IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v98y2019i2d10.1007_s11069-019-03728-8.html
   My bibliography  Save this article

Experimental study on the influence of vegetation on the slope flow concentration time

Author

Listed:
  • Qinge Peng

    (State Key Laboratory of Hydraulics and Mountain River Engineering)

  • Xingnian Liu

    (State Key Laboratory of Hydraulics and Mountain River Engineering)

  • Er Huang

    (State Key Laboratory of Hydraulics and Mountain River Engineering)

  • Kejun Yang

    (State Key Laboratory of Hydraulics and Mountain River Engineering)

Abstract

Due to the steep slope of mountainous watersheds and large changes in vegetation coverage degree, flood response processes after rainstorms are complicated. The flow concentration time of the slope is a key parameter for the simulation of flood processes. The most widely used flow concentration time formula currently in the distributed hydrological model is T = L0.6n0.6i−0.4S−0.3, which is derived from the kinematic wave theory (Melesse and Graham in J Am Water Resour As 40(4):863–879, 2004; Lee in Hydrol Sci 53(2):323–337, 2008). The flow confluence time T is characterized by the constant exponent of the slope length L, roughness n, effective rainfall intensity i and slope S, and the influence of vegetation on the flow concentration time is implied by the roughness. In this study, a series of heavy rainfall slope surface confluence tests under different slopes and vegetation coverage were carried out, a vegetation coverage factor, C, which was introduced, a statistical analysis method was used, and the vegetation coverage index was fitted. The results showed that the types of vegetation have a certain influence on the flow concentration time of slope, and the flow confluence time under turf vegetation was larger than the flow confluence time under shrubs vegetation; especially in the slope of the larger slope, the relative impact is more significant; at the same time, the influence of vegetation coverage on the flow concentration time of slope was more significant; no matter the condition of turf or shrub, the slope confluence time increased obviously with the increase in vegetation coverage. The index of vegetation coverage factor C varied with the slope and rain intensity. In general, the index of vegetation coverage factor C increased with the decrease in slope and decreased with the increase in rain intensity. In regard to the turf vegetation coverage index, when the slope is 45° and 30°, the decreasing trend of the vegetation coverage index a0 is obvious with increasing rainfall intensity. When the slope is 15°, the vegetation coverage index a0 also decreases with increasing rainfall intensity. When the slope is 5°, the vegetation coverage index a0 basically has no change. In regard to the shrubs vegetation coverage index, when the slope is 45° and 30°, the decreasing trend of the vegetation coverage index a0 is obvious with increasing rainfall intensity. When the slope is 15°, the vegetation coverage index a0 also decreases with increasing rainfall intensity. When the slope is 5°, the vegetation coverage index a0 basically has no change.

