In agriculture-dominated areas, water pollution resulting from nutrients migrating from farms to water bodies is a major concern. The migration is further exacerbated by traditional tile drain known as Uncontrolled Tile Drainage (UCTD), which removes excess water from areas to keep the water table low enough for crops to grow. UCTD, commonly used in Ontario, Canada, is believed to contribute to water quality issues, whereas Controlled Tile Drainage (CTD) is an alternative technique in which a structure controls the outlets of the drains so that water only leaves a field when the water table level exceeds a desired threshold. Considered as a Best Management Practice (BMP), CTD has been documented as an efficient practice preventing nutrients from migrating out of agricultural fields. This thesis aims to improve our understanding of the environmental benefits of replacing UCTD with CTD. Three significant contributions were achieved. The first contribution of the thesis is the improvements of the algorithm for calculating nitrates in tile flows in the Soil and Water Assessment Tool (SWAT) model. Researchers have simulated CTD by dynamically changing tile depth to mimic the operation of outlet structure gates, but it has been demonstrated that doing so results in inaccuracies, and so the algorithm in the model has been improved subsequently. The current author proposed and tested a new algorithm for calculating nitrates in tile flows that better represents the dynamics of water and nutrients in soil layers for the SWAT model. A model for the South Nation watershed, located in Ontario, Canada, was then developed and successfully calibrated using the improved SWAT model. The second contribution was the extension of the SWAT model to simulate riverine hydraulic and water quality processes by coupling it with the QUAL2Kw model. In this thesis, a procedure is developed to couple the SWAT model and the QUAL2Kw model to enable continuous simulations of 13 water quality parameters in the South Nation River system. The coupled model was calibrated and verified at various observed locations along the river during the five seasons of growth from 2006 to 2010. The simulation results suggested that CTD also improved the water quality of the river by lowering biologically available N levels of NO2--N, and NO3--N, thereby impeding phytoplankton growth in the river. The third contribution is the verification of the benefits of replacing UCTD with CTD in the future climates. The confirmation was done using the SWAT model alone, and then the coupled SWAT/QUAL2K models, using a matrix of climate change experiments performed with several Global Climate Models and Regional Climate Models. The results suggest that nutrient loading from the watershed will increase in the 2021–2050 period compared to the 1985–2006 period. Thus, pollution from agricultural fields will worsen with the current UCTD approach, while the results also show that CTD would perform effectively and stably in future climate scenarios and could counterbalance the effects of climate change on water quality. To the author’s knowledge, this study is the first attempt to date to assess the environmental effects of CTD on a watershed and river by coupling the SWAT and QUAL2Kw models. The findings expand the current scope of knowledge on the environmental effects of CTD on watersheds and rivers under current and future climate change regimes. Long periods of continuous simulation and a matrix of climate change scenarios also make this study stand out from other studies. It laid a foundation for future investigations.

Pollution of surface and groundwater, due to improper land management, has become a major problem worldwide. Integrated watershed modelling provides a tool for the understanding of the processes governing water and matter transport at different scales within the watershed. The Soil Water Assessment Tool (SWAT) has been successfully utilized for the combined modelling of water fluxes and quality within a large range of scales and environmental conditions across the world. For suitable assessments integrated watershed models require large data sets of measured information for both model parameterization as for model calibration and validation. Data scarcity represents a serious limitation to the use of hydrologic models for supporting decision making processes, and may lead unsupported statements, poor statistics, misrepresentations, and, ultimately, to inappropriate measures for integrated water resources management efforts. In particular, the importance of spatially distributed soil information is often overlooked. In this thesis the eco-hydrological SWAT model was been applied to assess the water balance and diffuse pollution loadings of two rivers within a rural context at the mesoscale watershed level: 1) the Western Bug River, Ukraine, 2) the Águeda River, Portugal. Both watersheds in focus serve as examples for areas where the amount and quality of the measured data hinders a strait forward hydrologic modelling assessment. The Dobrotvir watershed (Western Bug River, Ukriane) is an example of such a region. In