Bioretention systems for stormwater management: Recent advances and future prospects.

Bioretention is a popular stormwater management strategy that is often utilized in urban environments to combat water quality and hydrological impacts of stormwater. This goal is achieved by selective designing of a system, which consists of suitable vegetation at the top planted on an engineered media with drainage system and possible underdrain at the bottom. Bibliometric analysis on bioretention studies indicates that most of the original research contributions are derived from a few countries and selected research groups. Hence, most of the bioretention systems installed in diverse geographical locations are based on guidelines from climatically different countries, which often lead to operational failures. The current review critically analyzes recent research findings from the bioretention literature, provides the authors' perspectives on the current state of knowledge, highlights the key knowledge gaps in bioretention research, and points out future research directions to make further advances in the field. Specifically, the role and desired features of bioretention components, the importance of fundamental investigations in laboratory, field-based studies and modeling efforts, the real-time process control of bioretention cells, bioretention system design considerations, and life cycle assessment of full-scale bioretention systems are discussed. The importance of local conditions in guiding bioretention designs in difference climates is emphasized. At the end of the review, current technical challenges are identified and recommendations to overcome them are provided. This comprehensive review not only offers fundamental insights into bioretention technology, but also provides novel ideas to combat issues related to urban runoff and achieve sustainable stormwater management.

Assessment of spatiotemporal risks for nationwide groundwater nitrate contamination.

National assessments of groundwater contamination risks are crucial for sustaining high-quality groundwater supplies. However, traditional methods often treat groundwater contamination risk as a steady-state indicator without considering spatiotemporal variation in risk, both geographically and over time, caused by anthropogenic and climatic factors. In this work, XGBoost, a tree-based algorithm, was applied to comprehensively analyze the drivers of groundwater contamination from nitrate, using data on 13 physical features (as used by the index-based ranking method DRASTIC) and 30 anthropogenic features from 1985 to 2010 in the contiguous United States (CONUS). The results indicate that physical features controlling the transport processes, particularly those affecting contaminant travel time from land surface to groundwater (depth to water table and transmissivity), were the dominant factors for nitrate contamination in groundwater. This was followed by features representing the potential nitrogen loading. Positive correlations between most features and the nitrogen loading time (year) were found, suggesting their growing influence on contamination risk. Based on the drivers identified for nitrate concentrations exceeding 10 mg/L in groundwater and their varying temporal contributions, this study proposes a reformulated index-based method for contamination risk assessment. With this method, an overall accuracy of around 70 % was achieved based on the validation data set. The predicted high-risk areas are mainly intensive irrigation regions, such as the High Plains, northern Midwest, and Central Valley. This new approach contributes to a more accurate and effective assessment of the contamination risks of groundwater on a regional and national scale under temporally varying environmental conditions.

Reducing risk through real options in systems design: the case of architecting a maritime domain protection system.

Complex engineering systems are usually designed to last for many years. Such systems will face many uncertainties in the future. Hence the design and deployment of these systems should not be based on a single scenario, but should incorporate flexibility. Flexibility can be incorporated in system architectures in the form of options that can be exercised in the future when new information is available. Incorporating flexibility comes, however, at a cost. To evaluate if this cost is worth the investment a real options analysis can be carried out. This approach is demonstrated through analysis of a case study of a previously developed static system-of-systems for maritime domain protection in the Straits of Malacca. This article presents a framework for dynamic strategic planning of engineering systems using real options analysis and demonstrates that flexibility adds considerable value over a static design. In addition to this it is shown that Monte Carlo analysis and genetic algorithms can be successfully combined to find solutions in a case with a very large number of possible futures and system designs.

Occurrence and distribution of bacteria indicators, chemical tracers and pathogenic vibrios in Singapore coastal waters.

Water quality in Singapore's coastal area was evaluated with microbial indicators, pathogenic vibrios, chemical tracers and physico-chemical parameters. Sampling sites were grouped into two clusters (coastal sites at (i) northern and (ii) southern part of Singapore). The coastal sites located at northern part of Singapore along the Johor Straits exhibited greater pollution. Principal component analysis revealed that sampling sites at Johor Straits have greater loading on carbamazepine, while turbidity poses greater influence on sampling sites at Singapore Straits. Detection of pathogenic vibrios was also more prominent at Johor Straits than the Singapore Straits. This study examined the spatial variations in Singapore's coastal water quality and provided the baseline information for health risk assessment and future pollution management.

Valuing flexibilities in the design of urban water management systems.

Climate change and rapid urbanization requires decision-makers to develop a long-term forward assessment on sustainable urban water management projects. This is further complicated by the difficulties of assessing sustainable designs and various design scenarios from an economic standpoint. A conventional valuation approach for urban water management projects, like Discounted Cash Flow (DCF) analysis, fails to incorporate uncertainties, such as amount of rainfall, unit cost of water, and other uncertainties associated with future changes in technological domains. Such approach also fails to include the value of flexibility, which enables managers to adapt and reconfigure systems over time as uncertainty unfolds. This work describes an integrated framework to value investments in urban water management systems under uncertainty. It also extends the conventional DCF analysis through explicit considerations of flexibility in systems design and management. The approach incorporates flexibility as intelligent decision-making mechanisms that enable systems to avoid future downside risks and increase opportunities for upside gains over a range of possible futures. A water catchment area in Singapore was chosen to assess the value of a flexible extension of standard drainage canals and a flexible deployment of a novel water catchment technology based on green roofs and porous pavements. Results show that integrating uncertainty and flexibility explicitly into the decision-making process can reduce initial capital expenditure, improve value for investment, and enable decision-makers to learn more about system requirements during the lifetime of the project.