Property:CSDMS meeting abstract
From CSDMS
This is a property of type Text.
2
For a subset of global deltas, morphological evolution is due to the competing actions of the river, which brings about the delivery of terrestrial sediment, and waves, which redistribute the input sediment across the coastline. Given that there are many such coastlines where waves exert considerable influence worldwide, an improved understanding of the effect of waves on the morphological evolution of coastal delta settings is imperative, especially in view of the perceived declining influence of the river input. Accordingly, this study presents a preliminary numerical model approach applied to investigate the planform evolution of deltaic coastlines due to the interplay between flow discharge and waves. Model simulations were undertaken with the coupled Delft3D and SWAN (Simulating Waves Nearshore) numerical models for fluvial and wave input, respectively. Additionally, the idealized numerical model represents a straight, sandy deltaic coastline interrupted by two fluvial discharge outlets, and, at the same time, affected by waves approaching from a dominant direction. We found that the modelled deltas evolved into diverse shoreline - and - river–mouth forms under varying combinations of wave and river inputs. The modelling approach also makes a preliminary distinction between the relative effects of waves’ significant height (Hs) and incidence angle (αo) on deltaic planform morphological evolution. Future development of the model will focus on critically exploring the interaction between these two key morphodynamic processes along similar natural coastline settings. +
For landscapes to achieve a topographic steady state, they require steady tectonic uplift and climate, and a bedrock that is uniformly erodible in the vertical direction. Basic landscape evolution models predict that incising drainage networks will eventually reach a static geometric equilibrium – that is, the map-view channel pattern will remain constant. In contrast, natural rivers typically incise through heterogeneous bedrock, which can force reorganization of the drainage structure. To investigate how lithological variability can force landscape reorganization, we draw inspiration from formerly glaciated portions of the upper Mississippi Valley. In this region, depth-to-bedrock maps reveal buried dendritic river networks dissecting paleozoic sedimentary rock. During the Pleistocene, ice advance buried the bedrock topography with glacial till, resurfacing the landscape and resetting the landscape evolution clock. As newly formed drainage networks develop and incise into the till-covered surface, they exhume the buried bedrock topography. This then leads to a geomorphic "decision point": Will the rivers follow the course of the bedrock paleodrainage network? Or will they maintain their new pattern? Using a numerical landscape evolution model, we find that two parameters determine this decision: (1) the contrast between the rock erodibility of the glacial till (more erodible) and of the buried sedimentary rock (less erodible) and (2) the orientation of the surface drainage network with respect to the buried network. We find that as the erodibility contrast increases, the drainage pattern is more likely to reorganize to follow the buried bedrock valleys. Additionally, as the alignment of the two networks increases, the surface drainage network also tends to restructure itself to follow the paleodrainage network. However, when there is less contrast and/or alignment, the surface drainage pattern becomes superimposed on the bedrock topography, with streams cutting across buried bedrock ridges. Our results agree with field studies demonstrating that variability in erodibility exerts a first-order control on landscape evolution and morphology. Our findings can provide insight into how lithologic variation affects surface processes, drives drainage reorganization, and creates geopatterns.
For many deltas, their morphology reflects the 100-1000 year balance of wave, tidal, and river-driven sediment fluxes. Human-induced changes to these fluxes can also act on 100-1000 years and therefore influence delta morphology.
Wave, tidal, and river fluxes also change on much shorter (day-to seasonal) timescales. These fluctuations do not work their way into delta morphology immediately, but many studies have indicated substantial relevance, nevertheless.