the former Soviet Union, soil classification primarily focused on soils of agricultural importance, whereas, forested, urban, industrial, and shallow soil territories were left underrepresented in the classification systems and resulting soil maps. Similarly the forest-dominated Águeda watershed in North-Central Portugal is a second example of a region with serious soil data availability limitations. Through the use of pedotransfer functions (PTFs) and the construction of soil-landscape models the data gaps could be successfully diminished, allowing a subsequent integrated watershed modelling approach. A valuable tool for the data gap closure was the fuzzy logic Soil Land Inference Model (SoLIM) which, combined with information from several soil surveys, was used to create improved maps. In the Dobrotvir watershed the fuzzy approach was used to close the gaps of the existing soil map, while in the Águeda watershed a new soil properties map, based upon the effective soil depths of the landscape, was constructed. While the water balance simulation in both study areas was successful, a calibration parameter ensemble approach was tested for the Águeda watershed. In the common modelling practice the individual best simulation and best parameter set is considered, the tested approach involved merging individual model outputs from numerous acceptable parameter sets, tackling the problematic of parameter equifinality. This procedure was tested for both original soil map and the newly derived soil map with differentiation of soil properties. It was noticeable that a better model set-up, with a better representation of the soil spatial distribution, was reflected in tighter model output spreads and narrower parameter distances. A further challenge was the calibration of water quality parameters, namely nitrate-N in the Dobrotvir watershed and sediment loads in the Águeda watershed. The limited amount of water quality observations were handled by assessing and by process verification at the smallest modelling unit, the hydrological response unit (HRU). The ruling hydrological processes could be depicted by combining own measured data and modelling outputs. The management scenario simulations showed the anticipated response to changes in management and reflected the rational spatial variation within the watershed reasonably well. The impacts of the different intervention options were evaluated on water balance, nitrate-N export and sediment yield at the watershed, sub-watershed and, when feasible, HRU level. This thesis covers two regional case studies with particular data limitations and specific processes of water and matter fluxes. Still, data reliability is a problem across the globe. This thesis demonstrates how relevant it is to tackle shortages of spatially differentiated soil information. The considered approaches contribute toward more reliable model predictions. Furthermore, the tested methods are transferable to other regions with differing landscape and climate conditions with similar problems of data scarcity, particularly soil spatially differentiated information.

Considering the potential for natural wetlands to store and retain water in the landscape,restored and constructed wetlands are increasingly implemented as Nature‐BasedSolutions (NBS) to mitigate downstream flooding. However, there is a frequent lack ofknowledge of the performance of NBS, and particularly wetlands, and how to best selectperformance indicators to measure their effectiveness. The aim of this study was to assessthe flood regulation services of multiple constructed wetlands at catchment scale. TheSWAT+ model was used to assess the impacts of 35 constructed wetlands in the 193 km2Råån catchment in southwest Sweden. The assessment was based on a paired simulationscenario, with and without wetlands, and performance was evaluated based on impacts onthe downstream river hydrograph (peak flow rate, time-to-peak, recession curve shape,daily streamflow average) as well as event-based (daily average streamflow for differentprecipitation ranges), descriptive (average wetland storage capacity), consequential(overbank flooding) and social (social acceptance) indicators. The results implied that theflow regulating capability of the modeled wetlands was directly related to their outflowmechanisms. The wetlands had an average storage capacity of 0.38 m3 per m2 area butbecause the wetlands seemed to frequently exceed their maximum storage capacity duringhigh flow events, and the excess water was immediately spilled downstream, the wetlandsprovided limited flood regulation services. There were no visible impacts on thehydrograph-related indicators and the daily streamflow average was reduced by anegligible 0.02%. Furthermore, there were no significant differences in wetlandperformance between small and heavy rainfall events and the model output showed nosigns of overbank flooding for either wetland scenario. In terms of social acceptance, recentwetland projects in Råån catchment seem to have been well-received by farmers andlandowners in the area. However, lack of wetland-specific data, such as volume