Master's Thesis

The objective of this master thesis is to compare the damage potential of river flooding (fluvial flooding) and flooding from surface runoff (pluvial flooding) for selected case studies. For this, you will create a surface runoff model of a catchment and compute the surface runoff for several precipitation events with different annualities. You will make an on-site plausibility-check and compare your results with the BAFU indicative hazard map for surface runoff. Next, you will evaluate the damage potential with the help of the tool “EconoMe” due to surface runoff and due to river flooding. Download Read More (PDF, 195 KB)

This thesis will be performed in collaboration with Hunziker BetaTech.  

contact: João P. Leitão ()

In recent years, wastewater structures in urban drainage systems have been increasingly equipped with sensors with automatic transmission of the measurements to the operators. As a result, an increasing amount of data is now available that provides information about the processes in the drainage system. However, for data analysis and for deriving correct conclusions, the data must be plausible. Since often long periods of time of many different urban drainage structures are used for evaluation, a high number of measurements must be checked for plausibility.

The thesis aims to develop a method using artificial intelligence to automatically check the plausibility of wastewater measurements, minimizing the need for manual visual checks. It will investigate various sensors in different wastewater structures, conducting both measurement-oriented and process-oriented plausibility checks. This ensures accurate evaluation of parameters like combined sewer overflow statistics and dry weather discharge. Download Read More (PDF, 242 KB)

contact: Juan Pablo Carbajal ()

At Eawag, researchers are developing online monitoring of water reuse and wastewater treatment systems with fluorescence spectroscopy. This fast and green technique characterizes the inherent fluorescent properties of the biological substances (e.g., bacterial cells) and dissolved organic matter (DOM). Each measurement generates a unique image-like data (i.e., the “fingerprint”) that contains abundant information about the concentrations and compositions of pollutants. 

The association between fluorescence signal and other organic pollutants, including emerging micropollutants, is not fully understood yet. It is the assumption that important physical-chemical properties of DOM, such as molecular weight, aromaticity, and bio-degradability, can be estimated by fluorescence signal. This thesis aims at exploring this assumption, verification of which will further justify fluorescence spectroscopy as a versatile tool in water quality monitoring and process control.  Download Read More (PDF, 140 KB)

contact: Yongmin Hu ()

The objective of this MSc thesis is to assess the impact of flocs SRT control on the distribution of nitrifying populations and activities among the flocs and different sized granules in AGS and ultimately the impact on nitrification performance. To address this objective, a full-scale study at WWTP Kloten-Opfikon will be conducted. Reactors at different operating conditions will be monitored by characterizing the size distribution of AGS, conducting settling and activity tests and finally, by determining the distribution of nitrifying populations with DNA analysis. Download Read More (PDF, 240 KB)

contact: Livia Britschgi ()

In aerobic granular sludge (AGS) systems operated as sequencing batch reactors (SBR), a main strategy to enhance granulation is to selectively remove the slow settling biomass. This wastage affects sludge composition, i.e., distribution of flocs and different sized granules, and in turn the microbial performance of the system. The main goal of this master’s thesis is to develop a stratification model and a wastage strategy to control the sludge composition in AGS. The thesis will consist of the following phases:
(A) Short-term stratification experiment
(B) Developing settling model
(C) Simulation of sludge stratification and testing of various wastage strategies aiming for control of sludge composition

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contact: Livia Britschgi ()

Wastewater treatment needs to become net-zero by 2050. The potent GHG and ozone depleting substance N₂O (265 kgCO₂-eq) dominates GHG emissions of wastewater treatment and accounts for around 20% of N₂O emissions in Switzerland. To effectively reduce N₂O emissions, we need to understand the mechanisms behind its formation which is related to microbial pathways, controlling parameters, process engineering and plant operation. Unfortunately, there is currently no N₂O mechanistic model which is able to come up with those cross-plant reduction measures. On the other hand, multi-year N₂O monitoring campaigns across different full-scale plants are available, yet their potential to reveal hidden relationships and mechanisms remains unexplored. This thesis aims to use insights from explainable machine learning (XAI) to build a mechanistic model which is able to reduce N₂O emissions across different wastewater treatment plants in Switzerland and beyond. Download Read More (PDF, 306 KB)

contact: Laurence Strubbe ()

