Integrating water quality data with a Bayesian network model to improve spatial and temporal phosphorus attribution: Application to the Maumee River Basin.

Surface water nutrient pollution, the primary cause of eutrophication, remains a major environmental concern in Western Lake Erie despite intergovernmental efforts to regulate nutrient sources. The Maumee River Basin has been the largest nutrient contributor. The two primary nutrient sources are inorganic fertilizer and livestock manure applied to croplands, which are later carried to the streams via runoff and soil erosion. Prior studies of nutrient source attribution have focused on large watersheds or counties at annual time scales. Source attribution at finer spatiotemporal scales, which enables more effective nutrient management, remains a substantial challenge. This study aims to address this challenge by developing a generalizable Bayesian network model for phosphorus source attribution at the subwatershed scale (12-digit Hydrologic Unit Code). Since phosphorus release is uncertain, we combine excess phosphorus derived from manure and fertilizer application and crop uptake data, flow information simulated by the SWAT model, and in-stream water quality measurements using Approximate Bayesian Computation to derive a posterior that attributes phosphorus contributions to subwatersheds. Our results show significant variability in subwatershed-scale phosphorus release that is lost in coarse-scale attribution. Phosphorus contributions attributed to the subwatersheds are on average lower than the excess phosphorus estimated by the nutrient balance approach currently adopted by environmental agencies. Fertilizer contributes more soluble reactive phosphorus than manure, while manure contributes most of the unreactive phosphorus. While developed for the specific context of Maumee River Basin, our lightweight and generalizable model framework could be adapted to other regions and pollutants and could help inform targeted environmental regulation and enforcement.

Genetic model of the El Laco magnetite-apatite deposits by extrusion of iron-rich melt.

Magnetite-apatite deposits are important sources of iron and other metals. A prominent example are the magnetite lavas at the El Laco volcano, Northern Chile. Their formation processes remain debated. Here, we test the genetic hypothesis that an Fe-rich melt separated from silicate magma and ascended along collapse-related fractures. We complement recent analyses with thermodynamic modelling to corroborate Fe-Si liquid immiscibility evident in melt inclusions at El Laco and present viscometry of Fe- and Si-rich melts to assess the time and length scales of immiscible liquid separation. Using a rock deformation model, we demonstrate that volcano collapse can form failure zones extending towards the edifice flanks along which the ore liquid ascends towards extrusion driven by vapour exsolution despite its high density. Our results support the proposed magmatic genesis for the El Laco deposits. Geochemical and textural similarities indicate magnetite-apatite deposits elsewhere form by similar processes.

Science Translation During the COVID-19 Pandemic: An Academic-Public Health Partnership to Assess Capacity Limits in California.

On the basis of an extensive academic-public health partnership around COVID-19 response, we illustrate the challenge of science-policy translation by examining one of the most common nonpharmaceutical interventions: capacity limits. We study the implementation of a 20% capacity limit in retail facilities in the California Bay Area. Through a difference-in-differences analysis, we show that the intervention caused no material reduction in visits, using the same large-scale mobile device data on human movements (mobility data) originally used in the academic literature to support such limits. We show that the lack of effectiveness stems from a mismatch between the academic metric of capacity relative to peak visits and the policy metric of capacity relative to building code. The disconnect in metrics is amplified by mobility data losing predictive power after the early months of the pandemic, weakening the policy relevance of mobility-based interventions. Nonetheless, the data suggest that a better-grounded rationale for capacity limits is to reduce risk specifically during peak hours. To enhance the connection between science, policy, and public health in future times of crisis, we spell out 3 strategies: living models, coproduction, and shared metrics. (Am J Public Health. 2022;112(2):308-315. https://doi.org/10.2105/AJPH.2021.306576).

Integrating urban traffic models with coastal flood maps to quantify the resilience of traffic systems to episodic coastal flooding.

Sea level rise and coastal floods are disrupting coastal communities across the world. The impacts of coastal floods are magnified by the disruption of critical urban systems such as transportation. The flood-related closure of low-lying coastal roads and highways can increase travel time delays and accident risk. However, quantifying the flood-related disruption of the urban traffic system presents challenges. Traffic systems are complex and highly dynamic, where congestion resulting from road closures may propagate rapidly from one area to another. Prior studies identify flood-related road closures by spatially overlaying coastal flood maps onto road network models, but simplifications within the representation of the road network with respect to the coastline or creeks may lead to an incorrect identification of flooded roads. We identify three corrections to reduce potential biases in the identification of flooded roads: 1. We correct for the geometry of highways; 2. We correct for the elevation of bridges and highway overpasses; and 3. We identify and account for road-creek crossings. Accounting for these three corrections, we develop a methodology for accurately identifying flooded roads, improving our ability to quantify flood impacts on urban traffic systems and accident rates.

Crystal aggregates record the pre-eruptive flow field in the volcanic conduit at Kilauea, Hawaii.

