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• W16851903 abstract "Karstic aquifers present a great extension throughout the world (12 % of the emerged grounds) and in particular in countries around the Mediterranean sea (from 20 to 90 % of the surface of the Mediterranean countries). These aquifers represent important groundwater potentialities. In both countries (France and Turkey), these karstic aquifers are exploited for drinking water supply and other economic activities (agriculture, pisciculture,. . . ) and constitute the single water resource in certain areas of these countries. The role of these karstic hydrosystems in the social and economical context of some areas is extremely crucial. These aquifers are very vulnerable to contaminations and are overexploited, taking into account the increase in water requirements. Karstic aquifers are very complex and show very particular characteristics (strong heterogeneity, anisotropy, discontinuity of the medium, hierarchization of the flows), which make difficult any classical approach of identification of these systems and management of their water resources. The difficulty of modeling comes owing to the fact that these karstic systems are highly non-linear and are little adapted to the classical methods of identification (flow and transport modeling based on Darcy law). Soft computing methods (Artificial neural networks and fuzzy logic) are playing a key role in the modelling of complex and nonlinear problems. The uncertainty associated with the data, the immense size of the data to deal with, the diversity of the data type and the associated scales are important factors to rely on unconventional mathematical tools such as soft computing. In this thesis, the three pilot experimental sites are: the karst of La Rochefoucauld in France which is used in particular for the supply of the regional capital Angouleme; Orbe karstic spring which supplies the rural city of Arette (Southwestern France) and the karst of Safranbolu in Turkey which supplies the town of Safranbolu. The principal objective of this work is to test the ability of soft computing methods for modeling of complex karstic systems and predicting the discharge rates and quality of water at the outlets of these systems. The results show the ability of Soft computing method to model these highly non linear systems. All the modelling work was carried out using the Matlab programming environment." @default.
• W16851903 created "2016-06-24" @default.
• W16851903 creator A5087422551 @default.
• W16851903 date "2008-01-01" @default.
• W16851903 modified "2023-10-18" @default.
• W16851903 title "Modeling of groundwater flow and quality in karstic system using soft computing methods (neural networks, fuzzy logic)" @default.
• W16851903 hasPublicationYear "2008" @default.
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