Geoprocesses, geohazards - CSDMS 2018
May 22-24th 2018 in Boulder Colorado, USA
Agenda
Click here to view the final agenda
Presentations
Keynote talks
Clinics
| Presented by | Title |
|---|---|
| Irina Overeem | Permafrost Toolbox |
| Sediment Experimentalist Network (SEN) | Sediment Experimentalist Network (SEN) - Wrangling your research data |
| Guy Schumann and Jeffrey Neal | LISFLOOD-FP Clinic: Introduction to Flood Hazard Modeling |
| Steve Roberts and Mariela Perignon | Hydrodynamic modeling using the open source package ANUGA |
| Mark Piper | BMI Live! |
| Nicole Gasparini | Landlab with Hydroshare |
| Katy Barnhart | Model sensitivity analysis and optimization with Dakota and Landlab |
| Cam Wobus and Mark Lorie | Physical and Socio-Economic Data for Natural Hazards |
| Doug Edmonds and Samapriya Roy | An Introduction to using Google Earth Engine |
| Ethan Gutmann | Making Use of Climate Model Output: Downscaling for Regional Applications |
| Chris Jenkins and Jeff Obelcz | Forum on Artificial Intelligence & Machine Learning: What lies ahead for Earth Surface Modeling? |
| Chris Sherwood | How to make accurate digital elevation models using imagery from drones |
Posters
| Name | Abstract title | Poster |
|---|---|---|
| Antolini, Federico | A framework proposal for spatial distribution of small reservoirs | [[Distributed systems of reservoirs (DSR) provide an alternative to large dams and reservoirs for riverine flow regulation and flood management. A DSR consists of temporary, small-in-size reservoirs, or detention ponds, spatially distributed across a watershed. A DSR can be as effective as a single large reservoir in terms of water storage and flow regulation and has overall a limited environmental impact. The effectiveness of a DSR depends, among others, on the number of reservoirs and their locations, making this approach to flood management a geographic problem.
In this work I propose a framework for reservoir modeling and siting. The main research objective is to find the optimal spatial configuration for a DSR that overall maximizes water storage capacity and minimizes reservoir footprint extent and system cost. First, reservoir models are generated on numerous locations along a river network, especially on small streams and tributaries, based on local topography. Shape, geometry and capacity is defined for each candidate reservoir. Then heuristic search is used to find an optimal subset of reservoirs given some spatial and structural cost constraints. Preliminary results for real watersheds in northeastern Iowa suggest that, costs being equal, DSRs with many reservoirs of small average size have a higher storage capacity than DSRs with fewer reservoirs with a larger average size. That represents the necessary first step for future research on the effect of different configurations of DSRs on flood wave magnitude and propagation, assessing the scale of their benefits and comparing benefits with costs and impacts.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Antolini_CSDMS_POSTER_May2018.pdf]] |
| Ashley, Thomas | Statistical Bedload Modeling on the Colorado River in Grand Canyon National Park | [[Acoustic sediment monitoring technology provides a practical means to obtain high resolution estimates of suspended sand flux. However, bed bedload flux can be a significant component of total load and remains difficult to measure directly. In most cases, bedload is treated as a power-law function of water discharge, a constant fraction of suspended sand flux, or ignored. However, bedload flux may vary independently from water discharge or suspended sediment flux in supply-limited rivers due to systematic grain size and reach-geometric effects. We propose a model for bedload flux that enables improved prediction using variables that are routinely measured at acoustic sediment monitoring stations. Though this model is rooted in causal physical theory, it contains several scaling parameters that must be constrained empirically. To this end, we propose a Bayesian statistical procedure that facilitates propagation of uncertainty from multiple sources of information. Application of this procedure is demonstrated at one monitoring station on the Colorado River in Grand Canyon National Park. Repeat bathymetric surveys of dune migration in the reach adjacent to the monitoring station are used to estimate bedload flux, providing an observational basis for statistical analysis. Parameter estimation and prediction are also informed by data from other rivers, which is incorporated in a hierarchical framework. We find that conventional methods of estimating bedload flux fail to capture fluctuations driven by the interaction between flow strength and sediment supply, and can introduce large persistent biases to estimates of total load. Our model is applicable in a wide range of scenarios, and substantially reduces the uncertainty associated with estimating bedload flux in sand bed rivers.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Ashley_CSDMS_POSTER_May2018.pdf]] |
| Barnes, Richard | Efficient Parallel Algorithms For Terrain Analysis | [[To answer geomorphological questions at unprecedented spatial and temporal scales, we need to (a) parse terabyte-scale datasets (DEMs), (b) perform millions of model realizations to pinpoint the parameters which govern landscape evolution, and (c) do so with statistical rigor, which may require thousands of additional realizations.
A core set of operations underpin many geomorphic models. These include determination of terrain attributes such as slope and curvature; flow routing; depression flooding and breaching; flat resolution; and flow accumulation. Here, I present new, best-in-class algorithms which perform the foregoing. I explain how they are implemented in a high-performance, open source C++ library called RichDEM which is accessible to general practitioners via Python. This design is novel among terrain analysis software and I argue that it is necessary for moving the field forward in a way which allows for rapid scientific development and practitioner adoption.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Barnes_CSDMS_POSTER_May2018.pdf]] |
| Best, Üwe | Modelling Wave Action, Surges, Morphodynamics and Vegetation Dynamics: Do Salt Marsh & Mangrove Fringe Coastlines Survive Sea Level Rise? | [[This study aims to fundamentally assess the impact of sea level rise (SLR) on vegetated, muddy coastlines. This includes an assessment of the resilience of coupled salt marsh-mudflat and mangrove fringe-mudflat coastlines under different sea level rise scenarios.
Traditionally, the design of coastal protection measures revolved around the use of hard structures to ensure a certain level of design safety against flooding of the coastal hinterland. However, with the effects of climate change: sea level rise, increased intensities and frequencies of storms; these solutions appear to be unsustainable. Building-with-Nature strategies have reinforced the value of vegetated foreshores, as being capable of allowing for a flexible and adaptive response to climate change. They attenuate wave energy, stabilize and may heighten the foreshore at a rate that matches that of sea level rise. Important parameters related to the resilience of vegetated foreshores to sea level rise are site specific and include sediment supply, wave climate, tidal range, sea level rise rates, type of vegetation cover, vegetation dynamics and topography. Process-based numerical modelling tools are critical towards enhancing the understanding of the processes governing the morphological development of vegetated-mudflat systems. Limited studies have quantified the impact of sea level rise on the resilience of these intertidal systems with a key focus on determining the tipping points and the governing processes for bio-geomorphological development. Therefore, we applied an open-source 2D process-based model (Delft3D) that couples intertidal flow, wave-action, sediment transport, morphodynamic development with the vegetation dynamics for temporal and spatial growth and decay of vegetation and bio-accumulation. The vegetation growth model was developed using MATLAB, which was then coupled with a depth averaged Delft3D model. For the salt marsh species, the growth model was based on that of a population dynamics approach whereas the mangrove growth model was based on a windows of opportunity approach. The model setup was inspired by conditions within the Dutch South Western Scheldt and the Guyana coastline for the salt marshes and mangroves respectively. The numerical model and the coupling approach were validated quantitatively against existing theory, data and laboratory studies; after which the system’s resilience against sea level rise was examined. Spatial equilibrium of the marsh-mudflat system was attained within 120 years with wave action and sediment dynamics being key triggers. The mangrove fringe-mudflat model however attains equilibrium on longer timescales. The subsequent imposition of a 100 year period of rising sea-level (1.1m) in salt marsh-mudflat systems revealed the biomass accumulation as a critical determinant for the drowning rate. Though, initially highly resilient against the exponential increase of sea level rise, the marsh system starts to drown as channels incise the platform after 50-60 years. This corroborates recent studies which predict a decline in the carbon sequestration potential of salt marshes within the North Sea. Contrastingly, the mangrove fringe-mudflat system proved resilient after a 100 year period of extreme SLR and the increases in drag gained from their extensive mangrove root network and the below ground biomass accumulation proved to be the main drivers. However, after 150 years, there is a shift in the nature of the system as it starts to drown. Results show survival for both systems in sediment rich areas. Overall, the model can be applied to assess the vulnerability and resilience of vegetated coastal areas impacted by sea-level-rise worldwide. Thereby, proving to be a useful tool for developing countries where data is scare. Both the Delft3D software and MATLAB tools used in this study are open source and freely available online: https://oss.deltares.nl/web/delft3d. The running of the model requires the use of MATLAB versions 2013 or higher. This software can be attained through purchase, student version or trial online: https://nl.mathworks.com/products/matlab.html. With regards to the hardware required, a standard PC with minimum 8GB RAM. Additionally, the MATLAB source code will be made available via the Environmental Modelling and Software Journal (ESM) once published.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Best_CSDMS_POSTER_May2018.pdf]] |
