Post-pandemic intended use of remote teaching and digital learning media in higher education. Insights from a europe-wide online survey

The COVID-19 pandemic has had a transformational and potentially long-lasting impact on higher education institutions, with the rapid shift to “Emergency Remote Education”. Two years after the begin of the pandemic, institutions are either returning to presence formats with different speed or converging towards hybrid formats, begging the question what remains of the newly acquired skills and experience with remote teaching and digital learning media? Here, we present the findings of the first European-Union-wide survey on the potential longterm impacts of COVID-19 on higher education, evaluating over 800 responses from students and faculty members of higher education institutions located in 17 different European countries. Our survey – developed in the context of the ide3a university alliance (http://ide3a.net/) highlights possible differences between students and instructors in their attitude toward retaining digital teaching formats and media, examines which formats have increased in use over the course of the pandemic, and investigates which of them are intended to be kept and consolidated post-pandemic. The tools and formats examined in this survey include tools for communication and collaboration, formats of didactic activity, as well as assessment formats. Survey responses reveal that all evaluated tools and format have significantly increased in use during the pandemic and most of them are intended to be used at lower frequency in the future, while still at significantly higher frequency than before the pandemic. Moreover, attitudes toward long-term use of remote teaching and digital learning media seems to be comparable between students and faculty members, except regarding some tool

Practice makes the model: a critical review of stormwater green infrastructure modelling practice

Green infrastructures (GIs) have in recent decades emerged as sustainable technologies for urban stormwater management, and numerous studies have been conducted to develop and improve hydrological models for GIs. This review aims to assess current practice in GI hydrological modelling, encompassing the selection of model structure, equations, model parametrization and testing, uncertainty analysis, sensitivity analysis, the selection of objective functions for model calibration, and the interpretation of modelling results. During a quantitative and qualitative analysis, based on a paper analysis methodology applied across a sample of 270 published studies, we found that the authors of GI modelling studies generally fail to justify their modelling choices and their alignments between modelling objectives and methods. Some practices, such as uncertainty analysis, were also found to be limited, despite their necessity being widely acknowledged by the scientific community and their application in other fields. In order to improve current GI modelling practice, the authors suggest the following: i) a framework, called STAMP, designed to promote the standardisation of the documentation of GI modelling studies, and ii) improvements in modelling tools for facilitating good practices, iii) the sharing of data for better model testing, iv) the evaluation of the suitability of hydrological equations for GI application, v) the publication of clear statements regarding model limitations and negative results.publishedVersio

Coupled simulation of urban water networks and interconnected critical urban infrastructure systems: A systematic review and multi-sector research agenda

Adaptive planning of water infrastructure systems is crucial to bolster urban resilience in the face of climate change while meeting the needs of rapidly changing urban metabolisms. Urban water systems maintain intricate interconnections with other critical infrastructure domains (CIDs). Multi-sector dependencies and joint management of different CIDs have gained interest in recent research to mitigate undesired cascading effects across domains. Yet, combined modeling and joint simulation of multiple CIDs needs to overcome the limitations of tools and software often siloed to individual infrastructure domains. In this paper, we contribute a systematic review of 24 recent peer-reviewed publications on coupled simulation of urban water systems (water supply and drainage networks) and other CIDs, including energy grids, mobility networks, and IT infrastructure systems, extracted from a larger set of 222 publications. First, we identify trends, modeling frameworks, and simulation software enabling the combined simulation of interlinked CIDs. Then, we define an agenda of priorities for future research. Acknowledging the opportunities provided by open-source tools, data, and standardized evaluation schemes, future research fostering coupled simulation across CIDs should prioritize knowledge transfer, address differences in spatial and temporal dependencies, scale up simulations to a network level, and explore multi-sector interconnections beyond bilateral dependencies

Comparison of Multi-Criteria Decision Support Methods for Integrated Rehabilitation Prioritization

The decisions taken in rehabilitation planning for the urban water networks will have a long lasting impact on the functionality and quality of future services provided by urban infrastructure. These decisions can be assisted by different approaches ranging from linear depreciation for estimating the economic value of the network over using a deterioration model to assess the probability of failure or the technical service life to sophisticated multi-criteria decision support systems. Subsequently, the aim of this paper is to compare five available multi-criteria decision-making (MCDM) methods (ELECTRE, AHP, WSM, TOPSIS, and PROMETHEE) for the application in an integrated rehabilitation management scheme for a real world case study and analyze them with respect to their suitability to be used in integrated asset management of water systems. The results of the different methods are not equal. This occurs because the chosen score scales, weights and the resulting distributions of the scores within the criteria do not have the same impact on all the methods. Independently of the method used, the decision maker must be familiar with its strengths but also weaknesses. Therefore, in some cases, it would be rational to use one of the simplest methods. However, to check for consistency and increase the reliability of the results, the application of several methods is encouraged

