The mixing layer theory is not suitable for predicting solute transfer from initially saturated soil to surface runoff water under controlled drainage conditions. By coupling the mixing layer theory model with the numerical model Hydrus-1D, a hybrid solute transfer model has been proposed to predict soil solute transfer from an initially saturated soil into surface water, under controlled drainage water conditions. The model can also consider the increasing ponding water conditions on soil surface before surface runoff. The data of solute concentration in surface runoff and drainage water from a sand experiment is used as the reference experiment. The parameters for the water flow and solute transfer model and mixing layer depth under controlled drainage water condition are identified. Based on these identified parameters, the model is applied to another initially saturated sand experiment with constant and time-increasing mixing layer depth after surface runoff, under the controlled drainage water condition with lower drainage height at the bottom. The simulation results agree well with the observed data. Study results suggest that the hybrid model can accurately simulate the solute transfer from initially saturated soil into surface runoff under controlled drainage water condition. And it has been found that the prediction with increasing mixing layer depth is better than that with the constant one in the experiment with lower drainage condition. Since lower drainage condition and deeper ponded water depth result in later runoff start time, more solute sources in the mixing layer are needed for the surface water, and larger change rate results in the increasing mixing layer depth.
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http://dx.doi.org/10.1007/s11356-016-6452-4 | DOI Listing |
Langmuir
January 2025
School of Chemistry, Key Centre for Polymers and Colloids, The University of Sydney, Sydney, New South Wales 2006, Australia.
Polymer Janus nanoparticles with one hard cross-linked polystyrene lobe and one soft film-forming poly(methyl methacrylate--butyl acrylate) lobe were synthesized by reversible addition-fragmentation chain transfer (RAFT)-mediated emulsion polymerization. The Janus nanoparticles adsorbed to oil/water and air/water interfaces, where the soft lobes coalesced, forming films of thickness between 25 and 250 nm; droplets of silicone oil could be stably encapsulated in polymer in this way. When prepared by mechanical mixing without additives, capsules of diameter 5-500 μm could be prepared, and with additives and application of heat, capsules of diameter around 5 μm were achieved, even with highly viscous silicone oil (20,000 cSt).
View Article and Find Full Text PDFACS Nano
January 2025
Creative Research Initiative Center for Nanospace-confined Chemical Reactions (NCCR), Pohang University of Science and Technology (POSTECH), Pohang 37673, Korea.
Unlike homogeneous metal complexes, achieving absolute control over reaction selectivity in heterogeneous catalysts remains a formidable challenge due to the unguided molecular adsorption/desorption on metal-surface sites. Conventional organic surface modifiers or ligands and rigid inorganic and metal-organic porous shells are not fully effective. Here, we introduce the concept of "ligand-porous shell cooperativity" to desirably reaction selectivity in heterogeneous catalysis.
View Article and Find Full Text PDFFEMS Microbiol Ecol
January 2025
Departamento de Innovación Biomédica, Centro de Investigación Científica y de Educación Superior de Ensenada, México.
Marine protists are key components of biogeochemical cycles and microbial food webs, which respond quickly to environmental factors. In the Gulf of Mexico (GoM), the Loop Current intensifies in summer and supplies the gulf with warm and oligotrophic waters. However, the cyclonic eddies within the GoM create favorable conditions for biological productivity by bringing nutrient-rich water to the subsurface layer.
View Article and Find Full Text PDFComput Methods Programs Biomed
January 2025
Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, 400714, China.
Background And Objective: Cloud-based Deep Learning as a Service (DLaaS) has transformed biomedicine by enabling healthcare systems to harness the power of deep learning for biomedical data analysis. However, privacy concerns emerge when sensitive user data must be transmitted to untrusted cloud servers. Existing privacy-preserving solutions are hindered by significant latency issues, stemming from the computational complexity of inner product operations in convolutional layers and the high communication costs of evaluating nonlinear activation functions.
View Article and Find Full Text PDFJ Comput Chem
January 2025
Institute of Soil Science and Soil Conservation, Research Centre for BioSystems, Land Use and Nutrition (iFZ), Justus Liebig University Giessen, Giessen, Germany.
Halogenated benzenes (HBs) are hydrophobic organic chemicals belonging to persistent organic pollutants. Owing to their persistence, they represent a serious problem in environmental contamination, specifically of soils and sediments. One of the most important physical processes determining the fate of HBs in soils is adsorption to main soil components such as soil organic matter and soil minerals.
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