IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v111y2022i2d10.1007_s11069-021-05110-z.html
   My bibliography  Save this article

A step beyond susceptibility: an adaptation of risk framework for monetary risk estimation of gully erosion

Author

Listed:
  • Omid Asadi Nalivan

    (Department of Watershed Management, Gorgan University of Agricultural Sciences and Natural Resources (GUASNR))

  • Ziaedin Badehian

    (Lorestan University)

  • Majid Sadeghinia

    (Ardakan University)

  • Adel Soltani

    (Payame Noor University)

  • Iman Islami

    (Tarbiat Modares University)

  • Ali Boustan

    (Islamic Azad University, Kerman Branch)

Abstract

In an effort to improve the previous gully susceptibility assessments in Iran, we attempted to conglomerate the notions of susceptibility, vulnerability, and exposure associated with gully occurrence across the northeast of the Golestan province in Iran to test the feasibility of the provided risk framework. The adaptive neuro-fuzzy inference system (ANFIS) and its ensemble with the imperialist competitive algorithm (ANFIS-ICA) were adopted to assess gully susceptibility. Based on various performance metrics, including Pierce's skill score, Heidke's skill score, Gilbert's skill score, and the area under the receiver operating characteristic curve, the ANFIS-ICA model with the respective values of 0.64, 0.637, 0.47, and 0.887 evidently outperformed the solitarily used ANFIS model due to being fused to a robust optimization algorithm. The results of susceptibility assessment revealed that about 24% of the study area falls within the highly susceptible zone to gully occurrences which stems from the interactive role of such factors as the red relief image map (RRIM), valley depth, average annual rainfall, distance from roads, and distance from streams. Moreover, the RRIM factor provided promising multi-featured morphological information that boosted the pattern recognition power of the susceptibility model. Gully risk assessment results indicated that approximately 6% of the area falls within the high-risk zone. The highest average values of the monetary risk mainly pertain to residential areas, moderately dense forests, orchards, dense forests, and roads, which would impose a sizable risk to the region in case of crisis. Superimposition of the susceptibility map over the monetary risk map showed that their shared areal coverage only accounts for 17.7%, and there is an 82.3% difference which, in turn, indicated that considering the risk map as an alternative to the previous susceptibility maps would considerably change the spatial allocation of the mitigation measures. Graphical abstract