On the influence of input data uncertainty on sewer deterioration models – a case study in Norway

Visual inspection is currently the industry standard for assessing sewer and stormwater pipelines – a method prone to uncertainties as shown by previous studies. The data gathered from the visual inspection procedures is the main information base on which rehabilitation and replacement strategies are founded in current practice. Consequently, this study evaluates the quality of visual inspection data by quantifying the uncertainty and assessing its impact on the output of a deterioration model. The study was carried out by re-classifying pipe condition classes using the same video footage and transferring differences in the classifications into a distribution that was used as a measure of input data uncertainty. This quantified uncertainty was then propagated into a deterioration model using a Monte Carlo approach to assess its impact on the model behaviour. Results show that there is a considerable uncertainty in condition classes coded according to the Norwegian standard, and that it is comparable to uncertainties estimated in other studies using various European coding systems. The uncertainty assessment indicates that the uncertainties have a considerable impact on the model predictions, which in consequence demonstrates that the uncertainty in the visual inspection methodology can heavily influence the decisions for rehabilitation and replacement strategies

Comparison of Multi-Criteria Decision Support Methods for Integrated Rehabilitation Prioritization

The decisions taken in rehabilitation planning for the urban water networks will have a long lasting impact on the functionality and quality of future services provided by urban infrastructure. These decisions can be assisted by different approaches ranging from linear depreciation for estimating the economic value of the network over using a deterioration model to assess the probability of failure or the technical service life to sophisticated multi-criteria decision support systems. Subsequently, the aim of this paper is to compare five available multi-criteria decision-making (MCDM) methods (ELECTRE, AHP, WSM, TOPSIS, and PROMETHEE) for the application in an integrated rehabilitation management scheme for a real world case study and analyze them with respect to their suitability to be used in integrated asset management of water systems. The results of the different methods are not equal. This occurs because the chosen score scales, weights and the resulting distributions of the scores within the criteria do not have the same impact on all the methods. Independently of the method used, the decision maker must be familiar with its strengths but also weaknesses. Therefore, in some cases, it would be rational to use one of the simplest methods. However, to check for consistency and increase the reliability of the results, the application of several methods is encouraged.(VLID)2519672Version of recor

Flow Measurements Derived from Camera Footage Using an Open-Source Ecosystem

Sensors used for wastewater flow measurements need to be robust and are, consequently, expensive pieces of hardware that must be maintained regularly to function correctly in the hazardous environment of sewers. Remote sensing can remedy these issues, as the lack of direct contact between sensor and sewage reduces the hardware demands and need for maintenance. This paper utilizes off-the-shelf cameras and machine learning algorithms to estimate the discharge in open sewer channels. We use convolutional neural networks to extract the water level and surface velocity from camera images directly, without the need for artificial markers in the sewage stream. Under optimal conditions, our method estimates the water level with an accuracy of ±2.48% and the surface velocity with an accuracy of ±2.08% in a laboratory setting—a performance comparable to other state-of-the-art solutions (e.g., in situ measurements)

Uncertainty analysis in a large-scale water quality integrated catchment modelling study

Receiving water quality simulation in highly urbanised areas requires the integration of several processes occurring at different space-time scales. These integrated catchment models deliver results with a significant uncertainty level associated. Still, uncertainty analysis is seldom applied in practice and the relative contribution of the individual model elements is poorly understood. Often the available methods are applied to relatively small systems or individual sub-systems, due to limitations in organisational and computational resources. Consequently this work presents an uncertainty propagation and decomposition scheme of an integrated water quality modelling study for the evaluation of dissolved oxygen dynamics in a large-scale urbanised river catchment in the Netherlands. Forward propagation of the measured and elicited uncertainty input-parametric distributions was proposed and contrasted with monitoring data series. Prior ranges for river water quality-quantity parameters lead to high uncertainty in dissolved oxygen predictions, thus the need for formal calibration to adapt to the local dynamics is highlighted. After inferring the river process parameters with system measurements of flow and dissolved oxygen, combined sewer overflow pollution loads became the dominant uncertainty source along with rainfall variability. As a result, insights gained in this paper can help in planning and directing further monitoring and modelling efforts in the system. When comparing these modelling results to existing national guidelines it is shown that the commonly used concentration-duration-frequency tables should not be the only metric used to select mitigation alternatives and may need to be adapted in order to cope with uncertainties