AN EXPERIMENT ON THE EFFECT OF DIFFERENT SLOPES AND INFLOWS ON MANNING ROUGHNESS PARAMETER AT EINIGHAUSEN, SOUTHERN LIMBURG

Abstract

The region of Limburg in the Netherlands experienced heavy rainfall and flooding in 1993, 1995, and 2021. The 2021 flood caused significant damage, with around 2500 houses, 5000 inhabitants, and 600 businesses affected, resulting in a financial loss of €350-600 million. One of the most flooded villages in Southern Limburg is Einighausen, prompting a study by Waterschap Limburg and the municipality of Sittard-Geleen to reduce flooding. The study, conducted by Sweco, uses a hydraulic model and focuses on the Manning roughness parameter, which influences surface runoff. The aim of this research is to incorporate different slopes and different inflows in an experiment to obtain a more accurate Manning's roughness coefficient (n) for the village of Einighausen in Southern Limburg. To achieve this, an experiment was conducted to investigate the impact of different slopes and inflow rates on the Manning roughness coefficient (n). The experiment involved building a setup with synthetic grass and foam board to mimic impermeable surface conditions. Inflows of 3.5, 4.5, and 5.5 litres per minute (l/min) were tested with slopes ranging from 2° to 20°. Water velocity was measured using a dye tracer, and a 0.6 and 0.7 correction factor were applied for the observed velocities to obtain the mean flow velocity. Using these velocities, Manning roughness coefficients were calculated for various scenarios using the Manning’s equation. Linear regression analysis was used to observe different trends in the calculated Manning roughness coefficients. The obtained n values were then modelled in InfoWorks and analysed in QGIS to assess their effects on accumulated water depths in the area. The results showed that an inflow rate of 3.5 l/min displayed an increase in Manning’s roughness coefficient, whereas the other two experiments, 4.5 and 5.5 l/min, displayed a decrease and a slight decrease in Manning’s roughness coefficients, respectively, with the latter inflow rate showing more of an equilibrium state. The values of Manning n ranged from 0.015 to 0.147 s/m1/3. Furthermore, QGIS-generated difference maps showed higher water depths for Manning’s n with a 0.6 factor compared to no factor and 0.7 factor cases. In conclusion, for slopes ranging from 2° to 20 °, a correction factor of 0.6 should be applied for the observed velocities in combination with higher inflow rates to obtain a more accurate Manning roughness n.