Retrieval of an Available Water-Based Soil Moisture Proxy from Thermal Infrared Remote Sensing. Part I: Methodology and Validation

2009 ◽  
Vol 10 (3) ◽  
pp. 665-683 ◽  
Author(s):  
Christopher R. Hain ◽  
John R. Mecikalski ◽  
Martha C. Anderson
Keyword(s):  
Soil Moisture ◽  
Potential Evapotranspiration ◽  
Thermal Infrared ◽  
Surface Energy Budget ◽  
Rooting Depth ◽  
Thermal Infrared Remote Sensing ◽  
Water Fraction ◽  
Available Water ◽  
Oklahoma Mesonet ◽  
Moisture Conditions

Abstract A retrieval of available water fraction ( fAW) is proposed using surface flux estimates from satellite-based thermal infrared (TIR) imagery and the Atmosphere–Land Exchange Inversion (ALEXI) model. Available water serves as a proxy for soil moisture conditions, where fAW can be converted to volumetric soil moisture through two soil texture dependents parameters—field capacity and permanent wilting point. The ability of ALEXI to provide valuable information about the partitioning of the surface energy budget, which can be largely dictated by soil moisture conditions, accommodates the retrieval of an average fAW over the surface to the rooting depth of the active vegetation. For this method, the fraction of actual to potential evapotranspiration ( fPET) is computed from an ALEXI estimate of latent heat flux and potential evapotranspiration (PET). The ALEXI-estimated fPET can be related to fAW in the soil profile. Four unique fPET to fAW relationships are proposed and validated against Oklahoma Mesonet soil moisture observations within a series of composite periods during the warm seasons of 2002–04. Using the validation results, the most representative of the four relationships is chosen and shown to produce reasonable (mean absolute errors values less than 20%) fAW estimates when compared to Oklahoma Mesonet observations. Quantitative comparisons between ALEXI and modeled fAW estimates from the Eta Data Assimilation System (EDAS) are also performed to assess the possible advantages of using ALEXI soil moisture estimates within numerical weather predication (NWP) simulations. This TIR retrieval technique is advantageous over microwave techniques because of the ability to indirectly sense fAW—and hence soil moisture conditions—extending into the root-zone layer. Retrievals are also possible over dense vegetation cover and are available on spatial resolutions on the order of the native TIR imagery. A notable disadvantage is the inability to retrieve fAW conditions through cloud cover.

EVAPOTRANSPIRATION AND LEAF WATER STATUS OF ALFALFA GROWING UNDER ADVECTIVE CONDITIONS

1981 ◽  
Vol 61 (3) ◽  
pp. 601-607 ◽  
Author(s):  
R. J. WILLIAMS ◽  
DARRYL G. STOUT
Keyword(s):  
Soil Moisture ◽  
Potential Evapotranspiration ◽  
Water Status ◽  
Bowen Ratio ◽  
High Rate ◽  
Leaf Water Status ◽  
Leaf Osmotic Potential ◽  
Physically Based ◽  
Environmental Demand ◽  
Moisture Conditions

Actual evapotranspiration (LE) and leaf osmotic potential (ψs) were measured on a Medicago sativa L. (alfalfa, cv. Thor) field in interior British Columbia that is subject to advection. During periods of advection, LE, measured by the Bowen ratio energy balance method, exceeded both the net radiation (Q*) and the potential evapotranspiration (PE) calculated by the physically based formula of Priestley and Taylor (1972). During advection, Q* was a better approximation of LE than was PE. During nonadvection periods, LE was approximately equal to PE. It was found that the Jury and Tanner (1975) modification of PE for advective conditions gave favorable results during periods immediately following irrigation. Diurnal measurements revealed that leaf ψs reached a minimum by about 1200 h and then remained constant even though LE continued at a high rate. Leaf ψs measured at 0800 h reflected soil moisture conditions, and leaf ψs measured at 1400 h reflected both soil moisture conditions and environmental demand.

scholarly journals The Effect of the Dry Line and Convective Initiation on Drought Evolution over Oklahoma during the 2011 Drought

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Paul X. Flanagan ◽  
Jeffrey B. Basara ◽  
Bradley G. Illston ◽  
Jason A. Otkin
Keyword(s):  
Soil Moisture ◽  
Large Scale ◽  
Warm Season ◽  
Convective Initiation ◽  
Model Simulations ◽  
Variable Surface ◽  
Oklahoma Mesonet ◽  
Dry Conditions ◽  
Moisture Conditions ◽  
The Impact

Observations from the Oklahoma Mesonet and high resolution Weather Research and Forecasting model simulations were used to evaluate the effect that the dry line and large-scale atmospheric patterns had on drought evolution during 2011. Mesonet observations showed that a “dry” and “wet” pattern developed across Oklahoma due to anomalous atmospheric patterns. The location of the dry line varied due to this “dry” and “wet” pattern, with the average dry line location around 1.5° longitude further to the east than climatology. Model simulations were used to further quantify the impact of variable surface conditions on dry line evolution and convective initiation (CI) during April and May 2011. Specifically, soil moisture conditions were altered to depict “wet” and “dry” conditions across the domain by replacing the soil moisture values by each soil category’s porosity or wilting point value. Overall, the strength of the dry line boundary, its position, and subsequent CI were dependent on the modification of soil moisture. The simulations demonstrated that modifying soil moisture impacted the nature of the dry line and showed that soil moisture conditions during the first half of the warm season modified the dry line pattern and influenced the evolution and perpetuation of drought over Oklahoma.

