Pesticide concentrations in soil and surface water at field level

Background

Pesticides are used and released into the European environment. Despite their use is regulated by stringent pre-market evaluation, they create in the environment mixtures of multiple substances with potential to negatively affect soil and aquatic organisms. While the monitoring data are limited, there might be tools developed when pesticide emissions and their distribution in the environment and accumulated levels might be estimated based on existing data on pesticide usage and properties.

When farmers use chemicals to protect their crops, some of the "agrochemicals" can move into soil and nearby rivers. This can happen through wash-off from fields caused by rain, soil erosion by wind or drifting of sprayed product to off-field areas.

The developed modelling framework helps to understand where these chemicals go, how much of them end up in soil and water, and how long they will stay there. This crucial information helps in protecting resources necessary for animal and human well-being.

How it works

We utilized existing data about pesticides (their usage statistics, databases of their properties), crop maps, and other environmental data to estimate how much of each pesticide enters the environment after field application and how much of it then remain in soil and surface water. The tools's final output is a self-contained HTML file allowing end user to screen pesticide concentration levels at two scales, river basin and individual fields and streams. This means the interactive map can be opened in any standard web browser on a computer or mobile device. Users don't need to install any software or have technical expertise. The interactive nature of the map allows end users to zoom in on their own communities or areas of interest and explore the data firsthand.

What it offers

The general public often finds environmental data inaccessible due to its technical nature. Raw datasets, GIS files, and scientific reports can be intimidating. There is a need for tools that can translate this complex information into a format that is easy to understand and can be viewed on common devices without specialized software.

Possible relevance of the tool:

• Identification of potential pollution hotspots: by pinpointing areas where chemicals might be building up.
• Informing better practices: by helping farmers and authorities make decisions that reduce the impact of these chemicals on our environment.
• Communication of environmental data: Visually attractive and informative maps may help disseminate oftentimes inaccessible for broad audience data and educate target audience.

Limitations / Disclaimer

The primary limitation for the general public is the potential for misinterpretation. Without a full understanding of the underlying methodology, a user might misinterpret a high PEC value as an immediate health risk or might not understand that the value is a prediction and not a direct measurement. The aggregated data at the basin level, while useful for a screening of pesticide levels, may not be relevant to the specific conditions of a single field or stream. The static nature of the map also means it's not a real-time screening tool; it reflects the data at a specific point in time. 

Background

Policy makers require clear, concise, and defensible data to inform environmental legislation, manage resources, and justify strategic decisions. However, hardly any monitoring programme can cover the large European area and therefore the modelling and estimating are the available approaches to provide pan-European maps of pesticide environmental concentrations. To fulfil the EU’s goals under the Green Deal and Farm to Fork Strategy, policy-makers and regulators need pan-European view on possible environmental exposure to pesticides to prioritize pesticide reduction strategies.

How it works

The tool directly addresses this need by aggregating the granular stream-level data up to the river basin level. This aggregation provides a strategic, regional overview of the PEC. The interactive map, with its selectable layers, allows a policy maker to first view the broad trends at the basin level and then, if needed, zoom in to see the finer details at the stream level or consult field level static maps for even more detailed picture. This tiered approach to visualization is ideal for high-level decision-making.

What it offers

The implemented model offers a valuable tool for assessing the presence and movement of organic agrochemicals in agricultural topsoil and small rivers. By simulating agrochemical concentrations, it provides crucial insights into how agrochemicals interact with our environment and potential exposure levels for terrestrial and aquatic life.

The model's strength lies in its ability to generate detailed, location-specific estimates of agrochemical concentrations, considering factors such as how and when chemicals are applied, local soil and climate conditions, and river flow. This allows end-users to create tailored scenarios that reflect real-world farming practices. Furthermore, the model can aggregate these detailed findings to provide a broader picture, showing overall agrochemical distribution across regions or entire river basins. This allows policy makers to:

• Target interventions: Identify specific areas or practices that require attention to reduce environmental exposure.
• Inform regulations: Provide data-driven evidence to support the development and refinement of agrochemical use policies.
• Assess risk: Understand the potential risks to biodiversity in both terrestrial and aquatic ecosystems.

Currently model has been applied and evaluated in diverse agricultural landscapes in Czechia, Denmark, Netherlands.

Limitations / Disclaimer

The primary limitation for policy makers is the potential for oversimplification. A single basin-level average may mask significant "hot spots" of high concentration within that basin. Additionally, the temporal scope of a single annual PEC value does not account for acute, short-term risks that could be critically important for regulating specific events, like peak concentrations following a rainfall event. 

Background

Pesticide residues from agricultural fields are often found in soil, nearby surface waters and in surrounding areas leading to potentially adverse environmental effects on terrestrial and aquatic biodiversity if critical pesticide concentrations are exceeded. Mitigation of such negative environmental effects involves reduction of pesticide use, non-chemical alternatives and promotion of the principles of Integrated Pest Management (IPM) in agriculture. In order to evaluate potential adverse outcomes of pesticide and assess effectiveness of mitigating measures the Environmental risk assessment (ERA) is employed. Withing ERA the probability that exposure to one or more pesticides may result in adverse environmental effects is calculated. Scientific models are tools which support ERA of pesticides by calculating the development of pesticide risks in time and evaluating quantitatively risk reduction measures. Such models are necessary to consider the effects of risk mitigation measures by implementing a realistic representation of routes of entry of pesticides to soil and water such as deposition, run-off, erosion, drainage, drift.

