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Updated: Jul 4, 2025

Design and Construction of an Urban Runoff Research Facility
Published on: August 8, 2014
Experimental surface runoff hydrographs from linear impervious subcatchments for rainfalls of extremely high
Volodymyr Zhuk1, Lesya Vovk1, Ihor Popadiuk1
1Lviv Polytechnic National University, Institute of Civil Engineering and Building Systems, S. Bandera Str. 12, Lviv, 79013, Ukraine.
This study presents a new physical model for simulating surface runoff hydrographs in impervious urban areas. Findings reveal flow rate fluctuations and provide models for predicting runoff behavior under intense rainfall.
Area of Science:
- Hydrology
- Environmental Engineering
- Fluid Dynamics
Background:
- Surface runoff modeling is crucial for urban water management.
- Existing methods like the nonlinear reservoir and unit hydrograph methods have limitations.
- Accurate simulation of runoff hydrographs is essential for predicting flood events.
Purpose of the Study:
- To develop and validate an improved physical model for lab-scale surface runoff hydrograph simulations.
- To analyze dimensionless hydrographs and compare them with existing models.
- To investigate the relationship between rainfall intensity and runoff phase time.
Main Methods:
- Conducted lab-scale experiments on a linear impervious plane subcatchment.
- Applied model rains of varying intensities and durations.
- Utilized digital online data processing for high-resolution flow rate determination.
- Analyzed experimental hydrographs in dimensionless form.
- Compared results with nonlinear reservoir and unit hydrograph methods.
Main Results:
- Observed wave-like fluctuations in flow rate as runoff peaked.
- Derived a power-law equation relating dimensionless phase time to rainfall intensity.
- Developed an averaged dimensionless runoff hydrograph.
- Approximated the averaged hydrograph using the DR-Hill-Zerobackground and Weibull models.
Conclusions:
- The improved physical model accurately simulates surface runoff hydrographs.
- The derived dimensionless relationships enhance generalization and comparison capabilities.
- Findings are significant for modeling urban runoff, especially during high-intensity rainfall events.
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