Fang Yenn Teo

Urban stormwater pollution is an increasing challenge in rapidly developing tropical cities, where high runoff volumes, ageing drainage infrastructure, and mixed contaminant sources place growing pressure on receiving waters and conventional treatment systems. This paper proposes an integrated monitoring and evaluation framework for a hybrid stormwater treatment system which combines Continuous Deflective Separation with Nature-Based Solutions (CDS-NbS). The method includes CDS pre-treatment, followed by a vetiver floating wetland and biochar filtration media, with natural zeolite adsorption units. The performance of the system was assessed through staged sampling, independent third-party verification, accredited laboratory analysis, and real-time Internet of Things (IoT) monitoring under representative tropical urban operating conditions. The integrated procedure showed progressive improvements in water quality, reductions in suspended solids, organic pollutants, and selected contaminants, while nutrient behaviour was observed to vary depending on operational and seasonal conditions, and stable gravity-driven hydraulic performance. Besides efficient treatment, it also offers opportunities for water reuse, biomass recovery, and circular-economy applications for non-potable water not used for irrigation. This pilot project illustrated the potential of a hybrid CDS–NbS system which can be adopted to deliver practical, scalable solutions for resilient stormwater management in tropical cities while advancing broader sustainability, circular-economy, and water-security goals.

Rainwater harvesting systems (RWHS) are increasingly recognised as sustainable water management solutions, yet their adoption within Malaysia’s non-domestic sector remains limited despite growing water security concerns. Existing studies have largely focused on domestic applications, technical performance and economic feasibility, with limited attention to organisational readiness and decision-making processes in industrial and commercial contexts. This study proposes a methodological framework that integrates the Technology Acceptance Model (TAM) with the Technology-Organisation-Environment (TOE) framework to assess intention to adopt RWHS within Malaysia’s non-domestic sector. The methodology follows a sequential explanatory mixed-methods approach, where survey data are analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM) and then supplemented with expert interviews to interpret the quantitative results. The framework incorporates technological, organisational, environmental and perception-based factors influencing RWHS adoption intention. This study contributes a structured approach for assessing organisational readiness and offers practical value for policymakers and industry stakeholders seeking to promote wider adoption of sustainable water technologies in Malaysia.

The Marine Water Quality Index is a key indicator of coastal ecosystem health and is essential for sustainable water environmental management. Integration of the Malaysia Marine Water Quality Index (MMWQI) into the hydro-environmental assessment provides essential insights into the quality of marine water conditions across spatial scales in Malaysia. Hence, this study assessed the spatial variability of MMWQI across nine monitoring stations in the coastal area of Perak, Malaysia, from 2020 to 2024. The Mann–Whitney test and Kruskal–Wallis test with Dunn–Holm post-hoc comparisons were used to analyse 270 recorded samples. The study revealed significant categorical variability, with lower MMWQI values observed in the estuarine zone than in the coastal zone (W = 14694, p = 1.06 × 10 ⁻²⁷ ), indicating greater degradation in estuarine zones. Further exploration of localized variations among individual monitoring stations exhibited significant spatial variability in MMWQI (H = 164.343, p = 1.97×10 ⁻³¹ ). Post-hoc analysis using Dunn’s test confirmed that MMAE004 exhibited significantly lower MMWQI values compared to all other monitoring stations (p _adj < 0.001), identifying it as the primary localized pollution hotspot in the study area. The findings underscore the need for targeted pollution control measures and ongoing long-term monitoring, which provide crucial insights for sustainable coastal and estuarine development, environmental protection, and informed decision-making.

Rainwater harvesting systems (RWHS) are increasingly being adopted globally as part of green infrastructure to complement climate change adaptation and sustainable stormwater management. This study reviews the adoption of RWHS in non-domestic sectors, including commercial, industrial, and institutional settings, situating the topic within the broader challenges of water security in urban areas. This review aims to synthesise existing evidence on the key drivers, barriers, trends, and research gaps shaping RWHS adoption beyond the conventional domestic household scale. Following the PRISMA 2020 guidelines, peer-reviewed manuscripts published since 2000 were systematically identified and screened from the Scopus and Web of Science databases, focusing explicitly on adoption-related outcomes in non-domestic contexts. The findings indicate that RWHS adoption is primarily driven by anticipated water bill savings, sustainability, corporate environmental commitments, and stormwater management benefits, while major barriers include high initial capital costs, regulatory uncertainty, technical and maintenance complexity, and concerns regarding water quality and system reliability. This review also reveals sector-specific trends, such as the integration of RWHS with green building certification schemes and smart water technologies, and the prioritisation of process and utility water uses in non-domestic sectors. Overall, the findings indicate that non-domestic RWHS have substantial potential to contribute to sustainable stormwater management, but wider uptake depends on targeted policy support, economic incentives, clearer regulatory frameworks, and improved technical guidance, alongside further empirical research addressing the identified knowledge gaps.

