scholarly journals Investigating soil moisture dynamics for improved applications of radar satellites in agricultural water management

2021 ◽  
Author(s):  
Coleen Dorothy Urbano Carranza
Keyword(s):  
Water Management ◽  
Soil Moisture ◽  
Agricultural Water ◽  
Agricultural Water Management ◽  
Soil Moisture Dynamics ◽  
Moisture Dynamics

Field scale root zone soil moisture estimation by coupling cosmic-ray neutron sensor with soil moisture sensors

2020 ◽  
Author(s):  
Hami Said ◽  
Georg Weltin ◽  
Lee Kheng Heng ◽  
Trenton Franz ◽  
Emil Fulajtar ◽  
...  
Keyword(s):  
Water Management ◽  
Soil Moisture ◽  
Root Zone ◽  
Cosmic Ray ◽  
Agricultural Water ◽  
Field Scale ◽  
Agricultural Water Management ◽  
Soil Moisture Sensors ◽  
Major Disadvantage ◽  
Filter Approach

<p>Since it has become clear that climate change is having a major impact on water availability for agriculture and crop productivity, an accurate estimation of field-scale root-zone soil moisture (RZSM) is essential for improved agricultural water management. The Cosmic Ray Neutron Sensor (CRNS) has recently been used for field-scale soil moisture (SM) monitoring in large areas and is a credible and robust technique. Like other remote or proximal sensing techniques, the CRNS provides only SM data in the near surface. One of the challenges and needs is to extend the vertical footprint of the CRNS to the root zone of major crops. This can be achieved by coupling the CRNS measurements with conventional methods for soil moisture measurements, which provide information on soil moisture for whole rooting depth.</p><p>The objective of this poster presentation is to estimate field-scale RZSM by correlating the CRNS information with that from soil moisture sensors that provide soil moisture data for the whole root depth. In this study, the Drill and Drop probes which provide continuous profile soil moisture were selected. The RZSM estimate was calculated using an exponential filter approach.</p><p>Winter Wheat cropped fields in Rutzendorf, Marchfeld region (Austria) were instrumented with a CRNS and Drill & Drop probes. An exponential filter approach was applied on the CRNS and Drill and drop sensor data to characterize the RZSM. The preliminary results indicate the ability of the merging framework procedure to improve field-scale RZSM in real-time. This study demonstrated how to combine the advantages of CRNS nuclear technique (especially the large footprint and good representativeness of obtained data) with the advantages of conventional methods (providing data for whole soil profile) and overcome the shortcoming of both methods (the lack of information in the deeper part of soil profile being the major disadvantage of CRNS and the spatial limitation and low representativeness of point data being the major disadvantage of conventional capacitance sensors). This approach can be very helpful for improving agricultural water management.</p>

scholarly journals Effects of Surface Heterogeneity Due to Drip Irrigation on Scintillometer Estimates of Sensible, Latent Heat Fluxes and Evapotranspiration over Vineyards

Water ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 81
Author(s):  
Hatim M. E. Geli ◽  
José González-Piqueras ◽  
Christopher M. U. Neale ◽  
Claudio Balbontín ◽  
Isidro Campos ◽  
...  
Keyword(s):  
Water Management ◽  
Soil Moisture ◽  
Surface Heterogeneity ◽  
Irrigation Scheduling ◽  
Heat Fluxes ◽  
Source Surface ◽  
Agricultural Water ◽  
Agricultural Water Management ◽  
Vegetation Growth ◽  
Growth Variability

