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QMRAcatch: Microbial Quality Simulation of Water Resources including Infection Risk Assessment

  • National Institute of Public Health and the Environment

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

Given the complex hydrologic dynamics of water catchments and conflicts between nature protection and public water supply, models may help to understand catchment dynamics and evaluate contamination scenarios and may support best environmental practices and water safety management. A catchment model can be an educative tool for investigating water quality and for communication between parties with different interests in the catchment. This article introduces an interactive computational tool, QMRAcatch, that was developed to simulate concentrations in water resources of , a human-associated microbial source tracking (MST) marker, enterovirus, norovirus, , and as target microorganisms and viruses (TMVs). The model domain encompasses a main river with wastewater discharges and a floodplain with a floodplain river. Diffuse agricultural sources of TMVs that discharge into the main river are not included in this stage of development. The floodplain river is fed by the main river and may flood the plain. Discharged TMVs in the river are subject to dilution and temperature-dependent degradation. River travel times are calculated using the Manning-Gauckler-Strickler formula. Fecal deposits from wildlife, birds, and visitors in the floodplain are resuspended in flood water, runoff to the floodplain river, or infiltrate groundwater. Fecal indicator and MST marker data facilitate calibration. Infection risks from exposure to the pathogenic TMVs by swimming or drinking water consumption are calculated, and the required pathogen removal by treatment to meet a health-based quality target can be determined. Applicability of QMRAcatch is demonstrated by calibrating the tool for a study site at the River Danube near Vienna, Austria, using field TMV data, including a sensitivity analysis and evaluation of the model outcomes.

Original languageEnglish
Pages (from-to)1491-1502
Number of pages12
JournalJournal of Environmental Quality
Volume44
Issue number5
DOIs
Publication statusPublished - Sept 2015

Bibliographical note

Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 6 - Clean Water and Sanitation
    SDG 6 Clean Water and Sanitation

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