How to marry these two timescales? In this poster I will investigate the concept of river sediment retention, or trapping efficiency, and its potential to relate seasonality to long-term fluxes. For example, wave, river, and tidal fluxes might each dominate for a few months every year. If the order and respective magnitude of these fluxes throughout the year influence tidal sediment retention, it can affect long-term morphology and make it deviate from a balance based on simple annual averages. +
For paleo environmental studies, a key challenge is to partitioning physical signals operated under multiple spatio-temporal scales. For example, paleo relative sea-level (RSL) data record a combined signal from global ice-ocean mass exchange induced global mean sea-level change and gravitational, rotational and deformational effects, along with regional and local RSL change caused by changing ocean density, groundwater storage and sediment redistribution. Here we present an open-sourced spatio-temporal hierarchical model framework (PaleoSTeHM) that is conceptually suitable for investigating this problem by separating the underlying phenomenon of interest and its variability from the noisy mechanisms by which this underlying process is observed. PaleoSTeHM is built upon a modern, scalable machine-learning framework and offers flexible modelling and analytical choices. In this presentation, we will show some of the modelling choices in PaleoSTeHM along with an example application for Holocene sea level change. Also, we will seek inputs from potential users for this framework in order to make this co-develop framework more sustainable and allows a wide range of paleo-sea level and -climate researchers to easily and robustly incorporate spatio-temporal statistical modeling into their work. +
Fractal geometry is a branch of mathematics pioneered by Benoit Mandelbrot in the 1970's with the goal of finding a mathematically rigorous way to define the geometry found in nature, including what he saw in river networks. Since then, much work on the geometry and structure of river networks has involved fractal method, from passing mention to assumed fractal characteristic's to trying to tie older geomorphic parameters to Mandelbrot's fractal math. However results on the fractal dimensions of river networks have been contradictory and not always well matched to theoretical explanations of fractal geometry. For example, in a 1988 work, Tarboton et al. found that the measured fractal dimension of river networks transitioned from close to 1 at small scales to close to 2 at large scales. They attributed this to switching from a regime where fractal dimension was dominated by Sinuosity to one where it was dominated by the branching characteristics of rivers. Neither of these matches Mandelbrot's prediction of a fractal dimension of 1.2 for river networks, which he derived from a Hack exponent of 0.6, used in the relation between stream length and basin area, which would likely be influenced by river branching. More recent unpublished calculation of the fractal dimension of large North American river basins found a dimension close 1.1, which conveniently would correspond to a Hack exponent of 0.55 which matches more recent empirical work on Hack's law. To better understand the connection between fractal dimension and Hack's Law, in this poster I present work comparing the fractal dimension of modeled river networks to physical ones, and look at what theoretical parameters may explain them variability in measured fractal dimensions of river networks. +
Fresh impetus has been given to efforts for a unified bio+geo understanding of seafloor physical properties. In part the requirement comes from practical needs in: the dependability of automated modules (Autonomous Underwater Vehicles), for object detection (e.g. unexploded ordinance), and for more accurate Acoustic Seafloor Classification in habitat mapping. By the combination of various techniques, and especially new information resources, the opportunities for fresh advancement in the field have recently increased.
The new information resources include semantic structures such as Encyclopedia of Life, WoRMS, Traitbank and others where the characteristics of organisms are described, including their lifecycles, engineering activities, morphologies. They also include environmental databases of ever increasing resolution and scope, such as photosynthetically available radiation, sediment types, water flows, particulate matter and nutrients.
The challenge is a significant one, to combine these factors, but there are some approaches which have been tested and found very promising. Some are described in this poster. They include simulations (rather than analytical models) with data formats derived from the 3D printing industry, agent-based approaches, population models of various types (including cellular models), and more.
