Currently, our ability to predict the flux of fine sediment at the watershed scale is limited by the precision of erosion rate estimates for the many potential sources distributed throughout a landscape as well as our understanding of the connectivity of sediment pathways during transport. In absence of a robust predictive model which can be validated by measurements of sediment fluxes and use of geochemical tracers. Predicting fine sediment yield at the watershed scale requires multiple redundant lines of information. This thesis outlines the methods used, and the data sets collected in the Root River watershed in Southeastern Minnesota, all of which are multiple lines of evidence to the sediment dynamics in the Root River. The research indicates that the Root River is a very dynamic watershed. The hydrologic regime of the watershed has shifted over the last half century. Due to this shift sediment fluxes are very dependent of the magnitude and sequence of events. Geomorphic analysis of the landforms and the use of a developed tool, TerEx, indicate that many reaches of the river have easily accessible near-channel sources of sediment. Sediment fingerprinting results illustrate that source tracer concentrations are variable across the landscape, that as a whole, upland sources are still a major contributor to the suspended sediment load, and that in some sub-watersheds near-channel sources are dominate in the suspended load. Over all the channel-floodplain exchange exerts strong control on the flux of sediment through this river system.

Mud Lake is a wildlife refuge located in southeastern Idaho just north of Bear Lake that traps sediment from Bear River water flowing into Bear Lake.Very few water quality and sediment observations, if any, exist spatially in Mud Lake. Spatial patterns of sediment deposition may affect Mud Lake flows and habitat; prediction of those patterns should help refuge managers predict water quality constituents and spatial distribution of fine sediment.This will help sustain the purposes of Mud Lake as a habitat and migratory station for species. The main objective of the research is the development of Multivariate Relevant Vector Machine (MVRVM) to predict suspended fine sediment and water quality constituents, and to provide an understanding for the practical problem of determining the amount of data required for the MVRVM. MVRVM isa statistical learning algorithm that is based on Bayes theory.It has been widely used to predict patterns in hydrological systems and other fields. This research represents the first known attempt to use a MVRVM approach to predict transport of very fine sediment andwater quality constituents in a complex natural system. The results demonstrate the ability of the MVRVM to capture and predict the underlying patterns in data.Also careful construction of the experimental design for data collection can lead the Relevant Vectors (RVs is a subset of training observation which carries significant information that is used for prediction) to show locations of significant patterns. The predictions of water quality constituents will be of potential value to US Fish and Wildlife refuge managers in making decisions for operation and management in the case of Mud Lake based on their objectives, and will lead the way for scientists to expand the use of the MVRVM for modeling of suspended fine sediment and water quality in complex natural systems.

Frequently measured turbidity was examined as a surrogate for total phosphorus (TP) and total suspended solids (TSS) loads at two locations in the Little Bear River, Utah, USA. Using regression techniques, equations were developed for TP and TSS as functions of turbidity. The equations accounted for censored data, and additional explanatory variables to represent hydrological conditions were considered for inclusion in the equations. By using the resulting surrogate relationships with high frequency turbidity measurements, high frequency estimates of TP and TSS concentrations were calculated. To examine the effect of sampling frequency, reference loads were determined from the concentration records for two water years. The concentration records were artificially decimated to represent various frequencies of manual grab sampling from which annual loads were calculated and compared to the reference loads.

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The goal of this study was to demonstrate the application of aerial imagery as a tool in detecting water quality indicators in a three mile segment of Tibbee Creek in, Clay County, Mississippi. Water samples from 10 transects were collected per sampling date over two periods in 2010 and 2011. Temperature and dissolved oxygen (DO) were measured at each point, and water samples were tested for turbidity and total suspended solids (TSS). Relative reflectance was extracted from high resolution (0.5 meter) multispectral aerial images. A regression model was developed for turbidity and TSS as a function of values for specific sampling dates. The best model was used to predict turbidity and TSS using datasets outside the original model date. The development of an appropriate predictive model for water quality assessment based on the relative reflectance of aerial imagery is affected by the quality of imagery and time of sampling.

