Validity of agroecosystem models a comparison of results of different models applied to the same data set

Scenario analysis using the Daisy model to assess and mitigate nitrate leaching from complex agro-environmental settings in Denmark

Nitrate (N) leaching from intensively managed cropping systems is of environmental concern and it varies at local scale. To evaluate the performance of agricultural practices at this scale, there is a need to develop comprehensive assessments of N leaching and the N leaching reduction potential of mitigation measures. A model-based analysis was performed to (i) estimate N leaching from Danish cropping systems, representing 20 crop rotations, 3 soil types, 2 climates and 3-4 levels of manure (slurry)-to-fertilizer ratios, but with same available N (according to regulatory N fertilization norms), and (ii) appraise mitigation potential of on-farm measures (i.e. catch crops, early sowing of winter cereals) to reduce N leaching. The analysis was performed using a process-based agro-environmental model (Daisy). Simulated average N leaching over 24 years ranged from 16 to 85 kg N/ha/y for different crop rotations. Rotations with a higher proportion of spring crops were more prone to leaching than rotations having a higher proportion of winter cereals and semi-perennial grass-clover leys. N leaching decreased with increasing soil clay content under all conditions. The effect of two climates (different regions, mainly differing in precipitation) on N leaching was generally similar, with slight variation across rotations. Supplying a part of the available N as manure-N resulted in similar N leaching as mineral fertilizer N alone during the simulation period. Among the mitigation measures, both undersown and autumn sown catch crops were effective. Effectiveness of measures also depended on their place and frequency of occurrence in a rotation. Adopting catch crops during the most leaching-prone years and with higher frequency were effective choices. This analysis provided essential data-driven knowledge on N leaching risk, and potential of leaching reduction options. These results can serve as a supplementary guiding-tool for farmers to plan management practices, and for legislators to design farm-specific regulatory measures.

Crop Model Parameterisation of Three Important Pearl Millet Varieties for Improved Water Use and Yield Estimation

Pearl millet is an important crop for food security in Asia and Africa’s arid and semi-arid regions. It is widely grown as a staple cereal grain for human consumption and livestock fodder. Mechanistic crop growth and water balance models are useful to forecast crop production and water use. However, very few studies have been devoted to the development of the model parameters needed for such simulations for pearl millet. The objectives of the study were to determine crop-specific model parameters for each of three pearl millet varieties (landrace, hybrid, and improved), as well as to calibrate and validate the Soil Water Balance (SWB) model for predicting pearl millet production and water use based on weather data. The SWB was chosen because it is widely used in southern Africa; however, the developed parameters should benefit other models as well. The presented crop-specific parameter values were derived from field observations and literature. Varieties with different phenology, maturity dates and tillering habits were grown under well-watered and well-fertilised conditions for calibration purposes. The calibrated model was used to predict biomass production, grain yield and crop water use. The hybrid’s water use efficiency was higher than that of the landrace and improved variety.

Simulation of Soil Organic Carbon Effects on Long-Term Winter Wheat (Triticum aestivum) Production Under Varying Fertilizer Inputs

Soil organic carbon (SOC) has a vital role to enhance agricultural productivity and for mitigation of climate change. To quantify SOC effects on productivity, process models serve as a robust tool to keep track of multiple plant and soil factors and their interactions affecting SOC dynamics. We used soil-plant-atmospheric model viz. DAISY, to assess effects of SOC on nitrogen (N) supply and plant available water (PAW) under varying N fertilizer rates in winter wheat (Triticum aestivum) in Denmark. The study objective was assessment of SOC effects on winter wheat grain and aboveground biomass accumulation at three SOC levels (low: 0.7% SOC; reference: 1.3% SOC; and high: 2% SOC) with five nitrogen rates (0-200 kg N ha^-1) and PAW at low, reference, and high SOC levels. The three SOC levels had significant effects on grain yields and aboveground biomass accumulation at only 0-100 kg N ha^-1 and the SOC effects decreased with increasing N rates until no effects at 150-200 kg N ha^-1. PAW had significant positive correlation with SOC content, with high SOC retaining higher PAW compared to low and reference SOC. The mean PAW and SOC correlation was given by PAW% = 1.0073 × SOC% + 15.641. For the 0.7-2% SOC range, the PAW increase was small with no significant effects on grain yields and aboveground biomass accumulation. The higher winter wheat grain and aboveground biomass was attributed to higher N supply in N deficient wheat production system. Our study suggested that building SOC enhances agronomic productivity at only 0-100 kg N ha^-1. Maintenance of SOC stock will require regular replenishment of SOC, to compensate for the mineralization process degrading SOC over time. Hence, management can maximize realization of SOC benefits by building up SOC and maintaining N rates in the range 0-100 kg N ha^-1, to reduce the off-farm N losses depending on the environmental zones, land use and the production system.

