Evaluation of the DNDC Model to Estimate Soil Parameters, Crop Yield and Nitrous Oxide Emissions for Alternative Long-Term Multi-Cropping Systems in the North China Plain

Optimizing crop rotations is one of the proposed sustainable management strategies for increasing carbon sequestration. The main aim of this study was to evaluate the DeNitrification-DeComposition (DNDC) model for estimating soil parameters (temperature, moisture and exchangeable NO3− and NH4+), crop yield and nitrous oxide (N2O) emissions for long-term multi-cropping systems in Hebei, China. The model was validated using five years of data of soil parameters, crop yields and N2O emissions. The DNDC model effectively simulated daily soil temperature, cumulative soil nitrogen and crop yields of all crops. It predicted the trends of observed daily N2O emissions and their cumulative values well but overestimated the magnitude of some peaks. However, the model underestimated daily water filled pore space, especially in dry seasons, and had difficulties in correctly estimating daily exchangeable NO3− and NH4+. Both observed and simulated cumulative N2O results showed that optimized and alternative cropping systems used less nitrogen fertiliser, increased grain yield and decreased N2O emissions compared to the conventional cropping system. Our study shows that although the DNDC model (v. 9.5) is not perfect in estimating daily N2O emissions for these long-term multi-cropping systems, it could still be an effective tool for predicting cumulative emissions.

Modeling Nitrous Oxide Emissions From Large-Scale Intensive Cropping Systems in the Southern Amazon

Nitrogen (N) fertilizer use is rapidly intensifying on tropical croplands and has the potential to increase emissions of the greenhouse gas, nitrous oxide (N2O). Since about 2005 Mato Grosso (MT), Brazil has shifted from single-cropped soybeans to double-cropping soybeans with maize, and now produces 1.5% of the world's maize. This production shift required an increase in N fertilization, but the effects on N2O emissions are poorly known. We calibrated the process-oriented biogeochemical DeNitrification-DeComposition (DNDC) model to simulate N2O emissions and crop production from soybean and soybean-maize cropping systems in MT. After model validation with field measurements and adjustments for hydrological properties of tropical soils, regional simulations suggested N2O emissions from soybean-maize cropland increased almost fourfold during 2001–2010, from 1.1 ± 1.1 to 4.1 ± 3.2 Gg 1014 N-N2O. Model sensitivity tests showed that emissions were spatially and seasonably variable and especially sensitive to soil bulk density and carbon content. Meeting future demand for maize using current soybean area in MT might require either (a) intensifying 3.0 million ha of existing single soybean to soybean-maize or (b) increasing N fertilization to ~180 kg N ha−1 on existing 2.3 million ha of soybean-maize area. The latter strategy would release ~35% more N2O than the first. Our modifications of the DNDC model will improve estimates of N2O emissions from agricultural production in MT and other tropical areas, but narrowing model uncertainty will depend on more detailed field measurements and spatial data on soil and cropping management.

Multifactor Effects on the N2O Emissions and Yield of Potato Fields Based on the DNDC Model

Maintaining or increasing grain yields while also reducing the emissions of field agricultural greenhouse gases is an important objective. To explore the multifactor effects of nitrogen fertilizer on nitrous oxide (N2O) emissions and the yield of potato fields and to verify the applicability of the DeNitrification-DeComposition (DNDC) model when used to project the N2O emission load and yield, this research chooses a potato field in Shenyang northeast China from 2017~2019 as the experiment site. The experiment includes four nitrogen levels observed the emission of N2O by static chamber/gas chromatograph techniques. The results of this study are as follows: (1) DNDC has a good performance regarding the projection of N2O emissions and yields. The model efficiency index EFs were 0.45~0.88 for N2O emissions and 0.91, 0.85 and 0.85 for yields from 2017~2019. (2) The annual precipitation, soil organic carbon and soil bulk density had the most significant influence on the accumulated N2O emissions during the growth period of potato. The annual precipitation, annual average temperature and CO2 mass concentration had the most significant influences on yield. (3) Under the premise of a normal water supply, sowing potatoes within 5 days after the 5-day sliding average temperature in this area exceeds 10 °C can ensure the temperature required for the normal growth of potatoes and achieve the purpose of maintaining and increasing yield. (4) The application of 94.5 kg·hm-2 nitrogen and 15 mm irrigation represented the best results for reducing N2O emissions while also maintaining the yield in potato fields.

Research on the sensitivity of parameters and calibrates DNDC model for calculating emissionsfrom paddy rice cultivation activities

This study estimates the sensitivity of parameters to serve the adjustment and construction of standard parameters in the Decomposition - Denitrification (DNDC) model when calculating greenhouse gas emissions from rice cultivation on alluvial, alkali, acid-sulfate, and bleached soils of Red river delta, Vietnam. The research results show that the following parameters: bulk density, clay fraction, microbial activity index, soil organic carbon (SOC), temperature, conductivity, fertilization of urea, and porosity have a high sensitivity for the calculation of CH4 emissions; the following parameters: pH, drainage efficiency, depth of water retention layer, field capacity, initial nitrate and ammonium concentrations at surface soil, and rainfall have low sensitivity and less influence for the calculation of CH4 emissions; the wilt moisture and salinity index have no effect on CH4 emissions. In case of N2O emissions, the following parameters: amount of manure, clay fraction, microbial activity index, pH, initial nitrate concentration at surface soil, bulk density, SOC, field capacity, porosity and depth of water retention layer have a high sensitivity and more influence to N2O emissions; the following parameters: drainage efficiency, conductivity, initial ammonium concentration at surface soil, temperature, fertilisation of urea and rainfall have low sensitivity and less influence to N2O emissions; the wilting point and soil salinity index have no effect on N2O emissions. The results of model calibration show a good correlation between observed and simulated values in both spring and summer crops in 2018. The R2 of the spring and summer crops reach 0.86 and 0.79, the Nash-Sutclitffe efficiency index reaches 0.82 and 0.77 for CH4 emission; meanwhile, for N2O emission, these values are 0.62, 0.69, and 0.76, respectively. The study also found a model calibration parameter used to calculate greenhouse gas emissions from rice cultivation on alluvial, alkali, acid-sulfate, and bleached soils.