چارچوب هستانشناسی برای تخصیص بهینه و پایدار منابع آب
محورهای موضوعی : مقاله پژوهشی
مهدیه صادقیان
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صبا صارمی نیا
2
1 - 1. دانشجوی دکترا رشته مهندسی صنایع، دانشکده مهندسی صنایع و سیستمها، دانشگاه صنعتی اصفهان، اصفهان، ایران
2 - استادیار، دانشکدۀ مهندسی صنایع و سیستمها، دانشگاه صنعتی اصفهان
کلید واژه: مدیریت آب, تخصیص منابع آب, آنتولوژی, گراف دانش, مدلسازی مفهومی,
چکیده مقاله :
Introduction: Water, as one of the fundamental and vital natural resources, plays an indispensable role in sustainable development and in meeting human, agricultural, and industrial needs. However, population growth, rapid urbanization, climate change, and the unequal distribution of water resources worldwide have created major challenges in managing and optimally allocating these resources.
Methods: In this study, a comprehensive ontology was developed with the aim of intelligent modeling and addressing key questions related to the identification and assessment of water resources, resource allocation and analysis, modeling and forecasting, and the use of technology and alternative water sources. The proposed ontology not only covers the technical aspects of water supply and demand but also enables structural analysis and provides answers to questions concerning allocation models, influencing factors, and optimization methods.
Findings: The developed ontology considers various types of water demand, water resources, quality of each source, factors influencing resource changes, allocation models and methods, sustainability indicators, and essential constraints and solution techniques. The results revealed that pollution strongly affects water quality, thereby altering the usability of water sources and influencing allocation decisions. Moreover, the quantitative evaluation of the ontology based on three common metrics—Relation Richness (RR=0.24), Attribute Richness (AR=0.38), and Inheritance Richness (IR=1.20)—indicates acceptable diversity in relations, moderate attribute coverage, and a balanced hierarchical structure. A review of previous studies further revealed that most focused on surface water allocation aimed at reducing shortage costs and often relied on linear models, while less attention was given to pollution and groundwater resources.
Conclusion: Queries applied to the ontology demonstrated that existing quantitative studies have addressed complex issues such as climate change, hydrogeology, and multi-objective modeling. Although simple models provide preliminary insights, incorporating more realistic factors such as pollution and environmental characteristics leads to more accurate and practical results.
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