Global change, often human-induced, is causing a re-balancing between 'barren' sediment-dominated areas and those which are intensely colonized. Models such as these are required to see ahead to the consequences and management of the changes. +
Freshwater inflow plays a substantial role in the water quality of coastal and estuarine watersheds and ecosystems. The salinity of an estuary can vary depending on the amount of freshwater received. In highly managed systems, such as St. Lucie and Caloosahatchee estuaries in south Florida, USA, understanding total freshwater inflow and the sources of inflow is very important for management decision-making. There is very little information on the quantity of freshwater inflow to St. Lucie and Caloosahatchee estuaries from their ungauged tidal basins. This study examines a linked hydrologic, hydraulic, and watershed water quality model (WaSh) for simulating freshwater inflow to these two systems. The WaSh model is a time-dependent simulation model that represents basic surface hydrology, groundwater flow, surface water flow, and water quality fate and transport. The WaSh model consists of four basic components; a cell-based representation of the watershed basin land surface, a groundwater component, a surface-water drainage system, and a water management component that can consider the effects of reservoirs, stormwater treatment areas, irrigation supply and demand, and land-use changes. The model is capable of simulating hydrology in watersheds with high groundwater tables and dense drainage canal networks, which is typical in South Florida.
The model was developed using long-time series of rainfall, temperature, evapotranspiration, basin boundaries, hydrography including streams and canals features, soils, land use, and land surface elevations. The results indicate that the model accurately simulates the distribution of freshwater over the coastal watersheds and the transport of freshwater through the estuary and that it is a valuable tool for understanding the dynamics of freshwater inflow to estuaries in coastal watersheds.
Keywords: Coastal Hydrology, Ungauged basin, WaSh model, estuary, Salinity, hydrologic and hydraulic model, water quality
Freshwater resources in coastal Bangladesh fluctuate with extreme periods of shortage
and abundance. Bangladeshis have adapted to these alternating periods but are still
plagued with scarce drinking water resources due to pond water pathogens, salinity of
groundwater, and arsenic contamination. The success of attempts to correct the
problem of unsafe drinking water have varied across the southern Bangladesh as a
result of physical and social factors. We use a multicriteria decision analysis (MCDA) to
explore the various physical and social factors that influence decisions about freshwater
technologies and management schemes in southern Bangladesh.
MCDA is a holistic, analytical tool for evaluation of alternatives. MCDA is used to
support public participation and provide structured, rational, and transparent solutions to
complex management problems. To determine the best freshwater technologies and
management schemes, we examine four alternatives, including managed aquifer
recharge (MAR), pond sand filter (PSF), rain water harvesting (RWH), and tubewells
(TW). Criteria are grouped into four categories: environmental, technical, social, and
economic. Weighting of social factors will be determined by community surveys, nongovernmental
organizations (NGO) opinions, and academic interviews. Data
include regional water quality perceptions, perceptions of management/technology
success, MAR community surveys, and interviews with NGO partners. Environmental
and technical feasibility factors are determined from regional water quality data,
geospatial information, land use/land change, and regional stratigraphy.
Survey data suggest a wide range of criteria based on location and stakeholder
perception. MAR and PSF technologies likely have the greatest environmental and
technical potential for success but are highly influenced by community dynamics,
individual perspective, and NGO involvement. RWH solutions are used less frequently
due to quantity limitations but are most successful at reducing the water security threats
of contamination by pathogens, arsenic, and salts. This MCDA informs us of community
and stakeholder water resource decisions, specifically related to their objectives and
values.
From the classic U-shaped glacial valley to the convex soil-mantled hillslope, geomorphic processes leave clear signatures on the landscapes they create. However, it has been challenging to develop topographic metrics that can be used to extract process parameters. While researchers have gained significant insights into geomorphic processes through metrics like mean local relief, channel steepness, and ridgetop curvature, it is still difficult to make quantitative predictions about processes from quantitative topographic measurements.
Prior modeling work has found that in 2D models that combine stream incision with diffusive hillslope processes, valley spacing is strongly controlled by the relative rates of advective and diffusive processes (Perron et al. 2008). In this work we train a simple convolutional neural network to predict the ratio of the coefficient of stream erosion (K) and coefficient of diffusion (D) used to generate the model topography. Across a test set of 1800 model runs with different K and D values, the network had a normalized root mean square error of 0.03, showing that convolutional neural networks have significant promise for extracting complex and geomorphically meaningful topographic signatures.