| Best, Kelsea | Machine Learning to Identify Drivers of Internal Migration in Coastal Bangladesh | [[As climate change and environmental variability increase pressure on vulnerable communities, migration is one possible adaptation strategy. However, the decision to migrate is complex, and environmental factors are rarely the sole drivers of that decision. Rather, the decision to migrate is often influenced by a combination of economic, social, political, and environmental pressures. This is especially true in coastal communities in Bangladesh, where temporary migration has long been a method of livelihood diversification, and researchers are trying to understand how environmental factors influence existing migration flows. This work addresses a gap in current research by beginning to investigate how different “push” and “pull” drivers of migration might have distinctive variables that contribute to the ultimate decision to move or stay. In this study, random forest classification models are applied to a dataset consisting of household surveys from more than 1,200 households in southwestern Bangladesh to directly assess key variables that influence five types of migration in coastal communities: temporary migration within a village due to environmental stress, migration for education, migration for healthcare, migration for trade or commerce, and migration to visit relatives. This work demonstrates that these types of migration do have different drivers, which yields insights into the complex motivations that impact the decision to migrate. However, livelihood variables and individual aspirations were key for all investigated forms of migration. In the process, this work demonstrates that random forest models could be a powerful method for improving predictive accuracy of migration models to better inform migration policy and planning.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Best2_CSDMS_POSTER_May2018.pdf]] |
| Calhoun, Donna | ForestClaw : A parallel, adaptive Cartesian grid library for problems in geophysical hazards modeling | [[Depth averaged, adaptive, Cartesian grid models have been used effectively in the modeling of tsunamis, landslides, flooding, debris flows and other phenomena in which the computational domain can be reasonably approximated by a logically Cartesian mesh. One such code, GeoClaw (D. George, R. J. LeVeque, K. Mandli, M. Berger), is already part of the CSDMS model repository. A new code, ForestClaw, a parallel library based on adaptive quadtrees, has been extended with the GeoClaw library. This GeoClaw extension of ForestClaw gives GeoClaw users distributed parallelism and a C-interface for enhanced interoperability with other codes, while maintaining the core functionality of GeoClaw. We will describe the basic features of the ForestClaw code (www.forestclaw.org) and present results using the GeoClaw extension of ForestClaw to model the 1976 Teton Dam failure. If time permits, we will also describe on-going work to model dispersion and transport of volcanic ash using the Ash3d (H. Schweiger, R. Denlinger, L. Mastin, Cascade Volcanic Observatory, USGS) extension of ForestClaw.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Calhoun CSDMS POSTER May2018.pdf]] |
| Callaghan, Kerry | Coupled groundwater and surface water modelling to visualise lake extent and total terrestrial water storage under a changing climate | [[Large-scale flow-routing algorithms efficiently route water to the ocean, neglecting both inland basins that may be able to form lakes and changing groundwater storage. We add these elements of reality in a simplified and computationally-efficient way, combining groundwater and surface-water routing to simulate changing groundwater levels, surface-water flow pathways, and lake locations and extents through time. The groundwater component is based upon a linear-diffusive model for an unconfined aquifer developed by Reinfelder et al (2013), and surface water is routed through a simple downslope-flow algorithm that differs from most flow-routing algorithms in that it takes into account the elevation of the water surface, and not just the land surface. Our model requires as inputs topography, climatic data (P-ET and winter temperature), and an approximation of hydraulic conductivity based on topographic slope and mapped soils. The model outputs grids of depth to water table and thickness of surface water; the latter depicts any lakes that would form under the topographic and climatic conditions. The model can be run to equilibrium, or, if a starting depth to water table input is provided, for any user-selected length of time. Such solutions are transient only with respect to groundwater movement: surface-water flow is significantly faster, so it is always run to equilibrium. The model allows infiltration when surface water flows across cells that are not fully saturated in the groundwater, and it allows exfiltration and the formation of groundwater-fed lakes where convergent groundwater flow raises the water table above the land surface. We show sample results from this model on a test area. Future work using this model will include global runs since the Last Glacial Maximum, with ground truthing possible using past lake shoreline data. Changing depth to water table plus the surface water storage computed using this model allows computation of changing terrestrial water storage volume through time.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Callaghan CSDMS POSTER May2018.pdf]] |
| Campforts, Benjamin | Landslides in long term landscape evolution models | [[Landscape evolution models (LEMs) are a virtual representation of geomorphic processes as observed in the field or in experimental settings. LEMs offer the flexibility to evaluate a range of interactions between surface processes at timescales which cannot be observed. Notwithstanding the added value of LEMs in unravelling the tectonic-climate-erosion enigma at geological timescales, the use of LEMs to explain real-world earth surface processes remains challenging. For a LEM to be representative for a specific area, field data should be used to calibrate and validate the simulated processes. Notwithstanding the continuously growing database on erosion rates at different spatial and temporal scales, the number of datasets and the area they cover is inversely correlated with the timescale considered. Although more data is thus available at shorter timescales, including them into LEMs is not straightforward as short-term observations are known to reflect the stochasticity of earth surface processes.
In this contribution, we focus on the role landslides, a stochastic hillslope processes in steep mountainous mostly not included in long term LEMs, but strongly reflected in short term field data. We first integrate the formation of landslides and the transport of the thereby generated sediments in a previously developed LEM (TTLEM). Landslide initiation is implemented as a stochastic process depending on a landslide failure index whereas landslide size depends on the slope stability calculated using the Cullman index. The updated model (TTLEM_Sed) is thereafter applied to the New Zealand-Alps where long term erosion measurements and landslide inventories allow to calibrate model parameters. Landslide inventories are traditionally analyzed using statistical relationships between slope stability and conditioning factors such as distance to rivers and distance to active faults. However, the use of conditioning factors in landslide hazard maps is based on empirical observations and lacks physical grounding. Indeed, hillslopes closer to rivers should automatically become more prone to landslides as rivers incise and undercut hillslope foots. The integration of landslides in a LEM now allows to simulate this dynamic interplay over different timescales. By varying the simulated timescale over which the model is run, we identify critical timescales at which a-priori imposed statistical relations between landscape characteristics and landslide occurrence are no longer required and represented by the internal dynamics of the evolving landscape. With TTLEM_Sed, we present an open-source model tool that allows to simulate landslides and sediment propagation. A modelling approach to study landslides is different from classical landslide hazard mapping approaches as it allows to simulate landscapes over longer timescales therefore allowing to identify physical drivers of landslide formation and landslide initiation. Moreover, the explicit integration of landslides in TTLEM_Sed potentially allows for the integration of widely available short-term field data in future model applications. |100px|link=https://csdms.colorado.edu/csdms_wiki/images/]] |
| Chadwick, Austin | Predicting the location of avulsion hazards on deltas in the face of changing discharge regimes and relative sea-level rise | [[On densely populated deltas, the tendency for river channels to catastrophically avulse poses a hazard to human life and property. Previous work has shown that river avulsions preferentially occur around a spatial node with a distance from the shoreline that is controlled by backwater hydrodynamics, the interplay of dynamic river discharge and standing water near the shoreline. Our ability to forecast the location of future avulsion hazards is limited, however, because avulsions are relatively rare and many deltas are experiencing drastic changes in river discharge and sea level due to land-use and climate change. Building upon previous work, we present a predictive model of delta-lobe morphodynamics and repeated avulsion that is applicable to deltas over a range of spatial scales, sediment supplies, flood regimes, and relative-sea-level-rise conditions. In our model, delta lobes build on top of one another, demonstrating a distribution of avulsion lengths that is sensitive to flow regime and relative sea-level change. Variable flood regimes lead to a consistent avulsion length when low flows (less than bankfull) and high flows (greater than bankfull) compete to intermittently fill and scour portions of the backwater reach. The avulsion node is a spatial maximum in channel superelevation set by the downstream extent of low-flow deposition between erosive high-flows, and in general channels avulse farther upstream when high-flow events are more extreme and more frequent. Relative sea-level rise leads to a more variable avulsion node, driven by intermittent retreat and advance of the delta shoreline as the river periodically shifts the distribution of sediment. If rise rates are sufficiently high to sequester all sediment upstream of the river mouth, avulsions occur progressively farther upstream or not at all. These results have implications for the forecasting of avulsion hazards on modern deltas undergoing relative sea-level rise and human management.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Chadwick_CSDMS_POSTER_May2018.pdf]] |
