Efficiency of Some Meteorological Drought Indices in Different Time Scales (Case Study: Tajan Basin, Iran)

Authors
S. Mashari Eshghabad 1
E. Omidvar 2
K. Solaimani 2
1 Faculty of Agriculture and Natural Resources, Hormozgan University, Bandar Abbas, Iran
2 Faculty of Natural Resources, Sari Agricultural Sciences and Natural Resources University, Sari, Iran
Abstract
Drought is a climatic phenomenon that causes much detrimental influence on ecological environments. This research investigates the performance of meteorological drought indices in different time scales in theTajan basin in Iran. Indices undergone in this study include: Percent Normal Precipitation Index (PNPI), Z-Score Index (ZSI), Standard Precipitation Index (SPI), China Z Index (CZI), Modified CZI (MZCI), and Decile Precipitation Index (DPI). In this study, we used data of annual and monthly precipitation from meteorological stations in the basin. Drought indices were determined at time scales of 1, 3, 6, 9, 12, 18, 24 year of minimum precipitation with very intense drought and the method of correlation coefficients between drought indices values and monthly precipitation. The results showed that DPI was the best index at annual time scale, while at the time scale of 1,6,12 and 24-months, PNPI was the best index. MCZI was the best index for time scales of 9 and 48-months, and the ZCI had the maximum efficiency for a three-month scale.
Keywords
Drought
Drought indices
Precipitation data
Tajan basin
Alternate Hydro Energy Center. Guidelines on Project Hydrology. Indian Inst. Technol., 2011; 21 P.
Bonaccorso, B., Bordi, I., Cancielliere, A., Rossi, G. and Sutera, A. Spatial variability of drought: an analysis of the SPI in Sicily. Water Resour. Manag., 2003; 17: 273-296.
Caccamo, G., Chisholm, L.A., Bradstock, R.A. and Puotinen, M.L. Assessing the sensitivity of MODIS to monitor drought in high biomass ecosystems. Int. J. Appl. Earth. Obs. 2012; 18: 119-127.
Dalezios, N.R., Loucas, A.,Vasiliades, L. and Liakopoulos, E. Severity-Duration-Frequency Analysis of Droughts and Wet Periods in Greece. Hydrolog. Sc. J., 2000; 45: 751-769.
DHV Consultants BV and DELFT HYDRAULICS, Hydrology Project Training Module: How to correct and complete rainfall data. World Bank and Government of The Netherlands funded. Version 1999; 99P.
Dracup, J.A., KS. Lee, and E.G. Paulson, Jr. On the Definition of Drought. Water Resour. Res., 1980; 16: 297-302.
Dogan, S., Berktay, A. and Singh, V.P. Comparison of multi-monthly rainfall-based drought severity indices, with application to semi-arid Konya closed basin, Turkey. J. Hydrol., 2012; 470-471: 255-268.
Ensafi Moghaddam, T. An Investigation and assessment of climatological indices and determination of suitable index for climatological droughts in the Salt Lake Basin of Iran. Iranian J. Range Desert Res., (Abstract in English). 2007; 14(2): 271-288.
Gibbs, W.J. and Maher, J.V. Rainfall deciles as drought indicators. Bureau of Meteorology. Australia-Melburne. 1967; 118.
Goddard, S., Harms, S.K., Reichenbach, S.E., Tadesse, T. and Waltman, W.J. Geospatial decision support for drought risk management. Communication of the ACM. 2003; 46: 35-37.
Ezzine, H., Bouziane, A. and Ouazar, D. Seasonal comparisons of meteorological and agricultural droughtindices in Morocco using open short time-series data. Int. J. Appl. Earth. Obs. 2014; 26: 36-48.
Kendall, M.G. and Stuart, A. The advanced theory of statistics. Charles Griffin and Company: London, High Wycombe. 1997; 599.
Khalili, A. and BazrAfshan, J. Assessment of meteorological drought indices for some of different climates of Iran. J. NIVAR. 2003; 48: 79-93.
Lana, X. and Burgueno, A. Spatial and temporal characterization of annual extreme droughts in Catalonia (northeast Spain). Int. J. Climatol., 1998; 18: 93-110.
Loukas, A. and Vasiliades, L. Identification of the relationship between meteorological and hydrological drought. Geophys. Res. Abstr., 2005; 7: 05479.
Loukas, A. and Vasiliades, L. Probabilistic analysis of drought spatiotemporal characteristics in Thessaly region, Greece. Nat. Hazards Earth Sys. Sci., 2004; 4: 719-731.
