IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v96y2009i12p1737-1745.html
   My bibliography  Save this article

A method for spatial prediction of daily soil water status for precise irrigation scheduling

Author

Listed:
  • Hedley, C.B.
  • Yule, I.J.

Abstract

Available water holding capacity (AWC) and field capacity (FC) maps have been produced using regression models of high resolution apparent electrical conductivity (ECa) data against AWC (adj. R2=0.76) and FC (adj. R2=0.77). A daily time step has been added to field capacity maps to spatially predict soil water status on any day using data obtained from a wireless soil moisture sensing network which transmitted hourly logged data from embedded time domain transmission (TDT) sensors in ECa-defined management zones. In addition, regular time domain reflectometry (TDR) monitoring of 50 positions in the study area was used to assess spatial variability within each zone and overall temporal stability of soil moisture patterns. Spatial variability of soil moisture within each zone at any one time was significant (coefficient of variation [% CV] of volumetric soil moisture content ([theta])=3-16%), while temporal stability of this pattern was moderate to strong (bivariate correlation, R=0.52-0.95), suggesting an intrinsic soil and topographic control. Therefore, predictive ability of this method for spatial characterisation of soil water status, at this site, was limited by the ability of the sensor network to account for the spatial variability of the soil moisture pattern within each zone. Significant variability of soil moisture within each ECa-defined zone is thought to be due to the variable nature of the young alluvial soils at this site, as well as micro-topographic effects on water movement, such as low-lying ponding areas. In summary, this paper develops a method for predicting daily soil water status in ECa-defined zones; digital information available for uploading to a software-controlled automated variable rate irrigation system with the aim of improved water use efficiency. Accuracy of prediction is determined by the extent to which spatial variability is predicted within as well as between ECa-defined zones.

Suggested Citation

  • Hedley, C.B. & Yule, I.J., 2009. "A method for spatial prediction of daily soil water status for precise irrigation scheduling," Agricultural Water Management, Elsevier, vol. 96(12), pages 1737-1745, December.
    • Handle: RePEc:eee:agiwat:v:96:y:2009:i:12:p:1737-1745
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378-3774(09)00207-8
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Green, Steve R. & Kirkham, M.B. & Clothier, Brent E., 2006. "Root uptake and transpiration: From measurements and models to sustainable irrigation," Agricultural Water Management, Elsevier, vol. 86(1-2), pages 165-176, November.
    2. Thompson, R.B. & Gallardo, M. & Valdez, L.C. & Fernandez, M.D., 2007. "Determination of lower limits for irrigation management using in situ assessments of apparent crop water uptake made with volumetric soil water content sensors," Agricultural Water Management, Elsevier, vol. 92(1-2), pages 13-28, August.
    3. Blonquist, J.M. Jr. & Jones, S.B. & Robinson, D.A., 2006. "Precise irrigation scheduling for turfgrass using a subsurface electromagnetic soil moisture sensor," Agricultural Water Management, Elsevier, vol. 84(1-2), pages 153-165, July.
    4. Starr, G.C., 2005. "Assessing temporal stability and spatial variability of soil water patterns with implications for precision water management," Agricultural Water Management, Elsevier, vol. 72(3), pages 223-243, April.
    5. DeJonge, Kendall C. & Kaleita, Amy L. & Thorp, Kelly R., 2007. "Simulating the effects of spatially variable irrigation on corn yields, costs, and revenue in Iowa," Agricultural Water Management, Elsevier, vol. 92(1-2), pages 99-109, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bhatti, Sandeep & Heeren, Derek M. & Barker, J. Burdette & Neale, Christopher M.U. & Woldt, Wayne E. & Maguire, Mitchell S. & Rudnick, Daran R., 2020. "Site-specific irrigation management in a sub-humid climate using a spatial evapotranspiration model with satellite and airborne imagery," Agricultural Water Management, Elsevier, vol. 230(C).
    2. Fernández-Pacheco, D.G. & Ferrández-Villena, M. & Molina-Martínez, J.M. & Ruiz-Canales, A., 2015. "Performance indicators to assess the implementation of automation in water user associations: A case study in southeast Spain," Agricultural Water Management, Elsevier, vol. 151(C), pages 87-92.
    3. El-Naggar, A.G. & Hedley, C.B. & Horne, D. & Roudier, P. & Clothier, B.E., 2020. "Soil sensing technology improves application of irrigation water," Agricultural Water Management, Elsevier, vol. 228(C).
    4. López, Juan A. & Navarro, H. & Soto, F. & Pavón, N. & Suardíaz, J. & Torres, R., 2015. "GAIA2: A multifunctional wireless device for enhancing crop management," Agricultural Water Management, Elsevier, vol. 151(C), pages 75-86.
    5. Beeson Jr., R.C., 2011. "Weighing lysimeter systems for quantifying water use and studies of controlled water stress for crops grown in low bulk density substrates," Agricultural Water Management, Elsevier, vol. 98(6), pages 967-976, April.
    6. Imran Ali Lakhiar & Haofang Yan & Chuan Zhang & Guoqing Wang & Bin He & Beibei Hao & Yujing Han & Biyu Wang & Rongxuan Bao & Tabinda Naz Syed & Junaid Nawaz Chauhdary & Md. Rakibuzzaman, 2024. "A Review of Precision Irrigation Water-Saving Technology under Changing Climate for Enhancing Water Use Efficiency, Crop Yield, and Environmental Footprints," Agriculture, MDPI, vol. 14(7), pages 1-40, July.
    7. 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.
    8. Olutobi Adeyemi & Ivan Grove & Sven Peets & Tomas Norton, 2017. "Advanced Monitoring and Management Systems for Improving Sustainability in Precision Irrigation," Sustainability, MDPI, vol. 9(3), pages 1-29, February.

