Remote Sensing of Evapotranspiration over the Central Arizona Irrigation and Drainage District, USA

Knowledge of baseline water use for irrigated crops in the U.S. Southwest is important for understanding how much water is consumed under normal farm management and to help manage scarce resources. Remote sensing of evapotranspiration (ET) is an effective way to gain that knowledge: multispectral data can provide synoptic and time-repetitive estimates of crop-specific water use, and could be especially useful for this arid region because of dominantly clear skies and minimal precipitation. Although multiple remote sensing ET approaches have been developed and tested, there is not consensus on which of them should be preferred because there are still few intercomparison studies within this environment. To help build the experience needed to gain consensus, a remote sensing study using three ET models was conducted over the Central Arizona Irrigation and Drainage District (CAIDD). Aggregated ET was assessed for 137 wheat plots (winter/spring crop), 183 cotton plots (summer crop), and 225 alfalfa plots (year-round). The employed models were the Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC), the Two Source Energy Balance (TSEB), and Vegetation Index ET for the US Southwest (VISW). Remote sensing data were principally Landsat 5, supplemented by Landsat 7, MODIS Terra, MODIS Aqua, and ASTER. Using district-wide model averages, seasonal use (excluding surface evaporation) was 742 mm for wheat, 983 mm for cotton, and 1427 mm for alfalfa. All three models produced similar daily ET for wheat, with 6–8 mm/day mid-season. Model estimates diverged for cotton and alfalfa sites. Considering ET over cotton, TSEB estimates were 9.5 mm/day, METRIC 6 mm/day, and VISW 8 mm/day. For alfalfa, the ET values from TSEB were 8.0 mm/day, METRIC 5 mm/day, and VISW 6 mm/day. Lack of local validation information unfortunately made it impossible to rank model performance. However, by averaging results from all of them, ET model outliers could be identified. They ranged from −10% to +18%, values that represent expected ET modeling discrepancies. Relative to the model average, standardized ET-estimators—potential ET (ET ∘ ), FAO-56 ET, and USDA-SW gravimetric-ET— showed still greater deviations, up to 35% of annual crop water use for summer and year-round crops, suggesting that remote sensing of actual ET could lead to significantly improved estimates of crop water use. Results from this study highlight the need for conducting multi-model experiments during summer-months over sites with independent ground validation.

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Remote Sensing of Evapotranspiration over the Central Arizona Irrigation & Drainage District, USA

10.20944/preprints201809.0501.v1 ◽

2018 ◽

Author(s):

Andrew N. French ◽

Douglas J. Hunsaker ◽

Lahouari Bounoua ◽

Arnon Karnieli ◽

William Luckett ◽

...

Keyword(s):

Remote Sensing ◽

Energy Balance ◽

Vegetation Index ◽

Model Averaging ◽

Remote Sensing Data ◽

The Us ◽

Landsat 7 ◽

Terra Modis ◽

Model Variability ◽

Central Arizona

A remote sensing-based evapotranspiration (ET) study was conducted over the Central Arizona Irrigation and Drainage District (CAIDD), an Arizona agricultural region. ET was assessed means for 137 wheat plots, 183 cotton plots, and 225 alfalfa plots. The remote sensing ET models were the Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC), the Two Source Energy Balance (TSEB), and Vegetation Index ET for the US Southwest (VISW). Remote sensing data were principally Landsat 5, supplemented by Landsat 7, MODIS Terra, MODIS Aqua, and ASTER. The models produced similar daily ET for wheat, with 6–8 mm/d mid-season. For cotton and alfalfa daily ET showed greater differences, where TSEB produced largest daily ET, METRIC the least, and VISW in the midrange. Modeled cotton ET at mid-season ranged from 9.5 mm/d (TSEB), to 8 mm/d (VISW), and 6 mm/d (METRIC). For alfalfa ET, values at peak cover ranged from 8 mm/d (TSEB), 6 mm/d (VISW), and 5 mm/d (METRIC). Model bias ranged −10% to +18%. Relative to potential ET, FAO-56 ET, and USDA-SW gravimetric-ET, model variability ranged from negligible to 35% of annual crop water use. Model averaging was found a useful way to consider and reconcile all ET estimates.

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

Remote Sensing ◽

10.3390/rs10121867 ◽

2018 ◽

Vol 10 (12) ◽

pp. 1867 ◽

Cited By ~ 20

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. .

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

10.13031/2013.41797 ◽

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

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Evaluation of Evapotranspiration from Eddy Covariance Using Large Weighing Lysimeters

Agronomy ◽

10.3390/agronomy9020099 ◽

2019 ◽

Vol 9 (2) ◽

pp. 99 ◽

Cited By ~ 8

Author(s):

Jerry Moorhead ◽

Gary Marek ◽

Prasanna Gowda ◽

Xiaomao Lin ◽

Paul Colaizzi ◽

...