| Chen, Yunxiang | conduitFoam: a one-dimensional subglacial conduit mode | [[Subglacial hydraulics significantly affects the ice dynamics in Greenland and Antarctic ice sheets, however, has been poorly understood due to the lack of data. Here we present an OpenFOAM-based one-dimensional subglacial model, conduitFoam, to study the hydraulics and ice dynamics of polar ice sheets. This model solves the coupled mass conservation equations for ice and water, the momentum and energy conservation equations for water, with a lake-conduit or moulin-conduit system as constraint boundaries. The model is validated using the theoretical solution applied in early melting stage and lake melting stage of the Greenland ice sheet and can be used to infer the subglacial conduit properties and the ice sheet dynamics in both seasonal and diurnal melting situations.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Chen_CSDMS_POSTER_May2018.pdf]] |
| Ciarletta, Daniel | Long Term Risks: Novel Barrier Island Retreat Behaviors Arising from Increasing Rates of Sea Level Rise | [[The hazards faced by retreating barrier island systems to the increased rates of sea level rise predicted over the coming century and beyond lacks historic precedent. Consequently, exploration of the sedimentological record can provide key insights into how barrier systems might behave in the future. Continental shelves around the world preserve records of former barriers as relict deposits, providing a window into past behaviors. These relict barrier deposits are usually considered to originate from purely allogenic processes, or external environmental forcing, with barrier abandonment typically attributed to episodes of increased rate of sea level rise. However, using a cross-shore morphodynamic model, we show that the internal dynamics of migrating barriers can also result in autogenic deposition of relict sediments even under a constant rate of sea level rise. Subsequently, we propose that allogenic forcing from sea level rise and autogenic forcing from internal dynamics might interact to produce novel barrier retreat behaviors, with the potential to be recorded on the seabed by relict deposits. We model barriers through a range of scenarios with interacting autogenic and allogenic forcing, showing that the morphology of deposits might be used to infer the relative influence of external and internal processes. Intriguingly, our results demonstrate that the internal dynamics of barriers can both amplify and dampen losses of shoreface sediment to the seabed during increased rates of rise, in some cases with internal processes increasing the risk of barrier destruction. Future classification of relict deposits in the field could help explain if and when these allogenic/autogenic interactions have taken place, revealing long term hazards to modern barrier systems that have not previously been described.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Ciarletta_CSDMS_POSTER_May2018.pdf]] |
| Cohen, Sagy | The Floodwater Depth Estimation Tool (FwDET) | [[Information on flood inundation extent is important for understanding societal exposure, water storage volumes, flood wave attenuation, future flood hazard, and other variables. A number of organizations now provide flood inundation maps based on satellite remote sensing. These data products can efficiently and accurately provide the areal extent of a flood event, but do not provide floodwater depth, an important attribute for first responders and damage assessment. Here we present a new methodology and a GIS-based tool, the Floodwater Depth Estimation Tool (FwDET), for estimating floodwater depth based solely on an inundation map and a digital elevation model (DEM). We compare the FwDET results against water depth maps derived from hydraulic simulation of two flood events, a large-scale event for which we use medium resolution input layer (10 m) and a small-scale event for which we use a high-resolution (LiDAR; 1 m) input. Further testing is per- formed for two inundation maps with a number of challenging features that include a narrow valley, a large reservoir, and an urban setting. The results show FwDET can accurately calculate floodwater depth for diverse flooding scenarios but also leads to considerable bias in locations where the inundation extent does not align well with the DEM. In these locations, manual adjustment or higher spatial resolution input is required.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Cohen CSDMS POSTER May2018.pdf]] |
| Davis, Brisa | Targeted Adaptive Mesh Refinement for Tsunami Modeling Using Adjoint Equations | [[Tsunami modeling often combines the need for an ocean-wide simulation with the requirement that a small region of the coast (some community of interest) be simulated with a fine level of resolution (often ⅓ arcsecond, less than 10 meters). In the open ocean we might need 1-4 arcminute resolution, but only in regions that the waves have reached. This is addressed in the GeoClaw software package by using adaptive mesh refinement to place higher resolution grids around the waves based on where the water surface height is significant. We present a method of placing higher resolution grids when there is a small region of interest (say, a single coastal community) by using the adjoint equation. Advantages of this new method are presented, including reduced computational times and the capability to refine only the waves that will impact the specific community during a given time range of interest.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Davis_CSDMS_POSTER_May2018.pdf]] |
| Del Vecchio, Joanmarie | Using relict Pleistocene geomorphology to inform future permafrost change | [[A goal of the geomorphology community is to translate our understanding of past and present processes to predict landscape change in the future. Here we present our knowledge about relict permafrost landscapes across central Appalachia, and we propose a framework through which the geologic record and landscape models may be used to predict change in modern permafrost settings. The onset of Quaternary glacial cycles profoundly influenced the pace and pattern of erosion in mid-latitude settings through the development and subsequent degradation of perennially-frozen soils. Lidar-based mapping documents extensive periglacial alteration of the central Appalachian landscape, including solifluction lobes and other mass-wasting features. These features appear aspect-modulated, implying microclimate control. Geomorphic mapping, shallow geophysical imaging and cosmogenic nuclide dating reveal that periglacial erosion sets regolith patterns, subsurface architecture and erosion rates for multiple glacial cycles. Moreover, a combination of slow erosion rates and structural traps means headwater valleys and basins preserve direct records of upland erosional response to climate change, and planned work to core modern peat bogs may provide paleoclimate and paleoecological markers like pollen and leaf waxes in addition to quartz-rich debris for cosmogenic dating. Geologic data can be supplemented by permafrost hydrology models for an improved understanding of both the microclimate and long-term climate controls on periglacial hillslope processes. Informative models pair realistic active layer flow paths, accounting for both infiltration and permafrost thaw, with effective stress calculations to develop more accurate failure depth estimates. Such process-based models will be key to predicting future periglacial landscape change as warming exceeds historical trends.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/]] |
| Duan, Jennifer | Impact of Climate Change on Flood Frequency Curve: Santa Cruz River Case Study | [[Hourly precipitation for one historical (1991-2000) and two future periods (2031-2040 and 2071-2079) were generated using the Weather Research and Forecasting (WRF) Regional Climate Model (RCM). The climate simulations were conducted for the Southwest region of the United States using an hourly temporal and 10 km spatial resolution grid. The boundary forcing for the WRF model was developed by the Hadley Centre for Climate Prediction and Research/Met Office’s HadCM3 model with A2 emission scenario. The precipitation from the RCM-WRF model was bias-corrected using the observed data, and then used to quantify the impact of climate change on the magnitude and frequency of flood flow in the upper Santa Cruz River watershed (USCRW) in southern Arizona. The Computational Hydraulics and River Engineering two-dimensional (CHRE2D) model, a two-dimensional hydrodynamic and sediment transport model, was adapted for surface flow routing. The CHRE2D model was first calibrated using a storm event on July 15th, 1999, and then applied to the watershed for three selected periods. The simulated annual maximum discharges in two future periods were added to the historical records to obtain the flood frequency curve. Results indicate the peak discharges of 100-year, 200-year, and 500-year flood only increased slightly, and the increase is within the 90% confidence interval limits. Therefore, the flood magnitude and frequency curve will not change with the inclusion of projected future climate data for the study watershed.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Duan_CSDMS_POSTER_May2018.pdf]] |
| Ferdowsi, Behrooz | Glassy dynamics of landscape evolution | [[Soil creeps imperceptibly downhill, but also fails catastrophically to create landslides. Despite the importance of these processes as hazards and in sculpting landscapes, there is no agreed upon model that captures the full range of behavior. Here we examine the granular origins of hillslope soil transport by Discrete Element Method simulations, and re-analysis of measurements in natural landscapes. We find creep for slopes below a critical gradient, where average particle velocity (sediment flux) increases exponentially with friction coefficient (gradient). At critical there is a continuous transition to a dense-granular flow rheology. Slow earthflows and landslides thus exhibit glassy dynamics characteristic of a wide range of disordered materials; they are described by a two-phase flux equation that emerges from grain-scale friction alone. This glassy model reproduces topographic profiles of natural hillslopes, showing its promise for predicting hillslope evolution over geologic timescales.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Ferdowsi_CSDMS_POSTER_May2018.pdf]] |
