Role of modeling uncertainty in the estimation of climate and socioeconomic impact on river water quality. J. of Water Resources Planning and Management – Asce, 138(5), 479–490.

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Climate is one of the most important factors leading to changes in the hydrologic and environmental characteristics of river basins.When considering water quality, the natural factors should be weighed against anthropogenic factors (such as urbanization, increased population,and higher water demand) that may increase or decrease the effect of climatic modifications. Any prediction of future climatic andanthropogenic scenarios is affected by uncertainty and the modelling tools that are used for evaluating their impact on receiving water bodies.The present paper is aimed at investigating the complexity of such analyses and the uncertainty related to future impact predictions based onlimited databases. Specifically, the study is focused on quantifying the impact of urbanization and social changes coupled with climate onriver water quality under uncertainty. The study was carried out at a small catchment scale (less than 100 km2), an analysis that has beenlacking from the field so far. The analysis took into account both anthropogenic change and climate determined from observed data. Becauseof inherent uncertainty in the model caused by the complexity of the model and its calibration, the analysis was performed considering theeffect of such uncertainty on reliability by means of Monte Carlo simulations. This analysis has been applied to a monitored semiurbanizedbasin in Sicily (Italy). The study showed that the proposed analyses can useful for planners and urban managers; however, the uncertaintyconnected with mathematical modeling and small available databases has to be taken into account because it can affect decision making. Theimpacts of anthropogenic changes and climate can interact, thus requiring that such factors be jointly analyzed. A larger effort in monitoringand characterization of natural and urban water systems is needed to increase the reliability of models and to improve the effectiveness ofdecision making based on such models
Lingua originaleEnglish
pagine (da-a)479-490
Numero di pagine12
Stato di pubblicazionePublished - 2012


All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Geography, Planning and Development
  • Water Science and Technology
  • Management, Monitoring, Policy and Law

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