Solving the robustness puzzle: The joint impact of optimization approach, robustness metrics, and scenarios on water resources management under deep uncertainty.

The concept of robustness has been widely used in water resources management to identify solutions that perform satisfactorily across a range of plausible future conditions to increase confidence in decision-making in a deeply uncertain future. However, the selection of an appropriate metric to quantify robustness remains challenging due to the existence of multiple choices reflecting different risk preferences. In addition, different scenarios can be used to represent plausible future conditions, which adds another layer of complexity to solution identification.

Predicting burn probability: Dimensionality reduction strategies enable accurate and computationally efficient metamodeling.

Predicting the probability that a given location will be burnt by a wildfire is an important part of understanding the risk that wildfires pose and how our management actions (e.g., prescribed burning) can reduce this risk.

Water quality modeling in sewer networks: Review and future research directions.

Urban sewer networks (SNs) are increasingly facing water quality issues as a result of many challenges, such as population growth, urbanization and climate change. A promising way to addressing these issues is by developing and using water quality models. Many of these models have been developed in recent years to facilitate the management of SNs.

Integrating modelling and smart sensors for environmental and human health.

Sensors are becoming ubiquitous in everyday life, generating data at an unprecedented rate and scale. However, models that assess impacts of human activities on environmental and human health, have typically been developed in contexts where data scarcity is the norm. Models are essential tools to understand processes, identify relationships, associations and causality, formalize stakeholder mental models, and to quantify the effects of prevention and interventions.