Large scale modelling of groundwater contamination from nitrate leaching

Refsgaard, Jens Christian; Thorsen, Mette; Jensen, Jacob Birk; Kleeschulte, S.; Hansen, Søren

doi:10.1016/s0022-1694(99)00081-5

Cited by 151 publications

(74 citation statements)

References 39 publications

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“…For example, it was applied to nutrient modeling at basin scale (Styczen and Storm, 1993), in pesticide simulation (Thorsen et al, 1998), nitrate leaching simulation (Refsgaard et al, 1999), physically based integrated modeling of nitrogen cycle in catchment scale (Hansen et al, 2009), nitrate reduction simulation in a complex geologically heterogeneous region (Refsgaard et al, 2014), phosphorus transport simulation in Everglades National Park (Long et al, 2015), and agrochemical transport simulation in an agriculture area (Kourgialas and Karatzas, 2015). However, compared to a large number of water movement simulations, the number of mass transport and water quality simulations is relatively smaller; this shows that the research and practices of fundamental water movement modeling have not being so numerous and proficient as to sufficiently sustain further research on water quality simulation.…”

Section: Simulation Of Mass Transport and Water Pollutionmentioning

confidence: 99%

Nitrogen and phosphorus transformations and balance in a pond-ditch circulation system for rural polluted water treatment

Huang

et al. 2016

Ecological Engineering

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Section: Simulation Of Mass Transport and Water Pollutionmentioning

confidence: 99%

Nitrogen and phosphorus transformations and balance in a pond-ditch circulation system for rural polluted water treatment

Huang

et al. 2016

Ecological Engineering

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“…Process models aim to simulate the real-world mechanisms of hazard propagation and exposure; perhaps the most common examples are the dispersion models often used to estimate air pollution concentrations (Colvile and Briggs 2000). Similar models are also available, however, for a wide range of other hazards and media, including noise (Heimann 2007; Ploysing 2000; van Maercke and Defrance 2007), electromagnetic radiation (Kürner 2003), stream-water pollution (Rauch et al 1998), groundwater pollution (Refsgaard et al 1999), floods (Horritt and Bates 2002;Lamberti and Pilati 1996), geological hazards (Atkinson and Somerville 1994;Carey and Sparks 1986;Hurst and Turner 1999) and vector-borne and communicable diseases (Anderson and Garnett 2000;Rogers et al 1988). Likewise, demographic models have been developed to simulate both natural population dynamics and local and interregional migration (Cohen 1986;Lee and Tuljapurkar 1994;Newell 1988;van Imhoff and Post 1998).…”

Section: Analytical Uncertaintymentioning

confidence: 99%

Uncertainty in epidemiology and health risk and impact assessment

Briggs

Sabel

Lee

2008

Environ Geochem Health

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Environmental epidemiology and health risk and impact assessment have long grappled with problems of uncertainty in data and their relationships. These uncertainties have become more challenging because of the complex, systemic nature of many of the risks. A clear framework defining and quantifying uncertainty is needed. Three dimensions characterise uncertainty: its nature, its location and its level. In terms of its nature, uncertainty can be both intrinsic and extrinsic. The former reflects the effects of complexity, sparseness and nonlinearity; the latter arises through inadequacies in available observational data, measurement methods, sampling regimes and models. Uncertainty occurs in three locations: conceptualising the problem, analysis and communicating the results. Most attention has been devoted to characterising and quantifying the analysis-a wide range of statistical methods has been developed to estimate analytical uncertainties and model their propagation through the analysis. In complex systemic risks, larger uncertainties may be associated with conceptualisation of the problem and communication of the analytical results, both of which depend on the perspective and viewpoint of the observer. These imply using more participatory approaches to investigation, and more qualitative measures of uncertainty, not only to define uncertainty more inclusively and completely, but also to help those involved better understand the nature of the uncertainties and their practical implications.

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“…A greater ability was achieved in the coupling of process based field scale model DAISY and distributed hydrological model MIKESHE (Abbott et al 1986). The use of MIKESHE/DAISY was limited to vertical transport and groundwater flow modelling for macro pore flow analysis (Refsgaard et al 1999). Similar developments were undertaken in other process based hydrological model such as NMS model, which is a combination of the field-scale nitrogen model EPIC (Jones et al 1991) and the catchment-scale flow and transport modelling system SHETRAN (Abbott et al 1986).…”

mentioning

confidence: 99%

A Sub-Catchment Based Approach for Modelling Nutrient Dynamics and Transport at a River Basin Scale

Alam

Dutta

2016

Water Resour Manage

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The prediction of nutrient pollution at realistic details is difficult due to lack of proper description of inherent processes in modelling tools. To overcome that this study has adopted a process based approach to build a semi-distributed model to simulate nutrient pollution in changing environment. The model was built to describe: (1) nutrient generation process in the catchment with consideration of different aspects of external and internal sources, (2) nutrient release from surface to the waterways via runoff and soil erosion, and (3) in-stream transport and chemical reaction process. The key novelty of this research is the linking of the nutrient generation process with transport mechanism for modelling nutrient dynamics at a basin scale. A flow capacity based approach was introduced to determine nutrient export from catchment to the waterways, which was useful to achieve the high resolution outputs from the model. The model performed reasonably well to represent the behaviour of nutrient in high flow events as well as in seasonal flow in two catchments located in distinct hydro-climatic regions. The study has shown that the nutrient model is suitable for predicting actual nutrient pollution in rivers for both high flow and seasonal flow under different hydro-climatic conditions. By simulating organic and inorganic nutrients separately, the model allows to estimate river water quality status in detail.

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Large scale modelling of groundwater contamination from nitrate leaching

Cited by 151 publications

References 39 publications

Nitrogen and phosphorus transformations and balance in a pond-ditch circulation system for rural polluted water treatment

Nitrogen and phosphorus transformations and balance in a pond-ditch circulation system for rural polluted water treatment

Uncertainty in epidemiology and health risk and impact assessment

A Sub-Catchment Based Approach for Modelling Nutrient Dynamics and Transport at a River Basin Scale

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