In this work we focus on interpreting the neural network to try to help explain what it is calculating in a theoretically grounded way. The output of activation maximization, Fourier analysis, neuron ablation, and other interpretability techniques are complicated, but might imply that the network is detecting patterns that are geographically meaningful. This poster will present these interpretability results. +
A
GEOtop 1.145 is used to model the thermal and hydrological state of the subsurface in the Kuparuk basin, Alaska. GEOtop is a distributed hydrological model with coupled water and energy budgets. The surface energy balance scheme includes sensible, latent and radiative heat fluxes at the air-soil or air-snow interface. The subsurface represents heat fluxes in the vertical and water fluxes in the vertical and horizontal directions. The ERA-Interim atmospheric reanalysis product, which is used to force the model, is compared to meteorological and radiation data from the Kuparuk Basin and other stations on the North Slope of Alaska. The use of ERA-Interim reanalysis to force GEOtop enables large-scale simulations to be performed over areas where in situ meteorological data is sparse, such as the North Slope of Alaska. Model simulations forced by ERA-Interim reanalysis data are validated using borehole observations of soil temperature. Model results will be presented demonstrating the interactions between soil properties, snow cover, vegetation and climate. +
2
Geophysical datasets, thermal modelling, and drilling data suggest that most Arctic shelves are underlain by submarine permafrost due to their exposure during the glacial low water stands. The degradation of subsea permafrost depends on the duration of inundation, warming rate, the coupling of the seabed to the atmosphere from bottom-fast ice, and brine injections into the seabed. The impact of brine injections on permafrost degradation is dependent on seawater salinity, which changes seasonally in response to salt rejection from sea ice formation and terrestrial freshwater inflows. The relative importance of the upper boundary conditions responsible for permafrost table degradation rates, however, remain poorly understood. This study evaluates the effects of changing upper boundary conditions on subaquatic permafrost thaw rates using CRYOGRID, a one-dimensional heat diffusion model, which was extended to include coupled dissolved salt diffusion. More specifically, the impacts of using a seasonally varying seabed temperature function compared to a mean annual seabed temperature for both freshwater and saline water bodies were assessed. For saline conditions, the effects of different salinity regimes at the seabed, including mean annual concentrations and seasonal variations. Daily observations of seabed temperature and electrical conductivity from 01-09-2008 to 31-08-2009 offshore of Muostakh Island in Siberia were used to set up the upper boundary conditions for the base case model runs. For saline water bodies, sensitivity analyses for mean annual salt concentrations and seabed sediment type were also performed. In all model runs, a steady-state heat conduction function was used to calculate the initial ground thermal regime prior to inundation. The initial state of permafrost was assumed to contain no salt and the ramp-up time from a terrestrial to a sub-aquatic upper boundary condition was one year for all simulations. Generally, it was found that using a mean annual seabed temperature overestimates subaquatic permafrost thaw for shallow freshwater by approximately 2 metres after 65 years of inundation. Seasonal variation of the seabed temperature led to seasonal freezing and thawing of the sea bed. However, for water bodies with high mean annual concentrations of salt (i.e. 420 moles NaCl/m3), it was found that the difference between using mean annual versus seasonally varying seabed temperatures was negligible. Dissolved salts below the seabed depress the pore water freezing point sufficiently to prevent ice formation in the near-surface sediment despite sub-zero winter temperatures. Given the current trend of freshening in the Arctic Ocean, we expect seasonal freezing of the seabed to be more common for newly submerged permafrost caused by coastal erosion, and thus potentially leading to slower permafrost table degradation rates.
