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Soil water sensing for water balance, ET and WUE

Author

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  • Evett, Steven R.
  • Schwartz, Robert C.
  • Casanova, Joaquin J.
  • Heng, Lee K.

Abstract

The soil water balance can be solved for evapotranspiration (ET) using soil water change in storage data from either weighing lysimetry or soil water sensing and measurement, along with data on the other components of the water balance. Weighing lysimeters are expensive and, although accurate, are difficult to manage and afford little replication. Direct soil water measurement by coring is accurate enough, but plagued by spatial variability that induces unwanted variability in the change in soil water storage between dates, and is destructive and time/labor consuming. Here we focus on soil water sensing using the neutron probe and various electromagnetic (EM) sensors (capacitance, time domain reflectometry (TDR) and quasi-TDR) with respect to the relative levels of uncertainty in profile water content, change in soil water storage, and estimates of deep flux; and their impact on estimated ET and water use efficiency (WUE). Studies consistently showed errors up to and >0.05m3m−3 for capacitance sensors used in access tubes, which implied errors in soil water flux estimation of up to 50mmday−1, and calibrations that were so sensitive to soil bulk electrical conductivity (σdc) and temperature that water content and change in storage estimates were rendered unreliable. Also, larger spatial variability of water contents reported by capacitance sensors was tied to the EM field penetration in structured soils around access tubes being non-uniform and influenced by the random arrangement of soil micro-scale water content, σdc and bulk density distribution. Thus, we recommend that profiling sensor systems based on capacitance technology not be used for studies of water balance, ET and WUE, nor for irrigation scheduling. Recommended methods include the neutron probe, direct volumetric soil sampling and, in some cases, conventional time domain reflectometry with waveform capture and analysis. New sensor development efforts should focus on waveguide approaches using TDR technology.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:agiwat:v:104:y:2012:i:c:p:1-9
    DOI: 10.1016/j.agwat.2011.12.002
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    Citations

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    Cited by:

    1. Vinod Phogat & Jirka Šimůnek & Paul Petrie & Tim Pitt & Vilim Filipović, 2023. "Sustainability of a Rainfed Wheat Production System in Relation to Water and Nitrogen Dynamics in the Soil in the Eyre Peninsula, South Australia," Sustainability, MDPI, vol. 15(18), pages 1-22, September.
    2. Liu, Yutong & Lu, Yili & Sadeghi, Morteza & Horton, Robert & Ren, Tusheng, 2024. "Measurement and estimation of evapotranspiration in a maize field: A new method based on an analytical water flux model," Agricultural Water Management, Elsevier, vol. 295(C).
    3. Vinod Phogat & Tim Pitt & Paul Petrie & Jirka Šimůnek & Michael Cutting, 2023. "Optimization of Irrigation of Wine Grapes with Brackish Water for Managing Soil Salinization," Land, MDPI, vol. 12(10), pages 1-29, October.
    4. 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.
    5. Reinhard NOLZ & Willibald LOISKANDL, 2017. "Evaluating soil water content data monitored at different locations in a vineyard with regard to irrigation control," Soil and Water Research, Czech Academy of Agricultural Sciences, vol. 12(3), pages 152-160.
    6. 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.
    7. Phogat, V. & Pitt, T. & Cox, J.W. & Šimůnek, J. & Skewes, M.A., 2018. "Soil water and salinity dynamics under sprinkler irrigated almond exposed to a varied salinity stress at different growth stages," Agricultural Water Management, Elsevier, vol. 201(C), pages 70-82.
    8. Sun, Libo & Chang, Xiaomin & Yu, Xinxiao & Jia, Guodong & Chen, Lihua & Wang, Yusong & Liu, Ziqiang, 2021. "Effect of freeze-thaw processes on soil water transport of farmland in a semi-arid area," Agricultural Water Management, Elsevier, vol. 252(C).
    9. Hunsaker, D.J. & French, A.N. & Waller, P.M. & Bautista, E. & Thorp, K.R. & Bronson, K.F. & Andrade-Sanchez, P., 2015. "Comparison of traditional and ET-based irrigation scheduling of surface-irrigated cotton in the arid southwestern USA," Agricultural Water Management, Elsevier, vol. 159(C), pages 209-224.
    10. Datta, Sumon & Taghvaeian, Saleh, 2023. "Soil water sensors for irrigation scheduling in the United States: A systematic review of literature," Agricultural Water Management, Elsevier, vol. 278(C).
    11. 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).
    12. Zhang, Rui & Zhu, Miyuan & Mady, Ahmed Yehia & Huang, Mingbin & Yan, Xiaoying & Guo, Tianqi, 2024. "Effects of different long-term fertilization and cropping systems on crop yield, water balance components and water productivity in dryland farming," Agricultural Water Management, Elsevier, vol. 292(C).
    13. 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).
    14. Li, Jiang & Wang, Xinxin & Bai, Liangliang & Mao, Xiaomin, 2017. "Quantification of lateral seepage from farmland during maize growing season in arid region," Agricultural Water Management, Elsevier, vol. 191(C), pages 85-97.
    15. Rallo, G. & Paço, T.A. & Paredes, P. & Puig-Sirera, À. & Massai, R. & Provenzano, G. & Pereira, L.S., 2021. "Updated single and dual crop coefficients for tree and vine fruit crops," Agricultural Water Management, Elsevier, vol. 250(C).
    16. 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).
    17. 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).
    18. Iftikhar Ahmed Saeed & Wang Minjuan & Ji Qiang & Shi Qinglan & Zheng Li Hua & Liu Xinliang & Gao Wanlin, 2024. "Integrated Sensor for Estimating in situ Soil Water Content in Vertical Profile," Journal of Agricultural Science, Canadian Center of Science and Education, vol. 10(10), pages 1-53, April.
    19. Alcaras, L. Martín Agüero & Rousseaux, M. Cecilia & Searles, Peter S., 2016. "Responses of several soil and plant indicators to post-harvest regulated deficit irrigation in olive trees and their potential for irrigation scheduling," Agricultural Water Management, Elsevier, vol. 171(C), pages 10-20.
    20. Dietrich, Ottfried & Steidl, Jörg, 2021. "Field calibrations of a Diviner 2000 capacitive soil water content probe on a shallow groundwater site and the application in a weighable groundwater lysimeter," Agricultural Water Management, Elsevier, vol. 252(C).
    21. Esmaili, Maryam & Aliniaeifard, Sasan & Mashal, Mahmoud & Vakilian, Keyvan Asefpour & Ghorbanzadeh, Parisa & Azadegan, Behzad & Seif, Mehdi & Didaran, Fardad, 2021. "Assessment of adaptive neuro-fuzzy inference system (ANFIS) to predict production and water productivity of lettuce in response to different light intensities and CO2 concentrations," Agricultural Water Management, Elsevier, vol. 258(C).
    22. Pereira, L.S. & Paredes, P. & López-Urrea, R. & Hunsaker, D.J. & Mota, M. & Mohammadi Shad, Z., 2021. "Standard single and basal crop coefficients for vegetable crops, an update of FAO56 crop water requirements approach," Agricultural Water Management, Elsevier, vol. 243(C).
    23. Serra-Wittling, Claire & Molle, Bruno & Cheviron, Bruno, 2019. "Plot level assessment of irrigation water savings due to the shift from sprinkler to localized irrigation systems or to the use of soil hydric status probes. Application in the French context," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.

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