Field Characterization of Field Capacity and Root Zone Available Water Capacity for Variable Rate Irrigation

Lo, Tsz Him; Heeren, Derek M.; Mateos, Luciano; Luck, Joe D.; Martin, Derrel L.; Miller, Keith A.; Barker, J. Burdette; Shaver, Timothy M.

doi:10.13031/aea.11963

Cited by 35 publications

(22 citation statements)

References 29 publications

(48 reference statements)

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“…Martin et al (1990) demonstrated that "good indication of the field capacity water content can be determined by sampling field soils one to three days after a thorough irrigation or rain and when crop water use is small." This suggestion is consistent with the concept of FC obs (Lo et al, 2017). In this study, the FC obs was determined for the Yutan and Fillmore soil types from the graph of temporal trends in root zone water depth from the in situ GS-1 data (fig.…”

Section: Implications For Irrigation Managementsupporting

confidence: 86%

“…For field irrigation applications,  MAD is generally considered to be 50% of the plant-available water of the soil type, as error in  v measurement may result in unintended crop stress. The FC ( FC ) for the experimental site (silty clay loam soil) was 40% on average, and 50% MAD was attained at  MAD of 28% based on past studies (Barker et al, 2017;Lo et al, 2017). Therefore, as a part of the laboratory experiment, the soil was saturated initially and then readings were taken from  v of 41.5% to 28%, recording the weight at increments of 1.5%  v .…”

Section: Experiments Descriptionmentioning

confidence: 99%

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Soil Structure and Texture Effects on the Precision of Soil Water Content Measurements with a Capacitance- Based Electromagnetic Sensor

Singh

Heeren²,

Rudnick³

et al. 2020

Transactions of the ASABE

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Collection HIGHLIGHTS Capacitance-based electromagnetic soil moisture sensors were tested in disturbed and undisturbed soils.  The uncertainty in estimation of soil water depth was lower using the undisturbed soil sample calibrations.  The uncertainty in estimation of soil water depletion was lower than the uncertainty in volumetric water content.  Undisturbed calibration of water depletion quantifies water demand with better precision and avoids over-watering.ABSTRACT. The physical properties of soil, such as structure and texture, can affect the performance of an electromagnetic sensor in measuring soil water content. Historically, calibrations have been performed on repacked samples in the laboratory and on in situ soils in the field, but little research has been done on laboratory calibrations with intact (undisturbed) soil cores. In this study, three replications each of disturbed and undisturbed soil samples were collected from two soil texture classes (Yutan silty clay loam and Fillmore silt loam) at a field site in eastern Nebraska to investigate the effects of soil structure and texture on the precision of a METER Group GS-1 capacitance-based sensor calibration. In addition, GS-1 sensors were installed in the field near the soil collection sites at three depths (0.15, 0.46, and 0.76 m). The soil moisture sensor had higher precision in the undisturbed laboratory setup, as the undisturbed calibration had a better correlation [slope closer to one, R 2 undisturbed (0.89) > R 2 disturbed (0.73)] than the disturbed calibrations for the Yutan and Fillmore texture classes, and the root mean square difference using the laboratory calibration (RMSD L ) was higher for pooled disturbed samples (0.053 m 3 m -3 ) in comparison to pooled undisturbed samples (0.023 m 3 m -3 ). The uncertainty in determination of volumetric water content ( v ) was higher using the factory calibration (RMSD F ) in comparison to the laboratory calibration (RMSD L ) for the different soil structures and texture classes. In general, the uncertainty in estimation of soil water depth was greater than the uncertainty in estimation of soil water depletion by the sensors installed in the field, and the uncertainties in estimation of depth and depletion were lower using the calibration developed from the undisturbed soil samples. The undisturbed calibration of soil water depletion would determine water demand with better precision and potentially avoid over-watering, offering relief from water shortages. Further investigation of sensor calibration techniques is required to enhance the applicability of soil moisture sensors for efficient irrigation management.

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Section: Implications For Irrigation Managementsupporting

confidence: 86%

Section: Experiments Descriptionmentioning

confidence: 99%

Soil Structure and Texture Effects on the Precision of Soil Water Content Measurements with a Capacitance- Based Electromagnetic Sensor

Singh

Heeren²,

Rudnick³

et al. 2020

Transactions of the ASABE

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“…The water balance models required both field capacity (FC) and permanent wilting point (WP) for each plot. Plot FC was determined based on neutron probe readings (Lo et al, 2017, who cite Martin et al, 1990. Volumetric soil water content readings from June 30 and July 1, 2015, were used for this purpose for the 2015 season at Mead.…”

