Validation and evaluation of the DNDC model to simulate soil water content, mineral N and N2O emission in the North China Plain

Using measured datasets (various soil properties, the soil water content, daily N2O emissions, and different crop parameters) from a multi-factorial field experiment (N fertilisation, irrigation, and straw removal) in the years 1999-2002 on the experimental site Dong Bei Wang (DBW) in the North China Plain (NCP), the ability of the process-oriented model DNDC (DeNitrification-DeComposition) was tested to simulate soil processes, and especially N2O trace gas emissions. The soil is classified as ?calcaric cambisol? (16 % clay content), while the site itself is further characterised by the regime of a continental monsoon climate. The central hypothesis in this work was that a thorough testing of the model (using a considerable range of different datasets) will allow the identification of shortcomings or discrepancies in the model, and that, given the linear succession of model calculation steps, the model calculation can be improved step by step, starting with improvements of initial calculation steps before continuing the improvement of following calculation steps. Due to increases in the N2O atmospheric concentration, and a lifetime of 100 to 150 years for one molecule (as well as a global warming potential 32 times that of a CO2 molecule), N2O is estimated to account for 7.9 % of the global warming potential. 70 % ? 90 % of the anthropogenic N2O emissions are thought to origin from agriculture. The formation of nitrous oxide is dependent on the availability of reactive nitrogen, and, therefore, mainly influenced by the N fertilisation rate, fertiliser type, application timing and method. China, and the main cropping area NCP, are expected to contribute considerably to the anthropogenic N2O emissions. The DNDC model consists of two compartments, which first calculate soil temperature, moisture, pH, redox potential and substrate concentration profiles from climate, soil, vegetation and anthropogenic activity datasets, and in a second step NO, N2O, CH4 and NH3 fluxes. In accordance with the data availability, the simulation of the soil water content, the mineral nitrogen concentration, and the N2O fluxes were investigated. An automated parameter optimisation (using the software UCODE_2005) and programmed changes in the source code were conducted to improve the model simulations. In result, neither the automated parameter optimisations, nor the programmed changes, were able to improve the unsatisfying default simulations of the DNDC model. The results of the cascade model, employed by the DNDC model to simulate soil water dynamics, suggest that conceptual errors exist in the model calculation. Also the results of the mineral nitrogen and N2O emissions simulations suggest shortcomings in the model calculation. The best agreement between measured and simulated total cumulative N2O fluxes was achieved using an adapted (90 cm soil depth, adjusted SOC fractioning, and added atmospheric N deposition) default model version, despite unsatisfactory simulations of soil water content, mineral nitrogen, and daily N2O fluxes. Thus, in conclusion, the investigated DNDC model version appears to be able to give an approximation of seasonal N2O fluxes, without being able to simulate the underlying processes accurately in detail. Therefore, caution is suggested when modelling sites on the process level.Die Messergebnisse (generelle Bodenparameter, Bodenwassergehalt, tägliche N2O Emissionen, sowie verschiedene Pflanzenparameter) eines multifaktoriellen Feldversuchs (Stickstoffdüngung, Bewässerung und die Entfernung von Getreidestroh