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The disaster risk management cycle (DRMC) is a part of the important efforts designed to handle disaster risk. DRMC contains the following four phases: response, recovery, mitigation and preparedness. This paper aims to determine the awareness of stakeholder on DRMC and to explore the application of DRMC from stakeholder’s perspective.

Disaster is an extreme event that causes heavy loss of life, properties and livelihood. Every year, Malaysia has been affected by disasters, whether natural or manmade. DRM is the management of resources and the responsibility for dealing with all aspects of an emergency. An effective DRM requires a combination of knowledge and skills. Questionnaires were distributed to the construction industry players and flood victims.

Results obtained on the basis of the survey revealed that a majority of respondents are unaware of DRMC. In addition, combination of professional and non-professional respondent’s perspectives in each phase of DRMC and effects of disaster are presented by the hierarchy.

The study of DRMC is commonly about the explanation or comparison of the concept but infrequently in the application of the DRMC. This study will fill the gap between theory and application of DRMC. The study aimed to determine whether the construction industry player and community aware of DRMC and to explore DRMC of flood event from perspective of industry players and flood victims. From this comparison, the management can create a better cycle of disaster management to handle various type disaster and to anticipate disaster risks.

The US Department of Agriculture (USDA), Soil Conservation Services (SCS) rainfall-runoff model has been applied worldwide since 1954 and adopted by Malaysian government agencies. Malaysia does not have regional specific curve numbers (CN) available for the use in rainfall-runoff modelling, and therefore a SCS-CN practitioner has no option but to adopt its guideline and handbook values which are specific to the US region. The selection of CN to represent a watershed becomes subjective and even inconsistent to represent similar land cover area. In recent decades, hydrologists argue about the accuracy of the predicted runoff results from the model and challenge the validity of the key parameter, initial abstraction ratio coefficient (λ) and the use of CN. Unlike the conventional SCS-CN technique, the proposed calibration methodology in this chapter discarded the use of CN as input to the SCS model and derived statistically significant CN value of a specific region through rainfall-runoff events directly under the guide of inferential statistics. Between July and October of 2004, the derived λ was 0.015, while λ = 0.20 was rejected at alpha = 0.01 level at Melana watershed in Johor, Malaysia. Optimum CN of 88.9 was derived from the 99% confidence interval range from 87.4 to 96.6 at Melana watershed. Residual sum of square (RSS) was reduced by 79% while the runoff model of Nash–Sutcliffe was improved by 233%. The SCS rainfall-runoff model can be calibrated quickly to address urban runoff prediction challenge under rapid land use and land cover changes.

There is evidence that a stationary short memory process that encounters occasional structural break can show the properties of long memory processes or persistence behaviour which may lead to extreme weather condition. In this chapter, we applied three techniques for testing the long memory for six daily rainfall datasets in Kelantan area. The results explained that all the datasets exhibit long memory. An empirical fluctuation process was employed to test for structural changes using the ordinary least square (OLS)-based cumulative sum (CUSUM) test. The result also shows that structural change was spotted in all datasets. A long memory testing was then engaged to the datasets that were subdivided into their respective break and the results displayed that the subseries follows the same pattern as the original series. Hence, this indicated that there exists a true long memory in the data generating process (DGP) although structural break occurs within the data series.

Southeast Asia has been actively undergoing land conversion into agricultural lands over past few decades. This creates the challenges to the nation in dealing with the non-point source pollutants in many fluvial systems, thus requiring an effective approach in sediment source apportionment for an appropriate target mitigation procedure. The trace element property from different source points was used for catchment classification of Galas River. Sediment sample collection was carried out at the sources and sink areas of the catchment system. Fine sediment was analysed using X-ray fluorescence to obtain elemental composition followed by the statistical test and numerical model. Out of 83 elements, 12 elements (Mn, Ca, Cr, Ga, Dy Hf, Y, V, Th, Pb, Zn and Sr) have been selected as best tracer signatures. The solver model has indicated Pergau River as the major sediment contributor to this large catchment system. The model output could directly be proportional with the land-use practice, indicating excessive terrestrial alteration has taken place within the sites for agricultural plantation purposes. Thus, this highly recommends for the decision-making use to the targeted areas to overcome the serious sedimentation issues caused by the tillage operation in affected stream points and to improve the watershed quality.

