IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v287y2023ics0378377423002871.html
   My bibliography  Save this article

Evaluation of soil moisture estimation techniques based on Sentinel-1 observations over wheat fields

Author

Listed:
  • Arias, María
  • Notarnicola, Claudia
  • Campo-Bescós, Miguel Ángel
  • Arregui, Luis Miguel
  • Álvarez-Mozos, Jesús

Abstract

Soil moisture (SM) is a key variable in agriculture and its monitoring is essential. SM determines the amount of water available to plants, having a direct impact on the development of crops, on the forecasting of crop yields and on the surveillance of food security. Microwave remote sensing offers a great potential for estimating SM because it is sensitive to the dielectric characteristics of observed surface that depend on surface soil moisture. The objective of this study is the evaluation of three change detection methodologies for SM estimation over wheat at the agricultural field scale based on Sentinel-1 time series: Short Term Change Detection (STCD), TU Wien Change Detection (TUWCD) and Multitemporal Bayesian Change Detection (MTBCD). Different methodological alternatives were proposed for the implementation of these techniques at the agricultural field scale. Soil moisture measurements from eight experimental wheat fields were used for validating the methodologies. All available Sentinel-1 acquisitions were processed and the eventual benefit of correcting for vegetation effects in backscatter time series was evaluated. The results were rather variable, with some experimental fields achieving successful performance metrics (ubRMSE ∼ 0.05 m3/m3) and some others rather poor ones (ubRMSE > 0.12 m3/m3). Evaluating median performance metrics, it was observed that both TUWCD and MTBCD methods obtained better results when run with vegetation corrected backscatter time series (ubRMSE ∼0.07 m3/m3) whereas STCD produced similar results with and without vegetation correction (ubRMSE ∼0.08 m3/m3). The soil moisture content had an influence on the accuracy of the different methodologies, with higher errors observed for drier conditions and rain-fed fields, in comparison to wetter conditions and irrigated fields. Taking into account the spatial scale of this case study, results were considered promising for the future application of these techniques in irrigation management.

