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476 results for “Erosive”
InRESatE: Indian Regional Satellite based Erosivity Estimates
<p>The R-factor serves as a climatological index, reflecting the intensity and kinetic energy of rainfall and playing a pivotal role in evaluating the impacts of sheet and rill erosion.</p> <p>The InRESatE dataset introduces rainfall erosivity data, estimated from high-resolution IMERG Final Run 30-minute precipitation records spanning 2001 to 2018. Additionally, the dataset includes erosivity density values and calibrated parameters for a daily rainfall erosivity model tailored to the study area.</p> <p>Our analysis reveals an annual rainfall erosivity range of 77 to 20,662 MJ mm ha−1h−1 yr−1, with the summer monsoons accounting for approximately 85% of this yearly erosivity. While our erosivity map closely aligns with previous versions of rainfall erosivity datasets based on sparse gauge data, it registers marginally lower values in regions experiencing extreme rainfall. Erosivity density maps highlight erosion and landslide-prone zones, particularly in India's Northeast and Western Ghats regions, attributed to intense summer monsoon rainfall.</p> <p> </p> <p>Article Citation:</p> <p>Das, Subhankar, Manoj Kumar Jain, and Vivek Gupta. "A step towards mapping rainfall erosivity for India using high-resolution GPM satellite rainfall products." Catena 212 (2022): 106067. https://doi.org/10.1016/j.catena.2022.106067</p>
Data presented in Dupont et al. 2024 "Impact of dust source patchiness on the existence of a constant dust flux layer during aeolian erosion events"
<p>Meteorological and dust data used in Dupont et al. 2024. Data are based on measurements recorded above two erosive surfaces from two very different desert regions, one at a high-latitude location in Iceland and the other at a low-latitude location in Jordan. The Iceland campaign was co-organized by two projects: FRAGMENT (FRontiers in dust minerAloGical coMposition and its Effects upoN climaTe) and HiLDA (Iceland as a model for high-latitude dust sources – a combined experimental and <br>modeling approach for characterization of dust emission and transport processes); and the Jordan campaign (J-WADI: Jordan Wind erosion And Dust Investigation) was co-organized by the FRAGMENT and Helmholtz Young Investigator Group ``A big unknown in the climate impact of atmospheric aerosol: Mineral soil dust'' projects.</p>
Monitoring the effect of water erosion on soil surface microtopography using Lidar
<p>This dataset contains three dimensional (3D) reconstructions of laboratory soil surfaces eroding under rainfall simulation experiments. Experiments were conducted using the Walnut Gulch Rainfall Simulator at the USDA-ARS Southwest Watershed Research Center in Tucson, Arizona. A terrestrial laser scanner was used to collect soil surface 3D data.</p>
GeoTIFF Dataset for: Land-to-sea mapping of the glacial erosion unconformity reveals evolution of the Jasmund Glacitectonic Complex East of Rügen Island (SW Baltic Sea)
<p>This dataset comprises two GeoTIFF files, both with a WGS84 UTM 33 N (EPSG: 32633) projection. The erosional unconformity has a grid size of 100 x 100 metres, while the moraine or raft feature was gridded using a grid size of 20 x 20 metres. The two files were created using marine-multichannel seismic data from the Hübscher et al. (2024) dataset (<a href="https://deref-gmx.net/mail/client/7eMD7NnHVnY/dereferrer/?redirectUrl=https%3A%2F%2Fzenodo.org%2Fdoi%2F10.5281%2Fzenodo.11242567" target="_blank" rel="noopener">10.5281/zenodo.11242567</a>). The dataset was employed in the preparation of Paper by the same authors (<a href="https://doi.org/10.1029/2024GL111603">https://doi.org/10.1029/2024GL111603</a>).</p>
The role of non-native plant species in modulating riverbank erosion: a systematic review - extracted coded articles dataset
<p>Data extraction sheet of code typologies for the review titled: The role of non-native plant species in modulating riverbank erosion: a systematic review. The uploaded csv file contains all the extracted values for each typology. </p>
Input data for soil erosion practical
<p>This dataset is to be used for the soil erosion practical published at: https://github.com/wieka29/Soil-erosion-practical</p> <p> </p>
