Metabolic and biogeochemical processes in hyporheic zones may depend on inputs of coarse particulate organic matter. Our research focused on how differing quantity and quality of organic matter affects metabolism and nutrient retention in the hyporheic zone of a low-order Appalachian stream. We hypothesized that hyporheic metabolic rates should increase with organic matter additions because the biotic activity is limited by organic matter availability. Four sets (n=4 amendments/set) of plots were established on a tributary of Hugh White Creek, NC. Sediment was extracted and was either supplemented with leaves, wood, or plastic strips, or sediments remained unamended sediments. Following augmentation sediments were reimbedded and approximately three months later sediment was removed from each plot. Aerobic and anaerobic metabolism were measured as the change in O2, and CO2 in recirculating microcosms. At the same time, we monitored other possible terminal electron accepting processes and changes in nutrients. Aerobic metabolism was low in all treatments and respiratory quotients calculated for all treatments indicated that metabolism was dominated by anaerobic processes. Anaerobic and total (combined aerobic and anaerobic) respiration rates were significantly greater (P < 0.05) in plots treated with leaf organic matter compared to controls. Nutrient retention (NO3-N, NH4-N, and DOC) was enhanced in augmented treatments. Measured losses of dissolved organic carbon accounted for 50% total carbon liberated by respiration in amended sediments, whereas in unamended sediments loss of DOC represented only 7% of measured respiration. Augmentation with greater quality organic matter stimulated respiration in hyporheic sediments. Anaerobic processes dominated metabolic rates in both control and amended sediments. Enhanced metabolic rates increased retention of many solutes indicating that energy flow and nutrient dynamics in the subsurface of streams may depend upon the quantity and quality of imported carbon. / Master of Science

The structure and function of headwater streams was evaluated in response to livestock exclusion implemented through Virginia's Conservation Reserve Enhancement Program (CREP). We measured riparian plant characteristics along with stream organic matter dynamics, benthic macroinvertebrates, algal biomass, and leaf breakdown in non-fenced, fenced, and forested streams. Increased growth of non-woody vegetation and the pre-existence of woody plants had a significant influence on stream organic matter dynamics. Tree basal area in a 20 m wide riparian corridor was predictive of stream coarse benthic organic matter standing stocks. Higher benthic organic matter standing stocks and differences in algal biomass in fenced and forested sites indicate different food resources may be structuring macroinvertebrate communities in these systems. We found a significant relationship between coarse benthic organic matter and percent shredder density, and scraper density generally followed patterns of algal biomass among treatments. Leaf breakdown rates among treatments were not indicative of differences in shredder density with two of the three fenced sites having the fastest overall breakdown rates observed. We attributed faster breakdown rates in these streams to available food resources and shredder community structure existing prior to the implementation of livestock exclusion. Our results suggest that a certain amount of ecological recovery may be possible through livestock exclusion. Macroinvertebrate structure in our study streams was primarily influenced by the presence or absence of riparian trees. Maturation and successional changes in woody riparian vegetation after livestock exclusion may allow certain characteristics of pastoral streams to return to those found in forested reaches. / Master of Science

Current consumer GPUs can be used as high performance stream processors and are a tempting platform to be used to implement raytracing. In this paper I briefly present raytracing principles and methods used to accelerate it, modern GPUs programmable pipeline and examples of its use. I describe stream processing in general and available interfaces enabling the usage of GPU as stream processor. Then I present my GPU raytracer implementation, used algorithms and experiments I have made.

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Two existing stream dispersion computer models were applied to a hypothetical stream to analyze mixing zone requirements due to point and non-point discharges. Mixing zone curves were developed to define acceptable and unacceptable regions of stream response for stead-state and transient conditions. The impact on these regions due to varying quantitative and qualitative characteristics of the stream and waste discharges were investigated. In addition, a sensitivity analysis was conducted on the response of a transient one-dimensional stream dispersion model. A logarithmic linear regression analysis, relating the number of time increments specified to a dimensionless hydrograph shape factor for known storm water and combined events, gave correlation coefficients of 0.915 and0.925 for 94% and 98% model accuracies, respectively.

