Quasi-3D mapping of soil moisture for agriculture using electric conductivity sensing  

2021 ◽  
Author(s):  
Hira Shaukat ◽  
Ken Flower ◽  
Matthias Leopold
Keyword(s):  
Soil Moisture ◽  
Electric Conductivity ◽  
Least Square ◽  
Fast Method ◽  
Inversion Algorithm ◽  
Crop Fields ◽  
Non Invasive ◽  
Precise Quantification ◽  
Neutron Moisture ◽  
Moisture Conditions

<p>Knowledge of real time spatial distribution of soil moisture has great potential to improve yield and profit in agricultural systems. Rapid and precise quantification of water in crop fields is challenging due to the influence of highly variable soil properties such as texture and porosity.  Recent advances in non-invasive electromagnetic induction (EMI) techniques have created an opportunity to determine soil moisture content with high-resolution and minimal soil intrusion. So far, EMI has mainly been validated for homogenous soils, which are not common in agriculture. This study from a field site in Western Australia converts time series apparent electrical conductivity data recorded with a Dualem 1Hs EM-meter into spatiotemporal domains. A least square inversion algorithm was used to determine electric conductivities for individual soil layers (0-50cm, 50-80 cm and 80-160 cm) for two EMI surveys at a trial site, with different crop rotations and varying moisture conditions. A laboratory experiment under controlled conditions developed electric conductivity vs volumetric water content relations with power law functions for each layer with R<sup>2</sup> values between 0.98 and 0.99. Subsequently, EMI data were converted to volumetric water contents for each layer and predictions were spatially displayed. These EMI soil moisture predictions were compared with neutron moisture meter measurements, with R<sup>2</sup> values between 0.95 and 0.74 for the two surveys. The method is robust and offers a comparatively fast method to estimate the soil moisture status in fields and to subsequently make informed management decisions. </p>

scholarly journals Hyperspectral measurements of wet, dry and saline soils from the McMurdo Dry Valleys: soil moisture properties from remote sensing

2014 ◽  
Vol 26 (5) ◽  
pp. 565-572 ◽  
Author(s):  
Joseph Levy ◽  
Anne Nolin ◽  
Andrew Fountain ◽  
James Head
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Thermal State ◽  
Mcmurdo Dry Valleys ◽  
Dry Valleys ◽  
Non Invasive ◽  
High Concentrations ◽  
Remote Sensing Techniques ◽  
Moisture Conditions ◽  
Chloride Salts

AbstractSoil moisture is a spatially heterogeneous quantity in the McMurdo Dry Valleys of Antarctica that exerts a large influence on the biological community and on the thermal state of Dry Valleys permafrost. The goal of this project was to determine whether hyperspectral remote sensing techniques could be used to determine soil moisture conditions in the Dry Valleys. We measured the spectral reflectance factors of wetted soil samples from the Dry Valleys under natural light conditions and related diagnostic spectral features to surface layer soil moisture content. Diagnostic water absorption features in the spectra at 1.4 µm and 1.9 µm were present in all samples, including samples doped with high concentrations of chloride salts. The depth of the 1.4 µm absorption is shown to increase linearly with increasing gravimetric water content. These results suggest that airborne hyperspectral imaging of the Dry Valleys could generate soil moisture maps of this environment over large spatial areas using non-invasive remote-sensing techniques.

scholarly journals Improvement of the Soil Moisture Retrieval Procedure Based on the Integration of UAV Photogrammetry and Satellite Remote Sensing Information

2021 ◽  
Vol 13 (24) ◽  
pp. 4968
Author(s):  
Amal Chakhar ◽  
David Hernández-López ◽  
Rocío Ballesteros ◽  
Miguel A. Moreno
Keyword(s):  
Soil Moisture ◽  
Bare Soil ◽  
Arid Environment ◽  
Early Growth ◽  
Precise Determination ◽  
Growth Stages ◽  
Crop Fields ◽  
Moisture Conditions ◽  
Semi Arid ◽  
Cultivated Soils

