Comparison Efficiency of DNDC and DAYCENT Models in Sensitivity Analysis of Greenhouse Gases Estimation

Emission of greenhouse gases and their effects on global warming is one of the most serious challenges facing developed and developing countries. Examining emissions of greenhouse gases from different countries makes it possible to determine share of countries in greenhouse gas emissions. This article tries to estimate growth rate of methane, oxidantrose and oxidantric gases, as well as the amount of global warming potential in agricultural lands of Khuzestan by using DAYCENT and DNDC models.

Initially, emissions were measured in rice, wheat, and sugarcane fields using a static chamber, gas chromatography to measure methane and APNA-370 analyzer for nitrous oxide and nitric oxide. DAYCENT and DNDC models were used to estimate and model gas emissions.

Based on results data from two models, DAYCENT and DNDC, the highest amount of methane flux modeled at Baghmalek station was 1.369 and 1.094 tonnes of CO2 equivalent per hectare per year, respectively, the highest rate of nitrous oxide modeling at Shushtar station was 0.160 and 0.988 tonnes of CO2 equivalent per hectare per year, respectively. The highest global warming potential was determined based on observational data at Baghmalek station (55.074 tonnes of CO2 equivalent per hectare per year) and based on DAYCENT data at Shush station (68.059 tonnes of CO2 equivalent per hectare per year) and based on DNDC data in Shush station (47.06 tonnes of CO2 equivalent per hectare per year).

According to the statistical indicators both models showed acceptable accuracy in estimating greenhouse gases.