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The present study aims to evaluate the effect of climate change on the flood hazard potential in the Kelantan River Basin using current and future scenarios.

The intensity-duration-frequency (IDF) was used to estimate the current 50- and 100-year return period 24-h design rainfall, and the climate change factor (CCF) was used to compute the future design rainfall. The CCF was calculated from the rainfall projections of two global climate models, CGCM1 and CCSM3, with different pre-processing steps applied to each. The IDF data were used in the rainfall-runoff-inundation model to simulate current and future flood inundation scenarios.

The estimated CCF values demonstrate a contrast, whereby each station had a CCF value greater than one for CGCM1, while some stations had a CCF value of less than one for CCSM3. Therefore, CGCM1 projected an aggravation and CCSM3 a reduction of flood hazard for future scenarios. The study reveals that topography plays an essential role in calculating the CCF.

To the best of the author’s knowledge, this is the first study to examine flood projections in the Kelantan River Basin. It is, therefore, hoped that these results could benefit local managers and authorities by enabling them to make informed decisions regarding flood risk mitigation in a climate change scenario.

Time of concentration (T_c) is one of the main inputs in rainfall–runoff model which depends on catchment length, slope, soil properties and surface cover. Factor such as floodplain also has a significant contribution on the flood wave travel time. Floodplain which influences the flow and the travelling time is not possible to be calculated using common T_c formulae. One approach to handle this complex behaviour is to deploy the hydrodynamic model as part of the rainfall–runoff model. This chapter explains the application of hydrodynamic approach to determine T_c for large catchment with the effect of floodplain. A hydrodynamic river model for Sg Relai was developed as part of the rainfall–runoff model covering 460 km² catchment area. It includes channels covering 90 km long which is extended to the floodplain based on the digital terrain model. The simulation results show that once the flood water spill to the floodplain, the channel travelling time is delayed by several hours. The delay of the travel time increases as the rainfall intensity increase which demonstrates that hydrodynamic modelling with the integration of floodplain is capable to compute the variation of T_c.

Rainfall–runoff relationship is one of the most complex hydrological phenomena. A conventional neural network (NN) with backpropagation algorithm has successfully modelled various non-linear hydrological processes in recent years. However, the convergence rate of the backpropagation NN is relatively slow, and solutions may trap at local minima. Therefore, a new metaheuristic algorithm named as cuckoo search optimisation was proposed to combine with the NN to model the daily rainfall–runoff relationship at Sungai Bedup Basin, Sarawak, Malaysia. Two-year rainfall–runoff data from 1997 to 1998 had been used for model training, while one-year data in 1999 was used for model validation. Input data used are current rainfall, antecedent rainfall and antecedent runoff, while the targeted output is current runoff. This novel NN model is evaluated with the coefficient of correlation (R) and the Nash–Sutcliffe coefficient (E²). Results show that cuckoo search optimisation neural network (CSONN) is able to yield R and E² to 0.99 and 0.94, respectively, for model validation with the optimal configuration of number of nests (n) = 20, initial discovery rate of alien eggs (painitial) = 0.6, hidden neuron (HN) = 100, iteration number (IN) = 1,000 and learning rate (LR) = 1 for CSONND4 model. The results revealed that the newly developed CSONN is able to simulate runoff accurately using only precipitation and runoff data.

The Best Management Practices for Sustainable Urban Drainage System including On-Site Detention have been introduced in the Storm Water Management Manual for Malaysia. Flash floods are becoming frequent in the urbanised areas in this country. Inefficient drainage system has been highlighted as one of the factors. Urban drains were reported incapable of coping with the unexpected heavy rainfall. Concrete drains are favourable in construction industry for economic reasons. An experimental research was conducted out to investigate the effectiveness of infiltration integration with drainage system to reduce flash flood. This laboratory research was conducted in the Universiti Teknologi Malaysia. Experiments were performed for selected drainage bed slopes and focussed on several spacing between precast drain sections along the system. The total and infiltrated flow rates, water surface and velocity profiles were examined. The results showed that drain flow rates were reduced by 60.9%–89.6% when the spacing between drain sections were enlarged. Meanwhile, the flow depths in drain sections were dropped by 48.2%–68.9%, and the water velocity was lowered up to 49% as the spacing between drain sections were increased. The study found that the drainage bed slope also influenced the performance of the infiltrated concrete drainage system.