Long-term data from field erosion plot studies in eastern Austria
<p>Long-term runoff plot experiments were conducted at three sites in eastern Austria to evaluate the impact of conservation tillage. Following soil tillage treatments were investigated: 1) conventional tillage with ploughing in fall (CT), 2) mulch tillage with cover crops during winter period (MT), and 3) no tillage with cover crops during winter period (NT). Soil textures range from silt loam to loam.</p> <p>Datasets include for each site and each year the period of operation of the plots, the planted crop, the annual precipitation, surface runoff, soil loss, surface losses of nitrogen, phopshorus and soil organic carbon as well as absolute and relative crop yields.</p>
Long-term data from field erosion plot studies in eastern Austria
<p>Long-term runoff plot experiments were conducted at three sites in eastern Austria to evaluate the impact of conservation tillage. Following soil tillage treatments were investigated: 1) conventional tillage with ploughing in fall (CT), 2) mulch tillage with cover crops during winter period (MT), and 3) no tillage with cover crops during winter period (NT). Soil textures range from silt loam to loam.</p> <p>Datasets include for each site and each year the period of operation of the plots, the planted crop, the annual precipitation, surface runoff, soil loss, surface losses of nitrogen, phopshorus and soil organic carbon as well as absolute and relative crop yields.</p>
Early Mars EBM data for "CLIMATE SIMULATIONS OF EARLY MARS WITH ESTIMATED PRECIPITATION, RUNOFF, AND EROSION RATES"
<p>These are all the data and plots we used for the publication, CLIMATE SIMULATIONS OF EARLY MARS WITH ESTIMATED PRECIPITATION, 2 RUNOFF, AND EROSION RATES.</p>
Supplementary XRD Material for "Experimental Constraints on Barium Isotope Fractionation during Adsorption-Desorption Reactions: Implications for Weathering and Erosion Tracer Applications"
<p><strong>Repository Overview:</strong> Supplementary powder X-ray diffraction (XRD) data for the study "Experimental Constraints on Barium Isotope Fractionation during Adsorption-Desorption Reactions: Implications for Weathering and Erosion Tracer Applications"</p> <p><strong>Data Provided:</strong> Powder X-ray diffractograms of the minerals used in the laboratory batch experiments. Pow</p> <p><strong>Minerals Analysed:</strong></p> <p><span>Clay Minerals:</span></p> <ul> <li>Kaolinite (KGa-2): purchased from the Clay Minerals Society (CMS).</li> <li>Montmorillonite (SWy-2): purchased from the Clay Minerals Society (CMS).</li> </ul> <p><span>Iron Oxyhydroxide Minerals:</span></p> <ul> <li>Goethite synthesised under alkaline conditions in the laboratories at the Department of Earth Sciences, University of Cambridge, following the method detailed in Schwertmann and Cornell (2008).</li> <li>2-line ferriydrite synthesised in the laboratories at the Department of Earth Sciences, University of Cambridge, following the method detailed in Schwertmann and Cornell (2008) methods.</li> </ul> <p><strong>XRD Methods:</strong></p> <ul> <li>Instrument and Set Up: Theta-Theta D8 Bruker Advance diffractometer with a Mo anode, Lynxeye XE-T PSD detector and 2 mm divergent slit.</li> <li>Sample Preparation: Zero-background monocrystalline silicon plate was used to minimize sample mass. The X-ray diffractogram of the silicon plate was measured prior to each sample measurement.</li> <li>Clay Minerals: 0.02° step size and a 3s step rate.</li> <li>Iron Oxyhydroxide Minerals: 0.03° increments and a 1s step rate.</li> </ul> <p><strong>Purpose of XRD Analyses:</strong></p> <ul> <li>To verify the correct synthesis of iron oxyhydroxide phases and to detect impurities.</li> <li>To monitor any mineralogical changes that occurred during adsorption-desorption reactions with water.</li> </ul> <p><strong>Data Format</strong></p> <table> <tbody> <tr> <td><strong>Column Name</strong></td> <td><strong>Description</strong></td> <td><strong>Unit</strong></td> </tr> <tr> <td>twotheta</td> <td>2θ</td> <td>°</td> </tr> <tr> <td>intensity</td> <td>intensity</td> <td>counts per second (cps)</td> </tr> <tr> <td>ID</td> <td>mineral ID</td> <td>unitless</td> </tr> <tr> <td>mineral</td> <td>mineral name</td> <td>unitless</td> </tr> <tr> <td>duration</td> <td>reaction duration</td> <td>minutes</td> </tr> </tbody> </table> <p><strong>Extra Notes</strong></p> <p>A reaction duration of zero minutes corresponds to an unreacted mineral sample.</p>