While conventional WWTPs only focus on the removal of organic substrates and nutrients, water resource recovery facilities (WRRFs) will also aim at converting pollutants into valuable end-products. The current project aims at evaluating the conversion of organic carbon from municipal wastewater into bioplastics, i.e., poly-hydroxalkanoates (PHA). PHAs represent, to a certain extent, a relevant alternative to plastics produced by petro-chemical industry. Download Read More. (PDF, 486 KB)

A student interested in biotechnology applied to resource recovery and circular economy, is ideally suited for this thesis.

contact: Nico Derlon ()

A promising solution to increase treatment capacity of existing WWTPs is granulation, a technology where biomass self-aggregates and forms semi-spherical biofilm particles known as aerobic granular sludge (AGS). The main objective of the proposed master thesis is to investigate: (1) the feasibility of the organic media carrier technology and (2) the role of metabolic processes for achieving biomass colonization and granulation in continuous flow systems. The specific objectives are:

• To characterize the physical properties of granules formed.
• To investigate the partitioning of microbial functional groups in flocs versus granules.
• To make practical recommendations for integrating AGS technology in CF systems.
  

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contact: Stephany Wei ()

Water reuse can help lower domestic water consumption. Often, water reuse projects focus on the treatment of greywater as it is generally less polluted. Few studies have investigated opportunistic pathogen growth in treated and stored greywater. This project aims to compare different treatments of greywater and their impact on the treated and stored water over time. A student motivated to learn microbiology laboratory techniques is ideally suited for this thesis. Download Read More. (PDF, 368 KB)

contact: Anne Vescovi ()

This thesis explores how blue-green systems can be designed to reduce toxic micropollu-tant emissions to surface waters and groundwater systems. The student will:

• Assess the current blue-green infrastructure design practice, 
• Identify the most relevant blue-green infrastructure design parameters for water quality, and finally,
• Propose an optimised catchment-wide blue-green infrastructure design based on the micropollutant risks for surface waters and groundwater. 

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contact: Lena Mutzner ()

Growing urban surfaces coupled with climate change lead to increasing impacts on water resources. While wastewater treatment plants in Switzerland are being upgraded to enhance the removal of micropollutants, up to half of the overall micropollutant load can be discharged via combined and separate sewer overflows without treatment. 

The aim of this thesis is to develop a mass flow model to estimate the pollutant loads (micropollutants, nutrients) discharged in Switzerland via sewer overflows for future climate scenarios. Download Read More (PDF, 1.2 MB)

contact: Lena Mutzner ()

Micropollutants (MP) originating from different anthropogenic applications (e.g., pharmaceuticals, anticorrosive coating) are harmful to aquatic ecosystems even in very low concentrations, and thus, have become a key topic on today's political environmental agendas. The use of activated carbon has proven to be a successful option to eliminate MPs. However, many of these plants in Switzerland face problems to continually maintain the required elimination rate of 80%; especially during rain events. 

The goal of this thesis is to investigate whether we can explain the elimination behavior of a powdered activated carbon plant during rain events by using different modelling approaches. A student keen to develop their programming abilities and having a strong interest in MP removal is ideally suited for this thesis. Download Read More. (PDF, 4.4 MB)

contact: Andreas Frömelt ()

The wastewater treatment plant of the future will represent a net source of energy and valuable products, e.g., high-value polymers. Aerobic granular sludge (AGS) contains a wide range of exopolymers, such as Alginate-Like Exopolymers (ALE), associated with various relevant properties for industrial applications (coagulation, production of concrete, paper coating, etc.). 