This study explores the concept of hydraulic flushing gate with an automated control system as a flow control structure of the urban storm water system. The research team has implemented a flush gate with the automated control system to the flow of the water in a drainage channel. The flow control structure was used to determine the effectiveness of such design by applying the concept of virtually on a real-world drainage system at Jalan Astana, Kuching. Computer representations of the existing drainage system and flow control structure were built using EPA SWMM 5.0 model. The series of flow control structure was proven to hold the runoff from 10-year storm. The modelling result shows that there is 25.9% of flow reduction at outlet node. As a modification of the existing drainage system in the urban area involves high construction cost, by installing a flow control structure in the drainage system is an innovative way to control the flow of the water.

Big data have rapidly developed as a viable solution to many problems faced in engineering industries. Specifically, in the industry of water resource engineering, where there is a tremendous amount of data, various big data techniques could be applied to achieve innovative and efficient solutions for the industry. This study reviewed the proposal of big data as potential approaches to solve various difficulties encountered in managing water resources and related applications in Malaysia. The advantages and disadvantages of big data applications have also been discussed along with a brief literature review and some examples of case studies.

This study provides a performance analysis of using a rainwater harvesting system (RWHS) to supply water for toilet flushing and garden watering, with reference to a student accommodation hall in the University of Nottingham Malaysia in Semenyih, Selangor, Malaysia. Three different models were used in this analysis, in which the monthly analysis was based on the mass-balance approach, while the daily analysis was based on the yield before spillage and yield after spillage algorithms to define the tank release rule based on different sizes of storage tank (i.e. 3, 5, 7 and 10 m³). The performances of the various storage tanks were presented for water saving and reliability. The monthly analysis found promising results of collectable water on the demand, in which the average reliability is higher than 50%. Also, the daily water balance simulation verified the results from the monthly analysis. A cost analysis was performed that the best storage rainwater harvesting tank size was 10 m³ for the combined demand of toilet flushing and garden watering. Based on the findings, the proposed implementation of RWHS in the chosen campus university was reliable, not only environmentally beneficial but also economically viable.

The impact of climate change towards water surface resources is crucial, particularly in developing and non-developing countries. Groundwater as a main water resource is thus an essential. However, contamination due to hydrocarbon spills affects the groundwater as a water resource, especially as a main source of drinking water. This chapter investigates the light non-aqueous phase liquid (LNAPL) penetrations in double-porosity soil with different moisture contents and with or without vibration impact. It also explains the LNAPL penetration phenomena by employing image analysis. The physical laboratory experiments were implemented using an acrylic cylinder, a mirror, toluene and a Nikon D90 DSLR digital camera. Prepared soil was poured in an acrylic cylinder and compressed with compressor until it became 10 cm in height. LNAPL was then poured instantaneously onto the acrylic cylinder that was filled with soil sample. The LNAPL penetration patterns were recorded and monitored using a Nikon D90 DSLR digital camera. The processing technique was conducted at predetermined time intervals using Surfer software and Matlab routine to plot the LNAPL pattern. The results showed that a higher penetration rate of LNAPL occurred with higher moisture content and without vibration impact. The penetration time for LNAPL to reach the bottom of the soil sample was found to be longer for the soil that had low moisture content and with vibration impact.

This study assesses the effects of flood hazard on property price, which focus on residential property. The growth in the population has resulted in more areas being explored, including areas that are prone to flooding. The exploration of a new area for housing development also brings vulnerability to flood hazard. This research employed hedonic regression method to assess the impact of flood to property price between low-flood and non-flood areas. The case study areas are residential properties along Langar River, Selangor, Malaysia. The findings reveal that residential price in case study areas have only little impact in terms of price impact from the flood events. This study also establishes a new valuation model by considering flood hazard. It is expected that the impact from the flood to property price will be significant in future due to changes in property demand patterns as well as the increase in environmental issues.