A Method for Modeling Urban Water Infrastructures Combining Geo-Referenced Data

Water distribution networks are the backbone of any municipal water supply. Their task is to supply the population regardless of the respective demand. High resilience of these infrastructures is of great importance and has brought these infrastructures into the focus of science and politics. At the same time, the data collected is highly sensitive and often openly unavailable. Therefore, researchers have to rely on models that represent the topology of these infrastructures. In this work, a model is developed that allows the topology of an urban water infrastructure to be mapped using the example of Cologne, Germany by combining freely available data. On the one hand, spatial data on land use (local climate zones) are used to disaggregate the water demand within the city under consideration. On the other hand, the parallelism of water and urban transportation infrastructures is used to identify the topology of a network by applying optimization methods. These networks can be analyzed to identify vulnerable areas within urban structures.

[1]  Xiaoxiang Zhu,et al.  Land consumption in cities: A comparative study across the globe , 2021 .

[2]  Modelling the mutual interactions between hydrology, society and water supply systems , 2021 .

[3]  Marian Kremers 2021 , 2021, Vakblad Sociaal Werk.

[4]  Comparability of Water Infrastructure Resilience of Different Urban Structures , 2021 .

[5]  Rushikesh Padsala,et al.  Urban Water Demand Simulation in Residential and Non-Residential Buildings Based on a CityGML Data Model , 2020, ISPRS Int. J. Geo Inf..

[6]  Xiaoxiang Zhu,et al.  Seven city types representing morphologic configurations of cities across the globe , 2020 .

[7]  TIM M. MÜLLER,et al.  Optimization and validation of pumping system design and operation for water supply in high-rise buildings , 2020, Optimization and Engineering.

[8]  Peter F. Pelz,et al.  Optimal Resilience Enhancement of Water Distribution Systems , 2020 .

[9]  M. Demuzere,et al.  Combining expert and crowd-sourced training data to map urban form and functions for the continental US , 2020, Scientific Data.

[10]  Patryk Kot,et al.  Urban Water Demand Prediction for a City That Suffers from Climate Change and Population Growth: Gauteng Province Case Study , 2020, Water.

[11]  Patryk Kot,et al.  A Novel Methodology for Prediction Urban Water Demand by Wavelet Denoising and Adaptive Neuro-Fuzzy Inference System Approach , 2020, Water.

[12]  Emily Zechman Berglund,et al.  Smart meters data for modeling and forecasting water demand at the user-level , 2020, Environ. Model. Softw..

[13]  Peter F. Pelz,et al.  Resilience Enhancement of Critical Infrastructure – Graph-Theoretical Resilience Analysis of the Water Distribution System in the German City of Darmstadt , 2020 .

[14]  Xiao Xiang Zhu,et al.  Fusing Multi-Seasonal Sentinel-2 Images with Residual Convolutional Neural Networks for Local Climate Zone-Derived Urban Land Cover Classification , 2019, IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium.

[15]  Benjamin Bechtel,et al.  Mapping Europe into local climate zones , 2019, PloS one.

[16]  Marc E. Pfetsch,et al.  On Obligations in the Development Process of Resilient Systems with Algorithmic Design Methods , 2018 .

[17]  Andreas Schmitt,et al.  Resilience in Mechanical Engineering - A Concept for Controlling Uncertainty during Design, Production and Usage Phase of Load-Carrying Structures , 2018, Applied Mechanics and Materials.

[18]  K. Lansey,et al.  Estimation of Water Pipe Installation Construction Costs , 2018, Journal of Pipeline Systems Engineering and Practice.

[19]  Joaquín Izquierdo,et al.  Trunk Network Rehabilitation for Resilience Improvement and Energy Recovery in Water Distribution Networks , 2018 .

[20]  Steven J. Burian,et al.  A Systematic Review of Quantitative Resilience Measures for Water Infrastructure Systems , 2018 .

[21]  R. Cobacho,et al.  Water End Use Disaggregation Based on Soft Computing Techniques , 2018 .

[22]  Erik Hollnagel,et al.  Epilogue: RAG – The Resilience Analysis Grid , 2017 .

[23]  M. Mair,et al.  Where to Find Water Pipes and Sewers?—On the Correlation of Infrastructure Networks in the Urban Environment , 2017 .

[24]  Andrew J. Tatem,et al.  WorldPop, open data for spatial demography , 2017, Scientific Data.

[25]  Edo Abraham,et al.  A Graph-Theoretic Framework for Assessing the Resilience of Sectorised Water Distribution Networks , 2016, Water Resources Management.

[26]  Peter F. Pelz,et al.  As Good As It Can Be - Ventilation System Design By A Combined Scaling And Discrete Optimization Method , 2015 .

[27]  G. McCarthy FRAM: the functional resonance analysis method, modelling complex socio-technical systems , 2013 .

[28]  Wolfgang Rauch,et al.  Automatic generation of water distribution systems based on GIS data , 2013, Environ. Model. Softw..

[29]  Peter F. Pelz,et al.  Besser geht's nicht. TOR plant das energetisch optimale Fluidsystem , 2013 .

[30]  T. Oke,et al.  Local Climate Zones for Urban Temperature Studies , 2012 .

[31]  David L. Woodruff,et al.  Pyomo — Optimization Modeling in Python , 2012, Springer Optimization and Its Applications.

[32]  Louis H. Sullivan,et al.  The Tall Office Building Artistically Considered , 2012 .

[33]  Paul Jeffrey,et al.  Resilience enhancing expansion strategies for water distribution systems: A network theory approach , 2011, Environ. Model. Softw..

[34]  Wolfgang Rauch,et al.  Dynamic virtual infrastructure benchmarking: DynaVIBe , 2010 .

[35]  Helge Brattebø,et al.  Asset Management for Urban Wastewater Pipeline Networks , 2010 .

[36]  Aric Hagberg,et al.  Exploring Network Structure, Dynamics, and Function using NetworkX , 2008 .

[37]  Michel Bruneau,et al.  A Framework to Quantitatively Assess and Enhance the Seismic Resilience of Communities , 2003 .

[38]  Ezio Todini,et al.  Looped water distribution networks design using a resilience index based heuristic approach , 2000 .

[39]  Daniel P. Loucks,et al.  Reliability, resiliency, and vulnerability criteria for water resource system performance evaluation , 1982 .