| Ferrier, Ken | Transient relationships between chemical and physical erosion rates in regolith-mantled topography | [[Chemical erosion of regolith is of wide interest due to its role in Earth’s topographic evolution, the supply of nutrients to soils and streams, and the global carbon cycle. Theory and experiments suggest that chemical erosion rates (W) should be strongly controlled by physical erosion rates (E), which affect W by removing weathered regolith and regulating mineral supply rates to the regolith from its underlying parent material. A global compilation of field measurements reveals a wide range of relationships between W and E, with some sites exhibiting positive relationships between W and E, some exhibiting negative relationships, and others exhibiting a flat relationship within uncertainty. Here we apply a numerical model to explore the variety of W-E relationships that can be generated by transient perturbations in E in well-mixed regolith. Our modeling results show that transient relationships between W and E during erosional perturbations can strongly deviate from steady-state relationships. These deviations ultimately result from the time lag in changes in W following imposed changes in E. As a consequence of the lag, a hysteresis develops in plots of W versus E during transients in E. This yields a positive relationship between W and E at some times during a transient perturbation, a flat relationship at other times, and a negative relationship at other times. The shape and duration of these transient hystereses can be modulated by climate and lithology, as the lag time increases linearly with a characteristic regolith production time and decreases with a characteristic mineral dissolution time, both of which are affected by climatic and lithologic factors. Our results show that even in the absence of variations in climate and lithology, however, a range of W-E relationships can be generated by a single perturbation in E. To the extent that these model results capture the behavior of chemical and physical erosion in natural landscapes, these results may aid interpretation of field measurements of W and E.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/]] |
| Glade, Rachel | Modeling the 2-D evolution of blocky landscapes: Coupled model design | [[Large blocks of rock are common in steep landscapes developed in the presence of a resistant lithology. However, the influence of blocks on landscape evolution is not well known. We developed a hybrid discrete-continuum coupled numerical model of hillslope and channel evolution in the presence of blocks (BlockLab). The model consists of a horizontal resistant layer of rock overlying softer, more erodible rock. A channel reach, driven by an external base level forcing, incises through the middle of the domain and provides the base level for the hillslopes. The hillslope model uses a continuum approach to treat depth-dependent production and transport of soil. Retreat of the resistant layer, however, is treated discretely. A relief threshold determines release of discrete blocks from the resistant layer onto the hillslope, where each model cell is either filled with blocks or contains no blocks. These blocks are allowed to weather at a constant rate, and are tracked as they move downslope according to a relief threshold related to their diameter. Once blocks enter the channel, they influence channel evolution by covering the bed and reducing available bed shear stress. A force balance on in-channel blocks determines whether they can move downstream. Blocks in the channel are reduced in size by abrasion according to the shear stresses exerted on them. The presence of blocks affects channel incision rates, in turn influencing evolution of the hillslopes. This is the first model to account for the role of blocks in channel hillslope evolution feedbacks (CHEFs), allowing us to better model the evolution of real landscapes.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Glade_CSDMS_POSTER_May2018.pdf]] |
| Hoffimann, Julio | ImageQuilting.jl: A code for generating 3D stratigraphy from data collected in flume experiments | [[Surface processes are constantly reworking the landscape of our planet with perhaps the most diverse and beautiful patterns of sediment displacement known to humanity. Capturing this diversity is important for advancing our knowledge of systems, and for sustainable exploitation of natural resources by future generations. From a modeler's perspective, great diversity comes with great uncertainty. Although it is understandably very hard to quantify uncertainty about geological events that happened many years ago, we argue that modeling this uncertainty explicitly is crucial to improve our understanding of subsurface heterogeneity, as stratigraphy is direct function of surface processes. In this modeling work (and code), we aim to build realistic stratigraphic models that are constrained to local data (e.g. from wells, or geophysics) and that are, at the same time, subject to surface processes reflected in flume records. Experiments have improved tremendously in recent years, and the amount of data that they generate is posing new challenges to the surface processes community, who is asking more often the question "How do we make use of all this?" Traditional models based on differential equations and constitutive laws are not flexible enough to digest this information, nor were they created with this purpose. The community faces this limitation where the models cannot be conditioned on experiments, and even after exhaustive manual calibration of unobserved input parameters, these models often show poor predictive power. Our choice of inverse modeling and (geo)statistics (a.k.a. data science) was thus made knowing that these disciplines can provide the community with what we need: the ability to condition models of stratigraphy to measurements taken on a flume tank.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/]] |
| Istanbulluoglu, Erkan | A hydroclimatological approach to predicting regional landslide probability using Landlab | [[We develop a hydroclimatological approach to modeling regional shallow landslide initiation by integrating spatial and temporal dimensions of parameter uncertainty to estimate an annual probability of landslide initiation based on Monte Carlo simulations. The physically based model couples the infinite-slope stability model with a steady-state subsurface flow representation and operates in a digital elevation model. Spatially distributed gridded data for soil properties and vegetation classification are used for parameter estimation of probability distributions that characterize model input uncertainty. Hydrologic forcing to the model is through annual maximum daily recharge to subsurface flow obtained from a macroscale hydrologic model. We demonstrate the model in a steep mountainous region in northern Washington, USA, over 2700 km2. The influence of soil depth on the probability of landslide initiation is investigated through comparisons among model output produced using three different soil depth scenarios reflecting the uncertainty of soil depth and its potential long-term variability. We found elevation-dependent patterns in probability of landslide initiation that showed the stabilizing effects of forests at low elevations, an increased landslide probability with forest decline at midelevations (1400 to 2400 m), and soil limitation and steep topographic controls at high alpine elevations and in post-glacial landscapes. These dominant controls manifest themselves in a bimodal distribution of spatial annual landslide probability. Model testing with limited observations revealed similarly moderate model confidence for the three hazard maps, suggesting suitable use as relative hazard products. The model is available as a component in Landlab, an open-source, Python-based landscape earth systems modeling environment, and is designed to be easily reproduced utilizing HydroShare cyberinfrastructure.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Istanbulluoglu_CSDMS_POSTER_May2018.pdf]] |
| Janoff, Arye | A Coastal Geo-economic Model: Property Protection, Federal Buyouts, and Managed Retreat | [[The US east coast is heavily developed, necessitating adaptive approaches to mitigate property and infrastructure risk from storm events and shoreline changes. One soft-structural approach, beach nourishment, comprises artificial shoreline progradation for property protection. Construction of groins, a hard-structural approach, traps alongshore transported sediments, leading to updrift shoreline growth. Groins create a depositional sediment shadow in their lee, shrinking downdrift shorelines, thereby forcing communities to decide whether to protect properties or to retreat. Our research focuses on how these alternative adaptations may affect coastal risk. We present two field scenarios: West Hampton Dunes, NY, which decided to protect downdrift property through beach nourishment, and Oakwood Beach, NY, which decided to accept buyout offers from federal disaster relief funds. We build a coupled geo-economic model to explore management drivers and controls on coastal morphology and real estate and to analyze the emergent indicators within a two-community system. We quantify benefits as a function of beach width, number of housing rows, and federal property buyouts; costs are a function of groin construction, groin maintenance, and beach nourishment. We compare the net benefits of downdrift nourishment, retreat, and groin removal for different groin lengths, background erosion rates, baseline property values, and discount rates. Results elucidate which approach is most beneficial for coastal adaptation, providing a simple framework to compare future strategies for West Hampton Dunes. This geo-economic tool may prove useful as lawmakers continue to scrutinize fiscal implications of alternative adaptations to coastal risks.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Janoff_CSDMS_POSTER_May2018 .pdf]] |
| Kochanski, Kelly | Statistical classification of self-organized snow surfaces | [[Wind-swept snow self-organizes into bedforms. These bedforms affect local and global energy fluxes, but have not been incorporated into Earth system models because the conditions governing their development are not well understood. We created statistical classifiers, drawn from 736 hours of time-lapse footage in the Colorado Front Range, that predict bedform presence as a function of windspeed and time since snowfall. These classifiers provide the first quantitative predictions of bedform and sastrugi presence in varying weather conditions. The flat snow surfaces we saw were all short-lived. The probability that a surface remained flat, rather than bedform-covered, decreased with time and with the average shear stress exerted on the surface by the wind. The most persistent snow features were an erosional bedform known as sastrugi. The likelihood that a surface was covered by sastrugi increased with time and with the highest wind speeds experienced by the surface. These results identify the weather variables which have the strongest effect on snow surfaces. We expect that these variables will inform and feature in future process-based models of bedform growth. Our observations therefore represent a first step towards understanding a self-organized process that ornaments 8% of the surface of the Earth.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Kochanski_CSDMS_POSTER_May2018.pdf]] |