nach der Ernte) in den Jahren 1999-2002, erstellt auf der Versuchsfläche Dong Bei Wang in der Nordchinesischen Tiefebene, wurden verwendet um die Genauigkeit des Prozess-orientierten Simulationsmodells DNDC (DeNitrification-DeComposition) zu untersuchen. In diesem Sinne standen die Simulation von Bodenprozessen, und insbesondere die Simulation von N2O Treibhausgas-Emissionen, im Mittelpunkt der Arbeit. Der Boden der Versuchsfläche ist klassifiziert als ?kalkiger Cambisol? (16% Tongehalt), eine weitere charakteristische Eigenschaft des untersuchten Bodens ist der Einfluss des kontinentalen Monsun-Klimas. Zentrale Hypothese der Arbeit war, dass die schrittweise Verbesserung einzelner (möglicherweise) fehlerhafter Kalkulationsschritte es erlauben würde, am Ende eine Übereinstimmung zwischen simulierten und gemessenen Bodenprozess-Datensätzen zu erzielen. Der Anstieg der atmosphärischen N2O Konzentration, die geschätzte Lebensdauer von 100 bis 150 Jahren eines N2O Moleküls (und einem Treibhauspotential, welches das 32-fache des Treibhauspotentials eines CO2 Moleküls beträgt), führen zu der Schätzung dass N2O Emissionen für ca. 7.9 % des gesamten Treibhauspotentials verantwortlich sind. Es wird erwartet das 70 % ? 90 % dieser N2O Emissionen aus der Landwirtschaft stammen. Die Menge des emittierten N2Os wird bestimmt durch die Verfügbarkeit von reaktiven Stickstoffverbindungen, und ist damit abhängig von Stickstoff-Düngemengen, Düngertyp, Ausbringungstermin und ?methode. China gilt, und hier insbesondere das Hauptanbaugebiet Nordchinesische Tiefebene, als eine der Hauptquellen menschlich verursachter N2O Emissionen. Das DNDC model besteht aus zwei Teilen, in denen zuerst (aus Eingabewerten von Wetter, Boden, Vegetation und menschlichen Aktivitäten) Bodentemperatur, Bodenfeuchtigkeit, den pH Wert, das Boden Redox Potential, sowie Substratkonzentrationen im Bodenprofil, und in einem zweiten Schritt NO, N2O, CH4 und NH3 Flüsse berechnet werden. In Übereinstimmung mit der Datenverfügbarkeit wurden die Simulation des Bodenwassergehalts, des Stickstoffhaushalts und der N2O Flüsse überprüft. Eine automatisierte Parameter Optimierung (mit Hilfe der Software UCODE_2005) und programmierte Änderungen im DNDC Quellcode wurden genutzt um die Modellsimulationen zu verbessern. Im Ergebnis führten aber weder die automatisierte Parameter Optimierung, noch die programmierten Änderung zu einer Verbesserung der unzulänglichen Simulationsergebnisse des DNDC Modells. Die Resultate des Kaskaden-Modell, welches im DNDC Modell für die Simulation des Bodenwasserhaushalts zuständig ist, legen die Existenz grundlegender Fehler in der Berechnung nahe. Die Resultate der Simulation des Stickstoffhaushalts und der N2O Emissionen deuten ebenfalls auf Unzulänglichkeiten in der Modellberechnung. Die beste Übereinstimmung zwischen gemessenen und simulierten saisonalen N2O Emissionsraten wurde mit einer adaptierten DNDC Version erreicht (90 cm Bodentiefe, angepasste Fraktionierung des organischen Kohlenstoffgehalts und hinzugefügter atmosphärischer Stickstoffablagerung), allerdings basierend auf einer äußerst ungenauen Simulation des Bodenwassergehalts, des Stickstoffhaushalts und der täglichen N2O Emissionen. Deswegen muss geschlussfolgert werden, dass das Modell nicht in der Lage ist die Bodenprozesse auf dem Untersuchungsstandort detailgetreu nachzustellen, und dass Vorsicht geboten ist wenn das Modell zur Simulation der Bodenprozesse anderer Standorte eingesetzt wird. Es bleibt allerdings die Möglichkeit, das DNDC Modell zur Simulation von saisonalen N2O Emissionsraten in hypothetischen Situationen und zur Berechnung von regionalen N2O Emissionsraten zu verwenden

