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Showing 2 results for Monte Carlo Simulation
Predicting Nitrate Concentration in Groundwater Resources using Lumped-Parameter Model: Case Study in Qazvin Plain
R.s Hajimirmohammad Ali, H Karyab,
Volume 8, Issue 4 (3-2016)
Abstract

Background and Objective: The concentration of nitrate, factors affecting the balance sheet, and the changes in an aquifer is of utmost importance. Because modeling is an efficient method to predict the concentration of ions in water resources, in this study using lumped-parameter model and Monte Carlo simulation model, the nitrate concentrations in groundwater resources of Qazvin Plain were estimated and analyzed.

Materials and Methods: A total of 19 wells in different climates of saline watershed in Qazvin Plain were selected and entry and exit routes of nitrate to these sources were analyzed using lumped-parameter model.  Finally, Monte Carlo simulation was used to determine the probability of the estimated nitrate concentration in aquifer.

Results: Application of lumped-parameter model for a part of a part of groundwater resources in Qazvin Plain watershed predicted the nitrate concentration in the range of 8.12 to 15.94 mg/l.   The maximum concentration was estimated in cold-dry climate with 12.8±0.04 mg/L. Moreover, it was found that the difference between the estimated nitrate concentration and factors affecting its concentration in different climates was significant (p<0.05).

Conclusion: Despite the predicted concentrations of nitrate in the study area were in accordance with the Iran national standard for drinking purposes, the cumulative probability of Monte Carlo simulation showed that the possible violation of nitrate from the safe limit of 10 mg/l in the study area is 90% (p = 0.005).


Uncertainty analysis of a mass balance model to estimate the rate of aerobic processes in municipal solid waste landfills
R Rafiee, M Moeinaddini, N Khorasani,
Volume 11, Issue 1 (6-2018)
Abstract
Background and Objective: The aim of this study was to assess the sensitivity and uncertainty analysis of a mass balance model to estimate the rate of aerobic processes in a landfill.
Materials and Methods: Monte Carlo simulation is a common method to evaluate uncertainty of the results of a model. Here, we used a Monte Carlo (MC) simulation. The data obtained from the experiments were used as a baseline. Considering a uniform Probability Distribution Function (PDF) within ±15% deviation, samples were taken from the baseline data. Using randomly selected inputs, model was executed for 1000 iterations and outputs were evaluated. Then, the total Sobol index for each input parameter was determined. The uncertainty of each output was presented by standard error and means observed in MC simulation. 
Results: The results of this study revealed that while the uncertainty for the rate of composting process was mainly originated from the measured value of CO2 flux, the evaluated value for the rate of anaerobic digestion process was highly influenced by the value measured for CH4 emission flux. All inputs contributed equally to the uncertainty in the evaluated values for the rate of methane oxidation process. Although a variability of 15% was assumed for the model inputs, the mean value for the outputs from Monto Carlo simulations were close to those obtained by using base values that were in most cases within ±10% limit.
Conclusion: The majority of the uncertainty in the outputs came from the variability in the measurement of the flux of CH4 and CO2. The error in these parameters, however, can be minimized by increasing frequency and replicates of gas samples as these parameters are measured directly for each location.

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