Drought and Flood Distribution Variation Based on SPI in Nanjing, China

Article Preview

Abstract:

Many drought and flood indices have been developed, the Standardized Precipitation Index (SPI) is one which has various temporal scales together to form an overall judgment of drought and flood and can be applied easily to different locations to identify and monitor drought and flood. Take Nanjing, China in the study as an example to analysis drought and flood variation by computing SPI values of four time scales including 3-months, 6-months, 12-months and 24-months, applying precipitation data from 1946-2000 of the study area. The results demonstrated SPI can be appropriate to analyze drought and flood variation of Nanjing, while the precipitation data were divided into three stages(1946-1963,1964-1981,1982-2000), the frequencies of various drought and flood classes from various time scales are different, particularly 12-months and 24-months. The time series is longer, the frequencies are more reliable and the differences more little.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

2116-2120

Citation:

Online since:

February 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Vogt, J.V., Somma, F. (Eds. ), 2000. Drought and Drought Mitigation in Europe. Kluwer, Dordrecht.

Google Scholar

[2] Hayes, M.J., 2006. Drought indices. <http: /drought. unl. edu/ whatis/indices. htm>.

Google Scholar

[3] McKee, T.B., Doesken, N.J., Kleist, J., 1993. The relationship of drought frequency and duration to time scales. In: Proceedings of the Eighth Conference on Applied Climatology. American Meteorological Society, Boston, p.179–184.

Google Scholar

[4] McKee, T.B., Doesken, N.J., Kleist, J., 1995. Drought monitoring with multiple time scales. In: Proceedings of the Ninth Conference on Applied Climatology. Am. Meteor. Soc., Boston, p.233–236.

Google Scholar

[5] Hayes, M.J., Svoboda, M., Le Comte, D., Redmond, K.T., Pasteris, P., 2007. Drought monitoring: new tools for the 21st century. In: Wilhite, D.A. (Ed. ), Drought and Water Crisis. Science, Technology, and Management Issues. Taylor & Francis, Boca Raton, p.53.

DOI: 10.1201/9781420028386.ch3

Google Scholar

[6] Moreira, E.E., Paulo, A.A., Pereira, L.S., Mexia, J.T., 2006. Analysis of SPI drought class transitions using loglinear models. J. Hydrol. 331, 349–359.

DOI: 10.1016/j.jhydrol.2006.05.022

Google Scholar

[7] Moreira, E.E., Coelho, C.A., Paulo, A.A., Pereira, L.S., Mexia, J.T., 2008. SPI-based drought category predication using loglinear models. J. Hydrol. 354, 116–130.

DOI: 10.1016/j.jhydrol.2008.03.002

Google Scholar

[8] Luxin Zhai, Qi Feng, Dryness/wetness climate variation based on standardized precipitation index in Northwest China[J]. Journal of Natural Resources. 2011, 26(5), 847-857(in Chinese).

Google Scholar