Greenhouse Gas Emissions from Canadian Agriculture: Policies and Reduction Measures

Despite numerous national and international climate conferences, meetingsand workshops leading to various greenhouse gas (GHG) emission targets and agreements since the 1970s, total GHG emissions in Canada continue to increase. They reached 729 megatonnes of carbon dioxide equivalent (Mt CO2 eq) in 2018, with the Canadian agricultural sector contributing approximately 10 per cent of total GHGs emitted. Different regions of the country contribute different levels, face different challenges and have different capacities to address their GHG emissions. Designing climate guidelines, programs, policies and adopting best management practices (BMPs) that promote relevant local and regional adaptation and mitigation efforts is important. Mechanisms such as setting a carbon price, cap- and-trade systems and tax-based policies contribute to decreased GHG emissions. GHG emissions in Canada are regulated at the federal level via a national carbon pricing policy and provinces have set limitations on GHG emissions via pricing or taxation. Agriculture has the potential to mitigate GHG emissions by applying BMPs that reduce emissions and increase carbon storage in soils. Meanwhile, the pressure is increasing on the agricultural sector to increase production, both for local commodities and those destined for export, to feed a growing population. This paper explores agricultural policies and measures that encourage farmers and producers across Canada to reduce their GHG emissions. Specifically, national and provincial measures and implications are presented and compared to international measures and outcomes. Finally, recommendations are made for future climate policy research and adoption

Greenhouse Gas Emissions from Canadian Agriculture: Estimates and Measurements

Greenhouse gases (GHGs) cause the warming of the planet’s surface. Although this warming is vital for life on Earth, accelerated surface temperature rises due to increased GHGs in the atmosphere result in increasing atmospheric energy and rates of evaporation, causing unpredictable weather patterns and more intense weather events. The main GHGs are carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Of the 729 Megatonnes (Mt) of CO2 equivalent (CO2 eq) emitted by GHGs in Canada in 2018, 59 Mt were emitted by the agricultural sector in the form of CO2, N2O and CH4. The largest GHG emissions come from CH4 through enteric fermentation of beef and dairy cattle. Most N2O emissions come from agricultural soils through direct and indirect releases into the atmosphere. Carbon dioxide was also emitted after lime and urea applications as well as with the use of fossil fuel combustion machinery. Field techniques and empirical and process models have been developed to estimate and validate GHG emissions for different farm scenarios. These models aim to simulate every component of a farming system, whether a large beef cattle operation or a small animal and crop farm. Consequently, the models are constantly being assessed and revised as more data are available and methodologies are improved. As we gain better understanding of agricultural GHG emission estimates for different farm scenarios, the next step is to target emission sources and find ways to decrease emissions while maintaining or improving the financial sustainability of the farm and production system

Simulation of actual evapotranspiration from agricultural landscapes in the Canadian Prairies

Study region: This study was carried out in southwestern Manitoba, in the prairie region of Canada. Study focus: Mathematical models are routinely used to estimate evapotranspiration (ET) when measurements are lacking. This study was conducted to select the most relevant models for estimating ET in the Canadian Prairies. Eight reference ET models (i.e., Penman-Monteith, Priestley-Taylor, Makkink, Turc, Maulé et al., Blaney-Criddle, Hargreaves-Samani, and Hamon models) were evaluated. This study also assessed the applicability and transferability of the growing degree day (GDD)-based crop coefficients for estimating crop ET in the Canadian Prairies. New hydrological insights: The equation developed by Maulé et al. (2006) was found to be the best reference ET alternative to the Penman-Monteith equation with a mean relative error of 11%. However, when models were validated against measured crop ET, the simpler radiation-based Turc and Makkink models were found to be the most useful models with daily mean relative errors ranging from 16% to 49%, outperforming the widely accepted Penman-Monteith model. Discrepancies in the GDD-based crop coefficients were found to also contribute to errors; however, results show the potential transferability of GDD-based coefficients across different locations and climatic conditions

Effect of Increasing Species Diversity and Grazing Management on Pasture Productivity, Animal Performance, and Soil Carbon Sequestration of Re-Established Pasture in Canadian Prairie

