The topic of this thesis is creating a design of electric snowmobile considering technical, ergonomic and aesthetic requirements of this product. Based on marketing, technical and design analysis a design of electric snowmobile of the near future (5-10 years) is created. Built on knowledge of present models, it develops further certain ergonomic, design and other features. Thesis is focused mainly on the design of snowmobile with possibility of utility use for ski resorts and similar.

Remote monitoring through the use of cameras is widely utilized for traffic operation, but has not been utilized widely for roadway maintenance operations. The Utah Department of Transportation (UDOT) has implemented a new remote monitoring system, referred to as a Cloud-enabled Remote Video Streaming (CRVS) camera system for snow removal-related maintenance operations in the winter. The purpose of this study was to evaluate the effectiveness of the use of the CRVS camera system in snow removal-related maintenance operations. This study was conducted in two parts: opinion surveys of maintenance station supervisors and an analysis on snow removal-related maintenance costs. The opinion surveys were performed in two methods: direct interviews and an online questionnaire. The responses to the opinion surveys mostly displayed positive reviews of the use of the CRVS cameras. On a scale of 1 (least effective) to 5 (most effective), the average overall effectiveness given by the station supervisors was 4.3 for both direct interviews and online questionnaire. On the online questionnaire, supervisors were asked to give an estimate of the reduction in expedition trips after having the CRVS camera installed. An expedition trip for this study was defined as a trip that was made to just check the roadways if snow-removal was necessary. The average of the responses received was calculated to be a 33 percent reduction in expedition trips. For the second part of this study, an analysis was performed on the snow removal-related maintenance cost data provided by UDOT to see if the installation of a CRVS camera had an effect in reducing expedition trips. Weather data of precipitation was also collected and analyzed; the analysis showed a close relation between precipitation patterns and patterns of snow removal-related maintenance costs of pairs of adjacent maintenance stations selected for analysis. This close relation in precipitation pattern and snow removal-related costs allowed a comparison of expedition cost of a maintenance station with a CRVS camera and a station without one. This expedition cost comparison was performed for 10 sets of maintenance stations within Utah. It was difficult to make any definitive inferences from the comparison of expedition costs over the years for which precipitation and expedition cost data were available; hence a statistical analysis was performed using the Mixed Model ANOVA. This analysis resulted in an average of 14 percent higher ratio of expedition costs at maintenance stations with a CRVS camera before the installation of the camera compared to the ratio of expedition costs after the installation of the camera. This difference was not proven to be statistically significant at the 95 percent confident level, but indicated that the installation of CRVS cameras was on the average helpful in reducing expedition costs and may be considered practically significant. It is recommended that more detailed and consistent maintenance cost records be prepared for accurate analysis of cost records for this type of study in the future.

When buying a new car today customers expect that the safety systems built in the car and its tireswill do its job in every condition. This is especially important when driving on winter roads due to thedecrease in friction between the tire and the road surface. To get further understanding how snowbehaves on winter roads, knowing how the shear strength in the hard-packed snow found on winterroads changes when doing for example multiple brake test in the same tracks can be of greatimportance when designing a new, safer product. This thesis will go through the design process of anew device designed to measure shear strength in winter test tracks. The device consists of anelectric motor powered by 12 or 24 Vdc connected to a worm gear style gearbox and can measureup to 200 Nm of torque

This Diploma Thesis deal with complex assessment of spring flood in 1909. In the theoretical part there are described types of floods. It focuses on rain-on-snow events together with melting of the snow and ice phenomena on streams. It also describe hydraulic models and especially in detail AquaLog model and its individual parts. The flood in 2006 which is compared to the event in 1909 is also described in more detail. In the historical archive there were found informations about flood in 1909 and because of them we know its area range. Next the flooding waves in Czech Republic were analized. The AquaLog model was used for basin of the river Sazava. Flooding waves were simulated for 9 stations in the whole basin using this model.