    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. Starr, G.C. & Rowland, D. & Griffin, T.S. & Olanya, O.M., 2008. "Soil water in relation to irrigation, water uptake and potato yield in a humid climate," Agricultural Water Management, Elsevier, vol. 95(3), pages 292-300, March.
    2. Nolz, R. & Cepuder, P. & Balas, J. & Loiskandl, W., 2016. "Soil water monitoring in a vineyard and assessment of unsaturated hydraulic parameters as thresholds for irrigation management," Agricultural Water Management, Elsevier, vol. 164(P2), pages 235-242.
    3. Zhou, Zhenjiang & Plauborg, Finn & Parsons, David & Andersen, Mathias Neumann, 2018. "Potato canopy growth, yield and soil water dynamics under different irrigation systems," Agricultural Water Management, Elsevier, vol. 202(C), pages 9-18.
    4. Gao, Lei & Shao, Mingan, 2012. "Temporal stability of shallow soil water content for three adjacent transects on a hillslope," Agricultural Water Management, Elsevier, vol. 110(C), pages 41-54.
    5. Janik, Grzegorz & Kłosowicz, Izabela & Walczak, Amadeusz & Adamczewska-Sowińska, Katarzyna & Jama-Rodzeńska, Anna & Sowiński, Józef, 2021. "Application of the TDR technique for the determination of the dynamics of the spatial and temporal distribution of water uptake by plant roots during injection irrigation," Agricultural Water Management, Elsevier, vol. 252(C).
    6. Margarita A. Petoussi & Nicolas Kalogerakis, 2023. "Mathematical Modeling of Pilot Scale Olive Mill Wastewater Phytoremediation Units," Sustainability, MDPI, vol. 15(11), pages 1-36, May.
    7. Fabio V. Difonzo & Costantino Masciopinto & Michele Vurro & Marco Berardi, 2021. "Shooting the Numerical Solution of Moisture Flow Equation with Root Water Uptake Models: A Python Tool," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(8), pages 2553-2567, June.
    8. 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.
    9. Cai, Fu & Zhang, Yushu & Mi, Na & Ming, Huiqing & Zhang, Shujie & Zhang, Hui & Zhao, Xianli, 2020. "Maize (Zea mays L.) physiological responses to drought and rewatering, and the associations with water stress degree," Agricultural Water Management, Elsevier, vol. 241(C).
    10. Lo, Tsz Him & Rudnick, Daran R. & Singh, Jasreman & Nakabuye, Hope Njuki & Katimbo, Abia & Heeren, Derek M. & Ge, Yufeng, 2020. "Field assessment of interreplicate variability from eight electromagnetic soil moisture sensors," Agricultural Water Management, Elsevier, vol. 231(C).
    11. Sharma, Vasudha & Irmak, Suat, 2020. "Economic comparisons of variable rate irrigation and fertigation with fixed (uniform) rate irrigation and fertigation and pre-plant fertilizer management for maize in three soils," Agricultural Water Management, Elsevier, vol. 240(C).
    12. Kelly, T.D. & Foster, T., 2021. "AquaCrop-OSPy: Bridging the gap between research and practice in crop-water modeling," Agricultural Water Management, Elsevier, vol. 254(C).
    13. de Souza, Edivan Rodrigues & Montenegro, Abelardo Antônio de Assunção & Montenegro, Suzana Maria Gico & de Matos, José de Arimatea, 2011. "Temporal stability of soil moisture in irrigated carrot crops in Northeast Brazil," Agricultural Water Management, Elsevier, vol. 99(1), pages 26-32.
    14. Li, Yi-Jie & Yuan, Bao-Zhong & Bie, Zhi-Long & Kang, Yaohu, 2012. "Effect of drip irrigation criteria on yield and quality of muskmelon grown in greenhouse conditions," Agricultural Water Management, Elsevier, vol. 109(C), pages 30-35.
    15. Jia, Xucun & Shao, Lijie & Liu, Peng & Zhao, Bingqiang & Gu, Limin & Dong, Shuting & Bing, So Hwat & Zhang, Jiwang & Zhao, Bin, 2014. "Effect of different nitrogen and irrigation treatments on yield and nitrate leaching of summer maize (Zea mays L.) under lysimeter conditions," Agricultural Water Management, Elsevier, vol. 137(C), pages 92-103.
    16. Boyer, Christopher N. & Larson, James A. & Roberts, Roland K. & McClure, Angela T. & Tyler, Donald D., 2014. "The impact of field size and energy cost on the profitability of supplemental corn irrigation," Agricultural Systems, Elsevier, vol. 127(C), pages 61-69.
    17. Jia, Yu-Hua & Shao, Ming-An, 2013. "Temporal stability of soil water storage under four types of revegetation on the northern Loess Plateau of China," Agricultural Water Management, Elsevier, vol. 117(C), pages 33-42.
    18. Snyder, R.L. & Pedras, C. & Montazar, A. & Henry, J.M. & Ackley, D., 2015. "Advances in ET-based landscape irrigation management," Agricultural Water Management, Elsevier, vol. 147(C), pages 187-197.
    19. Olutobi Adeyemi & Ivan Grove & Sven Peets & Tomas Norton, 2017. "Advanced Monitoring and Management Systems for Improving Sustainability in Precision Irrigation," Sustainability, MDPI, vol. 9(3), pages 1-29, February.
    20. Hou, Lizhu & Wenninger, Jochen & Shen, Jiangen & Zhou, Yangxiao & Bao, Han & Liu, Haijun, 2014. "Assessing crop coefficients for Zea mays in the semi-arid Hailiutu River catchment, northwest China," Agricultural Water Management, Elsevier, vol. 140(C), pages 37-47.

    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:96:y:2009:i:12:p:1737-1745. 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.