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The book contains a description of the presence of micropollutants (medicines, hormones, pesticides) in surface water and shows that conventional water treatment poorly removes micropollutants. Nanofiltration and reverse osmosis are more appropriate technologies; however removals can vary depending on the properties of compounds and types of membranes. Thus, quantification of removals is studied by means of multivariate data analysis techniques and more understanding of the separation of micropollutants by membranes is achieved. Water reuse practices will increase due to overpopulation of cities, in that sense water membrane treatment will play an important role for the removal of micropollutants, therefore is important to understand characteristics, advantages and disadvantages of NF and RO, this book helps to achieve that understanding.

Seawater desalination is a rapidly growing coastal-based industry. The combined production capacity of all seawater desalination plants worldwide has increased by 30% over the last two years: from 28 million cubic meters per day in 2007—which is the equivalent of the average discharge of the River Seine at Paris—to more than 36 million cubic meters per day in 2009. Seawater desalination is an energy-intensive process. It furthermore consumes considerable amounts of natural resources in the form of chemicals and materials, and may have negative effects on the marine environment due to the discharges of concentrate waste waters and residual chemicals into the sea. The growing number of desalination plants worldwide and the increasing size of single facilities emphasizes the need for greener desalination technologies and more sustainable desalination projects. Two complementing approaches are the development and implementation of best available technology (BAT) standards and best practice guidelines for environmental impact assessment (EIA) studies. While BAT is a technology-based approach, which favors state of the art technologies that reduce resource consumption and waste emissions, EIA aims at minimizing impacts at a site- and project-specific level through environmental monitoring, evaluation of impacts, and mitigation where necessary. The dissertation contains a comprehensive evaluation and synthesis of the potential environmental impacts of desalination plants, with emphasis on the marine environment and aspects of energy use, followed by the development of strategies for impact mitigation. A concept for BAT for seawater desalination technologies is proposed, in combination with a methodological approach for the EIA of desalination projects. The scope of the EIA studies are outlined, including environmental monitoring, toxicity and hydrodynamic modeling studies, and the usefulness of multi-criteria analysis as a decision support tool for EIAs is explored and used to compare different intake and pretreatment options for seawater reverse osmosis plants.

This study showed that BF is an effective multiple objective barrier for removal of different contaminants present in surface water sources including bulk organic matter and organic micropollutants (OMPs) like pharmaceutically active compounds and endocrine disrupting compounds. It was found that biodegradation and adsorption play primary and secondary roles, respectively, in the removal of OMPs during soil passage. Furthermore, using field data from BF sites and chemical properties of OMPs, models were developed to estimate the removal of OMPs during soil passage.

This study provides a hydrology based assessment of (surface) water resources and its continuum of variability and change at different spatio-temporal scales in the semi-arid Karkheh Basin, Iran, where water is scarce, competition among users is high and massive water resources development is under way. The study reveals that the ongoing allocation planning is not sustainable and essentially requires reformulation, with consideration of spatio-temporal variability and observed trends in the streamflows regarding flood intensification and decline in low flows. The development of innovative methods for quantification of the hydrological fluxes (i.e., regionalization of model parameters based on similarity of the flow duration curve and the use of areal precipitation input in the hydrological modeling) helped better understanding and modeling the basin hydrology. The investigation of scenarios for upgrading rain-fed areas to irrigated agriculture, using SWAT, recommends the promotion of in-situ soil and water conservation techniques. Conversion of rain-fed areas to irrigation causes significant reduction in the downstream flows, and requires additional considerations such as less development in the upper catchments, practicing supplementary irrigation and developing water storage. The knowledge generated is instructive for hydrological assessment and its use in water resources planning and management in the river basin context.

Day-to-day water management is challenged by meteorological extremes, causing floods and droughts. Often operational water managers are informed too late about these upcoming events to be able to respond and mitigate their effects, such as by taking flood control measures or even requiring evacuation of local inhabitants. Therefore, the use of weather forecast information with hydrological models can be invaluable for the operational water manager to expand the forecast horizon and to have time to take appropriate action. This is called Anticipatory Water Management. Anticipatory actions may have adverse effects, such as when flood control actions turn out to have been unnecessary, because the actual rainfall was less than predicted. Therefore the uncertainty of the forecasts and the associated risks of applying Anticipatory Water Management have to be assessed. To facilitate this assessment, meteorological institutes are providing ensemble predictions to estimate the dynamic uncertainty of weather forecasts. This dissertation presents ways of improving the end-use of ensemble predictions in Anticipatory Water Management.

