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Experimental and Numerical Study on Soil-Gas Diffusivity in Pasture Topsoils
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  • Sathira Abeysinghe,
  • Hiruni Amarasinghe,
  • Tharindi Lakshani,
  • Chamindu Deepagoda Thuduwe Kankanamge,
  • Yuan Li,
  • Wei Fu,
  • Ting Yang,
  • Jun Fan,
  • Xiaoyi Ma,
  • Timothy Clough
Sathira Abeysinghe
University of Peradeniya
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Hiruni Amarasinghe
University of Peradeniya
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Tharindi Lakshani
University of Peradeniya
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Chamindu Deepagoda Thuduwe Kankanamge
University of Peradeniya

Corresponding Author:[email protected]

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Yuan Li
College of Pastoral Agriculture Science and Technology,
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Wei Fu
State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau
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Ting Yang
State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau
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Jun Fan
State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau
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Xiaoyi Ma
State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau
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Timothy Clough
Lincoln University, New Zealand
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Abstract

Soil-gas diffusivity plays a fundamental role on diffusion-controlled migration of climate impact gases from different terrestrial ecosystems including managed pasture systems. Soil-gas diffusivity has a strong bearing on soil type/texture and soil structure (e.g., density) and typically shows a depth-dependent behavior in subsurface. This study investigated the gas diffusivity in soils sampled from a managed pasture site at Ambewela, Sri Lanka at 0-5 cm depth range along a downgrading transect. The soils were pre-characterized for particle-size distribution, organic matter content, dry density and particle density. Soil-gas diffusivity was measured using one-chamber diffusion apparatus using N2 and O2 as experimental gases. The measured diffusivity, together with selected intact and repacked soil data from literature, were tested against the existing predictive gas diffusivity models. We used a generalized descriptive parametric two-region model to represent bimodal/two-region behaviour of selected soils which was able to statistically outperform the predictive models for both intact and repacked soils and hence demonstrated its applicability to better characterize site-specific greenhouse gas emissions with useful implications for pasture management.