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Models of Hysteresis Water Retention Capacity and Their Comparative Analysis on the Example of Sandy Soil

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International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies EMMFT 2018 (EMMFT-2018 2018)

Abstract

The reasons for the hysteresis of the soil water-retention capacity are indicated. An explanation of the closed loop, which is formed by the main drying and wetting branches, as well as open loops, which are formed with the participation of scanning hysteresis branches is proposed. The problem of the possible manifestation of an undesirable “pump effect” is analyzed, and a way to solve this problem is indicated. Mathematical models describing this phenomenon are presented. In these models, three functions of water-retention capacity of the soil are used: (i) Van Genuchten’s function, (ii) improved Kosugi function, (iii) improved Haverkamp and co-authors function. A physical interpretation of an additional additive parameter in the improved functions of the soil water-retention capacity is proposed. The prospects for the use of hysteresis models for calculating precision irrigation rates in land reclamation agriculture are characterized. Using the Williams-Kloot criterion, a comparative analysis of the presented hysteresis models was carried out with respect to the error of the point approximation of experimental data on the main branches (parameter identification), as well as with respect to the error in estimation of the scanning branches of water-retention capacity of the soil using the example of Dune Sand.

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Acknowledgments

The reported study was funded by RFBR according to the research projects No. 19-04-00939-a, No. 19-016-00148-a.

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Correspondence to Aleksandr Nikonorov .

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Terleev, V. et al. (2019). Models of Hysteresis Water Retention Capacity and Their Comparative Analysis on the Example of Sandy Soil. In: Murgul, V., Pasetti, M. (eds) International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies EMMFT 2018. EMMFT-2018 2018. Advances in Intelligent Systems and Computing, vol 983. Springer, Cham. https://doi.org/10.1007/978-3-030-19868-8_46

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