Using a map-based assessment tool for the development of cost-effective WFD river basin action programmes in a changing climate

For the 2nd and 3rd river basin management cycles (2015-2027) of the Water Framework Directive (WFD), EU Member States are required to fully integrate climate change into the process of river basin management planning (RBMP). Complying with the main WFD objective of achieving 'good ecological status' in all water bodies in Denmark requires Programmes of Measures (PoMs) to reduce nitrogen (N) pollution from point and diffuse sources. Denmark is among the world's most intensively farmed countries and in spite of thirty years of significant policy actions to reduce diffuse nutrient emissions, there is still a need for further reductions. In addition, the impacts of climate change are projected to lead to a situation where nutrient loads will have to be reduced still further in comparison to current climate conditions. There is an urgent need to address this challenge in WFD action programmes in order to develop robust and cost-effective adaptation strategies for the next WFD RBMP cycles. The aim of this paper is to demonstrate and discuss how a map-based PoMs assessment tool can support the development of adaptive and cost-effective strategies to reduce N losses in the Isefjord and Roskilde Fjord River Basin in the north east of Denmark. The tool facilitates assessments of the application of agri-environmental measures that are targeted towards low retention agricultural areas, where limited or no surface and subsurface N reduction takes place. Effects of climate change on nitrate leaching were evaluated using the dynamic agro-ecosystem model 'Daisy'. Results show that nitrate leaching rates increase by approx. 25% under current management practices. This impact outweighs the expected total N reduction effect of Baseline 2015 and the first RBMP in the case study river basin. The particular PoMs investigated in our study show that WFD N reduction targets can be achieved by targeted land use changes on approx. 4% of the agricultural area under current climate conditions and approx. 9% of the agricultural area, when projected climate change impacts on nitrate leaching rates are included in the assessment. The study highlights the potential of the PoMs assessment tool to assist in evaluation of alternative WFD RBMP scenarios to achieve spatially targeted and cost-effective reductions of N loads at catchment scale in the context of a changing climate.

Linking climate change mitigation and coastal eutrophication management through biogas technology: Evidence from a new Danish bioenergy concept

The interest in sustainable bioenergy solutions has gained great importance in Europe due to the need to reduce GHG emissions and to meet environmental policy targets, not least for the protection of groundwater and surface water quality. In the Municipality of Solrød in Denmark, a novel bioenergy concept for anaerobic co-digestion of food industry residues, manure and beach-cast seaweed has been developed and tested in order to quantify the potential for synergies between climate change mitigation and coastal eutrophication management in the Køge Bay catchment. The biogas plant, currently under construction, was designed to handle an annual input of up to 200,000 t of biomass based on four main fractions: pectin wastes, carrageenan wastes, manure and beach-cast seaweed. This paper describes how this bioenergy concept can contribute to strengthening the linkages between climate change mitigation strategies and Water Framework Directive (WFD) action planning. Our assessments of the projected biogas plant indicate an annual reduction of GHG emissions of approx. 40,000 t CO2 equivalents, corresponding to approx. 1/3 of current total GHG emissions in the Municipality of Solrød. In addition, nitrogen and phosphorous loads to Køge Bay are estimated to be reduced by approx. 63 t yr.(-1) and 9 tyr.(-1), respectively, contributing to the achievement of more than 70% of the nutrient reduction target set for Køge Bay in the first WFD river basin management plan. This study shows that anaerobic co-digestion of the specific food industry residues, pig manure and beach-cast seaweed is feasible and that there is a very significant, cost-effective GHG and nutrient loading mitigation potential for this bioenergy concept. Our research demonstrates how an integrated planning process where considerations about the total environment are integrated into the design and decision processes can support the development of this kind of holistic bioenergy solutions.

