Abstract
Optimal water allocation is an important means of improving water use efficiency. However, since water allocation options are usually characterized by multi-region, multi-principle and multi-criterion factors, decision-makers often have difficulty in making objective decisions using them because the many available water allocation options often make the ratings of the options so close to be ranked. This study present a hierarchy variable sets (VS) model, based on the single-layer variable sets model, for ranking the water allocation options of Jining City, China. The ratings of the options are evaluated using a fuzzy rating interval (FRI) that can overcome homogenization in the ratings. The structure of the model presented in this study is clear with a simple procedure of computation and the result is rational. The case study used illustrates that this model can help decision-makers know the rating of water allocation options partially and overall. The computed result from this model appears more convincing than a previous water allocation approach for the city based on the maximum entropy principle.
Similar content being viewed by others
Abbreviations
- RMD:
-
Relative membership degree
- VFS:
-
Variable fuzzy sets
- VS:
-
Variable sets
- FRI:
-
Fuzzy rating interval
References
Afshar A, Mariño MA, Saadatpour M, Afshar A (2011) Fuzzy TOPSIS multi-criteria decision analysis applied to Karun Reservoirs System. Water Resour Manag 25:545–563. doi:10.1007/s11269-010-9713-x
Chen SY (1994) Theory of fuzzy optimum selection for multistage and multiobjective decision making system. J Fuzzy Math 2:163–174
Chen S (1997) Relative membership function and new frame of fuzzy sets theory for pattern recognition. J Fuzzy Math 5:401–411
Chen SY (2001) Semi-structural decision-making theory and approach for flood control and dispatching system. J Hydraul Eng 11:26–33
Chen S, Guo Y (2006) Variable fuzzy sets and its application in comprehensive risk evaluation for flood-control engineering system. Fuzzy Optim Decis Making 5:153–162. doi:10.1007/s10700-006-7333-y
Chen S, Hou Z (2004) Multicriterion decision making for flood control operations: theory and applications. JAWRA J Am Water Resour Assoc 40:67–76. doi:10.1111/j.1752-1688.2004.tb01010.x
Chen SY, Xue ZC, Li M (2013a) Variable sets principle and method for flood classification. Sci China Technol Sci 56:2343–2348. doi:10.1007/s11431-013-5304-4
Chen SY, Xue ZC, Li M, Zhu X (2013b) Variable sets method for urban flood vulnerability assessment. Sci China-Technol Sci 56:3129–3136. doi:10.1007/s11431-013-5393-0
Cheng CT (1999) Fuzzy optimal model for the flood control system of the upper and middle reaches of the Yangtze River. Hydrol Sci J 44:573–582. doi:10.1080/02626669909492253
Cheng CT, Chau KW (2001) Fuzzy iteration methodology for reservoir flood control operation. J Am Water Resour Assoc 37:1381–1388. doi:10.1111/j.1752-1688.2001.tb03646.x
Christodoulou S, Deligianni A (2010) A neurofuzzy decision framework for the management of water distribution networks. Water Resour Manag 24:139–156. doi:10.1007/s11269-009-9441-2
Geng GT, Wardlaw R (2013) Application of multi-criterion decision making analysis to integrated water resources management. Water Resour Manag 27:3191–3207. doi:10.1007/s11269-013-0343-y
Hajkowicz S, Collins K (2007) A review of multiple criteria analysis for water resource planning and management. Water Resour Manag 21:1553–1566. doi:10.1007/s11269-006-9112-5
Islam MS, Sadiq R, Rodriguez MJ et al (2013) Evaluating water quality failure potential in water distribution systems: a fuzzy-TOPSIS-OWA-based methodology. Water Resour Manag 27:2195–2216. doi:10.1007/s11269-013-0283-6
Jafarzadegan K, Abed-Elmdoust A, Kerachian R (2013) A fuzzy variable least core game for inter-basin water resources allocation under uncertainty. Water Resour Manag 27:3247–3260. doi:10.1007/s11269-013-0344-x
Kim Z, Singh VP (2014) Assessment of environmental flow requirements by entropy-based multi-criteria decision. Water Resour Manag 28:459–474. doi:10.1007/s11269-013-0493-y
Mutikanga HE, Sharma SK, Vairavamoorthy K (2011) Multi-criteria decision analysis: a strategic planning tool for water loss management. Water Resour Manag 25:3947–3969. doi:10.1007/s11269-011-9896-9
Rani D, Moreira MM (2010) Simulation-optimization modeling: a survey and potential application in reservoir systems operation. Water Resour Manag 24:1107–1138. doi:10.1007/s11269-009-9488-0
Sechi GM, Sulis A (2009) Water system management through a mixed optimization-simulation approach. J Water Resour Plan Manag-ASCE 135:160–170. doi:10.1061/(ASCE)0733-9496(2009)135:3(160)
Tao T, Xin K, Lv C, Liu S (2011) Evaluation of drinking water quality in a water supply distribution network based on Grey correlation analysis. J Water Supply Res Technol 60:448. doi:10.2166/aqua.2011.042
Toosi SLR, Samani JMV (2012) Evaluating water transfer projects using analytic network process (ANP). Water Resour Manag 26:1999–2014. doi:10.1007/s11269-012-9995-2
Wang XJ, Zhao RH, Hao YW (2011) Flood control operations based on the theory of variable fuzzy sets. Water Resour Manag 25:777–792. doi:10.1007/s11269-010-9726-5
Xu K, Chen B, Chen Q (1999) Characteristic quantity of safety grade and its calculation method. China Saf Sci J 9:6–12
Zhong P, Zhang J, Bing J (2010) Maximum entropy evaluation for water resources allocation schemes based on GEM weighting method. Water Power 36:16–19
Acknowledgments
This research was supported by the National Natural Science Foundation of China (51379055), the National Key Technology R&D Program (2012BAB03B03) and the Fundamental Research Funds for the Central Universities (2011B04914).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Wan, XY., Zhong, PA. & Appiah-Adjei, E.K. Variable Sets and Fuzzy Rating Interval for Water Allocation Options Assessment. Water Resour Manage 28, 2833–2849 (2014). https://doi.org/10.1007/s11269-014-0640-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11269-014-0640-0