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Assumptions of trust in water systems are widespread in higher-income countries, often linked to expectations of “modern water.” The current literature on water and trust also tends to reinforce a technoscientific approach, emphasizing the importance of aligning water user perceptions with expert assessments. Although such approaches can be useful to document instances of distrust, they often fail to explain why patterns differ over time, and across contexts and populations. Addressing these shortcomings, we offer a relational approach focused on the trustworthiness of hydro-social systems to contextualize water-trust dynamics in relation to broader practices and contexts. In doing so, we investigate three high-profile water crises in North America where examples of distrust are prevalent: Flint, Michigan; Kashechewan First Nation; and the Navajo Nation. Through our theoretical and empirical examination, we offer insights on these dynamics and find that distrust may at times be a warranted and understandable response to experiences of water insecurity and injustice. We examine the interconnected experiences of marginality and inequity, ontological and epistemological injustice, unequal governance and politics, and histories of water insecurity and harm as potential contributors to untrustworthiness in hydro-social systems. We close with recommendations for future directions to better understand water-trust dynamics and address water insecurity. 

Traffic noise is one of the leading causes of reductions in animal abundances near roads. Acoustic masking of conspecific signals and adventitious cues is one mechanism that likely causes animals to abandon loud areas. However, masking effects can be difficult to document in situ and the effects of infrequent noise events may be impractical to study. Here, we present the Soundscapes model, a stochastic individual-based model that dynamically models the listening areas of animals searching for acoustic resources (“searchers). The model also studies the masking effects of noise for human detections of the searchers. The model is set in a landscape adjacent to a road. Noise produced by vehicles traveling on that road is represented by calibrated spectra that vary with speed. Noise propagation is implemented using ISO-9613 procedures. We present demonstration simulations that quantify declines in searcher efficiency and human detection of searchers at relatively low traffic volumes, fewer than 50 vehicles per hour. Traffic noise is pervasive, and the Soundscapes model offers an extensible tool to study the effects of noise on bioacoustics monitoring, point-count surveys, the restorative value of natural soundscapes, and auditory performance in an ecological context.