Factors that influence nitrous oxide emissions from agricultural soils as well as their representation in simulation models: a review

C Wang, B Amon, K Schulz, B Mehdi - Agronomy, 2021 - mdpi.com
Nitrous oxide (N2O) is a long-lived greenhouse gas that contributes to global warming.
Emissions of N2O mainly stem from agricultural soils. This review highlights the principal …

Diurnal variability in soil nitrous oxide emissions is a widespread phenomenon

YF Wu, J Whitaker, S Toet, A Bradley… - Global Change …, 2021 - Wiley Online Library
Manual measurements of nitrous oxide (N2O) emissions with static chambers are commonly
practised. However, they generally do not consider the diurnal variability of N2O flux, and …

Machine learning for predicting greenhouse gas emissions from agricultural soils

A Hamrani, A Akbarzadeh, CA Madramootoo - Science of The Total …, 2020 - Elsevier
Abstract Machine learning (ML) models are increasingly used to study complex
environmental phenomena with high variability in time and space. In this study, the potential …

Linking climate change and socioeconomic development to urban land use simulation: Analysis of their concurrent effects on carbon storage

H Yang, J Huang, D Liu - Applied Geography, 2020 - Elsevier
Land use/cover change (LUCC) in the context of rapid urbanization process has exerted
profound influences on carbon storage and ecosystem functions. Exploring the relationships …

Wastewater treatment and reuse in urban agriculture: exploring the food, energy, water, and health nexus in Hyderabad, India

L Miller-Robbie, A Ramaswami… - Environmental …, 2017 - iopscience.iop.org
Nutrients and water found in domestic treated wastewater are valuable and can be reutilized
in urban agriculture as a potential strategy to provide communities with access to fresh …

Assessment of Advanced Machine and Deep Learning Approaches for Predicting CO2 Emissions from Agricultural Lands: Insights Across Diverse Agroclimatic Zones

E Harsányi, M Mirzaei, S Arshad, F Alsilibe… - Earth Systems and …, 2024 - Springer
Prediction of carbon dioxide (CO2) emissions from agricultural soil is vital for efficient and
strategic mitigating practices and achieving climate smart agriculture. This study aimed to …

[HTML][HTML] KGML-ag: a modeling framework of knowledge-guided machine learning to simulate agroecosystems: a case study of estimating NO emission using data …

L Liu, S Xu, J Tang, K Guan, TJ Griffis… - Geoscientific model …, 2022 - gmd.copernicus.org
Agricultural nitrous oxide (N 2 O) emission accounts for a non-trivial fraction of global
greenhouse gas (GHG) budget. To date, estimating N 2 O fluxes from cropland remains a …

[HTML][HTML] Prediction of carbon dioxide emissions from Atlantic Canadian potato fields using advanced hybridized machine learning algorithms–Nexus of field data and …

M Hassan, K Khosravi, AA Farooque, TJ Esau… - Smart Agricultural …, 2024 - Elsevier
In this study, three novel machine learning algorithms of additive regression-random forest
(AR-RF), Iterative Classifier Optimizer (ICO-AR-RF), and multi-scheme (MS-RF) were …

Can seasonal soil N mineralisation trends be leveraged to enhance pasture growth?

F Bilotto, MT Harrison, MDA Migliorati… - Science of the total …, 2021 - Elsevier
Background Soil N mineralisation is the process by which organic N is converted into plant-
available forms, while soil N immobilisation is the transformation of inorganic soil N into …

Bayesian calibration of the DayCent ecosystem model to simulate soil organic carbon dynamics and reduce model uncertainty

RB Gurung, SM Ogle, FJ Breidt, SA Williams… - Geoderma, 2020 - Elsevier
Benefits of carbon sequestration in agricultural soils are well recognized, and process-
based models have been developed to better understand sequestration potential. However …