A Statistical Framework for Evaluating the Effectiveness of Vegetation Management in Reducing Power Outages Caused during Storms in Distribution Networks

This paper develops a statistical framework to analyze the effectiveness of vegetation management at reducing power outages during storms of varying severity levels. The framework was applied on the Eversource Energy distribution grid in Connecticut, USA based on 173 rain and wind events from 2005–2020, including Hurricane Irene, Hurricane Sandy, and Tropical Storm Isaias. The data were binned by storm severity (high/low) and vegetation management levels, where a maximum applicable length of vegetation management for each circuit was determined, and the data were divided into four bins based on the actual length of vegetation management performed divided by the maximum applicable value (0–25%, 25–50%, 50–75%, and 75–100%). Then, weather and overhead line length normalized outage statistics were taken for each group. The statistics were used to determine the effectiveness of vegetation management and its dependence on storm severity. The results demonstrate a higher reduction in damages for lower-severity storms, with a reduction in normalized outages between 45.8% and 63.8%. For high-severity events, there is a large increase in effectiveness between the highest level of vegetation management and the two lower levels, with 75–100% vegetation management leading to a 37.3% reduction in trouble spots. Yet, when evaluating system reliability, it is important to look at all storms combined, and the results of this study provide useful information on total annual trouble spots and allow for analysis of how various vegetation management scenarios would impact trouble spots in the electric grid. This framework can also be used to better understand how more rigorous vegetation management standards (applying ETT) help reduce outages at an individual event level. In future work, a similar framework may be used to evaluate other resilience improvements.

Biological response to hydrodynamic factors in estuarine-coastal systems: a numerical analysis in a micro-tidal bay

Phytoplankton primary production in coastal bays and estuaries is influenced by multiple physical variables, such as wind, tides, freshwater inputs or light availability. In a short-term perspective these factors may influence the composition of biological variables such as phytoplankton biomass, as well as the amount of nutrients within the waterbody. Observations in Fangar Bay, a small, shallow, stratified and micro-tidal bay in the Ebro Delta (NW Mediterranean Sea), have shown that during wind episodes the biological variables undergo sudden variations in terms of concentration and distribution within the bay. The Regional Ocean Model System (ROMS) coupled with a nitrogen-based nutrient, phytoplankton, zooplankton, and detritus (NPZD) model has been applied to understand this spatio-temporal variability of phytoplankton biomass in Fangar Bay. Idealised simulations prove that during weak wind events (< 6 m·s−1), the stratification is maintained and therefore there is not dynamic connection between surface and bottom layers, penalizing phytoplankton growth in the whole water column. Conversely, during intense wind events (> 10 m·s−1) water column mixing occurs, homogenising the concentration of nutrients throughout the column, and increasing phytoplankton biomass in the bottom layers. In addition, shifts in the wind direction generate different phytoplankton biomass distributions within the bay, in accordance with the dispersion of freshwater plumes from existing irrigation canals. Thus, the numerical results prove the influence of the freshwater plume evolution on the phytoplankton biomass distribution, which is consistent with remote sensing observations. The complexity of the wind-driven circulation due to the bathymetric characteristics and the modulation of the stratification implies that the phytoplankton biomass differs depending on the prevailing wind direction, leading to sharp Chl a gradients and complex patterns.

Seasonal dispersal of fjord meltwaters as an important source of iron and manganese to coastal Antarctic phytoplankton

Glacial meltwater from the western Antarctic Ice Sheet is hypothesized to be an important source of cryospheric iron, fertilizing the Southern Ocean, yet its trace-metal composition and factors that control its dispersal remain poorly constrained. Here we characterize meltwater iron sources in a heavily glaciated western Antarctic Peninsula (WAP) fjord. Using dissolved and particulate ratios of manganese to iron in meltwaters, porewaters, and seawater, we show that surface glacial melt and subglacial plumes contribute to the seasonal cycle of iron and manganese within a fjord still relatively unaffected by climate-change-induced glacial retreat. Organic ligands derived from the phytoplankton bloom and the glaciers bind dissolved iron and facilitate the solubilization of particulate iron downstream. Using a numerical model, we show that buoyant plumes generated by outflow from the subglacial hydrologic system, enriched in labile particulate trace metals derived from a chemically modified crustal source, can supply iron to the fjord euphotic zone through vertical mixing. We also show that prolonged katabatic wind events enhance export of meltwater out of the fjord. Thus, we identify an important atmosphere–ice–ocean coupling intimately tied to coastal iron biogeochemistry and primary productivity along the WAP.

