H. Kros

Approaches and uncertainties in nutrient budgets: implications for nutrient management and environmental policies

Nutrient budgets of agroecosystems are constructed either (i) to increase the understanding of nutrient cycling, (ii) as performance indicator and awareness raiser in nutrient management and environmental policy, or (iii) as regulating policy instrument to enforce a certain nutrient management policy in practice. This paper explores nutrient budgeting approaches and summarizes sources of uncertainty associated with these approaches. Possible implications of uncertainties associated with the different methodologies and approaches for nutrient management and environmental policy are discussed. Three types of nutrient budgets have been distinguished, i.e. farm-gate, soil surface and soil systems budgets. A farm-gate budget is the most integrative measure of environmental pressure, and seems most suitable as environmental performance indicator. A soil surface budget is appropriate for estimating the net loading of the soil with nutrients. Soil system budgets account for nutrient inputs and outputs, recycling of nutrients within the system, nutrient loss pathways and changes in soil nutrient pools; it is the most detailed budget and provides detailed information for nutrient management. Case studies for the dairy farm De Marke indicate that the three budgeting approaches supplement each other. The accuracy and precision of the nutrient budget depend on budgeting approach, data acquisition strategy and type of agroecosystem. There is often a considerable amount of uncertainty in the nutrient budget, due to various possible biases and errors, notably in the partitioning of nutrient losses. Possible sources of biases are personal bias, sampling bias, measurement bias, data manipulation bias and fraud. Sources of errors are sampling and measurement errors. Both biases and errors in nutrient budget estimates may lead to confusion and wrong conclusions. Yet, there is little published evidence that uncertainties are taken into account in decision making. Uncertainties are usually smaller for a farm-gate budget than for a soil surface budget. Therefore, farm-gate budgets are preferred over soil surface budgets as policy instrument. Quantifying uncertainties requires: (a) system identification and analysis, (b) classification of uncertainties, (c) specification of distributions of probabilities of the various sources using Monte Carlo simulation, and (d) monitoring of the nutrient pools, inputs and outputs over time. Analyses of uncertainties in nutrient budgets may provide information about the weakest chain in establishing agri-environmental cause–effect relationships and, therefore, may assist to better focus research efforts. Data for the nitrogen budget of The Netherlands indicate relatively large uncertainties for the items denitrification and leaching, with coefficients of variation >30%. In conclusion, there is a need for standard procedures and guidelines in nutrient budgeting and uncertainty analyses, to improve the confidence in and applicability of nutrient budgets.

Uncertainties in the fate of nitrogen I: an overview of sources of uncertainty illustrated with a Dutch case study.

This study focuses on the uncertainties in the ‘fate’ of nitrogen (N) in the Netherlands. Nitrogen inputs into the Netherlands in products, by rivers, and by atmospheric deposition, and microbial and industrial fixation of atmospheric N2 amount to about 4450 Gg N y−1. About 60% of this N is transported out of the Netherlands in products. The fate of the remaining 40%, however, is less clear. We discuss uncertainties in losses to the atmosphere (as ammonia or through denitrification), by leaching and runoff, and in N accumulation in biomass and soils. These processes may account for the fate of about 40% of the N in the Netherlands, and for the fate of about 60% of the N in Dutch agricultural soils. Reducing uncertainties in the estimates of these fluxes is necessary for reducing the impact of excess N in the environment. In particular, monitoring the environmental effects of ammonia emissions and nitrate leaching to groundwater and aquatic systems requires an increased understanding of the fate of N. Uncertainties arise because (1) some N fluxes cannot be measured directly and are usually quantified indirectly as the balance in N budgets, (2) direct measurements of N fluxes have inevitable inaccuracies, (3) lack of experimental data and other information (e.g. statistics) needed for upscaling, (4) large spatial and temporal variability of fluxes, and (5) poor understanding of the processes involved. These uncertainties can be reduced by additional experimental studies and by further development of process-based models and N budget studies. We prioritize these future research needs according to a range of different criteria.

