Jörg Rieckermann

Last Name

Rieckermann

First Name

Jörg

ORCID

0000-0003-4227-2429

Organisational unit

01109 - Lehre Bau, Umwelt und Geomatik

Show all metadata

Search Results

Publications 1 - 10 of 17

Does distributed monitoring improve the calibration of urban drainage models?
Wani, Omar Farooq; Maurer, Max; Rieckermann, Jörg; et al. (2022)
Costa Mesa
We conclude that while distributed sensing of discharge and water level helps understanding the dynamics of the stormwater runoff, it is not always straightforward to make better predictive models of complex urban drainage networks using this data. This analysis - by delineating the bottlenecks towards informative inference - provides via-negativa recommendations for the placement of distributed sensors, when improved model performance is also one of the motivating factors for such data collection campaigns.
Network condition simulator for benchmarking sewer deterioration models
Scheidegger, Andreas; Hug, Thomas; Rieckermann, Jörg; et al. (2011)
Water Research
Saubere Gewässer dank Messdatenmanagement
Manny, Liliane; Fischer, Manuel; Staufer, Philipp; et al. (2019)
Aqua & Gas
How Urban Storm- and Wastewater Management Prepares for Emerging Opportunities and Threats: Digital Transformation, Ubiquitous Sensing, New Data Sources, and Beyond - A Horizon Scan
Blumensaat, Frank; Leitão, João P.; Ort, Christoph; et al. (2019)
Environmental Science & Technology
Ubiquitous sensing will create many opportunities and threats for urban water management, which are only poorly understood today. To identify the most relevant trends, we conducted a horizon scan regarding how ubiquitous sensing will shape the future of urban drainage and wastewater management. Our survey of the international urban water community received an active response from both the academics and the professionals from the water industry. The analysis of the responses demonstrates that emerging topics for urban water will often involve experts from different communities, including aquatic ecologists, urban water system engineers and managers, as well as information and communications technology professionals and computer scientists. Activities in topics that are identified as novel will either require (i) cross-disciplinary training, such as importing new developments from the IT sector, or (ii) research in new areas for urban water specialists, for example, to help solve open questions in aquatic ecology. These results are, therefore, a call for interdisciplinary research beyond our own discipline. They also demonstrate that the water management community is not yet prepared for the digital transformation, where we will experience a data demand, i.e. a “pull” of urban water data into external services. The results suggest that a lot remains to be done to harvest the upcoming opportunities. Horizon scanning should be repeated on a routine basis, under the umbrella of an experienced polling organization.
Measuring diameters and velocities of artificial raindrops with a neuromorphic event camera
Micev, Kire; Steiner, Jan; Aydin, Asude; et al. (2024)
Atmospheric Measurement Techniques
Hydrometers that measure size and velocity distributions of precipitation are needed for research and corrections of rainfall estimates from weather radars and microwave links. Existing optical disdrometers measure droplet size distributions, but underestimate small raindrops and are impractical for widespread always-on IoT deployment. We study the feasibility of measuring droplet size and velocity using a neuromorphic event camera. These dynamic vision sensors asynchronously output a sparse stream of pixel brightness changes. Droplets falling through the plane of focus of a steeply down-looking camera create events generated by the motion of the droplet across the field of view. Droplet size and speed are inferred from the hourglass-shaped stream of events. Using an improved hard disk arm actuator to reliably generate artificial raindrops with a range of small sizes, our experiments show maximum errors of 7 % (mean absolute percentage error) for droplet sizes from 0.3 to 2.5 mm and speeds from 1.3 to 8.0 m s⁻¹. Measurements with the same setup from a commercial PARSIVEL disdrometer show similar results. Both devices slightly overestimate the small droplet volume with a volume overestimation of 25 % from the event camera measurements and 50 % from the PARSIVEL instrument. Each droplet requires processing of 5000 to 50 000 brightness change events, potentially enabling low-power always-on disdrometers that consume power proportional to the rainfall rate. Data and code are available at the paper website https://sites.google.com/view/dvs-disdrometer/home (Micev et al., 2023).
A distributed heat transfer model for thermal-hydraulic analyses in sewer networks
Figueroa, Alejandro; Hadengue, Bruno; Leitão, João P.; et al. (2021)
