Sustainable management of water demand using fuzzy inference system: a case study of Kenyir Lake, Malaysia

• Main Authors: Mohd Azlan, Nor Najwa Irina, Abdul Malek, Marlinda, Zolkepli, Maslina, Mohd Salim, Jamilah, Ahmed, Ali Najah
• Format: Article
• Published: Springer 2021
• Online Access: http://psasir.upm.edu.my/id/eprint/95232/; https://link.springer.com/article/10.1007/s11356-020-11908-4

Sustainable water demand management has become a necessity to the world since the immensely growing population and development have caused water deficit and groundwater depletion. This study aims to overcome water deficit by analyzing water demand at Kenyir Lake, Terengganu, using a fuzzy inference system (FIS). The analysis is widened by comparing FIS with the multiple linear regression (MLR) method. FIS applied as an analysis tool provides good generalization capability for optimum solutions and utilizes human behavior influenced by expert knowledge in water resources management for fuzzy rules specified in the system, whereas MLR can simultaneously adjust and compare several variables as per the needs of the study. The water demand dataset of Kenyir Lake was analyzed using FIS and MLR, resulting in total forecasted water consumptions at Kenyir Lake of 2314.38 m3 and 1358.22 m3, respectively. It is confirmed that both techniques converge close to the actual water consumption of 1249.98 m3. MLR showed the accuracy of the water demand values with smaller forecasted errors to be higher than FIS did. To attain sustainable water demand management, the techniques used can be examined extensively by researchers, educators, and learners by adding more variables, which will provide more anticipated outcomes.