Property:CSDMS meeting abstract
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Landscapes in a transient state can be described as areas that are undergoing topographical and geomorphological adjustments. In tectonically active areas, it is straightforward to interpret and reconstruct topography using transient geomorphic signals based on stream power theory. However, areas without tectonic activity are also rife with topographic transience but lack a clear trigger. Landscapes with heterogeneous lithological substrates present geomorphic signals of an ongoing transient state even when their geological context implies tectonic and climatic quiescence. Here, I propose to investigate the transient landscape response to the exhumation of heterogenous lithology. The main objective of this project is to quantify the influence of lithology on landscape evolution processes in the absence of tectonic activity. I hypothesize that divide asymmetries are created by the differential incision power each basin has at the lithologic transition. The differences are a function of the drainage area and the distance crossed over the resistant rocks. Our work is based on a LandLab simulation in which the synthetic DEM has a rock in its lower (southern) portion that is more resistant to erosion. The boundary conditions were configured so that only the southern part was open to the river system, which resulted in drainages flowing from north to south. The drainage basins was then analyzed from the same base level, controlled by the exhumation of the most resistant rock. Preliminary results indicate that basins with a smaller drainage area are subject to shrinkage processes after the exhumation of resistant rock in their outlet (base level). While the basins that had the largest drainage area gained area via river capture and divide migration, expanding their total area over time and thus shrinking the adjacent basins. +
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.
Landslides are key agents of sediment production and transport. Ongoing efforts to map and simulate landslides continuously improve our knowledge of landslide mechanisms. However, understanding sediment dynamics following landslide events is equally crucial for developing hazard mitigation strategies. An outstanding research challenge is to better constrain the dynamic feedbacks between landslides and fluvial processes. Fluvial processes simultaneously (i) act as conveyor belts evacuating landslide-derived sediment and (ii) lower the hillslope’s base level triggering further landsliding. Landslides in turn can choke river channels with sediment, thereby critically altering fluvial responses to external tectonic or climatic perturbations.
Here, we present HYLANDS, a hybrid landscape evolution model, which is designed to numerically simulate both landslide activity and sediment dynamics following mass failure. The hybrid nature of the model is in its capacity to simulate both erosion and deposition at any place in the landscape. This is achieved by coupling the existing SPACE (Stream Power with Alluvium Conservation and Entrainment) model for channel incision with a new module simulating rapid, stochastic mass wasting (landsliding).
In this contribution, we first illustrate the functionality of HYLANDS to capture river dynamics ranging from detachment-limited to transport-limited configurations. Subsequently, we apply the model to a portion of the Namch-Barwa massive in Eastern Tibet and compare simulated and observed landslide magnitude-frequency and area-volume scaling relationships. Finally, we illustrate the relevance of explicitly simulating stochastic landsliding and sediment dynamics over longer timescales on landscape evolution in general and river dynamics in particular under varying climatologic and tectonic configurations.
With HYLANDS we provide a hybrid tool to understand both the long and short-term coupling between stochastic hillslope processes, river incision and source-to-sink sediment dynamics. We further highlight the unique potential of bridging those timescales to generate better assessments of both on-site and downstream landslide risks.
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Landslides are often assumed to exhibit self-similarity in their failure geometry, and thus a linear scaling between slip depth and rupture length. This assumption has important implications for the prediction of large landslide volumes and for the estimation of erosion budgets by mass-wasting. Nevertheless, some field data indicate a break from self-similarity and imply that, in some circumstances, landslide depth may scale non-linearly with length. Here we test the simple scaling hypothesis by numerical experiment. Modeling is performed with SNAC (StGermaiN Analysis of Continua), a 3D community code originally designed to model viscoelastoplastic deformation on a crustal scale and newly adapted to treating hillslope failure. SNAC employs a parallelized, Lagrangian, explicit finite-difference scheme and dynamic relaxation to solve static, quasi-static and steady-state problems. Landslide rupture is treated as emergent shear localization under strain-weakening Mohr-Coulomb plasticity. We model only the initial slip and early motion of a landslide; granular flow during the runout phase is not considered. A set of 2+1D simulations of failures spanning lengths of 50–400m suffice to vindicate cross-sectional self-similarity—absent any dominant depth scale or trend in the variation of cohesion—and a depth-length ratio of 11–15% is recorded. An interesting by-product of the choice of experimental geometry is some unanticipated complexity in the evolution of the slip plane. Failure initiates at the toe, propagates upslope, and asymptotically parallels the planar upper boundary. However, a connected failure surface is only achieved once a secondary rupture has propagated downwards into this slip plane from the upper breakaway zone. The broader outcome of our numerical experiments is a demonstration of how 3D continuum modeling of soil and rock-slope failure, and the study of their rich behavior, is now feasible using non-commercial code on supercomputing platforms.