Developing reliable, quantitative conduit models that capture the physical processes governing eruptions is hindered by our inability to observe conduit flow directly. The closest we get to direct evidence is testimony imprinted on individual crystals or bubbles in the conduit and preserved by quenching during the eruption. For example, small crystal aggregates in products of the 1959 eruption of Kilauea Iki, Hawaii contain overgrown olivines separated by large, hydrodynamically unfavorable angles. The common occurrence of these aggregates calls for a flow mechanism that creates this crystal misorientation. Here, we show that the observed aggregates are the result of exposure to a steady wave field in the conduit through a customized, process-based model at the scale of individual crystals. We use this model to infer quantitative attributes of the flow at the time of aggregate formation; notably, the formation of misoriented aggregates is only reproduced in bidirectional, not unidirectional, conduit flow.

When floods hit the road: Resilience to flood-related traffic disruption in the San Francisco Bay Area and beyond.

As sea level rises, urban traffic networks in low-lying coastal areas face increasing risks of flood disruptions. Closure of flooded roads causes employee absences and delays, creating cascading impacts to communities. We integrate a traffic model with flood maps that represent potential combinations of storm surges, tides, seasonal cycles, interannual anomalies driven by large-scale climate variability such as the El Niño Southern Oscillation, and sea level rise. When identifying inundated roads, we propose corrections for potential biases arising from model integration. Our results for the San Francisco Bay Area show that employee absences are limited to the homes and workplaces within the areas of inundation, while delays propagate far inland. Communities with limited availability of alternate roads experience long delays irrespective of their proximity to the areas of inundation. We show that metric reach, a measure of road network density, is a better proxy for delays than flood exposure.

The protective benefits of tsunami mitigation parks and ramifications for their strategic design.

Nature-based solutions are becoming an increasingly important component of sustainable coastal risk management. For particularly destructive hazards like tsunamis, natural elements like vegetation are often combined with designed elements like seawalls or dams to augment the protective benefits of each component. One example of this kind of hybrid approach is the so-called tsunami mitigation park, which combines a designed hillscape with vegetation. Despite the increasing popularity of tsunami mitigation parks, the protective benefits they provide are poorly understood and incompletely quantified. As a consequence of this lack of understanding, current designs might not maximize the protective benefits of tsunami mitigation parks. Here, we numerically model the interactions between a single row of hills with an incoming tsunami to identify the mechanisms through which the park protects the coast. We initialize the tsunami as an N wave that propagates to shore and impacts the coast directly. We find that partial reflection of the incoming wave is the most important mechanism by which hills reduce the kinetic energy that propagates onshore. The protective benefit of tsunami mitigation parks is thus comparable to that of a small wall, at least for tsunamis with amplitudes that are comparable to the hill height. We also show that hills could elevate potential damage in the immediate vicinity of the hills where flow speeds increase compared to a planar beach, suggesting the need to include a buffer zone behind the hills into a strategic park design.

Spatial heterogeneity in subglacial drainage driven by till erosion.

The distribution and drainage of meltwater at the base of glaciers sensitively affects fast ice flow. Previous studies suggest that thin meltwater films between the overlying ice and a hard-rock bed channelize into efficient drainage elements by melting the overlying ice. However, these studies do not account for the presence of soft deformable sediment observed underneath many West Antarctic ice streams, and the inextricable coupling that sediment exhibits with meltwater drainage. Our work presents an alternate mechanism for initiating drainage elements such as canals where meltwater films grow by eroding the sediment beneath. We conduct a linearized stability analysis on a meltwater film flowing over an erodible bed. We solve the Orr-Sommerfeld equation for the film flow, and we compute bed evolution with the Exner equation. We identify a regime where the coupled dynamics of hydrology and sediment transport drives a morphological instability that generates spatial heterogeneity at the bed. We show that this film instability operates at much faster time scales than the classical thermal instability proposed by Walder. We discuss the physics of the instability using the framework of ripple formation on erodible beds.

Linking social, ecological, and physical science to advance natural and nature-based protection for coastal communities.

Interest in the role that ecosystems play in reducing the impacts of coastal hazards has grown dramatically. Yet the magnitude and nature of their effects are highly context dependent, making it difficult to know under what conditions coastal habitats, such as saltmarshes, reefs, and forests, are likely to be effective for saving lives and protecting property. We operationalize the concept of natural and nature-based solutions for coastal protection by adopting an ecosystem services framework that propagates the outcome of a management action through ecosystems to societal benefits. We review the literature on the basis of the steps in this framework, considering not only the supply of coastal protection provided by ecosystems but also the demand for protective services from beneficiaries. We recommend further attention to (1) biophysical processes beyond wave attenuation, (2) the combined effects of multiple habitat types (e.g., reefs, vegetation), (3) marginal values and expected damage functions, and, in particular, (4) community dependence on ecosystems for coastal protection and co-benefits. We apply our approach to two case studies to illustrate how estimates of multiple benefits and losses can inform restoration and development decisions. Finally, we discuss frontiers for linking social, ecological, and physical science to advance natural and nature-based solutions to coastal protection.