Satellite-based precipitation estimates (SPE) provide essential spatial coverage and near real-time availability for hydrological applications but often exhibit systematic biases in regions characterized by complex terrain and strong climatic variability, limiting their reliability for flood-related studies. To address these limitations, this study proposes an Adaptive Regularization framework integrated within a Long Short-Term Memory (LSTM) model to enhance satellite–gauge rainfall fusion beyond conventional optimization strategies. The framework dynamically adjusts learning rate and weight decay during training based on validation performance and overfitting indicators, improving training stability, data efficiency, and model generalization across diverse precipitation regimes. The proposed approach was applied to refine Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) daily rainfall estimates over the flood-prone east coast of Peninsular Malaysia. Model performance was assessed against ten optimization algorithms using correlation coefficient (CC), mean absolute error (MAE), normalized root mean squared error (NRMSE), percentage bias (PBias), and Kling–Gupta efficiency (KGE). Results show that the Adaptive Regularization framework consistently outperforms all benchmark optimizers, achieving an MAE of 6.87, CC of 0.68, NRMSE of 1.84, and KGE of 0.56. Overall, the proposed framework enhances spatial consistency and robustness across monsoon seasons, offering a scalable solution for improving SPE in flood-prone regions.

An extreme rainfall event that occurred from 16 to 18 December 2021 along the coastal regions of Peninsular Malaysia (PM) caused widespread flooding and substantial socioeconomic impacts. This study investigates the mechanisms leading to this event, focusing on the roles of climatic phenomena and local terrains. Two atmospheric interactions play key roles in triggering the event. Firstly, a strong cold surge (CS) associated with the East Asian winter monsoon (EAWM) interacted with the easterly surge over the southern South China Sea, leading to the formation of Borneo vortex. Secondly, a strong northeasterly and CS largely contributed to enhancing and transporting the vortex towards the PM and across the Titiwangsa mountain ranges. The phase change of the Indian Ocean Dipole (IOD) facilitated the eastward propagation of the vortex. Sumatra and PM terrains significantly modulated vortex evolution and moisture convergence over the Strait of Malacca. These findings are analyzed to shed light on interactions between large-scale climate drivers and localized terrain in generating extreme rainfall, emphasizing the necessity of multi-scale analysis for model accuracy.

Urban catchments increasingly face water-related challenges driven by rapid development and climate change, while conventional stormwater management is often insufficient for removing gross pollutants and sediments. This study evaluates an integrated treatment approach combining continuous deflective separation (CDS) technology with nature-based solutions (NbS)—including biochar, green zeolite, and floating wetlands planted with Vetiver grass—implemented at a commercial urban site in Malaysia. An on-site Internet of Things (IoT)-based monitoring system tracked pH, turbidity, electrical conductivity (EC), dissolved oxygen (DO), total dissolved solids (TDS), and temperature. Additional parameters, including biological oxygen demand (BOD), chemical oxygen demand (COD), nitrate (NO3−), total suspended solids (TSS), heavy metals (Pb, Cu, Zn), and nutrients (N, P), were analysed at the accredited laboratory of the National Water Research Institute of Malaysia (NAHRIM). Results indicate that biochar and green zeolite enhance system performance by adsorbing micro- and near-nano-sized particles and nutrients, preventing clogging, and achieving removal efficiencies of 57% for TDS, 90% for TSS, 78% for NO3−, 50% for oil and grease, 80% for BOD, and 57% for COD. Floating wetlands further improved removal of ammoniacal nitrogen (NH3-N) and phosphate (PO4³−), key eutrophication contributors. The study also demonstrates circularity: harvested Vetiver is processed into economic products, while residual biomass is converted into new biochar via pyrolysis to replace saturated biochar, which is then reused as compost. The integrated CDS-NbS system improves stormwater quality, supports reuse, contributes to carbon sequestration, and aligns with the United Nations sustainable development goals (SDGs).