The overall objective of the proposed master thesis is therefore to develop further our fundamental understanding of the mechanisms of phosphate/potassium recovery from municipal wastewater by ALE hydrogels. A student interested in learning about advanced technologies and microbial processes applied to wastewater treatement is ideally suited for this thesis. Download Read More. (PDF, 107 KB)

contact: Nicolas Derlon ()

Aerobic granular sludge (AGS) systems represent a relevant alternative to conventional activated sludge systems. Eawag recently developed a complete and powerful AGS model (Derlon et al., 2022). The main objective of the proposed master thesis is to (1) critically evaluate the Eawag AGS model by confronting it to datasets from full-scale AGS installations and (2) to develop a good modelling practice (GMP) unified protocol specific of AGS system. A student interested in the learning about advanced technologies and modelling of biological wastewater treatment is ideally suited for this thesis. Download Read More (PDF, 107 KB). 

contact: Nicolas Derlon ()

Aerobic granular sludge (AGS) represents a key advance for wastewater treatment processes (van Loosdrecht and Brdjanovic, 2014), and is presented as the main alternative to conventional activated sludge systems. AGS systems are however usually operated as sequencing batch reactors (SBR), where both microbial and physical selection mechanisms take place and ultimately lead to the formation of granules. But most of the existing WWTP are operated in continuous-flow (CF) mode, while the conversion of CF systems into SBR is very challenging. A main challenge is therefore to develop aerobic granules in systems operated in CF mode, where conditions in terms of microbial and hydraulic selection are not favourable.

The main objective is of the proposed master thesis is to better understand how to control aeration in order to regulate of microbial utilisation of organic substrates, and ultimately to maximize SND and TN removal in AGS systems operated in CF mode.

This master thesis is part of a collaboration between Eawag, Hunziker Betatech AG, ARA Consult and the WWTPs of Gossau and Laufacker.

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contact: Nicolas Derlon ()

Analyzing flood depth and velocity fields using stochastic two-dimensional shallow water equations

The shallow-water equations (SWEs) are a set of hyperbolic partial differential equations that are used to generate two-dimensional time-varying estimates of flood water depth and velocity, with topography of the region and flow from a flooding source as boundary conditions. However, there is considerable uncertainty in the results generated by these equations due to errors in the specification of the boundary conditions and the myriad of sub-processes that are neglected, or simplified, by the flood models based on these equations.

One way to deal with this uncertainty is to generate probabilistic forecasts. In this thesis, we will explore the applicability of introducing noise within the SWEs and converting them into standard stochastic differential equations to obtain more informative two-dimensional flood predictions. Download Read more (PDF, 416 KB)

contact: João P. Leitão ()

external page The BAFU funded project WABEsense has sensorized alpine water springs and produced data of their water production (discharge and water temperature). The detailed water production data allow municipalities to enhance their general water supply planning (Generelle Wasserversorgungsplanung) and it can also be used by researchers to model the behavior of alpine water springs and the water table in the alps. Furthermore, characterization of the spring behavior leads to a better understanding of their hydrogeology, their effect in the local ecology, and (by long-term tracking of the spring’s characteristics) allow us to assess how climate change and land use is affecting them. 

The objectives of this thesis are: 

1. To enhance the validation of the measurment systems installed, and data processing used by WABEsense; involves in-situ manual measurements at the spring.
2. To determine which spring models published in literature could be calibrated using available data, and in a next step performing such a calibration. 
3. To identify data-driven spring parameters (e.g., flushiness, retention time, stability, etc.) 

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contact: João P. Leitão ()

Traditional design methods in urban drainage use idealized model rainfalls, so-called “design storms". Modern approaches do not require these model rainfalls as they can assess the hydraulic performance directly based on continuous hydraulic simulations with long-term precipitation series. Where long-term observations are missing, synthetic rainfall series can be used.

In this thesis, available rainfall generators (Kim & Onof, 2020) (Bárdossy, et al., 2020) will be applied to produce synthetic rainfall series for entire CH, based on a variety of available rainfall information. It will thus improve first results with more detailed rainfall data from various sources. In addition, suitable interpolation techniques which consider the complex Swiss topography must be investigated to produce time series with a 1x1km resolution for Switzerland. A student with interest in spatio-temporal data analysis, an affinity for mathematical models, and basic knowledge of a programming languages like R, Python, etc., is ideally suited for this thesis. Download Read more (PDF, 878 KB)

contact: Jörg Rieckermann ()