Forecasting leachate generation from pilot woodchip stockpiles using a three-dimensional transient flow model

Matthew T. Amato, Daniel Giménez, Sarat Kannepalli, Peter F. Strom, Uta Krogmann, Robert J. Miskewitz

Research output: Contribution to journalArticle

Abstract

Leachate generation from open stockpiles of recycled woodchip materials is potentially harmful to aquatic ecosystems. There is growing interest in using numerical models to simulate leachate generation from outdoor piles, but this requires information about the hydraulic properties of the materials. The objectives of this study were to simulate leachate from woodchip piles with the numerical model HYDRUS-3D and to optimize subsets of parameters for single (SPM) and dual (DPM) pore flow models with the Bayesian Markov Chain Monte Carlo algorithm DREAMZS. Three experimental piles, each approximately 30 m3, were setup with mixtures of either once (coarse) or twice (fine) ground woodchips. Leachate continuously collected over a period of six months was similar across piles. As a result, subsets of optimized flow parameters for the coarse and fine woodchips were not different. Leachate predictions by the two pore flow models were similar and agreed reasonably with the field measurements, as indicated by Nash-Sutcliffe efficiency values greater than 0.6. This result suggests the simpler SPM is adequate for field predictions of leachate. However, leachate was consistently under-predicted by both pore models by 13–27% during rainfall events with more than 1 cm in 6 h. The optimized flow models can be used as a tool for studying pile management strategies.

Original languageEnglish (US)
Article number110379
JournalJournal of Environmental Management
Volume262
DOIs
StatePublished - May 15 2020

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All Science Journal Classification (ASJC) codes

  • Environmental Engineering
  • Waste Management and Disposal
  • Management, Monitoring, Policy and Law

Keywords

  • Hydrological modeling
  • Leachate collection
  • Parameter optimization
  • Recycling
  • Stormwater management
  • Urban wood

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