IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v273y2022ics0378377422004243.html
   My bibliography  Save this article

Site-specific irrigation scheduling using one-layer soil hydraulic properties and inverse modeling

Author

Listed:
  • Kumar, Hemendra
  • Srivastava, Puneet
  • Lamba, Jasmeet
  • Diamantopoulos, Efstathios
  • Ortiz, Brenda
  • Morata, Guilherme
  • Takhellambam, Bijoychandra
  • Bondesan, Luca

Abstract

Site-specific soil hydraulic properties (SHPs) are critical for determining irrigation thresholds and adopting the best irrigation practices. In this study, we optimized two single-layer SHPs for two management zones (namely, zone 1 and zone 2) delineated in a crop field using topographic attributes, soil texture, and historical crop yield to demonstrate the need for zone-specific SHPs. The inverse HYDRUS-1D model was used to optimize a single-layer zone-specific SHPs using multilayered observed soil water pressure heads (h) measured in both zones. Statistical indices for goodness of fit showed that a single layer SHPs simulate h during the growing season well. The irrigation thresholds and amounts determined using zone-specific optimized SHPs were used to trigger irrigations. Different irrigation scenarios using 15 cm, 30 cm, and 60 cm soil depths were developed using the zone-specific optimized SHPs in the HYDRUS-1D model to meet irrigation water demand and reduce water stress. The ratio of actual root water uptake (ARWU) and potential root water uptake (PRWU) were calculated to compare improvements in satisfying daily water demand and to reduce the water stress under different irrigation scenarios. Out of the total irrigation water triggered during growing seasons, greater than 61 % and 75 % in zone 1 was triggered in July 2018 and in May-June 2019, respectively. However, greater than 73 % in July 2018 and greater than 72 % in May-June 2019 were triggered in zone 2. Based on the simulations of various irrigation scenarios in HYDRUS-1D, we found that installing sensors at 15 cm or 30 cm can help meet the daily irrigation water demand on time than sensors at 60 cm depth. This study discussed the importance of critical water demands due to the distribution of precipitation over the growing season and need of zone-specific optimized SHPs for site-specific irrigation management within the field.