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Landslides are responsible for mobilizing enormous volumes of sediment from hillslopes into channels. At short timescales, these landslide deposits can change channel geometries and impact a system’s ability to efficiently export sediment. Mountain channels must mobilize this sediment before they can incise into their bedrock. There is evidence that mass failures like landsliding set an upper limit to relief and thus shape topography. However, few studies have investigated how landslides impact the landscape- and geologic-scale shape of landscapes. We aim to use topographic metrics to characterize how varying degrees of landsliding at geologic timescales shape landscapes. To address the long-term interplay between landslides, sediment dynamics, and the topographic evolution of Earth’s surface, we use landscape volution modeling which incorporates landslide triggering combined with river bedrock erosion, gravel transport that includes abrasion of both sediment load and bedrock, and dynamic channel adjustment consistent with that of near-threshold alluvial channels. We find that the inclusion of sediment attrition is necessary to reduce the flux of gravel and is consistent with inferences from field studies. We compare our model results to landscapes with constrained landslide histories among a spectrum of tectonic and climatic environments to assess our model’s ability to accurately capture realistic landscape features. This comparison enables us to explore the impact of future, rapid environmental climate change on landslide occurrence and risk, especially the influence of sediment supply on the cascade of downstream hazards +
Landslides represent a significant natural hazard that often cascade off earthquakes and other major disaster events, further impacting landscapes and human infrastructure globally. Accurate modelling of landslide-prone areas is crucial for risk assessment and mitigation strategies, especially in seismically active regions. This study introduces a novel simulation component designed to predict the spatial distribution of seismically-triggered landslides.
Seamlessly integrating within the broader Landlab modelling framework, the new component leverages high-resolution topographic data and incorporates key factors such as slope stability, soil thickness, and various hydrological conditions to predict locations that are particularly sensitive to failure in the event of an earthquake, mapping their probable extents.
A key aspect of this component is the incorporation of the Newmark method, a classical mechanical model used in seismic landslide hazard analysis. Proposed by Newmark in 1965, it models a landslide as a rigid block sliding on an inclined plane. It calculates the critical acceleration needed to overcome the friction of the sliding surface, allowing the block to move when seismic intensity exceeds the slope’s stability.
The model is currently being tested and validated against a detailed landslide inventory from central Nepal, with further plans to validate it against additional inventories from Papua New Guinea and New Zealand. Preliminary results demonstrate the component’s capability to accurately replicate observed shallow landslide patterns, and its potential for application in real-time hazard forecasting.
Here, we present the methodological framework, the challenges encountered during development, and the validation process. Additionally, we will showcase case studies highlighting the component’s practical applications, especially in seismically active regions, and discuss future enhancements to improve its predictive accuracy and computational efficiency.
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. +
Large sediment pulses deposited in river channels can alter channel morphology and amplify downstream flood hazards. In the Suiattle River of Washington State, abrasion controls the downstream impact of sediment supply from Glacier Peak, a stratovolcano that regularly supplies the channel with large sediment pulses. This phenomenon is evident by the persistence of strong volcanic grains on the streambed and the rapid downstream loss of weak volcanic grains to fine sediment. Although cobbles and boulders dominate pulses in the channel, the Suiattle has an unusually high supply of fine sediment and contributes to fine sediment impacts downstream. Despite the evidence that the abrasion of coarse sediment during downstream transport drastically impacts the balance of fine and coarse sediment in the channel and new studies on the variability of abrasion, no work – in the Suiattle or elsewhere – has been done to determine the importance of abrasion on sediment pulse evolution in a highly abrasion-prone setting. Here, we test the extent to which abrasion acts as a control on sediment pulse transport from large mass wasting deposits of heterogeneous sediment characteristics. We employ the use of the Network Sediment Transporter, a 1-D river morphodynamics and Lagrangian modeling component in Landlab, to explore channel response to a large sediment pulse in the Suiattle River basin, tracking bed elevation and grain size changes and compare model results of variable sediment abrasion scenarios. We simulate abrasion as the mass of the grain loss per distance traveled and the scenarios include: no abrasion, a distribution of Schmidt Hammer Rock Strength (SHRS) measurements (a proxy for tumbler-derived abrasion rate), and a doubling of the SHRS proxy to account for the underprediction of the tumbler and a lack of in-place abrasion. We drive the model with a 2-year exceedance flow from discharge data from a distributed hydrology model to account for the complicated rain/snow hydrology of this mountainous region. Our initial results indicate negligible variances in bed elevation solely attributable to abrasion. Instead, our primary findings highlight the importance of the canyon reaches in modulating the coherence of the pulse as it transports downstream. Before the canyon reaches, a coherent wave of bed elevation change is apparent in all model runs, with modest differences between abrasion scenarios. Downstream of this canyon reach, this coherence dissipates.
