Measuring the concentration of particles in water is important in many areas. Industries might measure it to run more efficiently while scientists might measure it to study the pollution of a body of water. Regardless of the area, the standard for taking a measurement is done by filtering out the particles by hand. This is a very slow and expensive method, so other alternative methods have been developed. However, all the alternative methods can only estimate the concentration. Therefore, Deepoid AB aims to investigate if ultrasound can be used to measure the concentration of particles in water.\parThis thesis shows that a direct ultrasound signal can be used to measure changes in the concentration of particles in water. It also shows how this method is much faster than measuring the concentration of particles in water by hand.

An autonomous underwater cable suspended dredging system is proposed with the application of combating the excess of nutrients in the Baltic Sea. The focus of the thesis is on modelling and designing of the control system used to guide an end-effector supplied with a pump along a predetermined path. The end-effector is guided with the help of four cables that are each controlled by a servomotor. The buoyancy of the end-effector in combination with the cables keeps the end-effector a few meter above the seafloor. The sediment is collected with tubes hanging down from the end-effector. Due to the large dimensions of the system a combination of force control and position control passed through a force distribution algorithm is suggested. A simulation of the system shows promising results with ability to trace the predetermined path closely. / Ett förslag till ett autonomt vajerstyrt muddringssytem för undervattensbruk har tagits fram som ska används för att motverka övergödningen i östersjön. Uppsatsen fokuserar på modelleringen och designen av reglersystemet för att styra en plattform utrustad med en pump längs en förutbestämd sträcka. Plattformen styrs med hjälp av fyra vajrar som i sin tur styrs av varsin servomotor. Flytkraften hos plattformen i kombination med vajrarna håller plattformen några meter från havsbotten. Bottensediment pumpas upp genom slangar som hänger ner från plattformen. På grund av systemet storlek regleras styrningen av plattformen genom båda kraft och position samt använder en algoritm för att distribuera krafterna mellan vajrarna. En simulering av systemet har utförts och visar på god förmåga att reglera positionen av plattformen i relation till den förutbestämda sträckan.

We suggest a computational approach for estimating the ring-like deposition of nanoparticles contained in a drying liquid droplet. The proposed method involves a Monte Carlo scheme, based on three independent probabilistic processes: (a) evaporation at the liquid surface, (b) convective motion of nanoparticles to the contact line, and (c) treatment of the nanoparticles floating in the air. According to the computational results, while the liquid is evaporating in nanoparticle-suspended liquid droplet (NSLD), the nanoparticles are moved to the contact line as the mass of droplet decreases linearly with time. Since the resulting ring-like deposition can be accounted for in terms of nanoparticle mobility and liquid evaporation from the droplet, our computational approach achieves a morphological and kinematical description of NSLD drying. Some other important features, such as self-pinning of the contact line, reduction of the droplet radius, and pattern formation, are also obtained from this simulation.

The discharge of sediment-laden rivers into the Mississippi Sound increases the turbidity of coastal waters. The concentration of suspended particulates is an important parameter in the analysis of coastal water quality factors. The spatiotemporal resolution associated with satellite sensors makes remote sensing an ideal tool to monitor suspended particulate concentrations. Accordingly, the presented research evaluated the validity of published algorithms that relate remote sensing reflectance (Rrs) with suspended particulate matter for the Mississippi Sound. Additionally, regression analysis was used to correlate in situ SPM concentrations with coincident observations of visible and near-infrared band reflectance collected by the MODIS Aqua sensor in order to develop a predictive model for SPM. The most robust algorithm yielded an RMSE of 15.53% (n = 86) in the determination of SPM concentrations. The application of this algorithm allows for the rapid assessment of water quality issues related to elevated SPM concentrations in the Mississippi Sound.

The overall goal of this thesis is to present a comprehensive understanding of the Nottawasaga River system. In the first chapter, we will examine how landscape features (geomorphology and land cover) drive spatial variation in nutrient and sediment loading from 11 sub-watersheds to the Nottawasaga River. The second chapter will relate how tributary loading and other in-stream processes (riffles, substrate, dissolved oxygen) contribute to the longitudinal variation in water quality along with middle and lower reaches of the Nottawasaga River. Finally, in the last chapter we use 13 water quality variables to develop a Stream Water Quality Index (SWQI) to identify critical areas in the NRW that are most at risk. This thesis will provide environmental agencies with useful information to help implement management strategies to improve the health of riverine systems at a watershed scale. / Eutrophication from agricultural runoff is a global problem, often resulting in formation of anoxic zones in receiving water bodies. The Nottawasaga River Watershed (2,900 km2) is dominated by agricultural land-use, and is a major source of nutrients and sediment to Nottawasaga Bay, Georgian Bay (Lake Huron). The primary objective of our study was to develop a holistic understanding of the different sources and processes that influence spatial variation of water quality across the Nottawasaga River (121 km). In our first chapter, we use landscape features to develop 6 models that predict daily base flow loading rates of total phosphorus (TP) and total suspended solids (TSS) from 11 sub-watersheds. We found that drainage area and % pasture land were the most significant predictive variables driving spatial variability in TP and TSS loading. We also found a significant positive relationship between TP and % wetland, suggesting that the Minesing Wetlands (largest inland wetland in southern Ontario) are a source of nutrients to the river. In our second chapter, we evaluate how tributary inputs and in-stream processes contribute to the longitudinal variation in water quality along the Nottawasaga River. We found that tributary concentration and discharge significantly predict downstream turbidity (TURB), but do not predict downstream TP. We also found that riffles improve water clarity, and that silt and clay substrate is significantly associated with high TURB. In our third chapter, we develop a Stream Water Quality Index (SWQI) using 13 variables collected at 15 stations along the Nottawasaga River. To predict SWQI scores for any site, we have provided 9 equations that use various combinations of available variables. Understanding landscape variables, as well as tributary and in-stream processes that influence water quality will enhance the development of restoration initiatives to improve ecosystem health in lotic systems at a watershed scale. / Thesis / Master of Science (MSc) / Eutrophication from agricultural runoff is a global problem, often resulting in formation of anoxic zones. The Nottawasaga River Watershed is dominated by agricultural land-use, and is a major source of nutrients and sediment to Georgian Bay, Lake Huron. The objective of our study was to develop a holistic understanding of sources and processes that influence spatial variation of water quality across the Nottawasaga River. We found that landscape features (drainage area, pasture, wetland), tributary inputs, and in-stream processes (riffles, substrate) significantly influence water quality. Our results will enhance restoration initiatives to improve health of riverine systems at a watershed scale.

