Model parameter estimation with imprecise information.

Model parameter estimation is a well-known inverse problem, as long as single-value point data are available as observations of system performance measurement. However, classical statistical methods, such as the minimization of an objective function or maximum likelihood, are no longer straightforward, when measurements are imprecise in nature. Typical examples of the latter include censored data and binary information. Here, we explore Approximate Bayesian Computation as a simple method to perform model parameter estimation with such imprecise information. We demonstrate the method for the example of a plain rainfall-runoff model and illustrate the advantages and shortcomings. Last, we outline the value of Shapley values to determine which type of observation contributes to the parameter estimation and which are of minor importance.

Integrating CFD-GIS modelling to refine urban heat and thermal comfort assessment.

Constant urban growth exacerbates the demand for residential, commercial and traffic areas, leading to progressive surface sealing and urban densification. With climate change altering precipitation and temperature patterns worldwide, cities are exposed to multiple risks, demanding holistic and anticipatory urban planning strategies and adaptive measures that are multi-beneficial. Sustainable urban planning requires comprehensive tools that account for different aspects and boundary conditions and are capable of mapping and assessing crucial processes of land-atmosphere interactions and the impacts of adaptation measures on the urban climate system. Here, we combine Computational Fluid Dynamics (CFD) and Geographic Information System (GIS) capabilities to refine an existing 2D urban micro- and bioclimatic modelling approach. In particular, we account for the vertical and horizontal variability in wind speed and air temperature patterns in the urban canopy layer. Our results highlight the importance of variability of these patterns in analysing urban heat development, intensity and thermal comfort at multiple heights from the ground surface. Neglecting vertical and horizontal variability, non-integrated CFD modelling underestimates mean land surface temperature by 7.8 °C and the Universal Thermal Climate Index by 6.9 °C compared to CFD-integrated modelling. Due to the strong implications of wind and air temperature patterns on the relationship between surface temperature and human thermal comfort, we urge caution when relying on studies solely based on surface temperatures for urban heat assessment and hot spot analysis as this could lead to misinterpretations of hot and cool spots in cities and, thus, mask the anticipated effects of adaptation measures. The integrated CFD-GIS modelling approach, which we demonstrate, improves urban climate studies and supports more comprehensive assessments of urban heat and human thermal comfort to sustainably develop resilient cities.

A rapid fine-scale approach to modelling urban bioclimatic conditions.

Surface characteristics play a vital role in simulations for urban bioclimatic conditions. Changing relationships and distribution patterns of sealed and vegetated surfaces as well as building geometry across different scales in urban environments influence surface temperatures. Cities comprise different urban forms, which, depending on their surface characteristics, enhance the heating process, increasing the emergence of urban heat islands (UHIs). Detecting priority areas to introduce multi-beneficial climate change adaptation measures is set to be a key task for the cities long-term strategies to improve climatic conditions across different urban structures and scales. We introduce a simple and fast spatial modelling approach to carry out fine-scale simulations for land surface temperature (LST), mean radiant temperature (MRT) and Universal Thermal Climate Index (UTCI) in a 2D environment. Capabilities of our modelling approach are demonstrated in evaluating urban thermal comfort in the alpine city of Innsbruck, the capital of Tyrol in western Austria. Results show a major contrast between sealed and vegetated surfaces reflected in the distributional patterns and values of LST, MRT and UTCI, correlating with the appearance and frequency of specific surface classes. We found the Sky View Factor to have a substantial impact on calculations for bioclimatic conditions and see high-albedo surfaces decrease LST but increase the apparent temperature (MRT and UTCI values) effecting human thermal comfort. Furthermore, MRT and UTCI are more sensitive to changes in emissivity values, whereas LST is more sensitive to changes in Bowen Ratio values. Application of our modelling approach can be used to identify priority areas and maximise multi-functionality of climate change adaptation measures, to support urban planning processes for heat mitigation and the implementation of policy suggestions to achieve sustainable development goals and other political objectives.

What can we learn from a 500-year event? Experiences from urban drainage in Austria.