| Kolodin, Jesse | Investigating Artificial Berm-Dune Management Along New Jersey’s Coastline Using a Coupled Geo-Economic Model | [[After Superstorm Sandy impacted the New Jersey coastline in 2012, the state’s primary coastal resiliency plan was to fortify the entire shoreline by constructing large-scale berm-dune systems along the beach. These large artificial dunes, funded entirely by Congress, were constructed with the goal of mitigating future storm damage to houses and infrastructure. Two long-term management questions are 1) is it feasible for a beachfront community to maintain these projects over the long term?; and 2) if not, what fraction of the cost would need to be subsidized? To tackle these questions, we use a “geo-economic” model that captures the natural processes of beach and dune erosion and migration via storm overwash coupled with engineering interventions of beach nourishment and dune construction. The economic portion of the model accounts for the relationship between property values and berm-dune geometry. Previous work suggests that due to their protective and recreational value, higher dunes and wider beaches increase that property values. However, it is unclear whether this relationship holds true for dune protection some years after a storm has occurred as lags in major storm events may lead to perceptions of lower risks. Thus, beachfront communities may place greater value upon viewership and private property, rather than on protection by artificial dunes. By deriving mathematical expressions for optimal berm and dune size as a function of geologic and economic parameters, our model suggests that changes in risk perception can lower property values and therefore reduce the ability of a community to keep up with the costs of maintaining these structures. We are currently testing this hypothesis by analyzing past and present LiDAR imagery (i.e. 2010, 2014, and 2018) and real-estate data from Long Beach Island, NJ.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Kolodin_CSDMS_POSTER_May2018.pdf]] |
| Kozlowski, Estanislao | Multi-scale modelling of microbial lacustrine carbonates with Carbo-CAT and Mounds3D | [[Two numerical forward stratigraphic models are used to explore the origin of carbonate lacustrine strata characteristics at various scales. The large-scale model (Carbo-CAT; Burgess, 2013) focuses on exploring kilometre scale carbonate stratal heterogeneity developing in extensional settings. New developments include spatial distribution of dissolved carbonate in water controlling carbonate production and subsidence produced by various 3D fault configurations. The small-scale model (Mounds3D) investigates the controls on microbial mound development in the metre to decametre scale. Modelled microbial growth includes precipitation and trapping and binding processes. These are affected by energy, slope and spatial distribution of the microbial community. The model incorporates a depth-averaged hydrodynamic model to assess the impact of transported sediment deposition, erosion and trapping and binding in mound development. Numerical experiments using these models show the complex relationship between initial conditions, processes and resulting stratal geometry. For example, large-scale models of carbonate systems developing over relay ramps show that their size, shape and facies distribution is controlled by the combined effect of varying basement surface, the platform ability to keep up with relative water-level rise and sediment transport processes. The tests performed with the small-scale model show that, although the initial bathymetry exerts a first order control on initial location of microbial mounds, the dynamic behaviour of the systems suggests that mound spacing is also controlled by local variations on the hydrodynamic and depositional conditions.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/]] |
| Leonarduzzi, Elena | Towards a landslide warning concept for Switzerland using rainfall thresholds and multi-scale hydrological modeling | [[Landslides are hazardous phenomena affecting mountainous regions worldwide. Our objective is to develop a Warning System for rainfall-induced shallow landslides in Switzerland, where such a dedicated tool is currently missing. Initially, we focused on empirical rainfall thresholds for landslide triggering based on long-term precipitation data and historical landslide inventories. The results showed that, although precipitation is the main triggering factor, event magnitude (intensity) by itself is not sufficient to explain the occurrence of many landslides. To improve the performance, the antecedent soil moisture prior to the rainfall event has to be taken into account, which we explore using a distributed hydrological model. The overall aim is to understand and quantify (a) the geological and hydrologic conditions critical for landslide initiation and (b) the optimal resolutions for hydrological modelling geared towards landslide prediction.
In fact, while slope stability assessment with a geotechnical model requires high resolution topography, the optimal spatial resolution for the computationally expensive hydrological modeling component remains unknown. To address this question, we conducted numerical experiments for a synthetic digital elevation model (DEM) used to simulate a simplified valley. The DEM is an inclined V-shaped domain and simulations are carried out with the coupled hydrologic-land surface model, ParFlow-CLM, in combination with the infinite slope stability model. We tested different slopes, valley convergence angles, soil layering, and permeability contrasts to assess the effect of spatial resolution on the estimation of antecedent soil moisture and the corresponding Factor of Safety. These numerical experiments will help inform comparative simulations for real catchments in Switzerland and Colorado, as we explore the potential of using topographic methods for downscaling of the estimated antecedent soil wetness from coarser to fine scales. In particular, we will explore whether or not the soil-topographic index can provide a viable alternative to running the hydrological model at the very high spatial resolutions needed for the geotechnical model.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/]] |
| Li, Jiao | Embedding Seawall Models in Coastal Flooding Simulations | [[A barrier aware Riemann solver is developed for the shallow water equations in the presence of the sub-grid-scale barriers using an explicit finite volume scheme. Our algorithm guarantees that the barrier-containing cell can be split into two effective cells that are maintained outside of the reset of the grid structure. To avoid time-steps constrained by the size of small cut cells, we redistribute the fluxes computed on those cells engaging a modified h-box method. The solver ensures that water does not cross the barrier when it is not supposed to, maintain large time-steps relative to the cells being cut through and retain the desirable properties. Also, the wet-dry interface, the boundary between cells that are wet (or flooded) and dry are well handled so that quantities going to zero and conservation are carefully integrated into the method. The work is built off of the GeoClaw package so inherits various extensions to tsunami and storm surge simulations.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/]] |
| Li, Jin | Influence of wave-induced currents on sediment transport and coral growth of atolls | [[As one of the three major Asian marginal seas in the western Pacific, the SCS occupies less than 1% total ocean area while accommodating 15% atoll (25434.6 km2) in the globe (GSA, 2009), which mainly distribute in the Xisha, Zhongsha and Nansha Islands. Atolls in the SCS are generally ellipse-shaped with a longer axis extending in the NE-SW direction and a wider southwest reef platform compared to the northeast. One possible explanation ascribed such features to the monsoon circulation (northeast and southwest monsoons blow alternatively in winter and summer) over the SCS (Zeng, 1984). Waves and currents influence the atoll development by (1) sediment suspension and transportation that can influence the transparency of the water, thus the symbiotic algae and the coral growth, (2) supply of dissolved oxygen and nutrient and (3) removal of metabolic wastes under normal weathers, while storm waves can cause large-scaled breakage, transportation and reconfiguration of reefs (e.g. Chappell, 1980; Storlazzi et al., 2005). Yet, little data was available regarding the hydrodynamic conditions of the forereef of the SCS atolls. Here, we conducted in situ tripod mooring observations (ADCP, ADV & CTD) for at least one tide cycle in 15-18 m water depth at the southeast forereef of three typical atolls – Xiaonanxun (NX), Anda (AD) and Kugui (KG) Reef – in the SCS, respectively, and collected coral sediment samples at different zonation of atolls in September 2017. During the observation periods, tide elevations varied by ca.1 m in all the three sites, with the highest 1.16 m in AD and lowest 0.96 m in KG. Mean flow velocity turns out to be as weak as about 0.1 m/s, with the weakest ~0.05 m/s in KG. Wave influence appears to be strongest in NX, with the significant wave height of ~1 m, in contrast to the 0.6 m and 0.4 m in AD and KG, respectively. The hydrodynamic observations under normal weathers should be able to transport the fine reef debris alone, with limited sediment transport rates of 0.61, 0.01 and 0.64 m3/m per tidal period in the observations in NX, AD and KG, respectively. Coarse coral rubbles and gravels might be only transported during extreme weathers. More observations and modeling work are needed, e.g. simulations of waves’ influence on atoll sedimentary systems’ development with XBeach.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/]] |
| Lyons, Nathan | Coupled models of landscape and species evolution | [[Changes in landscape structure are known to affect species macroevolution largely by altering habitat connectivity. Species can disperse across a greater area when habitats expand. Habitat fragmentation reduces gene flow and increases rates of speciation. Conversely, a shrinking habitat increases the likelihood of species extinction.
