stream surface by one third compared to complete vegetation removal. However, standing dead trees doubled daytime net radiation reaching the stream compared to pre-wildfire conditions. The results of this study have highlighted the need to account for the spatial variability of energy exchange processes, specifically net radiation and surface-subsurface water interactions, when understanding and predicting stream thermal regimes.

The primary objectives of this study were to address how stream temperature is influenced by (1) spatial variability in energy exchanges, (2) reach-scale stream-subsurface water interactions and (3) the net radiation dynamics associated with standing dead riparian vegetation. Stream temperature, riparian microclimate, and hydrology were characterized for a 1.5 km reach of Fishtrap Creek, located north of Kamloops, British Columbia. Within-reach air temperature and humidity variability was small, while wind speed, net radiation and surface-subsurface interactions exhibited considerable spatially variability. The field data were used to drive a deterministic energy budget model to predict stream temperature. The model was evaluated against measured stream temperature and performed well. The model indicated that the spatially complex hydrology was a significant control on the observed stream temperature patterns. A modelling exercise using three canopy cover scenarios revealed that post-disturbance standing dead trees reduce daytime net radiation reaching the stream surface by one third compared to complete vegetation removal. However, standing dead trees doubled daytime net radiation reaching the stream compared to pre-wildfire conditions. The results of this study have highlighted the need to account for the spatial variability of energy exchange processes, specifically net radiation and surface-subsurface water interactions, when understanding and predicting stream thermal regimes. / Arts, Faculty of / Geography, Department of / Graduate

<p> A levitation apparatus has been constructed for investigating the behaviour of liquid iron drops containing sulphur, whilst suspended in a moving gas stream.</p> <p> To further this investigation, a source of iron-sulphur alloys, in form and size suitable for levitation, was required. Four methods for the preparation of the desired alloys were suggested, and each was experimentally examined in sequence.</p> <p> The first 2 methods involved the quenching of a liquid solution of sulphur in iron, to give a solid alloy. The well-known behaviour of sulphur, to segregate on solidification, was observed, and the non-uniformity of the resulting alloys could not be tolerated. The third method involved preparing a large number of individual iron-sulphur samples by allowing drops of iron to fall and quench on particles of sulphur or iron sulphide. The repeatability of the method was found to be unsatisfactory. In the final attempt a levitated liquid drop of iron was equilibrated in a gas mixture of hydrogen-hydrogen sulphide. This method was considered more successful than the earlier three, and has the advantage that the prepared alloy drop is levitated and at the desired temperature.</p> / Thesis / Master of Engineering (MEngr)

Beaver dams alter streams characteristics in a way that promotes the diversity of aquatic species and provides a wide distribution of temperatures within beaver ponds. In order to quantify the spatial distribution of these temperatures, a process-based temperature model was developed for a beaver pond in Northern Utah. This model provided insight into the processes and characteristics that are driving these temperatures. Solar radiation is one of these processes that is often the primary driver of stream temperature. There is a need to develop methods to measure the fate of solar radiation within the water to better represent solar radiation within stream temperature models. Black-body pyranometers are instruments that measure solar radiation in air, but require corrections for use underwater. Studies were conducted investigating methods for correcting these instruments. Based on the results of these studies it is suggested that these corrections are dependent on the spectrum of the light source and that the instrument needs further corrections when the light source is measured from different angles; therefore there is a need for further investigation into pyranometer corrections in order to measure the fate of solar radiation in natural water bodies. Combined, this research provides methods and suggests additional research opportunities for more accurately quantifying and predicting stream temperatures for waters impacted by beaver.

Water temperature is an important variable for aquatic ecosystems. Salmonid population numbers and distribution are heavily influenced by stream temperature, and there is growing concern about the health of salmonid populations with anticipated climate change. Managers are looking to efficiently evaluate options to maintain stream temperatures needed by salmonids. This study evaluated and compared stream temperature restoration alternatives in two streams with warm temperatures using stream temperature monitoring and modeling. The first study identified pockets of cold water that are important to native fish species in Nevada’s Walker River. Comparison of monitoring results with existing basin-scale model outputs identified two habitat features, beaver dams and irrigation return flow channels, that maximize stream temperature variability. Restoration should maintain and enhance these features, although different restoration approaches may be needed at different locations. This study may provide guidance for the interpretation of stream temperature results from other basin-scale models. The second study quantified stream temperature effects of wildfire and restoration plantings in Oregon’s Meadow Creek with current and projected mid-21st century climate. A stream temperature model developed and applied using Heat Source found restoration eliminated days above the lethal threshold (25°C) for salmonids and decreased the number of days exceeding spawning criteria during spawning periods. Days exceeding salmonid spawning (13°C) and rearing (18°C) thresholds were reduced by all vegetation restoration scenarios, but elimiated by none. Results highlights the importance of the length and location of restoration, which can maximize pockets of cold water for salmonids or alleviate the impact of warm water sections.