Keyword(s):

Energy Balance ◽

Eddy Covariance ◽

Water Use ◽

Growing Season ◽

Irrigation Scheduling ◽

Error Rates ◽

Energy Balance Closure ◽

Crop Water ◽

Crop Water Use ◽

Hourly Data

Evapotranspiration (ET) is an important component in the water budget and used extensively in water resources management such as water planning and irrigation scheduling. In semi-arid regions, irrigation is used to supplement limited and erratic growing season rainfall to meet crop water demand. Although lysimetery is considered the most accurate method for crop water use measurements, high-precision weighing lysimeters are expensive to build and operate. Alternatively, other measurement systems such as eddy covariance (EC) are being used to estimate crop water use. However, due to numerous explicit and implicit assumptions in the EC method, an energy balance closure problem is widely acknowledged. In this study, three EC systems were installed in a field containing a large weighing lysimeter at heights of 2.5, 4.5, and 8.5 m. Sensible heat flux (H) and ET from each EC system were evaluated against the lysimeter. Energy balance closure ranged from 64% to 67% for the three sensor heights. Results showed that all three EC systems underestimated H and consequently overestimated ET; however, the underestimation of H was greater in magnitude than the overestimation of ET. Analysis showed accuracy of ET was greater than energy balance closure with error rates of 20%–30% for half-hourly values. Further analysis of error rates throughout the growing season showed that energy balance closure and ET accuracy were greatest early in the season and larger error was found after plants reached their maximum height. Therefore, large errors associated with increased biomass may indicate unaccounted-for energy stored in the plant canopy as one source of error. Summing the half-hourly data to a daily time-step drastically reduced error in ET to 10%–15%, indicating that EC has potential for use in agricultural water management.

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Satellite remote sensing of crop water use in an irrigation area of south-east Australia

2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS ◽

10.1109/igarss.2013.6723525 ◽

2013 ◽

Cited By ~ 1

Author(s):

M. Abuzar ◽

D. Whitfield ◽

A. McAllister ◽

G. Lamb ◽

K. Sheffield ◽

...

Keyword(s):

Remote Sensing ◽

Water Use ◽

Satellite Remote Sensing ◽

Crop Water ◽

Irrigation Area ◽

Crop Water Use

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

10.5194/egusphere-egu2020-12539 ◽

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

This paper proposes a new approach to estimate and map separately gross and net water requirements and actual crop water use by applying multi&#8211;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&#8217;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 (EA) and canopy interception loss (Ic). 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 (ES) and plant transpiration (ET) by applying the ETMonitor model. High-resolution multi&#8211;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. EA and IC. The estimates were in good agreement with the ground observations, i.e. an R2 of 0.64 &#8211; 0.80 for actual water use and 0.66 &#8211; 0.97 for water losses. The RMSE was 0.6 &#8211; 1.2 mm/day for actual daily water use and 0.64 &#8211; 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.

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Determining water use of sorghum from two-source energy balance and radiometric temperatures

Hydrology and Earth System Sciences ◽

10.5194/hess-15-3061-2011 ◽

2011 ◽

Vol 15 (10) ◽

pp. 3061-3070 ◽

Cited By ~ 21

Author(s):

J. M. Sánchez ◽

R. López-Urrea ◽

E. Rubio ◽

V. Caselles

Keyword(s):

Energy Balance ◽

Water Use ◽

Irrigation Management ◽

Crop Coefficient ◽

Balance Model ◽

Crop Water ◽

Phenological Stages ◽

Crop Water Use ◽

Promising Tool ◽

Experimental Campaign

Abstract. Estimates of surface actual evapotranspiration (ET) can assist in predicting crop water requirements. An alternative to the traditional crop-coefficient methods are the energy balance models. The objective of this research was to show how surface temperature observations can be used, together with a two-source energy balance model, to determine crop water use throughout the different phenological stages of a crop grown. Radiometric temperatures were collected in a sorghum (Sorghum bicolor) field as part of an experimental campaign carried out in Barrax, Spain, during the 2010 summer growing season. Performance of the Simplified Two-Source Energy Balance (STSEB) model was evaluated by comparison of estimated ET with values measured on a weighing lysimeter. Errors of ±0.14 mm h−1 and ±1.0 mm d−1 were obtained at hourly and daily scales, respectively. Total accumulated crop water use during the campaign was underestimated by 5%. It is then shown that thermal radiometry can provide precise crop water necessities and is a promising tool for irrigation management.

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