Environinformatics in ecological risk assessment of agroecosystems pollutant leaching

Nazzareno Diodato, Michele Ceccarelli

Research output: Contribution to journalArticle

9 Citations (Scopus)


In this paper, a novel approach for mapping leaching risk at large sub-regional scale under limited information is presented, with acronym environinformatics in ecological risk assessment. The problem consists into quantifying the exchange frequency of the plant available soil water (Narula et al. in J Geogr Inform Decision Anal 7(1)32-46, 2002), this frequency can be adopted as a measure indicating the nutrient and contaminant leaching risk for a site. Our approach is based on integrating soil water balance with spatial analysis tools. However, any decision involved in scientific risk evaluation requires the accurate quantification of the degree of uncertainty arising from sampling, modelling and interpolation errors. The non-parametric geostatistical procedure of Indicator Kriging enables to circumvent this problem by estimating the probability that the true value exceed a set of threshold values. The transformation of leaching data to a binary response variable, known as "indicator", can lead to a soft description of leaching. Such soft description can mitigate the uncertainty in exchange frequency estimates of the plant available soil water. The approach was applied to a test site in Beneventan agroecosystem (South Italy) by using a long-term hydrological water balance acquired in a 40-years period. In this way, about 400 km2 (25%) of the total 2,000 km2 of the Benevento province were classified as areas sensitive to nutrient and contaminant leaching.

Original languageEnglish
Pages (from-to)292-300
Number of pages9
JournalStochastic Environmental Research and Risk Assessment
Issue number4
Publication statusPublished - 1 Oct 2005
Externally publishedYes



  • Geostatistics
  • Pollutant leaching
  • Probability maps
  • Risk assessment
  • Soil-water-balance
  • Southern Italy

ASJC Scopus subject areas

  • Environmental Engineering
  • Environmental Science(all)
  • Environmental Chemistry
  • Water Science and Technology
  • Statistics and Probability
  • Civil and Structural Engineering

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