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12 results for “soil erosion modelling”
Long term response of arctic tussock tundra to thermal erosion features: A modeling analysis. Tussock tundra regrowth after a thermal erosion event: Simulation A - increased Phase II soil organic matter
The Multiple Element Limitation (MEL) model is used to simulate the recovery of Alaskan arctic tussock tundra to thermal erosion features (TEFs) caused by permafrost thaw and mass wasting. TEFs could be significant to regional carbon (C) and nutrient budgets because permafrost soils contain large stocks of soil organic matter (SOM) and TEFs are expected to become more frequent as climate warms. These simulations deal only with recovery following TEF stabilization and do not address initial losses of C and nutrients during TEF formation. To capture the variability among and within TEFs, we simulate a range of post-stabilization conditions by varying the initial size of SOM pools and nutrient supply rates. This file contains the results for 100 years of tussock tundra recovery after a thermal erosion event. This simulation is of TEF recovery with increased Phase II soil organic matter compared to the base simulation. Data is presented for day 250 of each year.
Long term response of arctic tussock tundra to thermal erosion features: A modeling analysis. Tussock tundra regrowth after a thermal erosion event: Simulation C - increased Phase I and Phase II soil organic matter
The Multiple Element Limitation (MEL) model is used to simulate the recovery of Alaskan arctic tussock tundra to thermal erosion features (TEFs) caused by permafrost thaw and mass wasting. TEFs could be significant to regional carbon (C) and nutrient budgets because permafrost soils contain large stocks of soil organic matter (SOM) and TEFs are expected to become more frequent as climate warms. These simulations deal only with recovery following TEF stabilization and do not address initial losses of C and nutrients during TEF formation. To capture the variability among and within TEFs, we simulate a range of post-stabilization conditions by varying the initial size of SOM pools and nutrient supply rates. This file contains the results for 100 years of tussock tundra recovery after a thermal erosion event. This simulation is of TEF recovery with increased Phase I and Phase II soil organic matter compared to the base simulation. Data is presented for day 250 of each year.
Long term response of arctic tussock tundra to thermal erosion features: A modeling analysis. Tussock tundra regrowth after a thermal erosion event: Simulation D - reduced Phase I and Phase II soil organic matter
The Multiple Element Limitation (MEL) model is used to simulate the recovery of Alaskan arctic tussock tundra to thermal erosion features (TEFs) caused by permafrost thaw and mass wasting. TEFs could be significant to regional carbon (C) and nutrient budgets because permafrost soils contain large stocks of soil organic matter (SOM) and TEFs are expected to become more frequent as climate warms. These simulations deal only with recovery following TEF stabilization and do not address initial losses of C and nutrients during TEF formation. To capture the variability among and within TEFs, we simulate a range of post-stabilization conditions by varying the initial size of SOM pools and nutrient supply rates. This file contains the results for 100 years of tussock tundra recovery after a thermal erosion event. This simulation is of TEF recovery with reduced Phase I and Phase II soil organic matter compared to the base simulation. Data is presented for day 250 of each year. .
Long term response of arctic tussock tundra to thermal erosion features: A modeling analysis. Tussock tundra regrowth after a thermal erosion event: Simulation B - increased Phase I soil organic matter
The Multiple Element Limitation (MEL) model is used to simulate the recovery of Alaskan arctic tussock tundra to thermal erosion features (TEFs) caused by permafrost thaw and mass wasting. TEFs could be significant to regional carbon (C) and nutrient budgets because permafrost soils contain large stocks of soil organic matter (SOM) and TEFs are expected to become more frequent as climate warms. These simulations deal only with recovery following TEF stabilization and do not address initial losses of C and nutrients during TEF formation. To capture the variability among and within TEFs, we simulate a range of post-stabilization conditions by varying the initial size of SOM pools and nutrient supply rates. This file contains the results for 100 years of tussock tundra recovery after a thermal erosion event. This simulation is of TEF recovery with increased Phase I soil organic matter compared to the base simulation. Data is presented for day 250 of each year.
Long term response of arctic tussock tundra to thermal erosion features: A modeling analysis. Tussock tundra regrowth after a thermal erosion event: Simulation E - reduced Phase I soil organic matter
The Multiple Element Limitation (MEL) model is used to simulate the recovery of Alaskan arctic tussock tundra to thermal erosion features (TEFs) caused by permafrost thaw and mass wasting. TEFs could be significant to regional carbon (C) and nutrient budgets because permafrost soils contain large stocks of soil organic matter (SOM) and TEFs are expected to become more frequent as climate warms. These simulations deal only with recovery following TEF stabilization and do not address initial losses of C and nutrients during TEF formation. To capture the variability among and within TEFs, we simulate a range of post-stabilization conditions by varying the initial size of SOM pools and nutrient supply rates. This file contains the results for 100 years of tussock tundra recovery after a thermal erosion event. This simulation is of TEF recovery with decreasing Phase I soil organic matter compared to the base simulation. Data is presented for day 250 of each year.
Modelling impacts of tramlines on soil erosion processes at the catchment scale.
