School of Water, Energy and Environment (SWEE)

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Browsing School of Water, Energy and Environment (SWEE) by Publisher "American Geophysical Union (AGU)"

Now showing 1 - 6 of 6
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    The 28 November 2020 landslide, tsunami, and outburst flood – a hazard cascade associated with rapid deglaciation at Elliot Creek, British Columbia, Canada
    (American Geophysical Union (AGU), 2022-02-21) Geertsema, Marten; Menounos, Brian; Bullard, G.; Carrivick, Jonathan L.; Clague, J. J.; Dai, Chunli; Donati, Davide; Ekstrom, Goran; Jackson, Jennifer M.; Lynett, Patrick; Pichierri, M.; Pon, Andy; Shugar, Dan H.; Stead, D.; Del Bel Belluz, J.; Friele, P.; Giesbrecht, Ian J. W.; Heathfield, D.; Millard, Thomas H.; Nasonova, S.; Schaeffer, Andrew; Ward, B. C.; Blaney, D.; Blaney, Erik; Brillon, C.; Bunn, C.; Floyd, W.; Higman, B.; Hughes, Katie E.; McInnes, William; Mukherjee, Kriti; Sharp, Meghan A.
    We describe and model the evolution of a recent landslide, tsunami, outburst flood, and sediment plume in the southern Coast Mountains, British Columbia, Canada. On November 28, 2020, about 18 million m3 of rock descended 1,000 m from a steep valley wall and traveled across the toe of a glacier before entering a 0.6 km2 glacier lake and producing >100-m high run-up. Water overtopped the lake outlet and scoured a 10-km long channel before depositing debris on a 2-km2 fan below the lake outlet. Floodwater, organic debris, and fine sediment entered a fjord where it produced a 60+km long sediment plume and altered turbidity, water temperature, and water chemistry for weeks. The outburst flood destroyed forest and salmon spawning habitat. Physically based models of the landslide, tsunami, and flood provide real-time simulations of the event and can improve understanding of similar hazard cascades and the risk they pose.
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    Bias correction of high-resolution regional climate model precipitation output gives the best estimates of precipitation in Himalayan catchments
    (American Geophysical Union (AGU), 2019-12-14) Bannister, Daniel; Orr, Andrew; Jain, Sanjay K.; Holman, Ian P.; Momblanch, Andrea; Phillips, Tony; Adeloye, Adebayo J.; Snapir, Boris; Waine, Toby W.; Hosking, J. Scott; Allen‐Sader, Clare
    The need to provide accurate estimates of precipitation over catchments in the Hindu Kush, Karakoram, and Himalaya mountain ranges for hydrological and water resource systems assessments is widely recognised, as is identifying precipitation extremes for assessing hydro‐meteorological hazards. Here, we investigate the ability of bias‐corrected Weather Research and Forecasting model output at 5 km grid spacing to reproduce the spatiotemporal variability of precipitation for the Beas and Sutlej river basins in the Himalaya, measured by 44 stations spread over the period 1980 to 2012. For the Sutlej basin, we find that the raw (uncorrected) model output generally underestimated annual, monthly, and (particularly low‐intensity) daily precipitation amounts. For the Beas basin, the model performance was better, although biases still existed. It is speculated that the cause of the dry bias over the Sutlej basin is a failure of the model to represent an early‐morning maximum in precipitation during the monsoon period, which is related to excessive precipitation falling upwind. However, applying a non‐linear bias‐correction method to the model output resulted in much better results, which were superior to precipitation estimates from reanalysis and two gridded datasets. These findings highlight the difficulty in using current gridded datasets as input for hydrological modelling in Himalayan catchments, suggesting that bias‐corrected high‐resolution regional climate model output is in fact necessary. Moreover, precipitation extremes over the Beas and Sutlej basins were considerably under‐represented in the gridded datasets, suggesting that bias‐corrected regional climate model output is also necessary for hydro‐meteorological risk assessments in Himalayan catchments.
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    Continuous isoprene measurements in a UK temperate forest for a whole growing season: effects of drought stress during the 2018 heatwave
    (American Geophysical Union (AGU), 2020-07-08) Ferracci, Valerio; Bolas, Conor G.; Freshwater, Ray A.; Staniaszek, Zosia; King, Thomas; Jaars, Kerneels; Otu‐Larbi, Frederick; Beale, John; Malhi, Yadvinder; Waine, Toby William; Jones, Roderic L.; Ashworth, Kirsti; Harris, Neil
    Isoprene concentrations were measured at four heights below, within and above the forest canopy in Wytham Woods (UK) throughout the summer of 2018 using custom-built gas chromatographs (the iDirac). These observations were complemented with selected ancillary variables, including air temperature, photosynthetically active radiation (PAR), occasional leaf gas exchange measurements and satellite retrievals of normalized difference vegetation and water indices (NDVI and NDWI). The campaign overlapped with a long and uninterrupted heatwave accompanied by moderate drought. Peak isoprene concentrations during the heatwave-drought were up to a factor of 4 higher than those before or after. Higher temperatures during the heatwave could not account for all the observed isoprene; the enhanced abundances correlated with drought stress. Leaf-level emissions confirmed this and also included compounds associated with ecosystem stress. This work highlights that a more in-depth understanding of the effects of drought stress is required to better characterize isoprene emissions.
