Jason Lowell Jitolis, Farrell Nereus Aegidius, N. Bolong
{"title":"Modelling and Simulation of Bioretention System with HYDRUS-1D","authors":"Jason Lowell Jitolis, Farrell Nereus Aegidius, N. Bolong","doi":"10.1109/IICAIET55139.2022.9936812","DOIUrl":null,"url":null,"abstract":"The design of lab-scale bioretention cell column was constructed based on Urban Stormwater Management Manual for Malaysia (MSMA) specifications. The stormwater runoff flowrate applied to each column was calculated to mimic the actual scale impervious area for generation of runoff. An inflow and outflow of water was measured using water flow sensor, simulating rainfall runoff correlation with depth and hydraulic conductivity parameters effects. A model to simulate the water movement beneath the engineered soil media, one dimensional (l-D) model of water flow was used to study the effect of different media depth and rainfall intensity on hydraulic conductivity parameter value. It resulted that at lower rainfall intensity of 5.3mm/min small percentage of runoff volume reduction was observed at low height of media (150mm) with a total of 11% compared to 55% of 250 mm media height. The recommended media depth values for moderate storm event are <250mm but not less than 150mm to achieve half of the volume to be treated and maintain the acceptable contact time for higher treatment capabilities. An average of 0.03mm/min hydraulic conductivity is suitable for moderate rainfall scenario as simulate by HYDRUS 1D. On the other hand, results at higher rainfall intensity (12mm/min), no large deviation was observed in terms of percentage of runoff volume reduction between both heights. The thickness ranges are not within the required control volume runoff. Thus, further optimization at lower depth is essential.","PeriodicalId":142482,"journal":{"name":"2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","volume":"46 9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IICAIET55139.2022.9936812","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The design of lab-scale bioretention cell column was constructed based on Urban Stormwater Management Manual for Malaysia (MSMA) specifications. The stormwater runoff flowrate applied to each column was calculated to mimic the actual scale impervious area for generation of runoff. An inflow and outflow of water was measured using water flow sensor, simulating rainfall runoff correlation with depth and hydraulic conductivity parameters effects. A model to simulate the water movement beneath the engineered soil media, one dimensional (l-D) model of water flow was used to study the effect of different media depth and rainfall intensity on hydraulic conductivity parameter value. It resulted that at lower rainfall intensity of 5.3mm/min small percentage of runoff volume reduction was observed at low height of media (150mm) with a total of 11% compared to 55% of 250 mm media height. The recommended media depth values for moderate storm event are <250mm but not less than 150mm to achieve half of the volume to be treated and maintain the acceptable contact time for higher treatment capabilities. An average of 0.03mm/min hydraulic conductivity is suitable for moderate rainfall scenario as simulate by HYDRUS 1D. On the other hand, results at higher rainfall intensity (12mm/min), no large deviation was observed in terms of percentage of runoff volume reduction between both heights. The thickness ranges are not within the required control volume runoff. Thus, further optimization at lower depth is essential.