RETRACTED ARTICLE: On the prediction of methane fluxes from pristine tropical peatland in Sarawak: application of a denitrification–decomposition (DNDC) model

• Published in: Environmental science and pollution research international Vol. 29; no. 20; pp. 30724 - 30738
• Main Authors: Sa’adi, Zulfaqar, Yaseen, Zaher Mundher, Muhammad, Mohd Khairul Idlan, Iqbal, Zafar
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2022; Springer Nature B.V
• Subjects: Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Earth and Environmental Science; Ecotoxicology; Environment; Environmental Chemistry; Environmental Health; Research Article; Waste Water Technology; Water Management; Water Pollution Control; Relative importance index; DNDC; Sarawak; Tropical peatland; Methane emissions
• ISSN: 0944-1344; 1614-7499
• DOI: 10.1007/s11356-021-17917-1

Tropical peatlands have high potential function as a major source of atmospheric methane (CH 4 ) and can contribute to global warming due to their large soil carbon stock, high groundwater level (GWL), high humidity and high temperature. In this study, a process-based denitrification–decomposition (DNDC) model was used to simulate CH 4 fluxes in a pristine tropical peatland in Sarawak. To test the accuracy of the model, eddy covariance tower datasets were compared. The model was validated for the year 2014, which showed the good performance of the model for simulating CH 4 emissions. The monthly predictive ability of the model was better than the daily predictive ability, with a determination coefficient ( R 2 ) of 0.67, model error (ME) of 2.47, root mean square error (RMSE) of 3.33, mean absolute error (MAE) of 2.92 and mean square error (MSE) of 11.08. The simulated years of 2015 and 2016 showed the good performance of the DNDC model, although under- and overestimations were found during the drier and rainy months. Similarly, the monthly simulations for the year were better than the daily simulations for the year, showing good correlations at R 2 at 0.84 (2015) and 0.87 (2016). Better statistical performance in terms of monthly ME, RMSE, MAE and MSE at − 0.11, 3.38, 3.05 and 11.45 for 2015 and − 1.14, 5.28, 4.93 and 27.83 for 2016, respectively, was also observed. Although the statistical performance of the model simulation for daily average CH 4 fluxes was lower than that of the monthly average, we found that the results for total fluxes agreed well between the observed and the simulated values (E = 6.79% and difference = 3.3%). Principal component analysis (PCA) showed that CH 4 , GWL and rainfall were correlated with each other and explained 41.7% of the total variation. GWL was found to be relatively important in determining the CH 4 fluxes in the naturally inundated pristine tropical peatland. These results suggest that GWL is an essential input variable for the DNDC model for predicting CH 4 fluxes from the pristine tropical peatland in Sarawak on a monthly basis.