Analyzing agricultural land use with cellular automata ‑ MARCOV and forecasting future marine water quality index: a case study in east coast peninsular Malaysia

Samsudin, Mohd Saiful and Azid, Azman and Zaudi, Muhammad Amar and Adam, Mohd Ridhwan and Abdullah Sani, Muhamad Shirwan and Saharuddin, Shazlyn Millenana and Ibrahim, Aminu and Mohd Nasir, Mohd Fahmi and Tan, Mou Leong and Mohd Ali, Nurul Izzati (2024) Analyzing agricultural land use with cellular automata ‑ MARCOV and forecasting future marine water quality index: a case study in east coast peninsular Malaysia. Water, Air, & Soil Pollution, 235. pp. 1-20. ISSN 0049-6979 E-ISSN 1573-2932

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Abstract

The land use/land cover pattern of a region is an outcome of natural and socioeconomic factors and the utilisation by humans in time and space. This study aims to model the marine water quality using the relative impact of land use on marine water quality of selected river estuary between 2006-2013, Geographical Information System (GIS) and Cellular Automata (CA)-Markov method as a planning tool in evaluating Marine Water Quality Index (MWQI) were applied. The CA-Markov model revealed agricultural land use changes from 2006-2013 using land use land cover (LULC) in GIS as Setiu and Semerak River basins have 5.72% and 2.75%, respectively. The result indicated the impact of agricultural lands on MWQI, which is very low, according to projections of land use in 2020. Thus, the MWQI value in 2020 (Setiu 76.27 and Semerak 67.64) will be higher than MWQI mean value for 2006-2013

Item Type:	Article (Journal)
Uncontrolled Keywords:	Water Ecosystem · Forecaster Model ·Marine Water Quality · Safe Water Access · Land Use
Subjects:	Q Science > QD Chemistry
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	International Institute for Halal Research and Training (INHART)
Depositing User:	Muhamad Shirwan Abdullah Sani
Date Deposited:	02 Jul 2024 09:06
Last Modified:	02 Jul 2024 09:16
URI:	http://irep.iium.edu.my/id/eprint/112827

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