Regional Hydrological Drought Monitoring Using Principal Components Analysis
Publication: Journal of Irrigation and Drainage Engineering
Volume 142, Issue 1
Abstract
Drought quantification is a decision-making approach for water resources planners and managers. There are different statistical methods for regional quantification of droughts, depending on the event being regionally discrete or continuous. Calculating a drought index in the measured grid points of a given region is a prerequisite for the regionalization process of drought by these methods. The aim of this study is the regional analysis of the streamflow drought using the multivariate technique of principal components analysis (PCA). To this end, the streamflow drought index (SDI) was calculated in the seven hydrometric stations of the Sefid-Rud basin in Iran for the period of 1984–2013 in seasonal (winter, spring, summer, and autumn), semiannual (October–March and May–September), and annual (October–September) time scales. Regional monitoring of the SDI was carried out using the PCA technique summarizing the SDI series of all stations into a new series, the so-called the multivariate streamflow drought index (MSDI). The MSDI series at each time scale were analyzed from several statistical aspects. Results showed that there are relatively high correlations between the SDI series of the stations for given time scales. The first principal component () explains 58–85% of the regional variations of the SDI series at the mentioned time scales. The MSDI series at multiple time scales follow all stations’ SDI fluctuations and appropriately monitor droughts that occurred in the region, especially in long dry periods. The dry and wet severity classes derived from the MSDI series greatly corresponded to those of the SDI time series on different stations. The highest percentage of correspondence between MSDI and SDIs was calculated for the semiannual time scale and the lowest for the spring season.
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References
Allen, P. M., Harmel, R. D., Dunbar, J. A., and Arnold, J. G. (2011). “Upland contribution of sediment and runoff during extreme drought: A study of the 1947–1956 drought in the Blackland Prairie, Texas.” J. Hydrol., 407(1–4), 1–11.
Bazrafshan, J., Hejabi, S., and Rahimi, J. (2014). “Drought monitoring using the multivariate standardized precipitation index (MSPI).” Water Resour. Manage., 28(4), 1045–1060.
Bonaccorso, B., Bordi, I., Cancielliere, A., Rossi, G., and Sutera, A. (2003). “Spatial variability of drought: An analysis of the SPI in Sicily.” Water Resour. Manage., 17(4), 273–296.
Bordi, I., Fraedrich, K., Jiang, J. M., and Sutera, A. (2004). “Spatio-temporal variability of dry and wet periods in eastern China.” Theor. Appl. Climatol., 79(1–2), 81–91.
Cancelliere, A., Di Mauro, G., Bonaccorso, B., and Rossi, G. (2007). “Drought forecasting using the standardized precipitation index.” Water Resour. Manage., 21(5), 801–819.
Dai, A. (2011). “Drought under global warming: A review.” Wiley Interdiscip. Rev. Clim. Change, 2(1), 45–65.
Gumbel, E. J. (1963). “Statistical forecast of droughts.” Bull. Int. Assoc. Sci. Hydrol., 8(1), 5–23.
Heim, R. R. (2002). “A review of twentieth-century drought indices used in the United States.” Bull. Am. Meteorol. Soc., 83(8), 1149–1165.
Iranian Nation Organization of Surveying. (2013). “Technical service management datasets archives: Digital elevation model.” 〈http://tsm.ncc.org.ir/〉 (May 1, 2014).
Keyantash, J., and Dracup, J. A. (2004). “An aggregate drought index: Assessing drought severity based on fluctuations in the hydrologic cycle and surface water storage.” Water Resour. Res., 40(9), W09304.
McKee, T. B., Doesen, N. J., and Kleist, J. (1993). “The relationship of drought frequency and duration to time scales.” Proc., 8th Conf. on Applied Climatology, Anaheim, CA, 179–184.
Mishra, A. K., and Desai, V. R. (2005). “Drought forecasting using stochastic models.” Stochastic Environ. Res. Risk Assess., 19(5), 326–339.
Mishra, A. K., and Singh, V. P. (2010). “A review of drought concepts.” J. Hydrol., 391(1–2), 202–216.
Nalbantis, I. (2008). “Evaluation of a hydrological drought index.” Eur. Water, 23(24), 67–77.
Nalbantis, I., and Tsakiris, G. (2009). “Assessment of hydrological drought revisited.” Water Resour. Manage., 23(5), 81–97.
Özger, M., Mishra, A. K., Singh, V. P. (2012). “Long lead time drought forecasting using a wavelet and fuzzy logic combination model.” J. Hydrometeorol., 13(1), 284–297.
Palmer, W. C. (1965). “Meteorological drought.”, U.S. Dept. of Commerce Weather Bureau Research, Washington, DC.
Panu, U. S., and Sharma, T. C. (2002). “Challenges in drought research: Some perspectives and future directions.” J. Hydrol. Sci., 47, S19–S30.
Paulo, A. A., and Pereira, L. S. (2008). “Stochastic prediction of drought class transitions.” Water Resour. Manage., 22(9), 1277–1296.
Raziei, T., Bordi, I., and Pereira, L. S. (2011). “An application of GPCC and NCEP/NCAR datasets for drought variability analysis in Iran.” Water Resour. Manage., 25(4), 1075–1086.
Shafer, B. A., and Dezman, L. E. (1982). “Development of a Surface Water Supply Index (SWSI) to assess the severity of drought conditions in snowpack runoff areas.” Proc., 50th Annual Western Snow Conf., Western Snow Conference, Reno, NV, 164–75.
Shahabfar, A., and Eitzinger, J. (2011). “Agricultural drought monitoring in semi-arid and arid areas using MODIS data.” J. Agric. Sci., 149(04), 403–414.
Sharma, S. (1996). Applied multivariate techniques, Wiley.
Sharma, T. C., and Panu, U. S. (2012). “Prediction of hydrological drought durations based on Markov chains: Case of the Canadian prairies.” Hydrol. Sci. J., 57(4), 705–722.
Snedecor, G. W., and Cochran, W. G. (1989). Statistical methods, 8th Ed., Iowa State Univ. Press, Ames, IA.
Sonmez, F. K., Komuscu, A. U., Erkan, A., and Turgu, E. (2005). “An analysis of spatial and temporal dimension of drought vulnerability in Turkey using the standardized precipitation index.” Nat. Hazards, 35(2), 243–264.
UN Secretariat General. (1994). “United Nations Convention to combat drought and desertification in countries experiencing serious droughts and/or desertification, particularly in Africa.” Paris.
Webster, K. E., Kratz, T. M., Bowser, C. J., and Adagnuson, J. J. (1996). “The influence of landscape position on lake chemical responses to drought in northern Wisconsin.” Limnol. Oceanogr., 41(5), 977–984.
Wilks, D. S. (2011). Statistical methods in the atmospheric sciences, 3rd Ed., Academic, London.
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Journal of Irrigation and Drainage Engineering
Volume 142 • Issue 1 • January 2016
Copyright
© 2015 American Society of Civil Engineers.
History
Received: Sep 3, 2014
Accepted: Apr 27, 2015
Published online: Jun 23, 2015
Discussion open until: Nov 23, 2015
Published in print: Jan 1, 2016
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