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Assessing Soil Erosion by Monitoring Hilly Lakes Silting

Author

Listed:
  • Yamuna Giambastiani

    (CNR-IBE, National Research Council, Institute of Bioeconomy, 50019 Florence, Italy)

  • Riccardo Giusti

    (CNR-IBE, National Research Council, Institute of Bioeconomy, 50019 Florence, Italy)

  • Lorenzo Gardin

    (CNR-IBE, National Research Council, Institute of Bioeconomy, 50019 Florence, Italy)

  • Stefano Cecchi

    (CNR-IBE, National Research Council, Institute of Bioeconomy, 50019 Florence, Italy)

  • Maurizio Iannuccilli

    (CNR-IBE, National Research Council, Institute of Bioeconomy, 50019 Florence, Italy)

  • Stefano Romanelli

    (Environmental Modelling and Monitoring Laboratory for Sustainable Development, LaMMA Consortium, 50019 Florence, Italy)

  • Lorenzo Bottai

    (Environmental Modelling and Monitoring Laboratory for Sustainable Development, LaMMA Consortium, 50019 Florence, Italy)

  • Alberto Ortolani

    (CNR-IBE, National Research Council, Institute of Bioeconomy, 50019 Florence, Italy
    Environmental Modelling and Monitoring Laboratory for Sustainable Development, LaMMA Consortium, 50019 Florence, Italy)

  • Bernardo Gozzini

    (CNR-IBE, National Research Council, Institute of Bioeconomy, 50019 Florence, Italy
    Environmental Modelling and Monitoring Laboratory for Sustainable Development, LaMMA Consortium, 50019 Florence, Italy)

Abstract

Soil erosion continues to be a threat to soil quality, impacting crop production and ecosystem services delivery. The quantitative assessment of soil erosion, both by water and by wind, is mostly carried out by modeling the phenomenon via remote sensing approaches. Several empirical and process-based physical models are used for erosion estimation worldwide, including USLE (or RUSLE), MMF, WEPP, PESERA, SWAT, etc. Furthermore, the amount of sediment produced by erosion phenomena is obtained by direct measurements carried out in experimental sites. Data collection for this purpose is very complex and expensive; in fact, we have few cases of measures distributed at the basin scale to monitor this phenomenon. In this work, we propose a methodology based on an expeditious way to monitor the volume of hilly lakes with GPS, sonar sensor and aquatic drone. The volume is obtained by means of an automatic GIS procedure based on the measurements of lake depth and surface area. Hilly lakes can be considered as sediment containers. Time-lapse measurements make it possible to estimate the silting rate of the lake. The volume of 12 hilly lakes in Tuscany was measured in 2010 and 2018, and the results in terms of silting rate were compared with the estimates of soil loss obtained by RUSLE and MMF. The analyses show that all the lakes measured are subject to silting phenomena. The sediment estimated by the measurements corresponds well to the amount of soil loss estimated with the models used. The relationships found are significant and promising for a distributed application of the methodology, which allows rapid estimation of erosion phenomena. Substantial differences in the proposed comparison (mainly found in two cases) can be justified by particular conditions found on site, which are difficult to predict from the models. The proposed approach allows for a monitoring of basin-scale erosion, which can be extended to larger domains which have hilly lakes, such as, for example, the Tuscany region, where there are more than 10,000 lakes.

Suggested Citation

  • Yamuna Giambastiani & Riccardo Giusti & Lorenzo Gardin & Stefano Cecchi & Maurizio Iannuccilli & Stefano Romanelli & Lorenzo Bottai & Alberto Ortolani & Bernardo Gozzini, 2022. "Assessing Soil Erosion by Monitoring Hilly Lakes Silting," Sustainability, MDPI, vol. 14(9), pages 1-20, May.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5649-:d:810533
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    References listed on IDEAS

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    1. David Pimentel, 2006. "Soil Erosion: A Food and Environmental Threat," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 8(1), pages 119-137, February.
    2. David Pimentel & Michael Burgess, 2013. "Soil Erosion Threatens Food Production," Agriculture, MDPI, vol. 3(3), pages 1-21, August.
    3. Shen, Z.Y. & Gong, Y.W. & Li, Y.H. & Hong, Q. & Xu, L. & Liu, R.M., 2009. "A comparison of WEPP and SWAT for modeling soil erosion of the Zhangjiachong Watershed in the Three Gorges Reservoir Area," Agricultural Water Management, Elsevier, vol. 96(10), pages 1435-1442, October.
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    Cited by:

    1. Antonio Ganga & Mario Elia & Blaž Repe, 2023. "Applications of GIS and Remote Sensing in Soil Environment Monitoring," Sustainability, MDPI, vol. 15(18), pages 1-2, September.
    2. Yamuna Giambastiani & Gherardo Biancofiore & Matteo Mancini & Antonio Di Giorgio & Riccardo Giusti & Stefano Cecchi & Lorenzo Gardin & Alessandro Errico, 2022. "Modelling the Effect of Keyline Practice on Soil Erosion Control," Land, MDPI, vol. 12(1), pages 1-12, December.
    3. Xuyang Cai & Baoer Hao & Haiyang Liu & Xin Tong & Mengjun Guo & Zhanfeng Hou, 2023. "The Design and Experimental Study of a Double-Column Scrambler Wind–Sand Separator for Sustainable Soil Wind Erosion Monitoring," Sustainability, MDPI, vol. 15(20), pages 1-19, October.

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