This thesis presents the development and validation of a novel three-dimensional sediment transport and morphological numerical model suitable for coastal regions. The thesis discusses the modelling of both suspended and bed-load transport of non-cohesive sediment, important aspects of the morphological updating scheme, and approaches used to model the three-dimensional effects of waves on coastal hydrodynamics. Results of several validation studies are presented and the model is shown to perform well in several theoretical, laboratory, and full scale test cases. Application of the model and acceleration techniques to the complex and dynamic entrance to Willapa Bay, WA, USA is also critically analysed and discussed. A new method to select a representative morphological tide for coastal environments containing significant diurnal tidal energy is presented.

Due to relatively high phosphorus removal efficiency and economy, the enhanced biological phosphorus removal (EBPR) in activated sludge wastewater treatment systems is a widely applied process to control and prevent eutrophication in surface water bodies. However, the EBPR process can be prone to suffer of upsets and deterioration. Since glycogen-accumulating organisms (GAO) compete with polyphosphate-accumulating organisms (PAO), which are the microorganisms that perform the biological phosphorus removal process, the proliferation of GAO has been linked with the instability of the EBPR process. Based on laboratory- and full-scale experimental work as well as mathematical modeling, this research contributes to get a better understanding about the environmental and operating conditions affecting the PAO-GAO competition and, therefore, the EBPR process performance and stability.

In this thesis, several modelling approaches are explored to represent spatial pattern dynamics of aquatic populations in aquatic ecosystems by the combination of models, knowledge and data in different scales. It is shown that including spatially distributed inputs retrieved from Remote Sensing images, a conventional physically-based Harmful Algal Bloom model can be enhanced. Also, Cellular Automata based models using high resolution photographs prove to be good in representing aquatic plant growth. Multi-Agent Systems can capture well the spatial patterns exhibited in GIS density maps. A synthesis modelling framework was developed to include biological/ecological growth and diffusive processes, and local effects in conventional modelling framework. The results of the complementary modelling paradigms investigated in this research can be of help in achieving a sustainable environmental management strategy.

This book presents the investigation of different architectures of integrating hydrological knowledge and models with data-driven models for the purpose of hydrological flow forecasting. The models resulting from such integration are referred to as hybrid models. The book addresses the following topics: A classification of different hybrid modelling approaches in the context of flow forecasting. The methodological development and application of modular models based on clustering and baseflow empirical formulations. The integration of hydrological conceptual models with neural network error corrector models and the use of committee models for daily streamflow forecasting. The application of modular modelling and fuzzy committee models to the problem of downscaling weather information for hydrological forecasting.

This thesis presents powerful machine learning (ML) techniques to build predictive models of uncertainty with application to hydrological models. Two different methods are developed and tested. First one focuses on parameter uncertainty analysis by emulating the results of Monte Carlo simulations of hydrological models using efficient ML techniques. Second method aims at modelling uncertainty by building an ensemble of specialised ML models on the basis of past hydrological model’s performance. Methods employed include artificial neural networks, model trees, locally weighted regression and fuzzy logic. The application of the methods to several real-world case studies demonstrates the capacity of machine learning techniques for building accurate and efficient predictive models of uncertainty.

Accurate predictions of storm surge are of importance in many coastal areas. This book focuses on data-driven modelling using methods of nonlinear dynamics and chaos theory for predicting storm surges. A number of new enhancements are presented: phase space dimensionality reduction, incomplete time series, phase error correction, finding true neighbours, optimization of chaotic model, data assimilation and multi-model ensembles. These were tested on the case studies in the North Sea and Caribbean Sea. Chaotic models appear to be are accurate and reliable short and mid-term predictors of storm surges aimed at supporting decision-makers for flood prediction and ship navigation.

This study on sustainable irrigation development identified growing markets for irrigated products as an important driving force behind the expansion of irrigation which has given rise to new technologies. The new technologies have spread because they gave farmers direct control over water sources. These new technologies allow relatively small farm sizes which can be adequately managed by the surveyed farmers. As a result high productivities are achieved. The hydrological impact of upscaling irrigation in the sub-basin is sustainable and will maximize the overall benefits derived from water resources in the Volta Basin.

