The nexus of inhabitants and impervious surfaces at city scale — wastewater and stormwater travel time distributions and an approach to calibrate diurnal variations

ABSTRACT

We present an approach to calibrate dry weather flow patterns of people in eight subnetworks of Dresden, Germany. The monitored data was pre-processed, and SWMM model runs were performed. Congruence of modelled results and observed data was evaluated with the Nash-Sutcliffe Efficiency (NSE). New diurnal variation patterns of dry weather flow were quantified based on the presented calibration approach. Most of the modelled hydrographs exceeded an NSE of 0.9 just after the second SWMM model run, which is a sign of model adequacy. Travel time distributions (TTDs) of upstream wastewater from connected people and stormwater from impervious surfaces of the monitored locations were determined, and a dynamic index ƒ_iA-PE(k) was proposed, determined and its adequacy was assessed. In general, TTDs confirmed a lower population density and a less meshed urban drainage network in the outer parts of Dresden. The functional information within ƒ_iA-PE(k) considers development characteristics among the subnetworks and within a subnetwork of interest. The presented index is useful to evaluate prospective strategies of developments and the implementation of green and blue infrastructures in residential areas.

KEYWORDS:

• Dry weather flow pattern calibration
• travel time distribution
• impervious area per population equivalent index

Acknowledgements

This study is an outcome from the Synthesis Workshop on ‘Dynamics of Structure and Functions of Complex Networks’ held at Korea University in 2015 and at Purdue University in 2016.

Financial support for this study has been provided by the research project ‘COLABIS’ (Collaborative Early Warning Information Systems for Urban Infrastructures), which was funded by the German Federal Ministry of Education and Research (BMBF) (Grant reference 03G0852A).

PSCR was supported, in part, by NSF Collaborative Research Project ‘Resilience Simulation for Water, Power, and Road Networks (Award 1441188)’, and the Lee A Rieth Endowment in the Lyles School of Civil Engineering, Purdue University.

The authors gratefully acknowledge the cooperation with Stadtentwässerung Dresden GmbH and two anonymous reviewers for their advice and valuable comments.

Disclosure statement

No potential conflict of interest was reported by the authors.

Supplementary material

Supplementary data for this article can be accessed here.

Additional information

Funding

This work was supported by the German Federal Ministry of Education and Research [03G0852A].