Modelling methane emissions and grain yields for a double-rice system in Southern China with DAYCENT and DNDC models
Yang Guo, Guangbin Zhang, Mohamed Abdalla, Matthias Kuhnert, Haijun Bao, Hua Xu, Jing Ma, Khadiza Begum, Pete Smith
Abstract
Methane (CH4) is an important greenhouse gas that contributes to climate change and one of its major sources is rice cultivation. The main aim of this paper was to compare two well-established biogeochemical models, namely Daily Century (DAYCENT) and DeNitrification-DeComposition (DNDC) for estimating CH4 emissions and grain yields for a double-rice cropping system with tillage practice and/or stubble incorporation in the winter fallow season in Southern China. Both models were calibrated and validated using field measured data from November 2008 to November 2014. The calibrated models performed effectively in estimating the daily CH4 emission pattern (correlation coefficient, r = 0.58–0.63, p < 0.001), but model efficiency (EF) values were higher in stubble incorporation treatments, with and without winter tillage (treatments S and WS) (EF = 0.22–0.28) than that in winter tillage without stubble incorporation treatment (W) (EF = −0.06–0.08). We recommend that algorithms for the impacts of tillage practice on CH4 emission should be improved for both models. DAYCENT and DNDC also estimated rice yields for all treatments without a significant bias. Our results showed that tillage practice in the winter fallow season (treatments WS and W) significantly decreased annual CH4 emissions, by 13–37 % (p < 0.05) for measured values, 15–20 % (p < 0.05) for DAYCENT-simulated values, and 12–32 % (p < 0.05) for DNDC-simulated values, respectively, compared to no-till practice (treatments S), but had no significant impact on grain yields.