Suggested Citation

  • Qinge Peng & Xingnian Liu & Er Huang & Kejun Yang, 2019. "Experimental study on the influence of vegetation on the slope flow concentration time," 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(2), pages 751-763, September.
  • Handle: RePEc:spr:nathaz:v:98:y:2019:i:2:d:10.1007_s11069-019-03728-8
    DOI: 10.1007/s11069-019-03728-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-019-03728-8
    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/s11069-019-03728-8?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. Konstantinos Tsanakas & Kalliopi Gaki-Papanastassiou & Kleomenis Kalogeropoulos & Christos Chalkias & Petros Katsafados & Efthimios Karymbalis, 2016. "Investigation of flash flood natural causes of Xirolaki Torrent, Northern Greece based on GIS modeling and geomorphological analysis," 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(2), pages 1015-1033, November.
    2. Johnny Douvinet & Marco Wiel & Daniel Delahaye & Etienne Cossart, 2015. "A flash flood hazard assessment in dry valleys (northern France) by cellular automata modelling," 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. 75(3), pages 2905-2929, February.
    3. Fei Teng & Wenrui Huang & Isaac Ginis, 2018. "Hydrological modeling of storm runoff and snowmelt in Taunton River Basin by applications of HEC-HMS and PRMS 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. 91(1), pages 179-199, March.
    4. Jia Liu & Jianhua Wang & Shibing Pan & Kewang Tang & Chuanzhe Li & Dawei Han, 2015. "A real-time flood forecasting system with dual updating of the NWP rainfall and the river flow," 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. 77(2), pages 1161-1182, June.
    5. Xiaozhang Hu & Lixiang Song, 2018. "Hydrodynamic modeling of flash flood in mountain watersheds based on high-performance GPU computing," 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. 91(2), pages 567-586, March.
    6. Tian Liu & Zhongmin Liang & Yuanfang Chen & Xiaohui Lei & Binquan Li, 2018. "Long-duration PMP and PMF estimation with SWAT model for the sparsely gauged Upper Nujiang River Basin," 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. 90(2), pages 735-755, January.
    7. Bilal Ahmad Munir & Javed Iqbal, 2016. "Flash flood water management practices in Dera Ghazi Khan City (Pakistan): a remote sensing and GIS prospective," 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. 81(2), pages 1303-1321, March.
    8. Bilal Munir & Javed Iqbal, 2016. "Flash flood water management practices in Dera Ghazi Khan City (Pakistan): a remote sensing and GIS prospective," 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. 81(2), pages 1303-1321, March.
    9. Yumeng Yang & Juan Du & Linlin Cheng & Wei Xu, 2017. "Applicability of TRMM satellite precipitation in driving hydrological model for identifying flood events: a case study in the Xiangjiang River Basin, China," 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. 87(3), pages 1489-1505, July.
    10. A. Fernández Bou & R. Sá & M. Cataldi, 2015. "Flood forecasting in the upper Uruguay River basin," 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. 79(2), pages 1239-1256, November.
    11. Simon Deslauriers & Tew-Fik Mahdi, 2018. "Flood modelling improvement using automatic calibration of two dimensional river software SRH-2D," 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. 91(2), pages 697-715, March.
    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. Pramod Kumar & Vikas Garg & Saurabh Mittal & Y. V. N. Krishna Murthy, 2022. "GIS-based hazard and vulnerability assessment of a torrential watershed," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(1), pages 921-951, January.
    2. Maaz Saleem & Muhammad Arfan & Kamran Ansari & Daniyal Hassan, 2023. "Analyzing the Impact of Ungauged Hill Torrents on the Riverine Floods of the River Indus: A Case Study of Koh E Suleiman Mountains in the DG Khan and Rajanpur Districts of Pakistan," Resources, MDPI, vol. 12(2), pages 1-18, February.
    3. Muhammad Farooq & Muhammad Shafique & Muhammad Shahzad Khattak, 2019. "Flood hazard assessment and mapping of River Swat using HEC-RAS 2D model and high-resolution 12-m TanDEM-X DEM (WorldDEM)," 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(2), pages 477-492, June.
    4. Awais Jabbar & Qun Wu & Jianchao Peng & Ali Sher & Asma Imran & Kunpeng Wang, 2020. "Mitigating Catastrophic Risks and Food Security Threats: Effects of Land Ownership in Southern Punjab, Pakistan," IJERPH, MDPI, vol. 17(24), pages 1-18, December.