Although there have been extensive studies on the hydrological and erosional impacts of logging, relatively little is known about the impacts of conversion into agricultural plantation (namely rubber and oil palm). Furthermore, studies on morphological impacts, sediment-bound chemistry and forensic attribution of deposited sediment to their respective sources are scarcer. This chapter introduces the potential for using the multi-proxy sediment fingerprinting technique in this context. Featuring pilot projects in two major flood-prone river systems in Malaysia, the studies explore application of geochemistry-based sediment source ascription. The geochemical signatures of sediment mixtures on floodplains were compared to sediments from upstream source tributaries. The tributaries were hypothesised to have different geochemical signatures in response to dominant land management. The first case study took place in the Segama River system (4,023 km²) of Sabah, Malaysian Borneo where a mixture of primary forest, logged-forests and oil palm plantations were predominant. The second case study was in the Kelantan River Basin (13,100 km²) with two major tributaries (Galas River and Lebir River) where logged-forests and rubber and oil palm plantations are dominant land-uses. Both case studies demonstrated the applicability of this method in ascribing floodplain deposited sediment to their respective upstream sources. Preliminary results showed that trace elements associated with fertilisers (e.g. copper and vanadium) contribute to agricultural catchment signatures. Alkaline and alkaline-earth elements were linked to recently established oil palm plantations due to soil turnover. Mixing model outputs showed that contributions from smaller, more severely disturbed catchment are higher than those from larger but milder disturbed catchments. This method capitalises on flood events to counter its adverse impacts by identifying high-priority sediment source areas for efficient and effective management.

This chapter reviews and compares Southeast Asia country practices on global, regional, and local practices for disaster risk assessment (DRA). DRA research and practices include and create a disaster risk management (DRM) solution. There are 11 countries in Southeast Asia, but only 10 countries are members of the Association of Southeast Asian Nations (ASEAN), except Timor-Leste. The key objective of ASEAN’s formation is cooperation in economic growth, social, regional peace and cultural development, disaster management cooperation, and humanitarian assistance at the regional level. The DRM system practiced in ASEAN member countries is discussed in this chapter. Furthermore, the system and findings of DRAs are also addressed. Globally, two DRA structures are discussed and compared, namely Index of Risk Management (INFORM) and World Risk Index (WRI). In addition, regional vulnerability assessment guidelines for regional and national levels are discussed. However, several selected studies and practices such as the Indonesian Risk Index (InaRISK) are being discussed at the local level. Overall, there is space for improvement of coordination in terms of data and technology sharing for DRM, especially for assessment. The finding of this review highlighted the complexity of DRA at the global and regional levels and encouraging community DRA among the ASEAN members.

This study aims to investigate the effect of temperature applied at the initial deposition of Aluminium Nitride (AlN) thin-film on a silicon substrate by high-power impulse magnetron sputtering (HiPIMS) technique.

HiPIMS system was used to deposit AlN thin film at a low output power of 200 W. The ramping temperature was introduced to substrate from room temperature to maximum 100°Cat the initial deposition of thin-film, and the result was compared to thin-film sputtered with no additional heat. For the heat assistance AlN deposition, the substrate was let to cool down to room temperature for the remaining deposition time. The thin-films were characterized by X-ray diffraction (XRD) and atomic force microscope (AFM) while the MIS Schottky diode characteristic investigated through current-voltage response by a two-point probe method.

The XRD pattern shows significant improvement of the strong peak of the c-axis (002) preferred orientation of the AlN thin-film. The peak was observed narrowed with temperature assisted where FWHM calculated at 0.35° compared to FWHM of AlN thin film deposited at room temperature at around 0.59°. The degree of crystallinity of bulk thin film was improved by 28% with temperature assisted. The AFM images show significant improvement as low surface roughness achieved at around 0.7 nm for temperature assisted sample compares to 3 nm with no heat applied.

The small amount of heat introduced to the substrate has significantly improved the growth of the c-axis AlN thin film, and this method is favorable in the deposition of the high-quality thin film at the low-temperature process.