An outlook for a national integrated nitrogen policy

Reactive nitrogen in the environment is a current and future major policy issue. Nitrogen pollution and its emissions are difficult to control, because they are associated with two of the most important human needs i.e. food and energy. In the Netherlands, several measures have been taken to decrease emissions with varying success. So far policy has been focussed on individual environmental issues related to specific sources. This paper summarises the results of a study to analyse the nitrogen problem in the Netherlands in an integrated way All relevant aspects are taken into account simultaneously. This was done by deriving regional agricultural nitrogen production ceilings, including all relevant nitrogen flows in agriculture and most relevant effects, i.e. protection of ground and surface water from nitrate pollution and N-eutrophication, controlling NH3 volatilisation in view of impacts on terrestrial ecosystems and reducing NOx and N2O emissions in view of climate change policies. For agriculture, nitrogen ceilings provide a good basis for regulating nitrogen through fertiliser use and feed import. Results show that reactive nitrogen production in the Netherlands should be decreased by 50–70% in order to reach the ceilings necessary to protect the environment against nitrogen pollution from agriculture.

Application of the model NUCSAM to the Solling spruce site

The NUtrient Cycling and Soil Acidification Model (nucsam) was applied to a spruce site at Solling, Germany, within the scope of a workshop on comparison of forest soil atmosphere models. Simulated trends and dynamics in the concentrations of SO4, Al and base cations and in pH between 1970 and 1990 compared favourably with time series of measured data during that period. Dynamics and concentrations of NO3 in the subsoil were overestimated. Simulation results for the period 1990–2090 for two deposition scenarios showed ongoing acidification (pH decrease) of the soil at the present acid load and a rapid response of soil solution chemistry to reduced acid input, but there was a long time delay before favourable AlCa ratios were reached.

Modelling critical loads for the Solling spruce site

Abstract After an introduction to the historical development of the critical load concept, methods for calculating critical loads are presented. Besides empirical relationships three types of models are identified and evaluated: steady-state soil models, dynamic soil models and integrated forest-soil models. Critical load assessments are carried out with examples from each of the three types of models, using data from the Solling spruce site. The resulting critical loads of sulphur obtained with the dynamic and integrated models are close (within 30%) to the steady-state model calculations. For nitrogen, the spread in the model results is wider due to the very different criteria (soil solution chemistry vs. forest vitality) used for deriving the critical loads. This agreement lends confidence to the simplified critical load calculations carried out on a European scale. However, much work remains to be done, both in the modelling efforts and the data collection, before truly integrated forest-soil models can be used for assessing critical loads on a large regional scale.

The Dutch N-cascade in the european perspective.

The Netherlands is “well known” for its nitrogen problems; it has one of the highest reactive nitrogen (Nr) emission densities in the world. It is a small country at the delta of several large European rivers. Ever since the industrial revolution, there has been a growing excess of nutrients and related emissions into the atmosphere (ammonia, nitrogen oxides and nitrous oxide) and into groundwater and surface water (nitrate), leading to a large range of cascading environmental impacts. Vehicular traffic, sewage and animal husbandry are the main sources of oxidized and reduced forms of Nr. This paper provides an overview of the origin and fate of nitrogen in the Netherlands, the various reported impacts of nitrogen, the Dutch and European policies to reduce nitrogen emissions and related impacts. In addition, ways are presented to go forward to potentially solve the problems in a European perspective. Solutions include the improvement of nitrogen efficiencies in different systems, technological options and education.

NitroGenius: A Nitrogen Decision Support System

Abstract A nitrogen decision support system in the form of a game (NitroGenius) was developed for the Second International Nitrogen Conference. The aims were to: i) improve understanding among scientists and policy makers about the complexity of nitrogen pollution problems in an area of intensive agricultural, industrial, and transportation activity (The Netherlands); and ii) search for optimal policy solutions to prevent pollution effects at lowest economic and social costs. NitroGenius includes a model of nitrogen flows at relevant spatial and temporal scales including emissions of ammonia and nitrogen oxides and contamination of surface- and groundwaters. NitroGenius also includes an economic model describing relationships for important sectors and impacts of different nitrogen control measures on Gross Domestic Product (GDP), unemployment, energy use, and environmental costs. About 50 teams played NitroGenius during the Second International Nitrogen Conference. The results show that careful planning and selection of abatement options can solve Dutch nitrogen problems at reasonable cost.