Glacial erosion has shaped many high mountain belts during the cold periods of the Late Cenozoic. Theoretical models of glacial erosion generally link the pace of erosion to some subglacial properties including basal sliding, basal thermal regime, and effective water pressure. The energy balance of glaciers is a strong control on these properties and therefore, has a potential impact on glacial erosion. Specifically, the geothermal heat from the bedrock can potentially control the patterns and rates of glacial erosion by changing the basal temperature and the supply of meltwater to the subglacial water system. Here, we investigate the impact of geothermal heat flow on glacial erosion using a coupled model of erosion and ice dynamics. The rate of glacial erosion is modeled as a linear function of the basal sliding velocity. The ice flow is modeled using the Parallel Ice Sheet Model (PISM). PISM solves the conservation of energy using an enthalpy-based scheme, and it links basal sliding to subglacial hydrology through a pseudo-plastic basal resistance model. We model glacial erosion over a synthetic glacial landscape using a range of values for geothermal heat flux. Preliminary results demonstrate that higher geothermal heat flux can increase the total amount of erosion significantly by accelerating the rate of basal sliding and expanding the area of sliding into higher elevations. +
Glacial isostatic adjustment creates characteristic patterns of relative sea level change (RSL) as a function of distance to melting ice sheets (Clark et al., 1978). During the last termination and through the Holocene, regions formerly covered by large ice sheets experienced rapidly falling RSL due to the processes involved in glacial isostatic adjustment (GIA), primarily isostatic uplift. Surrounding this region of uplift is a narrow band that similarly records RSL fall but is interrupted at sometime during the Holocene by a period of sea level rise (i.e. a transgressions) culminating in a high stand. Holocene transgressions and highstands have been well documented in many locations including Norway, Canadian Atlantic coast, the Canadian Pacific coast, Svalbard, the Baltic Sea, and the British Isles (Forman, 2004; Smith et al., 2011; Shugar et al., 2014; Shennan et al., 2018; Vacchi et al., 2018; Rosentau et al., 2021; Creel et al., 2022). We investigate the origins of these Holocene transgressions using GIA/sea level modeling and test the hypothesis that they are the direct result of solid Earth deformation. Our modeling results highlight a unique pattern of solid Earth deformation in which the region of subsidence (peripheral bulge) surrounding the ice sheet migrates first towards and then away from the melted ice mass. We show how this effect, we term ’reverse migration’, is the direct result of the contrast in viscosity between the upper and lower mantle. We compare our GIA model predictions of RSL change to 1) RSL data since the last glacial maximum and 2) constrains on the transgression magnitude in Norway and eastern Canada. Both tests show a preference for GIA models that include a mantle with a substantial (1-2 orders of magnitude) increase in vicosity with depth. This suggests that, in contrast to the conventional view that Holocene transgressions record GMSL temporarily outpacing isostatic uplift, solid Earth deformation and specifically reverse migration played an important role in generating nearfield Holocene transgressions. Finally, by comparing GIA model results to RSL observations, we show how Holocene transgressions can be used to constrain the vertical viscosity structure of the mantle. Our findings suggest that a significant increase in viscosity with depth (1-2 orders of magnitude) likely exists below continents with nearfield transgressions.
