IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v238y2020ics0378377419318281.html
   My bibliography  Save this article

Impact of regional characteristics on the estimation of root-zone soil moisture from the evaporative index or evaporative fraction

Author

Listed:
  • Sahaar, Shukran A.
  • Niemann, Jeffrey D.

Abstract

Accurate knowledge of root-zone soil moisture is of vital significance to many applications in agriculture, such as crop yield estimation, precision irrigation, salinity and groundwater management. Remote-sensing methods based on optical and thermal satellite imagery have been proposed to estimate fine-resolution (30 m grid cells) maps of root-zone soil moisture θ¯ or degree of saturation s¯ over large regions. These methods usually calculate the evaporative fraction ΛSEB as the ratio of the latent heat flux to the difference of the net radiation and ground heat flux. Then, they estimate θ¯ or s¯ from an empirical relationship with ΛSEB. A similar approach estimates θ¯ or s¯ using the evaporative index ΛPET, which is the ratio of the actual to potential evapotranspiration. However, previous research has shown that a single relationship between either θ¯ or s¯ and ΛSEB does not apply to all regions. The objective of this study is to evaluate the impact of regional soil, vegetation, and climatic conditions on the form and strength of the ΛSEB−θ¯, ΛPET−θ¯, ΛSEB−s¯, and ΛPET−s¯ relationships. To accomplish this goal, Extended Fourier Amplitude Sensitivity Test (eFAST) is applied to a physically-based model (HYDRUS 1-D) that simulates both evapotranspiration and soil moisture dynamics. The sensitivity results show that, within a given climatic region, soil characteristics such as the percent clay and percent silt are most important in determining the shape of the relationships, while vegetation characteristics such as leaf area index and maximum rooting depth have the greatest effect on the strength of these relationships. The total annual precipitation, which helps determine the climatic region, also has a strong effect on both the form and strength of the relationships. The parameters that define the ΛSEB−θ¯ and ΛPET−θ¯ relationships are also estimated using the regional characteristics. Estimating the parameters in this way allows the methods to be adapted to local conditions and has the potential to improve the θ¯ and s¯ estimates.

Suggested Citation

  • Sahaar, Shukran A. & Niemann, Jeffrey D., 2020. "Impact of regional characteristics on the estimation of root-zone soil moisture from the evaporative index or evaporative fraction," Agricultural Water Management, Elsevier, vol. 238(C).
  • Handle: RePEc:eee:agiwat:v:238:y:2020:i:c:s0378377419318281
    DOI: 10.1016/j.agwat.2020.106225
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377419318281
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.agwat.2020.106225?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. Bastiaanssen, Wim G. M. & Molden, David J. & Makin, Ian W., 2000. "Remote sensing for irrigated agriculture: examples from research and possible applications," Agricultural Water Management, Elsevier, vol. 46(2), pages 137-155, December.
    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. Zhu, Pingzong & Zhang, Guanghui & Wang, Hongxiao & Zhang, Baojun & Liu, Yingna, 2021. "Soil moisture variations in response to precipitation properties and plant communities on steep gully slope on the Loess Plateau," Agricultural Water Management, Elsevier, vol. 256(C).
    2. Weiying Feng & Jiayue Gao & Rui Cen & Fang Yang & Zhongqi He & Jin Wu & Qingfeng Miao & Haiqing Liao, 2020. "Effects of Polyacrylamide-Based Super Absorbent Polymer and Corn Straw Biochar on the Arid and Semi-Arid Salinized Soil," Agriculture, MDPI, vol. 10(11), pages 1-17, November.

