scholarly journals Comparison of the gravimetric sampling and impedance methods for measuring soil moisture content

2015 ◽  
Vol 62 (1) ◽  
pp. 14-25
Author(s):  
Michal Allman ◽  
Martin Jankovský ◽  
Zuzana Allmanová ◽  
Valéria Messingerová
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Gravimetric Method ◽  
Calibration Method ◽  
Impedance Method ◽  
Statistical Sample ◽  
Stage Analysis ◽  
Similar Depth ◽  
Gravimetric Sampling

Abstract This paper was focused on determining whether gravimetric sampling and impedance method of measuring soil moisture content provided different results and if they did, what was the size of the differences between particular methods on rendzinas and cambisols. The means of moisture content should be equal when using both methods on similar spots. During the research, an Eijkelkamp Penetrologger penetrometer equipped with impedance probes and gravimetric sampling cylinders from Eijkelkamp were used. The samples were taken from the undisturbed stand, ruts, and the centre of the skid trail. The impedance probes were inserted six centimetres deep into the soil. Soil samples were taken from similar depth in order to calculate the moisture content through the gravimetric method. 138 measurements were carried out for each method. The minimal difference of moisture contents measured by individual methods was 0.01%, maximal difference was 22.06%, and on average it was 7.42%. Oneway ANOVA was used for first stage analysis of the statistical sample. It proved that the differences between measurements were statistically significant in two out of three considered stands. Tukey’s HSD test was used to identify which data groups contributed to refuting the aforementioned hypothesis. The test showed that in one stand all relevant pairs of data were significantly different, while in the other stand only data pairs from the ruts were significantly different. The calibration method provided by the producers did not refine the accuracy of the impedance probes sufficiently and different calibration procedures have to be used.

scholarly journals Design and Construction of a Soil Moisture Measuring

2020 ◽  
pp. 29-34
Author(s):  
A. A. Ijah ◽  
O. W. Bolaji ◽  
O. O. Adedire ◽  
J. Z. Emmanuel ◽  
N. E. Onwuegbunam ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Regression Coefficient ◽  
Gravimetric Method ◽  
Voltage Regulator ◽  
Moisture Determination ◽  
Moisture Contents ◽  
Design And Construction

A digital soil moisture reader was constructed and tested. It uses a lipo battery of 9v which was regulated to a constant 5v with the help of a voltage regulator 7805. The digital soil moisture reader developed was tested and the result obtained was compared with that obtained using the gravimetric method of determining soil moisture contents. In determining the soil moisture content, a certain quantity of soil was collected and a particular volume of water was added incrementally. The result shows that the soil moisture reader is accurate. The evaluation was carried out using the gravimetric method of soil moisture determination as a basis of comparison. Nine samples of 50g of soli were collected from Federal College of Forestry Mechanization Farm and a certain amount of water was added incrementally during the process of determining the soil moisture content. The soil reader was calibrated using the gravimetric method which shows a regression coefficient R^2 of 0.986 which indicates that the soil reader is accurate, sensitive and reliable.

scholarly journals Development and testing of a capacitive digital soil moisture sensor with printed circuit board as a probe

2020 ◽  
Vol 39 (3) ◽  
pp. 911-917
Author(s):  
V. Ogwo ◽  
K.N. Ogbu ◽  
C.C. Anyadike ◽  
O.A. Nwoke ◽  
C.C. Mbajiorgu
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Real Time ◽  
Printed Circuit Board ◽  
Soil Moisture Content ◽  
Gravimetric Method ◽  
Circuit Board ◽  
Moisture Sensor ◽  
Printed Circuit ◽  
Soil Moisture Sensor

The quantity and quality of water present in the soil determine to a greater extent the performance of agricultural crops. Real-time determination of moisture content has a greater advantage over the traditional gravimetric method of determining soil moisture content. Thus, this work was based on the design and construction of a cost effective digital capacitive soil moisture sensor for real-time measurement. The moisture sensors comprised four integrated units namely: power supply unit with a 9V DC battery as a power source, sensor unit with a locally sourced Printed Circuit Board (PCB) as the single sensing probe, control unit made up of PIC16f877 microcontroller programmed with a C language and the C source code compiled in Corporate Computer Services Compiler (CSS C) compiler development environment, and a 16x2 display unit which displays the readings in percentage moisture content (%MC) and capacitance (μF) of the soil obtained from the sensor on its screen. Standard gravimetric moisture content was carried out to get the calibration factor which was used to calibrate the sensor for reliability. The validation was done by taking the reprogrammed (calibrated) sensor to the field for further measurement, after which soil samples were collected for further gravimetric analysis. A regression equation was obtained by plotting the moisture content obtained from gravimetric method (%MCG) against that from sensor reading (%MCS) with a high degree correlation coefficient (R2) of 0.998. The developed capacitive soil moisture sensor is cheap, portable, reliable and easy to use even by local farmers. Keywords: Calibration, Capacitive sensor, Printed circuit board, Soil moisture content, Validation.

