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Commercial microwave links for urban drainage modelling: The effect of link characteristics and their position on runoff simulations.

  • Pastorek J Department of Hydraulics and Hydrology, Czech Technical University in Prague, Thákurova 7, 166 29, Prague 6, Czech Republic. Electronic address: jaroslav.pastorek@fsv.cvut.cz.
  • Fencl M Department of Hydraulics and Hydrology, Czech Technical University in Prague, Thákurova 7, 166 29, Prague 6, Czech Republic. Electronic address: martin.fencl@cvut.cz.
  • Rieckermann J Department of Urban Water Management, Eawag: Swiss Federal Institute of Aquatic Science and Technology, Überlandstrasse 133, CH-8600, Dübendorf, Switzerland. Electronic address: joerg.rieckermann@eawag.ch.
  • Bareš V Department of Hydraulics and Hydrology, Czech Technical University in Prague, Thákurova 7, 166 29, Prague 6, Czech Republic. Electronic address: vojtech.bares@cvut.cz.
  • 2019-09-22
Published in:
  • Journal of environmental management. - 2019
Commercial microwave links
Opportunistic sensing
Quantitative precipitation estimates
Rainfall monitoring
Rainfall-runoff modelling
Urban catchment
Cities
Czech Republic
Environmental Monitoring
Microwaves
Models, Theoretical
Rain
Water Movements
English Commercial microwave links (CMLs), radio connections widely used in telecommunication networks, can provide path-integrated quantitative precipitation estimates (QPEs) which could complement traditional precipitation observations. This paper assesses the ability of individual CMLs to provide relevant QPEs for urban rainfall-runoff simulations and specifically investigates the influence of CML characteristics and position on the predicted runoff. The analysis is based on a 3-year-long experimental data set from a small (1.3 km2) urban catchment located in Prague, Czech Republic. QPEs from real world CMLs are used as inputs for urban rainfall-runoff predictions and subsequent modelling performance is assessed by comparing simulated runoffs with measured stormwater discharges. The results show that model performance is related to both the sensitivity of CML to rainfall and CML position. The bias propagated into the runoff predictions is inversely proportional to CML path length. The effect of CML position is especially pronounced during heavy rainfalls, when QPEs from shorter CMLs, located within or close to catchment boundaries, better reproduce runoff dynamics than QPEs from longer CMLs extending far beyond the catchment boundaries. Interestingly, QPEs averaged from all available CMLs best reproduce the runoff temporal dynamics. Adjusting CML QPEs to three rain gauges located 2-3 km outside of the catchment substantially reduces the bias in CML QPEs. Unfortunately, this compromises the ability of the CML QPEs to reproduce runoff dynamics during heavy rainfalls. More experimental case studies are necessary to provide specific recommendations on CML preprocessing methods tailored to different water management tasks, catchments and CML networks.
Language
  • English
Open access status
green
Identifiers
Persistent URL
https://sonar.ch/global/documents/16298
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