Urban drainage systems are designed to capture the runoff for a certain return period of a design rainfall event. Typically, numerical models are used, which are calibrated by comparing model response and measured system performance. The applicability of such models to predict the system behaviour under extreme events is unclear, as usually then no data are available. This paper describes the analysis of an extreme rainfall event in the year 2016. The event is characterized by a very short duration and very high rainfall intensities. The maximum-recorded rainfall peak was 47.1 mm rainfall within 10 min, which corresponds to a return period of 500 years. The event caused local flooding on streets, interruptions of traffic and damages in buildings. In order to improve the flood resilience of the city, the event was analysed with an existing 1D hydrodynamic model of the sewer system. Model results were compared to water level measurements in the drainage system and citizen observations of surface flooding (gathered from social media and citizen reports). Although the hydrodynamic model could reproduce water level measurements in parts of the system, the plausibility check using descriptive data showed that the model failed to predict flooding in some areas.

Lost in calibration: why people still do not calibrate their models, and why they still should - a case study from urban drainage modelling.

From a scientific point of view, it is unquestioned that numerical models for technical systems need to be calibrated. However, in sufficiently calibrated models are still used in engineering practice. Case studies in the scientific literature that deal with urban water management are mostly large cities, while little attention is paid to the differing boundary conditions of smaller municipalities. Consequently, the aim of this paper is to discuss the calibration of a hydrodynamic model of a small municipality (15,000 inhabitants). To represent the spatial distribution of precipitation, three distributed rain gauges were used for model calibration. To show the uncertainties imminent to the calibration process, 17 scenarios, differing in assumptions for calibration, were distinguished. To compare the impact of the different calibration scenarios on actual design values, design rainfall events were applied. The comparison of the model results using the different typical design storm events from all the surrounding data points showed substantial differences for the assessment of the sewers regarding urban flooding, emphasizing the necessity of uncertainty analysis for hydrodynamic models. Furthermore, model calibration is of the utmost importance, because uncalibrated models tend to overestimate flooding volume and therefore result in larger diameters and retention volumes.

Simplifying impact of urban development on sewer systems.

Linking urban development and urban drainage models is a more and more popular approach when impacts of pavement of urban areas on sewer system performance are evaluated. As such an approach is a difficult task, this is not a feasible procedure for everyday engineering practice. We propose an alternative method, based on a developed simple near-quadratic relationship, which directly translates change (increase or decrease) of paved area into a change in the return period (RP) of the design rainfall event or design rainfall intensity. This formula is simple to use and compatible with existing design guidelines. A further advantage is that the calculated design RP can also be used to communicate the impact of a change in impervious areas to stakeholders or the public community. The method is developed using a set of 250 virtual and two real-world case studies and hydrodynamic simulations. It is validated on a small catchment for which we compare system performance and redesigned pipe diameters. Of course such a simplification contains different uncertainties. But these uncertainties have to be seen in the context of overall uncertainties when trying to predict city development into the future. Hence it still is a significant advantage compared to today's engineering practice.

Adaptation of sewer networks using integrated rehabilitation management.

The urban water structure is aging and in need of rehabilitation. Further, the need to address future challenges (climate change, urban development) also arise lines. This study investigates if it is possible to combine rehabilitation and adaptation measures. To do so, we combined an urban development model, an urban drainage model and a rehabilitation model. A case study of a medium-sized alpine city with a sewer length of 228 km and a population of 125,431 was used to develop and apply this method. A priority model to pinpoint the structures in need of replacement was used. This model considered a deterioration model, vulnerability estimation and other influences. Further different rehabilitation rates and methods were examined. The urban development model used is a simplistic approach specifically tailored for the field of urban infrastructure management. Climate change is considered in terms of climate change factors. All these different influences together create scenarios for which the construction costs and the flooding volume are estimated and compared. Consequently the aim of this paper was to test to which degree it is possible to reduce urban flooding by adapting those parts of the network which require rehabilitation anyway. In our case study it could be reduced by 5%.

A planning algorithm for quantifying decentralised water management opportunities in urban environments.