scholarly journals Uncertainties in Measuring Soil Moisture Content with Actively Heated Fiber-Optic Distributed Temperature Sensing

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3723
Author(s):  
Robert Wu ◽  
Pierrick Lamontagne-Hallé ◽  
Jeffrey M. McKenzie
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Fiber Optic ◽  
Calibration Method ◽  
Temperature Sensing ◽  
Soil Conditions ◽  
Calibration Data ◽  
Distributed Temperature Sensing ◽  
Fiber Optic Cable

Actively heated fiber-optic distributed temperature sensing (aFO-DTS) measures soil moisture content at sub-meter intervals across kilometres of fiber-optic cable. The technology has great potential for environmental monitoring but calibration at field scales with variable soil conditions is challenging. To better understand and quantify the errors associated with aFO-DTS soil moisture measurements, we use a parametric numerical modeling approach to evaluate different error factors for uniform soil. A thermo-hydrogeologic, unsaturated numerical model is used to simulate a 0.01 m by 0.01 m two-dimensional domain, including soil and a fiber-optic cable. Results from the model are compared to soil moisture values calculated using the commonly used Tcum calibration method for aFO-DTS. The model is found to have high accuracy between measured and observed saturations for static hydrologic conditions but shows discrepancies for more realistic settings with active recharge. We evaluate the performance of aFO-DTS soil moisture calculations for various scenarios, including varying recharge duration and heterogeneous soils. The aFO-DTS accuracy decreases as the variability in soil properties and intensity of recharge events increases. Further, we show that the burial of the fiber-optic cable within soil may adversely affect calculated results. The results demonstrate the need for careful selection of calibration data for this emerging method of measuring soil moisture content.

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

2011 ◽  
Vol 28 (1) ◽  
pp. 85-91 ◽  
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

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

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.

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

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.

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

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.

scholarly journals A GNSS-IR Method for Retrieving Soil Moisture Content from Integrated Multi-Satellite Data That Accounts for the Impact of Vegetation Moisture Content

2021 ◽  
Vol 13 (13) ◽  
pp. 2442
Author(s):  
Jichao Lv ◽  
Rui Zhang ◽  
Jinsheng Tu ◽  
Mingjie Liao ◽  
Jiatai Pang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Satellite Data ◽  
Vegetation Index ◽  
Soil Moisture Content ◽  
Support Vector ◽  
Observation Data ◽  
Multipath Effect ◽  
Mars Model ◽  
The Impact

There are two problems with using global navigation satellite system-interferometric reflectometry (GNSS-IR) to retrieve the soil moisture content (SMC) from single-satellite data: the difference between the reflection regions, and the difficulty in circumventing the impact of seasonal vegetation growth on reflected microwave signals. This study presents a multivariate adaptive regression spline (MARS) SMC retrieval model based on integrated multi-satellite data on the impact of the vegetation moisture content (VMC). The normalized microwave reflection index (NMRI) calculated with the multipath effect is mapped to the normalized difference vegetation index (NDVI) to estimate and eliminate the impact of VMC. A MARS model for retrieving the SMC from multi-satellite data is established based on the phase shift. To examine its reliability, the MARS model was compared with a multiple linear regression (MLR) model, a backpropagation neural network (BPNN) model, and a support vector regression (SVR) model in terms of the retrieval accuracy with time-series observation data collected at a typical station. The MARS model proposed in this study effectively retrieved the SMC, with a correlation coefficient (R2) of 0.916 and a root-mean-square error (RMSE) of 0.021 cm3/cm3. The elimination of the vegetation impact led to 3.7%, 13.9%, 11.7%, and 16.6% increases in R2 and 31.3%, 79.7%, 49.0%, and 90.5% decreases in the RMSE for the SMC retrieved by the MLR, BPNN, SVR, and MARS model, respectively. The results demonstrated the feasibility of correcting the vegetation changes based on the multipath effect and the reliability of the MARS model in retrieving the SMC.

Sign in / Sign up

Export Citation Format

Share Document