Research Article Open Access

Detention Pond Sediment Accumulation Prediction using Monte Carlo Simulation

Supiah Shamsudin, Abd Rashid Mohd Darom, Irma Norazurah Mohamad and Azmi Ab Rahman

Abstract

Problem statement: A study in Malaysia had been carried out to predict the sediment accumulation in urban detention ponds. Suspended sediment is pollutant of primary concern to the river that results in adverse environmental effect. Detention pond becomes a practical approach to this problem. Suspended sediment that settled in stormwater detention pond, can bring effect to the detention pond functions. Questions were raised on how certain were the observed and predicted values of sediment depth and load accumulation estimations. Secondly the question was what the sediment accumulation be in the next 100 years. The uncertainties of sediments estimation vary greatly due to the hydrological variability and rainfall random nature obtain the relationship between flow discharge and suspended sediment rate using on-site data collection at UTM and Ledang Heights, Nusajaya. Predict accumulated sediment loads and depth from MUSLE over 10-100 years. Analyze the uncertainties of sediment loads and depth using Monte Carlo Simulation (MCS) combining normal distribution. Obtain the maximum probability of occurrence of sediment loads and depth in the detention pond. Approach: Modified Universal Soil Loss Equation (MUSLE) and Trap Efficiency (TE) Method was applied to predict sediment accumulation. This uncertainty of sediment loads and depth was carried out using Monte Carlo Simulation (MCS) Method. The water samples were collected for suspended solids data and other water quality parameters at Ledang Heights, Nusajaya, Johor and University Technology Malaysia (UTM), Johor. Sampling station were randomly selected at the inlet and outlet of the detention pond. The hydrological parameters such as flow and velocity were also collected. Results: The simulation results showed the maximum probability of occurrence value for observed sediment loads and sediment depth from Ledang Heights were 0.0062 tons (16.5%) and 0.0005 mm (17.5%) respectively. The maximum probability of occurrence values for observed sediment loads and sediment depth at UTM showed no obvious differences with Ledang Heights; about 0.015 tons (16.8%) and 0.00037 mm (15.5%) respectively. The maximum occurrence of predicted sediment loads and sediment depth using MUSLE method for Ledang Height was 77.8 tons (16.8%) and 7.5 mm (26.8%) respectively. The maximum occurrence for UTM was slightly higher, about 264 tons (15.70%) and 7.0 mm (21.10%) respectively. The higher values for UTM were suspected due to its larger watershed. The sediment loads and depths were also predicted for the next 50-100 years considering no significant watershed land use changes. Conclusion: The sediment accumulation estimation and forecasting are very important to ensure the effectiveness and proper operation of the detention pond. The continuous effort through natural sediment control measures such as proper vegetation and grass inplants are always encourage around the detention pond and surrounding areas throughout its lifespan.

American Journal of Environmental Sciences
Volume 8 No. 1, 2012, 25-34

DOI: https://doi.org/10.3844/ajessp.2012.25.34

Submitted On: 23 December 2011 Published On: 30 January 2012

How to Cite: Shamsudin, S., Darom, A. R. M., Mohamad, I. N. & Rahman, A. A. (2012). Detention Pond Sediment Accumulation Prediction using Monte Carlo Simulation. American Journal of Environmental Sciences, 8(1), 25-34. https://doi.org/10.3844/ajessp.2012.25.34

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Keywords

  • Sediemnt loads
  • accumulation
  • Total Suspended Solid (TSS)
  • detention pond
  • Universal Soil Loss Equation (USLE)
  • monte carlo