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Bioflocculation of Wastewater Treatment Pond Suspended Solids Louis Lefebvre Wastewater treatment lagoons and high rate algae ponds (HRAPs) can provide cost effective wastewater treatment, but they commonly have high effluent concentrations of total suspended solids (TSS). In this thesis algae pond effluent was treated in a beaker testing apparatus (mixed and aerated) with various mixtures of activated sludge and primary effluent simulating differing activated sludge aeration basin compositions then was allowed to settle to assess settleability. Conventionally, microalgal suspended solids are removed by chemical coagulation followed by separation methods that often have a high cost relative to the low cost lagoon or HRAP system where the solids were produced. This separation step is often cost prohibitive or operationally complex for municipalities or too energy intensive for application in algae biofuels production. This research investigates using a small amount of activated sludge material to promote bioflocculation of algae in pond effluent. It was hoped that the findings may demonstrate a path for municipalities to keep their lagoons, while increasing capacity and improving treatment without excessive cost or complexity. Experiments were conducted on microalgae samples from a pilot-scale HRAP and activated sludge and primary effluent samples from a local municipal wastewater plant. The samples were placed in a mixing apparatus and allowed to settle for a given period of time, after which TSS was analyzed for settleability. The experiments investigated the effect of various lab-scale activated sludge reactor operational schemes by varying the volumes (and masses) of activated sludge, algae-rich water, and activated sludge in the beaker. Results in the sorption test (tests with only activated sludge and algae-rich water) demonstrated algae pond effluent treated with activated sludge concentrations of 3000 mg/L or greater produced final effluent TSS concentrations near discharge requirements (40-50 mg/L) with only 30 minutes of settling and without addition of primary effluent. However, such high activated sludge concentrations are not feasible at full scale. Furthermore, beakers with activated sludge concentrations greater than 3000 mg/L reduced TSS concentrations by more than 150 mg/L with only 30 minutes of settling and without addition of primary effluent. Results in the aerobic beaker tests (tests with primary effluent, activated sludge, and algae-rich water) showed greater than 200 mg/L TSS removal and final effluent TSS concentration less than 30 mg/L was achieved using activated sludge to primary effluent volumetric ratios of 1:1 and greater which corresponded to activated sludge concentrations of 730 mg/L and greater. Activated sludge concentrations of 730 mg/L may not be feasible at full scale. This report shows that a PETRO-like process is effective in lowering wastewater pond suspended solids, however not to typical discharge standards.

Particle suspension is a phenomenon when solid particles get trapped in a liquid. This phenomenon is a common occurrence in the water treatment industry. It is typically measured continuously throughout the treatment process to ultimately ensure high water-quality. Cerlic Controls AB specializes in developing sensors for the water treatment industry and have been doing so since 1977. Cerlic Control's sensors are used within the various stages of water-purification. The type of sensor central to this project uses transmission of light to determine a concentration of suspended particles. This project describes the development-process for one of Cerlic Controls existing embedded systems. The embedded system is undergoing a modernization process where the electronics and software are updated to a more modern design. This report describes the improvements to the measurement range while maintaining the same or improved resolution. These improvements are mostly performed by modern electronics and more advanced signal processing techniques in comparison to the previous implementation. A large portion of the previous implementation's software was split over two embedded systems due to limitations in processing power. This modern version focuses on bringing these two systems into one. The sensor's microprocessor has been replaced with a more modern higher performance alternative which allows all computations to be performed in the sensor. Linearity and stability are key aspects defining system performance. Optical filters block a certain amount of light and are heavily used in verification of performance. Suspensions using activated carbon were also used to evaluate the measurement range. The results of the project were largely successful. An initial implementation was achieved with optimistic results, but further work must be done before the sensor is ready for use in industry.