Large-scale Earth system and land surface models often lack an adequate representation of subgrid-scale processes in permafrost landscapes. Small-scale processes such as thermokarst formation might, however, considerably impact the energy and carbon budgets in way which is not resolved within large-scale models. Since a spatially high-resolved simulation of such processes is not feasible, novel techniques for up-scaling subgrid processes are demanded.
Within this work a one-dimensional model of the ground thermal regime of land surfaces, CryoGrid 3, is employed to conceptually represent small-scale features of permafrost landscapes, particularly those related to thermokarst. For example, the model has been shown to adequately describe the degradation of permafrost underneath waterbodies in a warming climate. Using tiling approaches such point-wise realizations can be up-scaled in a statistical way in order to represent larger land surface units.
The model development is closely linked to field campaigns to the Lena River Delta in Siberia which offers very diverse land surface features such as polygonal tundra and thermos-erosional valleys. These features are related to the region’s diverse soil stratigraphies, in particular the occurrence of ice-rich ground. Combining field measurements with modelling ultimately allows an improvement in the qualitative and quantitative understanding of the typical geomorphological processes in permafrost landscapes and their representation in large-scale land surface models. +
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.<br>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.
Launched in December 2022, the Surface Water and Ocean Topography (SWOT) Mission houses a first-of-its-kind satellite instrument, KaRin, with an interferometric Ka-band active radar and a near-nadir look angle. Most importantly, SWOT's KaRin instrument measures coincident water surface elevation and widths, and over a large 120 km swath every 10 days on average, enabling estimation of volume change in static waterbodies and discharge in rivers. SWOT measures 0.5% earth’s surface area per hour and offers stunning new insights into ocean and inland waterbodies. Less well known are SWOT’s capabilities for rivers, particularly rivers that are otherwise difficult to sample with field equipment. Using SWOT and field data, this presentation will discuss the hydraulic and geomorphic implications of one year of SWOT measurements, including data from rivers in Western North America. +
Like many densely populated deltas worldwide, the Ganges-Brahmaputra Delta faces cascading flood and salinization hazards associated with relative sea-level rise (RSLR). One of the greatest uncertainties in future RSLR projections stems from the compaction of unconsolidated sediments, which causes land to subside with significant spatiotemporal variations. Here we constrain compaction variations on the Ganges Brahmaputra Delta, using a state-of-the-art 1D compaction model based upon fundamental principles of porous-media mechanics and groundwater flow; as well as constitutive relations for porosity and edaphic factors (e.g., roots, burrows). The model accurately reproduces field observations from GNSS, RSET-MH, and optical fiber strainmeters with compaction-induced subsidence rates of 1–30 mm/y depending upon local thickness and lithology of underlying Holocene deposits, forest tree density, and sedimentation rate. Sedimentation drives a dynamic compaction response over timescales of 10–100 years, such that floodplains cut off from sediment after 1950’s embankment construction have undergone significant elevation loss and are now experiencing a gradual subsidence slowdown. Updated RSLR projections informed by our model indicate that compaction-induced subsidence will be responsible for up to 50% of twenty-first-century RSLR, and exert a first-order control on hotspots of flooding and salinization hazards. +
Long-term tectonics shape the landscape we live on. Collision over 10s of millions of years has produced the Himalayan mountain chain, the Tibetan Plateau and the atmospheric disturbance that produces the Asian monsoon. But it is the dynamic, short-term manifestations of tectonics and plate boundaries and their aftermath that most dramatically impact people’s lives. The shaking of a large main shock, while overwhelming, is over within minutes but the consequences of the shaking on the landscape can last for years to decades. In particular, in mountainous environments, a sedimentary hazard cascade (SHC) can dominate a region in the decades following a large earthquake. The 1999 Chi-Chi earthquake in Taiwan, the 2008 Wenchuan earthquake in China and most recently the 2016 Kaikioura earthquake in New Zealand provide the opportunity to quantify and model some of these impacts. In particular, improved knowledge of spatial and temporal variations in rock erodibility help us to understand the physical connections between tectonic structure and the Earth surface, both in the short and in the long term. Quantifying rock damage (erodibility) as a result of tectonic processes is an important step in exploring the link between the processes that occur on the timescales of the human dimension and long term tectonics. +
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Low-lying coastal barriers face an uncertain future over the next century, with many projections suggesting end-of-century rates of sea-level rise as high as 1 cm/yr. The hazards associated with this passive inundation can be reasonably estimated using state-of-the-art tools. However, the coast is not a bathtub - increased sea levels enhance the ability for waves to reorganize the coast, typically resulting in increased shoreline retreat by moving sediment either offshore into deeper waters or onshore by overwashing the existing coast.