    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. Bipul Neupane & Teerayut Horanont & Nguyen Duy Hung, 2019. "Deep learning based banana plant detection and counting using high-resolution red-green-blue (RGB) images collected from unmanned aerial vehicle (UAV)," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-22, October.
    2. Anna‐Katharina Hornidge & Lisa Oberkircher & Bernhard Tischbein & Gunther Schorcht & Anik Bhaduri & Ahmad M. Manschadi, 2011. "Reconceptualizing water management in Khorezm, Uzbekistan," Natural Resources Forum, Blackwell Publishing, vol. 35(4), pages 251-268, November.
    3. Corbari, Chiara & Paciolla, Nicola & Rossi, Greta & Mancini, Marco, 2023. "A double two-sources energy-water balance model for improving evapotranspiration estimates and irrigation management in fruit trees fields," Agricultural Water Management, Elsevier, vol. 289(C).
    4. Singh, Ajay, 2016. "Managing the water resources problems of irrigated agriculture through geospatial techniques: An overview," Agricultural Water Management, Elsevier, vol. 174(C), pages 2-10.
    5. van Opstal, Jonna D. & Neale, Christopher M.U. & Hipps, Lawrence E., 2022. "Evaluating the adaptability of an irrigation district to seasonal water availability using a decade of remotely sensed evapotranspiration estimates," Agricultural Water Management, Elsevier, vol. 261(C).
    6. Martin de Santa Olalla, F. & Calera, A. & Dominguez, A., 2003. "Monitoring irrigation water use by combining Irrigation Advisory Service, and remotely sensed data with a geographic information system," Agricultural Water Management, Elsevier, vol. 61(2), pages 111-124, June.
    7. Bastiaanssen, W. G. M. & Chandrapala, L., 2003. "Water balance variability across Sri Lanka for assessing agricultural and environmental water use," Agricultural Water Management, Elsevier, vol. 58(2), pages 171-192, February.
    8. Corbari, Chiara & Salerno, Raffaele & Ceppi, Alessandro & Telesca, Vito & Mancini, Marco, 2019. "Smart irrigation forecast using satellite LANDSAT data and meteo-hydrological modeling," Agricultural Water Management, Elsevier, vol. 212(C), pages 283-294.
    9. Muhammad Usman & Talha Mahmood & Christopher Conrad & Habib Ullah Bodla, 2020. "Remote Sensing and Modelling Based Framework for Valuing Irrigation System Efficiency and Steering Indicators of Consumptive Water Use in an Irrigated Region," Sustainability, MDPI, vol. 12(22), pages 1-33, November.
    10. Margaret Yejide Onanuga & Adebayo Oluwole Eludoyin & Ifeanyi Emmanuel Ofoezie, 2022. "Urbanization and its effects on land and water resources in Ijebuland, southwestern Nigeria," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(1), pages 592-616, January.
    11. Karatas, Bekir S. & Akkuzu, Erhan & Unal, Halil B. & Asik, Serafettin & Avci, Musa, 2009. "Using satellite remote sensing to assess irrigation performance in Water User Associations in the Lower Gediz Basin, Turkey," Agricultural Water Management, Elsevier, vol. 96(6), pages 982-990, June.
    12. Yongqing Zhao & Rendong Li & Juan Qiu & Xiangdong Sun & Lu Gao & Mingquan Wu, 2019. "Prediction of Human Brucellosis in China Based on Temperature and NDVI," IJERPH, MDPI, vol. 16(21), pages 1-15, November.
    13. Ajaz, Ali, 2016. "Analyzing Growth-Track and Uncertainties in Asia’s Irrigated Areas," OSF Preprints mbpk2, Center for Open Science.
    14. Consoli, Simona & D'Urso, Guido & Toscano, Attilio, 2006. "Remote sensing to estimate ET-fluxes and the performance of an irrigation district in southern Italy," Agricultural Water Management, Elsevier, vol. 81(3), pages 295-314, March.
    15. Xiaoxiao Li & Man Yu & Jing Ma & Zhanbin Luo & Fu Chen & Yongjun Yang, 2018. "Identifying the Relationship between Soil Properties and Rice Growth for Improving Consolidated Land in the Yangtze River Delta, China," Sustainability, MDPI, vol. 10(9), pages 1-14, August.
    16. Yotsaphat Kittichotsatsawat & Varattaya Jangkrajarng & Korrakot Yaibuathet Tippayawong, 2021. "Enhancing Coffee Supply Chain towards Sustainable Growth with Big Data and Modern Agricultural Technologies," Sustainability, MDPI, vol. 13(8), pages 1-20, April.
    17. Nahry, A.H. El & Ali, R.R. & Baroudy, A.A. El, 2011. "An approach for precision farming under pivot irrigation system using remote sensing and GIS techniques," Agricultural Water Management, Elsevier, vol. 98(4), pages 517-531, February.
    18. Yonela Mndela & Naledzani Ndou & Adolph Nyamugama, 2023. "Irrigation Scheduling for Small-Scale Crops Based on Crop Water Content Patterns Derived from UAV Multispectral Imagery," Sustainability, MDPI, vol. 15(15), pages 1-21, August.
    19. Santiago Castaño & David Sanz & Juan Gómez-Alday, 2010. "Methodology for Quantifying Groundwater Abstractions for Agriculture via Remote Sensing and GIS," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(4), pages 795-814, March.
    20. Er-Raki, S. & Chehbouni, A. & Guemouria, N. & Duchemin, B. & Ezzahar, J. & Hadria, R., 2007. "Combining FAO-56 model and ground-based remote sensing to estimate water consumptions of wheat crops in a semi-arid region," Agricultural Water Management, Elsevier, vol. 87(1), pages 41-54, January.

    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:238:y:2020:i:c:s0378377419318281. 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.