scholarly journals An inverse dielectric mixing model at 50 MHz that considers soil organic carbon

2021 ◽  
Vol 25 (12) ◽  
pp. 6407-6420
Author(s):  
Chang-Hwan Park ◽  
Aaron Berg ◽  
Michael H. Cosh ◽  
Andreas Colliander ◽  
Andreas Behrendt ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Moisture ◽  
Soil Organic Matter ◽  
Climate Models ◽  
Mineral Soil ◽  
Organic Matter Content ◽  
Mixing Model ◽  
Multiphase Model ◽  
Validation Experiment ◽  
Wide Range

Abstract. The prevalent soil moisture probe algorithms are based on a polynomial function that does not account for the variability in soil organic matter. Users are expected to choose a model before application: either a model for mineral soil or a model for organic soil. Both approaches inevitably suffer from limitations with respect to estimating the volumetric soil water content in soils with a wide range of organic matter content. In this study, we propose a new algorithm based on the idea that the amount of soil organic matter (SOM) is related to major uncertainties in the in situ soil moisture data obtained using soil probe instruments. To test this theory, we derived a multiphase inversion algorithm from a physically based dielectric mixing model capable of using the SOM amount, performed a selection process from the multiphase model outcomes, and tested whether this new approach improves the accuracy of soil moisture (SM) data probes. The validation of the proposed new soil probe algorithm was performed using both gravimetric and dielectric data from the Soil Moisture Active Passive Validation Experiment in 2012 (SMAPVEX12). The new algorithm is more accurate than the previous soil-probe algorithm, resulting in a slightly improved correlation (0.824 to 0.848), 12 % lower root mean square error (RMSE; 0.0824 to 0.0727 cm3 cm−3), and 95 % less bias (−0.0042 to 0.0001 cm3 cm−3). These results suggest that applying the new dielectric mixing model together with global SOM estimates will result in more reliable soil moisture reference data for weather and climate models and satellite validation.

scholarly journals An inverse dielectric mixing model at 50 MHz that considers soil organic carbon

2021 ◽  
Author(s):  
Chang-Hwan Park ◽  
Aaron Berg ◽  
Michael H. Cosh ◽  
Andreas Colliander ◽  
Andreas Behrendt ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Moisture ◽  
Soil Organic Matter ◽  
Climate Models ◽  
Mineral Soil ◽  
Organic Matter Content ◽  
Mixing Model ◽  
Multiphase Model ◽  
Validation Experiment ◽  
Wide Range

Abstract. The prevalent soil moisture probe algorithms are based on a polynomial function that does not account for the variability in soil organic matter. Users are expected to choose a model before application: either a model for mineral soil or a model for organic soil. Both approaches inevitably suffer from limitations with respect to estimating the volumetric soil water content in soils having a wide range of organic matter content. In this study, we propose a new algorithm based on the idea that the amount of soil organic matter (SOM) is related to major uncertainties in the in-situ soil moisture data obtained using soil probe instruments. To test this theory, we derived a multiphase inversion algorithm from a physically based dielectric mixing model capable of using the SOM amount, performed a selection process from the multiphase model outcomes, and tested whether this new approach improves the accuracy of soil moisture (SM) data probes. The validation of the proposed new soil probe algorithm was performed using both gravimetric and dielectric data from the Soil Moisture Active Passive Validation Experiment in 2012 (SMAPVEX12). The new algorithm is more accurate than the previous soil-probe algorithm, resulting in a slightly improved correlation (0.824 0.848), 12 % lower root mean square error (RMSE; 0.0824 0.0725 cm3·cm−3), and 90 % less bias (−0.0042 0.0004 cm3·cm−3). These results suggest that applying the new dielectric mixing model together with global SOM estimates will result in more reliable soil moisture reference data for weather and climate models and satellite validation.

A modular terrain model for daily variations in machine-specific forest soil trafficability

2009 ◽  
Vol 89 (1) ◽  
pp. 93-109 ◽  
Author(s):  
Daniel J Vega-Nieva ◽  
Paul N. C. Murphy ◽  
Mark Castonguay ◽  
Jae Ogilvie ◽  
Paul A Arp
Keyword(s):  
Organic Matter ◽  
Soil Moisture ◽  
Pore Space ◽  
Mineral Soil ◽  
Forest Harvesting ◽  
Soil Conditions ◽  
Soil Resistance ◽  
Space Module ◽  
Wide Range ◽  
Cone Index