Evaluation of model behaviour with respect to the biogeochemistry at the Solling spruce site

Abstract The performance and predictions of 11 biogeochemical models, applied to time series data from a spruce site in Solling, Germany were evaluated. All models are deterministic, process-oriented models, and represent a wide range of modelling approaches with respect to time and space resolution and complexity. Although process formulations vary, the basic processes are shared by most models. The scope of the models is to calculate soil chemistry characteristics relevant to assess stress factors for forests (e.g. unfavourable high inorganic Al concentrations and Al Ca rations in soil solution) induced by acid deposition. The evaluation showed that the general trends and levels in chemical variables, such as soil solution pH, and concentrations of base cations, SO2−4 and Al, as well as base saturation can be reproduced by the models. Most models are incapable of modelling correctly pH and Al concentrations simultaneously. Modelling NO−3 concentrations was generally not very successful, despite several complex modelling approaches. The modelling efforts highlighted that the concentrations of base cation, SO2−4 and Ali are coupled in a complex and nonlinear way, which has strong implications for the response to reductions in acid deposition. The rate of chemical weathering obtained by budget studies was supported by the models. The comparison of the models showed that the links between soil chemistry and to forest growth are incomplete. It is recommended to continue to work on certain processes such as Al-chemistry and N transformations, and on the interaction between soil chemical status and biota.

Assessment of Nitrogen Ceilings for Dutch Agricultural Soils to Avoid Adverse Environmental Impacts

In the Netherlands, high traffic density and intensive animal husbandry have led to high emissions of reactive nitrogen (N) into the environment. This leads to a series of environmental impacts, including: (1) nitrate (NO3) contamination of drinking water, (2) eutrophication of freshwater lakes, (3) acidification and biodiversity impacts on terrestrial ecosystems, (4) ozone and particle formation affecting human health, and (5) global climate change induced by emissions of N2O. Measures to control reactive N emissions were, up to now, directed towards those different environmental themes. Here we summarize the results of a study to analyse the agricultural N problem in the Netherlands in an integrated way, which means that all relevant aspects are taken into account simultaneously. A simple N balance model was developed, representing all crucial processes in the N chain, to calculate acceptable N inputs to the farm (so-called N ceiling) and to the soil surface (application in the field) by feed concentrates, organic manure, fertiliser, deposition, and N fixation. The N ceilings were calculated on the basis of critical limits for NO3 concentrations in groundwater, N concentrations in surface water, and ammonia (NH3) emission targets related to the protection of biodiversity of natural areas. Results show that in most parts of the Netherlands, except the western and the northern part, the N ceilings are limited by NH3 emissions, which are derived from critical N loads for nature areas, rather than limits for both ground- and surface water. On the national scale, the N ceiling ranges between 372 and 858 kton year depending on the choice of critical limits. The current N import is 848 kton year. A decrease of nearly 60% is needed to reach the ceilings that are necessary to protect the environment against all adverse impacts of N pollution from agriculture.

Metafore: The Afforest Deposition-Soil-Water-Vegetation Metamodel

This chapter describes the development of the METAFORE metamodel for the AFFOREST project, focusing on aspects that are important in defining the role of the metamodel in the entire system. Two modes are distinguished: one in which the METAFORE metamodel operates in a batch mode for generating the AFFOREST-sDSS tables for decision support, and another mode of operating with an extended user interface and extended possibilities for evaluating detailed results. The various detailed process-based models are from different sources and each of the institutes had experts on the processes that were modelled. From these models, the individual partners developed meta-descriptions of their parts of the system. The task of the METAFORE metamodel was to combine all this knowledge into a single model executable, and assure a correct calculation of the values needed for the AFFOREST database and the AFFOREST-sDSS. The design of the METAFORE distinguishes a metamodel framework and the model components or submodels. The metamodel framework focuses on the interface and communication between the different submodels and it is responsible for the communication between the submodels. In this design, the submodels are merely servers, waiting to be initialized or called to perform one step of the simulation (i.e. one month or one year of the simulation). To do this, each submodel has only a limited set of exposed methods. Although the detailed process models, as part of their scientific development process, have been extensively validated and calibrated, this does not automatically assure a proper simulation of the processes by the metamodel. During the entire process of the development of METAFORE, the simulation behaviour of the METAFORE modules were constantly tested against the detailed process models. In the end, METAFORE has been developed as a simplification of the detailed models with a lesser demand on data. This means that the detailed behaviour in the process models can at best result in similar but aggregated behaviour in the METAFORE metamodel. It is concluded that the results are satisfactory.