ROLE OF SOIL MOISTURE CONTENT IN REDUCING ENVIRONMENTAL POLLUTION FROM PESTICIDES

Abstract Nearly one-half of the earth’s terrestrial surface is susceptible to drought, which can have significant social, economic, and environmental impacts. Therefore, it is important to develop better descriptions and models of the processes linking the land surface and atmosphere during drought. Using data collected during the International H2O Project, the study presented here investigates the effects of variations in the environmental factors driving the latent heat flux (λE) during drought conditions at a rangeland site located in the panhandle of Oklahoma. Specifically, this study focuses on the relationships of λE with vapor pressure deficit, wind speed, net radiation, soil moisture content, and greenness fraction. While each of these environmental factors has an influence, soil moisture content is the key control on λE. The role of soil moisture in regulating λE is explained in terms of the surface resistance to water vapor transfer. The results show that λE transitioned between being water or energy limited during the course of the drought. The implications of this on the ability to understand and model drought conditions and transitions into or out of droughts are discussed.

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Role of Climatic Factors In The Toxicity of Fipronil Toward Earthworms In Two Tropical Soils: Effects of Increased Temperature And Reduced Soil Moisture Content

10.21203/rs.3.rs-1092710/v1 ◽

2021 ◽

Author(s):

Thuanne Braúlio Hennig ◽

Paulo Roger Lopes Alves ◽

Felipe Ogliari Bandeira ◽

Liziara da Costa Cabrera ◽

Jonas Simon Dugatto ◽

...

Keyword(s):

Soil Moisture ◽

Moisture Content ◽

Soil Moisture Content ◽

Climatic Factors ◽

Hazard Quotient ◽

Tropical Soils ◽

Effect Of Temperature ◽

Water Holding ◽

Water Contents

Abstract The aim of this study was to assess the effect of temperature on the toxicity of fipronil toward earthworms (Eisenia andrei) in two Brazilian soils (Entisol and Oxisol) with contrasting textures. In the case of Entisol, the influence of the soil moisture content on the toxicity was also investigated. Earthworms were exposed for 56 days to soils spiked with increasing concentrations of fipronil under scenarios with different combinations of temperature (20, 25 and 27 ºC) and soil moisture content (60 and 30% of water holding capacity (WHC) for Entisol and 60% WHC for Oxisol). The number of juveniles produced was taken as the endpoint and a risk assessment was performed based on the hazard quotient (HQ). In Entisol, at 60% WHC the fipronil toxicity decreased at 27 ºC compared with the other temperatures tested (EC50 = 52.58, 48.48 and 110 mg kg-1 for 20, 25 and 27 ºC, respectively). In the case of Oxisol at 60% WHC, the fipronil toxicity increased at 27 ºC compared with other temperatures (EC50 = 277.57, 312.87 and 39.89 mg kg-1 at 20, 25 and 27 ºC, respectively). An increase in fipronil toxicity was also observed with a decrease in soil moisture content in Entisol at 27 ºC (EC50 = 27.95 and 110 mg kg-1 for 30% and 60% WHC, respectively). The risk of fipronil was only significant at 27 ºC in Entisol and Oxisol with water contents of 30% and 60% WHC, respectively, revealing that higher temperatures can increase the risk of fipronil toxicity toward earthworms. The results reported herein show that soil properties associated with climatic shifts could enhance the ecotoxicological effects and risk of fipronil for earthworms, depending on the type of soil.

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The role of soil moisture content on maize (Zea Mays L.) emergence and production

Abstract book of the 18th Alps-Adria Scientific Workshop ◽

10.34116/nti.2019.aa.47 ◽

2019 ◽

pp. 112-113

Author(s):

Gabor Milics ◽

Viliam Nagy ◽

Tomas Orfanus ◽

Lubomir Lichner ◽

Peter Surda

Keyword(s):

Zea Mays ◽

Soil Moisture ◽

Moisture Content ◽

Soil Moisture Content ◽

Zea Mays L

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A comparative study on the role of electro-conductive plastics electrode in direct current electroosmosis

E3S Web of Conferences ◽

10.1051/e3sconf/202019801047 ◽

2020 ◽

Vol 198 ◽

pp. 01047

Author(s):

Wei Bai ◽

Tao Jian ◽

Rongbing Lin ◽

Xiaoqian Luo ◽

Lingwei Kong

Keyword(s):

Soil Moisture ◽

Energy Consumption ◽

Moisture Content ◽

Soil Moisture Content ◽

Metal Electrode ◽

Residual Moisture ◽

Factors Affecting ◽

The Difference ◽

Conductive Plastics

The electrode material is one of the critical factors affecting the electroosmosis efficiency. The electroosmotic test was conducted to compare the current, volume moisture content, and energy consumption of Electro-Conductive Plastics Electrode (ECPE) and metal electrode in the dispose of sludge. The results show that: the current decreases of ECPE is smaller than the metal electrode before 20h, and the difference value of moisture content between cathode and anode of ECPE is smaller when electroosmosis is stable. The energy consumption of ECPE is lower in the range of soil moisture content of 35% - 60%. The ECPE has a particular advantage in energy consumption and uniformity of soil moisture content, but has a disadvantage in residual moisture content as compared with the metal electrode.

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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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