We integrated macroevolution processes (dispersal, speciation, and extinction) into the landscape evolution modeling toolkit called Landlab. Here, we present a new Landlab component, BiotaEvolver that tracks and evolves the species introduced to a model grid. In one model, surface process components evolve the landscape and BiotaEvolver evolves the species in response to topographic change or other characteristics of the model set by the user. BiotaEvolver provides a base species and users can subclass this object to define properties and behaviors of species types. We demonstrate BiotaEvolver using scenarios of drainage rearrangement and stream species. Stream captures and high macroevolution process rates occurred within a limited combination of parameters and conditions in hundreds of model runs. The number of species increased most rapidly after a response period following a perturbation. Species numbers declined then became stable after this period.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/]] |
| Morris, Chloe | The Coastline Evolution Model 2D (CEM2D) | [[Coasts are among the most intensely used environments on the planet, but they also present dynamic and unique hazards including flooding and erosion. Over the next century, these risk are likely to intensify across many coastal localities due to changes in environmental conditions, including sea level rise and changing wave climate patterns as induced by climate change. Managing these hazards and protecting vulnerable areas is challenging and requires an understanding of the behavior of coastal systems and longer-term prediction of their future evolution in the face of a changing climate.
Many existing one-dimensional coastal evolution models can effectively simulate the evolution of coastal environments. However, due to their 1D nature, they are unable to model the additional and combined effects of a variable water level and sea level rise. Hence, a new model, the Coastline Evolution Model 2D (CEM2D), has been built that is capable of simulating these processes. CEM2D has been built from the 1D parent model – the Coastline Evolution Model (CEM) - that was originally developed by Ashton et al. (2001), Ashton and Murray (2006) and Valvo et al. (2006). CEM2D has been developed accordingly to the underlying assumption and mathematical framework of CEM, but applied over a two-dimensional grid. At the core of this framework is the calculation of longshore sediment transport rates using the CERC formula and Linear Wave Theory. Wave shadowing calculations are also used to ensure that sediment transport is negligible in shadowed areas. The distribution of material across the shoreface is controlled by a steepest descent formula that routes sediment from higher to lower elevations across the domain according to defined thresholds, whilst maintaining the average slope angle. CEM2D provides a step forward in the field of coastal numerical modelling. It fills a gap between one-dimensional models of shoreline change that provide insights into the fundamental processes that control coastal morphodynamics and more complex and computationally expensive two- and three-dimensional models that are capable of simulating more complex processes and feedbacks. Key applications of CEM2D include improving our understanding of the meso-scale morphodynamic behaviour of coastal systems, their sensitivities to changing environmental conditions and the influence that climate change may have on their evolution over centennial to decadal timescales.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/]] |
| Nienhuis, Jaap | Can barrier islands survive sea level rise? Tidal inlets versus storm overwash | [[Barrier island response to sea level rise depends on their ability to transgress and move sediment to the back barrier, either through flood-tidal delta deposition, or via storm overwash. Our understanding of these processes over decadal to centennial time scales, however, is limited and poorly constrained.
We have developed a new barrier inlet environment (BRIE) model to better understand the interplay between tidal dynamics, overwash fluxes, and sea-level rise on barrier evolution. The BRIE model combines existing overwash and shoreface formulations with alongshore sediment transport, inlet stability, inlet migration and flood-tidal delta deposition. Within BRIE, inlets can open, close, migrate, merge with other inlets, and build flood-tidal delta deposits. The model accounts for feedbacks between overwash and inlets through their mutual dependence on barrier geometry. Model results suggest that when flood-tidal delta deposition is sufficiently large, barriers require less storm overwash to transgress and aggrade during sea level rise. In particular in micro-tidal environments with asymmetric wave climates and high alongshore sediment transport, tidal inlets are effective in depositing flood-tidal deltas and constitute the majority of the transgressive sediment flux. Additionally, we show that artificial inlet stabilization (via jetty construction or maintenance dredging) can make barrier islands more vulnerable to sea level rise.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Nienhuis_CSDMS_POSTER_May2018.pdf]] |
| Obelcz, Jeffrey | Towards a Quantitative Understanding of Parameters Driving Submarine Slope Failure: A Data Mining and Machine Learning Approach | [[Submarine slope failure is a ubiquitous process and dominant pathway for sediment and organic carbon flux from continental margins to the deep sea. Slope failure occurs over a wide range of temporal and spatial scales, from small (10e4-10e5 m3/event), sub-annual failures on heavily sedimented river deltas to margin-altering and tsunamigenic (10-100 km3/event) open slope failures occurring on glacial-interglacial timescales. Despite their importance to basic (closing the global source-to-sink sediment budget) and applied (submarine geohazards) research, submarine slope failure frequency and magnitude on most continental margins remains poorly constrained. This is primarily due to difficulty in 1) directly observing events, and 2) reconstructing age and size, particularly in the geologic record. The state of knowledge regarding submarine slope failure preconditioning and triggering factors is more qualitative than quantitative; a vague hierarchy of factor importance has been established in most settings but slope failures cannot yet be forecasted or hindcasted from a priori knowledge of these factors. A new approach to address the knowledge gaps outlined above is using machine learning to quantitatively identify triggering and preconditioning factors that are most strongly correlated with submarine slope failure occurrence. This occurs in three general steps: 1) compile potential predictors of slope failure occurrence gridded and interpolated at desired resolution, 2) compile predictands (specific values that we wish to predict), and 3) recursively test predictor/predictand correlation with observed data until the strongest correlations are found. Potential predictors can be parsed into categories such as morphology (gradient, curvature, roughness), geology (clay fraction, grain size, sedimentation rate, fault proximity), and triggers (seismicity, significant wave height, river discharge). Predictands (i.e. training data) are various proxies for slope failure occurrence, including depth change between bathymetric surveys and sediment shear strength. The initial test sites are heavily sedimented, societally important river deltas, as they host both frequent slope failures and ample predictor/predictand measurements. Once predictors that strongly correlate with submarine slope failure occurrence are identified, this approach can be applied in more data-poor settings to further our current understanding of global submarine slope failure distribution, frequency, and magnitude.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Obelcz_CSDMS_POSTER_May2018.pdf]] |
| Pfeiffer, Allison | How do source-to-sink geomorphic processes mediate flood hazards? Using historical changes to inform predictions | [[Flood hazards can increase or decrease as a result of changes in the frequency of high flows and changes in the geometry of river channels, through aggradation, incision, or widening. Across the US, Slater et al. (2015) found that a statistically significant majority of studied sites saw increases in the frequency of flooding over the past several decades. Notably, the magnitude of channel response and hydrologic non-stationarity varied between channels within a region. Here, we focus in on a single region, the Pacific Northwest, and ask 1) can the geomorphic characteristics of a basin explain historical changes in flood hazard? And, 2) how will flood risk change with climate change in relation to source-to-sink sediment dynamics? As a first step in understanding the sensitivity of different basins to future climate change, we look at historical records of both channel geometry change and discharge records at ~60 USGS gage sites across Washington state. We find substantial variation among the studied sites in the magnitude of channel change (quantified in terms of changes in the stage-discharge relationship) over the past 3 decades. Some channels have maintained a steady stage-discharge relationship over 30 years, while others change dramatically on an annual basis. Many, but not all, of these unstable channels drain basins with retreating alpine glaciers. Inspecting the discharge records, we find substantial variation as well, likely driven by the differences in hydrologic regime. In the future, we will use this understanding of historical channel sensitivity to inform our predictive models of both channel geometry change and non-stationarity in high flows.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/]] |
| Phillips, Colin | Coupling fine particle transport, storage, and remobilization with sediment bed morphodynamics | [[During storms nutrients and contaminants are washed from landscapes into rivers in the form of fine particulate matter. Once in a river, fine particles are typically treated as if they pass through the environment as wash load without interacting with the stream bed. However, laboratory and field experiments have demonstrated that fine particles can be advected towards the bed where they participate in hyporheic exchange and eventual filtration within the river bed. Irreversibly filtered particles can only be remobilized through scour and bed erosion. Therefore, understanding fine particle transport, storage, and remobilization in rivers requires coupling fine particle dynamics and sediment morphodynamics. Here we analyze the dynamics of solute tracers, fine suspended particles, and bed morphodynamics within a coastal stream during baseflow and an experimental flood. These field data represent a unique set of coupled surface and subsurface observations of solute and fine particle dynamics and simultaneous time-lapse photography of sandy bedform motion. From the time-lapse photography, we use novel image analysis techniques to extract time series of bedform wavelength and celerity. In tandem, we utilize existing databases of bedform topography from laboratory experiments to determine relations between the statistical distributions of bedform wavelength, height, and the maximum scour depths. The understanding gained from the high-resolution experimental dataset allows us to create time series of bedform height and scour depth to explore how changing bedform dynamics affects solute and fine particle residence times within the stream bed.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Phillips CSDMS POSTER May2018.pdf]] |