Suggested Citation

  • Arias, María & Notarnicola, Claudia & Campo-Bescós, Miguel Ángel & Arregui, Luis Miguel & Álvarez-Mozos, Jesús, 2023. "Evaluation of soil moisture estimation techniques based on Sentinel-1 observations over wheat fields," Agricultural Water Management, Elsevier, vol. 287(C).
    • Handle: RePEc:eee:agiwat:v:287:y:2023:i:c:s0378377423002871
    DOI: 10.1016/j.agwat.2023.108422
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377423002871
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2023.108422?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. Laibao Liu & Lukas Gudmundsson & Mathias Hauser & Dahe Qin & Shuangcheng Li & Sonia I. Seneviratne, 2020. "Soil moisture dominates dryness stress on ecosystem production globally," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
    2. Carranza, Coleen & Benninga, Harm-jan & van der Velde, Rogier & van der Ploeg, Martine, 2019. "Monitoring agricultural field trafficability using Sentinel-1," Agricultural Water Management, Elsevier, vol. 224(C), pages 1-1.
    3. Julia K. Green & Sonia I. Seneviratne & Alexis M. Berg & Kirsten L. Findell & Stefan Hagemann & David M. Lawrence & Pierre Gentine, 2019. "Large influence of soil moisture on long-term terrestrial carbon uptake," Nature, Nature, vol. 565(7740), pages 476-479, January.
    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. Wang, Chunyu & Li, Sien & Wu, Mousong & Zhang, Wenxin & Guo, Zhenyu & Huang, Siyu & Yang, Danni, 2023. "Co-regulation of temperature and moisture in the irrigated agricultural ecosystem productivity," Agricultural Water Management, Elsevier, vol. 275(C).
    2. Ning Chen & Yifei Zhang & Fenghui Yuan & Changchun Song & Mingjie Xu & Qingwei Wang & Guangyou Hao & Tao Bao & Yunjiang Zuo & Jianzhao Liu & Tao Zhang & Yanyu Song & Li Sun & Yuedong Guo & Hao Zhang &, 2023. "Warming-induced vapor pressure deficit suppression of vegetation growth diminished in northern peatlands," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    3. Wei Wei & Jiping Wang & Libang Ma & Xufeng Wang & Binbin Xie & Junju Zhou & Haoyan Zhang, 2024. "Global Drought-Wetness Conditions Monitoring Based on Multi-Source Remote Sensing Data," Land, MDPI, vol. 13(1), pages 1-19, January.
    4. Zheng Fu & Philippe Ciais & I. Colin Prentice & Pierre Gentine & David Makowski & Ana Bastos & Xiangzhong Luo & Julia K. Green & Paul C. Stoy & Hui Yang & Tomohiro Hajima, 2022. "Atmospheric dryness reduces photosynthesis along a large range of soil water deficits," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    5. Riao, Dao & Guga, Suri & Bao, Yongbin & Liu, Xingping & Tong, Zhijun & Zhang, Jiquan, 2023. "Non-overlap of suitable areas of agro-climatic resources and main planting areas is the main reason for potato drought disaster in Inner Mongolia, China," Agricultural Water Management, Elsevier, vol. 275(C).
    6. Krishna, Dyvavani K. & Watham, Taibanganba & Padalia, Hitendra & Srinet, Ritika & Nandy, Subrata, 2023. "Improved gross primary productivity estimation using semi empirical (PRELES) model for moist Indian sal forest," Ecological Modelling, Elsevier, vol. 475(C).
    7. Sourav Mukherjee & Ashok Kumar Mishra & Jakob Zscheischler & Dara Entekhabi, 2023. "Interaction between dry and hot extremes at a global scale using a cascade modeling framework," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    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. Cailin Wang & Enliang Guo & Yongfang Wang & Buren Jirigala & Yao Kang & Ye Zhang, 2023. "Spatiotemporal variations in drought and waterlogging and their effects on maize yields at different growth stages in Jilin Province, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 118(1), pages 155-180, August.
    10. Hajdu, Istvan & Yule, Ian & Bretherton, Mike & Singh, Ranvir & Hedley, Carolyn, 2019. "Field performance assessment and calibration of multi-depth AquaCheck capacitance-based soil moisture probes under permanent pasture for hill country soils," Agricultural Water Management, Elsevier, vol. 217(C), pages 332-345.
    11. Visconti, Fernando & de Paz, José Miguel & Martínez, Delfina & Molina, Mª José, 2014. "Laboratory and field assessment of the capacitance sensors Decagon 10HS and 5TE for estimating the water content of irrigated soils," Agricultural Water Management, Elsevier, vol. 132(C), pages 111-119.
    12. Yaoping Wang & Jiafu Mao & Forrest M. Hoffman & Céline J. W. Bonfils & Hervé Douville & Mingzhou Jin & Peter E. Thornton & Daniel M. Ricciuto & Xiaoying Shi & Haishan Chen & Stan D. Wullschleger & Shi, 2022. "Quantification of human contribution to soil moisture-based terrestrial aridity," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    13. Zhang, Yong-Rong & Shang, Guo-Fei & Leng, Pei & Ma, Chunfeng & Ma, Jianwei & Zhang, Xia & Li, Zhao-Liang, 2023. "Estimation of quasi-full spatial coverage soil moisture with fine resolution in China from the combined use of ERA5-Land reanalysis and TRIMS land surface temperature product," Agricultural Water Management, Elsevier, vol. 275(C).
    14. Guangcun Hao & Zhongmin Hu & Qun Guo & Kai Di & Shenggong Li, 2019. "Median to Strong Rainfall Intensity Favors Carbon Sink in a Temperate Grassland Ecosystem in China," Sustainability, MDPI, vol. 11(22), pages 1-13, November.
    15. Guo, Youzheng & Ma, Yingjun & Ding, Changjun & Di, Nan & Liu, Yang & Tan, Jianbiao & Zhang, Shusen & Yu, Weichen & Gao, Guixi & Duan, Jie & Xi, Benye & Li, Ximeng, 2023. "Plant hydraulics provide guidance for irrigation management in mature polar plantation," Agricultural Water Management, Elsevier, vol. 275(C).
    16. 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).
    17. Li, Bingbing & Yang, Yi & Li, Zhi, 2021. "Combined effects of multiple factors on spatiotemporally varied soil moisture in China’s Loess Plateau," Agricultural Water Management, Elsevier, vol. 258(C).
    18. Ouyang, Lei & Lu, Longwei & Wang, Chunlin & Li, Yanqiong & Wang, Jingyi & Zhao, Xiuhua & Gao, Lei & Zhu, Liwei & Ni, Guangyan & Zhao, Ping, 2022. "A 14-year experiment emphasizes the important role of heat factors in regulating tree transpiration, growth, and water use efficiency of Schima superba in South China," Agricultural Water Management, Elsevier, vol. 273(C).
    19. Zhang, Yuanhong & Peng, Xingxing & Ning, Fang & Dong, Zhaoyang & Wang, Rui & Li, Jun, 2022. "Assessing the response of orchard productivity to soil water depletion using field sampling and modeling methods," Agricultural Water Management, Elsevier, vol. 273(C).
    20. Haibo Lu & Zhangcai Qin & Shangrong Lin & Xiuzhi Chen & Baozhang Chen & Bin He & Jing Wei & Wenping Yuan, 2022. "Large influence of atmospheric vapor pressure deficit on ecosystem production efficiency," Nature Communications, Nature, vol. 13(1), pages 1-4, December.

    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:287:y:2023:i:c:s0378377423002871. 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.