Accurate estimates of sensible (H) and latent (LE) heat fluxes and actual evapotranspiration (ET) are required for monitoring vegetation growth and improved agricultural water management. A large aperture scintillometer (LAS) was used to provide these estimates with the objective of quantifying the effects of surface heterogeneity due to soil moisture and vegetation growth variability. The study was conducted over drip-irrigated vineyards located in a semi-arid region in Albacete, Spain during summer 2007. Surface heterogeneity was characterized by integrating eddy covariance (EC) observations of H, LE and ET; land surface temperature (LST) and normalized difference vegetation index (NDVI) data from Landsat and MODIS sensors; LST from an infrared thermometer (IRT); a data fusion model; and a two-source surface energy balance model. The EC observations showed 16% lack of closure during unstable atmospheric conditions and was corrected using the residual method. The comparison between the LAS and EC measurements of H, LE, and ET showed root mean square difference (RMSD) of 25 W m−2, 19 W m−2, and 0.41 mm day−1, respectively. LAS overestimated H and underestimated both LE and ET by 24 W m−2, 34 W m−2, and 0.36 mm day−1, respectively. The effects of soil moisture on LAS measurement of H was evaluated using the Bowen ratio, β. Discrepancies between HLAS and HEC were higher at β ≤ 0.5 but improved at 1 ≥ β > 0.5 and β > 1.0 with R2 of 0.76, 0.78, and 0.82, respectively. Variable vineyard growth affected LAS performance as its footprints saw lower NDVILAS compared to that of the EC (NDVIEC) by ~0.022. Surface heterogeneity increased during wetter periods, as characterized by the LST–NDVI space and temperature vegetation dryness index (TVDI). As TVDI increased (decreased) during drier (wetter) conditions, the discrepancies between HLAS and HEC, as well as LELAS and LEEC Re decreased (increased). Thresholds of TVDI of 0.3, 0.25, and 0.5 were identified, above which better agreements between LAS and EC estimates of H, LE, and ET, respectively, were obtained. These findings highlight the effectiveness and ability of LAS in monitoring vegetation growth over heterogonous areas with variable soil moisture, its potential use in supporting irrigation scheduling and agricultural water management over large regions.

High-resolution soil moisture mapping through the use of Cosmic-Ray Neutron Sensor and Sentinel-1 data for temperate and semi-arid environments

2021 ◽  
Author(s):  
Hami Said ◽  
Modou Mbaye ◽  
Lee Kheng Heng ◽  
Emil Fulajtar ◽  
Georg Weltin ◽  
...  
Keyword(s):  
Water Management ◽  
Remote Sensing ◽  
Soil Moisture ◽  
Regional Scale ◽  
Cosmic Ray ◽  
Microwave Remote Sensing ◽  
Nuclear Technology ◽  
Agricultural Water ◽  
Agricultural Water Management ◽  
Semi Arid

<p>Global climate change has a major impact on the availability of water in agriculture. Sustainable agricultural productivity to ensure food security requires good agricultural water management.</p><p>Soil moisture is one of the important variables in irrigation management, and there are many different techniques for estimating it at different scales, from point to landscape scales.</p><p>Cosmic-Ray Neutron Sensor (CRNS) technology has the capability to estimate field-scale soil moisture (SM) in large areas of up to 20 to 30 ha and has demonstrated its ability to support agricultural water management and hydrology studies. However, measurement of soil moisture on a global or regional scale can only be achieved from satellite remote sensing.</p><p>Recently, active microwave remote sensing Synthetic Aperture Radar (SAR) imaging from Sentinel-1 shows great potential for high spatial resolution soil moisture monitoring and can be the basis for producing soil moisture maps. However, these maps can be only used after calibration. Such calibration can be done through traditional, point soil moisture sampling or measurement, which is time-consuming and costly. CRNS technology can be used for calibration and validation remote sensing imagery predictions at field and area-wide level.</p><p>In this study a conversion model to retrieve soil moisture from Sentinel-1 (SAR) was developed using the VV (vertical-vertical) polarization, which is highly sensitive to soil moisture, and then calibrated and validated using CRNS data from temperate (Austria) and semi-arid (Kuwait) Environments. This study is a major step in the monitoring of soil moisture at high spatial and temporal resolution by combining remote sensing and the CRNS based nuclear technology. The preliminary results show the great potential of using nuclear technology such as CRNS for remote sensing calibration of Sentinel-1 (SAR).</p>

Soil moisture dynamics of different land-cover types in the blacksoil regions of China

2009 ◽  
Vol 17 (2) ◽  
pp. 256-260 ◽  
Author(s):  
Feng WANG ◽  
Shu-Qi WANG ◽  
Xiao-Zeng HAN ◽  
Feng-Xian WANG ◽  
Ke-Qiang ZHANG
Keyword(s):  
Soil Moisture ◽  
Land Cover ◽  
Soil Moisture Dynamics ◽  
Land Cover Types ◽  
Moisture Dynamics
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