The objective of the study was to determine the effect of type of pasture mix and grazing management on pasture productivity, animal response and soil organic carbon (SOC) level. Pasture was established in 2001 on 16 paddocks of 2.1 ha that had been primarily in wheat and summer fallow. Treatments consisted of a completely randomized experimental design with two replicates: two pasture mixes (7-species (7-mix) and 12-species (12-mix)) and two grazing systems (continuous grazing (CG) and deferred-rotational grazing (DRG)). Pasture was stocked with commercial yearling Angus steers (Bos Taurus, 354 ± 13 kg) between 2005 and 2014. All pastures were grazed to an average utilization rate of 50% (40% to 60%). Average peak and pre-grazing pasture dry matter (DM) yield and animal response were independent of pasture seed mixture but varied with grazing management and production year. Average peak DM yield was 26.4% higher (p = 0.0003) for pasture under DRG relative to CG (1301 kg ha−1). However, total digestible nutrient for pasture under DRG was 4% lower (p < 0.0001) as compared to CG (60.2%). Average daily weight gain was 18% higher (p = 0.017) for CG than DRG (0.81 kg d−1), likely related to higher pasture quality under CG. Soil carbon sequestration was affected by seed mixture × grazing system interaction (p ≤ 0.004). Over the fourteen years of production, pasture with 7-mix under CG had the lowest (p < 0.01) average SOC stock at 15 cm (24.5 Mg ha−1) and 30 cm depth (42.3 Mg ha−1). Overall, the results from our study implied that increasing species diversity for pasture managed under CG may increase SOC gain while improving animal productivity

Estimating enteric methane production for beef cattle using empirical prediction models compared with IPCC Tier 2 methodology

The IPCC (2006), Tier 2 methodology and 16 empirical models together with dietary information were used to estimate daily Methane (CH4) production and Ym (CH4 energy expressed as a percentage of gross energy intake) for mature cows (lactating, dry) and growing steers (backgrounding, grazing, finishing) in Eastern and Western Canada. Monthly simulations accounted for changes in body weight, feed intake and diet composition. Coefficient of variation (CV) and uncertainty (95% confidence interval divided by mean) were used to estimate variability. Estimates of CH4 (g d-1) and Ym from models differed from IPCC estimates. For models, the CV of Ym ranged from 0.8 to 29.7% and uncertainty from 0.9 to 45.2% over the production phases of the animals in contrast to the fixed Ym used by IPCC. When information on diet composition is lacking, a Ym value of 7.0 to 7.3% can be used for beef cows depending on stage and location, and 6.4 to 6.6% for growing cattle fed high forage diets, while 4.8% is recommended for finishing diets instead of the default values of 6.5% for high forage diets and 3.0% for finishing diets typically used in the IPCC Tier 2 method.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Demonstrating the Effect of Forage Source on the Carbon Footprint of a Canadian Dairy Farm Using Whole-Systems Analysis and the Holos Model: Alfalfa Silage vs. Corn Silage

Before recommending a feeding strategy for greenhouse gas (GHG) mitigation, it is important to conduct a holistic assessment of all related emissions, including from those arising from feed production, digestion of these feeds, managing the resulting manure, and other on-farm production processes and inputs. Using a whole-systems approach, the Holos model, and experimentally measured data, this study compares the effects of alfalfa silage- versus corn silage-based diets on GHG estimates in a simulated Canadian dairy production system. When all emissions and sources are accounted for, the differences between the two forage systems in terms of overall net GHG emissions were minimal. Utilizing the functional units of milk, meat, and total energy in food products generated by the system, the comparison demonstrates very little difference between the two silage production systems. However, the corn silage system generated 8% fewer emissions per kg of protein in food products as compared to the alfalfa silage system. Exploratory analysis of the impact of the two silage systems on soil carbon showed alfalfa silage has greater potential to store carbon in the soil. This study reinforces the need to utilize a whole-systems approach to investigate the interrelated effects of management choices. Reported GHG reduction factors cannot be simply combined additively because the interwoven effects of management choices cascade through the entire system, sometimes with counter-intuitive outcomes. It is necessary to apply this whole-systems approach before implementing changes in management intended to reduce GHG emissions and improve sustainability