Soil water content sensors from laboratory calibration to field monitoring: discrepancies and uncertainties

2021 ◽  
Author(s):  
Angela Gabriela Morales Santos ◽  
Reinhard Nolz
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Root Zone ◽  
Sandy Loam ◽  
Irrigation Scheduling ◽  
Water Monitoring ◽  
Rooting Depth ◽  
Water Fraction ◽  
Laboratory Calibration

<p>Monitoring soil water status is one key option to optimise water use in agriculture. Soil moisture sensors are widely used for investigating available soil water to optimally adapt irrigation scheduling to crop water requirements. Although reliable measurements are subject to proper soil-specific calibration of sensors, meaningful calibration functions are not always available. Another question is the plausibility of soil water monitoring under field conditions. The objective of this study was to calibrate four multi-sensor capacitance probes in the laboratory and  to evaluate the calibrated water content readings under natural conditions in an irrigated field by means of a modelling approach.</p><p>The multi-sensor capacitance probes (SM1 by ADCON Telemetry) were of 90 cm length and contained nine sensors (S1 to S9) at 10 cm spacing. The digital output values were given in scaled frequency units (SFU). The laboratory calibration was carried out on sandy loam and sand. Measurements were undertaken by placing the probes inside a PVC tube backfilled with soil at different water contents. Soil samples were collected using metallic cylinders of 250 cm<sup>3</sup>, from which volumetric water content (θ) was determined gravimetrically. The sensor readings in soil were normalised by using sensor readings in air and water as lower and upper limit, respectively. The pairs of measured θ and normalised SFU were related to each other by curve fitting. For each soil type, eight sensor-specific calibration functions were developed that allowed the calculation of θ in cm<sup>3</sup> cm<sup>−</sup><sup>3</sup> from SM1 readings.</p><p>After calibration, the SM1 probes were installed in a field in Obersiebenbrunn, Lower Austria, where sandy loam is the main soil. Three of the probes monitored irrigated plots and the fourth a rainfed plot. To obtain reference values, one HydraProbe soil moisture sensor (Stevens Water Monitoring Systems) was installed in 20 cm depth, near each SM1. The average daily θ-values from the S2 (20 cm depth) contained in each SM1 probe were compared to the water fraction collected with the corresponding HydraProbe. Moreover, the SM1 θ-values were used to determine the daily soil water depletion in the root zone (Dr) for a rooting depth of 1 m. The obtained Dr datasets were compared to Dr simulated using CROPWAT 8.0 by FAO.</p><p>The field results showed that the SM1 probes were able to reproduce the HydraProbe dynamics of wetting and drying periods during the crop season. Nevertheless, a considerable difference was noted between the sensor measurements. The SM1 overestimated θ in the irrigated plots, whereas it underestimated θ in the rainfed plot. The discrepancies can be attributed mainly to the different physical mechanisms behind the sensors and to the unfeasible reproduction of field bulk density and soil structure in the laboratory. Furthermore, the operational frequency and permittivity response of the SM1 probes should be revised for future versions. The simulation results showed that the observed Dr values were more consistent with CROPWAT Dr results at the end of the simulation period, suggesting that the SM1 required several weeks to consolidate and give representative θ-values for the soil profile.</p>

scholarly journals Surface Soil Moisture Retrieval Using Optical/Thermal Infrared Remote Sensing Data

2018 ◽  
Vol 56 (9) ◽  
pp. 5433-5442 ◽  
Author(s):  
Yawei Wang ◽  
Jian Peng ◽  
Xiaoning Song ◽  
Pei Leng ◽  
Ralf Ludwig ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Surface Soil ◽  
Remote Sensing Data ◽  
Thermal Infrared ◽  
Surface Soil Moisture ◽  
Thermal Infrared Remote Sensing ◽  
Sensing Data ◽  
Infrared Remote Sensing

scholarly journals Estimation of Surface Soil Moisture from Thermal Infrared Remote Sensing Using an Improved Trapezoid Method

2015 ◽  
Vol 7 (7) ◽  
pp. 8250-8270 ◽  
Author(s):  
Yuting Yang ◽  
Huade Guan ◽  
Di Long ◽  
Bing Liu ◽  
Guanghua Qin ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Surface Soil ◽  
Thermal Infrared ◽  
Surface Soil Moisture ◽  
Thermal Infrared Remote Sensing ◽  
Infrared Remote Sensing ◽  
Trapezoid Method

Mesoscale Monitoring of Soil Moisture across a Statewide Network

2008 ◽  
Vol 25 (2) ◽  
pp. 167-182 ◽  
Author(s):  
Bradley G. Illston ◽  
Jeffrey B. Basara ◽  
Christopher A. Fiebrich ◽  
Kenneth C. Crawford ◽  
Eric Hunt ◽  
...  
Keyword(s):  
Quality Assurance ◽  
Soil Moisture ◽  
Land Surface ◽  
Surface Processes ◽  
Background Information ◽  
Technical Design ◽  
Once Daily ◽  
Oklahoma Mesonet ◽  
Moisture Conditions

Abstract Soil moisture is an important component in many hydrologic and land–atmosphere interactions. Understanding the spatial and temporal nature of soil moisture on the mesoscale is vital to determine the influence that land surface processes have on the atmosphere. Recognizing the need for improved in situ soil moisture measurements, the Oklahoma Mesonet, an automated network of 116 remote meteorological stations across Oklahoma, installed Campbell Scientific 229-L devices to measure soil moisture conditions. Herein, background information on the soil moisture measurements, the technical design of the soil moisture network embedded within the Oklahoma Mesonet, and the quality assurance (QA) techniques applied to the observations are provided. This project also demonstrated the importance of operational QA regarding the data collected, whereby the percentage of observations that passed the QA procedures increased significantly once daily QA was applied.

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