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SIMULATING FLOOD OF MAOZHOU WATERSHED WITH DISTRIBUTED HYDROLOGICAL MODEL

Yangbo Chen, Luying Pan, Peng Dou, Yanyang Wang

First published: 2017-06-20https://doi.org/10.5593/sgem2017/31/s12.074View metrics

Abstract

Maozhou watershed is a highly urbanized watersheds in southern China that is a typical watershed in ChinaпїЅs rapid urbanization. Changed land use/cover(LUC) within the watershed changed the flood response, that requires the model parameter updating with the LUC changes induced by urbanization to have an accurate flood forecasting. Flooding in Maozhou watershed is serious, which was aggravated by increased urban land area within the watershed. Accurately forecasting the flood of Maozhou watershed is imperative, but currently there is no effective flood forecasting model to be used for the flood forecasting of Maozhou river. Hydrological models used for flood forecasting are usually categorized as lumped hydrological models and distributed hydrological models, with the latter the latest development. Distributed hydrological model derives model parameters directly from the watershed terrain properties, so has the potential to update model parameters with the changed terrain properties if it could be acquired. In this study, the Liuxihe model, a physically based distributed hydrological model is employed to simulate the flood processes of Maozhou watershed, and the latest LUCs were estimated by using SVM algorithm for updating the model parameters. The result shows that Liuxihe model could be used for the flood forecasting of Maozhou watershed.

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Publication details

Title
SIMULATING FLOOD OF MAOZHOU WATERSHED WITH DISTRIBUTED HYDROLOGICAL MODEL
Authors
Yangbo Chen, Luying Pan, Peng Dou, Yanyang Wang
Proceedings
SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings; 17th International Multidisciplinary Scientific GeoConference SGEM2017, Water Resources. Forest, Marine and Ocean Ecosystems
Publisher
STEF92 Technology
Year
2017
Pages
593-600
SWS Citekey
Chen201712593600
ISSN
1314-2704
ISBN
978-619-7408-04-1
Language
en
Publication type
Conference Paper
Keywords
References15
  1. Hollis G. E., The effect of urbanization on floods of different recurrence interval, Water Resour. Res., 11/3, pp 431-435, 1975.

  2. Refsgaard J. C., and Storm B., Construction, calibration and validation of hydrological models, In: Abbott M. B. and Refsgaard J. C.(Eds.), Distributed Hydrological Modelling, Kluwer Academic, pp. 41-54, 1996.

  3. USDA, National engineering handbook, section 4, hydrology. USDA, Soil Conservation Service. US Government Printing Office, Washington, DC, 1972.

  4. Zhao R. J., Flood Forecasting Method for Humid Regions of China, East China College of Hydraulic Engineering, Nanjing, China, 1977.

  5. Abbott M. B. et al., An Introduction to the European Hydrologic System-System Hydrologue Europeen, ‘SHE’, a: History and Philosophy of a Physically-based, Distributed Modelling System, Journal of Hydrology, 87, pp 45-59,1986.

  6. Vieux B. E., and Vieux, J. E., VfloTM: A Real-time Distributed Hydrologic Model, In: Proceedings of the 2nd Federal Interagency Hydrologic Modeling Conference, July 28-August 1, Las Vegas, Nevada. Abstract and paper on CD-ROM, 2002.

  7. Liu Z., Mario L. V. M, Todini E., Flood forecasting using a fully distributed model: application of the TOPKAPI model at the upper Xixian Catchment, Hydrology and Earth System Sciences, 9/4, pp 347-364, 2005.

  8. Treitz P. M., Howard P. J., and Gong P., Application of satellite and GIS technologies for land-cover and land use mapping at the rural-urban fringe: a case study, Photogrammetric Engineering and Remote Sensing, 58, pp 439-448, 1992.

  9. Zhu G. B., Blumberg D. G., Classification using ASTER data and SVM algorithms: the case study of Beer Sheva, Israel, Remote Sensing of Environment, 80/2, pp 233-240, 2002.

  10. Kavzoglu T., Mather P. M., The use of back propagating artificial neural networks in land cover classification, International Journal of Remote Sensing, 24, pp 4907-4938, 2003.

  11. Yang C., Bruzzone L., Sun F. Y., A Fuzzy-Statistics-Based Affinity Propagation Technique for Clustering in Multispectral Images, IEEE Transactions on Geoscience and Remote Sensing, 48/6, pp 2647-2659, 2010.

  12. Chen Y., Ren Q., Huang F., Xu H., and Cluckie I., Liuxihe Model and its modeling to river basin flood, Journal of Hydrologic Engineering, 16, pp 33-50, 2011.

  13. Jensen S. K., and Dominggue J. O., Extracting topographic structure from digital elevation data for geographic information system analysis, Photogramm. Eng. Remote Sens., 54/11, pp 1593-1600, 1988.

  14. Strahler A. N., Quantitative analysis of watershed Geomorphology, Transactions of the American Geophysical Union, 8/6, pp 913-920, 1957.

  15. Arya L. M., and Paris J. F., A physioempirical model to predict the soil moisture characteristic from particle-size distribution and bulk density data, Soil Sci. Soc. Am. J., 45, pp 1023-1030, 1981.

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