A modular approach is presented to assess terrain-specific soil trafficability in terms of soil resistance to penetration and machine-specific rut depths. These modules address: (1) soil resistance to cone penetration (cone index, or CI) as affected by soil moisture, texture and pore space (Module 1), (2) machine-induced rut depths (single-pass and multi-cycles) as affected by wheel loads, tire specifications and CI (accounting for depth of compactable soil, Module 2), (3) temporal variations in hydrothermal conditions, CI, and potential rut depths due to daily soil moisture and temperature variations (Module 3), and (4) spatial variations in CI and rut depth across terrain due to corresponding changes in soil moisture, depth of compactable soil, bulk density, texture, frost depth, organic matter and coarse fragments (Module 4). The approach is applied to off-road wood-forwarding operations. Modules 1 and 2 were calibrated to apply to a wide range of soil conditions. Modules 3 and 4 were initialized for a wood-forwarding case study at CFB Gagetown, New Brunswick, Canada. Model results should be most applicable for flat to near-flat terrain, with insignificant wheel obstructions, and no organic matter accumulations on top of the mineral soil. Key words: Forest harvesting, soil penetration resistance, cone index, soil rut depth, soil disturbance, soil trafficability, soil compaction, terrain modelling

THE EFFECT OF SAWDUST, STRAW, COMPOST AND MANURE ON THE YIELD AND CHEMICAL COMPOSITION OF STRAWBERRIES AND ON SOIL MOISTURE, ACIDITY AND ORGANIC MATTER CONTENT

1961 ◽  
Vol 41 (1) ◽  
pp. 42-49 ◽  
Author(s):  
G. R. Webster
Keyword(s):  
Organic Matter ◽  
Soil Moisture ◽  
Soil Organic Matter ◽  
Soil Acidity ◽  
Organic Matter Content ◽  
Nutrient Content ◽  
Matter Content ◽  
Soil Organic Matter Content ◽  
Per Se ◽  
Nitrogen Phosphorus

Sawdust, straw, compost and manure were applied under dryland conditions to strawberry plantings at two locations. The effects on yield, leaf nutrient content, soil moisture, soil acidity and soil organic matter content were evaluated. Sawdust mulch and sawdust incorporation, the former being slightly better, produced highly significant increased yields over the check treatment and were superior to all other treatments. Soil moisture measurements showed that the sawdust treatments conserved soil moisture and this was regarded as the chief reason for the increased yields. The nitrogen, phosphorus, potassium, calcium and magnesium contents of leaves were affected somewhat by the treatments but the levels were considered adequate in all cases.Soil acidity was significantly increased in the sawdust plots but this was attributed to the additional nitrogen applied rather than to the sawdust per se. Sawdust incorporation, manure and compost treatments significantly increased soil organic matter content when compared to the check treatment.

Estimate Soil Organic Matter Content in the Heihe River Basin Using Hyperspectral Method

2012 ◽  
Vol 500 ◽  
pp. 838-842
Author(s):  
Hai Ying Li ◽  
Hong Chun Peng
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
River Basin ◽  
Large Scale ◽  
Organic Matter Content ◽  
Matter Content ◽  
Heihe River Basin ◽  
Heihe River ◽  
Soil Organic Matter Content ◽  
Wide Range

.Soil properties are very absent and sorely needed for many models. Conventional measurements are expensive and many samples are required. Hence it is difficult to quantitatively analysis them at a large-scale region. Hyperspectral methods are now used for the rapid characterization of a wide range of soil. In this paper, it was used to estimate organic matter content in soil of Heihe River basin. A total of 84 samples were collected and their reflected spectral were measured with ASD spectrometers. Then the organic matter were predicted using four forms of spectra and PLS method. The results show:1) the hyperspectral remote sensing can be used to predict soil organic matter content, and the precision can meet the requirement; 2) the best region of spectrum is 400~800nm in R, 1/R and Log (1/R) formation, and the FDR and FD(Log (1/R)) centered in 800nm based on the correlation coefficient and Variable Importance in Projection.

scholarly journals Soil nitrogen supply of peat grasslands estimated by degree days and soil organic matter content

2020 ◽  
Vol 117 (3) ◽  
pp. 351-365
Author(s):  
J. Pijlman ◽  
G. Holshof ◽  
W. van den Berg ◽  
G. H. Ros ◽  
J. W. Erisman ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Soil Nitrogen ◽  
Organic Matter Content ◽  
Matter Content ◽  
Nitrogen Supply ◽  
Degree Days ◽  
Soil Organic Matter Content ◽  
Soil Nitrogen Supply

scholarly journals Effect of Clay, Soil Organic Matter, and Soil pH on Initial and Residual Weed Control with Flumioxazin

Agronomy ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1326
Author(s):  
Calvin F. Glaspie ◽  
Eric A. L. Jones ◽  
Donald Penner ◽  
John A. Pawlak ◽  
Wesley J. Everman
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Weed Control ◽  
Soil Ph ◽  
Organic Matter Content ◽  
Amaranthus Retroflexus ◽  
Matter Content ◽  
Weed Species ◽  
Soil Organic Matter Content ◽  
Field Soils