In the United States, stream restoration is currently a billion-dollar industry. Though it is commonly used as a method for stream impact mitigation, Total Maximum Daily Load (TMDL) crediting, and stormwater management, there is little scientific knowledge defending stream restoration as an effective tool for addressing these issues. In particular, few studies have been conducted with the goal of providing recommendations for future design improvements. To improve stream restoration success rates by advising practitioners and stakeholders in site selection and project assessment, a selection of completed Maryland stream restoration projects were assessed at the watershed and project level. Watershed, site, and design characteristics were quantified using ArcGIS, restoration design plans and monitoring reports. Using current literature and expert advice, stream restoration assessment methodologies were developed to assess geomorphic function and design success both in the field and through monitoring reports. Multiple linear regression analysis and related methods were then used to identify correlations and relationships between watershed- and project-level characteristics and stream restoration success. At the watershed scale, land use was most strongly related to functional success, with projects in more natural watersheds exhibiting higher geomorphic function. Design scores correlated negatively with watershed area. At the project level, projects with higher width to depth ratios scored higher on the functional assessment, while particle size was negatively correlated with geomorphic function. Study results suggest stream restoration designs are improving over time, but the ability to determine project success from monitoring remains limited. / Master of Science / In the United States, stream restoration is currently a multi-billion-dollar industry. Though it is commonly used as a method for water quality improvement, stormwater management, and habitat restoration after human disturbance, there is little scientific knowledge defending stream restoration as an effective tool for addressing these issues. In particular, few studies have been conducted with the goal of providing recommendations for future design improvements. To improve stream restoration success rates by advising practitioners and stakeholders in site selection and project assessment, a selection of completed Maryland stream restoration projects were assessed at the watershed and project level. Watershed, site, and design characteristics were quantified using spatial data analysis software along with restoration design plans and monitoring reports. Using current literature and expert advice, stream restoration assessment methodologies were developed to assess stream ability to transport water and sediment, as well as design resilience using monitoring reports, and during field visits. Data analysis showed projects built in more rural, natural watersheds were more similar to undisturbed streams. Projects constructed in large watersheds were less likely to remain stable after repeated storm events. At the project level, projects that were wider rather than deep were more functional, while those with significant amounts of large rock were less successful. Stream restoration designs seem to be improving with time, but the ability to determine project success from monitoring remains limited.

Passive samplers can be used to determine time-integrated patterns of water chemistry at one or many locations throughout a stream network while minimizing cost and sampling time. A passive flux meter (PFM) simultaneously estimates time-averaged water and solute mass fluxes in flowing water. PFMs have been used in groundwater to quantify contaminant flux but have been used only very recently in streams. In this study, PFMs were deployed in the surface and subsurface of headwater stream channels to examine the efficacy of the device to quantify mean concentrations of calcium, aluminum, and sulfur in streams of the Hubbard Brook Experimental Forest in New Hampshire, USA. In general, the PFM estimates of surface and subsurface stream chemistry were more accurate when flow rates were higher and more water passed through the PFM. During the lowest flows, PFMs overpredicted concentrations by 50 to 800%. In estimating calcium concentrations, 5 PFMs were within 10% of grab sample concentrations and 7 PFMs were within 30% of grab sample concentrations out of a total of 35 comparisons. Likewise, for sulfur concentrations, 4 PFMs were within 10% of grab sample concentrations and 7 PFMs were within 30% of grab sample concentrations out of 35 comparisons. Concentrations of aluminum were too low to be quantified above 90% confidence. PFMs calculated a lower cumulative discharge through the surface water PFMs than through the subsurface which may be explained by flow divergence around the sampler. Changes to PFM design and shorter deployment times are proposed to increase the efficacy of the PFM. / Master of Science

In manufacturing industries, sensors are often installed on industrial equipment generating high volumes of data in real-time. For shortening the machine downtime and reducing maintenance costs, it is critical to analyze efficiently this kind of streams in order to detect abnormal behavior of equipment. For validating data streams to detect anomalies, a data stream management system called SVALI is developed. Based on requirements by the application domain, different stream window semantics are explored and an extensible set of window forming functions are implemented, where dynamic registration of window aggregations allow incremental evaluation of aggregate functions over windows. To facilitate stream validation on a high level, the system provides two second order system validation functions, model-and-validate and learn-and-validate. Model-and-validate allows the user to define mathematical models based on physical properties of the monitored equipment, while learn-and-validate builds statistical models by sampling the stream in real-time as it flows. To validate geographically distributed equipment with short response time, SVALI is a distributed system where many SVALI instances can be started and run in parallel on-board the equipment. Central analyses are made at a monitoring center where streams of detected anomalies are combined and analyzed on a cluster computer. SVALI is an extensible system where functions can be implemented using external libraries written in C, Java, and Python without any modifications of the original code. The system and the developed functionality have been applied on several applications, both industrial and for sports analytics.

Thesis (doctoral)--Swedish University of Agricultural Sciences, 2004. / Thesis documentation sheet inserted. Appendix reproduces three papers and manuscripts co-authored with R.K. Johnson and two papers co-authored with R.K. Johnson and L. Sandin. Includes bibliographical references. Also issued electronically via World Wide Web in PDF format; online version lacks appendix.