| Pérez-Hincapié, Ana María | Comparative geomorphological analysis applied to the hazard assessment of debris flows in three watersheds of the Western Cordillera of Colombia | [[The watershed of the Tapartó and Farallones rivers and the La Arboleda stream in the central zone of Colombia’s western mountain range are known to have experienced important debris flow events historically. In the same manner, there is geomorphological evidence that suggests a complex dynamic associated with the conditions of high slope, heavy rainfall and a soil profile with an important development. The geomorphological analysis carried out in these watersheds enabled recognition of different levels of deposits in addition to their stratigraphic characterization. Likewise, radiocarbon dating allowed the establishment of ages between 100 +/- 30 and 2010 +/- 30 years for the different levels of deposits characterized. The integration of geomorphological and stratigraphic information along with radiocarbon dating allowed for the differentiation of the debris flow dynamics of each of the basins and suggests the existence of three phases. The first is an ancient one (with deposits older than 2000 years), followed by a sub-recent dynamic (represented by levels between 1500 and 2000 years old) and a current dynamic, with low incised deposits systems and ages that do not exceed 500 years. Finally, it was established that even though these basins have great potential for the generation of debris flow events of significant magnitude, the deposits show a tendency of decreasing magnitudes in the last 1000 years. These analyses and their results are input to the construction of knowledge in relation to the understanding of this phenomenon in tropical environments and the generation of elements that would allow to address the problem in other zones with similar characteristics in throughout the country.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Perez_CSDMS_POSTER_May2018.pdf]] |
| Qin, Xinsheng | Accelerating Block-Structured Adaptive Mesh Refinement (AMR) with GPUs | [[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.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Qin CSDMS POSTER May2018.pdf]] |
| Qureshi, Huda | A Sensitivity Analysis of the Effect of Parametric Wind Model Inputs on Hurricane Storm Surge Simulations | [[The high speed winds of a hurricane account for 95% of a hurricane’s storm surge. Thus, parametric wind models are vital components of numerical storm surge modeling. These parametric hurricane wind models are used as inputs for a storm surge computation to hindcast and forecast hurricane surge heights. These wind models are dependent on several input parameters including but not limited to the radius at which the maximum wind speed of the hurricane occurs and the speed of the maximum winds. The impact of these input parameters on the final surge computation is not well known. Our study is a sensitivity analysis of the effect of uncertainty in the input parameters on the uncertainty in the final computation of the storm surge model. This study will help us to understand the robustness of a parametric wind model, the parameters that must be precise in order to reduce model error, and can aid in model simplification.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/]] |
| Richmond, Nick | 3D Bedrock Channel Evolution with Smoothed Particle Hydrodynamics Coupled to a Finite Element Earth | [[An enduring obstacle to reliable modeling of the short and long-term evolution of the stream channel-hillslope ensemble has been the difficulty of estimating stresses generated by stream hydrodynamics. To capture the influence of complex three-dimensional (3D) flows on bedrock channel evolution, we derive the contribution of hydrodynamic stresses to the stress state of the underlying bedrock through a Smoothed Particle Hydrodynamics (SPH) approximation of the Navier-Stokes equations as calculated by the DualSPHysics code (Crespo et al., 2015). Coupling the SPH flow solutions to the stress-strain formulation of the Failure Earth REsponse Model (FERM) (Koons et al., 2013) provides three-dimensional erosion as a function of the strength-stress ratio of each point in the computational domain. From the coupling of SPH and FERM we gain a 3D physics-based erosion scheme and a two-way link between complex flows and hillslope dynamics in a finite element framework.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Richmond_CSDMS_POSTER_May2018.pdf]] |
| Schumann, Guy | Integrating EO Data of Floods with a Hydrodynamic Event Model: Harvey 2017 | [[Floods can be devastating to society and the environment. Recent flood events around the globe, such as Harvey and Irma for instance, have been disastrous and broke records in damage and loss of life. Flood disasters often operate at spatial and temporal scales that far exceed local and regional, or even national, assessment and response capabilities. There is no doubt that remote sensing observations of floods, particularly from satellites, can be of great value. Earth observation (EO) data of floods can either be used directly through numerous services providing flood maps and other datasets, or indirectly through integration with hydrodynamic models simulating events continuously in time and space. In this project, we demonstrate the value of satellite flood maps for Harvey 2017 and Twitter feeds during the event for integration with a forecast inundation model (LISFLOOD-FP). Initial results are illustrated and we discuss current challenges and next steps.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Schumann_CSDMS_POSTER_May2018.pdf]] |
| Shobe, Charles | Modeling the 2-D evolution of blocky landscapes: Hillslope-channel interactions | [[Block-mantled hillslopes responding to river incision deliver large blocks of rock to channels. These blocks inhibit fluvial erosion by shielding the bed and reducing available bed shear stress. Block delivery by hillslopes in response to channel incision therefore feeds back on the boundary conditions felt by the hillslopes: larger numbers of blocks, or larger blocks, reduce the rate at which the hillslope boundary condition is lowering. This coupled set of feedbacks can lead to oscillatory behavior in both channels and hillslopes with periods of rapid channel incision interspersed with intervals of little to no incision. For a hillslope with a line supply of blocks (such as might originate from a resistant caprock overlying a less resistant layer), we expect that these feedbacks are strong only when the source of blocks is relatively close to the channel. Once the block source has retreated sufficiently far from the channel, blocks will weather away before reaching the channel and the oscillatory channel-hillslope feedbacks described above will cease. Our questions are 1) For how long after initial river incision through a caprock do oscillatory channel-hillslope feedbacks persist? and 2) How far must the block source retreat from the channel before such feedbacks become negligible? We use the new BlockLab 2-D landscape evolution model to assess the spatial and temporal extent of oscillatory channel-hillslope feedbacks. We model a channel incising a lithological sequence consisting of a weak layer underlying a resistant caprock. Blocks from the caprock are delivered to the channel and inhibit river incision. We find that at early time, temporal variation in the erosion rate boundary condition felt by the hillslope is significant. As the resistant layer retreats further from the channel, variations in both the channel erosion rate and the resistant layer retreat rate decline. The rate of these reductions in variability with time is set by competition between 1) the ability of the hillslope to deliver multiple large blocks to the channel (a function of initial block size, block weathering rate, and the distance the blocks had to travel before arriving at the channel), and 2) the ability of the channel to overcome the erosion-inhibiting effects of blocks (set by fluvial discharge and the block erodibility coefficient). We find that after enough model time has passed, the resistant layer has retreated far enough from the channel that block effects on the channel are negligible and oscillatory channel-hillslope feedbacks no longer exist. This distance is primarily a function of initial block size and block weathering rate. Our results indicate that channel and hillslope evolution rates in block-mantled landscapes may be highly unsteady, depending on the strength of coupling between the channels and hillslopes.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Shobe_CSDMS_POSTER_May2018.pdf]] |
| Sincavage, Ryan | Deterioration of the eastern margin of the Colonia Glacier, northern Patagonia: the end of a glacially-dammed alpine lake? | [[Lago Cachet Dos (LC2) is a glacially-dammed lake adjacent to the Northern Patagonian Ice Field (NPIF), formed by the blockage of Cachet Basin (CB) by the Colonia Glacier. This glacier has experienced rapid (~1-2 km) retreat of its terminus as well as ~1-2 m/yr of thinning, documented over the past several decades. Furthermore, the glacier has exhibited a change in hydrologic regime and the frequency of high energy glacial lake outburst flood (GLOF) events since 2008. These historical changes appear to be coupled with regional climate change; summer mean maximum and minimum temperatures in nearby Cochrane show a steady increase since 1971, whereas winter mean maximum temperatures show cooling in the 1970s and 1980s, followed by gradual warming with rapid acceleration in the 2000s-present. Preliminary correlations with a recently installed weather station at Sol de Mayo (~12 km downstream of the Colonia Glacier terminus) show a strong positive correlation with the Cochrane data, indicating these climate changes are regional and not local and thereby have implications for the evolution of other alpine basins of the NPIF and perhaps glaciers on a global scale. Recent observations from unmanned aerial vehicle (UAV) flights, satellite imagery, and geologic mapping suggest unprecedented glacier deterioration near the southern limit of CB. An UAV flight in January 2016 revealed that during GLOF events, the lake drained through a large hole at the base of the glacier. Upon entering this chasm, the water made a sharp east turn (towards the bedrock abutting the glacier’s eastern margin) and appeared to flow beneath the ice at this point. Subsequently, a large (~2km long x 100 m wide) supra-glacial channel has opened directly above the drainage hole, effectively separating the glacier from bedrock. Ice elevation data reveal that healing of this channel may not be possible under the current climate regime, suggesting the basin could be experiencing a long-term (over human timescales) shift to fluvial deposition from a dominantly lacustrine environment, corresponding to an inability to impound water associated with the glacier's retreat. Basin stratigraphy indicates these oscillations between lacustrine and fluvial conditions have occurred repeatedly throughout the Holocene, but the timing of these changes are poorly constrained. Optically stimulated luminescence (OSL) dating of CB sediments will be applied to identify the timing and periodicity of these depositional shifts, with the broader goal of linking these oscillations with local and regional climate and stability of the Colonia Glacier.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/]] |