and dailyinflow and outflow data, as well as other model uncertainties, motivated a low confidencegrade for the indicators. In fact, if indicator values are to be useful tools in the futureintegration of wetlands as nature-based solutions, in-situ monitoring data of wetland waterbalance components are required. To support future policies and decision-making, adaptedtools and further research are needed to assess the impact of NBS on upstream-downstream processes. / Naturliga våtmarkers förmåga att hålla kvar och lagra vatten i landskapet gör attrestaurerade och anlagda våtmarker alltmer implementeras som naturbaserade lösningarför att mildra översvämningar i nedströms belägna områden. Det råder dock brist påkunskap om hur effektiva naturbaserade lösningar är och hur nyckelindikatorer bäst kanväljas för att mäta hur väl dessa system fungerar. Syftet med denna studie var att utvärderaanlagda våtmarkers förmåga att mildra översvämningar i ett avrinningsområde. SWAT+modellen användes för att bedöma påverkan av 35 anlagda våtmarker i Råånsavrinningsområde (193 km2) utanför Helsingborg. Bedömningen baserades på ettsimuleringspar, med och utan våtmarker, och effektiviteten utvärderades baserat påhydrografens egenskaper (flödestopp, stegringsfasen, recessionsfasen, daglig medel-vattenföring) samt med en nederbördsbaserad (daglig medelvattenföring för olikanederbördsintervall), beskrivande (genomsnittlig lagringskapacitet), konsekvensbaserad(översvämmad mark) och social (social acceptans) indikator. Resultatet antydde att denflödesreglerande förmågan hos de modellerade våtmarkerna var direkt kopplad till derasutflödesmekanismer. Våtmarkerna hade en genomsnittlig lagringskapacitet på 0.38 m3 perm2 yta men eftersom de ofta verkade överskrida sina maximala lagringskapaciteter underhögflöden, och överskottsvattnet omedelbart släpptes igenom nedströms, tillhandahöllvåtmarkerna en mycket begränsad flödesdämpande funktion. Det fanns inga synligaeffekter på de hydrografrelaterade indikatorerna och den dagliga medelvattenföringenminskade med försumbara 0.02%. Dessutom sågs inga signifikanta skillnader mellan småoch kraftiga nederbördshändelser och modellen visade inga tecken på översvämmad markför något av våtmarksscenarierna. Vad gäller social acceptans tycks de senastevåtmarksprojekten i Rååns avrinningsområde ha tagits emot väl av lantbrukare ochmarkägare i området. Bristen på våtmarksspecifika data, såsom volym och dagliga in- ochutflödesdata, samt andra modellosäkerheter medförde dock ett lågt förtroende förindikatorerna. Om indikatorvärden ska vara användbara verktyg i den framtida integ-reringen av våtmarker krävs uppmätta data över våtmarkernas vattenbalanskomponenter.För att stödja framtida beslutsfattande behövs även anpassade verktyg och ytterligareforskning för att bedöma påverkan av naturbaserade lösningar på uppströms-nedströmsprocesser.

La prévision hydrologique nécessite une connaissance adéquate des quantités de neige présentes sur ses bassins versants, particulièrement pour des bassins versants montagneux. Pour beaucoup de bassins, la densité du réseau de stations nivométriques est faible ou parfois même inexistante. De leur côté, les données satellitaires MODIS permettent de suivre l’évolution du couvert de neige sur de grandes superficies de façon journalière et à une résolution spatiale de 500 m. Dans ce contexte, un projet de recherche a été proposé en partenariat entre Rio Tinto Alcan (RTA) et l’Université de Sherbrooke afin d’évaluer l’apport de la télédétection du couvert de neige (MODIS) pour améliorer la prévision hydrologique en période de crue. Le bassin versant à l’étude est celui de la rivière Nechako, situé en Colombie-Britannique (Canada) et caractérisé par sa topographie montagneuse et les grandes quantités de neige s’accumulant sur son territoire. D’abord, une analyse statistique a été réalisée permettant d’obtenir une relation empirique entre l’évolution du volume de crue et la variation de la superficie du couvert de neige (SCN) tirée des images MODIS. Ensuite, les SCN MODIS ont été utilisées pour le calage du modèle hydrologique SWAT selon 9 différentes techniques de calage. Finalement, avec l’aide d’un système de prévision, assimilant d’abord les SCN MODIS pour mettre à jour les conditions initiales, la performance de 5 des 9 calages effectués a été analysée en prévision hydrologique court terme (déterministe) et moyen terme (probabiliste). À partir des résultats, il a été possible d’observer que l’assimilation des SCN MODIS permet d’améliorer les prévisions à plus long terme, particulièrement des volumes de crue. À court terme, la qualité des prévisions d’apports est sensiblement identique avec ou sans assimilation MODIS bien qu’une meilleure simulation des conditions initiales de neige soit observée avec assimilation MODIS. Finalement, la comparaison des calages en prévision hydrologique démontre qu’une légère amélioration des prévisions d’apports moyen terme (3 à 5 mois) est possible lorsque les données MODIS sont utilisées dans la procédure de calage. Cependant, les résultats sont variables dépendamment de la technique de calage utilisée.

