With the growing concerns over emerging contaminants in indirect potable reuse (IPR) applications, we investigate the impact on human health risk of emerging contaminants introduced into groundwater. Some emerging contaminants have potential endocrine-related health effects at a specific exposure range that is much lower than current guidelines. We start by analyzing Bisphenol A (BPA), which is one of the frequently detected emerging contaminants in groundwater. The objective of this study is to understand how the non-trivial toxicity of BPA affects the estimation of human health risks and, consequentially, aquifer resilience. Based on our results, we aim to provide indications on how to improve water resources management in BPA contaminated sites. We use numerical methods to model BPA contamination of a three-dimensional aquifer, and human health risks and aquifer resilience are estimated at a control plane representing an environmentally sensitive target. A Monte Carlo simulation is conducted to compute uncertainty associated with two levels of heterogeneity. In order to evaluate health risks due to BPA, two types of Dose-Response (DR) models are considered: the monotonic DR model for general exposure and the non-monotonic DR model for prenatal/postnatal exposure. The aquifer resilience is defined as the capacity to recover the state where water is considered potable (i.e., negligible health risks due to BPA). When using the non-monotonic DR model, computational results indicate that the aquifer resilience (reduces) decreases and its uncertainty increases as the aquifer heterogeneity increases. On the other hand, the aquifer resilience considering the monotonic DR model (enhances) increases, and its uncertainty increases relatively smaller than the one considering the non-monotonic DR model. In addition, the variability of the aquifer resilience is controlled by the residence time of the BPA plumes at the control plane, which is related to the volumetric flow rate at the front side of the contamination source. Finally, the decision making strategy for BPA contaminated sites should be established in accordance with the heterogeneous structure of aquifer and land uses that determine which DR model of BPA is more important in estimating the aquifer resilience.

Over the last 30 years, constructed wetlands (CWs) have been used as an alternative, cost-efficient way of treating wastewater, mainly in combination with conventional wastewater technologies. When CWs are attached at the end of conventional wastewater treatment plants, they adequately remove pollutants and thus provide a polishing step. However, recent studies have shown that when CWs are used as a main wastewater treatment method for agricultural reuse of effluents, they perform poorly on meeting the accepted limit of microbial contamination. Moreover, CWs are increasingly used within the scope of circular economy and water reuse applications. Therefore, there is a need for a comprehensive exploration of the performance of CWs on pathogen removal. This paper explores relevant case studies regarding pathogen removal from constructed wetlands in order to create a comprehensive dataset that provides a complete overview of CWs performance under various conditions. After performing a systematic literature review, a total of 48 case studies qualified for both qualitative and quantitative analyses. From the dataset, the general performance, optimal conditions, and knowledge gaps were identified. The review confirmed what was already known, that constructed wetlands (as a standalone treatment) cannot meet the accepted limits of pathogen removal. However, they can be a credible choice for wastewater polishing when they are combined with conventional wastewater treatment systems. Regarding the most common indicators that were recorded, the removal of Escherichia coli ranged between 0.01-5.6 log, the removal of total and fecal coliforms was 0.2-5.32 and 0.07-6.08 log respectively while the removal of fecal streptococci was 0.2-5.2 log. The great variability on pathogen removal indicates that the complexity of CWs makes it difficult to draw robust conclusions regarding their removal efficiency. Moreover, the inadequate reporting of extractable data and CW conditions (except hydraulic characteristics) in the reviewed papers, made it difficult to validate any relationship between CW performance and external parameters. However, the spatial distribution of case studies in the climatic zones around the world indicated a potential statistical correlation between temperature and removal of pathogens. Finally, the dataset can be used as a benchmark of CWs performance as a barrier against the spreading of pathogens in the environment. The knowledge gaps identified in this review can provide direction for further research. A potential meta-analysis of the dataset using statistical analysis can pave the way for a better understanding of the design and operational parameters of CWs in order to fine-tune and quantify the factors that influence the performance of these systems.

One of the challenges to managing water resources and understanding their sources is the heterogeneity created by interactions among hydrological, ecological and anthropological processes and how it is best characterized. An option recently applied to other scientific disciplines is identifying and analyzing the emergent phenomena of complex systems or networks, which are far from equilibrium and whose components self-organize into novel structures/processes via their collective interactions with each other and the environment. A new level of organization and complexity emerges that cannot be predicted from or attributed to the components alone. Deriving predictions based on functionally emergent properties (top-down) of watershed systems differs considerably from making predictions based on reductionist models (bottom-up) of those systems.

River networks have been shown to function as hierarchically nested processes from which stability emerges as a property that buffers variation and extreme events. It is the connectivity and interactions (over a range of spatiotemporal scales) among geomorphic and hydrologic components of watersheds or river networks that give rise to the emergent properties. There are a number of statistical and representative sampling techniques available to identify and quantify component connectivity, the importance of which is exemplified by the extent to which connectivity affects the way that rainfall events alter moisture, heat and carbon fluxes associated with drought. In essence, events transmit information through connected components of watersheds, such that accrued information is at the root of a system’s emergent properties. This presentation highlights some of the ways that emergent properties, which have been influential in expanding the perspectives applied to other sciences, are now being applied to water resources and the associated systems.

Solute transport in groundwater is characterized by a high level of uncertainty since it is impossible to completely measure the spatial distribution of key soil properties, such as the hydraulic conductivity. Several studies have shown how an heterogeneous hydraulic conductivity field may lead to the formation of preferential channels (or high conductivity channels) in which the solute flows. Given a realization of the hydraulic conductivity field, it is possible to estimate the location of preferential channels using a graph-theory based method. The minimum hydraulic resistance and least resistance path are efficiently computed, so that these metrics can be effectively employed to assess the uncertainty of preferential flows using computationally intensive stochastic methods, such as Monte-Carlo simulations. For example, these metrics can be used for site characterization, choosing locations where to sample the hydraulic conductivity in order to reduce the uncertainty of high conductivity channels. As a consequence, our preliminary studies displayed more than 40% reduction on first arrival time uncertainty, when compared to a regular grid sampling protocol with the same number of sampling locations. The iterative sampling strategy can be reproduced using LazyMole, an open-source tool implementing the algorithms to compute the minimum hydraulic resistance and least resistance path for a given hydraulic conductivity field.

The fifth evaluation report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) of the United Nations mentions that extreme rainfall might increase its intensity and frequency in most mid-latitude locations and tropical regions by the end of this century, as a consequence of the rise of the average global surface temperature. Human actions provoked global warming which manifests with an increase in extreme rainfall. These climatic conditions together with the urban development generated a scenario of growing concern for the managers of drainage systems. The objective of drainage networks is preventing the accumulation of rainwater on the surface. Under the new conditions of climate change, the urban drainage systems need to be adapted.

The following article describes a method for flood control by using a rehabilitation model. The method uses a genetic algorithm that iteratively calls the SWMM 5 hydraulic model to perform a hydraulic analysis to search solutions. The results consist of a Pareto front relating investment versus damage. The stakeholders might use this information to adopt the best solution.

This method includes a hydraulic control strategy by using a local head loss in the drainage network, allowing the upstream flow to be retained by decreasing the downstream concentration time. This head loss represents a control device in the beginning of some pipes that come out of storm tanks. As a case study, the method was applied in a section of the drainage network of the city of Bogotá.