Performance assessment of nitrate leaching models for highly vulnerable soils used in low-input farming based on lysimeter data

The agricultural sector faces the challenge of ensuring food security without an excessive burden on the environment. Simulation models provide excellent instruments for researchers to gain more insight into relevant processes and best agricultural practices and provide tools for planners for decision making support. The extent to which models are capable of reliable extrapolation and prediction is important for exploring new farming systems or assessing the impacts of future land and climate changes. A performance assessment was conducted by testing six detailed state-of-the-art models for simulation of nitrate leaching (ARMOSA, COUPMODEL, DAISY, EPIC, SIMWASER/STOTRASIM, SWAP/ANIMO) for lysimeter data of the Wagna experimental field station in Eastern Austria, where the soil is highly vulnerable to nitrate leaching. Three consecutive phases were distinguished to gain insight in the predictive power of the models: 1) a blind test for 2005-2008 in which only soil hydraulic characteristics, meteorological data and information about the agricultural management were accessible; 2) a calibration for the same period in which essential information on field observations was additionally available to the modellers; and 3) a validation for 2009-2011 with the corresponding type of data available as for the blind test. A set of statistical metrics (mean absolute error, root mean squared error, index of agreement, model efficiency, root relative squared error, Pearson's linear correlation coefficient) was applied for testing the results and comparing the models. None of the models performed good for all of the statistical metrics. Models designed for nitrate leaching in high-input farming systems had difficulties in accurately predicting leaching in low-input farming systems that are strongly influenced by the retention of nitrogen in catch crops and nitrogen fixation by legumes. An accurate calibration does not guarantee a good predictive power of the model. Nevertheless all models were able to identify years and crops with high- and low-leaching rates.

How do various maize crop models vary in their responses to climate change factors?

Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2 ], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha(-1) per °C. Doubling [CO2 ] from 360 to 720 μmol mol(-1) increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2 ] among models. Model responses to temperature and [CO2 ] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.

Spatially distributed lateral nitrate transport at the catchment scale

In river catchments, N transformation and storage processes during lateral transport are important in controlling N loads of surface waters. There is a lack of approaches which capture lateral flows and associated N transformation in a spatially distributed way. The aim of this paper is to develop a new conceptual N transport and transformation model which simulates the lateral nitrate transport in subsurface flow from the source area to the receiving water body. The developed tool is based on the object modeling system (OMS) framework and consists of the analytical spatially distributed hydrological model J2000, the nitrate recharge model Meta Candy and a new groundwater N routing component. Nitrate degradation in groundwater is calculated stoichiometrically according to a predefined amount on oxidizable substrate. The new modeling approach was tested in a small agricultural lower mountain range catchment of Thuringia, Germany. The calibration of the N model using a 4-yr period showed reasonable results for nitrate load calculations with a Nash and Sutcliff coefficient of 0.78. The 3-yr validation period produced Nash-Sutcliff (NS) values of 0.75. There was a clear relationship of the goodness-of-fit between the hydrological simulations and the nitrate concentration calculations. Due to short residence times of the interflow nitrate degradation was restricted to slow base flow components. The new approach can be used to target N source areas within a catchment and assess the impact of these source areas on the N load of surface waters in a spatially distributed manner.