Measured properties in soil samples and marine sediment collected in Galion Bay (Martinique, France) in order to trace erosion sources in insular tropical catchments
<p>This dataset was compiled in order to select the optimal suite of tracers and identify and quantify the main sources of sediment deposited in Galion Bay and associated chlordecone transfers since the 1960s. It includes measured properties for potential sources collected across the Galion catchment (Martinique, France) and along a sediment core sampled in Galion Bay (GAL17-04, N°IGSN TOAE0000000573). Associated with this dataset, metadata are integrated for sources and targets registered using International Geological Sample Numbers (IGSN).</p>
Replication Package for the Paper: Understanding Software Architecture Erosion: A Systematic Mapping Study
<p>This is the replication package for the paper: "Understanding Software Architecture Erosion: A Systematic Mapping Study". It contains five files as described below:</p> <p><strong>1. List of the Selected Studies_SMS.xlsx</strong><br> includes the detailed information of the 73 selected studies.</p> <p><strong>2. Data Extraction.xlsx</strong><br> includes the extracted data based on the data items (i.e., D1-D16).</p> <p><strong>3. Sample of Study Selection.xlsx</strong><br> includes the 100 randomly selected papers from the search results and the results of each round selection.</p> <p><strong>4. Pilot Data Extraction.xlsx</strong><br> includes the pilot data extraction results from five papers.</p> <p><strong>5. Sample of Data Extraction.xlsx</strong><br> includes the data extraction results from another randomly selected five papers.</p>
Electronic supplemental material for Mann et al. "Multi-decadal records of shoreline erosion reveal the roles of river delta dynamics, hard protection measures, and other interventions in Eastern Ghana"
<p>Electronic supplemental material for Mann et al. "Multi-decadal records of shoreline erosion reveal the roles of river delta dynamics, hard protection measures, and other interventions in Eastern Ghana"</p> <p><br> The supplemental material comprises the database "Geodatabase Ghana.mdb" and the MSc thesis by Aleksandra Serwa (Serwa 2017), the results of which built the foundation for the paper.</p> <p>The database contains one layer with all digitized shorelines (HWL_END) as indicated in table 1 of the manuscript, and additional baseline and transect layers that are necessary for the shoreline change analyses with DSAS (Thieler & Danforth 1994). Further information can be found in Serwa (2017).</p> <p>References:</p> <p>Serwa, A., 2017. Shoreline changes in the Keta Municipal District (Ghana): Evidence from multi-decadal records. Master Thesis, Department of Geosciences, University of Bremen, 88 p.</p> <p><br> Thieler, E.R. & Danforth, W.W., 1994. Historical Shoreline Mapping ( II ): Application of the Digital Shoreline Mapping and Analysis Systems ( DSMS / DSAS ) to Shoreline Change Mapping in Puerto Rico. Journal of Coastal Research, 10(3), pp.600–620.</p>
META-DATA for IEA Wind Task 46. WP2: Atmospheric drivers of wind turbine blade leading edge erosion: Ancillary variables
<p>Leading edge erosion (LEE) of wind turbine blades has been identified as a major factor in decreased wind turbine blade lifetimes and energy output over time. Accordingly, the International Energy Agency Wind Technology Collaboration Programme (IEA Wind TCP) created Task 46 to undertake cooperative research in the key topic of blade erosion.</p> <p>This report is a product of WorkPackage 2 <strong>Climatic conditions driving blade erosion. </strong></p> <p>The objectives of the work summarized in this report are to:</p> <ul> <li>Summarize efforts to elucidate critical atmospheric co-stressors that may accelerate leading edge erosion and hence for which meta-data regarding observations should be collated.</li> <li>Briefly describe and summarize additional data pertaining to those LEE co-stressors from sites that were the focus of analyses of hydrometeors in the report “Atmospheric drivers of wind turbine blade leading edge erosion: Hydrometeors” (Pryor et al. 2021)</li> </ul> <p>Accompanying this report is a detailed spreadsheet that summarizes the meta-data regarding these co-stressor variables.</p>
