STUDY OF THE MINERALISATION OF PELLETIZED CHICKEN MANURE AT DIFFERENT SOIL MOISTURE CONTENT OF A SANDY SOIL

Synthetic polymers, such as polyacrylamide (PAM), and biochar are generally used as soil amendments to improve soil properties. This paper explores a laboratory column experiment conducted to investigate the effects of biochar (pyrolysis at 400–450 °C) and polymers, with different application rates, on the hydro-physical properties of sandy soil. The experiment evaluated four rates each of biochar (0.0% (C), 2% (B1), 4% (B2), 6% (B3) and 8% (B4)) and polymers (0.0% (C), 0.2% (P1), 0.4% (P2), 0.6% (P3), and 0.8%(P4)), as well as a mixture of them. The infiltration rate decreased significantly when a mixture of biochar and polymers was adopted. B1 showed a decrease of 32.73% while a mixture of 8% (B4) and (0.8%) P4 exhibited a decrease of 57.31%. The polymers increased the infiltration rate at low concentrations (P1 and P2) and reduced it at high concentrations (P3 and P4). The cumulative evaporation decreased significantly for most treatments. B1 recorded the highest decrease in cumulative evaporation with a percentage decrease of 31.9%. The highest decrease in hydraulic conductivity (Ks) was for B1. However, the mixture of B4 and P4 resulted in the highest increase in soil moisture content at field capacity compared to the control and other treatments. P4 and the mixture of B2 and P2 showed significant (p < 0.05) increases in the percentage of stable aggregate (SA) in fraction size (0.25–0.125 mm). Although the mixture of B4 and P4 had the highest increase in soil moisture content, this study recommends using the B1 treatment on sandy soil in arid environments due to its strong hydro-physical properties and affordability.

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Precipitation, Soil Moisture Content and Ground Water Storage in a Sandy Soil in Southern Sweden

Oikos ◽

10.2307/3565010 ◽

1968 ◽

Vol 19 (2) ◽

pp. 234 ◽

Cited By ~ 4

Author(s):

Åke Fleetwood ◽

Ingemar Larsson ◽

Ake Fleetwood

Keyword(s):

Soil Moisture ◽

Moisture Content ◽

Ground Water ◽

Sandy Soil ◽

Soil Moisture Content ◽

Water Storage ◽

Southern Sweden

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Predicting sandy soil moisture content with hyperspectral imaging

International Journal of Agricultural and Biological Engineering ◽

10.25165/j.ijabe.20171006.2614 ◽

2017 ◽

Vol 10 (6) ◽

pp. 175-183 ◽

Cited By ~ 5

Author(s):

Qi Haijun ◽

◽

Jin Xiu ◽

Zhao Liu ◽

DEDO Irene Maxime ◽

...

Keyword(s):

Soil Moisture ◽

Moisture Content ◽

Hyperspectral Imaging ◽

Sandy Soil ◽

Soil Moisture Content

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The Effect of Soil Coverings on Cellulose Decomposition Activity of Sandy Soil

Acta Agraria Debreceniensis ◽

10.34101/actaagrar/12/3424 ◽

2003 ◽

pp. 15-20

Author(s):

Csaba Varga

Keyword(s):