Context. In recent years, Software Quality Assurance (SQA) has become a crucial part of software development processes. Therefore, modern software development processes led to an increase in demand for manual and automated code quality assurance. Manual code quality reviews can be a time-consuming and expensive process with varying results. Thus, automated code reviews turn out to be a preferred alternative for mitigating this process. However, commercial and open-source static code analyzer tools often offer deep analysis with long lead time. Objectives. In this thesis work, the main aim is to introduce an early code quality assurance tool, which features a combination of software metrics. The tool should be able to examine code quality and complexity of a telecommunication grade software product such as source code of specific Ericsson product by Ericsson. This tool should encapsulate complexity and quality of a software product with regards to its efficiency, scope, flexibility, and execution time. Methods. For this purpose, the background section of the thesis is dedicated to in-depth research on software metrics included in well-known static code analyzers. Then, development environment, under investigation source code of Ericsson product, and collected software metric for evaluation were presented. Next, according to each software metric’s characteristics, point of interest, and requirement, a set of steps based on a Susman’s action research cycle were defined. Moreover, SWAT, a suitable software analytics toolkit, employed to extract conducted experiment data of each software metric from a static analyzer code named Lizard in order to detect most efficient software metrics. Outcome of conducted experiment demonstrates relationship of selected software metrics with one another. Results. The chosen software metrics were evaluated based on a variety of vital factors especially actual data from number of defects of specific Ericsson product. Highly effective software metrics from investigations in this thesis work were implemented as a new model named hybrid model to be utilized as an early quality assurance. Conclusions. The proposed model, which consist of well-performing software metrics, demonstrate an impressive performance as an early code quality indicator. Consequently, the utilized model in this master thesis could be studied in a future research to further investigate the effectiveness and robustness of this tool an early quality assurance.

A Soil and Water Assessment Tool (SWAT) model was developed for the Iowa-Cedar River Basin (ICRB), a 32,660 km2 watershed dominated by agricultural land cover (∼70%) to simulate hydrology and water quality for the prediction of stream discharge, nitrate loads, and nitrate concentration under climate and land use change scenarios. Iowa exports as much as 20% of the nitrogen entering the Gulf of Mexico at the mouth of the Mississippi, contributing to Gulf hypoxia as well as local threats to water quality in the ICRB. The model utilized a combined autocalibration and sensitivity procedure incorporating Sequential Uncertainty Fitting (SUFI) and generalized additive models. This procedure resulted in Nash-Sutcliffe Efficiency (NSE) goodness-of-fit statistics that met literature guidelines for monthly mean stream discharge (NSE≥0.60) and daily nitrate load (NSE≥0.50). Artificial neural networks coupled with SWAT stream discharges aided in the simulation of daily mean nitrate concentrations that met the literature guideline (NSE≥0.50). The North American Regional Climate Change Assessment Program (NARCCAP) provided an ensemble of 11 climate change scenarios. NARCCAP is a multi-institutional effort to simulate climate change at the mesoscale by downscaling global circulation models (GCM) with regional climate models (RCM). The resulting GCM-RCM produced synthetic precipitation and temperature time-series that drove the SWAT simulations and scenarios. The land use scenarios were a collaboration with the U.S. Army Corps of Engineers, using a rule-based GIS method to generate scenarios that (1) maximized agricultural productivity, (2) improved water quality and reduced flooding, and (3) enhanced local biodiversity. The SWAT simulations and ensemble climate change scenarios resulted in a warmer and wetter climate with greater and more extreme discharge in all seasons except summer where the models indicate a somewhat higher probability of extreme low flows (p-value<0.05). The land use scenarios for SWAT showed that nitrate load and discharge positively and linearly scale with percent of agricultural land area (p-value<0.05).

