The matlab code, digital elevation data, and landslide volume data here support the findings of Medwedeff et al. (2024) in JGR: Earth Surface. In this article, we study past landslides to understand how the strength of rocks and soil vary across the landscape and below the ground. We develop a matlab-based model that uses the length, width, slope angle, and thickness of landslides that have occurred in the past to estimate how strong the rock or soil was before it gave way. We improve upon previous studies by using elevation data from before and after landslides occurred to measure how thick the sliding mass was for each landslide. The thickness measurements help us understand how the strength of the ground changes as a function of depth below the surface, like for example, when rocks get weaker near the surface due to increased weathering. We apply our model to landslides that occurred during earthquakes in Greece and Nepal, and we compare the results to rock strength field data. In addition to our model code, we include in this data repository the landslide volume and elevation data for Nepal and Greece that we used to run our model for this study.
Medwedeff, W.G., Clark, M.K., Zekkos, D. (in review 2024) Regional Back-Analysis of Earthquake Triggered Landslide Inventories: a 2D Method for Estimating Rock Strength from Remote Sensing Data. In review in JGR Earth Surface.
The research that produced this data tested how sleep loss impacted the phenomena of reactivation and replay, which occurs when recently-learned information is reactivated/replayed during post-learning sleep/rest.
This dataset is part of a research project that aims to study how bark and wood traits shape species ecological strategies at the seedling stage in four tropical forests in Colombia. These forests are located in the municipalities of Jabiru (Tolima), Cotove (Antioquia), Colorados (Bolivar) and Tyrona (Magdalena). Detailed information on the location of these forests can be found in: https://doi.org/10.1111/ele.13659
This collection contains estimates of the water balance of the Laurentian Great Lakes that were produced by the Large Lakes Statistical Water Balance Model (L2SWBM). Each data set has a different configuration and was used as the supplementary for a published peer-reviewed article (see "Citations to related material" section in the metadata of individual data sets). The key variables that were estimated by the L2SWBM are (1) over-lake precipitation, (2) over-lake evaporation, (3) lateral runoff, (4) connecting-channel outflows, (5) diversions, and (6) predictive changes in lake storage. and Contact: Andrew Gronewold
Office: 4040 Dana
Phone: (734) 764-6286
Email: drewgron@umich.edu
Smith, J. P., & Gronewold, A. D. (2017). Development and analysis of a Bayesian water balance model for large lake systems. arXiv preprint arXiv:1710.10161., Gronewold, A. D., Smith, J. P., Read, L., & Crooks, J. L. (2020). Reconciling the water balance of large lake systems. Advances in Water Resources, 103505., and Do, H.X., Smith, J., Fry, L.M., and Gronewold, A.D., Seventy-year long record of monthly water balance estimates for Earth’s largest lake system (under revision)
Professor Revzen and his team at the Biologically Inspired Robotics and Dynamical Systems (BIRDS) Lab are working on discovering, modeling, and reproducing the strategies animals use when interacting with physical objects. This work consists of collaboration with biomechanists to analyze experimental data, developing new mathematical tools for modeling and estimation of model parameters, and construction of robots which employ the new principles.
This sub-collection includes Photographs and Photologs of the sites, a Site Database with information collected and observed about the site and Site documentation. Documentation consists of PDFs of scans of miscellaneous documents related to a particular site, including maps, wall drawings, original notes, etc. Data are organized according to site number: S001, S002, etc. There are 17 sites in total.
The following works contain the databases, field notebooks, unit and profile drawings, photographs, photo descriptions, radiocarbon dates, and geophysical survey data related to the Gajtan settlement excavation.
This database contains six datasets intended to aid in the conception, training, demonstration, evaluation, and comparison of reduced-complexity models for fluid mechanics. The six datasets are: large-eddy-simulation data for a turbulent jet, direct-numerical-simulation data for a zero-pressure-gradient turbulent boundary layer, particle-image-velocimetry data for the same boundary layer, direct-numerical-simulation data for laminar stationary and pitching flat-plate airfoils, particle-image-velocimetry and force data for an airfoil encountering a gust, and large-eddy-simulation data for the separated, turbulent flow over an airfoil.
All data are stored within hdf5 files, and each dataset additionally contains a README file and a Matlab script showing how the data can be read and manipulated. Since all datafiles use the hdf5 format, they can alternatively be read within virtually any other programing environment. An example.zip file included for each dataset provides an entry point for users.
The database is an initiative of the AIAA Discussion Group on Reduced-Complexity Modeling and is detailed in the paper listed below. For each dataset, the paper introduces the flow setup and computational or experimental methods, describes the available data, and provide an example of how these data can be used for reduced-complexity modeling. All users should cite this paper as well as appropriate primary sources contained therein.
Towne, A., Dawson, S., Brès, G. A., Lozano-Durán, A., Saxton-Fox, T., Parthasarthy, A., Biler, H., Jones, A. R., Yeh, C.-A., Patel, H., Taira, K. (2022). A database for reduced-complexity modeling of fluid flows. AIAA Journal 61(7): 2867-2892.
The Division of Reptiles and Amphibians maintains a collection that is worldwide in scope. The research collections contain over 200,000 catalogued lots representing approximately 435,000 individual specimens.
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