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7 results for “sediment yield”
Hubbard Brook Experimental Forest: Sediment Yield in Weir Basins, 1956 - ongoing
Each year the sediment that collects in the stilling basin behind the v-notch weir is measured, excavated, sampled, dried, and weighed for Watersheds 1 through 8 at the Hubbard Brook Experimental Forest. Oven-dry weights are then calculated for all the sediment removed from the basin and extrapolated back over the watershed as mass of soil material lost per unit area. These data were gathered at the Hubbard Brook Experimental Forest in Woodstock, NH, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Cover crop application on dredged sediments increases corn yield through microorganism-associated enzyme-driven nutrient mineralization.
Common strategies to mitigate soil degradation of agricultural soils include cover crop application and soil amendment addition. Applying dredged sediments as a soil amendment is gaining popularity since they often provide benefits other amendments lack; however, their use with a cover crop is largely unexplored. To understand how cover crop use changes the restorative properties of dredged sediments, we assessed soil physical and chemical properties, enzymatic activities, and corn yield for plots of dredged sediments with and without a cover crop. Cover crop application on dredged sediments increased corn yields by ~24% when compared to dredged sediments alone. Increases in corn yield were driven by changes in nutrient mineralization, specifically within the nitrogen cycle. The physical and chemical properties of dredged sediments remained unchanged regardless of cover crop application. Our results suggest that when cover crops are applied to dredged sediments, crop yield increased through microorganism-driven nutrient mineralization. However, the physical and chemical environment remained optimal for corn growth within dredged sediments, regardless of cover crop application. This research is a vital step into understanding the use of dredged sediments in agricultural soil systems.
Soil Erosion and Sediment Yield Modeling - Southern Caspian Sea River Basins
<p>Soil Erosion and Sediment Yield Modeling - Southern Caspian Sea River Basins</p>
Dataset and codes for "BaHSYM: parsimonious Bayesian Hierarchical Model to predict river Sediment Yield"
<p>This folder contains:</p> <ul> <li>R project file</li> <li>R code for Best Fit model</li> <li>R code for temporal cross-validation</li> <li>R code for spatial cross-validation</li> <li>R code for cluster analysis</li> <li>dataset containing all input variables for the river gauges (and catchments) used for the development and testing of the BaHSYM model in Austria</li> </ul> <p>It also contains the same codes and datasets adapted to reproduce the model by de Vente et al. (2011), i.e. with the same structure but with the variables used in such model.</p>
Supplementary material 1 from: Brasell KA, Pochon X, Howarth J, Pearman JK, Zaiko A, Thompson L, Vandergoes MJ, Simon KS, Wood SA (2022) Shifts in DNA yield and biological community composition in stored sediment: implications for paleogenomic studies. Metabarcoding and Metagenomics 6: e78128. https://doi.org/10.3897/mbmg.6.78128
Figures S1–S4
Supplementary material 2 from: Brasell KA, Pochon X, Howarth J, Pearman JK, Zaiko A, Thompson L, Vandergoes MJ, Simon KS, Wood SA (2022) Shifts in DNA yield and biological community composition in stored sediment: implications for paleogenomic studies. Metabarcoding and Metagenomics 6: e78128. https://doi.org/10.3897/mbmg.6.78128
Table S1
Quantitatively distinguishing the factors driving runoff and sediment yield variations in karst watersheds: relevant data.
<p>Due to the coupled or interconnected relationships among frequent climate extremes, unique geological conditions, discontinuous soil distribution, rugged geomorphology, and highly heterogeneous landscapes in different karst watersheds, few studies were conducted to decouple the relative magnitudes of the of climate, lithology, soil, topography, and landscape on soil erosion in karst regions. The objective of this study was to quantify the relative importance of these influencing factors on <span>runoff</span> and sediment <span>yield </span>in 40 typical karst watersheds in southwest China. To address this issue, the Pearson correlation and random forest were firstly to select the dominant factors influencing runoff and sediment yield. Subsequently, the partial least squares-structural equation model (PLS-SEM) was used to decouple the complex relationships among runoff, sediment <span>yield</span> and their potential influencing factors. Results showed that climate, lithology, soil, topography and landscape could explain 79% of the runoff variation, and only climate factors <span>have</span> significant impact on runoff <span>for heterogeneous karst watersheds</span> (<em>P</em><0.01<span>, </span>path coefficient (<em><span>β</span></em>)<span>=</span><span>0.589</span>). T<span>he explanation of </span>five factors <span>to sediment yield</span> variability <span>is </span>59%<span>, and the </span>landscape <span>ha</span>s the greatest impact on sediment yield <span>(</span><em><span>P</span></em><span><0.01, </span><em><span>β</span></em><span>=-0.458</span><span>)</span>. Different from runoff, climatic factors have no significant influence on sediment yield. By elucidating a complex coupled relationship framework, this study can provide a scientific basis for the formulation of soil and water loss program, and the optimization of land resources and ecological environment sustainable development in karst watersheds.</p>
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OpenNeuro
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