Fluviokarst landscapes are dominated by both fluvial and karst features. Interpreting hydrologic pathways of fluviokarst can be confounded by the unknown connectivity of the various flow regimes. A combined discrete-continuum (CDC) hybrid numeric model for simulating the surface and subsurface hydrology and hydraulics in fluviokarst basins was formulated to investigate fluviokarst pathways. This model was applied to the Cane Run Royal Springs basin in Kentucky USA. A priori constraints on parameterization were avoided via multi-stage optimization utilizing Sobol sequencing and high performance computing. Modelling results provide evidence of hydrologic pathways dominated by fracture flow, epikarst transfer and runoff. Fractures in karst basins with high fracture-matrix permeability ratios may influence both springflow and streamflow. Swallet features can be as important as spring features as they are sink features in streamflow during hydrologic events. Inflections in spring hydrographs represent shifts in the surface-subsurface connectivity via the fractures, as opposed to shifts in dominant storage zones. Existing methods of dual- and triunal hydrograph separation of karst springflow may not be directly transferrable to fluviokarst springs. The numerical model herein has advantages of suggesting dominant pathways in complex terrane and highlighting unforeseen surface-subsurface connectivity. However, disadvantages include computational expense and previous site studies.

Doctor of Philosophy / The problem of water scarcity has become one of the most controversial topics in Australia over the past decades, with particular focus being the ‘sustainable’ allocation of water between extractive and environmental purposes. Geographical factors are defining the extreme variability in climate and water supply in Australia and, in the past, this was used as a rationale for the construction of large irrigation projects to deliver water to rural, urban, and industrial users. During this ‘expansionary’ phase of Australia’s water use sector, the cost of augmenting supply was relatively low and environmental considerations were secondary to the development imperative. As a result, water resources became over-allocated for extractive uses spurred on by consistent underpricing of water, which indicated a failure to reflect the true cost of water supply. As Australia’s water economy entered a ‘mature’ phase, it was no longer possible to increase supply cheaply as the most easily accessible water resources had already been captured. This was followed by widespread environmental degradation manifested in the Murray- Darling Basin, the nation’s largest river basin which hosts much of Australia’s agricultural production. Consequently, the focus shifted towards demand management, leading to a myriad of regulation aimed at increasing the allocative efficiency of scarce water resources. Towards this end, substantial government funding was injected into the various initiatives throughout the water reform process. Despite the on-going government activities in the area of water reform, the understanding of the actual economic impact and environmental outcomes of various water policies in practice remains limited. In the absence of such understanding, the effectiveness of various government water initiatives is ambiguous and inevitably compromised. The present study addresses this knowledge gap by establishing a method for evaluating the economic and environmental outcomes of environmentally-oriented polices that affect irrigated industries in a catchment. The method is based on an integrated biophysical and economic modelling approach, which enables spatial relationships to be captured accurately allowing a more realistic analysis. Information generated from a computer based biophysical simulation model form the basis of an economic optimisation model with constraints pertaining to environmental targets and water supply limits. The economic model consists of a linear programming and dynamic programming component, and involves the optimisation of resource use from a catchment manager’s perspective, seeking to achieve efficient resource use but at the same time conform to given environmental objectives. This embedded linear and dynamic programming approach was required to determine the optimal intra-seasonal and inter-seasonal water allocation, given various catchment environmental targets. The interdisciplinary approach enables the economic and ecological outcomes of the catchment management policies to be simulated and assessed at a spatially explicit scale, due to the link to Geographical Information Systems (GIS) in the biophysical model. The overall objective was to create a decision-making framework that could be used to determine the least-cost means of meeting environmental targets and resource constraints. The solutions to the analysis are directly applicable to the case study, the Mooki catchment in northern New South Wales (NSW), but with an adaptable framework that can be applied to other catchments. Specific objectives include an evaluation of the possibility of using alternative irrigation systems, as well as an evaluation of the benefits that can be realised by establishing water market, in the light of environmentally-oriented catchment policies for the case study. The economic cost of achieving environmental targets pertaining to environmental flow requirements and salinity reduction, in the form of end-of-valley salinity targets, was explicitly calculated through the economic model. While salinity targets have been set for NSW catchments, the practicality of such targets is in question, given the substantial reductions in water allocation to irrigation activities, which is one of the key contributors to deep-drainage. An additional objective in this study was therefore to investigate the value of having deep drainage targets. A further consideration is the effect of “external agents” in the form of government plans to buyback entitlements from irrigation districts, or the possibility of significant water rights purchases from mining industries. The implications of external water market entrants on the regional agricultural industry were examined.