In countries characterized by arid and semi-arid climates, a precise determination of soil moisture conditions on the field scale is critically important, especially in the first crop growth stages, to schedule irrigation and to avoid wasting water. The objective of this study was to apply the operative methodology that allowed surface soil moisture (SSM) content in a semi-arid environment to be estimated. SSM retrieval was carried out by combining two scattering models (IEM and WCM), supplied by backscattering coefficients at the VV polarization obtained from the C-band Synthetic Aperture Radar (SAR), a vegetation descriptor NDVI obtained from the optical sensor, among other essential parameters. The inversion of these models was performed by Neural Networks (NN). The combined models were calibrated by the Sentinel 1 and Sentinel 2 data collected on bare soil, and in cereal, pea and onion crop fields. To retrieve SSM, these scattering models need accurate measurements of the roughness surface parameters, standard deviation of the surface height (hrms) and correlation length (L). This work used a photogrammetric acquisition system carried on Unmanned Aerial Vehicles (UAV) to reconstruct digital surface models (DSM), which allowed these soil roughness parameters to be acquired in a large portion of the studied fields. The obtained results showed that the applied improved methodology effectively estimated SSM on bare and cultivated soils in the principal early growth stages. The bare soil experimentation yielded an R2 = 0.74 between the estimated and observed SSMs. For the cereal field, the relation between the estimated and measured SSMs yielded R2 = 0.71. In the experimental pea fields, the relation between the estimated and measured SSMs revealed R2 = 0.72 and 0.78, respectively, for peas 1 and peas 2. For the onion experimentation, the highest R2 equaled 0.5 in the principal growth stage (leaf development), but the crop R2 drastically decreased to 0.08 in the completed growth phase. The acquired results showed that the applied improved methodology proves to be an effective tool for estimating the SSM on bare and cultivated soils in the principal early growth stages.

Evaluation of Presswheels and Seed Coverers for Direct Seeding of Brassica

HortScience ◽  
1997 ◽  
Vol 32 (4) ◽  
pp. 599E-600
Author(s):  
Regina P. Bracy ◽  
Richard L. Parish
Keyword(s):  
Soil Moisture ◽  
Sandy Loam ◽  
Visual Observation ◽  
Mustard Seed ◽  
High Soil Moisture ◽  
Loam Soil ◽  
Direct Seeded ◽  
Plant Emergence ◽  
Moisture Conditions ◽  
Determine Effect

Improved stand establishment of direct-seeded crops has usually involved seed treatment and/or seed covers. Planters have been evaluated for seed/plant spacing uniformity, singulation, furrow openers, and presswheel design; however, effects of presswheels and seed coverers on plant establishment have not been widely investigated. Five experiments were conducted in a fine sandy loam soil to determine effect of presswheels and seed coverers on emergence of direct-seeded cabbage and mustard. Seed were planted with Stanhay 870 seeder equipped with one of four presswheels and seed coverers. Presswheels included smooth, mesh, concave split, and flat split types. Seed coverers included standard drag, light drag, paired knives, and no coverer. Soil moisture at planting ranged from 8% to 19% in the top 5 cm of bed. Differences in plant counts taken 2 weeks after planting were minimal with any presswheel or seed coverer. Visual observation indicated the seed furrow was more completely closed with the knife coverer in high soil moisture conditions. All tests received at least 14 mm of precipitation within 6 days from planting, which may account for lack of differences in plant emergence.

Exploring the potential of soil moisture reanalysis data for improving the identification of regional landslide triggering thresholds

2021 ◽  
Author(s):  
Nunziarita Palazzolo ◽  
David J. Peres ◽  
Enrico Creaco ◽  
Antonino Cancelliere
Keyword(s):  
Soil Moisture ◽  
Rainfall Event ◽  
Rainfall Thresholds ◽  
Rainfall Duration ◽  
Soil Moisture Data ◽  
Initial Soil Moisture ◽  
Initial Soil ◽  
Different Depths ◽  
Moisture Conditions ◽  
Landslide Triggering

