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Comparison between prediction models and monitored data on leachate generation from a sanitary landfill in the metropolitan region of rio de janeiro, Brazil


International Journal of Hydrology
Michelle Bellas Romariz Gaudie Ley,1 Ricardo Abranches Felix Cardoso Junior,2 Henrique Vieira de Mendonça,3 Alexandre Lioi Nascentes,4 Leonardo Duarte Batista da Silva5

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Abstract

Estimating leachate generation during a landfill lifespan is a key issue in reducing its potential risk. Hence, a useful tool is represented by empirical and computational models. In order to ratify the applicability of the Swiss Method, most applied tool in Brazil, and the Hydrologic Evaluation of Landfill Performance (HELP), most utilized in USA, the present article carried out a case study in the São Gonçalo Waste Treatment Center (CTRSG), located in a humid subtropical climate. Firstly, climate data were collected with Brazil’s National Institute of Meteorology, and landfill structural and operational data were assembled with the company responsible for CTR-SG’ management, Foxx-Haztec, from 2014 to 2018. Subsequently, simulations were conducted on both tools, which indicated that: Swiss Method and HELP do not consider relevant variables for leachate prediction, such as: waste composition and moisture content, organic matter decomposition and dumping methods; thus, these techniques results vary mainly according to annual precipitation, landfill surface area and, for HELP, covering layer thickness. In addition, it was verified that the models forecasted approximately half of the actual volume of generated leachate. In this bias, despite the requirement of few and generally known parameters, these are not reliable tools for assertive prediction. Furthermore, it was found that the Swiss Method employs an imprecise variable, the compaction coefficient, which made pertinent the proposal of a new coefficient, suitable to tropical regions, which should be validated in other landfill scenarios.

Keywords

data science, mathematical models, simulation software, climate data, Swiss method, HELP

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