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A soil moisture experiment for validating high-resolution satellite products and monitoring irrigation at agricultural field scale

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Listed:
  • Wang, Weizhen
  • Ma, Chunfeng
  • Wang, Xufeng
  • Feng, Jiaojiao
  • Dong, Leilei
  • Kang, Jian
  • Jin, Rui
  • Li, Xingze

Abstract

Validating the satellite soil moisture products is always an active research topic for the application of the products and improvement of the retrieval algorithms, attracting extensive attention. Nevertheless, seldom existing validation activities focus on the validation of high-resolution soil moisture products at the fine scale. To this end, an experiment was conducted in the middle stream of the Heihe River Basin in northwestern China in August to October of 2021, aiming to validate high-resolution satellite remote sensing products of soil moisture. The paper introduces the design, composite, and preliminary results of the experiment. A soil moisture observation network was established with two kinds of sensors (CS616 and Stevens Hydra Probe) validated against soil core measurements. Several synchronized campaigns were performed, and data were collected to validate the SMAP/Sentinel-1 L2 Radiometer/Radar 30-Second Scene 3 and 1 km EASE-Grid Soil Moisture (SPL2SMAP_S) products. Besides, an optical trapezoid model (OPTRAM) and collected Sentinel-2 data were applied to estimate soil moisture and to map irrigated area. Preliminary analyses show that: 1) Steven probes perform best, with an RMSE = 0.040 m3m−3 and ubRMSE=0.034 m3m−3; 2) Both the SPL2SMAP_S products at 3 km and 1 km show large RMSE (0.128 m3m−3 for 3 km and 0.158 m3m−3 for 1 km) and ubRMSE (0.115 m3m−3 for 3 km and 0.158 m3m−3 for 1 km); 3) The OPTRAM retrievals over bare surface present relatively smaller RMSE (0.06 m3m−3) and ubRMSE (0.057 m3m−3), while retrievals over vegetated croplands present a relatively large RMSE/ubRMSE (0.083/0.083 m3m−3), and the retrievals can identify the irrigated area at field scale. Overall, the experiment provides fruitful methodologies and datasets for the validation of high-resolution remote sensing products, benefiting the development and improvement of soil moisture retrieval algorithms and products to support irrigation scheduling and management at a precision agricultural scale in the future.

Suggested Citation

  • Wang, Weizhen & Ma, Chunfeng & Wang, Xufeng & Feng, Jiaojiao & Dong, Leilei & Kang, Jian & Jin, Rui & Li, Xingze, 2024. "A soil moisture experiment for validating high-resolution satellite products and monitoring irrigation at agricultural field scale," Agricultural Water Management, Elsevier, vol. 304(C).
  • Handle: RePEc:eee:agiwat:v:304:y:2024:i:c:s0378377424004074
    DOI: 10.1016/j.agwat.2024.109071
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    References listed on IDEAS

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    1. Holsten, Anne & Vetter, Tobias & Vohland, Katrin & Krysanova, Valentina, 2009. "Impact of climate change on soil moisture dynamics in Brandenburg with a focus on nature conservation areas," Ecological Modelling, Elsevier, vol. 220(17), pages 2076-2087.
    2. Ma, Chunfeng & Johansen, Kasper & McCabe, Matthew F., 2022. "Combining Sentinel-2 data with an optical-trapezoid approach to infer within-field soil moisture variability and monitor agricultural production stages," Agricultural Water Management, Elsevier, vol. 274(C).
    3. Hong, Eun-Mi & Nam, Won-Ho & Choi, Jin-Yong & Pachepsky, Yakov A., 2016. "Projected irrigation requirements for upland crops using soil moisture model under climate change in South Korea," Agricultural Water Management, Elsevier, vol. 165(C), pages 163-180.
    4. 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.
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