Reservoirs serve many essential purposes, including water resource, flood mitigation, recreation, and hydropower generation. However, these reservoirs created by constructing hydraulic structures across the waterways encounter substantial challenges in water quality. One of the issues is eutrophication, which demands attention in reservoir management. This study employs a two-dimensional (2D) depth-averaged hydrodynamic model, utilising Delft3D, to analyse the spatial distributions and hydro-environmental processes occurring in Putrajaya Lake, Malaysia. The model effectively simulates various scenarios for both dry and wet seasons. Calibration and validation were performed using measured data from 72 points within the lake. The water quality modelling focuses on key parameters (i.e. phosphate, nitrate, and chlorophyll a). The results indicate higher phosphate concentrations during dry seasons, ranging from 0.1 to 0.4 mg∙dm−3, compared to wet seasons, suggesting a higher risk of eutrophication during dry seasons. In assessing lake eutrophication, a modified Lamparelli index was developed and adopted to evaluate the lake’s eutrophication status. The findings indicate that increasing phosphorus concentration to 0.35 mg∙dm−3 at the upstream inflow will likely trigger eutrophication in Putrajaya Lake. We recommend this phosphorus concentration as a critical threshold value at all drainage inlets as the best management practice to prevent eutrophication. A detailed assessment of water quality can be established from this finding as one of the design criteria for any hydraulic structures that could jeopardise water quality, rather than an afterthought. Addressing water quality problems through rehabilitation after they arise can be costly and often irreversible.

Stakeholder engagement has emerged as a fundamental tool for navigating the social, economic, and cultural complexities of integrated river basin management (IRBM). Engagement helps reconcile competing interests and promotes sustainable water resource management practices by fostering collaboration and dialogue among stakeholders. This study identifies key stakeholders, their selection criteria, and the factors that contribute to effective engagement in IRBM in Malaysia. A questionnaire survey was designed to understand individual stakeholder perceptions of the importance of engagement and the mechanisms that facilitate this, their views on how key stakeholders can be identified, and the factors contributing to effective engagement. Based on data from 250 online respondents, factors influencing engagement effectiveness were categorised into three stages: pre-engagement, during-engagement, and post-engagement. Statistical analysis ensured reliability, with Cronbach’s alpha values (>0.7) indicating strong internal consistency. The Friedman test was applied to identify statistically significant differences within the same group of parameters across the three engagement phases. Findings highlight the importance of stakeholder inclusion, selection criteria, and credibility at the pre-engagement stage for developing the IRBM plan. Transparent, structured participatory processes during engagement facilitated the most fruitful collaborative discussions, while post-engagement emphasised implementing stakeholder contributions and feedback and the need for monitoring and evaluation mechanisms. The study underscores the need for an inclusive and legitimate governance model within IRBM to enhance the effectiveness and credibility of stakeholder engagement.

Coastal regions face escalating challenges, including climate change, rapid urbanisation, ocean pollution, habitat degradation, and nutrient enrichment, which threaten coastal ecosystem health, biodiversity, and human livelihoods. A comprehensive understanding of coastal hydro-environmental processes, encompassing hydrodynamics, sediment transport driven by waves and currents, and biogeochemical dynamics influencing water quality, is essential for sustainable coastal management. This study presents a global systematic review of assessment methods for these processes, focusing on field data collection, laboratory experiments, numerical modelling, and artificial intelligence techniques. A bibliometric analysis was conducted on 165 peer-reviewed articles from Scopus and Web of Science, adhering to PRISMA 2020 guidelines. The findings reveal a significant shift from conventional standalone methods to integrated approaches, with 31.5% of studies combining field data with numerical models and 20% incorporating AI with field data, emphasising the need for real-time data integration and interdisciplinary strategies to enhance model reliability. This study also introduces a novel process–method–time classification framework that functionally aligns various assessment methods with specific coastal processes. However, challenges such as limited long-term datasets, high computational costs, and data resolution constraints persist. By synthesising global research trends and methodological advancements, this study offers critical insights to support more resilient, adaptive, and data-driven coastal management strategies.