Lauriola, Ilaria
  
(2019)
Sustainable groundwater management based on probabilistic risk analysis, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. 
 Dottorato di ricerca in 
Ingegneria civile, chimica, ambientale e dei materiali, 31 Ciclo. DOI 10.48676/unibo/amsdottorato/8925.
  
 
  
  
        
        
        
  
  
  
  
  
  
  
    
  
    
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      Abstract
      Risk assessment related to the qualitative/quantitative status of groundwater is a controversial issue, compared to which it is difficult to identify an exhaustive approach. A key factor for assessing vulnerability of aquifers is the analysis of natural renewal capacity associated with the quantity of available resource and compared to the overall water demand. Groundwater recharge is a complex process to analyze because it varies in space and time, and may be severely affected by future scenarios related to climate change and population dynamics. At the same time, local and diffuse contaminations may threaten the quality of groundwater availability with respect to the standards provided to the different uses and represent a critical environmental issue.
Consequently, even if there are many studies dealing with groundwater vulnerability, the definition of a shared approach capable of (i) exhaustively describing in an integrated framework the phenomena occurring in different hydrogeological and climatic contexts and (ii) considering all the significant uncertainties according to a stochastic method, has not yet been achieved. In order to address these points, this thesis suggest an innovative methodological framework in which application of uncertainty quantification is applied both to parametric uncertainty, which is relevant to subsurface flow and transport processes, and to the projections of climate change scenarios. In support of this, an algorithm is applied and further developed based on metamodeling techniques to accelerate risk and global sensitivity analysis. The algorithm is applied to different case studies in order to provide an
insight on some of the main quantitative/qualitative processes that affect groundwater status, leading to potentially risk conditions. The results presented in this work lay the basis for the computation of indicators which can be used for the assessment of the vulnerability of groundwater at different scales, in accordance with the requirements of European and National Regulations.
     
    
      Abstract
      Risk assessment related to the qualitative/quantitative status of groundwater is a controversial issue, compared to which it is difficult to identify an exhaustive approach. A key factor for assessing vulnerability of aquifers is the analysis of natural renewal capacity associated with the quantity of available resource and compared to the overall water demand. Groundwater recharge is a complex process to analyze because it varies in space and time, and may be severely affected by future scenarios related to climate change and population dynamics. At the same time, local and diffuse contaminations may threaten the quality of groundwater availability with respect to the standards provided to the different uses and represent a critical environmental issue.
Consequently, even if there are many studies dealing with groundwater vulnerability, the definition of a shared approach capable of (i) exhaustively describing in an integrated framework the phenomena occurring in different hydrogeological and climatic contexts and (ii) considering all the significant uncertainties according to a stochastic method, has not yet been achieved. In order to address these points, this thesis suggest an innovative methodological framework in which application of uncertainty quantification is applied both to parametric uncertainty, which is relevant to subsurface flow and transport processes, and to the projections of climate change scenarios. In support of this, an algorithm is applied and further developed based on metamodeling techniques to accelerate risk and global sensitivity analysis. The algorithm is applied to different case studies in order to provide an
insight on some of the main quantitative/qualitative processes that affect groundwater status, leading to potentially risk conditions. The results presented in this work lay the basis for the computation of indicators which can be used for the assessment of the vulnerability of groundwater at different scales, in accordance with the requirements of European and National Regulations.
     
  
  
    
    
      Tipologia del documento
      Tesi di dottorato
      
      
      
      
        
      
        
          Autore
          Lauriola, Ilaria
          
        
      
        
          Supervisore
          
          
        
      
        
          Co-supervisore
          
          
        
      
        
          Dottorato di ricerca
          
          
        
      
        
      
        
          Ciclo
          31
          
        
      
        
          Coordinatore
          
          
        
      
        
          Settore disciplinare
          
          
        
      
        
          Settore concorsuale
          
          
        
      
        
          Parole chiave
          Probabilistic risk analysis; Global sensitivity analysis; Stochastic groundwater hydrology; Probabilistic collocation method; Climate change; flow and transport in porous media.
          
        
      
        
          URN:NBN
          
          
        
      
        
          DOI
          10.48676/unibo/amsdottorato/8925
          
        
      
        
          Data di discussione
          4 Aprile 2019
          
        
      
      URI
      
      
     
   
  
    Altri metadati
    
      Tipologia del documento
      Tesi di dottorato
      
      
      
      
        
      
        
          Autore
          Lauriola, Ilaria
          
        
      
        
          Supervisore
          
          
        
      
        
          Co-supervisore
          
          
        
      
        
          Dottorato di ricerca
          
          
        
      
        
      
        
          Ciclo
          31
          
        
      
        
          Coordinatore
          
          
        
      
        
          Settore disciplinare
          
          
        
      
        
          Settore concorsuale
          
          
        
      
        
          Parole chiave
          Probabilistic risk analysis; Global sensitivity analysis; Stochastic groundwater hydrology; Probabilistic collocation method; Climate change; flow and transport in porous media.
          
        
      
        
          URN:NBN
          
          
        
      
        
          DOI
          10.48676/unibo/amsdottorato/8925
          
        
      
        
          Data di discussione
          4 Aprile 2019
          
        
      
      URI
      
      
     
   
  
  
  
  
  
    
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