Details zur Publikation |
| Kategorie | Textpublikation |
| Referenztyp | Zeitschriften |
| DOI | 10.1016/j.wroa.2025.100466 |
Lizenz  |
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| Titel (primär) | Urban blocks enable data-reduced, hydraulically sound planning for combined sewer overflow mitigation |
| Autor | Despot, D.
; Khurelbaatar, G.
; Lippera, M.C.; Dev Roy, S.; Müller, R.
; Friesen, J.
|
| Quelle | Water Research X |
| Erscheinungsjahr | 2025 |
| Department | SUBT |
| Seite von | art. 100466 |
| Sprache | englisch |
| Topic | T7 Bioeconomy |
| Supplements | Supplement 1 |
| Keywords | combined sewer overflows; stormwater management; data-reduced; block-scale planning; network generation |
| Abstract | Combined sewer overflows (CSOs) remain a major source of urban water pollution, exacerbated by increasing rainfall extremes and expanding impervious surfaces. Yet efforts to model and mitigate CSOs are often hampered by limited access to detailed sewer infrastructure data. This study presents a data-reduced modelling framework based on delineated urban blocks, which serve as both hydrological response units and the spatial basis for generating gravity-consistent synthetic sewer networks from open geospatial data. We compared four model configurations: Thiessen polygons with a real network, blocks with a real network, blocks with a synthetic network, and a lumped model, using 32 monitored overflow events in a Swiss catchment. The synthetic block model reproduced overflow volumes within –10% to +20%, matched 80% of peak timings within 15 minutes, while reducing structural complexity by approximately 30%. Kling–Gupta efficiency scores confirmed valid performance, though simplified models tended to overpredict peak flows and underestimate overflow durations. The synthetic configuration exhibited more frequent surcharging and lower conduit storage near the outlet, reflecting geometric trade-offs in the automated layout. Despite these limitations, block-based models preserve spatial attribution of runoff and enable rapid screening of decentralised interventions without requiring full network datasets. The framework supports early-stage planning and is compatible with both open-source and utility-held data. By aligning model structure with urban form and reducing data demands, this approach offers a scalable, reproducible framework for planning and prioritising decentralised interventions for CSO mitigation, even in cities with limited access to sewer infrastructure data. |
| dauerhafte UFZ-Verlinkung | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=31709 |
| Despot, D., Khurelbaatar, G., Lippera, M.C., Dev Roy, S., Müller, R., Friesen, J. (2025): Urban blocks enable data-reduced, hydraulically sound planning for combined sewer overflow mitigation Water Res. X , art. 100466 10.1016/j.wroa.2025.100466 |
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