    5. Ahmet Ozan Celik & Volkan Kiricci & Canberk Insel, 2017. "Reassessment of the flood damage at a river diversion hydropower plant site: lessons learned from a case study," 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. 86(2), pages 833-847, March.
    6. Chaohui Chen & Yindong Zhang & Yihan Lou & Ziyi Tang & Pin Wang & Tangao Hu, 2024. "Impact of Refined Boundary Conditions of Land Objects on Urban Hydrological Process Simulation," Land, MDPI, vol. 13(11), pages 1-22, November.
    7. María Isabel Arango & Edier Aristizábal & Federico Gómez, 2021. "Morphometrical analysis of torrential flows-prone catchments in tropical and mountainous terrain of the Colombian Andes by machine learning techniques," 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. 105(1), pages 983-1012, January.
    8. Emmanuel Mavhura, 2020. "Learning from the tropical cyclones that ravaged Zimbabwe: policy implications for effective disaster preparedness," 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. 104(3), pages 2261-2275, December.
    9. Nekruz Gulahmadov & Yaning Chen & Aminjon Gulakhmadov & Moldir Rakhimova & Manuchekhr Gulakhmadov, 2021. "Quantifying the Relative Contribution of Climate Change and Anthropogenic Activities on Runoff Variations in the Central Part of Tajikistan in Central Asia," Land, MDPI, vol. 10(5), pages 1-29, May.
    10. Weiwei Jiang & Jingshan Yu, 2022. "Impact of rainstorm patterns on the urban flood process superimposed by flash floods and urban waterlogging based on a coupled hydrologic–hydraulic model: a case study in a coastal mountainous river b," 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. 112(1), pages 301-326, May.
    11. Jingming Hou & Nie Zhou & Guangzhao Chen & Miansong Huang & Guangbi Bai, 2021. "Rapid forecasting of urban flood inundation using multiple machine learning 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(2), pages 2335-2356, September.
    12. Efthimios Karymbalis & Maria Andreou & Dimitrios-Vasileios Batzakis & Konstantinos Tsanakas & Sotirios Karalis, 2021. "Integration of GIS-Based Multicriteria Decision Analysis and Analytic Hierarchy Process for Flood-Hazard Assessment in the Megalo Rema River Catchment (East Attica, Greece)," Sustainability, MDPI, vol. 13(18), pages 1-25, September.
    13. Shahla Azizi & Ali Reza Ilderomi & Hamid Noori, 2021. "Investigating the effects of land use change on flood hydrograph using HEC-HMS hydrologic model (case study: Ekbatan Dam)," 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. 109(1), pages 145-160, October.
    14. Leandro Casagrande & Javier Tomasella & Regina Célia Santos Alvalá & Marcus Jorge Bottino & Rochane Oliveira Caram, 2017. "Early flood warning in the Itajaí-Açu River basin using numerical weather forecasting and hydrological modeling," 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. 88(2), pages 741-757, September.
    15. Louise Fonseca Aguiar & Marcio Cataldi, 2021. "Social and environmental vulnerability in Southeast Brazil associated with the South Atlantic Convergence Zone," 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. 109(3), pages 2423-2437, December.
    16. Wenchao Qi & Chao Ma & Hongshi Xu & Zifan Chen & Kai Zhao & Hao Han, 2021. "A review on applications of urban flood models in flood mitigation strategies," 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 31-62, August.
    17. P. Shirisha & K. Venkata Reddy & Deva Pratap, 2019. "Real-Time Flow Forecasting in a Watershed Using Rainfall Forecasting Model and Updating Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(14), pages 4799-4820, November.
    18. Fernando Mainardi Fan & Dirk Schwanenberg & Rodolfo Alvarado & Alberto Assis dos Reis & Walter Collischonn & Steffi Naumman, 2016. "Performance of Deterministic and Probabilistic Hydrological Forecasts for the Short-Term Optimization of a Tropical Hydropower Reservoir," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(10), pages 3609-3625, August.
    19. Wen-Cheng Liu & Tien-Hsiang Hsieh & Hong-Ming Liu, 2021. "Flood Risk Assessment in Urban Areas of Southern Taiwan," Sustainability, MDPI, vol. 13(6), pages 1-22, March.
    20. Y. Umer & V. Jetten & J. Ettema & L. Lombardo, 2022. "Application of the WRF model rainfall product for the localized flood hazard modeling in a data-scarce environment," 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 1813-1844, March.

    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:98:y:2019:i:2:d:10.1007_s11069-019-03728-8. 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.