Glacial lake outburst floods pose an increasing hazard to communities living downstream of glaciated areas. The Northern Patagonia Icefield has experienced catastrophic glacial lake outburst floods (GLOFs), and understanding past events will help to understand and prepare for future events. This region is vastly understudied, and much research remains to be completed to thoroughly understand such complex phenomena such as GLOFs. Satellite imagery, supplemented by high-resolution UAV imagery derived 3D models, are used to understand the hydrodynamics of a GLOF which took place March 16, 1989, in the Valle Soler of the Northern Patagonia Icefield. Using the 3D model and satellite-derived digital elevation model, flood parameters are calculated in order to describe the 1989 Soler GLOF. The results of this analysis are used to understand mass extraction and gradational fining of moraine material in Valle Soler. Blocks of rock, exceeding 10m, are found throughout the valley and a comparison of peak discharge and the necessary force to deposit the blocks are discussed. +
Glacially-derived debris often blankets alpine streams, yet few models have explicitly linked sediment supply and transport between glacial and fluvial systems. Here, we combine a 1-D river-incision model with a quarrying-dominated glacial erosion model. We link sediment production and supply between the two systems, and include a valley width variable that allows glaciers to widen valleys and temporarily store glacially-derived sediment within those valleys. A lateral erosion factor in the fluvial model re-incorporates this sediment, which is transported using a modified Meyer-Peter and Mueller equation and incorporated into bedrock erosion through a cover effect. We calibrated this model using the DAKOTA calibration software to Holocene glaciated alpine rivers in North America and are able to match observed topography within an acceptable Χ^2 fit of <2. +
Glaciers around the world are retreating in response to climate change, leaving behind tens of thousands of glacier-contact lakes in their wake. Some lake-terminating glaciers have been observed to flow, lose ice mass, and retreat at faster rates than land-terminating glaciers. However, these observations appear to contradict theory, which suggests that the cold, freshwater, and shallow conditions in these lakes should inhibit ice calving and melting—collectively “frontal ablation”—at the glacier terminus. To resolve this discrepancy between theory and observations, we must disentangle the relative influence of surface mass balance and frontal ablation on observed glacier retreat. In this study, we modeled three lake-terminating glaciers on the Juneau Icefield, Alaska (Gilkey, Meade, and Field) from 2005–2019 using a physics-informed ice flow model emulator—the Informed Glacier Model (IGM). We drove IGM with surface mass balance outputs from a COupled Snowpack and Ice surface energy and mass-balance (COSIPY) climate reanalysis model of the Juneau Icefield. These glacier simulations were then compared with LANDSAT-observed glacier terminus positions from 2005-2019 to assess modeled predictions of lake-terminating glacial retreat.
Preliminary results indicate that when the ice flow model is only forced by surface mass balance—as current theory suggests for lake-terminating glaciers—IGM underpredicts observed terminus retreat at all three glaciers. These results suggest that lake-terminating glaciers on the Juneau Icefield are experiencing an additional component of ice mass loss that significantly contributes to terminus retreat. Upcoming modeling work will aim to verify the quality of these preliminary results by performing similar model runs on land-terminating glaciers in the Juneau Icefield (e.g. Lemon Creek Glacier) as a control case. We will also perform field campaigns over 2025-2027 to the Gilkey, Meade, and Field glacier termini to quantify their in-situ ice mass loss rates.
Globally, more people are impacted by floods than all other forms of natural disasters combined. In global megacities, defined by the United Nations as cities with a population of over ten million, increased human exposure to flooding is both ubiquitous and extremely difficult to characterize. Over the past three decades, most of these cities have experienced a gradual or very rapid growth as the global population continues to urbanize. As both urban expansion and global climate change contribute to hydrologic intensification, and as globally more people live in urban areas than rural ones, the need to assess both the drivers and magnitude of flood risk associated with rapid growth in megacities is of critical humanitarian concern. Through a multitemporal analysis (2000, 2010, and 2020) of urban growth modes and urban landscape change detection using the Landsat dataset (ETM+, OLI), we estimate the growth rates and development patterns in ten global megacities (Guangzhou, Tokyo, Lagos, Jakarta, Delhi, Manila, Mumbai, Seoul, Mexico City, New York) representing different global climate zones using machine learning. Trends in runoff magnitudes over the time period are quantified and associated with urban expansion and non-stationarity in regional historical precipitation patterns. Preliminary results showed that the ten cities have experienced major flooding within the last ten years resulting mostly as a result of heavy rainfall. +
Globally, the occurrence of extreme hydrologic events such as flooding is known to be the widespread aftermath of torrential rain and the impacts are adverse and devastating in built areas with proximity to water bodies. An example is the 2012 and 2022 flooding along the Niger and Benue rivers in Nigeria. While Nigeria experiences seasonal flooding during the rainy season, the decadal interval between these two catastrophic flood events and the similarities between the natural and anthropogenic conditions responsible for their occurrence prompted this study. Additionally, some hydrologic characteristics and attributes of these flood events are yet to be evaluated. Hence, for the 2012 and 2022 floods, we estimated and compared the floodwater depths at different sections of the Niger and Benue Rivers using the Floodwater Depth Estimation Tool (FwDETv2.0 and FwDETv2.1) implemented in Google Earth Engine, Jupyter Notebook, and ArcGIS Pro. Since this algorithm requires minimal input (flood inundation map and Digital Elevation Model) which favors data-sparse regions such as Nigeria, the potential for the FwDET tool to automatically quantify flood water depths, an important variable in flood intensity estimation was assessed. This tool could be invaluable in flood management and mitigation studies along the rivers. +
Graphics Processing Units (GPUs) have been shown to be very successful in accelerating simulation in many fields. When they are used to accelerate simulation of earthquakes and tsunamis, a big challenge comes from the use of adaptive mesh refinement (AMR) in the code, often necessary for capturing dynamically evolving small-scale features without excessive resolution in other regions of the domain.