Impact of selected agricultural management options on the reduction of nitrogen loads in three representative meso scale catchments in Central Germany

Nitrogen inputs into surface waters from diffuse sources are still unduly high and the assessment of mitigation measures is associated with large uncertainties. The objective of this paper is to investigate selected agricultural management scenarios on nitrogen loads and to assess the impact of differing catchment characteristics in central Germany. A new modelling approach, which simulates spatially distributed N-transport and transformation processes in soil and groundwater, was applied to three meso scale catchments with strongly deviating climate, soil and topography conditions. The approach uses the integrated modelling framework JAMS to link an agro-ecosystem, a rainfall-runoff and a groundwater nitrogen transport model. Different agricultural management measures with deviating levels of acceptance were analysed in the three study catchments. N-leaching rates in all three catchments varied with soil type, the lowest leaching rates being obtained for loess soil catchment (18.5 kg nitrate N ha(-1) yr(-1)) and the highest for the sandy soils catchment (41.2 kg nitrate N ha(-1) yr(-1)). The simulated baseflow nitrogen concentrations varied between the catchments from 1 to 6 mg N l(-1), reflecting the nitrogen reduction capacity of the subsurfaces. The management scenarios showed that the highest N leaching reduction could be achieved by good site-adapted agricultural management options. Nitrogen retention in the subsurface did not alter the ranking of the management scenarios calculated as losses from the soil zone. The reduction effect depended strongly on site specific conditions, especially climate, soil variety and the regional formation of the crop rotations.

Modeling nitrate fluxes at the catchment scale using the integrated tool CAWAQS

Nitrates fluxes in the Grand Morin basin (1200 km(2)), that is subjected to intense agricultural pressure, are considered using in-stream observations (around 250 sampling days over 5 years) and physically based simulations using the CAWAQS model (CAtchment WAter Quality Simulator). In-stream nitrate concentration averaged 6 mg N L(-1), increasing by approximately 0.2 mg N L(-1) yr(-1) around this value (period 1991-1996). Our results show that, over the period of 1991-1996, the differences between in-stream observed nitrate concentrations and simulated nitrate concentrations result from nitrate losses at the basin scale. These losses are due to denitrification by transfer through wetlands, alluvial plains, the hyporheic zone, and by benthic processes in rivers. A mean annual mass balance at the basin scale indicates that 40% of the infiltration flux (3360 kg N km(-2) yr(-1)) is removed from the system via the river network, 40% is stored in aquifers and 20% is lost by denitrification (period 1991-1996).

Life cycle modelling of environmental impacts of application of processed organic municipal solid waste on agricultural land (EASEWASTE)

A model capable of quantifying the potential environmental impacts of agricultural application of composted or anaerobically digested source-separated organic municipal solid waste (MSW) is presented. In addition to the direct impacts, the model accounts for savings by avoiding the production and use of commercial fertilizers. The model is part of a larger model, Environmental Assessment of Solid Waste Systems and Technology (EASEWASTE), developed as a decision-support model, focusing on assessment of alternative waste management options. The environmental impacts of the land application of processed organic waste are quantified by emission coefficients referring to the composition of the processed waste and related to specific crop rotation as well as soil type. The model contains several default parameters based on literature data, field experiments and modelling by the agro-ecosystem model, Daisy. All data can be modified by the user allowing application of the model to other situations. A case study including four scenarios was performed to illustrate the use of the model. One tonne of nitrogen in composted and anaerobically digested MSW was applied as fertilizer to loamy and sandy soil at a plant farm in western Denmark. Application of the processed organic waste mainly affected the environmental impact categories global warming (0.4-0.7 PE), acidification (-0.06 (saving)-1.6 PE), nutrient enrichment (-1.0 (saving)-3.1 PE), and toxicity. The main contributors to these categories were nitrous oxide formation (global warming), ammonia volatilization (acidification and nutrient enrichment), nitrate losses (nutrient enrichment and groundwater contamination), and heavy metal input to soil (toxicity potentials). The local agricultural conditions as well as the composition of the processed MSW showed large influence on the environmental impacts. A range of benefits, mainly related to improved soil quality from long-term application of the processed organic waste, could not be generally quantified with respect to the chosen life cycle assessment impact categories and were therefore not included in the model. These effects should be considered in conjunction with the results of the life cycle assessment.