Although many models of coastal change have been developed, the majority are either highly calibrated and intended to operate at the temporal scales of engineering projects (< ~5 years), offering little possibility of forecasting never-seen behaviors such as barrier drowning, or long-term geologic models, which typically assume that the coast maintains an ‘equilibrium’ configuration that moves with sea level. We aim at bridging the gap between these approaches by constructing a simple model that focuses on dynamical coupling of two primary barrier components: the marine domain represented by the active shoreface, which is constantly affected by transport and reworking by waves, and the backbarrier system, where the infrequent process of overwash controls landward mass fluxes. The model demonstrates that coastal barriers can respond to an accelerated sea-level rise in complex, less predictable manners than suggested by existing conceptual and long-term numerical models. Model behaviors under constant sea-level rise reveal two potential modes of barrier failure: ‘height drowning’, which occurs when overwash fluxes are insufficient to maintain the landward migration rate required to keep in pace with sea-level rise; and ‘width drowning’, which occurs when the shoreface response is insufficient to maintain the barrier geometry during landward migration. We also identify a mode of discontinuous barrier retreat, where barriers can experience punctuated intervals of rapid rollover and shoreline stability, even with constant rates of sea-level rise. We explore the sensitivity of these modes to external and internal variables, including sea-level rise rate, maximum overwash rate, shoreface response rate, and inland topography.
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Low-lying regions of river deltas (marshes, swamps, and tidal flats) are an important part of the delta life cycle. Marsh sedimentation is characterized by non-riverine, low-bulk density material, and interacts with the riverine sediment delivered by distributary channel networks. These two forms of sedimentation interact to produce the channel properties and kinematics observed in the system. Here, we aim to understand this interaction by comparing two physical delta experiments, one with marsh deposition (treatment) and one without (control). We show that the addition of the marsh proxy (kaolinite) alters the channel properties and kinematics of a river delta. Notably, the channels are longer in the treatment experiment and the shoreline roughness is enhanced. The treatment channels have the same width from the entrance to the shoreline, while the control channels get narrower as they approach the shore. Flow is concentrated in the channels in the treatment experiment, as it has about one-fourth the amount of overbank flow as the control experiment. Interestingly, the channel beds in the treatment experiment often exist below sea level in the aerial portion of the delta top, a phenomena observed in global deltas. However, in the control experiment, the channel beds generally exist above relative sea level. The channels in the treatment experiment have a slope break, on average, which is also seen in some global deltaic rivers (e.g., Mississippi River Delta). The difference in channel properties created by the addition of the marsh proxy in the overbank region helps offset the channel bed aggradation rates in the treatment experiment, as the overbank region aggrades faster (relative to the channel) than in the control. This difference in in-channel and far-field aggradation shows a longer channel in-filling time for the treatment as compared to the control. Although the lateral channel mobility statistics are similar in both experiments, there is more area on the delta top in the treatment experiment that is rarely visited by a channel. This suggests that the marsh proxy may buttress the channels in the treatment experiment. Ultimately, marsh sedimentation on the delta top plays a key role in the channel properties and kinematics of a river delta, producing channels which are more analogous to channels in global river deltas, and which cannot be produced solely by increasing cohesion in an experimental river delta.