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    Global changes in 20‐year, 50‐year, and 100‐year river floods
    (American Geophysical Union (AGU), 2021-03-18) Slater, L.; Villarini, G.; Archfield, S.; Faulkner, D.; Lamb, R.; Khouakhi, Abdou; Yin, J.
    Concepts like the 100‐year flood event can be misleading if they are not updated to reflect significant changes over time. Here, we model observed annual maximum daily streamflow using a nonstationary approach to provide the first global picture of changes in: (a) the magnitudes of the 20‐, 50‐, and 100‐year floods (i.e., flows of a given exceedance probability in each year); (b) the return periods of the 20‐, 50‐, and 100‐year floods, as assessed in 1970 (i.e., flows of a fixed magnitude); and (c) corresponding flood probabilities. Empirically, we find the 20‐/50‐year floods have mostly increased in temperate climate zones, but decreased in arid, tropical, polar, and cold zones. In contrast, 100‐year floods have mostly decreased in arid/temperate zones and exhibit mixed trends in cold zones, but results are influenced by the small number of stations with long records, and highlight the need for continued updating of hazard assessments.
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    Spatial sensitivity of river flooding to changes in climate and land cover through explainable AI
    (American Geophysical Union (AGU), 2024-05-01) Slater, Louise; Coxon, Gemma; Brunner, Manuela; McMillan, Hilary; Yu, Le; Zheng, Yanchen; Khouakhi, Abdou; Moulds, Simon; Berghuijs, Wouter
    Explaining the spatially variable impacts of flood‐generating mechanisms is a longstanding challenge in hydrology, with increasing and decreasing temporal flood trends often found in close regional proximity. Here, we develop a machine learning‐informed approach to unravel the drivers of seasonal flood magnitude and explain the spatial variability of their effects in a temperate climate. We employ 11 observed meteorological and land cover (LC) time series variables alongside 8 static catchment attributes to model flood magnitude in 1,268 catchments across Great Britain over four decades. We then perform a sensitivity analysis to assess how a 10% increase in precipitation, a 1°C rise in air temperature, or a 10 percentage point increase in urban or forest LC may affect flood magnitude in catchments with varying characteristics. Our simulations show that increasing precipitation and urbanization both tend to amplify flood magnitude significantly more in catchments with high baseflow contribution and low runoff ratio, which tend to have lower values of specific discharge on average. In contrast, rising air temperature (in the absence of changing precipitation) decreases flood magnitudes, with the largest effects in dry catchments with low baseflow index. Afforestation also tends to decrease floods more in catchments with low groundwater contribution, and in dry catchments in the summer. Our approach may be used to further disentangle the joint effects of multiple flood drivers in individual catchments.
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    Uncertain pathways to a future safe climate
    (American Geophysical Union (AGU), 2024-06-06) Sherwood, S. C.; Hegerl, Gabriele; Braconnot, P.; Friedlingstein, P.; Goelzer, Heiko; Harris, Neil R. P.; Holland, E.; Kim, Hyungjun ; Mitchell, Molly; Naish, Tim; Nobre, P.; Otto-Bliesner, Bette L.; Reed, Kevin A.; Renwick, James; van der Wel, N. P. M.
    Global climate change is often thought of as a steady and approximately predictable physical response to increasing forcings, which then requires commensurate adaptation. But adaptation has practical, cultural and biological limits, and climate change may pose unanticipated global hazards, sudden changes or other surprises–as may societal adaptation and mitigation responses. These poorly known factors could substantially affect the urgency of mitigation as well as adaptation decisions. We outline a strategy for better accommodating these challenges by making climate science more integrative, in order to identify and quantify known and novel physical risks including those arising from interactions with ecosystems and society. We need to do this even–or especially–when they are highly uncertain, and to explore risks and opportunities associated with mitigation and adaptation responses by engaging across disciplines. We argue that upcoming climate assessments need to be more risk-aware, and suggest ways of achieving this. These strategies improve the chances of anticipating potential surprises and identifying and communicating “safe landing” pathways that meet UN Sustainable Development Goals and guide humanity toward a better future.