With global change bringing about greater challenges for the resilient planning and management of urban water infrastructure, research has been invested in the development of a strategic planning tool, DAnCE4Water. The tool models how urban and societal changes impact the development of centralised and decentralised (distributed) water infrastructure. An algorithm for rigorous assessment of suitable decentralised stormwater management options in the model is presented and tested on a local Melbourne catchment. Following detailed spatial representation algorithms (defined by planning rules), the model assesses numerous stormwater options to meet water quality targets at a variety of spatial scales. A multi-criteria assessment algorithm is used to find top-ranking solutions (which meet a specific treatment performance for a user-defined percentage of catchment imperviousness). A toolbox of five stormwater technologies (infiltration systems, surface wetlands, bioretention systems, ponds and swales) is featured. Parameters that set the algorithm's flexibility to develop possible management options are assessed and evaluated. Results are expressed in terms of 'utilisation', which characterises the frequency of use of different technologies across the top-ranking options (bioretention being the most versatile). Initial results highlight the importance of selecting a suitable spatial resolution and providing the model with enough flexibility for coming up with different technology combinations. The generic nature of the model enables its application to other urban areas (e.g. different catchments, local municipal regions or entire cities).

Integrated planning of rehabilitation strategies for sewers.

Building measures in sewer systems are increasingly driven by rehabilitation/retrofitting and adaptation needs. Aging infrastructure together with changing boundary conditions (due to climate change, land-use change, demographic change) and also changing design standards and legislation require a prospective design to preserve the functionality of urban drainage systems not only today, but also in a long-term perspective. To improve a prospective design of urban water infrastructure, the Austrian Research Promotion Agency funded the research project 'REHAB - Integrated planning of rehabilitation strategies of urban infrastructure systems'. Therein a novel strategic planning tool which considers these external drivers of rehabilitation strategies is developed. In this study the scope of the project is described and, as well as first results regarding sewer pipe conditions, future development and vulnerability assessment are also discussed.

Comparison of different uncertainty techniques in urban stormwater quantity and quality modelling.

Urban drainage models are important tools used by both practitioners and scientists in the field of stormwater management. These models are often conceptual and usually require calibration using local datasets. The quantification of the uncertainty associated with the models is a must, although it is rarely practiced. The International Working Group on Data and Models, which works under the IWA/IAHR Joint Committee on Urban Drainage, has been working on the development of a framework for defining and assessing uncertainties in the field of urban drainage modelling. A part of that work is the assessment and comparison of different techniques generally used in the uncertainty assessment of the parameters of water models. This paper compares a number of these techniques: the Generalized Likelihood Uncertainty Estimation (GLUE), the Shuffled Complex Evolution Metropolis algorithm (SCEM-UA), an approach based on a multi-objective auto-calibration (a multialgorithm, genetically adaptive multi-objective method, AMALGAM) and a Bayesian approach based on a simplified Markov Chain Monte Carlo method (implemented in the software MICA). To allow a meaningful comparison among the different uncertainty techniques, common criteria have been set for the likelihood formulation, defining the number of simulations, and the measure of uncertainty bounds. Moreover, all the uncertainty techniques were implemented for the same case study, in which the same stormwater quantity and quality model was used alongside the same dataset. The comparison results for a well-posed rainfall/runoff model showed that the four methods provide similar probability distributions of model parameters, and model prediction intervals. For ill-posed water quality model the differences between the results were much wider; and the paper provides the specific advantages and disadvantages of each method. In relation to computational efficiency (i.e. number of iterations required to generate the probability distribution of parameters), it was found that SCEM-UA and AMALGAM produce results quicker than GLUE in terms of required number of simulations. However, GLUE requires the lowest modelling skills and is easy to implement. All non-Bayesian methods have problems with the way they accept behavioural parameter sets, e.g. GLUE, SCEM-UA and AMALGAM have subjective acceptance thresholds, while MICA has usually problem with its hypothesis on normality of residuals. It is concluded that modellers should select the method which is most suitable for the system they are modelling (e.g. complexity of the model's structure including the number of parameters), their skill/knowledge level, the available information, and the purpose of their study.

An application of Austrian legal requirements for CSO emissions.

The Austrian standard for designing combined sewer overflow (CSO) detention basins introduces the efficiency of the combined sewer overflows as an indicator for CSO pollution. Additionally criteria for the ambient water quality are defined, which comprehend six kinds of impacts. In this paper, the Austrian legal requirements are described and discussed by means of hydrological modelling. This is exemplified with the case study Innsbruck (Austria) including a description for model building and model calibration. Furthermore an example is shown in order to demonstrate how - in this case- the overall system performance could be improved by implementing a cost-effective rearrangement of the storage tanks already available at the inflow of the wastewater treatment plant. However, this guideline also allows more innovative methods for reducing CSO emissions as measures for better usage of storage volume or de-centralised treatment of stormwater runoff because it is based on a sewer system simulation.