Water quality regulators, such as the Tennessee Department of Environment and Conservation, are challenged by data scarcity when identifying surface water quality impairment causes and pollutant sources. Surface water quality model users also seek to identify pollutant sources and design and place best management practices to efficiently improve water quality, but have insufficient data for model calibration. This research documents the design and evaluation of a novel, intensive water quality data collection system consisting of a automatic sampler, bi-weekly grab sampling, and a long term deployment sonde. System design characteristics that were emphasized included a focus on gathering data for common impairment causes (pathogens, siltation, nutrients, and dissolved oxygen-DO) and water quality criteria not currently being evaluated (pH and temperature rate of change and diurnal DO fluctuations). In addition, the system was designed to gather data for watershed model calibration in rural, un-gauged watersheds because agriculture is listed as the predominant source of water quality impairment in Tennessee. Thus, the system was unmanned to reduce labor input, self-powered because of limited access to the electrical grid, provided sample preservation (refrigeration at low pH), and included stage measurement. Two identical prototype systems were installed in adjacent ecoregion 67g watersheds in Greene County, Tennessee: Lick Creek, impaired for pathogens, nutrients, and low DO, and Little Chucky Creek, which is unimpaired and a former ecoregion reference stream. The two primary objectives of this research were to evaluate the system power demand and determine whether a large water quality dataset improved impairment cause and source identification. A 270 watt solar panel power supply ultimately failed at Lick Creek during the summer when the refrigerated sampler cooling demand peaked, but was sufficient at Little Chucky Creek. System power supply design equations are provided, but with optimization the power supply used would likely be sufficient. The data collected did significantly improve insight into impairment cause identification. For example, total phosphorus rather than total nitrogen concentrations and low DO appeared to be a potential cause of impairment at Lick Creek. The system design was reliable and could be used to calibrate watershed models to improve source assessment.

Farming communities in the United States and around the world lose billions of dollars every year due to drought. Drought Indices such as the Palmer Drought Severity Index (PDSI) and Standardized Precipitation Index (SPI) are widely used by the government agencies to assess and respond to drought. These drought indices are currently monitored at a large spatial resolution (several thousand km2). Further, these drought indices are primarily based on precipitation deficits and are thus good indicators for monitoring large scale meteorological drought. However, agricultural drought depends on soil moisture and evapotranspiration deficits. Hence, two drought indices, the Evapotranspiration Deficit Index (ETDI) and Soil Moisture Deficit Index (SMDI), were developed in this study based on evapotranspiration and soil moisture deficits, respectively. A Geographical Information System (GIS) based approach was used to simulate the hydrology using soil and land use properties at a much finer spatial resolution (16km2) than the existing drought indices. The Soil and Water Assessment Tool (SWAT) was used to simulate the long-term hydrology of six watersheds located in various climatic zones of Texas. The simulated soil water was well-correlated with the Normalized Difference Vegetation Index NDVI (r ~ 0.6) for agriculture and pasture land use types, indicating that the model performed well in simulating the soil water. Using historical weather data from 1901-2002, long-term weekly normal soil moisture and evapotranspiration were estimated. This long-term weekly normal soil moisture and evapotranspiration data was used to calculate ETDI and SMDI at a spatial resolution of 4km ?? 4km. Analysis of the data showed that ETDI and SMDI compared well with wheat and sorghum yields (r > 0.75) suggesting that they are good indicators of agricultural drought. Rainfall is a highly variable input both spatially and temporally. Hence, the use of NEXRAD rainfall data was studied for simulating soil moisture and drought. Analysis of the data showed that raingages often miss small rainfall events that introduce considerable spatial variability among soil moisture simulated using raingage and NEXRAD rainfall data, especially during drought conditions. The study showed that the use of NEXRAD data could improve drought monitoring at a much better spatial resolution.