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SMART(Environmental impact assessment model ) is a soil acidification model developed to estimate the long term chemical changes in soil and soil water in response to changes in atmospheric deposition. This model simulates the concentrations of aluminium (Al), base cations, NH4, sulphate (SO4) and nitrate (NO3) in the soil solution. In SMART most of the geochemical processes are included (weathering, cation exchange, sulphate absorption). However, only a very limited number of biological processes are taken into account. Nutrient cycling processes are not included, but net N-immobilisation is taken into account to include the effect of an increase in the N content in organic matter as a result of high N deposition. Cation exchange, sulphate adsorption, dissolution of carbonates and Al hydroxides are treated as equilibrium reactions. Weathering of base cations and denitrification/nitrification are described as first-order reactions. The SMART2 model is an extension of the dynamic SMART. It includes a complete nutrient cycle and an improved modelling of hydrology. With SMART2 it is possible to calculate nutrient availability, which is, beside pH, input for the Nature Technical Model (NTM) that is able to quantify floristic diversity. SMART and SMART2 consist of a set of mass balance equations, describing the soil input-output relationships, and a set of equations describing the rate-limited and equilibrium soil processes.[1]


Typical Model Applications:

  • Predictions of changes in groundwater quality resulting from acidification processes under scenarios of acid deposition
  • Simulation of long-term development in soil water chemistry
  • Prediction of pH and nutrient availability for plant diversity
  • Prediction of C sequestration[1]

Standard Model Specification:

The SMART2 model consists of a set of mass balance equations that describe the soil input-output relationships, and a set of equations that describe a number of rate-limited and equilibrium soil processes, related to soil acidification.

The soil solution chemistry in SMART2 depends solely on the net element input from the atmosphere (the product of deposition and filtering factor) and groundwater, canopy interactions (foliar uptake, foliar exudation), geochemical interactions in the soil and a complete nutrient cycle. Growth of the vegetation and litterfall are modelled by a logistic growth function, which acts as a forcing function.

Nutrient uptake is only limited when there is a shortage in the soil solution. Soil interactions are either described by simple rate-limited (zero-order) reactions or by equilibrium reactions.

SMART2 is a single-layer model that considers the top metre of the soil (roughly equivalent to the root zone).[1]

Dynamic structure:

  • The time step of SMART and SMART2 is one year.

Main Model Results:

  • Soil water composition: aluminium, nitrate, pH, base cations and sulphate.
  • Nutrient availability

Required technical infrastructure:

Windows NT and Windows XP

Structure of Input Data:

SMART2 needs about 25 input parameters for each location it is run. For regional applications of SMART2 the input parameters are needed for each point location in the region it is run. Usually these values are derived from map information such as the soil type and land use maps by ways of pedo-transfer functions. Because of spatial variability of derived parameters within soil and vegetation units as well as uncertainty regarding this spatial variability, these pedo-transfer functions are not typically a one-to-one mapping. They are better characterised as a random field for each soil or vegetation type.[1]

Model Extensions:

In 2002 the model is extended for land use change, which means change from agricultural land use into nature. However, due to lack of data this is just tested for a few locations in the Netherlands.

The model SUMO (Succession Module (Wamelink et al., 2000)) is integrated in SMART2 and replaces the logistic growth function. With SUMO, there is interaction between nutrient availability and growth. Parameterisation is just done for the Netherlands.

Links to other Models, Projects, Networks:

NUCSAM: Nutrient Cycling and Soil Acidification Model MAGIC: Model for Acidification of Groundwater In Catchments MERLIN: Model of Ecosystem Retention and Loss of Inorganic Nitrogen WANDA: Regional nitrogen model With Aggregated Nitrogen DynAmics

Regional Scope:

National scale: Finland, the Netherlands

Continental scale: Europe[1]

See also


  1. 1.0 1.1 1.2 1.3 1.4 JRC: IA TOOLS. Supporting inpact assessment in the European Commission. [1]

Kros, J., E.J. Pebesma, G. J. Reinds, P.A. Finke (1999) Uncertainty in Modelling Soil Acidification at the European Scale, A case study, Journal of Environmental Quality 28/2: 366-377.

Kros, J. (2002), Evaluation of biogeochemical models at local and regional scale. Wageningen, PhD thesis Wageningen University.

Mol-Dijkstra, J.P. and Kros, J. (2001), Modelling effects of acid deposition and climatic change on soil and run-off chemistry at Risdalsheia, Norway. Hydrology and Earth System Sciences, 5:487-498

Wamelink, G.W.W., J.P. Mol-Dijkstra, H.F. van Dobben, J. Kros & F. Berendse (2000), In Dutch. Eerste fase van de ontwikkeling van het successie model SUMO 1; verbetering van de vegetatiemodellering in de Natuurplanner.Wageningen, Alterra, 2000. Alterra-rapport 045, 84 blz.

Wamelink G.W.W., C.J.F. ter Braak and H.F. van Dobben (2003), Changes in large-scale patterns of plant biodiversity predicted from environmental economic. Landscape Ecology scenarios 18 (5): 513-527.

W. de Vries, G.J. Reinds, M. Posch, M. J. Sanz, G.H.M. Krause, V. Calatayud, J.P. Renaud, J.L. Dupouey, H. Sterba, E.M. Vel, M. Dobbertin, P. Gundersen and J.C.H. Voogd (2003), Intensive Monitoring of Forest Ecosystems in Europe, 2003 Technical Report. EC, UN/ECE 2003, Brussels, Geneva, 163 pp.