IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v243y2021ics0378377420310829.html
   My bibliography  Save this article

Propagation of soil moisture sensing uncertainty into estimation of total soil water, evapotranspiration and irrigation decision-making

Author

Listed:
  • Sharma, Kiran
  • Irmak, Suat
  • Kukal, Meetpal S.

Abstract

Soil moisture sensors are subject to uncertainty (inaccuracy) in measuring soil water status, that hinders various applications. User groups (researchers and growers/advisers) rely on these sensors for estimating critical agricultural water management decisions and information such as total soil water in the crop root zone (TSW), crop evapotranspiration (ETc) and predicting irrigation triggers (IT), i.e., when TSW is equal to or lower than readily available water. There is a lack of translation of errors in sensor-reported soil moisture (θv) into TSW, ETc, and IT, which is critical to farm-level decision-making as well as research assessments. Nine soil moisture sensors (based on principles of time-domain reflectometry, capacitance and electrical resistance) were investigated in field conditions for silt loam and loamy sand soils under two installation orientations (vertical and horizontal) during two growing seasons (2017 and 2018). Accurate representation of TSW, ETc, and IT was found to be a function of sensor-type, soil-type as well as calibration-type [factory calibration (F.C.) vs. site-specific calibration (S.S.C.)]. Sensor installation orientation did not affect sensor accuracy. Uncertainties in estimation of TSW, ETc and IT were quantified under each condition of use, and sensors were comparatively ranked for effective selection. It was found that all sensors underestimated ETc in silt loam soil. The deviation of sensor-measured ETc from true ETc ranged from −14 to −31 %, which implies that the choice of sensor under a given soil type impacts the quantification of consumptive use of the soil-vegetation system being monitored. Sensors showed both overstimation and underestimation of ETc in loamy sand soil with deviations of sensor-estimated ETc from true ETc ranging from 14 to −61 %. The S.S.C. resulted in 45 and 17 % improvement in TSW and ETc in silt loam soil, respectively, and 42, 80 and 86 % improvement observed in TSW, IT and ETc in loamy sand soil, respectively. The research findings showed that suitability of soil moisture sensors can differ when different target metrics are used as criteria. These findings emphasize the need for evaluating soil moisture sensors based on practical and application-oriented criteria, in addition to reliance on θv accuracy. To the best of authors’ knowledge, this research is the first to translate traditional θv accuracy assessments into practical and application-oriented criteria and use them to evaluate sensors for these specific applications. Sensor rankings and uncertainty associated with their use presented here will allow diverse users to effectively identify sensors for targeted applications in water management decision-making and research.

