Probabilistic indicators for soil and groundwater contamination risk assessment

Daniele la Cecilia, Giovanni M. Porta, Fiona H.M. Tang, Monica Riva, Federico Maggi

Research output: Contribution to journalArticleResearchpeer-review

19 Citations (Scopus)

Abstract

Deterministic assessments of whether, when, and where environmental safety thresholds are exceeded by pollutants are often unreliable due to uncertainty stemming from incomplete knowledge of the properties of environmental systems and limited sampling. We present a global sensitivity analysis to rank the contribution of uncertain parameters to the probability, P, of a target quantity to exceed user-defined environmental safety thresholds. To this end, we propose a new index (AMAP) which quantifies the impact of a parameter on P and can be readily employed in probabilistic risk assessment. We apply AMAP, along with existing moment-based sensitivity indices, to quantify the sensitivity of soil and aquifer contamination following herbicide glyphosate (GLP) dispersal to soil hydraulic parameters. Target quantities are GLP and its toxic metabolite aminomethylphosphonic acid (AMPA) concentrations in the top soil as well as their leaching below the root zone. The global sensitivity analysis encompasses six scenarios of managed water amendments and rainfall events. The biodegradation of GLP and AMPA varies slightly across scenarios, while leaching below the root zone is greatly affected by the assumed hydrologic boundary conditions. AMAP shows that, among the tested uncertain parameters, absolute permeability, air-entry suction, and porosity have the greatest impact on GLP and AMPA probability to pollute the aquifer by exceeding the aqueous concentration thresholds. Our results show that AMAP is effective to thoroughly explore time histories arising from model-based predictions of environmental pollution hazards. The proposed methodology may support informed decision making in risk assessments and help assessing ecological indicators through threshold-based analyses.

Original languageEnglish
Article number106424
Number of pages13
JournalEcological Indicators
Volume115
DOIs
Publication statusPublished - Aug 2020
Externally publishedYes

Keywords

  • AMPA
  • Environmental risk assessment
  • Global sensitivity analysis
  • Glyphosate
  • Groundwater
  • Modeling
  • Pollution
  • Soil
  • Uncertainty quantification

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