This dissertation qualitatively investigates the morphodynamic response of a large inlet system to IPCC projected relative sea level rise (RSLR). Adopted numerical approach (Delft3D) used a highly schematised model domain analogous to the Ameland inlet in the Dutch Wadden Sea. Predicted inlet evolution indicated the typical channel/shoal pattern of the Ameland inlet and an agreement with the empirical-equilibrium relations. RSLR enhances the existing flood-dominance of the system leading to erosion on the ebb-tidal delta and accretion in the basin. Tidal flat evolution was quite stable applying low RSLR whereas the system indicated turning into a lagoon under high RSLR. Nourishment application hardly enabled the RSLR induced sediment demand of tidal flat evolution.

Particulate/colloidal and organic fouling in seawater reverse osmosis (SWRO) systems results in flux decline, higher energy costs, increased salt passage, increased cleaning frequency, and use of chemicals. In practice, indices like SDI and MFI are used to assess particulate fouling, but they are performed at very high initial flux (> 1500 L/m2-h) and do not take into account the deposition of particles/colloids in RO systems. In this study, the Modified Fouling Index with ultrafiltration membranes (MFI-UF) at constant flux was further developed by incorporating the effects of particle/ colloidal deposition and flux. The percentage of particle deposition in real RO plants was between 10-30 % for Mediterranean seawater and between 80-90 % for North seawater. The biopolymer fraction (~60 %) and humic substances (~10-40 %) were found more likely to deposit on RO membranes in full scale desalination plants. A new portable set-up was developed capable of working with membranes of various pore sizes (10-100 kDa) and flux ranges between 10-350 L/m2-h. A model equation to predict particulate fouling was further developed to incorporate the effects of particle/ colloid deposition and flux. Employing the new improved model, the rate of particulate/ colloidal fouling potential of pre-treated seawater was found to be close to that of full scale desalination plants (between 0.2-1 bar/month), using a 10 kDa membrane at similar flux rate to a real RO system. The new developments presented in this study will enable engineers, plant operators and scientists not only to design better plants, but also to improve operation and monitoring of organic and particulate/colloidal fouling in SWRO systems.

This thesis presents the development a generic morphological model for both structured and unstructured grid and the extension to a biogeomorphological model. For the morphological model, numerical algorithms are adjusted to adapt unstructured grid and are validated against analytical solutions and flume experiments. For the bio-geomorphological extension, relevant ecological processes are coupled with morphodynamic processes at various scales and are validated against the field data in Lake Veluwe. Capability of the model has been explored for applications of two salt marsh restoration cases in United States and the large scale morphodynamics of shoreface connected radial sand ridges located in South-east China Sea. Validations and applications show that this modelling platform is capable to be a multidiscipline research tool for morphologists and ecologists / biologists.

Floods are one of the most common and widely distributed natural risks to life and property worldwide. An important part of modern flood risk management is to evaluate vulnerability to floods. This evaluation can be done only by using a parametric approach. Worldwide there is a need to enhance our understanding of vulnerability and to also develop methodologies and tools to assess vulnerability. One of the most important goals of assessing flood vulnerability is to create a readily understandable link between the theoretical concepts of flood vulnerability and the day-to-day decision-making process and to encapsulate this link in an easily accessible tool.

Water utilities in developing countries are struggling to provide customers with a reliable level of service due to their peculiar water distribution characteristics including poorly zoned networks with irregular supply operating under restricted budgets. These unique conditions demand unique tools and methods for water loss control. Water loss management: Tools and Methods for Developing Countries provide a decision support toolbox (appropriate tools and methodologies) for assessing, quantifying, prioritising strategies and improving water distribution efficiency in the developing countries. It promotes good stewardship of water resources and sustainable delivery of water supply services in urban water distribution systems.

This dissertation presents a potential way forward for adaptation to climate change, termed the resilience approach. This approach takes a dynamic perspective on adaptive processes and the effects of these processes at/across different spatio-temporal scales. Experience is provided with four methods that can be used to apply the resilience approach: Adaptive Policy Making, Real-In-Options, Adaptation Tipping Points and - Adaptation Mainstreaming Opportunities. This dissertation discusses the concept, procedure and benefits/limitations of each method, examining its usefulness for informing investment decisions for flood risk management. It also gives specific recommendations on which method to use under what circumstances.