N loss indicators (NLIs) are defined according to Buczko and Kuchenbuch (2010a) as environmental management tools for assessing the risk of diffuse N losses from agricultural fields.

They range in complexity from simple proxy variables to elaborate systems of algebraic equations. With reference to the DPSLIR-model, Nitrogen loss indicators may be composed of driving forces, pressure and link indicators. Buczko and Kuchenbuch (2010a) divide the N loss indicators into three main- and 5 sub-groups.

NLIs based on the N source

The amount of nitrogen which is possibly available to nitrogen leaching and other diffuse N losses can be estimated by two different types of approaches: either by calculating a nitrogen budget (=N input/output budget) or by measuring directly the mineral N content in the soil profile, usually immediately before the start of the main leaching period (Nmin-concentration)

NLIs based on transport terms

Other indicators only (or primarily) refer to the transport properties of the soil, the vadose zone and/or the aquifer.

  • Groundwater vulnerability indices: The widely used groundwater vulnerability indices are based on the concept of the ‘‘intrinsic vulnerability’’ of the groundwater and are used independently from the type of contaminant. They are often utilized with respect to vulnerability for diffuse nitrate pollution from agricultural areas.
  • Approaches based on the hydrology of the soil zone: The Exchange frequency of the soil solution within the effective root zone’ (EF) and similar NLIs are based on the hydrology of the soil zone.

Composite NLI approaches

  • Score-based NLIs: An example for a score based NLI is an aquifer vulnerability map, based on the evaluation and scoring of various environmental frame conditions such as presence or absence of a primary aquifer, depth of the groundwater, soil drainage class, recharge available and land use (Ceplecha et al., 2004)

DRASTIC is the most widely used method to evaluate the intrinsic vulnerability not assigned to a specific chemical pollutant as e. g. nitrate. It evaluates the vunerability based on the hydrogeological structures of the site and considers seven factors (Aller et al., 1987):

  1. Depth to groundwater
  2. Recharge (Net)
  3. Aquifer media
  4. Soil media
  5. Topography (slope)
  6. Impact of unsaturated zone media
  7. Conductivity (hydraulic) of aquifer

Pollution potential is rated for each factor: for example, groundwater deeper than 100 m, the rate value is 1 while the depth between 0-5 m rated as 10. The factors are also weighted for their importance. Then, the vulnerability can be assessed by summing up these seven factors.

  • Model-type NLIs: simple equation: Simple equations to estimate nitrate leaching were used by De Jong et al. (2007) in Canada: the authors combindes the amount of residual soil nitrogen, estimated from the annual nitrogen budget with an estimation of nitrate leaching using a simplified water balance.
  • Model-type NLIs, complex approaches: Furter information on the single models can be found in the comprehensive review of Buczko and Kuchenbuch (2010a).

Buczo and Kuchenbuch (2010a) summarised their review as follows:

  • NLIs developed from the “agricultural viewpoint” are usually restricted to the soil zone (what corresponds to the driving force and pressure ADWIs within the DPSLIR-framework in the FAIRWAY project) and estimate the N losses that leave the root zone. The fate of diffuse nitrogen losses – and their impact on the environment, are very much influenced by the properties of the unsaturated (vadose) zone beneath the root zone (thickness, hydraulic conductivity, texture, organic matter content) and the aquifer). The autors conclude, that it is not sufficient to estimate the amount of N that leaves the root zone alone (this is the reason why we introduce the Link indicator for the DPSLIR-framework).
  • The authors criticise a lack of calibration and validation of the NLIs against field data.
  • As each NLI is using another scaling, a comparison between them is hampered.
  • Especially composite NLIs show – related to the number of single components and their weighting – a low relative sensitivity for changing conditions.

Cannova et al. (2008) compiled a review on the modelling of N dynamics in order to assess environmental impact of cropped soils. The spacial scale of most of the models discussed (51 of 62 models studied) was the field scale, followed by the watershed scale (6 models) and the farm scale (4 models). Most of the models operating at farm and watershed scale are indicators.


Go To Top