scholarly journals Estimating Soil Heat Flux at Surface Soil Layer

2011 ◽  
pp. 0433-0434
Author(s):  
Milan Hofreiter
Keyword(s):  
Heat Flux ◽  
Surface Soil ◽  
Soil Layer ◽  
Soil Heat Flux ◽  
Surface Soil Layer

Outflows of Organic Halide Precursors from Forest Regions

1989 ◽  
Vol 21 (12) ◽  
pp. 1877-1880 ◽  
Author(s):  
S. Saito ◽  
K. Hattori ◽  
T. Okumura
Keyword(s):  
Water Quality ◽  
River Basin ◽  
Surface Soil ◽  
Soil Layer ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Deep Soil ◽  
Organic Halide ◽  
Forest Regions ◽  
Surface Soil Layer

Outflows of organic halide precursors (OXPs) from forest regions were studied in relation to water quality monitoring in the Yodo River basin. Firstly, the contribution of outflows from forest regions relative to the total was roughly estimated. Then equations for flows of these substances were formulated, divided into four different subflow categories: precipitation; throughfall; surface soil layer; and, deep soil layer. Finally, annual outflow loads were calculated for a test forest area.

scholarly journals Biochar induced improvement in root system architecture enhances nutrient assimilation by cotton plant seedlings

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Lei Feng ◽  
Wanli Xu ◽  
Guangmu Tang ◽  
Meiying Gu ◽  
Zengchao Geng
Keyword(s):  
Root System ◽  
System Architecture ◽  
Fine Roots ◽  
Nitrogen Assimilation ◽  
Surface Soil ◽  
Soil Layer ◽  
Root System Architecture ◽  
Seedling Stage ◽  
Agronomic Efficiency ◽  
Surface Soil Layer

Abstract Background Raising nitrogen use efficiency of crops by improving root system architecture is highly essential not only to reduce costs of agricultural production but also to mitigate climate change. The physiological mechanisms of how biochar affects nitrogen assimilation by crop seedlings have not been well elucidated. Results Here, we report changes in root system architecture, activities of the key enzymes involved in nitrogen assimilation, and cytokinin (CTK) at the seedling stage of cotton with reduced urea usage and biochar application at different soil layers (0–10 cm and 10–20 cm). Active root absorption area, fresh weight, and nitrogen agronomic efficiency increased significantly when urea usage was reduced by 25% and biochar was applied in the surface soil layer. Glutamine oxoglutarate amino transferase (GOGAT) activity was closely related to the application depth of urea/biochar, and it increased when urea/biochar was applied in the 0–10 cm layer. Glutamic-pyruvic transaminase activity (GPT) increased significantly as well. Nitrate reductase (NR) activity was stimulated by CTK in the very fine roots but inhibited in the fine roots. In addition, AMT1;1, gdh3, and gdh2 were significantly up-regulated in the very fine roots when urea usage was reduced by 25% and biochar was applied. Conclusion Nitrogen assimilation efficiency was significantly affected when urea usage was reduced by 25% and biochar was applied in the surface soil layer at the seedling stage of cotton. The co-expression of gdh3 and gdh2 in the fine roots increased nitrogen agronomic efficiency. The synergistic expression of the ammonium transporter gene and gdh3 suggests that biochar may be beneficial to amino acid metabolism.

scholarly journals Prediction of the chrome distribution in subarctic Noyabrsk using co-kriging, generalized regression neural network, multilayer perceptron, and hybrid technics

2019 ◽  
pp. 77-86
Author(s):  
A. G. Buevich ◽  
I. E. Subbotina ◽  
A. V. Shichkin ◽  
A. P. Sergeev ◽  
E. M. Baglaeva
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Multilayer Perceptron ◽  
Surface Soil ◽  
Soil Layer ◽  
Generalized Regression Neural Network ◽  
Residual Kriging ◽  
Surface Soil Layer ◽  
Artificial Neural ◽  
Generalized Regression

Combination of geostatistical interpolation (kriging) and machine learning (artificial neural networks, ANN) methods leads to an increase in the accuracy of forecasting. The paper considers the application of residual kriging of an artificial neural network to predicting the spatial contamination of the surface soil layer with chromium (Cr). We reviewed and compared two neural networks: the generalized regression neural network (GRNN) and multilayer perceptron (MLP), as well as the combined method: multilayer perceptron residual kriging (MLPRK). The study is based on the results of the screening of the surface soil layer in the subarctic Noyabrsk, Russia. The models are developed based on computer modeling with minimization of the RMSE. The MLPRK model showed the best prognostic accuracy.

A method to estimate diurnal surface soil heat flux from MODIS data for a sparse vegetation and bare soil

2014 ◽  
Vol 511 ◽  
pp. 139-150 ◽  
Author(s):  
Weiwei Zhu ◽  
Bingfang Wu ◽  
Nana Yan ◽  
Xueliang Feng ◽  
Qiang Xing
Keyword(s):  
Heat Flux ◽  
Surface Soil ◽  
Bare Soil ◽  
Soil Heat Flux ◽  
Modis Data ◽  
Sparse Vegetation

scholarly journals Fertilization of high-yield corn with poultry litter based on nitrogen doses

2018 ◽  
Vol 53 (3) ◽  
pp. 342-350 ◽  
Author(s):  
Juliano Corulli Corrêa ◽  
Marco André Grohskopf ◽  
Agostinho Rebellatto ◽  
Amanda Zolet Rigo ◽  
Arlei Coldebella
Keyword(s):  
Surface Soil ◽  
Poultry Litter ◽  
Soil Layer ◽  
Mineral Fertilizer ◽  
Organic Fertilizers ◽  
High Yield ◽  
No Tillage ◽  
Corn Crop ◽  
Surface Soil Layer ◽  
N Requirement

Abstract: The objective of this work was to recommend nitrogen doses from poultry litter-based organic fertilizers in powder and pellet forms, compared with mineral fertilizer, in a high-yield corn crop under no-tillage. The treatments consisted of a 3×3+1 factorial arrangement, with: three fertilizers, two organic derived from poultry litter in powder (OPo) and pelletized (OPe) forms and one mineral fertilizer (M); three N doses of 65, 100, and 135% of the recommended N requirement for corn; and an unfertilized control. After five corn crops farmed under no-tillage in a Rhodic Kandiudox, the recommended doses for fertilization with poultry litter organic fertilizers, with an expected yield equal to or greater than 8,000 kg ha-1, could be achieved from doses of 100 kg ha-1 N in OPe and M and of 121 kg ha-1 N in OPo. Increasing doses of the OPe, OPo, and M fertilizers raise the contents of organic carbon, N, and available P in the surface soil layer (0.0-0.1 m) and of exchangeable K up to a depth of 0.2 m, allowing to obtain N, P, and K contents in the plant tissue within the sufficiency range of the corn crop.

Coupling effect of water and nitrogen on the morphology and distribution of fine root in surface soil layer of youngPopulus×euramericanaplantation

2015 ◽  
Vol 35 (11) ◽  
Author(s):  
闫小莉 YAN Xiaoli ◽  
戴腾飞 DAI Tengfei ◽  
邢长山 XING Changshan ◽  
贾黎明 JIA Liming ◽  
张龙宁 ZHANG Longning
Keyword(s):  
Surface Soil ◽  
Fine Root ◽  
Coupling Effect ◽  
Soil Layer ◽  
Effect Of Water ◽  
Surface Soil Layer
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