Simulation of water flow and nitrogen transport for a Bulgarian experimental plot using SWAP and ANIMO models

Unsaturated zone models are useful tools in predicting effects of measures and can be used to optimise agricultural practice aiming to minimise the impact on the environment. However, current soil models have a varying degree of abstraction level referring to simulated processes in time and space. In the framework of an EU funded project the SWAP (Soil-Water-Atmosphere-Plant) and ANIMO (Agricultural-Nutrient-Model) models were tested for an experimental arable plot in Bulgaria. SWAP was used to simulate water flow in the soil while ANIMO describes nitrogen movement and transformations. The objectives of this study are: (i) to show results of the combined application of water and nitrogen dynamics of originally Dutch models SWAP and ANIMO for specific Bulgarian soil and hydrological conditions; (ii) to calibrate and evaluate SWAP and ANIMO models by comparing numerical results with field measurements collected for an arable field in western Bulgaria and (iii) to analyse possible contamination of groundwater due to agricultural practice in the considered region. Further a short description of the experimental plot, as well as information about parameters of the investigated soil profiles, is provided. The obtained SWAP results evidenced that the model gives sufficient adaptation for soil water dynamics. The simulations of ANIMO for nitrogen cycle show greater divergence with observations but are satisfactory precise for the purposes of assessing land use impact on groundwater quality. In general, differences between model results and field measurements do not exceed 10-15%. For the experimental plot predictions indicate nitrate-N concentrations less then 5 mg/l in deeper soil compartments and low downward annual flux containing 0.133 kg N/ha. These results indicate that there is no serious pollution of the shallow groundwater table by nitrogen resulting from land use and agricultural activities.

Parameterisation, evaluation and comparison of pesticide leaching models to data from a Bologna field site, Italy

Effective prediction of pesticide fate using mathematical models requires good process descriptions in the models and good choice of parameter values by the user. This paper examines the ability of seven pesticide leaching models (LEACHP, MACRO, PELMO, PESTLA, PLM, PRZM and VARLEACH) to describe an arable field environment where sunflowers are grown in the Po Valley, northern Italy. Two pesticides were considered, aclonifen and ethoprophos. The models were evaluated in terms of their ability to reproduce field data of soil water content and pesticide residues in the soil and ground water. The evaluation was based on a combination of calibrated and uncalibrated runs. The results from the models were compared with each other to explore the differences between the models. The models varied in their ability to predict soil water content in the summer: the capacity models PRZM, PELMO and VARLEACH predicted less drying than MACRO, PESTLA, PLM and LEACHP. The models varied in their ability to simulate the persistence of the pesticides in the soil. Differences in the simulated pesticide degradation rate were observed between the models, due to variations in the simulated soil water content and soil temperature, and also differences in the equation linking degradation rate to soil water content. There were large differences among the predictions of the models for the mean leaching depth of ethoprophos. PRZM, PELMO, PESTLA and LEACHP all showed similar mean leaching depth to each other, whereas VARLEACH predicted lower ethoprophos mobility and PLM and MACRO predicted greater mobility. All the models overpredicted dispersion of ethoprophos through the soil profile, as compared to the field data. None of the models was able to simulate the field data of rapid leaching of pesticide to ground water except PLM after calibration of the percentage of macropores in the mobile pore space. More work is required in the parameterisation of macropore flow for those models that include this process.

Calibration of pesticide leaching models: critical review and guidance for reporting

Calibration of pesticide leaching models may be undertaken to evaluate the ability of models to simulate experimental data, to assist in their parameterisation where values for input parameters are difficult to determine experimentally, to determine values for specific model inputs (e.g. sorption and degradation parameters) and to allow extrapolations to be carried out. Although calibration of leaching models is a critical phase in the assessment of pesticide exposure, lack of guidance means that calibration procedures default to the modeller. This may result in different calibration and extrapolation results for different individuals depending on the procedures used, and thus may influence decisions regarding the placement of crop-protection products on the market. A number of issues are discussed in this paper including data requirements and assessment of data quality, the selection of a model and parameters for performing calibration, the use of automated calibration techniques as opposed to more traditional trial-and-error approaches, difficulties in the comparison of simulated and measured data, differences in calibration procedures, and the assessment of parameter values derived by calibration. Guidelines for the reporting of calibration activities within the scope of pesticide registration are proposed.