Improving Flood Management, Prediction and Monitoring: Volume 20

This chapter explores the ways in which residents in Pekan, Kuantan and Temerloh districts dealt with extreme floods in the Pahang River Basin. The data were based on a survey of 602 respondents who were affected by the floods, using a set of questionnaire in a face-to-face interview conducted in June 2015. Results of the study show that the flood has destructed the livelihood, crops and small business activities of the affected communities. Vulnerabilities of the communities are linked to the lack of flood warning, landlessness, unstable housing and food insecurity, in addition to female-headed households with financial burden. Community empowerment is necessary for recovering and reducing the loss and damages incurred and improving the quality of life. The prevention and coping measures aim to reduce risk of disasters for the communities in areas that are most vulnerable and less resilient. Flood preparedness is a good preventive measure to limit the negative impacts of extreme flooding in the future. Upgrading of communication system, diversification of income and strengthening of social institution networks are most appropriately recommended for flood adaptation and mitigation strategies.

Flood Emergency Response Plan (ERP) is a plan that guides responsibilities for proper operation of Sultan Abu Bakar (SAB) dam in response to emergency incidents affecting the dam by high water storage capacity. Based on this study, four major responsibilities are needed for SAB dam owing to protect any probable risk for downstream which can be Incident Commander, Deputy Incident Commander, On-scene Commander and Civil Engineer. Having organisation charts based on ERP exercise can be helpful for decreasing the probable risks in any projects such as Abu Bakar Dam and it is a way to identify and suspected and actual dam safety emergencies. A dam safety emergency is an event, which could potentially lead to dam break and need to be taken care of a massive plan. To mitigate the hydro hazard due to dam break, UNITEN has developed a new application software known as INSPiRE (Interactive Dam Safety Decision Support System). INSPiRE, as an intelligent dam safety software, is developed to address emergencies, which demand fast, decision making and effective multi-agency collaboration due to SAB dam break event. INSPiRE will contribute towards the sustainability of SAB dam’s owner as corporate reputations can be ruined through dam structural failures that can affect the economy of the nation and enhance the quality of life of the people.

River flood exposes the population to multiple attacks from the physical, mental, health risks and its related negative effects. This study focused on the Pahang River and the three worst-hit district population (Pekan, Kuantan and Temerloh). Tools on areas of self-perceived health symptoms, QOL, depression, PTSD and community empowerment were assessed. Semi-guided questionnaires were distributed to a total of 602 victims. Questions on health symptoms were asked to respondents (R) and household members (HM). PTSD screening, i.e., the Trauma Screening Questionnaire, was used. Depression was assessed through the Beck Depression Inventory (BDI). WHOQOL-BREF assessed four domains of QOL, i.e., physical activity, psychological, social relationships and environment. Community empowerment using the Individual Community Related Empowerment tool to assess five domains, i.e., self-efficacy, participation, motivation, intention and critical awareness. Prevalent disease showed that majority suffered from hypertension (11.0%) and diabetes (7.3%). Two main symptoms experienced were cough (R = 47.2%, HM = 43.7%) and flu (R = 42.7%, HM = 40.4). Monthly health expenditure was higher post flood. Purchase of prescription medications rose from MYR24.40 to 31.02. A total of 33 people were suspected to suffer from PTSD. Through BDI assessment, it was estimated that as many as 104 (17.3%) suffered overt (high) depression. The prevalence of QOL domains are as such: low physical activity was highest at 59%, low psychological activity at 53.3%, low social relationships at 43% and low environment at 45.2%. On community empowerment, low empowerment was seen on four domains: self-efficacy at 52%, participation at 55%, motivation at 54.2% and critical awareness at 74.4%. The domain with good intention and willing to participate was at 54%. Results indicate that the community was not adaptable to flood events. This is evident from high amount of experienced symptoms, low QOL (physical and psychological aspects) and empowerment (except intention). Proportion of PTSD and overt (high) depression was however quite low.

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.

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.

Natural hazards cause enormous damage to human beings including loss of life and property. Although Malaysia is fortunate as it does not experience disasters such as volcanic eruptions and typhoons, the country is prone to flood and landslides. In December 2014, Malaysia was hit by the worst flood in Kelantan called Bah Kuning meaning yellow flood. The flood has caused thousands homeless. During the flood, the victims were evacuated to the nearest evacuation centres for shelter. However, the victims received little support due to agencies involved were unable to gain access. Lack of supporting transportation and infrastructure for disaster relief has caused deficiency in coordination. The evacuation preparedness for disaster management may be improved by integrating information through geographical information system (GIS). This research aims to assess and identify suitable locations for shelters and routes for disaster reliefs. The December 2014 flood was simulated using HEC-RAS and ArcGIS. Suitability analysis was used to determine best locations for helipads and routes based on the simulated inundated areas, roads, rivers and evacuations centres. The study also maps the best possible locations for evacuation centres and transportation modes for disaster reliefs.

Composite slabs are gaining wide acceptance in many countries as they lend themselves to faster, lighter and more economic in construction buildings. The strength of composite slabs system relies on the bonding action between the concrete and the steel deck, the shear connections and the cross-sectional resistance of steel beam. However, structural behaviour of composite slab is a complex phenomenon and therefore experimental study is often conducted to establish the actual strength of the structure under ultimate load capacity. The main objective of this study is to determine the structural behaviour of composite slab system until ultimate limit state. Total of two specimens are examined in order to obtain failure mechanism of the composite structure under full load capacity. A new design approach of composite slab for roofing system are proposed in this study to construct a composite slab system that can float in the water but not wash away by flood. The lightweight materials in this composite construction are cold-formed steel and foam concrete. The system focuses on the concept of Industrialised building system (IBS) to reduce the cost and construction time.

