Site selection for managed aquifer recharge using fuzzy rules: integrating geographical information system (GIS) tools and multi-criteria decision making | Sélection de site pour la recharge contrôlée d’aquifère en utilisant des règles multiples diverses: intégration de systèmes d’infirmation géographique (SIG) et de prise de décision conditionnelle Selección del sitio para el manejo de la recarga de acuíferos usando reglas difusa: integración de herramientas del sistema de información geográfica (SIG) y múltiples criterios de toma de decisiones 使用模糊规则为含水层人工补给选址:结合地理信息系统(GIS)工具和多准则决策方法 مکانيابي محلهای تغذيه مصنوعي آبخوان با استفاده از قواعد فازي: تلفيق سامانه اطلاعات جغرافيايي و روش تصميم گيري چند معياره Seleção de locais para recarga de aquíferos usando regras difusas: integração de sistemas de informação geográfica (SIG) e sistemas de decisão multi-critério
2012
Malekmohammadi, Bahram | Ramezani Mehrian, Majid | Jafari, Hamid Reza
One of the most important water-resources management strategies for arid lands is managed aquifer recharge (MAR). In establishing a MAR scheme, site selection is the prime prerequisite that can be assisted by geographic information system (GIS) tools. One of the most important uncertainties in the site-selection process using GIS is finite ranges or intervals resulting from data classification. In order to reduce these uncertainties, a novel method has been developed involving the integration of multi-criteria decision making (MCDM), GIS, and a fuzzy inference system (FIS). The Shemil-Ashkara plain in the Hormozgan Province of Iran was selected as the case study; slope, geology, groundwater depth, potential for runoff, land use, and groundwater electrical conductivity have been considered as site-selection factors. By defining fuzzy membership functions for the input layers and the output layer, and by constructing fuzzy rules, a FIS has been developed. Comparison of the results produced by the proposed method and the traditional simple additive weighted (SAW) method shows that the proposed method yields more precise results. In conclusion, fuzzy-set theory can be an effective method to overcome associated uncertainties in classification of geographic information data.
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