<p>Landslide triggering thresholds provide the rainfall conditions that are likely to trigger landslides, therefore their derivation is key for prediction purposes. Different variables can be considered for the identification of thresholds, which commonly are in the form of a power-law relationship linking rainfall event duration and intensity or cumulated event rainfall. The assessment of such rainfall thresholds generally neglects initial soil moisture conditions at each rainfall event, which are indeed a predisposing factor that can be crucial for the proper definition of the triggering scenario. Thus, more studies are needed to understand whether and the extent to which the integration of the initial soil moisture conditions with rainfall thresholds could improve the conventional precipitation-based approach. Although soil moisture data availability has hindered such type of studies, yet now this information is increasingly becoming available at the large scale, for instance as an output of meteorological reanalysis initiatives. In particular, in this study, we focus on the use of the ERA5-Land reanalysis soil moisture dataset. Climate reanalysis combines past observations with models in order to generate consistent time series and the ERA5-Land data actually provides the volume of water in soil layer at different depths and at global scale. Era5-Land project is, indeed, a global dataset at 9 km horizontal resolution in which atmospheric data are at an hourly scale from 1981 to present. Volumetric soil water data are available at four depths ranging from the surface level to 289 cm, namely 0-7 cm, 7-28 cm, 28-100 cm, and 100-289 cm. After collecting the rainfall and soil moisture data at the desired spatio-temporal resolution, together with the target data discriminating landslide and no-landslide events, we develop automatic triggering/non-triggering classifiers and test their performances via confusion matrix statistics. In particular, we compare the performances associated with the following set of precursors: a) event rainfall duration and depth (traditional approach), b) initial soil moisture at several soil depths, and c) event rainfall duration and depth and initial soil moisture at different depths. The approach is applied to the Oltrepò Pavese region (northern Italy), for which the historical observed landslides have been provided by the IFFI project (Italian landslides inventory). Results show that soil moisture may allow an improvement in the performances of the classifier, but that the quality of the landslide inventory is crucial.</p>

Rainfall thresholds for the triggering of landslides considering previous soil moisture conditions (Asturias, NW Spain)

Landslides ◽  
2017 ◽  
Vol 15 (2) ◽  
pp. 273-282 ◽  
Author(s):  
Pablo Valenzuela ◽  
María José Domínguez-Cuesta ◽  
Manuel Antonio Mora García ◽  
Montserrat Jiménez-Sánchez
Keyword(s):  
Soil Moisture ◽  
Nw Spain ◽  
Rainfall Thresholds ◽  
Moisture Conditions

scholarly journals Germination of Ocotea pulchella (Nees) Mez (Lauraceae) seeds in laboratory and natural restinga environment conditions

2009 ◽  
Vol 69 (3) ◽  
pp. 935-942 ◽  
Author(s):  
LA. Pires ◽  
VJM. Cardoso ◽  
CA. Joly ◽  
RR. Rodrigues
Keyword(s):  
Soil Moisture ◽  
Soil Moisture Content ◽  
Weibull Model ◽  
Limiting Factors ◽  
Base Temperature ◽  
Temperature Range ◽  
Optimal Temperature Range ◽  
Dry Soil ◽  
Moisture Conditions ◽  
Temperature Water

The germination response of Ocotea pulchella (Nees) Mez seeds to light, temperature, water level and pulp presence is introduced. The laboratory assays were carried out in germination chambers and thermal-gradient apparatus, whereas the field assays were performed in environments with distinct light, temperature and soil moisture conditions within a permanent parcel of Restinga forest of the Parque Estadual da Ilha do Cardoso, Cananéia, São Paulo. The seeds do not exhibit dormancy, they are non photoblastic, and a loss of viability in dry stored seeds can be related to a decrease in water content of the seed. The presence of the pulp and the flooded substratum influenced negatively the germination of O. pulchella seeds tested in the laboratory. Otherwise, light and temperature probably are not limiting factors of the germination of O. pulchella seeds in the natural environment of Restinga. The optimum temperature range for germination of Ocotea pulchella seeds was 20 to 32 ºC, the minimum or base temperature estimated was 11 ºC and the maximum ranged between 33 and 42 ºC. The isotherms exhibited a sigmoidal pattern well described by the Weibull model in the sub-optimal temperature range. The germinability of O. pulchella seeds in the understorey, both in wet and dry soil, was higher than in gaps. Germination was not affected by fluctuations in soil moisture content in the understorey environment, whereas in gaps, germination was higher in wet soils. Thus, the germination of this species involves the interaction of two or more factors and it cannot be explained by a single factor.

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