In Sweden 16 environmental objectives has been adapted to improve sustainability and assure that future generations has access to a healthy living environment without adding environmental pressure outside the Swedish borders. Snow handling occurs yearly and can be seen to affect several of these objectives and local environment. The municipalities have the responsibility to assure that clearing of snow is carried out and that the snow is deposited according to Swedish laws. This calls for choosing locations for snow deposits in a suitable manner. This study therefore aims to build a generic model in geographic information systems to find suitable places to deposit snow that can increase sustainability by using a simple multi criteria analysis and easy accessible data. The model uses constraints, as only using open land and excludes cultural heritage sites and nature reserves, and factors as visibility, availability, salt contamination and infiltration, for indicating suitable areas for snow depositing. The model was tried on Lidingö municipality to evaluate the result and the resulting suitability map shows good results by indicating areas that can be used for snow deposits but also some areas that aren’t possible to deposit snow on. The model works well with generic data for planners in the early stages of planning and can with some modifications to local properties and general factors be even more specific to point out suitable areas for snow deposits.

The simplest form of a snow particle is a hexagonal prism which can grow into a stellar crystal by growing branches from the six corners of the prism. The snow particle is affected by the temperature and supersaturation in the air, giving its unique form. Manual classification of snow particles based on shape is tedious work. Convolutional Neural Network (CNN) can therefor be of great assistance and are common in automatic image processing. From a data set consisting of 3165 images sorted into 15 shape classes, a sub set of 2193 images and 7 classes was used. The selected classes had the highest number of snow particle images and were used to train, validate and test on. Four data sets were constructed and eight models were used to classify the snow particles into seven classes. To reduce the amount of training data needed pretrained versions of neural networks AlexNet and ResNet50 were used with a technique called transfer learning. The 2193 images make up the first data set, Data set 1. To handle unbalanced classes in the first data set Synthetic Minority Oversampling Technique (SMOTE) was used to increase the number of snow particles in classes with few examples, creating Data set 2. A third data set was constructed to mimic a real world application. The data for training and validation was increased with SMOTE, while the test data only consisted of real snow particles. The performance of both ResNet50 and AlexNet on the data met the requirements for a practical application. However, ResNet50 had a higher overall accuracy, 72%, compared to AlexNet 69% on the evaluated data set. A t-test was conducted with a significance of p < 1·10−8. To enhance the shape of the snow particles a Euclidean Distance Transform (EDT) was used, creating Data set 4. However, this did not increase the accuracy of the trained model. To increase the accuracy of the models more training data of snow particles is needed, especially for classes with few examples. A larger data set would also allow more classes to be included in the classification.