Suggested Citation

  • Kumar, Hemendra & Srivastava, Puneet & Lamba, Jasmeet & Diamantopoulos, Efstathios & Ortiz, Brenda & Morata, Guilherme & Takhellambam, Bijoychandra & Bondesan, Luca, 2022. "Site-specific irrigation scheduling using one-layer soil hydraulic properties and inverse modeling," Agricultural Water Management, Elsevier, vol. 273(C).
    • Handle: RePEc:eee:agiwat:v:273:y:2022:i:c:s0378377422004243
    DOI: 10.1016/j.agwat.2022.107877
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377422004243
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2022.107877?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. Lena, Bruno Patias & Bondesan, Luca & Pinheiro, Everton Alves Rodrigues & Ortiz, Brenda V. & Morata, Guilherme Trimer & Kumar, Hemendra, 2022. "Determination of irrigation scheduling thresholds based on HYDRUS-1D simulations of field capacity for multilayered agronomic soils in Alabama, USA," Agricultural Water Management, Elsevier, vol. 259(C).
    2. Wang, Jun & Huang, Guanhua & Li, Jiusheng & Zheng, Jianhua & Huang, Quanzhong & Liu, Haijun, 2017. "Effect of soil moisture-based furrow irrigation scheduling on melon (Cucumis melo L.) yield and quality in an arid region of Northwest China," Agricultural Water Management, Elsevier, vol. 179(C), pages 167-176.
    3. Libing Song & Jiming Jin & Jianqiang He, 2019. "Effects of Severe Water Stress on Maize Growth Processes in the Field," Sustainability, MDPI, vol. 11(18), pages 1-18, September.
    4. Ramos, T.B. & Gonalves, M.C. & Castanheira, N.L. & Martins, J.C. & Santos, F.L. & Prazeres, A. & Fernandes, M.L., 2009. "Effect of sodium and nitrogen on yield function of irrigated maize in southern Portugal," Agricultural Water Management, Elsevier, vol. 96(4), pages 585-594, April.
    5. Li, Yong & Šimůnek, Jirka & Jing, Longfei & Zhang, Zhentin & Ni, Lixiao, 2014. "Evaluation of water movement and water losses in a direct-seeded-rice field experiment using Hydrus-1D," Agricultural Water Management, Elsevier, vol. 142(C), pages 38-46.
    6. Yost, Jenifer L. & Huang, Jingyi & Hartemink, Alfred E., 2019. "Spatial-temporal analysis of soil water storage and deep drainage under irrigated potatoes in the Central Sands of Wisconsin, USA," Agricultural Water Management, Elsevier, vol. 217(C), pages 226-235.
    7. Liang, Xi & Liakos, Vasilis & Wendroth, Ole & Vellidis, George, 2016. "Scheduling irrigation using an approach based on the van Genuchten model," Agricultural Water Management, Elsevier, vol. 176(C), pages 170-179.
    8. Girona, J. & Mata, M. & Fereres, E. & Goldhamer, D. A. & Cohen, M., 2002. "Evapotranspiration and soil water dynamics of peach trees under water deficits," Agricultural Water Management, Elsevier, vol. 54(2), pages 107-122, March.
    9. Fontanet, Mireia & Scudiero, Elia & Skaggs, Todd H. & Fernàndez-Garcia, Daniel & Ferrer, Francesc & Rodrigo, Gema & Bellvert, Joaquim, 2020. "Dynamic Management Zones for Irrigation Scheduling," Agricultural Water Management, Elsevier, vol. 238(C).
    10. 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).
    11. Zhou, Hong & Zhao, Wen zhi, 2019. "Modeling soil water balance and irrigation strategies in a flood-irrigated wheat-maize rotation system. A case in dry climate, China," Agricultural Water Management, Elsevier, vol. 221(C), pages 286-302.
    12. Himanshu, Sushil Kumar & Fan, Yubing & Ale, Srinivasulu & Bordovsky, James, 2021. "Simulated efficient growth-stage-based deficit irrigation strategies for maximizing cotton yield, crop water productivity and net returns," Agricultural Water Management, Elsevier, vol. 250(C).
    13. Šimůnek, Jiří & Hopmans, Jan W., 2009. "Modeling compensated root water and nutrient uptake," Ecological Modelling, Elsevier, vol. 220(4), pages 505-521.
    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. Zhang, Junwei & Xiang, Lingxiao & Liu, Yuxin & Jing, Dan & Zhang, Lili & Liu, Yong & Li, Wuqiang & Wang, Xiaoyan & Li, Tianlai & Li, Jianming, 2024. "Optimizing irrigation schedules of greenhouse tomato based on a comprehensive evaluation model," Agricultural Water Management, Elsevier, vol. 295(C).
    2. Ramos, Tiago B. & Liu, Meihan & Paredes, Paula & Shi, Haibin & Feng, Zhuangzhuang & Lei, Huimin & Pereira, Luis S., 2023. "Salts dynamics in maize irrigation in the Hetao plateau using static water table lysimeters and HYDRUS-1D with focus on the autumn leaching irrigation," Agricultural Water Management, Elsevier, vol. 283(C).
    3. Kumar, Hemendra & Srivastava, Puneet & Lamba, Jasmeet & Lena, Bruno & Diamantopoulos, Efstathios & Ortiz, Brenda & Takhellambam, Bijoychandra & Morata, Guilherme & Bondesan, Luca, 2023. "A methodology to optimize site-specific field capacity and irrigation thresholds," Agricultural Water Management, Elsevier, vol. 286(C).
    4. Feng, Zhuangzhuang & Miao, Qingfeng & Shi, Haibin & Feng, Weiying & Li, Xianyue & Yan, Jianwen & Liu, Meihan & Sun, Wei & Dai, Liping & Liu, Jing, 2023. "Simulation of water balance and irrigation strategy of typical sand-layered farmland in the Hetao Irrigation District, China," Agricultural Water Management, Elsevier, vol. 280(C).

