A conceptual model of supra‐glacial lake formation on debris‐covered glaciers based on GPR facies analysis

Supra‐glacial lakes and ponds can create hotspots of mass loss on debris‐covered glaciers. While much research has been directed at understanding lateral lake expansion, little is known about the rates or processes governing lake deepening. To a large degree, this knowledge gap persists due to sparse observations of lake beds. Here we report on the novel use of ground penetrating radar (GPR) surveys to simultaneously collect supra‐glacial lake bathymetry and bottom composition data from Spillway Lake (surface area of 2.4 × 10⁵ m²; volume of 9.5 × 10⁴ m³), which is located in the terminus region of the Ngozumpa Glacier in the Khumbu region of the Nepal Himalaya. We identified two GPR bottom signals corresponding to two sedimentary facies of (1) sub‐horizontal layered fine sediment drape and (2) coarse blocky diamict. We provide an understanding of the changes in subaqueous debris distribution that occur through stages of lake expansion by combining the GPR results with in situ observations of shoreline deposits matching the interpreted facies. From this, we present an updated conceptual model of supra‐glacial lake evolution, with the addition of data on the evolving debris environment, showing how dominant depositional processes can change as lakes evolve from perched lakes to multi‐basin base‐level lakes and finally onto large moraine‐dammed lakes. Throughout lake evolution, processes such as shoreline steepening, lakebed collapse into voids and conduit interception, subaerial and subaqueous calving and rapid areal expansion alter the spatial distribution and makeup of lakebed debris and sediments forcing a number of positive and negative feedbacks on lake expansion. Copyright © 2016 John Wiley & Sons, Ltd.     

Large wood inhibits debris flow runout in forested southeast Alaska

Due to their potentially long runout, debris flows are a major hazard and an important geomorphic process in mountainous environments. Understanding runout is therefore essential to minimize risk in the near-term and interpret the pace and pattern of debris flow erosion and deposition over geomorphic timescales. Many debris flows occur in forested landscapes where they mobilize large volumes of large woody debris (LWD) in addition to sediment, but few studies have quantitatively documented the effects of LWD on runout. Here, we analyze recent and historic debris flows in southeast Alaska, a mountainous, forested system with minimal human alteration. Sixteen debris flows near Sitka triggered on August 18, 2015 or more recently had volumes of 80 to 25 000 m³ and limited mobility compared to a global compilation of similarly-sized debris flows. Their deposits inundated 31% of the planimetric area, and their runout lengths were 48% of that predicted by the global dataset. Depositional slopes were 6°–26°, and mobility index, defined as the ratio of horizontal runout to vertical elevation change, ranged from 1.2 to 3, further indicating low mobility. In the broader southeast Alaskan region consisting of Chichagof and Baranof Islands, remote sensing-based analysis of 1061 historic debris flows showed that mobility index decreased from 2.3–2.5 to 1.4–1.8 as average forest age increased from 0 to 416 years. We therefore interpret that the presence of LWD within a debris flow and standing trees, stumps, and logs in the deposition zone inhibit runout, primarily through granular phenomena such as jamming due to force chains. Calibration of debris flow runout models should therefore incorporate the ecologic as well as geologic setting, and feedbacks between debris flows and vegetation likely control the transport of sediment and organic material through steep, forested catchments over geomorphic time. © 2020 John Wiley & Sons, Ltd.     

Impact of recycling and lateral sediment input on grain size fining trends—Implications for reconstructing tectonic and climate forcings in ancient sedimentary systems

Grain size trends in basin stratigraphy are thought to preserve a rich record of the climatic and tectonic controls on landscape evolution. Stratigraphic models assume that over geological timescales, the downstream profile of sediment deposition is in dynamic equilibrium with the spatial distribution of tectonic subsidence in the basin, sea level and the flux and calibre of sediment supplied from mountain catchments. Here, we demonstrate that this approach in modelling stratigraphic responses to environmental change is missing a key ingredient: the dynamic geomorphology of the sediment routing system. For three large alluvial fans in the Iglesia basin, Argentine Andes we measured the grain size of modern river sediment from fan apex to toe and characterise the spatial distribution of differential subsidence for each fan by constructing a 3D model of basin stratigraphy from seismic data. We find, using a self‐similar grain size fining model, that the profile of grain size fining on all three fans cannot be reproduced given the subsidence profile measured and for any sediment supply scenario. However, by adapting the self‐similar model, we demonstrate that the grain size trends on each fan can be effectively reproduced when sediment is not only sourced from a single catchment at the apex of the system, but also laterally, from tributary catchments and through fan surface recycling. Without constraint on the dynamic geomorphology of these large alluvial systems, signals of tectonic and climate forcing in grain size data are masked and would be indecipherable in the geological record. This has significant implications for our ability to make sensitive, quantitative reconstructions of external boundary conditions from the sedimentary record.     