Stream temperature (ST) is a primary determinant of individual stream species distributions and community composition. Moreover, thermal modifications associated with urbanization, agriculture, reservoirs, and climate change can significantly alter stream ecosystem structure and function. Despite its importance, we lack ST measurements for the vast majority of USA streams. To effectively manage these important systems, we need to understand how STs vary geographically, what the natural (reference) thermal condition of altered streams was, and how STs will respond to climate change. Empirical ST models, if calibrated with physically meaningful predictors, could provide this information. My dissertation objectives were to: (1) develop empirical models that predict reference- and nonreference-condition STs for the conterminous USA, (2) assess how well modeled STs represent measured STs for predicting stream biotic communities, and (3) predict potential climate-related alterations to STs. For objective 1, I used random forest modeling with environmental data from several thousand US Geological Survey sites to model geographic variation in nonreference mean summer, mean winter, and mean annual STs. I used these models to identify thresholds of watershed alteration below which there were negligible effects on ST. With these reference-condition sites, I then built ST models to predict summer, winter, and annual STs that should occur in the absence of human-related alteration (r2 = 0.87, 0.89, 0.95, respectively). To meet objective 2, I compared how well modeled and measured ST predicted stream benthic invertebrate composition across 92 streams. I also compared predicted and measured STs for estimating taxon-specific thermal optima. Modeled and measured STs performed equally well in both predicting invertebrate composition and estimating taxon-specific thermal optima (r2 between observation and model-derived optima = 0.97). For objective 3, I first showed that predicted and measured ST responded similarly to historical variation in air temperatures. I then used downscaled climate projections to predict that summer, winter, and annual STs will warm by 1.6 °C - 1.7 °C on average by 2099. Finally, I used additional modeling to identify initial stream and watershed conditions (i.e., low heat loss rates and small base-flow index) most strongly associated with ST vulnerability to climate change.

For this dissertation I studied groundwater and surface water interactions in the Kenai Lowlands, Alaska. In particular, I examine two important aspects of groundwater and surface water interactions: 1) Groundwater's influence on surface-water temperature; and 2) Groundwater's role in forming hydrologic flow paths that can connect uplands to streamside wetlands and streams. Chapter 2 investigates the controls on stream temperature in salmon-bearing headwater streams in two common hydrogeologic settings: 1) drainage-ways, which are low-gradient streams that flow through broad valleys; and 2) discharge-slopes, which are high gradient streams that flow through narrow valleys. The results from chapter 2 showed significant differences in stream temperatures between the two hydrogeologic settings. Observed stream temperatures were higher in drainage-way sites than in discharge-slope sites, and showed strong correlations as a continuous function with the calculated topographic metric flow-weighted slope. Additionally, modeling results indicated that the potential for groundwater discharge to moderate stream temperature is not equal between the two hydrogeologic settings, with groundwater having a greater moderating effect on stream temperature at the low gradient drainage-way sites. Chapter 3 examines the influence of groundwater on juvenile coho salmon winter habitat along the Anchor River. Two backwater habitats were selected from the larger set of 25 coho overwintering sites from a previous study for an in-depth hydrologic analysis. The results from chapter 3 showed that the type of groundwater discharge (i.e., focused versus diffuse groundwater discharge) can play an important role in determining habitat suitability in these backwater sites. During winter, focused discharge from a local groundwater seep maintained higher surface-water temperatures and higher concentrations of dissolved oxygen compared to the site with more diffuse groundwater discharge. Chapter 4 investigates the linkages along hydrologic flow paths among alder (Alnus spp.) stands, streamside wetlands, and headwater streams. Chapter 4 tested four related hypotheses: 1) groundwater nitrate concentrations are greater along flow paths with alder compared to flow paths without alder; 2) on hillslopes with alder, groundwater nitrate concentrations are highest when alder stands are located near the streamside wetlands at the base of the hillslope; 3) primary production of streamside wetland vegetation is N limited and wetlands are less N limited when alder stands are located nearby along flow paths; and 4) stream reaches at the base of flow paths with alder have higher nitrate concentrations than reaches at the base of flow paths without alder. The results from chapter 4 showed that groundwater nitrate concentrations were highest along flow paths with alder, however no difference was observed between flow paths with alder located near versus alder located further from streamside wetlands. Vegetation had a greater response to N fertilization in streamside wetlands that were connected to flow paths without alder and less when alder stands were near. Finally, higher nitrate concentrations were measured in streams at the base of flow paths with alder. The combined results of this dissertation showed that, in the Kenai Lowlands, groundwater and surface water interactions have a direct influence on the local ecology and that a fundamental understanding of the hydrology can aid in the successful management and protection of this unique and important ecosystem.