Flame retardants are substances, which addition in various materials (furniture, plastics, electronics equipment, textiles, etc) could save a lot of lives and injuries caused by fires. On the other side, the migration of flame retardants from products during their whole life cycle results in their ubiquitous presence in the environment and reflects negative effects on ecosystems and human health. Global consumption of organophosphate flame retardants (OFR) as alternative substitutes of polybrominated diphenyl ethers has increased sharply in recent years. Studies on the presence and sources of OFR in surface water, ground water, sediments, snow, rainwater, indoor and outdoor air and analyses of OFR in these compartments have also increased in the last decade. In this doctoral thesis an analytical method was developed to determine six OFR (tris(2-chloroethyl) phosphate (TCEP), tris(2-chlorisopropyl) phosphate (TCPP), tris(1,3-dichloro-2-propyl) phosphate (TDCP), tris(2-butoxyethyl) phosphate (TBEP), tri(n-butyl) phosphate (TnBP) and triphenyl phosphate (TPP)) in soil. The method consists of a combination of Twisselmann extraction and solid-phase microextraction (SPME), followed by gas chromatography-mass spectrometry (GC-MS). To develop the method, spiked soils were extracted using a Twisselmann extractor after freeze-drying. The extracts were evaporated to dryness, redissolved, and filtered. A volume of 7 mL was then analysed by SPME, followed by GC-MS. The effects of different parameters on analyte recoveries during sample preparation e.g. solvent for Twisselmann extraction, solvent for redissolving the extract, addition of copper, and filtration of the extract were systematically investigated. Under optimum conditions, 10 g of soil were extracted using toluene, and the extract was redissolved in methanol/water (1:14) and filtered. It was not necessary to add copper. For TnBP, TBEP, TCPP, and TCEP, recoveries ranged from 77.0 % to 89.6 %. Those for TPP and TDCP were much lower, at 31.5 % and 42.0 %, respectively (addition level 22.9-45.8 ng/g). The variability of recoveries under these conditions was between 0.3 and 16.2 % (n = 3). Limits of detection (LOD) were 0.002-3 ng/g. When ultrasonication was used instead of Twisselmann extraction in the developed method, recoveries were three to four times lower (27.4 % to 30.6 %), but the variability of recoveries was below 3 % (n = 3). The method was applied to quantify OFR in soils collected from different sampling locations (urban, semi-urban and rural) in Germany. The results indicated for the first time that atmospheric deposition leads to soil contamination by OFR. Since it has been shown in animal experiments (F344/N rats and B6C3F1 mice) that chlorinated OFR were carcinogen and also have negative effects on human health (Matthews et al., 1991, 1993, Johnson, 1999), the further studies were focused on sources of chlorinated OFR. Therefore, the influence of dry and wet deposition processes as a source of chlorinated OFR in soils was systematically investigated. Soil samples were collected in 2010/11 during a period of snow falling to snow melting, a period of rainfall and a dry period. Snow and rainwater samples were also collected from the soil sampling site. Concentrations of TCEP were between 236 and 353 ng/L in snow and 78 and 234 ng/L in rain. TCPP concentrations were between 226 and 284 ng/L in snow and 371 and 385 ng/L in rain. In soil samples, concentrations ranged from 5.07 to 23.48 ng/g dry weight (dwt) for TCEP and 5.66 to 19.82 ng/g dwt for TCPP. Concentrations of TDCP in rainwater and snow samples were rather low (46 and 100 ng/L, respectively); concentrations of TDCP were below the limit of detection in soil samples. Snow melting caused enhanced soil concentrations of TCEP and TCPP. However a greater effect of snow melting was observed for TCEP than for TCPP. No significant correlation between precipitation amounts and soil concentrations was observed for both compounds. The influence of wet deposition to the soil contents of TCEP and TCPP may be covered by volatilisation or by the migration of both compounds to deeper soil zones with seepage water, based on their volatility and high water solubility, respectively. Snow was found to be even a more efficient source of chlorinated OFR in soil than rainwater. During dry weather, the soil concentrations of both compounds seemed to be driven mainly by concentrations in air, which are driven by source emission strengths and photochemical degradation in the atmosphere. Rainwater concentrations of OFR were used to assess air concentrations from the scavenging ratios at equilibrium conditions and the potential for the accumulation of OFR in soil based on the air-soil exchange was estimated. Calculated values of median air concentrations were 0.0034 ng/m3 for TCEP and 0.99 ng/m3 for TCPP. Total OFR specific loads were 3756 ng m-2 day-1 within the first 24 hours and 3028 ng m-2 day-1 within the next 24 h. Fugacity calculations (0.011 to 0.103 for TCPP and 0.005 to 0.073 for TCEP) indicated net deposition from air to soil for both compounds.

