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Water 2018, 10(6), 786; https://doi.org/10.3390/w10060786

Evaluation of Water Resource Security Based on an MIV-BP Model in a Karst Area

1
College of River and Ocean Engineering, Chongqing Jiaotong University, Chongqing 400074, China
2
College of Mathematics and Statistics, Chongqing Technology and Business University, Chongqing 400067, China
3
College of Architecture and Urban Planning, Chongqing Jiaotong University, Chongqing 400074, China
4
Key Laboratory of Mountain Town Construction and New Technology, Ministry of Education, Chongqing University, Chongqing 400045, China
*
Author to whom correspondence should be addressed.
Received: 14 May 2018 / Revised: 8 June 2018 / Accepted: 11 June 2018 / Published: 14 June 2018
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Abstract

Evaluation of water resource security deserves particular attention in water resource planning and management. A typical karst area in Guizhou Province, China, was used as the research area in this paper. First, based on data from Guizhou Province for the past 10 years, the mean impact value–back propagation (MIV-BP) model was used to analyze the factors influencing water resource security in the karst area. Second, 18 indices involving five aspects, water environment subsystem, social subsystem, economic subsystem, ecological subsystem, and human subsystem, were selected to establish an evaluation index of water resource security. Finally, a BP artificial neural network model was constructed to evaluate the water resource security of Guizhou Province from 2005 to 2014. The results show that water resource security in Guizhou, which was at a moderate warning level from 2005 to 2009 and a critical safety level from 2010 to 2014, has generally improved. Groundwater supply ratio, industrial water utilization rate, water use efficiency, per capita grain production, and water yield modulus were the obstacles to water resource security. Driving factors were comprehensive utilization rate of industrial solid waste, qualifying rate of industrial wastewater, above moderate rocky desertification area ratio, water requirement per unit gross domestic product (GDP), and degree of development and utilization of groundwater. Our results provide useful suggestions on the management of water resource security in Guizhou Province and a valuable reference for water resource research. View Full-Text
Keywords: BP neural network; karst; MIV; water resource security BP neural network; karst; MIV; water resource security
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Liu, L.; Guan, D.; Yang, Q. Evaluation of Water Resource Security Based on an MIV-BP Model in a Karst Area. Water 2018, 10, 786.

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