Mapping river corridors remains challenging due to the dynamic interactions between water, sediment, and vegetation. Existing land cover maps often misclassify fluvial sediments, limiting their use in river system studies. We present a deep learning framework using incremental learning to refine river corridor mapping by integrating Sentinel-2 imagery with global land cover datasets (ESRI, Google Dynamic World, ESA WorldCover). Our method builds on existing classifications to improve differentiation between fluvial sediment, bare ground, and mining-related disturbances. The results show that incremental learning can enhance river mapping accuracy, providing a customizable approach to better capture riverine landscapes. +
Marine Hydrokinetic (MHK) technologies provide an opportunity to expand renewable energy by harnessing waves and currents power and converting to electricity for residential and commercial application. Locations with rapid tidal flow, large waves, and large tidal range are being considered for implementation of MHK technologies and extraction of energy. However, little is known about the impact of MHK structures on the surrounding ocean morphology. In this study, the hydrodynamic and morphodynamic numerical model, Delft3d, is used to simulate the erosion and deposition around a bed mounted MHK structure to analyze the impacts of seabed slope, sediment grain size, and wave condition on the long-term stability of the device. We analyzed 10, 15, and 20 degree seabed slopes, and three different sediment grain sizes representing fine, medium, and coarse-grained sand. For wave conditions, we ran storm condition of the frequent 1-2 year recurring storm in North Carolina Coast, which occurred during Hurricane Mathew in 2016. We also tested the mean wave conditions and the extreme 100-year storm for the same location. Our initial results suggest that steeper sloped beds, finer sediment grains, and larger wave heights will be more problematic for increasing total deposition and burial of bed-mounted MHK devices. However, depending on the type of MHK device, this impact may not be as important as potential scour around the MHK leading to toppling and failure of the device. Moreover, for extreme storm conditions (i.e. the 100 year storm), scour and potential collapse of the foundation or anchor of the bed-mounted MHK may be a serious concern. +
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Marine carbonates are created by the metabolism, growth, death and skeletal accumulations of a diverse array of benthic organisms (e.g. corals, bryozoa, molluscs, foraminifera, calcareous algae, and micro-organisms), but carbonate accretion requires a positive net balance among biological growth processes, processes of biological erosion (mainly by fishes, urchins, polychaetes, molluscs, sponges, algae and micro-organisms), and physical processes of destruction, suspension, transport, deposition and cementation. We are creating a knowledge base (KB) containing empirical quantitative data about individual, population and community properties of major calcifying and bio-eroding species to capture the ecological variation inherent in all biological processes, both spatial (e.g. latitude, longitude, habitat, climate, oceanography, depth) and temporal (e.g. diurnal, seasonal, interannual). The KB will provide realistic values for input to a “virtual aquarium” of characteristic organisms at the center of biologically-based carbonate models describing the initiation, growth and maturation through ecological to geological timescales of such formations as shallow and deep-sea coral reefs, Halimeda beds, bryozoan reefs, and maerl deposits. +
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Marshes are highly dynamic landscapes that are shaped through feedbacks between hydrodynamic, morphodynamic, and ecological processes. Future marsh resilience is therefore dependent on the interaction between these different drivers rather than any individual piece. Marshes face a variety of threats, both natural and anthropogenic, resulting in a need for restoration actions that increase survivability. Because many of these threats are unprecedented or acting at unprecedented rates, statistical models do not adequately represent future conditions and require process-based models to better capture the complex interactions between both physical and ecological processes. The comprehensive marsh model integrates tidal flow, morphodynamics, and vegetation growth using the python based Landlab toolkit. This model is then applied at a site within the Seven Mile Island Innovation Laboratory complex in coastal New Jersey. +
Migration is a complex phenomenon that is impacted by economic, social, cultural, and environmental factors. This complexity makes it challenging to study, and especially challenging to understand how future environmental and climatic change may affect mobility and population movements. Agent-based modeling (ABM) is a promising but underutilized method for studying environmental impacts on human migration because of its ability to study connections between large-scale dynamics and individual decision-making. This work presents initial results from an original ABM that simulates household migration decisions in Bangladesh under environmental pressure. The model seeks to understand how riverbank erosion and land inundation impact mobility patterns under varying decision-making frameworks and livelihood opportunities. The model stochastically simulates inundation of land bordering a river. Agents whose land is flooded seek employment in a local labor market. Agents who cannot find employment within the community then face the decision to migrate or remain in the community with limited economic opportunity. We compare several different decision frameworks of varying complexity, in which the probability of choosing to migrate depends upon: household wealth alone, wealth, age, and household size, and finally using the Theory of Planned Behavior, which incorporates interactions between individual-level variables and community-level phenomenon, such as social norms, which are mediated through each agent’s social network. This model serves as a starting point to begin to test how different decision-making frameworks and environmental scenarios may produce different dynamics in the response to environmental stress. +