Indeed, tools which primary goal is to assess the potential impact of pesticides, by calculating its concentration in both individual fields and streams and at the broader river basin level are needed to make complex environmental information more accessible for risk analysis and communication, bridging the gap between scientific data and practical applications. Such tools are designed to perform environmental modeling and visualization of the Predicted Environmental Concentration (PEC) of an active substance in environmental compartments. The PEC is a crucial metric in environmental risk assessment, as it provides an estimate of the expected concentration of a substance in a given environment. This "predicted" value is used because it is often impractical and cost-prohibitive to measure the actual concentration of a substance in every single water body at all times.

How it works

Pesticide fate model provides a framework for assessing the spatio-temporal distribution of organic agrochemicals in agricultural topsoil and adjacent surface water bodies. Operating on a daily resolution, the model integrates chemical application patterns, physicochemical properties, detailed pedo-climatic data, and river hydrology. This multi-parameter approach allows for site-specific scenario development, reflecting the inherent variability of agricultural landscapes.

The model deterministically calculates time-dependent, geo-referenced PECs at fine scales, specifically individual fields and river segments. These fine-scale outputs can be aggregated to generate frequency distributions or lumped PECs at coarser administrative or geographical units, such as country districts and river basins. This hierarchical output structure facilitates both detailed mechanistic analysis and broader-scale risk assessment.

This framework accounts for key pesticide attenuating processes including plant interception, degradation, sorption, surface runoff depth, terrain slope, and buffer strip efficacy. While exchanges within topsoil are mechanistically derived, empirical relationships inform modules related to surface runoff and spray drift loadings (implemented only for Netherlands).

The resulting PECs serve as a critical input for deriving time-dependent and spatially distributed Risk Quotients (RQs) for relevant terrestrial and aquatic endpoints. The model's application in diverse EU contexts (Czech Republic, Denmark, Netherlands) highlights its adaptability to varied environmental and agricultural settings, providing essential data for both exposure assessment and the refinement of regulatory frameworks.

What it offers

Researchers can easily adapt and use the tool together with supporting information such as model scripts and documentation to simulate PEC of different substances or to study the effects of various scenarios, such as changes in agricultural practices, land-use changes, or climate patterns. For instance, a scientist could modify the script to test a hypothetical scenario where the active substance is replaced with a more biodegradable alternative to see its potential environmental benefit, compare the PEC values between periods to understand the impact of intra annual or month variation in precipitation on concentration, or assess effectiveness of mitigation strategies such as implementation of buffers. This tool allows for the analysis of how local impacts scale up to regional effects, thereby informing further research and providing valuable insights into environmental dynamics. Additionally, a sensitivity analysis can be applied to analyse the impacts of input parameters on total PEC values and on the contribution of different routes of entry, and to single the most important parameters. Such analysis can be used to further direct research to focusing on crucial aspects of the model.

Limitations / Disclaimer

The script and its output are subject to several limitations and uncertainties that should be considered:

• Data Quality: The accuracy of the PEC values is entirely dependent on the quality and resolution of the input data, including stream locations, and basin boundaries. Inaccuracies in the source data, such as outdated stream maps, or incomplete datasets, can lead to misleading PEC values and conclusions. These errors will be propagated through the modeling process and into the final visualization.
• Oversimplification of (Dis)aggregation: The PEC modelling involves aggregation of input data over the river basin with summary statistic method. This may oversimplify complex hydrological processes and granularity of model input data that influence the actual concentration. For example, a simple mean value does not capture the high-resolution variability or potential hotspots that exist within a basin, which can lead to an over- or under-estimation of risk. Likewise, disaggregating input data to smaller spatial units may lead to additional sources of uncertainty.
• Temporal Scope: The script is written to calculate annual PEC values for a specific timeframe (e.g., following a July application). It does not account for continuous, long-term environmental dynamics, seasonal variations, or the effects of specific weather events. A single annual and even monthly value, for instance, might not reflect the peak concentrations that could occur immediately after a heavy rainfall event or the long-term degradation of the substance over time, which could be critical for assessing short-term risks to aquatic life.
• Modeling Assumptions: The model is based on pre-existing formulas constituting SYNOPS Model for synoptic assessment of risk potential of chemical plant protection products. Being an indicator model, it is predominantly used as a screening tool. Thus, the model does not fully account for environmental dynamics or variability in factors such as soil type, runoff rates, topography, or the substance's half-life in soil and water, and therefore limit possible number of environmental scenarios where it can be applied. These assumptions can significantly influence the results, making it difficult to independently verify the findings or compare them to those of other environmental models.