Dam building activity by North American Beaver (Castor canadensis) alters the timing and delivery of stream water and facilitates groundwater infiltration, overall increasing natural water storage behind and adjacent to dams. At the stream reach scale, increased water storage often alters hydrologic regimes by attenuating annual, and storm-event hydrographs, and increasing base flows. In the montane west, the most important water storage reservoirs are not human-made dams, but mountain snowpack, which slowly releases water through a mix of runoff and infiltration. Given estimates of decreasing snowpack with warming temperatures, beaver dams could provide a conceptually similar function to snowpack by delaying the delivery of precipitation by increasing surface and groundwater storage, thus lengthening residence time as water travels downstream. However, lack of predictive methods for modeling storage increases associated with relatively small magnitude beaver ponds at large spatial scales has precluded further investigation of this hypothesis. I address this knowledge gap by supplementing existing empirical data regarding the height of beaver dams and implement these empirical height distributions to develop the Beaver Dam Surface Water Estimation Algorithm (Chapter 2), a predictive model estimating beaver pond water storage that can be applied spatially at large scales. I then apply this model to estimate potential surface water storage and parameterize a groundwater model to estimate resulting groundwater storage increases for the entire Bear River basin under four different beaver dam capacity scenarios (Chapter 3). Estimated water storage changes from beaver dams are presented in the context of expected reductions in average annual maximum snow water equivalent, and existing and proposed reservoir storage within the basin. While the water storage provided by beaver dams is only a small fraction of expected snow water equivalent loss, it is not insubstantial and may prove beneficial for ecosystems where human-made reservoirs are not available to regulate hydrologic regimes. These results also stress the importance of further research examining how the cumulative effects of dams may affect the timing of runoff under changing precipitation regimes.

Studies were conducted in a mountain habitat to determine the effects of altered light and temperature upon the natural growth and/or carbohydrate cycles of Claytonia lanceolata during the period of winter snow cover. Treatments included natural control, light exclusion, and temperature alteration by insulation and by heating for a brief period. Monthly measurements were made of soil temperature (upper 12 cm), shoot development, soluble sugar, and soluble starch. The quantity and quality of light penetrating the snow cover was also determined. About 0.0052% of the available visible light (400-750 nm) penetrated 70 cm of snow and 0.02% penetrated 50 cm of snow. The under snow spectral curve remained constant with a peak at 575 nm, while absolute energy increased 35 times from January to April. Soil temperatures were unchanged by treatments averaging 0.0 to 0.3 C at the surface and slightly warmer at each successive depth. Shoot development and carbohydrate cycles were the same for all treatments. Carbohydrate depletion was generally correlated with increased shoot development. The cycles are traced and discussed. The starch/sugar ratio remained almost constant at one.

This thesis is a combination of two separate studies which examine hydrologic data assimilation techniques: 1) to determine the applicability of assimilation of remotely sensed data in operational models and 2) to compare the effectiveness of assimilation and other calibration techniques. The first study examines the ability of Data Assimilation of remotely sensed microwave radiance data to improve snow water equivalent prediction, and ultimately operational streamflow forecasts. Operational streamflow forecasts in the National Weather Service River Forecast Center are produced with a coupled SNOW17 (snow model) and SACramento Soil Moisture Accounting (SAC-SMA) model. A comparison of two assimilation techniques, the Ensemble Kalman Filter (EnKF) and the Particle Filter (PF), is made using a coupled SNOW17 and the Microwave Emission Model for Layered Snowpack model to assimilate microwave radiance data. Microwave radiance data, in the form of brightness temperature (TB), is gathered from the Advanced Microwave Scanning Radiometer-Earth Observing System at the 36.5GHz channel. SWE prediction is validated in a synthetic experiment. The distribution of snowmelt from an experiment with real data is then used to run the SAC-SMA model. Several scenarios on state or joint state-parameter updating with TB data assimilation to SNOW-17 and SAC-SMA models were analyzed, and the results show potential benefit for operational streamflow forecasting. The second study compares the effectiveness of different calibration techniques in hydrologic modeling. Currently, the most commonly used methods for hydrologic model calibration are global optimization techniques. While these techniques have become very efficient and effective in optimizing the complicated parameter space of hydrologic models, the uncertainty with respect to parameters is ignored. This has led to recent research looking into Bayesian Inference through Monte Carlo methods to analyze the ability to calibrate models and represent the uncertainty in relation to the parameters. Research has recently been performed in filtering and Markov Chain Monte Carlo (MCMC) techniques for optimization of hydrologic models. At this point, a comparison of the effectiveness of global optimization, filtering and MCMC techniques has yet to be reported in the hydrologic modeling community. This study compares global optimization, MCMC, the PF, the Particle Smoother, the EnKF and the Ensemble Kalman Smoother for the purpose of parameter estimation in both the HyMod and SAC-SMA hydrologic models.