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Real-Time Scanning Curve of Soil–Water Characteristic Curve for Sustainability of Residual Soil Slopes

Author

Listed:
  • Abdulroqeeb Mofeyisope Daramola

    (Department of Civil and Environmental Engineering, Nazarbayev University, 53 Kabanbay Batyr Ave, Astana 010000, Kazakhstan)

  • Alfrendo Satyanaga

    (Department of Civil and Environmental Engineering, Nazarbayev University, 53 Kabanbay Batyr Ave, Astana 010000, Kazakhstan)

  • Babatunde David Adejumo

    (Department of Civil and Environmental Engineering, Nazarbayev University, 53 Kabanbay Batyr Ave, Astana 010000, Kazakhstan)

  • Yongmin Kim

    (James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK)

  • Zhai Qian

    (School of Civil Engineering, Southeast University, Nanjing 211189, China)

  • Jong Kim

    (Department of Civil and Environmental Engineering, Nazarbayev University, 53 Kabanbay Batyr Ave, Astana 010000, Kazakhstan)

Abstract

The scanning curve of the soil–water characteristic curve (SWCC) represents the intermediate paths followed by soil as it transitions between the initial drying and main wetting cycles. The alternating occurrence of climatic conditions, such as rainfall and evaporation in different regions globally, provides a valuable framework for understanding how these dynamics influence the scanning curve. Monitoring the scanning curve can provide valuable insights for managing water resources and mitigating the impacts of drought, contributing to environmental sustainability by enabling more precise agricultural practices, promoting water conservation, and supporting the resilience of ecosystems in the face of climate change. It enhances sustainability by enabling data-driven designs that minimize resource use, reduce environmental impact, and increase the resilience of slopes to natural hazards like landslides and flooding. Available studies to determine the scanning curve of SWCC are limited and mostly conducted in the laboratory. This study aims to determine the real-time measurement of the scanning curve of SWCC for unsaturated soil. The research focuses on assessing the hysteresis behavior of residual soil slope from old alluvium through a combination of field instrumentation and laboratory testing. The pore size distribution was derived from the initial drying and main wetting SWCC. Field monitoring (scanning curve) indicates measurable deviations from the experimental results, including a 10% lower saturated water content and a 25% lower air-entry value. This study demonstrates the potential for field-based determination of scanning curves. It highlights their role in improving the prediction of the hydraulic behavior of residual slopes during varying climatic conditions.

Suggested Citation

  • Abdulroqeeb Mofeyisope Daramola & Alfrendo Satyanaga & Babatunde David Adejumo & Yongmin Kim & Zhai Qian & Jong Kim, 2025. "Real-Time Scanning Curve of Soil–Water Characteristic Curve for Sustainability of Residual Soil Slopes," Sustainability, MDPI, vol. 17(5), pages 1-16, February.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:5:p:1803-:d:1595911
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    References listed on IDEAS

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    1. Fasheng Miao & Yiping Wu & Linwei Li & Kang Liao & Longfei Zhang, 2019. "Risk assessment of snowmelt-induced landslides based on GIS and an effective snowmelt model," 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. 97(3), pages 1151-1173, July.
    2. Gaoliang Tao & Yinjie Peng & Yiming Liu, 2023. "A Method For Predicting Unsaturated Soil Permeability Coefficient Based On Clay Content," FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 31(08), pages 1-11.
    3. Xiaokun Hou & Shengwen Qi & Fangcui Liu, 2023. "Soil Water Retention and Pore Characteristics of Intact Loess Buried at Different Depths," Sustainability, MDPI, vol. 15(20), pages 1-10, October.
    4. Xichun Jia & Xuebing Jiang & Jun Huang & Shunchao Yu & Bingjun Liu, 2024. "Slope Stability Analysis Based on the Explicit Smoothed Particle Finite Element Method," Sustainability, MDPI, vol. 16(2), pages 1-21, January.
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