A Metric Model on Identifying the National Water Scarcity Management Ability

Yue Chen (), Guoping Cen, Chuanping Hong, Jiying Liu and Song Lu
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Yue Chen: Air Force Engineering University
Guoping Cen: Air Force Engineering University
Chuanping Hong: Air Force Engineering University
Jiying Liu: Air Force Engineering University
Song Lu: Air Force Engineering University

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2018, vol. 32, issue 2, No 14, 599-617

Abstract: Abstract Our planet is getting thirstier and thirstier. Water scarcity has become an increasingly hard but urgent problem. The world's water situation engenders little optimism. About one quarter of the world's population is experiencing water scarcity. Moreover, water resources are unevenly distributed and extremely scarce in Africa and the Middle East. Water scarcity further incurs many international issues such as international conflicts, environmental refugees and disease caused by water pollution, which have made a more unstable world. To make contributions to solve the water problems, this study proposed a metric model to identify the ability of each country to manage water scarcity, and offered solutions to a country considered water over-loaded. In this paper, we developed our metric, Total Scarcity Metric, and divided it into Physical Scarcity Metric ( affected by environmental factors and population) and Economic Scarcity Metric ( affected by social factors other than population) by the two causes of water scarcity. This paper made some adjustments to an indicator we found widely-used in the literatures, and determine Physical Scarcity Metric based on it. Based on that result, Pakistan was chose as a sample region for further analysis, and Pakistan still has a long way to go. This model will prove to be advantageous for a region’s authoritative figures to consult with when in pursuit of obtaining a higher level of water resources allocation. It also can serve as a public rationale to support certain superficially incomprehensive judgments made by the administration.

Keywords: Water scarcity; Total scarcity metric; Physical scarcity metric; Economic scarcity metric; Grey relational analysis; Pakistan; Water situation forecasting; Grey forecasting model; Regression analysis; Sample plan (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11269-017-1829-9

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