Water Research
Thermal-hydraulic considerations in urban drainage networks are essential to utilise available heat capacities from waste- and stormwater. However, available models are either too detailed or too coarse; fully coupled thermal-hydrodynamic modelling tools are lacking. To predict efficiently water-energy dynamics across an entire urban drainage network, we suggest the SWMM-HEAT model, which extends the EPA-StormWater Management Model with a heat-balance component. This enables conducting more advanced thermal-hydrodynamic simulation at full network scale than currently possible. We demonstrate the usefulness of the approach by predicting temperature dynamics in two independent real-world cases under dry weather conditions. We furthermore screen the sensitivity of the model parameters to guide the choice of suitable parameters in future studies. Comparison with measurements suggest that the model predicts temperature dynamics adequately, with RSR values ranging between 0.71 and 1.1. The results of our study show that modelled in-sewer wastewater temperatures are particularly sensitive to soil and headspace temperature, and headspace humidity. Simulation runs are generally fast; a five-day period simulation at high temporal resolution of a network with 415 nodes during dry weather was completed in a few minutes. Future work should assess the performance of the model for different applications and perform a more comprehensive sensitivity analysis under more scenarios. To facilitate the efficient estimation of available heat budgets in sewer networks and the integration into urban planning, the SWMM-HEAT code is made publicly available.
Accounting for erroneous model structures in biokinetic process models
Villez, Kris; Del Giudice, Dario; Neumann, Marc B.; et al. (2020)
Reliability Engineering & System Safety
In engineering practice, model-based design requires not only a good process-based model, but also a good description of stochastic disturbances and measurement errors to learn credible parameter values from observations. However, typical methods use Gaussian error models, which often cannot describe the complex temporal patterns of residuals. Consequently, this results in overconfidence in the identified parameters and, in turn, optimistic reactor designs. In this work, we assess the strengths and weaknesses of a method to statistically describe these patterns with autocorrelated error models. This method produces increased widths of the credible prediction intervals following the inclusion of the bias term, in turn leading to more conservative design choices. However, we also show that the augmented error model is not a universal tool, as its application cannot guarantee the desired reliability of the resulting wastewater reactor design. (© 2020 Elsevier Ltd )
Assessing the performance of international water management at Lake Titicaca
Rieckermann, Jörg; Daebel, Helge; Ronteltap, Mariska; et al. (2006)
Aquatic Sciences
Principal component analysis and sparse polynomial chaos expansions for global sensitivity analysis and model calibration: application to urban drainage simulation
Nagel, Joseph B.; Rieckermann, Jörg; Sudret, Bruno (2019)
Reliability Engineering & System Safety
This paper presents an efficient surrogate modeling strategy for the uncertainty quantification and Bayesian calibration of a hydrological model. In particular, a process-based dynamical urban drainage simulator that predicts the discharge from a catchment area during a precipitation event is considered. The goal of the case study is to perform a global sensitivity analysis and to identify the unknown model parameters as well as the measurement and prediction errors. These objectives can only be achieved by cheapening the incurred computational costs, that is, lowering the number of necessary model runs. With this in mind, a regularity-exploiting metamodeling technique is proposed that enables fast uncertainty quantification. Principal component analysis is used for output dimensionality reduction and sparse polynomial chaos expansions are used for the emulation of the reduced outputs. Sobol’ sensitivity indices are obtained directly from the expansion coefficients by a mere post-processing. Bayesian inference via Markov chain Monte Carlo posterior sampling is drastically accelerated.
Impact of different sources of precipitation data on urban rainfall-runoff predictions: A comparison of rain gauges, commercial microwave links and radar
Disch, A.; Scheidegger, Andreas; Wani, Omar Farooq; et al. (2019)
Rainfall Monitoring, Modelling and Forecasting in Urban Environment. UrbanRain18: 11th International Workshop on Precipitation in Urban Areas. Conference Proceedings

Publications 1 - 10 of 17

Jörg Rieckermann

Last Name

First Name

ORCID

Organisational unit

Filters

Search Results