Mapping daily and seasonal evapotranspiration from irrigated crops using global climate grids and satellite imagery: Automation and methods comparison

Biggs, Trent W.; Marshall, Michael; Messina, Alex

doi:10.1002/2016wr019107

Cited by 53 publications

(32 citation statements)

References 60 publications

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“…This makes Landsat a better option than MODIS when it comes to studying spatially heterogeneous riparian water consumption. The underestimation of MOD16 has been reported for croplands in previous studies [65][66][67]. The MOD16-ET from the CA portion was 34% greater than the AZ areas.…”

Section: Comparisons With Mod16 and Lcrassupporting

confidence: 52%

Mapping Annual Riparian Water Use Based on the Single-Satellite-Scene Approach

2017

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Abstract:The accurate estimation of water use by groundwater-dependent riparian vegetation is of great importance to sustainable water resource management in arid/semi-arid regions. Remote sensing methods can be effective in this regard, as they capture the inherent spatial variability in riparian ecosystems. The single-satellite-scene (SSS) method uses a derivation of the Normalized Difference Vegetation Index (NDVI) from a single space-borne image during the peak growing season and minimal ground-based meteorological data to estimate the annual riparian water use on a distributed basis. This method was applied to a riparian ecosystem dominated by tamarisk along a section of the lower Colorado River in southern California. The results were compared against the estimates of a previously validated remotely sensed energy balance model for the year 2008 at two different spatial scales. A pixel-wide comparison showed good correlation (R 2 = 0.86), with a mean residual error of less than 104 mm·year −1 (18%). This error reduced to less than 95 mm·year −1 (15%) when larger areas were used in comparisons. In addition, the accuracy improved significantly when areas with no and low vegetation cover were excluded from the analysis. The SSS method was then applied to estimate the riparian water use for a 23-year period . The average annual water use over this period was 748 mm·year −1 for the entire study area, with large spatial variability depending on vegetation density. Comparisons with two independent water use estimates showed significant differences. The MODIS evapotranspiration product (MOD16) was 82% smaller, and the crop-coefficient approach employed by the US Bureau of Reclamation was 96% larger, than that from the SSS method on average.

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Section: Comparisons With Mod16 and Lcrassupporting

confidence: 52%

Mapping Annual Riparian Water Use Based on the Single-Satellite-Scene Approach

2017

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“…In contrast, high temporal resolution satellites are coarse in spatial resolution for field-scale observations [25]. The daily or even instantaneous estimation of ET c at the field scale is crucial for irrigation scheduling and is expected to have great application prospects in the future [240,259,262,263]. In this regard, the future direction of satellite-based ET estimates may focus on temporal downscaling either by extrapolation of instantaneous measurement [264], interpolation between two successive observations [201], data fusion of multiple satellites [25,260], and spatial downscaling using multiple satellites [265][266][267][268].…”

Section: Evapotranspirationmentioning

confidence: 99%

A Review of Current and Potential Applications of Remote Sensing to Study the Water Status of Horticultural Crops

Gautam

Pagay

2020

Agronomy

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With increasingly advanced remote sensing systems, more accurate retrievals of crop water status are being made at the individual crop level to aid in precision irrigation. This paper summarises the use of remote sensing for the estimation of water status in horticultural crops. The remote measurements of the water potential, soil moisture, evapotranspiration, canopy 3D structure, and vigour for water status estimation are presented in this comprehensive review. These parameters directly or indirectly provide estimates of crop water status, which is critically important for irrigation management in farms. The review is organised into four main sections: (i) remote sensing platforms; (ii) the remote sensor suite; (iii) techniques adopted for horticultural applications and indicators of water status; and, (iv) case studies of the use of remote sensing in horticultural crops. Finally, the authors' view is presented with regard to future prospects and research gaps in the estimation of the crop water status for precision irrigation.

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“…The selection of these anchor pixels typically involves some training and manual image interpretation, and is often arbitrary. To make the process more consistent, we developed a method to select those pixels automatically based on the statistics of NDVI and Ts maps, following and integrating similar concepts proposed by previous studies [48][49][50][51]. The cumulative histogram of NDVI and Ts were first generated.…”

Section: Automated "Cold" and "Hot" Pixel Selectionmentioning

confidence: 99%

Evapotranspiration Estimate over an Almond Orchard Using Landsat Satellite Observations

Jin

Kandelous

et al. 2017

Remote Sensing

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California growers face challenges with water shortages and there is a strong need to use the least amount of water while optimizing yield. Timely information on evapotranspiration (ET), a dominant component of crop consumptive water use, is critical for growers to tailor irrigation management based on in-field spatial variability and in-season variations. We evaluated the performance of a remote sensing-based approach, Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC), in mapping ET over an almond orchard in California, driven by Landsat satellite observations. Reference ET from a network of weather stations over well-watered grass (ET o ) was used for the internal calibration and for deriving ET at daily and extended time period, instead of alfalfa based reference evapotranspiration (ET r ). Our study showed that METRIC daily ET estimates during Landsat overpass dates agreed well with the field measurements. During 2009-2012, a root mean square error (RMSE) of 0.53 mm/day and a coefficient of determination (R 2 ) of 0.87 were found between METRIC versus observed daily ET. Monthly ET estimates had a higher accuracy, with a RMSE of 12.08 mm/month, a R 2 of 0.90, and a relatively small relative mean difference (RMD) of 9.68% during 2009-2012 growing seasons. Net radiation and Normalized Difference Vegetation Index (NDVI) from remote sensing observations were highly correlated with spatial and temporal ET estimates. An empirical model was developed to estimate daily ET using NDVI, net radiation (R n ), and vapor pressure deficit (VPD). The validation showed that the accuracy of this easy-to-use empirical method was slightly lower than that of METRIC but still reasonable, with a RMSE of 0.71 mm/day when compared to ground measurements. The remote sensing based ET estimate will support a variety of State and local interests in water use and irrigation management, for both planning and regulatory/compliance purposes, and it provides the farmers observation-based guidance for site-specific and time-sensitive irrigation management.

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Mapping daily and seasonal evapotranspiration from irrigated crops using global climate grids and satellite imagery: Automation and methods comparison

Cited by 53 publications

References 60 publications

Mapping Annual Riparian Water Use Based on the Single-Satellite-Scene Approach

Mapping Annual Riparian Water Use Based on the Single-Satellite-Scene Approach

A Review of Current and Potential Applications of Remote Sensing to Study the Water Status of Horticultural Crops

Evapotranspiration Estimate over an Almond Orchard Using Landsat Satellite Observations

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