Optimization of yield and water-use of different cropping systems for sustainable groundwater use in North China Plain

A groundwater crisis is going on in the North China Plain (NCP), due to the excessive water consumption of the traditional winter wheat (WW)/summer maize (SM) double cropping system (two harvests in one year). In order to improve the water use efficiency in this particular cropping system and to evaluate the sustainability of water usage in Chinese agroecosystems, two field experiments were conducted from October 2004 to September 2006 at two sites of the North China Plain. The field experiments included four treatments: (1) farmers' practice (FP) with two harvests in one year (WW/SM rotation), (2) FP with reduced input (RI) of water and nitrogen (WW/SM rotation), (3) three harvests in two years (TW, 1st year: WW/SM; 2nd year: spring maize), and (4) continuous spring-maize monoculture (CS) with one harvest per year (spring maize). In the treatments RI, TW and CS, the amount and timing of irrigation and nitrogen fertilization was optimized using TDR based soil moisture measurements and the Nmin-method, respectively. Data showed that the utilization efficiency of irrigation water can be improved by optimizing soil water management compared to the traditional water management (FP). However, the groundwater net consumption required for RI still surpassed 300 mm yr-1. Both FP and RI, still overused groundwater resources. The groundwater consumption in the continuous spring maize (CS) was on average 139 mm yr-1. Therefore, the CS system can show the potential to use groundwater sustainably in the long term. Water usage of the TW treatment was in between the water usage of the other treatments. The grain yields in the double cropping systems (FP and RI) were higher than that in the two other systems (TW and CS). But the CS treatment showed the higher WUE than others.Groundwater balance Double cropping systems Irrigation water utilization efficiency North China Plain

Deriving Canada-wide soils dataset for use in Soil and Water Assessment Tool (SWAT)

The objective of this work was to pre-process the Soil Landscapes of Canada (SLC) database to offer a country-level soils dataset in a format ready to be used in SWAT simulations. A two-level screening process was used to identify critical information required by SWAT and to remove records with information that could not be calculated or estimated. Out of the 14,063 unique soils in the SLC, 11,838 soils with complete information were included in the dataset presented here. Soils with missing records for the required SWAT variables were removed from the analysis. These soils were compiled into a soils list provided as a reference ("incomplete" dataset)

Effect of changes in management practices and animal performance on ammonia emissions from Canadian beef production in 1981 as compared to 2011

The present study compared ammonia (NH3) emissions from Canadian beef production in 1981–2011. Temporal and regional differences in cattle categories, feed types and management systems, average daily gains, carcass weights, and manure handling practices were considered. A scenario-based sensitivity analysis in 2011 estimated the impact of substituting corn dried distillers’ grains with solubles (DDGS) for grain in feedlot diets. On average, 22% of the total nitrogen (N) intake was lost as ammoniacal nitrogen (NH3-N) in both years. Manure emission sources were consistent across years, averaging 12%, 40%, 28%, and 21% for grazing, confinement, storage, and land spreading, respectively. Emissions per animal in 1981 and 2011 were 16.0 and 18.4 kg NH3 animal−1 yr−1, respectively. On an intensity basis, kilogram of NH3 emitted per kilogram of beef decreased 20%, from 0.17 in 1981 to 0.14 in 2011. This reduction was attributed to increases in reproductive efficiency, average daily gain and carcass weight, and improved breeding herd productivity. In 2011, substituting DDGS for grain in feedlot diets increased total NH3 emissions and losses per animal. Although addition of by-products from the bioethanol industry can lower diet costs, it will be at the expense of an increase in NH3 emissions.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author