Development of a web-based decision support system for supporting integrated water resources management in Daegu city, South Korea

  • Authors:

  • Yong Zeng;Yanpeng Cai;Peng Jia;Hoogkee Jee

  • Affiliations:

  • State Key Laboratory of Petroleum Resource and Prospecting, College of Geosciences, China Petroleum University, Beijing 102249, China;AIRS-CSEE, Environment Canada, Regina, Canada S4S 0A2 and State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China;Center for Geocomputation and Geoinformatics, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China and Water Resources Engineering Laboratory, Department ...;Water Resources Engineering Laboratory, Department of Civil and Environmental Engineering, Yeungnam University, Republic of Korea

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2012

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Abstract

Demands on fresh water by human beings have been continuously increasing due to population growth, living standard improvement, and economic development. At the same time, many regions are suffering greatly from floods and droughts. Those are the results of ineffective management of water resources due to the associated complexities. In this study, a decision support system (DSS) was developed for supporting integrated water resources management in Daegu city, Republic of Korea. The developed DSS contained four subsystems including database, modelbase, and knowledgebase, as well as general user interface (GUI). It was then connected with the National Water Management Information System (WAMIS). A flow prediction could be conducted through the incorporated HEC-HMS Version 3.0.1. Also, an urban water demand forecasting model was developed using an artificial neural network (ANN) based model. At the same time, a water resources management model based on genetic algorithm (GA) was developed in the DSS, facilitating efficient allocation of water resources among different regions within a city. The result indicated that the developed DSS is very useful to deal with complex water resources management problems and could be further applied to similar cities in South Korea.