Update article: applicability of artificial neural networks to integrate socio-technical drivers of buildings recovery following extreme wind events

In a companion article, previously published in Royal Society Open Science , the authors used graph theory to evaluate artificial neural network models for potential social and building variables interactions contributing to building wind damage. The results promisingly highlighted the importance of social variables in modelling damage as opposed to the traditional approach of solely considering the physical characteristics of a building. Within this update article, the same methods are used to evaluate two different artificial neural networks for modelling building repair and/or rebuild (recovery) time. By contrast to the damage models, the recovery models (RMs) consider (A) primarily social variables and then (B) introduce structural variables. These two models are then evaluated using centrality and shortest path concepts of graph theory as well as validated against data from the 2011 Joplin tornado. The results of this analysis do not show the same distinctions as were found in the analysis of the damage models from the companion article. The overarching lack of discernible and consistent differences in the RMs suggests that social variables that drive damage are not necessarily contributors to recovery. The differences also serve to reinforce that machine learning methods are best used when the contributing variables are already well understood.

New Theory Connects Tree Uprooting and Sediment Movement

Tree throw from extreme wind events plays an important role in the movement of sediment and erosion on forested hillslopes. A new theory offers a novel way to measure its impact.

Sedimentology and numerical modelling of aeolian sediment dispersal, McMurdo Sound, southwest Ross Sea, Antarctica

<p>Large volumes of aeolian sand and dust are deflated from unconsolidated till deposits, and supraglacial debris surrounding McMurdo Sound, Antarctica. This material is transported offshore with windblown snow onto extensive winter-formed sea ice in the southwest Ross Sea, and is subsequently released into the water-column during summer sea ice breakup. Aeolian sediment samples were collected from a ~600 km² area of sea ice in western McMurdo Sound to determine the magnitude of deposition and identify sediment sources. A new 2-dimensional numerical aeolian sediment transport model (NaMASTE) tuned specifically for the McMurdo Sound area, was used to explore the ability of the local wind system to move sediment from source areas to sea ice and to determine the pattern and extent of aeolian sediment dispersal to the southwest Ross Sea. Debris deposits on the McMurdo Ice Shelf debris bands are the most dominant sediment source for the area. Unconsolidated deposits between Cape Bernacchi and Spike Cape, and the Taylor Valley mouth are significant secondary deposits. Mass accumulation rates varied between 0.15 g m⁻² y⁻¹ and 54.6 g m⁻² y⁻¹, equating to a background aeolian sediment accumulation rate, excluding extremely high values, of 1.14 ± 0.59 g m⁻² y⁻¹ for the McMurdo Sound coastal sea ice zone. This is 3–5 orders of magnitude more than global background dust fallout for the Ross Sea. Modal grain size is very-fine sand to coarse silt. Notably, much of this material is distributed in localised, high sand content plumes that are oriented downwind from source, with finer deposits found outside these zones. An average seafloor linear sedimentation rate of 0.2 cm ky⁻¹ is calculated for McMurdo Sound, which is minor compared to biogenic sedimentation for the region. This equates to ~0.7 Gg y⁻¹ aeolian sediment entering McMurdo Sound during sea ice melt. Application of NaMASTE successfully simulated the general aeolian sediment distribution pattern. Testing of model variables suggests that aeolian material is mainly transported during strong (>20 m s⁻¹) wind events. Modelling also suggests aeolian material from McMurdo Sound can be transported north to the Drygalski Ice Tongue, ~250 km from source, but only in very trace quantities.</p>

Sedimentology and numerical modelling of aeolian sediment dispersal, McMurdo Sound, southwest Ross Sea, Antarctica