Dataset: Proposed Origin of the Burns Formation (Meridiani Planum, Mars) by Erosion, Reworking, and Diagenetic Alteration of a Grasberg-like Precursor
<p>Dataset for the study entitled "Proposed Origin of the Burns Formation (Meridiani Planum, Mars) by Erosion, Reworking, and Diagenetic Alteration of a Grasberg-like Precursor" submitted to JGR-Planets. Contents include: (1) a compilation of chemical compositions for the Burns, Grasberg, and Murray formations, basaltic rocks, and soils measured by rovers on Mars; (2) geochemical mass-balance models for diagenetic addition of MgO and SO3 to the Burns formation; (3) diagrams and additonal calculations based on the compiled set of chemical compositions.</p>
Long-term soil erosion monitoring in China using the RUSLE model based on Google Earth Engine
<p>This dataset contains soil erosion maps in China at 500m resolution from 2010 to 2020. The dataset is stored in GeoTif format with the unit of t/(km<sup>2 </sup>· a).</p>
Vulnerability of sea turtle nesting sites to erosion and inundation: a decision support framework to maximize conservation
<p>Sandy beaches provide essential nesting habitat for sea turtles but are threatened globally by a rapidly changing climate. Identifying which nesting sites are at greatest risk from erosion and inundation remains an important goal of sea turtle conservation globally. Yet, efforts to identify at-risk sites have been hindered by the ability to model complex processes and incomplete information on nesting distribution and abundance. To assess the erosion and inundation risk to the reproductive success of a discrete genetic stock of flatback turtles (<em>Natator</em> <em>depressus</em>) across its nesting range in the Pilbara region of Western Australia, we used the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) Coastal Vulnerability Model. A relative exposure index was calculated for 402 nesting beaches in terms of six geophysical variables: wind and wave exposure, surge potential, relief, observed sea level rise and coastal geomorphology, and coupled with published information on the distribution and abundance of turtle tracks in the region. </p> <p>The majority of beaches (74%) had an intermediate to high exposure. In particular, 36% of beaches with a high abundance of flatback tracks (the top 25% of the frequency distribution) had a high exposure (the top 25% of the frequency distribution). This suggests that coastal exposure is a key vulnerability to the reproductive success of sea turtles that nest in this region. Promisingly, five beaches with a high abundance of turtle tracks also had a low exposure (bottom 25% of the frequency distribution) and these beaches may be critical for the long-term resilience of the stock against sea level rise and severe storms. Exposure varied across nesting sites and the approach presented here allows for a rapid and broadscale assessment of relative erosion and inundation risks at a scale most relevant to management. </p>
Indian Rainfall Erosivity Dataset (IRED)
<p>Soil erosion induced by water has been identified as one of the major environmental problems worldwide. The erosive force of rainfall, also known as rainfall erosivity (R-factor), is the potential of rain to cause soil degradation and one of the factors in the widely adopted RUSLE (Revised Universal Soil Loss Equation) empirical soil erosion estimation model. About 68.4% of total eroded soil in India is eroded due to erosion by water, and rainfall erosivity is one of the major factors. The past assessments of rainfall erosivity in India were however largely based on rain-gauge recordings and surveys which hinders its understanding and estimation over large areas. Growing availability of gridded precipitation datasets presents an unprecedented opportunity to study long-term rainfall erosivity over varied terrains and address some of the limitations of point data-based studies. IRED (Indian Rainfall Erosivity Dataset) is the first such national-scale assessment of rainfall erosivity over India using gridded precipitation datasets, which will be helpful for agricultural experts, watershed managers, agronomists, and soil-conservational experts in order to understand and mitigate rainfall-induced erosion. In this dataset, long term yearly average R-factor, Fourier Index (FI), and Modified Fourier Index (MFI) maps have been included with a distributional analysis over IMD (India Metrological Department) defined regions, states and districts of India.</p>
