Kamde Shivanand1*, Ghosh PK2 and Gupta MK3
1Research Scholar, Bhilai Institute of Technology, Durg, Chhattisgarh, India
2Principal, Krishna Engineering College, Bhilai, Chhattisgarh, India
3Professor and Head, Department of Civil Engineering, Bhilai Institute of Technology, Durg, Chhattisgarh, India
*Corresponding Author: Kamde Shivanand, Research Scholar, Bhilai Institute of Technology, Durg, Chhattisgarh, India.
Received: March 08, 2021; Published: May 06, 2021
Citation: Kamde Shivanand., et al. “Landfill Leachate Management Using Modelling”. Acta Scientific Agriculture 5.6 (2021): 11-14.
Most landfills are unengineered in the country; therefore it is difficult to manage municipal solid waste, with respect to collection, transportation, disposal, composting and leachate treatment. This paper attempted to focus on various leachate modelling being used in leachate management to control over various characteristics found in leachate generated. Some important models, studied here are HELP model, LPI, water Balance model (wBm), Deterministic Multiple Linear Reservoir model (DMLRm), Stochastic Multiple Linear Reservoir model (SMLRm), Leachate Generate (LG) prototype model. In this paper experimental analytical and mathematic model have also been considered. Most of the models performed under certain conditions and bounded to limits. The results of modelling studies showed that they provided specific value of specific parameters which is not viable. A prototype leachate generated model which is based on layer theory, using Gomutra as a simulator was found to be effective, economic, ease to manage. The results revealed that the effects of Gomutra to control pH value, temperature, moisture content ratio of BOD/COD, C/N ratio and other minerals was found to be positive; which would helpful to prevent contamination of surface water and enhances, soil conditions growth of plants successfully.
Keywords: MSW; Leachate Generated (LG); Leachate Management; HELP; SMLRM; DMLRM; BOD; COD; WBM; EPIC; UNSAT-H; HYDRUS-2D; NPK
Copyright: © 2021 Kamde Shivanand., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.