<p>Large volumes of aeolian sand and dust are deflated from unconsolidated till deposits, and supraglacial debris surrounding McMurdo Sound, Antarctica. This material is transported offshore with windblown snow onto extensive winter-formed sea ice in the southwest Ross Sea, and is subsequently released into the water-column during summer sea ice breakup. Aeolian sediment samples were collected from a ~600 km² area of sea ice in western McMurdo Sound to determine the magnitude of deposition and identify sediment sources. A new 2-dimensional numerical aeolian sediment transport model (NaMASTE) tuned specifically for the McMurdo Sound area, was used to explore the ability of the local wind system to move sediment from source areas to sea ice and to determine the pattern and extent of aeolian sediment dispersal to the southwest Ross Sea. Debris deposits on the McMurdo Ice Shelf debris bands are the most dominant sediment source for the area. Unconsolidated deposits between Cape Bernacchi and Spike Cape, and the Taylor Valley mouth are significant secondary deposits. Mass accumulation rates varied between 0.15 g m⁻² y⁻¹ and 54.6 g m⁻² y⁻¹, equating to a background aeolian sediment accumulation rate, excluding extremely high values, of 1.14 ± 0.59 g m⁻² y⁻¹ for the McMurdo Sound coastal sea ice zone. This is 3–5 orders of magnitude more than global background dust fallout for the Ross Sea. Modal grain size is very-fine sand to coarse silt. Notably, much of this material is distributed in localised, high sand content plumes that are oriented downwind from source, with finer deposits found outside these zones. An average seafloor linear sedimentation rate of 0.2 cm ky⁻¹ is calculated for McMurdo Sound, which is minor compared to biogenic sedimentation for the region. This equates to ~0.7 Gg y⁻¹ aeolian sediment entering McMurdo Sound during sea ice melt. Application of NaMASTE successfully simulated the general aeolian sediment distribution pattern. Testing of model variables suggests that aeolian material is mainly transported during strong (>20 m s⁻¹) wind events. Modelling also suggests aeolian material from McMurdo Sound can be transported north to the Drygalski Ice Tongue, ~250 km from source, but only in very trace quantities.</p>

Brief communication: The anomalous winter 2019 sea-ice conditions in McMurdo Sound, Antarctica

McMurdo Sound sea ice can generally be partitioned into two regimes: (1) a stable fast-ice cover, forming south of approximately 77.6∘ S around March–April and then breaking out the following January–February, and (2) a more dynamic region north of 77.6∘ S that the McMurdo Sound and Ross Sea polynyas regularly impact. In 2019, a stable fast-ice cover formed unusually late due to repeated break-out events. We analyse the 2019 sea-ice conditions and relate them to a modified storm index (MSI), a proxy for southerly wind events. We find there is a strong correlation between the timing of break-out events and several unusually large MSI events.

Time-Dependent Damage Estimation of a High-Rise Steel Building Equipped with Buckling-Restrained Brace under a Series of Earthquakes and Winds

This study investigates the cumulative damage of a 20-story high-rise steel building equipped with buckling-restrained braces (BRB) under the likely occurrence of earthquake and wind events in the design life of the building. The objective of this research is to introduce a method for evaluating the cumulative damage of BRBs under multi-hazard events that are expected to occur during the service life of a high-rise building in order to achieve a safer building. A methodology is proposed using a Poisson point process to estimate the timeline of earthquake and wind events, wherein the events are assumed to be independent in nature. The 20-story high-rise steel building with BRBs is designed according to the Japanese standard and analyzed using the finite element approach, considering nonlinearities in the structural elements and BRBs. The building is analyzed consecutively using the timeline of earthquakes and winds, and the results are compared with those under individual earthquakes and winds. In addition to the responses of the frame such as the floor displacement and acceleration, the damage of BRBs in terms of the damage index, the energy absorption, the plastic strain energy, and the maximum and cumulative ductility factor are evaluated. It is observed that the BRB’s fatigue life under multi-hazard scenarios is a multi-criteria issue that requires more precise investigation. Moreover, the overall building’s performance and BRB’s cumulative damage induced by the sequence of events in the design life of the building is significantly larger than that under an individual event.