    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. Kumar, Hemendra & Srivastava, Puneet & Lamba, Jasmeet & Lena, Bruno & Diamantopoulos, Efstathios & Ortiz, Brenda & Takhellambam, Bijoychandra & Morata, Guilherme & Bondesan, Luca, 2023. "A methodology to optimize site-specific field capacity and irrigation thresholds," Agricultural Water Management, Elsevier, vol. 286(C).
    2. Li, Yong & Šimůnek, Jirka & Zhang, Zhentin & Jing, Longfei & Ni, Lixiao, 2015. "Evaluation of nitrogen balance in a direct-seeded-rice field experiment using Hydrus-1D," Agricultural Water Management, Elsevier, vol. 148(C), pages 213-222.
    3. Rosa, R.D. & Ramos, T.B. & Pereira, L.S., 2016. "The dual Kc approach to assess maize and sweet sorghum transpiration and soil evaporation under saline conditions: Application of the SIMDualKc model," Agricultural Water Management, Elsevier, vol. 177(C), pages 77-94.
    4. Feng, Zhuangzhuang & Miao, Qingfeng & Shi, Haibin & Feng, Weiying & Li, Xianyue & Yan, Jianwen & Liu, Meihan & Sun, Wei & Dai, Liping & Liu, Jing, 2023. "Simulation of water balance and irrigation strategy of typical sand-layered farmland in the Hetao Irrigation District, China," Agricultural Water Management, Elsevier, vol. 280(C).
    5. Lena, Bruno Patias & Bondesan, Luca & Pinheiro, Everton Alves Rodrigues & Ortiz, Brenda V. & Morata, Guilherme Trimer & Kumar, Hemendra, 2022. "Determination of irrigation scheduling thresholds based on HYDRUS-1D simulations of field capacity for multilayered agronomic soils in Alabama, USA," Agricultural Water Management, Elsevier, vol. 259(C).
    6. Azad, Nasrin & Behmanesh, Javad & Rezaverdinejad, Vahid & Abbasi, Fariborz & Navabian, Maryam, 2018. "Developing an optimization model in drip fertigation management to consider environmental issues and supply plant requirements," Agricultural Water Management, Elsevier, vol. 208(C), pages 344-356.
    7. Tenreiro, Tomás R. & García-Vila, Margarita & Gómez, José A. & Jimenez-Berni, José A. & Fereres, Elías, 2020. "Water modelling approaches and opportunities to simulate spatial water variations at crop field level," Agricultural Water Management, Elsevier, vol. 240(C).
    8. Li, Danfeng, 2020. "Quantifying water use and groundwater recharge under flood irrigation in an arid oasis of northwestern China," Agricultural Water Management, Elsevier, vol. 240(C).
    9. Shouse, Peter J. & Ayars, James E. & Simunek, Jirí, 2011. "Simulating root water uptake from a shallow saline groundwater resource," Agricultural Water Management, Elsevier, vol. 98(5), pages 784-790, March.
    10. Nandi, R. & Mondal, K. & Singh, K.C. & Saha, M. & Bandyopadhyay, P.K. & Ghosh, P.K., 2021. "Yield-water relationships of lentil grown under different rice establishments in Lower Gangetic Plain of India," Agricultural Water Management, Elsevier, vol. 246(C).
    11. Phogat, V. & Skewes, M.A. & Cox, J.W. & Alam, J. & Grigson, G. & Šimůnek, J., 2013. "Evaluation of water movement and nitrate dynamics in a lysimeter planted with an orange tree," Agricultural Water Management, Elsevier, vol. 127(C), pages 74-84.
    12. 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).
    13. Mompremier, R. & Her, Y. & Hoogenboom, G. & Migliaccio, K. & Muñoz-Carpena, R. & Brym, Z. & Colbert, R.W. & Jeune, W., 2021. "Modeling the response of dry bean yield to irrigation water availability controlled by watershed hydrology," Agricultural Water Management, Elsevier, vol. 243(C).
    14. Wang, Jianjun & Wang, Chuantao & Li, Hongchen & Liu, Yanfang & Li, Huijie & Ren, Ruiqi & Si, Bingcheng, 2023. "Rock water use by apple trees affected by physical properties of the underlying weathered rock," Agricultural Water Management, Elsevier, vol. 287(C).
    15. Imran Sajid & Bernhard Tischbein & Christian Borgemeister & Martina Flörke, 2022. "Assessing Barriers in Adaptation of Water Management Innovations under Rotational Canal Water Distribution System," Agriculture, MDPI, vol. 12(7), pages 1-16, June.
    16. Mubarak, Ibrahim & Mailhol, Jean Claude & Angulo-Jaramillo, Rafael & Bouarfa, Sami & Ruelle, Pierre, 2009. "Effect of temporal variability in soil hydraulic properties on simulated water transfer under high-frequency drip irrigation," Agricultural Water Management, Elsevier, vol. 96(11), pages 1547-1559, November.
    17. Yi, Jun & Li, Huijie & Zhao, Ying & Shao, Ming'an & Zhang, Hailin & Liu, Muxing, 2022. "Assessing soil water balance to optimize irrigation schedules of flood-irrigated maize fields with different cultivation histories in the arid region," Agricultural Water Management, Elsevier, vol. 265(C).
    18. Abrisqueta, I. & Vera, J. & Tapia, L.M. & Abrisqueta, J.M. & Ruiz-Sánchez, M.C., 2012. "Soil water content criteria for peach trees water stress detection during the postharvest period," Agricultural Water Management, Elsevier, vol. 104(C), pages 62-67.
    19. 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.
    20. Savé, R. & de Herralde, F. & Aranda, X. & Pla, E. & Pascual, D. & Funes, I. & Biel, C., 2012. "Potential changes in irrigation requirements and phenology of maize, apple trees and alfalfa under global change conditions in Fluvià watershed during XXIst century: Results from a modeling approximat," Agricultural Water Management, Elsevier, vol. 114(C), pages 78-87.

    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:273:y:2022:i:c:s0378377422004243. 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.