Kuala Lumpur, the capital of Malaysia, is exposed to several natural hazards, among which flash floods are most common and frequent. Expanding development and higher intensity of rainfall are the primary causes of flash floods. As the urbanisation is growing, the number of exposed properties, people and business premises are also increasing. This may have a detrimental impact on the socio-economic state of the city. Therefore, the purpose of this chapter is to investigate the frequency and intensity of flash flood occurrences between 2011 and 2016 and to delineate how it is impacting the urban livelihood. For this study, several news reports of flash flood events, previously published and reports were reviewed to elicit information so that the frequency and intensity of flash floods can be analysed for identifying flash flood risk areas. Along with the information from newspapers, Google map was used to identify the spatial locations of flash flood events, thus identifying the risk zones. This study found the City Centre as the most risk prone to flash floods. It was noted that 39% of flash floods occurred in this place. The Damansara-Penchala area comes in the second position with 20% of flash floods occurring in this place. Most of the people of these zones are exposed to flash flood and the affected people suffer from road blocking and heavy traffic jam. This study will help researchers and policymakers to understand the impact of flash floods in the city. This will also help to identify the most flood-prone areas of the city.

Flood is one of the most common disasters in Malaysia especially during northeast monsoon season (November–March). This chapter analyses flood disaster management strategies in Pahang on preparations and vulnerabilities of the local communities along the Pahang River Basin, especially in Temerloh. In Malaysia, the National Security Council (MKN) is the organisation that is fully responsible in managing the national disaster management system, which provides an effective relieve mechanism for flood disaster. This study utilises two type of sources which are primary and secondary sources to collect the data. The primary data were collected in June 2015 through a survey of 202 respondents affected by the flood by using semi-structured questionnaires through an interview conducted in person. Meanwhile, the secondary data were collected from the local authorities. From both sources, the survey shows that 31% of the population in Temerloh did not get an early warning notification, more than half involving those in the rural area. Lack of efficient early warning system became one of the vulnerability factors affecting local community. About 78% of respondents have been relocated to the relief centres around Temerloh. Agricultural income dropped by 31.2% as the result of damaged crops and cessation of small businesses, which contributed to the increase in hardcore-poor category by 6.5%. The study concludes that it is essential to review the effectiveness of flood disaster management strategies in Pahang to minimise the aftermath impact of flooding to the community.

Natural flood disasters frequently happen in Malaysia especially during monsoon season and Kuala Kangsar, Perak, is one of the cities with the frequent record of natural flood disasters. Previous flood disaster faced by this city showed the failure in notifying the citizen with sufficient time for preparation and evacuation. The authority in charge of the flood disaster in Kuala Kangsar depends on the real-time monitoring from the hydrological sensor located at several stations along the main river. The real-time information from hydrological sensor failed to provide early notification and warning to the public. Although many hydrological sensors are available at the stations, only water level sensors and rainfall sensors are used by authority for flood monitoring. This study developed a flood prediction model using artificial intelligence to predict the incoming flood in Kuala Kangsar area based on artificial neural network (ANN). The flood prediction model is expected to predict the incoming flood disaster by using information from the variety of hydrological sensors. The study finds that the proposed ANN model based on nonlinear autoregressive network with exogenous inputs (NARX) has better performance than other models with the correlation coefficient that is equal to 0.98930. The NARX model of flood prediction developed in this study can be referred to as the future flood prediction model in Kuala Kangsar, Perak.

The impact of mitigating flood occurrence in the rural and urban areas has become crucial as it has affected government policies for countries that are prone to flood disaster. Efforts and funds have been put up to a higher level of capabilities to ensure that coping and managing flood disaster could be resolved. Several initiatives made in managing flood are: effectively monitoring the potential at-risk inundated area, improving the river water irrigation and drainage and undertaking the environmental pollution. This chapter basically focusses more on the improvement of flood monitoring system device at the potential flood area. The approach of ubiquitous mobile SCADA offers a low-cost, portable, and small in size flood monitoring system device with easily accessible data. An easy web monitoring of environment surrounding anywhere and at any time offers a real-time data updated with a very minimum delay of each and every environment data required. There are several sensors like ultrasonic, sound, temperature and humidity, water drop and vibration sensors are equipped together with one small monitoring system platform. The alert of water level condition is notified through a beeping buzzer and light LED notation of various colors of green, yellow and red, which notify any increase of water exceeded. The platform is powered by a rechargeable battery that allows the platform to be mobile and portable. Hence, flood monitoring system platform promotes a low-cost, easy-to-handle and ubiquitous data updated device for a better monitoring system platform.

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.

This study compares the performance of two types of clustering methods, time-based and non-time-based clustering, in the identification of river discharge patterns at the Johor River basin during the northeast monsoon season. Time-based clustering is represented by employing dynamic time warping (DTW) dissimilarity measure, whereas non-time-based clustering is represented by employing Euclidean dissimilarity measure in analysing the Johor River discharge data. In addition, we combine each of these clustering methods with a frequency domain representation of the discharge data using Discrete Fourier Transform (DFT) to see if such transformation affects the clustering results. The clustering quality from the hierarchical data structures of the identified river discharge patterns for each of the methods is measured by the Cophenetic Correlation Coefficient (CPCC). The results from the time-based clustering using DTW based on DFT transformation show a higher CPCC value as compared to that of non-time-based clustering methods.