Predicting high-frequency variation in stream solute concentrations with water quality sensors and machine learning

Stream solute monitoring has produced many insights into ecosystem and Earth system functions. Although new sensors have provided novel information about the fine-scale temporal variation of some stream water solutes, we lack adequate sensor technology to gain the same insights for many other solutes. We used two machine learning algorithms – Support Vector Machine and Random Forest – to predict concentrations at 15-min resolution for 10 solutes, of which eight lack specific sensors. The algorithms were trained with data from intensive stream sensing and manual stream sampling (weekly) for four full years in a hydrologic reference stream within the Hubbard Brook Experimental Forest in New Hampshire, USA. The Random Forest algorithm was slightly better at predicting solute concentrations than the Support Vector Machine algorithm (Nash-Sutcliffe efficiencies ranged from 0.35 to 0.78 for Random Forest compared to 0.29 to 0.79 for Support Vector Machine). Solute predictions were most sensitive to the removal of fluorescent dissolved organic matter, pH and specific conductance as independent variables for both algorithms, and least sensitive to dissolved oxygen and turbidity. The predicted concentrations of calcium and monomeric aluminium were used to estimate catchment solute yield, which changed most dramatically for aluminium because it concentrates with stream discharge. These results show great promise for using a combined approach of stream sensing and intensive stream discrete sampling to build information about the high-frequency variation of solutes for which an appropriate sensor or proxy is not available.     

Teleconnections in a warmer climate: the pliocene perspective

Migrations toward altered sea surface temperature (SST) patterns in the Indo-Pacific region are present in the recent observational record and in future global warming projections. These SSTs are in the form of ??permanent?? El Ni?o-like (herein termed ??El Padre??) and Indian Ocean Dipole (IOD)-like patterns. The Early Pliocene Warm Period, which bears similarity to future warming projections, may have also exhibited these Indo-Pacific SST patterns, as suggested by regional terrestrial paleo-climatic data and general circulation model studies. The ability to corroborate this assessment with paleo-data reconstructions is an advantage of the warm Pliocene period that is not afforded by future warming scenarios. Thus, the Pliocene period provides us with a warm-climate perspective and test bed for understanding potential changes to future atmospheric interactions given these altered SST states. This study specifically assesses how atmospheric teleconnections from El Padre/IOD SST patterns are generated and propagate to create the regional climate signals of the Pliocene period, as these signals may be representative of future regional climatic changes as well. To do this, we construct a holistic diagnostic rubric that allows us to examine atmospheric teleconnections, both energetically and dynamically, as produced by a general circulation model. We incorporate KE??, a diagnostic adapted from the eddy kinetic energy generation field, to assess the available energy transferred to these teleconnections. Using this methodology, we found that relative to our Modern Control experiments, weaker atmospheric teleconnections prevail under warm Pliocene conditions, although pathways of propagation still appear directed toward the southwestern United States from our tropical Pacific sector forcing. Propagation directly emanating from the Indian Ocean forcing sector appears to be largely blocked, although indirect teleconnective pathways appear traversing the Asian continent toward the North Pacific. The changes in the atmospheric circulation of Indian Ocean region in response to the underlying specified SST forcing (and indicated by Pliocene paleo-data) may have a host of implications for energy transfer out of and into the region, including interactions with the Asian jet stream and changes to the seasonal monsoon cycle. These interactions warrant further study in both past and future warm climate scenarios.     

The COVID-19 pandemic and global environmental change: Emerging research needs

The outbreak of COVID-19 raised numerous questions on the interactions between the occurrence of new infections, the environment, climate and health. The European Union requested the H2020 HERA project which aims at setting priorities in research on environment, climate and health, to identify relevant research needs regarding Covid-19. The emergence and spread of SARS-CoV-2 appears to be related to urbanization, habitat destruction, live animal trade, intensive livestock farming and global travel. The contribution of climate and air pollution requires additional studies. Importantly, the severity of COVID-19 depends on the interactions between the viral infection, ageing and chronic diseases such as metabolic, respiratory and cardiovascular diseases and obesity which are themselves influenced by environmental stressors. The mechanisms of these interactions deserve additional scrutiny. Both the pandemic and the social response to the disease have elicited an array of behavioural and societal changes that may remain long after the pandemic and that may have long term health effects including on mental health. Recovery plans are currently being discussed or implemented and the environmental and health impacts of those plans are not clearly foreseen. Clearly, COVID-19 will have a long-lasting impact on the environmental health field and will open new research perspectives and policy needs.     

The COVID-19 pandemic and global environmental change: Emerging research needs

The outbreak of COVID-19 raised numerous questions on the interactions between the occurrence of new infections, the environment, climate and health. The European Union requested the H2020 HERA project which aims at setting priorities in research on environment, climate and health, to identify relevant research needs regarding Covid-19. The emergence and spread of SARS-CoV-2 appears to be related to urbanization, habitat destruction, live animal trade, intensive livestock farming and global travel. The contribution of climate and air pollution requires additional studies. Importantly, the severity of COVID-19 depends on the interactions between the viral infection, ageing and chronic diseases such as metabolic, respiratory and cardiovascular diseases and obesity which are themselves influenced by environmental stressors. The mechanisms of these interactions deserve additional scrutiny. Both the pandemic and the social response to the disease have elicited an array of behavioural and societal changes that may remain long after the pandemic and that may have long term health effects including on mental health. Recovery plans are currently being discussed or implemented and the environmental and health impacts of those plans are not clearly foreseen. Clearly, COVID-19 will have a long-lasting impact on the environmental health field and will open new research perspectives and policy needs.     

Drought triggers and declarations: science and policy considerations for drought risk management

This paper explores the value of triggers and declarations in the management of drought, bringing together two disciplinary perspectives, those of the public policy scholar and the climate scientist. These two perspectives highlight the complexity of the development and use of triggers in drought risk management by drawing on the experience of the United States, which has the most sophisticated system of drought triggers in the world, and that of Australia that has the most developed and longest standing national drought policy based on principles of risk management. The paper explores the advantages and disadvantages of triggers in managing drought, concluding that triggers are useful risk management tools at the individual level but become problematic and can lead to perverse outcomes when linked to some forms of government support programs.