Suggested Citation

  • Omid Asadi Nalivan & Ziaedin Badehian & Majid Sadeghinia & Adel Soltani & Iman Islami & Ali Boustan, 2022. "A step beyond susceptibility: an adaptation of risk framework for monetary risk estimation of gully erosion," 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. 111(2), pages 1661-1684, March.
    • Handle: RePEc:spr:nathaz:v:111:y:2022:i:2:d:10.1007_s11069-021-05110-z
    DOI: 10.1007/s11069-021-05110-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-021-05110-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11069-021-05110-z?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. Sina Paryani & Aminreza Neshat & Saman Javadi & Biswajeet Pradhan, 2020. "Comparative performance of new hybrid ANFIS models in landslide susceptibility mapping," 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. 103(2), pages 1961-1988, September.
    2. Norman Ferrier & C. Haque, 2003. "Hazards Risk Assessment Methodology for Emergency Managers: A Standardized Framework for Application," 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. 28(2), pages 271-290, March.
    3. E. E. Koks & J. Rozenberg & C. Zorn & M. Tariverdi & M. Vousdoukas & S. A. Fraser & J. W. Hall & S. Hallegatte, 2019. "A global multi-hazard risk analysis of road and railway infrastructure assets," Nature Communications, Nature, vol. 10(1), pages 1-11, December.
    4. Khanali, Majid & Akram, Asadollah & Behzadi, Javad & Mostashari-Rad, Fatemeh & Saber, Zahra & Chau, Kwok-wing & Nabavi-Pelesaraei, Ashkan, 2021. "Multi-objective optimization of energy use and environmental emissions for walnut production using imperialist competitive algorithm," Applied Energy, Elsevier, vol. 284(C).
    5. L. Lombardo & G. Fubelli & G. Amato & M. Bonasera, 2016. "Presence-only approach to assess landslide triggering-thickness susceptibility: a test for the Mili catchment (north-eastern Sicily, Italy)," 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. 84(1), pages 565-588, October.
    6. Vahedberdi Sheikh & Aiding Kornejady & Majid Ownegh, 2019. "Application of the coupled TOPSIS–Mahalanobis distance for multi-hazard-based management of the target districts of the Golestan Province, Iran," 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. 96(3), pages 1335-1365, April.
    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. Yin, Sihua & Yang, Haidong & Xu, Kangkang & Zhu, Chengjiu & Zhang, Shaqing & Liu, Guosheng, 2022. "Dynamic real–time abnormal energy consumption detection and energy efficiency optimization analysis considering uncertainty," Applied Energy, Elsevier, vol. 307(C).
    2. Lena I. Fuldauer & Scott Thacker & Robyn A. Haggis & Francesco Fuso-Nerini & Robert J. Nicholls & Jim W. Hall, 2022. "Targeting climate adaptation to safeguard and advance the Sustainable Development Goals," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    3. Nabavi-Pelesaraei, Ashkan & Azadi, Hossein & Van Passel, Steven & Saber, Zahra & Hosseini-Fashami, Fatemeh & Mostashari-Rad, Fatemeh & Ghasemi-Mobtaker, Hassan, 2021. "Prospects of solar systems in production chain of sunflower oil using cold press method with concentrating energy and life cycle assessment," Energy, Elsevier, vol. 223(C).
    4. Liang Jia & Saini Yang & Weiping Wang & Xinlong Zhang, 2022. "Impact analysis of highways in China under future extreme precipitation," 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. 110(2), pages 1097-1113, January.
    5. Saeed Davar & Masoud Nobahar & Mohammad Sadik Khan & Farshad Amini, 2022. "The Development of PSO-ANN and BOA-ANN Models for Predicting Matric Suction in Expansive Clay Soil," Mathematics, MDPI, vol. 10(16), pages 1-38, August.
    6. Dorokhov, V.V. & Kuznetsov, G.V. & Vershinina, K.Yu. & Strizhak, P.A., 2021. "Relative energy efficiency indicators calculated for high-moisture waste-based fuel blends using multiple-criteria decision-making," Energy, Elsevier, vol. 234(C).
    7. Bo Li & Jing Liu & Qian Liu & Muhammad Mohiuddin, 2022. "The Effects of Broadband Infrastructure on Carbon Emission Efficiency of Resource-Based Cities in China: A Quasi-Natural Experiment from the “Broadband China” Pilot Policy," IJERPH, MDPI, vol. 19(11), pages 1-27, May.
    8. Liu, Huan & Tatano, Hirokazu & Pflug, Georg & Hochrainer-Stigler, Stefan, 2021. "Post-disaster recovery in industrial sectors: A Markov process analysis of multiple lifeline disruptions," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    9. Majid Mohammady & Hamid Reza Pourghasemi & Mojtaba Amiri, 2019. "Assessment of land subsidence susceptibility in Semnan plain (Iran): a comparison of support vector machine and weights of evidence data mining algorithms," 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. 99(2), pages 951-971, November.
    10. Pantua, Conrad Allan Jay & Calautit, John Kaiser & Wu, Yupeng, 2021. "Sustainability and structural resilience of building integrated photovoltaics subjected to typhoon strength winds," Applied Energy, Elsevier, vol. 301(C).
    11. C. Emdad Haque & Mahed-Ul-Islam Choudhury & Md. Sowayib Sikder, 2019. "“Events and failures are our only means for making policy changes”: learning in disaster and emergency management policies in Manitoba, Canada," 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. 98(1), pages 137-162, August.
    12. Antunes, Jorge Junio Moreira & Neves, Juliana Campos & Elmor, Larissa Rosa Carneiro & Araujo, Michel Fontaine Reis De & Wanke, Peter Fernandes & Tan, Yong, 2023. "A new perspective on the U.S. energy efficiency: The political context," Technological Forecasting and Social Change, Elsevier, vol. 186(PA).
    13. Christos Polykretis & Manolis G. Grillakis & Athanasios V. Argyriou & Nikos Papadopoulos & Dimitrios D. Alexakis, 2021. "Integrating Multivariate (GeoDetector) and Bivariate (IV) Statistics for Hybrid Landslide Susceptibility Modeling: A Case of the Vicinity of Pinios Artificial Lake, Ilia, Greece," Land, MDPI, vol. 10(9), pages 1-23, September.
    14. Amin Salehpour Jam & Jamal Mosaffaie & Faramarz Sarfaraz & Samad Shadfar & Rouhangiz Akhtari, 2021. "GIS-based landslide susceptibility mapping using hybrid MCDM models," 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. 108(1), pages 1025-1046, August.
    15. Bo Cao & Qingyi Li & Yuhang Zhu, 2022. "Comparison of Effects between Different Weight Calculation Methods for Improving Regional Landslide Susceptibility—A Case Study from Xingshan County of China," Sustainability, MDPI, vol. 14(17), pages 1-15, September.
    16. Doh Dinga, Christian & Wen, Zongguo, 2021. "Many-objective optimization of energy conservation and emission reduction in China’s cement industry," Applied Energy, Elsevier, vol. 304(C).
    17. Mühlhofer, Evelyn & Koks, Elco E. & Kropf, Chahan M. & Sansavini, Giovanni & Bresch, David N., 2023. "A generalized natural hazard risk modelling framework for infrastructure failure cascades," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    18. Laurie Jayne Kurilla & Giandomenico Fubelli, 2022. "Global debris flow susceptibility based on a comparative analysis of a single global model versus a continent-by-continent approach," 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. 113(1), pages 527-546, August.
    19. Byeong-Cheol Kang, & Choi, Hyeong-Jun & Park, Sang-Joon & Ha, Tae-Jun, 2021. "Wearable triboelectric nanogenerators with the reduced loss of triboelectric charges by using a hole transport layer of bar-printed single-wall carbon nanotube random networks," Energy, Elsevier, vol. 233(C).
    20. Mehtab Alam & Fu-Ren Lin, 2022. "Internalizing Sustainability into Research Practices of Higher Education Institutions: Case of a Research University in Taiwan," Sustainability, MDPI, vol. 14(15), pages 1-30, August.

    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:spr:nathaz:v:111:y:2022:i:2:d:10.1007_s11069-021-05110-z. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.