Climate change is undeniably the greatest issue facing our society. Around the globe,
increasingly unpredictable weather patterns and extreme weather events are
observed, causing considerable risks to human lives, properties and health safety and
also on the natural ecosystem. The magnitude and impacts of climate change are
growing, and particularly in Malaysia, studies show increases in temperature and
changes in rainfall regimes. Such changes have profound implications, especially for
coastal communities. Since knowledge and perceptions of the public on climate change
could affect the success of implemented adaptation and mitigation options, it is
essential to conduct assessments to gather such information. A public awareness and
perception study was conducted at Sabak and Tanjung Karang, two coastal
communities which were affected by changes in sea level and flooding incidences. The
knowledge level and perceptions of climate change among respondents were assessed
covering areas such as level of awareness of the respondents, their perceptions of
climate change issues, their sentiments on climate change and adaptation measures,
their socio-economic activity and the effect on their lives. Results show that majority
of respondents were aware of climate change issues and challenges. High levels of
concern about climate change were expressed with the majority were worried and
uncertain about the climate change impact and hoped for government measures.
Almost half of respondents cited significant damage to their properties and reduction
in income generation. Overall, the results of the present study gave insights of the
affected parties on perceptions and awareness pertaining to climate change, which
could potentially be used to promote greater awareness of climate change matters and
to gauge the public response to related policies and strategies.
The well-known geostatistics method (variance-reduction method) is commonly used to determine the optimal rain gauge network. The main problem in geostatistics method to determine the best semivariogram model in order to be used in estimating the variance. An optimal choice of the semivariogram model is an important point for a good data evaluation process. Three different semivariogram models which are Spherical, Gaussian and Exponential are used and their performances are compared in this study. Cross validation technique is applied to compute the errors of the semivariograms. Rain-fall data for the period of 1975 – 2008 from the existing 84 rain gauge stations covering the state of Johor are used in this study. The result shows that the exponential model is the best semivariogram model and chosen to determine the optimal number and location of rain gauge station.