Suggested Citation

  • Sharma, Kiran & Irmak, Suat & Kukal, Meetpal S., 2021. "Propagation of soil moisture sensing uncertainty into estimation of total soil water, evapotranspiration and irrigation decision-making," Agricultural Water Management, Elsevier, vol. 243(C).
    • Handle: RePEc:eee:agiwat:v:243:y:2021:i:c:s0378377420310829
    DOI: 10.1016/j.agwat.2020.106454
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377420310829
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2020.106454?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kukal, M.S. & Irmak, S., 2020. "Characterization of water use and productivity dynamics across four C3 and C4 row crops under optimal growth conditions," Agricultural Water Management, Elsevier, vol. 227(C).
    2. Payero, J.O. & Tarkalson, D.D. & Irmak, S. & Davison, D. & Petersen, J.L., 2009. "Effect of timing of a deficit-irrigation allocation on corn evapotranspiration, yield, water use efficiency and dry mass," Agricultural Water Management, Elsevier, vol. 96(10), pages 1387-1397, October.
    3. Evett, Steven R. & Schwartz, Robert C. & Casanova, Joaquin J. & Heng, Lee K., 2012. "Soil water sensing for water balance, ET and WUE," Agricultural Water Management, Elsevier, vol. 104(C), pages 1-9.
    4. Varble, J.L. & Chávez, J.L., 2011. "Performance evaluation and calibration of soil water content and potential sensors for agricultural soils in eastern Colorado," Agricultural Water Management, Elsevier, vol. 101(1), pages 93-106.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kukal, M.S. & Irmak, S., 2020. "Impact of irrigation on interannual variability in United States agricultural productivity," Agricultural Water Management, Elsevier, vol. 234(C).
    2. Nakabuye, Hope Njuki & Rudnick, Daran & DeJonge, Kendall C. & Lo, Tsz Him & Heeren, Derek & Qiao, Xin & Franz, Trenton E. & Katimbo, Abia & Duan, Jiaming, 2022. "Real-time irrigation scheduling of maize using Degrees Above Non-Stressed (DANS) index in semi-arid environment," Agricultural Water Management, Elsevier, vol. 274(C).
    3. Phogat, V. & Skewes, M.A. & McCarthy, M.G. & Cox, J.W. & Šimůnek, J. & Petrie, P.R., 2017. "Evaluation of crop coefficients, water productivity, and water balance components for wine grapes irrigated at different deficit levels by a sub-surface drip," Agricultural Water Management, Elsevier, vol. 180(PA), pages 22-34.
    4. Motazedian, Azam & Kazemeini, Seyed Abdolreza & Bahrani, Mohammad Jafar, 2019. "Sweet corn growth and GrainYield as influenced by irrigation and wheat residue management," Agricultural Water Management, Elsevier, vol. 224(C), pages 1-1.
    5. Murley, Cameron B. & Sharma, Sumit & Warren, Jason G. & Arnall, Daryl B. & Raun, William R., 2018. "Yield response of corn and grain sorghum to row offsets on subsurface drip laterals," Agricultural Water Management, Elsevier, vol. 208(C), pages 357-362.
    6. Comas, Louise H. & Trout, Thomas J. & DeJonge, Kendall C. & Zhang, Huihui & Gleason, Sean M., 2019. "Water productivity under strategic growth stage-based deficit irrigation in maize," Agricultural Water Management, Elsevier, vol. 212(C), pages 433-440.
    7. Tarkalson, David D. & King, Bradley A. & Bjorneberg, Dave L., 2022. "Maize grain yield and crop water productivity functions in the arid Northwest U.S," Agricultural Water Management, Elsevier, vol. 264(C).
    8. Sandhu, Rupinder & Irmak, Suat, 2022. "Effects of subsurface drip-irrigated soybean seeding rates on grain yield, evapotranspiration and water productivity under limited and full irrigation and rainfed conditions," Agricultural Water Management, Elsevier, vol. 267(C).
    9. Lankford, Bruce, 2012. "Fictions, fractions, factorials and fractures; on the framing of irrigation efficiency," Agricultural Water Management, Elsevier, vol. 108(C), pages 27-38.
    10. Mukherjee, A. & Kundu, M. & Sarkar, S., 2010. "Role of irrigation and mulch on yield, evapotranspiration rate and water use pattern of tomato (Lycopersicon esculentum L.)," Agricultural Water Management, Elsevier, vol. 98(1), pages 182-189, December.
    11. Zou, Haiyang & Fan, Junliang & Zhang, Fucang & Xiang, Youzhen & Wu, Lifeng & Yan, Shicheng, 2020. "Optimization of drip irrigation and fertilization regimes for high grain yield, crop water productivity and economic benefits of spring maize in Northwest China," Agricultural Water Management, Elsevier, vol. 230(C).
    12. Reinhard NOLZ & Willibald LOISKANDL & Gerhard KAMMERER & Margarita L. HIMMELBAUER, 2016. "Survey of soil water distribution in a vineyard and implications for subsurface drip irrigation control," Soil and Water Research, Czech Academy of Agricultural Sciences, vol. 11(4), pages 250-258.
    13. Srinivasan, M.S. & Measures, Richard & Muller, Carla & Neal, Mark & Rajanayaka, Channa & Shankar, Ude & Elley, Graham, 2021. "Comparing the water use metrics of just-in-case, just-in-time and justified irrigation strategies using a scenario-based tool," Agricultural Water Management, Elsevier, vol. 258(C).
    14. Pereira, L.S. & Paredes, P. & Hunsaker, D.J. & López-Urrea, R. & Mohammadi Shad, Z., 2021. "Standard single and basal crop coefficients for field crops. Updates and advances to the FAO56 crop water requirements method," Agricultural Water Management, Elsevier, vol. 243(C).
    15. Pascual-Seva, Núria & San Bautista, Alberto & López-Galarza, Salvador & Maroto, José Vicente & Pascual, Bernardo, 2018. "Influence of different drip irrigation strategies on irrigation water use efficiency on chufa (Cyperus esculentus L. var. sativus Boeck.) crop," Agricultural Water Management, Elsevier, vol. 208(C), pages 406-413.
    16. Kukal, M.S. & Irmak, S., 2020. "Characterization of water use and productivity dynamics across four C3 and C4 row crops under optimal growth conditions," Agricultural Water Management, Elsevier, vol. 227(C).
    17. Rudnick, D.R. & Irmak, S. & Djaman, K. & Sharma, V., 2017. "Impact of irrigation and nitrogen fertilizer rate on soil water trends and maize evapotranspiration during the vegetative and reproductive periods," Agricultural Water Management, Elsevier, vol. 191(C), pages 77-84.
    18. Zhang, Yan & Ma, Qian & Liu, Donghua & Sun, Lefeng & Ren, Xiaolong & Ali, Shahzad & Zhang, Peng & Jia, Zhikuan, 2018. "Effects of different fertilizer strategies on soil water utilization and maize yield in the ridge and furrow rainfall harvesting system in semiarid regions of China," Agricultural Water Management, Elsevier, vol. 208(C), pages 414-421.
    19. Katimbo, Abia & Rudnick, Daran R. & DeJonge, Kendall C. & Lo, Tsz Him & Qiao, Xin & Franz, Trenton E. & Nakabuye, Hope Njuki & Duan, Jiaming, 2022. "Crop water stress index computation approaches and their sensitivity to soil water dynamics," Agricultural Water Management, Elsevier, vol. 266(C).
    20. Katimbo, Abia & Rudnick, Daran R. & Liang, Wei-zhen & DeJonge, Kendall C. & Lo, Tsz Him & Franz, Trenton E. & Ge, Yufeng & Qiao, Xin & Kabenge, Isa & Nakabuye, Hope Njuki & Duan, Jiaming, 2022. "Two source energy balance maize evapotranspiration estimates using close-canopy mobile infrared sensors and upscaling methods under variable water stress conditions," Agricultural Water Management, Elsevier, vol. 274(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agiwat:v:243:y:2021:i:c:s0378377420310829. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agwat .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.