Greenhouse studies were conducted to evaluate the effects of soil organic matter content and soil pH on initial and residual weed control with flumioxazin by planting selected weed species in various lab-made and field soils. Initial control was determined by planting weed seeds into various lab-made and field soils treated with flumioxazin (71 g ha−1). Seeds of Echinochloa crus-galli (barnyard grass), Setaria faberi (giant foxtail), Amaranthus retroflexus (redroot pigweed), and Abutilon theophrasti (velvetleaf) were incorporated into the top 1.3 cm of each soil at a density of 100 seeds per pot, respectively. Emerged plants were counted and removed in both treated and non-treated pots two weeks after planting and each following week for six weeks. Flumioxazin control was evaluated by calculating percent emergence of weeds in treated soils compared to the emergence of weeds in non-treated soils. Clay content was not found to affect initial flumioxazin control of any tested weed species. Control of A. theophrasti, E. crus-galli, and S. faberi was reduced as soil organic matter content increased. The control of A. retroflexus was not affected by organic matter. Soil pH below 6 reduced flumioxazin control of A. theophrasti, and S. faberi but did not affect the control of A. retroflexus and E. crus-galli. Flumioxazin residual control was determined by planting selected weed species in various lab-made and field soils 0, 2, 4, 6, and 8 weeks after treatment. Eight weeks after treatment, flumioxazin gave 0% control of A. theophrasti and S. faberi in all soils tested. Control of A. retroflexus and Chenopodium album (common lambsquarters) was 100% for the duration of the experiment, except when soil organic matter content was greater than 3% or the soil pH 7. Eight weeks after treatment, 0% control was only observed for common A. retroflexus and C. album in organic soil (soil organic matter > 80%) or when soil pH was above 7. Control of A. theophrasti and S. faberi decreased as soil organic matter content and soil pH increased. Similar results were observed when comparing lab-made soils to field soils; however, differences in control were observed between lab-made organic matter soils and field organic matter soils. Results indicate that flumioxazin can provide control ranging from 75–100% for two to six weeks on common weed species.

scholarly journals Assessment of Potato Farmland Soil Nutrient Based on MDS-SQI Model in the Loess Plateau

2021 ◽  
Vol 13 (7) ◽  
pp. 3957
Author(s):  
Yingying Xing ◽  
Ning Wang ◽  
Xiaoli Niu ◽  
Wenting Jiang ◽  
Xiukang Wang
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Soil Fertility ◽  
Soil Quality ◽  
Soil Nutrients ◽  
Organic Matter Content ◽  
Soil Nutrient ◽  
Matter Content ◽  
Soil Organic Matter Content ◽  
Farmland Soil

Soil nutrients are essential nutrients provided by soil for plant growth. Most researchers focus on the coupling effect of nutrients with potato yield and quality. There are few studies on the evaluation of soil nutrients in potato fields. The purpose of this study is to investigate the soil nutrients of potato farmland and the soil vertical nutrient distributions, and then to provide a theoretical and experimental basis for the fertilizer management practices for potatoes in Loess Plateau. Eight physical and chemical soil indexes were selected in the study area, and 810 farmland soil samples from the potato agriculture product areas were analyzed in Northern Shaanxi. The paper established the minimum data set (MDS) for the quality diagnosis of the cultivated layer for farmland by principal component analysis (PCA), respectively, and furthermore, analyzed the soil nutrient characteristics of the cultivated layer adopted soil quality index (SQI). The results showed that the MDS on soil quality diagnosis of the cultivated layer for farmland soil included such indicators as the soil organic matter content, soil available potassium content, and soil available phosphorus content. The comprehensive index value of the soil quality was between 0.064 and 0.302. The SPSS average clustering process used to classify SQI was divided into three grades: class I (36.2%) was defined as suitable soil fertility (SQI < 0.122), class II (55.6%) was defined as moderate soil fertility (0.122 < SQI < 0.18), and class III (8.2%) was defined as poor soil fertility (SQI > 0.186). The comprehensive quality of the potato farmland soils was generally low. The proportion of soil nutrients in the SQI composition ranged from large to small as the soil available potassium content = soil available phosphorus content > soil organic matter content, which became the limiting factor of the soil organic matter content in this area. This study revolves around the 0 to 60 cm soil layer; the soil fertility decreased gradually with the soil depth, and had significant differences between the respective soil layers. In order to improve the soil nutrient accumulation and potato yield in potato farmland in northern Shaanxi, it is suggested to increase the fertilization depth (20 to 40 cm) and further study the ratio of nitrogen, phosphorus, and potassium fertilizer.

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