Genetic erosion in an endangered desert fish during a multi-decadal megadrought despite long-term supportive breeding
<p>Human water use combined with a recent megadrought have reduced river and stream flow through the Southwestern United States and led to periodic drying of formerly perennial river segments. Reductions in snowmelt runoff and increased extent of drying collectively threaten short-lived, obligate aquatic species, including the endangered Rio Grande Silvery Minnow. This species experiences 'boom-and-bust' population dynamics where large fluctuations in abundance are expected to lower estimates of effective population size and erode genetic diversity over time. Rates of diversity loss are also affected by additions of hatchery-origin fish used to supplement the wild population. We leveraged demographic and genetic data from wild and hatchery individuals to understand the relationship of genetic diversity and effective population size to abundance over the last two decades. Genetic diversity was low during the early 2000s, but diversity and demographic metrics stabilized after the hatchery program was initiated and environmental conditions improved. Yet, from 2017 onward, allelic diversity declined (Cohen's <em>d</em>=1.34) and remains low despite hatchery stocking and brief wild population recovery. Across the time series, single-sample estimates of effective population size (N<sub>eD</sub>) were positively associated (<em>r</em>=0.53) with wild/total abundance, but as the proportion of hatchery-origin spawners increased, N<sub>eD</sub> was reduced (N<sub>eD</sub> <em>r</em>= -0.55). Megadrought limits wild spawner abundance and precludes refreshment of hatchery brood stocks with wild fish, hence we predict an increasingly hatchery-dominated population, and accelerated loss of genetic diversity despite supplementation. We recommend an adaptive and accelerated management plan that integrates river flow management and hatchery operations to slow the pace of genetic diversity loss exacerbated by megadrought.</p>
Data from: Erosion regime controls sediment environmental DNA-based community reconstruction
<p><span>Analysis of environmental DNA detected in lake sediments shows promise to become a great paleoecological technique that can provide detailed information about organism communities living in past environments. However, when interpreting sedimentary environmental DNA records, it is of crucial importance to separate ecosystem responses to large-scale environmental change from 'noise' caused by changes in sediment provenance or potential post-depositional DNA mobility. In this study, we show that plant and mammalian communities reconstructed from sediments are strongly affected by sediment provenance, but unaffected by vertical mobility of DNA after sediment deposition. We observe that DNA from aquatic plants was abundant in background sediment, while embedded detrital event layers (sediment deposited under erosion events) primarily contained terrestrial plants; hence, vertical mobility of aquatic plant DNA across sediment layers was negligible within our studied lakes. About 33% of the identified terrestrial plant genera were only found in detrital sediment suggesting that sediment origin had a strong impact on the reconstructed plant community. Similarly, DNA of some mammalian taxa (<em>Capra hircus</em>, <em>Ursus arctos</em>, <em>Lepus</em>, <em>Felis</em>) were only or preferentially found in detrital event layers. Temporal changes across the Holocene were the main drivers of change for reconstructed plant communities, but sediment type was the second most important factor of variance. Our results highlight that erosion and sediment provenance need to be considered when reconstructing past mammalian and plant communities using environmental DNA from lake sediments.</span></p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.