Clawpack is an open source library for solving general hyperbolic wave-propagation problems with AMR. It is the basis for the GeoClaw package used for modeling tsunamis, storm surge, and floods. It has also been used for coupled seismic-tsunami simulations. Recently, we have accelerated the library with GPUs and observe a speed-up of 2.5 in a benchmark problem using AMR on a NVIDIA K20 GPU. Many functions that facilitate the execution of computing kernels are added. Customized and CPU thread-safe memory managers are designed to manage GPU and CPU memory pools, which is essential in eliminating overhead of memory allocation and de-allocation. A global reduction is conducted on each AMR grid patch for dynamically adjusting the time step. To avoid copying back fluxes at cell edges from the GPU memory to the CPU memory, the conservation fixes required between patches on different levels are also conducted on the GPU. Some of these kernels are merged into bigger kernels, which greatly reduces the overhead of launching CUDA kernels. +
Gravel-bedded rivers are shaped during floods. Over time, certain floods do the most “geomorphic work” on river beds and banks by maximizing the product of sediment transport magnitude and frequency. The flood that does the most geomorphic work is known as the “formative flood” - it may not be the peak, but it reoccurs more often. However, it is unclear if this concept applies to freshet-dominated rivers in the Arctic. Gravel-bedded rivers in the Arctic continuous permafrost zone are occupied by river ice for 7-9 months each year. Freshet-dominated rivers in this region, like the Canning River, AK, receive a peak flood following snow melt while river ice can resist breakup for weeks, extending flood duration and magnitude. Still, the spring freshet occurs when hydraulic cross-sections are restricted by bedfast ice, limiting bed and bank exposure, but maximizing stage height. In contrast, summer floods generated by storm runoff occur when ice is absent, multiple times per year. Still, river bank and bed gravel is coarse and difficult to transport under low flows. We aim to investigate which flood maintains the Canning River’s hydraulic geometry, and more generally the hydraulic geometry of all ice-impacted, gravel-bedded rivers.
We explore if there is a formative flood for rivers that develop bedfast river ice with Basement V4. We focus on a 20 km reach of the Canning River in Arctic Alaska, where we monitored break-up period from 2021 through 2024. We use USGS data for realistic peak discharges, ArcticDEM for surface topography, and field measurements of river ice thickness to drive the model. We assess geomorphic significance of bedfast river ice with metrics for potential sediment transport along river bank toes - the main process eroding river banks in this setting.
Initial results suggest that even extreme floods are unlikely to fill the bankfull channel or erode river banks when the channel is free of ice. Conversely, we find that up to 1m of river ice during the spring freshet can induce bank erosion, under a constant discharge of 900 m3/s. For the Canning River, the spring freshet is likely the formative flood. Our findings also suggest that the recurrent development of bedfast river ice over winter leads to wider rivers.