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According to the US Environmental Protection Agency (USEPA) sediment is a leading cause of water quality impairment (US EPA, 2002). The annual costs of sediment pollution in North America alone are estimated to range between $20 and $50 billion (Pimentel et al., 1995; Osterkamp et al, 1998, 2004). Due to the large spatial and temporal variations inherent in sediment transport, suspended sediment measurement is challenging. The overall goal of this research was to develop and test an inexpensive sensor for continuous suspended sediment monitoring in streams. This study was designed to determine if the gain and phase components of permittivity could be used to predict suspended sediment concentrations (SSC). A bench-scale suspension system was designed and tested to guarantee that there were no significant differences in the sediment suspension vertically or horizontally within the system. This study developed prediction models for SSC with input variables of temperature, specific conductivity, and gain and/or phase at multiple frequencies. The permittivity sensor is comprised of an electrode, power source, and a control box or frequency generator. Fixed and mixed effect, multiple, linear regression models were created and compared for target frequencies. However, it was not possible to meet the normality requirements for prediction accuracy. Partial Least Squares (PLS) regression techniques were also applied to gain and phase data for 127 of the 635 frequencies. The three models with the lowest error between predicted and actual values of SSC for validation were further tested with nine levels of independent validation data. The largest model error (error>50%) occurred for the top three models at 0 and 500 mg/L. At the higher concentrations error varied from 1-40%. Once the treatment levels, of the independent validation data set, were near 1000 mg/L the prediction accuracy increased for the top three models. Model 3A, a phase based model, preformed the best. Model 3A was able to predict six of the nine independent validation treatment levels within 300 mg/L. Future research will provide additional laboratory and field testing of the prototype sensor. / Ph. D.

This research incorporates streambank erosion and failure processes into a distributed watershed model and evaluates the impacts of climate change on the processes driving streambank sediment mobilization at a watershed scale. Excess sediment and nutrient loading are major water quality concerns for streams and receiving waters. Previous work has established that in addition to surface and road erosion, streambank erosion and failure are primary mechanisms that mobilize sediment and nutrients from the landscape. This mechanism and other hydrological processes driving sediment and nutrient transport are likely to be highly influenced by anticipated changes in climate, particularly extreme precipitation and flow events. This research has two primary goals: to develop a physics-based watershed model with more inclusive representation of sediment by including simulation of streambank erosion and geotechnical failure; and to investigate the impacts of climate change on unstable streams and suspended sediment mobilization by overland erosion, erosion of roads, and the erosion as well as failure of streambanks. This advances mechanistic simulation of suspended sediment mobilization and transport from watersheds, which is particularly valuable for investigating the impacts of climate and land use changes, as well as extreme events. Model development involved coupling two existing physics-based models: the Bank Stability and Toe Erosion Model (BSTEM) and the Distributed Hydrology Soil Vegetation Model (DHSVM). This approach simulates streambank erosion and failure in a spatially explicit environment. The coupled model is applied to the Mad River watershed in central Vermont as a test case. I then use the calibrated Mad River model to predict the response in watershed sediment loading to future climate scenarios that specifically represent local temperature and precipitation trends for the northeastern US, particularly changing trends in the frequency and magnitude of extreme precipitation. Overall the streambank erosion and failure processes are captured in the coupled model approach. Although the presented calibration of the model underestimates suspended sediment concentrations resulting from relatively small storm/flow events, it still improves prediction of cumulative loads and in some cases suspended sediment concentrations during elevated flow events in comparison to model results without including BSTEM. Increases in temperature affect the timing and magnitude of snow melt and spring flows, as well as associated sediment mobilization, in the watershed. Increases in annual precipitation and in extreme precipitation events produce increases in annual as well as peak discharge and sediment loads in the watershed. This research adds to the body of evidence indicating that streambank erosion and failure can be a major source of suspended sediment, and thereby a major source of phosphorus as well. It also shows that local climate trends in the Northeast are likely to result in higher peak discharges and sediment yields from meso-scale, high-gradient watersheds that encompass headwater forested streams and agricultural floodplains. One limitation was that we could not drive the model with meteorological data that represented changes in both temperature and precipitation, highlighting the need for improved climate predictions. This coupled model approach could be parameterized for alternative watersheds and be re-applied to answer various questions related to erosion processes and sediment transport in a watershed. These findings have important implications for resource allocation and targeted watershed management strategies.