Water Level Evaluation at Southern Malaysia Reservoir using Fuzzy Composite Programming
Supiah Shamsudin1, Azmi Ab Rahman2, Zaiton Binti Haron3, Lat Da A,P Ai Nam4
1Dr Supiah Shamsudin, Associate Professor in the Water Resources and Hydrology area at the Department of Civil Engineering, Malaysia.
2Dr Azmi Bin Ab. Rahman,  Department of Management, Faculty of Management and Human Resource Development, UTM, Skudai, Johor, Malaysia.
Dr. Zaiton Binti Haron,  Department of Structures and Materials, Faculty of Civil Engineering, University Technology Malaysia.
Manuscript received on March 22, 2013. | Revised Manuscript received on April 09, 2013. | Manuscript published on April 30, 2013. | PP: 127-131 | Volume-2, Issue-4, April 2013. | Retrieval Number: D1329042413/2013©BEIESP

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Abstract: Ranking and evaluation of properreservoir water level outflowing into downstream river system under multi-criterion environment was presented using multi-criteria decision approach specifically Fuzzy Composite Programming (FCP). The optimum water level evaluation is vital to take into consideration the various environmental, water quantity and economical aspects of the overall systems. This multicriteria analysis will optimize water release, ensuring water quality, providing economical benefits and maintaining high quality of the natural landscape. The study mainly focuses on optimizing outflowing water level by identifying and grouping the basic indicators into its particular composite structure. The basic indicators include various water quality parameters, flowrates, rainfall, scenery etc. The composite structure of the overall reservoir water use system was presented. Five(5) alternatives based on reservoir water level was adopted which include 20.6m (Alternative 1), 22.2m(Alternative 2), 23.8m(Alternative 3), 25.4m (Alternative 4) and 27.0m(Alternative 5) respectively. Sensitivity analysis using three (3) set of different weights was performed for analyzing the robustness of the optimum water level obtained. The FCP structure consists of 15 first level indicators, 5 second level indicators, 2 third level indicators and the final indicators. The optimum value was determined based on the shortest distance between the fuzzy box and an ideal point. The optimum answer was also obtained from the highest ordered sequence value. The highest ranking order indicated by highest ordered sequence value obtained was Alternative 3 (0.660), followed by Alternative 4 (0.596), Alternative 2 (0.555), Alternative 5 (0.515) and lastly Alternative 1(0.500). The highest ranking order indicated the most optimum, advisable and appropriate water level for Layang Reservoir.
Keywords: Fuzzy Composite Programming, MCDM, Optimum water level, Reservoir.