Modelling pesticides leaching in cropping systems: Effect of uncertainties in climate, agricultural practices, soil and pesticide properties

Lammoglia, Sabine-Karen; Brun, François; Quemar, Thibaud; Moeys, Julien; Barriuso, Enrique; Gabrielle, Benoît; Mamy, Laure

doi:10.1016/j.envsoft.2018.08.007

Cited by 44 publications

(24 citation statements)

References 41 publications

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“…We show the sensitivity of the sustainability indices to the input parameters in Table 4. The input parameters which are expected to have the most uncertainty are the adsorption coefficient and the degradation rate constant [79,80]. Additionally, there may also be significant uncertainty in the drainage, evapotranspiration, and irrigation rates [79,81].…”

Section: Sensitivity Analysismentioning

confidence: 99%

Framework for the Integrated Sustainability Assessment of Irrigation with Marginal Water

Cornelissen

Zee

Leijnse

2021

Water

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The use of marginal water, such as reclaimed wastewater or effluent, for irrigation can reduce the pressure on existing freshwater resources. However, this can cause contaminants to accumulate in compartments such as the soil, crop, air, surface- and groundwater, which may harm the public health and the environment. Environmental quality standards for these compartments are generally considered separately. However, the compartments are related to each other by the fluxes between them, and the concept of sustainability should hold for all compartments simultaneously. An integrated approach is therefore required for the sustainability assessment of irrigation with marginal water. Since such an approach has not been provided yet, we develop an integrated framework in this study. We provide sustainability indicators by comparing the long-term contaminant concentration and fluxes with quality standards for each environmental compartment. These indicators give comprehensible information on which contaminants will cause problems, which environmental compartments are threatened, and on what timescale this will occur. This allows for the prioritization of mitigation and preventive measures for better sustainability management. We illustrate the use of the framework by means of a case study.

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Section: Sensitivity Analysismentioning

confidence: 99%

Framework for the Integrated Sustainability Assessment of Irrigation with Marginal Water

Cornelissen

Zee

Leijnse

2021

Water

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“…The first group applies a systematic sensitivity analysis (SSA) regarding uncertain model parameters, typically referred to as epistemic uncertainty resulting from a lack of knowledge (Uusitalo et al 2015) (e.g., Arndt and Hertel 1997;Valenzuela et al 2007;Beckman et al 2011;Villoria et al 2013;Cho et al 2016). The second group explicitly considers the uncertainties inherent in the input variables, such as the weather, by describing such variables with probability distributions and producing distributions of the model outputs under an input uncertainty (e.g., European Commission 2018; Lammoglia et al 2018; OECD/FAO 2018). The latter group is a type of UA (Loucks and van Beek 2017).…”

Section: Uncertainty In Simulation Modelingmentioning

confidence: 99%

Multiple rotations of Gaussian quadratures: An efficient method for uncertainty analyses in large-scale simulation models

Stepanyan

Grethe

Zimmermann

et al. 2021

Environmental Modelling & Software

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Concerns regarding the impact of climate change, food price volatility, and weather uncertainty have motivated users of simulation models to consider uncertainty in their simulations. One way to do this is to integrate uncertainty components in the model equations, thus turning the model into a problem of numerical integration. Most of these problems do not have analytical solutions, and researchers, therefore, apply numerical approximation methods. This article presents a novel approach to conducting an uncertainty analysis as an alternative to the computationally burdensome Monte Carlo-based (MC) methods. The developed method is based on the degree three Gaussian quadrature (GQ) formulae and is tested using three large-scale simulation models. While a standard single GQ method often produces low-quality approximations, the results of this study demonstrate that the proposed approach reduces the approximation errors by a factor of nine using only 3.4% of the computational effort required by the MC-based methods in the most computationally demanding model.

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“…The most cited research works consider the processing of digital images collected by UAVs as a fundamental tool to get vegetation index. An opportunity in the monitoring and evaluation of crop maps with plant disease detection (Lammoglia et al, 2018;Thomas et al, 2018) to integrate with risk management strategies for help to producers in the generation of guided action plans to solve these undesired effects based on collected data.…”

Section: No Citations Research Topicmentioning

confidence: 99%

Use of unmanned aerial vehicles (UAV) as an innovation in agriculture

Cornejo-Velazquez¹,

Romero-Trejo²,

Acevedo-Sandoval³

et al. 2020

Afr. J. Agric. Res.

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Modelling pesticides leaching in cropping systems: Effect of uncertainties in climate, agricultural practices, soil and pesticide properties

Cited by 44 publications

References 41 publications

Framework for the Integrated Sustainability Assessment of Irrigation with Marginal Water

Framework for the Integrated Sustainability Assessment of Irrigation with Marginal Water

Multiple rotations of Gaussian quadratures: An efficient method for uncertainty analyses in large-scale simulation models

Use of unmanned aerial vehicles (UAV) as an innovation in agriculture

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