| Southard, Paul | Impact of spring-associated riparian vegetation on channel morphology in ephemeral dryland channels: Henry Mountains, Utah, USA | [[Climate change and reduced water availability in arid regions has important implications for how channels will change as they adjust to a new steady-state characterized by different riparian populations. While much study has been devoted to the effects riparian vegetation has on fluvial processes (Tal & Paola, 2010; Osterkamp & Hupp, 2010; Corenblit et al., 2009), the complexity of natural channels obscures exactly how these feedbacks modify long-term channel evolution, making prediction of the larger impacts of vegetation change on channel morphology difficult. In order to isolate the impact vegetation has on morphology, single channels that are variably vegetated along their length are desirable for study because flow conditions and long-term sediment flux change minimally between major tributaries (Bertoldi et al., 2011). Comparisons made in such dryland channels in Henry Mountains, Utah, USA, where groundwater springs juxtapose vegetated and un-vegetated reaches allow us to examine two hypotheses: first, that disruptions to normal fluvial processes caused by in-channel vegetation produce distinct morphological responses to floods at the scale of single flood events, and, second, that these responses accumulate on the timescale of multiple floods to produce channel morphologies in vegetated reaches that are fundamentally different from those in unvegetated reaches. Analysis of repeat airborne LiDAR data for these areas provides an opportunity to quantify morphological parameters and elevation differences, and to attempt to correlate these metrics with quantitative metrics of vegetation. Field observations from October, 2017 in this region agree with the results of LiDAR analyses and indicate that the presence of dense vegetation seems to produce more uniform cross-sectional shape with narrow, deeply incised channels supported by intense rooting on banks, and a longitudinal profile that is characterized by frequent vegetation-supported, non-bedrock knickpoints. Future work will involve modelling flood flows to determine the degree and areal extent of channel reworking during a flooding event and the influence of vegetation on shear stress for comparison with LiDAR differencing results.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/]] |
| Strom, Kyle | A simple, single-size and time-dependent flocculation model | [[The accuracy of sediment transport models depends heavily on the selection of an appropriate sediment settling velocity. Determining this value for mud suspensions can be difficult because the cohesive particles within the mud can aggregate to form flocs whose sizes are a function of hydrodynamic and physiochemical conditions of the suspension. Here we present a new model for predicting floc size in a dynamic way as a function of the hydrodynamic conditions and inherited floc sizes. The new model is a simple modification to the existing Winterwerp (1998) floc size model. The modification is significant in that it yields predictions that are more inline with observations and theory regarding the upper limit on ultimate floc size. The modification we propose is to make the ratio of the applied stress on a floc over the strength of the floc a function of the floc size relative to the Kolmogorov microscale. The outcome of this modification is that flocs are not allowed to surpass the Kolmogorov microscale in size and that calibrated aggregation and breakup coefficients obtained at one suspended sediment concentration can be used to predict floc size under other concentration values without recalibration of the coefficients. In this paper, we present the motivation for the modification, the functionality of the modification, and a comparison of the updated model with laboratory and field data. Overall the model shows promise as a tool that could be incorporated into larger hydrodynamic and sediment transport models for improved prediction of cohesive mud transport.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Kuprenas_CSDMS_POSTER_May2018.pdf]] |
| Tang, Hui | Physics-informed machine learning approach for predicting post-fire debris flows based on thresholds | [[Post-fire debris flow is a common hazard in the western United States. However, after decades of efforts in the debris flow research community, universally applicable post-fire debris flow predict methods are still lacking. Large discrepancies in the post-fire debris flow initiation mechanism are the main source that limits the predictive accuracy of debris flow. Improve and understanding these discrepancies is significant to possibly improve the debris flow modeling. In this work, we propose a data-driven, physics-informed machine learning approach for reconstructing and predicting debris flows. By using a classic supervising modern learning technique based on logistics regression, the logistics regression functions are trained by existing direct field measurements and debris flow numerical simulations from Las Lomas after 2016 Fish fire and then used to predict debris flow in different drainage basin where data are not available. The proposed method is evaluated by two classes of simulations: sediment transport model and runoff model. In runoff simulations, five drainage basins are considered: Las Lomas, Arroyo Seco, Dunsmore 1, Dunsmore 2, Big Tujunga. In sediment transport model, Las Lomas and Arroyo Seco watersheds are applied. Excellent predictive performances were observed in both scenarios, demonstrating the capabilities of the proposed method.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/]] |
| Wang, Kang | Effect of Enhanced Cold-Season Climate Warming on Permafrost Temperatures | [[It has been well documented that climate warming was greater in the Arctic than elsewhere. However, it is still poorly understood how climate changed over different permafrost zones and its potential impacts on permafrost thermal dynamics. In this study, we investigated changes in air temperatures, especially seasonal air temperatures, over different permafrost regions in the Northern Hemisphere using the Climate Research Unit (CRU) gridded datasets from 1976-2016. The primary results indicated that permafrost regions as a whole experienced a warming at 0.36, 0.41, and 0.46 °C/decade in mean annual maximum, mean, and minimum air temperature, respectively, which are 16%, 32%, and 44% higher than the corresponding trend in non-permafrost regions. More importantly, strong increases occurred in cold months and nighttime over continuous permafrost zone, exceeding 0.72 °C/decade in Spring and Autumn; while summer air temperature had a relatively small increase or no statistically significant trends. As a result, the decrease of air freezing index by 529 °C-day would result in permafrost temperature increase by 1.43 °C in continuous permafrost zone over the past four decades. This may explain the observed evidence that increase of cold permafrost temperature was greater than that of warm permafrost, while active layer thickness had little or no change during the past several decades. These results suggest that predicted reduction of permafrost area by previous studies might be overestimated.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/Wang_CSDMS_POSTER_May2018.pdf]] |
| Wickert, Andrew | Long-profile evolution of transport-limited gravel-bed rivers | [[Transport-limited gravel-bed rivers are ubiquitous across Earth's upland environments. Sediment transport processes, while notoriously difficult, are better-understood than bedrock erosion, meaning that solutions to transport-limited river long profiles can help us gain a physics-based toehold into landscape evolution. Here we demonstrate how the coupling of equations for gravel transport, channel morphodynamics, and simple flow hydraulics that produce steady-state river profiles and show how they respond to changes in climate and tectonics. This coupled set of equations is analytically solvable for special cases, and we have also developed efficient semi-implicit numerical solutions that can solve millions of years of landscape evolution in seconds. Gravel-bed rivers become steeper as the sediment-to-water supply ratio increases, and become less concave as uplift rates (relative to input sediment supply and valley dimensions) increase. These distinctive responses allow us to use transport-limited gravel-bed rivers as recorders of climatic versus tectonic influence on river systems.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/]] |
| Yanites, Brian | Quantitative constraints on landslide frequency through the use of cosmogenic nuclides: a numerical modeling perspective | [[Quantitative constraints on the frequency of hazards is vital to risk assessments and appropriate mitigation strategies. The frequency of landslides, a common hazard in steep landscapes, is difficult to quantify for a number of reasons including: (1) infrequent occurrence; (2) rapid deterioration of the morphological signature of a landslide event; (3) expensive geochronological approaches are often require to obtain the age of a single event. Through the use of numerical modeling, I propose that more careful approach of using cosmogenic nuclide concentrations of alluvial sediment sourced in landslide dominated drainage basins can alleviate many of these hurdles and provide regional constraints on landslide frequency. This suggestion stems from new development of an old numerical code that quantifies the impacts of landslides on CRN concentrations in alluvial sediment. The modeling shows that quantitative insight can be obtained by measuring CRN concentrations (1) of multiple nuclides (10Be and 14C), (2) of multiple grain sizes (i.e. coarse material sourced from depth in the hillslope), and (3) over time. I will present the new model developments and results as well as discuss some strategies towards applying this in field settings.|100px|link=https://csdms.colorado.edu/csdms_wiki/images/]] |