Soil Moisture ◽

Moisture Content ◽

Sandy Soil ◽

Soil Moisture Content ◽

Soil Cover ◽

Field Research ◽

Laboratory Research ◽

First Year ◽

Cellulose Decomposition ◽

The Difference

The purpose of our experiments is to discover the effect of different soil cover matter (agroszövet and black polyethylene) on actual (under field circumstances) and potential (under laboratory circumstances) cellulose decomposition activity. In our field research, the Unger-test was used, and in laboratory research, the Petkov-Markova method was applied. In the first year of the experiment (2000) actual cellulose decomposition activity was significantly higher in covered than in the uncovered soil both in spring and autumn. The difference between the two treatments was significant only in spring. In the spring of 2001 black polyethylene showed significantly the lowest, activity, while in autumn the agroszövet (a porous black polyethylene) showed significantly the highest activity. In the autumn of 2001 the soil covered by black polyethylene gave non-significant,and the soil covered by agroszövet gave a significant higher activity value than the control. Averaging the two experimental years (2000-2001), the actual cellulose decomposition activity was significantly higher in covered soils both in spring (with 30-39%) and in autumn (with 34-69%). Moreover, in autumn a significantly higher value was detected under agroszövet than in any other treatment. The difference between the effect of treatments was not significant. In 2000, the potential cellulose decomposition activity was the highest in soil covered by agroszövet in spring, but in autumn higher activity value was detected in every covered soil than in the control. In the spring of 2001, every covered soil showed a lower, but in autumn a higher, potential cellulose decomposition rate than the control. The activity decreased significantly 27 (agroszövet) and 45 (black polyethylene) percent in spring, and increased no- significantly 8 (agroszövet) and 4 (black polyethylene) percent in autumn. During the two experimental years, we observed on average lower potential cellulose decomposition activity (15-60%) in spring and a higher one (14-43%) in autumn. Neither was significant. The dynamic of potential cellulose decomposition activity averaging 2000 and 2001 showed a slight, the actual cellulose decomposition activity an explicit non-significant upward tendency. There was a strong (r=0,189) correlation obtained between the actual and potential cellulose decomposition activity of soil, and a medium-strong (r=0,673) relationship between the soil moisture content and actual cellulose decomposition activity.

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Analysis on Soil Moisture Content in the Middle Reaches of the Yellow River

Arid Zone Research ◽

10.3724/sp.j.1148.2011.00085 ◽

2011 ◽

Vol 28 (1) ◽

pp. 85-91 ◽

Cited By ~ 2

Author(s):

Run-chun LI ◽

Xiu-zhi ZHANG ◽

Li-hua WANG ◽

Xin-yan LV ◽

Yuan GAO

Keyword(s):

Soil Moisture ◽

Moisture Content ◽

Soil Moisture Content ◽

Yellow River ◽

The Yellow River

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Analysis on Grey Correlation Degree of Soil Moisture Content under Different Land Use Types in Wind-Blown Sand Area

Arid Zone Research ◽

10.3724/sp.j.1148.2009.00840 ◽

2010 ◽

Vol 26 (6) ◽

pp. 840-845

Author(s):

Lin CHEN ◽

Lei WANG ◽

Qing-xia ZHANG ◽

Nai-ping SONG

Keyword(s):

Land Use ◽

Soil Moisture ◽

Moisture Content ◽

Soil Moisture Content ◽

Grey Correlation ◽

Land Use Types ◽

Correlation Degree ◽

Grey Correlation Degree

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Distribution of soil moisture content and its effect on the potential growth of the over-story species in North-East Chalkidiki

Silva Gandavensis ◽

10.21825/sg.v66i0.817 ◽

2001 ◽

Vol 66 ◽

Author(s):

M. Aslanidou ◽

P. Smiris

Keyword(s):

Soil Moisture ◽

Moisture Content ◽

Soil Moisture Content ◽

Soil Depth ◽

Moisture Distribution ◽

Taxus Baccata ◽

Mixed Stands ◽

Potential Growth ◽

North East ◽

Soil Moisture Distribution

This study deals with the soil moisture distribution and its effect on the potential growth and adaptation of the over-story species in north-east Chalkidiki. These species are: Quercus dalechampii Ten, Quercus conferta Kit, Quercus pubescens Willd, Castanea sativa Mill, Fagus moesiaca Maly-Domin and also Taxus baccata L. in mixed stands with Fagus moesiaca. Samples of soil, 1-2 kg per 20cm depth, were taken and the moisture content of each sample was measured in order to determine soil moisture distribution and its contribution to the growth of the forest species. The most important results are: i) available water is influenced by the soil depth. During the summer, at a soil depth of 10 cm a significant restriction was observed. ii) the large duration of the dry period in the deep soil layers has less adverse effect on stands growth than in the case of the soil surface layers, due to the fact that the root system mainly spreads out at a soil depth of 40 cm iii) in the beginning of the growing season, the soil moisture content is greater than 30 % at a soil depth of 60 cm, in beech and mixed beech-yew stands, is 10-15 % in the Q. pubescens stands and it's more than 30 % at a soil depth of 60 cm in Q. dalechampii stands.

