Evaluating Remote Sensing-based Crop Water Use Monitoring Methods Using Soil Moisture Sensors

2012 ◽  
Author(s):  
José Luis Chávez ◽  
Saleh Taghvaeian ◽  
Thomas J Trout
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Water Use ◽  
Crop Water ◽  
Monitoring Methods ◽  
Crop Water Use ◽  
Soil Moisture Sensors

scholarly journals CubeSats Enable High Spatiotemporal Retrievals of Crop-Water Use for Precision Agriculture

2018 ◽  
Vol 10 (12) ◽  
pp. 1867 ◽  
Author(s):  
Bruno Aragon ◽  
Rasmus Houborg ◽  
Kevin Tu ◽  
Joshua B. Fisher ◽  
Matthew McCabe
Keyword(s):  
Remote Sensing ◽  
Eddy Covariance ◽  
Water Use ◽  
Spatial Resolution ◽  
Precision Agriculture ◽  
High Spatial Resolution ◽  
Assessment Tools ◽  
Optical Data ◽  
Crop Water ◽  
Crop Water Use

Remote sensing based estimation of evapotranspiration (ET) provides a direct accounting of the crop water use. However, the use of satellite data has generally required that a compromise between spatial and temporal resolution is made, i.e., one could obtain low spatial resolution data regularly, or high spatial resolution occasionally. As a consequence, this spatiotemporal trade-off has tended to limit the impact of remote sensing for precision agricultural applications. With the recent emergence of constellations of small CubeSat-based satellite systems, these constraints are rapidly being removed, such that daily 3 m resolution optical data are now a reality for earth observation. Such advances provide an opportunity to develop new earth system monitoring and assessment tools. In this manuscript we evaluate the capacity of CubeSats to advance the estimation of ET via application of the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) retrieval model. To take advantage of the high-spatiotemporal resolution afforded by these systems, we have integrated a CubeSat derived leaf area index as a forcing variable into PT-JPL, as well as modified key biophysical model parameters. We evaluate model performance over an irrigated farmland in Saudi Arabia using observations from an eddy covariance tower. Crop water use retrievals were also compared against measured irrigation from an in-line flow meter installed within a center-pivot system. To leverage the high spatial resolution of the CubeSat imagery, PT-JPL retrievals were integrated over the source area of the eddy covariance footprint, to allow an equivalent intercomparison. Apart from offering new precision agricultural insights into farm operations and management, the 3 m resolution ET retrievals were shown to explain 86% of the observed variability and provide a relative RMSE of 32.9% for irrigated maize, comparable to previously reported satellite-based retrievals. An observed underestimation was diagnosed as a possible misrepresentation of the local surface moisture status, highlighting the challenge of high-resolution modeling applications for precision agriculture and informing future research directions. .

Evaluating crop water requirements and actual crop water use with center pivot irrigation system in Inner Mongolia of China

2020 ◽  
Author(s):  
Peejush Pani ◽  
Li Jia ◽  
Massimo Menenti ◽  
Guangcheng Hu ◽  
Chaolei Zheng ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Water Use ◽  
Inner Mongolia ◽  
Crop Water ◽  
Water Requirements ◽  
Water Losses ◽  
Crop Water Use ◽  
Crop Water Requirements ◽  
Center Pivot

<p>This paper proposes a new approach to estimate and map separately gross and net water requirements and actual crop water use by applying multi–spectral satellite data. Remote sensing information is witnessing a boom in the availability of high-resolution multi-spectral data with frequent revisit time, paving the path for improved assessment of precision agriculture and minimizing the wastage of irrigation water. In this study, we have tried to integrate multi-source remote sensing information with farmer’s irrigation practices to evaluate the water use and losses at farm-scale for center pivot irrigation systems (CPIS) in Inner Mongolia autonomous region of China. The region is practicing modernized irrigation methods to efficiently use groundwater. Crop gross water requirements are estimated by evaluating separately the net crop water requirements (CWR) and the water losses inherently from a CPIS, i.e. droplet evaporation to the air directly before they fell on the crop canopy during irrigation application (<em>E<sub>A</sub></em>) and canopy interception loss (<em>I<sub>c</sub></em>). The crop water requirement is estimated according to the FAO-56 method based on the Penman-Monteith equation. Actual crop water use is evaluated by estimating separately soil evaporation (<em>E<sub>S</sub></em>) and plant transpiration (<em>E<sub>T</sub></em>) by applying the ETMonitor model. High-resolution multi–spectral data acquired by Sentinel-2 MSI and Landsat-8 OLI together with meteorological forcing data and soil moisture retrievals were used to construct daily estimates of crop water requirements and actual use. Finally, the performance of irrigation scenarios was assessed by applying a performance indicator (IP), as the ratio between gross water requirement and the volume of irrigation applied, where values closer to unity referring to optimum utilization and minimum loss. Measurements of actual evapotranspiration by eddy covariance system were applied to evaluate the actual evapotranspiration estimates by the ETMonitor. Field experiments were also carried out to validate the estimated irrigation losses, i.e. <em>E<sub>A</sub></em> and <em>I<sub>C</sub></em>. The estimates were in good agreement with the ground observations, i.e. an R<sup>2</sup> of 0.64 – 0.80 for actual water use and 0.66 – 0.97 for water losses. The RMSE was 0.6 – 1.2 mm/day for actual daily water use and 0.64 – 1.55 mm water losses for each irrigation, respectively. The IP was estimated as 1.6 for the performance of CPIS as per the above definition. Overall, the study shows that CPIS has under-performed in minimizing water losses in the study area with losses of 25.4% per season of the total volume of water applied for wheat, and 23.7% per season for potato. This implies that the amount of water applied was largely insufficient to meet the gross water requirements, i.e. including losses.</p>

A thermal-based remote sensing modelling system for estimating crop water use and stress from field to regional scales

2016 ◽  
pp. 71-80 ◽  
Author(s):  
W.P. Kustas ◽  
M.C. Anderson ◽  
K.A. Semmens ◽  
J.G. Alfieri ◽  
F. Gao ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Use ◽  
Crop Water ◽  
Crop Water Use ◽  
Modelling System

Making sense of cosmic-ray soil moisture measurements and eddy covariance data with regard to crop water use and field water balance

2018 ◽  
Vol 204 ◽  
pp. 271-280 ◽  
Author(s):  
Enli Wang ◽  
Chris J. Smith ◽  
Ben C.T. Macdonald ◽  
James R. Hunt ◽  
Hongtao Xing ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Balance ◽  
Eddy Covariance ◽  
Water Use ◽  
Cosmic Ray ◽  
Crop Water ◽  
Crop Water Use ◽  
Making Sense ◽  
Field Water Balance

Estimating Crop Water Use for Camelina with Remote Sensing

2008 ◽  
Author(s):  
Andrew N French ◽  
Douglas J Hunsaker ◽  
Kelly Thorp ◽  
Thomas R Clarke
Keyword(s):  
Remote Sensing ◽  
Water Use ◽  
Crop Water ◽  
Crop Water Use
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