- Tolib Berdiyev
Head of Laboratories Biogeochemistry, Research Institute of Soil Science and Agrochemistry, Tashkent, Uzbekistan.
gosniipa@gmail.com 0000-0001-6488-8350 - Rana Warid Maya
Mazaya University College, Nasiriyah, Dhi Qar, Iraq.
ranawarid14@gmail.com 0000-0002-3986-1989 - Munisa Urmanova
Associate Professor, Tashkent State Agrarian University, Uzbekistan.
munisa.urmanova@mail.ru 0009-0000-2949-7338 - Ramy R. Hussein
Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University, Najaf, Iraq; Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University of Al Diwaniyah, Al Diwaniyah, Iraq.
eng.ramy_riad@iunajaf.edu.iq 0009-0006-1833-5353 - Dilnavoza Burkhanova
Associate Professor, Tashkent State Agrarian University, Uzbekistan.
d.burxanova77@mail.ru 0009-0001-5786-6767 - Dr. Srishti Singh Chauhan
Assistant Professor, Department of Biotechnology, Kalinga University, Naya Raipur, Chhattisgarh, India.
ku.srishtisinghchauhan@kalingauniversity.ac.in 0009-0001-3116-2016
Volume 10 - No: 3
Carbon and Nitrogen Flux Simulation Using the DNDC (Denitrification-Decomposition) Model in Temperate Soils
DOI: 10.28978/nesciences.1811120
Keywords: DNDC model, carbon flux, nitrogen cycling, temperate soils, greenhouse gas emissions, soil modelling, sustainable agriculture.
Abstract
Sustainability: The sustainability of ecosystem services, greenhouse gas emissions, and soil fertility in temperate soils requires knowledge of their carbon (C) and nitrogen (N) fluxes. The biogeochemical model of decomposition, which is process-based and also known as Nitrification, denitrification, and plant-soil processes, incorporates both washout processes and interactions to represent these fluxes. This study is based on the DNDC model of carbon fluxes in temperate soils. It evaluates its performance in monitoring variations in soil organic carbon, CO2, N2O emissions, and nitrate leaching, compared with various land management approaches. The field data were used to verify the model simulations, and the findings revealed excellent agreement, indicating the model's potential as a decision-support tool for studies of agronomic practice sustainability and environmental impact. These findings highlight the availability of precise inputs based on the location, calibration to increase reliability in the simulation, application of regional mitigation strategies, and change of strategies to steer changes in the targeted land-use paths.