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Mapping barrier island soil moisture using a radiative transfer model of hyperspectral imagery from an unmanned aerial system

Scientific Reports ◽

10.1038/s41598-021-82783-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Rehman S. Eon ◽

Charles M. Bachmann

Keyword(s):

Soil Moisture ◽

Radiative Transfer ◽

Moisture Content ◽

Layer Thickness ◽

Soil Moisture Content ◽

Hyperspectral Imagery ◽

Barrier Island ◽

Water Layer ◽

Radiative Transfer Model ◽

Transfer Model

AbstractThe advent of remote sensing from unmanned aerial systems (UAS) has opened the door to more affordable and effective methods of imaging and mapping of surface geophysical properties with many important applications in areas such as coastal zone management, ecology, agriculture, and defense. We describe a study to validate and improve soil moisture content retrieval and mapping from hyperspectral imagery collected by a UAS system. Our approach uses a recently developed model known as the multilayer radiative transfer model of soil reflectance (MARMIT). MARMIT partitions contributions due to water and the sediment surface into equivalent but separate layers and describes these layers using an equivalent slab model formalism. The model water layer thickness along with the fraction of wet surface become parameters that must be optimized in a calibration step, with extinction due to water absorption being applied in the model based on equivalent water layer thickness, while transmission and reflection coefficients follow the Fresnel formalism. In this work, we evaluate the model in both field settings, using UAS hyperspectral imagery, and laboratory settings, using hyperspectral spectra obtained with a goniometer. Sediment samples obtained from four different field sites representing disparate environmental settings comprised the laboratory analysis while field validation used hyperspectral UAS imagery and coordinated ground truth obtained on a barrier island shore during field campaigns in 2018 and 2019. Analysis of the most significant wavelengths for retrieval indicate a number of different wavelengths in the short-wave infra-red (SWIR) that provide accurate fits to measured soil moisture content in the laboratory with normalized root mean square error (NRMSE)< 0.145, while independent evaluation from sequestered test data from the hyperspectral UAS imagery obtained during the field campaign obtained an average NRMSE = 0.169 and median NRMSE = 0.152 in a bootstrap analysis.

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Estimating Agricultural Soil Moisture Content through UAV-Based Hyperspectral Images in the Arid Region

Remote Sensing ◽

10.3390/rs13081562 ◽

2021 ◽

Vol 13 (8) ◽

pp. 1562

Author(s):

Xiangyu Ge ◽

Jianli Ding ◽

Xiuliang Jin ◽

Jingzhe Wang ◽

Xiangyue Chen ◽

...

Keyword(s):

Data Mining ◽

Soil Moisture ◽

Moisture Content ◽

Hyperspectral Imaging ◽

Fractional Order ◽

Arid Regions ◽

Soil Moisture Content ◽

Order Derivative ◽

Imaging Data ◽

Strategy I

Unmanned aerial vehicle (UAV)-based hyperspectral remote sensing is an important monitoring technology for the soil moisture content (SMC) of agroecological systems in arid regions. This technology develops precision farming and agricultural informatization. However, hyperspectral data are generally used in data mining. In this study, UAV-based hyperspectral imaging data with a resolution o 4 cm and totaling 70 soil samples (0–10 cm) were collected from farmland (2.5 × 104 m2) near Fukang City, Xinjiang Uygur Autonomous Region, China. Four estimation strategies were tested: the original image (strategy I), first- and second-order derivative methods (strategy II), the fractional-order derivative (FOD) technique (strategy III), and the optimal fractional order combined with the optimal multiband indices (strategy IV). These strategies were based on the eXtreme Gradient Boost (XGBoost) algorithm, with the aim of building the best estimation model for agricultural SMC in arid regions. The results demonstrated that FOD technology could effectively mine information (with an absolute maximum correlation coefficient of 0.768). By comparison, strategy IV yielded the best estimates out of the methods tested (R2val = 0.921, RMSEP = 1.943, and RPD = 2.736) for the SMC. The model derived from the order of 0.4 within strategy IV worked relatively well among the different derivative methods (strategy I, II, and III). In conclusion, the combination of FOD technology and the optimal multiband indices generated a highly accurate model within the XGBoost algorithm for SMC estimation. This research provided a promising data mining approach for UAV-based hyperspectral imaging data.

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