Section: Water Balance Models For Irrigation Schedulingmentioning

confidence: 99%

Evaluation of variable rate irrigation using a remote-sensing-based model

Barker

Heeren

Neale

et al. 2018

Agricultural Water Management

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Neale, Christopher M.U.; and Rudnick, Daran, "Evaluation of variable rate irrigation using a remote-sensing-based model" (2018). Biological Systems Engineering: Papers and Publications. 525. https://digitalcommons.unl.edu/biosysengfacpub/525 B a r k e r e t a l . i n A g r i c u l t u r a l W a t e r M a n a g e m e n t 2 0 3 ( 2 0 1 8 ) AbstractImprovements in soil water balance modeling can be beneficial for optimizing irrigation management to account for spatial variability in soil properties and evapotranspiration (ET). A remote-sensing-based ET and water balance model was tested for irrigation management in an experiment at two University of Nebraska-Lincoln research sites located near Mead and Brule, Nebraska. Both fields included a center pivot equipped with variable rate irrigation (VRI). The study included maize in 2015 and 2016 and soybean in 2016 at Mead, and maize in 2016 at Brule, for a total of 210 plot-years. Four irrigation treatments were applied at Mead, including: VRI based on a remote sensing model (VRI-RS); VRI based on neutron probe soil water content measurement (VRINP); uniform irrigation based on neutron probe measurement; and rainfed. Only the VRI-RS and uniform treatments were applied at Brule. Landsat 7 and 8 imagery were used for model input. In 2015, the remote sensing model included reflectance-based crop coefficients for ET estimation in the water balance. In 2016, a hybrid component of the model was activated, which included energy-balance-modeled ET as an input. Both 2015 and 2016 had above-average digitalcommons.unl.edu B a r k e r e t a l . i n A g r i c u l t u r a l W a t e r M a n a g e m e n t 2 0 3 ( 2 0 1 8 ) 2 precipitation at Mead; subsequently, irrigation amounts were relatively low. Seasonal irrigation was greatest for the VRI-RS treatment in all cases because of drift in the water balance model. This was likely caused by excessive soil evaporation estimates. Irrigation application for the VRI-NP at Mead was about 0 mm, 6 mm, and -12 mm less in separate analyses than for the uniform treatment. Irrigation for the VRIRS was about 40 mm, 50 mm, and -98 mm greater in separate analyses than the uniform at Mead and about 18mm greater at Brule. For maize at Mead, treatment effects were primarily limited to hydrologic responses (e.g., ET), with differences in yield generally attributed to random error. Rainfed soybean yields were greater than VRI-RS yields, which may have been related to yield loss from lodging, perhaps due to over-irrigation. Regarding the magnitude of spatial variability in the fields, soil available water capacity generally ranked above ET, precipitation, and yield. Future research should include increased cloud-free imagery frequency, incorporation of soil water content measurements into the model, and improved wet soil evaporation and drainage estimates.

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“…1, 2). The gSSURGO data were also used to develop R maps for the two study fields since R could be spatially estimated without the need for field data collection (Lo et al 2017). The gSSURGO data include AWC values for soil horizons, along with their depth.…”

Section: Development Of Root Zone Available Water Capacity Mapsmentioning

confidence: 99%

“…One necessity for writing a prescription map is defining IMZs. Of the different methods for delineating IMZs, a common one is based on observed changes in soil properties (Lo et al 2017). The range in R determines the number, size and distribution of IMZs (Daccache et al 2015).…”

Section: Introductionmentioning

confidence: 99%

A geospatial variable rate irrigation control scenario evaluation methodology based on mining root zone available water capacity

Miller¹,

Luck

Heeren

et al. 2017

Precision Agric

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Increasing concern for sustainable water use has the agriculture industry working toward higher efficiency in use of irrigation water. Recent advancements have improved the capabilities of center pivot irrigation systems to vary water application depths across the field, a technology known as variable rate irrigation (VRI). The goal of this study was to provide a geospatial method for potential VRI technology adopters to evaluate control scenarios and potential water savings using freely available datasets. Root zone available water capacity (R) was estimated spatially across two case study fields using the Natural Resources Conservation Service Gridded Soil Survey Geographic Database. The difference in application depth between conventional irrigation (CI) and both sector and zone control VRI was then estimated based on R. Prescription maps were developed to mine undepleted soil water from each irrigation management zone based on a soil water balance approach with a management-allowed depletion of 50%. For CI management, the areal 10th percentile (PCTL) of R for the field was used, while for VRI the 10th PCTL of R for each management zone was used. The highest reduction in irrigation depth was 18 mm where higher digitalcommons.unl.eduM i l l e r e t a l . i n P r e c i s i o n A g r i c u l t u r e , 2 0 1 7 2values of R were estimated; however, field average reductions ranged from 0 to 12 mm. The greatest improvements in pumpage reduction resulted from converting from sector control to zone control, while increasing the angular resolution only had a minor impact. Energy savings generally increased with higher VRI control resolution. Conclusions support previous notions that VRI may result in small pumping water reductions for some fields; however, improved water distribution may be achieved throughout the field.

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Field Characterization of Field Capacity and Root Zone Available Water Capacity for Variable Rate Irrigation

Cited by 35 publications

References 29 publications

Soil Structure and Texture Effects on the Precision of Soil Water Content Measurements with a Capacitance- Based Electromagnetic Sensor

Soil Structure and Texture Effects on the Precision of Soil Water Content Measurements with a Capacitance- Based Electromagnetic Sensor

Evaluation of variable rate irrigation using a remote-sensing-based model

A geospatial variable rate irrigation control scenario evaluation methodology based on mining root zone available water capacity

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