The health of freshwater aquatic systems, particularly stream networks, is mainly influenced by water temperature, which controls biological processes and influences species distributions and aquatic biodiversity. Thermal regimes of rivers are likely to change in the future, due to climate change and other anthropogenic impacts, and our ability to predict stream temperatures will be critical in understanding distribution shifts of aquatic biota. Spatial statistical network models take into account spatial relationships but have drawbacks, including high computation times and data pre-processing requirements. Machine learning techniques and generalized additive models (GAM) are promising alternatives to the SSN model. Two machine learning methods, gradient boosting machines (GBM) and Random Forests (RF), are computationally efficient and can automatically model complex data structures. However, a study comparing the predictive accuracy among a variety of widely-used statistical modeling techniques has not yet been conducted. My objectives for this study were to 1) compare the accuracy among linear models (LM), SSN, GAM, RF, and GBM in predicting stream temperature over two stream networks and 2) provide guidelines in choosing a prediction method for practitioners and ecologists. Stream temperature prediction accuracies were compared with the test-set root mean square error (RMSE) for all methods. For the actual data, SSN had the highest predictive accuracy overall, which was followed closely by GBM and GAM. LM had the poorest performance overall. This study shows that although SSN appears to be the most accurate method for stream temperature prediction, machine learning methods and GAM may be suitable alternatives.

Forest harvesting has been shown to cause various changes in water quantity and water quality parameters, highlighting the need for comprehensive forest practice rules. Studies show a myriad of impacts to ecosystems as a result of watershed level changes, such as forest harvesting. Being able to better understand the impact that forest harvesting can have on stream temperature is especially critical in locations where federally threatened or endangered fish species are located. The overall goal of this research project is to assess responses in stream temperature to various riparian and forest harvest treatments in a maritime, mountainous environment. The results of this study aim to inform decision makers with additional information pertaining to the effects of forest harvest on water temperature. Modeling is done as a part of the third Caspar Creek Paired Experimental Watershed study. Located in Mendocino County, the site provides a place for California researchers and decision makers to learn about the cumulative watershed effects of forest management operations on peak flows, sediment production, anadromous fish, macro-invertebrate communities, nutrient cycling and more. Historic data was used to calibrate the Distributed Hydrology Soil Vegetation Model (DHSVM) and River Basin Model (RBM) to measured stream temperatures in the South Fork of Caspar Creek (SFC) for hydrologic years 2010-2016. Critical summer time periods, when temperatures are highest and flows are low, are the primary concern for this work. The key modeling scenarios evaluated were (1) varying percentages of Watercourse and Lake Protection Zones (WLPZ) canopy cover, (2) the 2018-2019 SFC forest harvest and (3) an experimental design converting dominant riparian vegetation along 300-yard stream reaches. Modeling results showed that stream temperatures begin to rise above third-growth conditions when canopy cover is reduced to 25% and 0% retention levels. Larger increases in Maximum Weekly Maximum Temperature (MWMT) values, compared to Maximum Weekly Average Temperature (MWAT) values, were seen across all scenarios. There was essentially no difference between altering buffer areas along only class I streams, compared to along all stream classes. At the 0% canopy retention, MWMT values consistently rose above recommended thermal limits for Coho salmon (Oncorhynchus kisutch) and state regulations prohibiting more than a 5 degree F increase in waters. Clearcutting the entire watershed produced less of an effect than simulations clearing on only the riparian area, suggesting that groundwater inflows act to mitigate stream temperature rises in the SFC. The 2018-2019 harvest showed a relatively consistent increase in MWAT values (avg. 0.11 degree C) and more varied increases in MWMT values (avg. 0.32 degree C). Simulations converting dominant riparian vegetation by clearing could not be considered conclusive due to sensitivity analyses suggesting potentially unrealistic tracking of downstream temperatures. Additional sensitivity analyses suggest that tree height and the monthly extinction coefficient (a function of Leaf Area Index) are most influential on stream temperature changes in SFC. This is consistent with other modeling studies and suggests stream temperature management focus on tall, dense buffers as opposed to wider buffer widths.