<p>The data refers to the following article:</p> <p>Saggau, P., M. Kuhwald, W. B. Hamer, R. Duttmann (2021): Are compacted tramlines underestimated features in soil erosion modelling? A catchment‐scale analysis using a process‐based soil erosion model. In: Land Degradtaion & Development. doi: 10.1002/ldr.4161</p> <p>The data only contains distributable raw data and R-codes.</p>
Dataset of bank soil parameters and stochastic modelling of bank erosion processes in the Middle Yangtze River
<p><span>A probabilistic process-based model of bank erosion has proposed, </span><span>embedding the probability distributions of</span><span> different bank soil parameters. <span><span> The dataset includes the spatial distribution characteristics of critical shear stress, friction angle, and cohesion. The prediction results analyzed the effects of soil erosion resistance capacity and the variability of shear strength parameters in the simulation of bank erosion processes, obtaining the probability of mass failure and the distributions of bank erosion width. Additionally, the study investigated the effect of varying water content on bank erosion modeling and further analyzed how considering more influencing factors in the model affects prediction uncertainty and accuracy. Moreover, the relationship between the variability of these factors and river morphology was discussed. The dataset provides the aforementioned prediction results, and relevant plots were generated using MATLAB or Python, with the associated plotting code also uploaded.</span></span></span></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>
Incorporating biological soil crusts into the B factor to enhance the accuracy of soil erosion models in drylands
Open the record for dataset details and reuse information.
Integrated Modeling of Flow, Soil Erosion, and Nutrient Dynamics in a Regional Watershed: Assessing Natural and Human-Induced Impacts
<p>Attached file is the verification data for the submitted manuscript "Integrated Modeling of Flow, Soil Erosion, and Nutrient Dynamics in a Regional Watershed: Assessing Natural and Human-Induced Impacts" .</p>
Soil Erosion and Sediment Yield Modeling - Southern Caspian Sea River Basins
<p>Soil Erosion and Sediment Yield Modeling - Southern Caspian Sea River Basins</p>
Soil Erosion Modeling dataset
<p><strong><span>Descriptions of the soil erosion modeling dataset</span></strong></p> <p><span>Introduction</span></p> <p><span>The "Soil Erosion Modeling dataset.xlsx" file contains data on soil erosion modeling studies conducted in Ethiopia. It includes information about the study area, modeling methods, erosion agents, soil loss estimates, and model validation techniques. This dataset can be used to analyze trends in soil erosion modeling research in Ethiopia, identify the most used models and methods, and assess the effectiveness of different soil conservation practices. The dataset <span>focuses on studies related to soil erosion modeling and contains detailed information on various research articles. </span></span></p> <p><strong><span>Methodology</span></strong></p> <p><span>The data was collected from scientific peer-reviewed papers published between 2003 and 2023 in reputable<span>, Scopus-indexed international journals. We used the Scopus, ScienceDirect, and SpringerLink databases to retrieve and download all the articles in the present dataset. The dataset contains 38 attributes, 38 columns, and 371 rows, excluding the header. </span></span></p> <p><strong><span>Here's a brief description of the dataset:</span></strong></p> <p><span>Sheet Name: Sheet1</span></p> <p><span>Total Columns: 38</span></p> <p><span>Total Rows: Includes multiple rows<span>, each representing a distinct research study.</span></span></p> <p><strong><span>Column Descriptions</span></strong></p> <p><span>ID: Unique identifier for each study.</span></p> <p><span>Publication Year: The year the study was published.</span></p> <p><span>Publisher: The publishing entity.</span></p> <p><span>Journal: The journal where the study was published.</span></p> <p><span>DOI: Digital Object Identifier for the study.</span></p> <p><span>Authors: contains authors of each study.</span></p> <p><span>Title: Title of the research paper.</span></p> <p><span>Region of Study: Geographic region where the study was conducted.</span></p> <p><span>Name of the Study Area: Specific area within the region.</span></p> <p><span>Study Scale: The scale at which the study was conducted (e.g., Watershed, Plot).</span></p> <p><span>Erosion Agent: The agent at which the study was aimed</span></p> <p><span>Modeling Type: Modeled <span>erosion type (e.g., Rill and sheet, sediment yield)</span></span></p> <p><span>Quantification Synthesis: a <span>method of soil loss estimate (gross, net)</span></span></p> <p><span>The approach of soil loss estimate: The methodology (qualitative/quantitative)</span></p> <p><span>Average Soil loss (Mg ha-1 yr-1): The predicted average soil loss for each study</span></p> <p><span>Model Name: contains the name of all soil erosion models <span>applied in Ethiopia</span></span></p> <p><span>Modeling Aim: The aim at which the study was focused</span></p> <p><span>LUC/BMPs Status: The studies that focused on land use change or best management practices</span></p> <p><span>Modeled land use/cover (LU): The <span>land use/cover in which the study was modeled</span></span></p> <p><span>Land use/cover data sources: The sources of land use and land cover data for each study</span></p> <p><span>Modeled Period: The period when the study period was focused on</span></p> <p><span>Latitude/Longitude: The geographic coordinates of the study area</span></p> <p><span>Altmin/Altmax: The maximum and minimum altitude</span></p> <p><span>Area: Contains the area of each study</span></p> <p><span>Rainfall data indicative period: The period when the rainfall data was collected for each study</span></p> <p><span>Rainfall Data Type: <span>The type of rainfall data (point, gridded, etc.)</span></span></p> <p><span>Rainfall Time Resolution: Temporal resolution of the rainfall data (e.g., Daily, Event-based).</span></p> <p><span>Rainfall Amount (mm): Annual or seasonal rainfall amount.</span></p> <p><span>DEM Size for Topography: The size of Digital Elevation Model resolution.</span></p> <p><span>Fieldwork Activities: Whether fieldwork was conducted (Yes/No).</span></p> <p><span>Type of Fieldwork Activities: Specific types of fieldwork activities conducted.</span></p> <p><span>Soil Sampling Activities: <span>Was soil sampling conducted (Yes/No)?</span></span></p> <p><span>Type of Soil Information: <span>The soil information collected (e.g., Point, Maps).</span></span></p> <p><span>Validation of Model Results: Whether the model results were validated (Yes/No).</span></p> <p><span>Type of Validation: Method used for validation (e.g., Measured Sediment Yield).</span></p> <p><span>Model Calibration: Whether the model was calibrated (Yes/No).</span></p>
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