Loukas, A., Vasilides, L. and Dalezios, N.R. Inter comparision of meteorological drought indices for drought assessment and monitoring in Greece.8 th International Conference on Environmental Science and Technology, Lemons Island, Greece, 8-10 September 2003; 484-491.
McKee, T.B., Doesken, N.J. and Kleist, J. The relationship of drought frequency and duration to time scales. Eighth Conference on Applied Climatology, Am. Meteorol. Soci., Boston, U.S. 17-22 Jan 1993; 179-184.
Mcmahon, T.A. River and Reservoir Yield. Water resources publications, United States. 1986; 368.
Mendicino, G., Senatore, A. and Versace, P. A. Groundwater Resource Index (GRI) for drought monitoring and forecasting in a mediterranean climate. J. Hydrol., 2008; 357: 282-302.
Moradi, H. R, Rajabi, M. and Farajzadeh, M. Investigation of meteorological drought characteristics in Fars province, Iran. Catena., 2011; 84: 35-46.
Moreira, Elsa E., Coelho, Carlos A., Paulo, Ana A., Pereira, Luís S. and Mexia, João T. SPI-based drought category prediction using loglinear models. J. Hydrol., 2008; 354: 116-130.
Morid, S., Smakhtin, V. and Moghaddasi, M., Comparison of seven meteorological indices for drought monitoring in Iran. Int. J. Climatol., 2006; 26: 971-985.
Paulo, A.A., Ferreira, E., Coelho, C. and Pereira, L.S. Drought class transition analysis through Markov and Loglinear models, an approach to early warning. Agr. Water Manage., 2005; 77: 59-81.
Pereira, L.S., Cordery, I. and Iacovides, I. Coping with Water Scarcity. UNESCO IHP VI, Tech. Doc. Hydrol., UNESCO, Paris. 2002; 269.
Piechota, T.C. and Dracup, J.A. Drought and Regional Hydrologic Variation in the United States: Associations with the El Niño-Southern Oscillation. Water Resour. Res., 1996; 32: 1359-1373.
Richard, R.H. A Review of Twentieth Century Drought Indices Used in the United States. Am. Meteorol. Soci. 2002; 167: 1149-1165.
Vicente-Serrano, S.M. and Lopez-Moreno, J.I. Hydrological response to different time scales of climatological drought: an evaluation of the Standardized Precipitation Index in a mountainous Mediterranean basin. Hydrol. Earth Syst. Sc., 2005; 9: 523-533.
Sivakumar, M.V.K. and Wilhite, D.A. Drought preparedness and drought management. Drought Mitigation and Prevention of Land Desertification, University of Ljubljana, Slovenia, 21-25 April 2002; (CD-ROM paper 2).
Smakhtin, V.U. and Hughes, D.A. Automated estimation and analyses of meteorological drought characteristics from monthly rainfall data. Environ. Modell. Softw., 2007; 22(6): 880-890.
Tadesse, T., Wilhite, D.A., Harms, S.K., Hayes, M.J. and Goddard, S. Drought Monitoring Using Data Mining Techniques: A Case Study for Nebraska. USA Natural Hazard., 2004; 33: 137-159.
Tadesse, T., Brown, J. and Hayes, M. A new approach for predictingdrought-related vegetation stress: integrating satellite, climate, and biophysical data over the U.S. central plains. ISPRS J. Photogramm. 2005; 59: 244-253.
Vafakhah, M. and Rajabi, M. Efficiency of meteorological drought Indices for monitoring and assessment of drought in Bakhtegan, Tashk, and Maharlo Lakes Watershed. Biaban J., 2005; 10: 369-382.
Vasiliades, L. and Athanasios, L. Hydrological response to meteorological drought using the Palmer drought indices in Thessaly, Greece. Desalination., 2009; 237:3-21.
Vicente-Serrano, S.M., Cuadrat, J.M. and Romo, A. Early prediction of crop productions using drought indices at different time scales and remote sensing data: application in the Ebro valley (North-east Spain). Int. J. Remote Sens., 2006; 27:511-518.
World Meteorological Organization (WMO). Early Warning Systems for Drought Preparedness andDrought Management. Donald, A.W., Sivakumar, M.V.K. and Deborah A. W. (Ed.). Lisbon. 2000; 101-118.
Wu, H., Hayes, M.J., Weiss, A. and Hu, Q. An evaluation of the Standardized Precipitation Index, the China-Z Index and the statistical Z-Score. Int. J. Climatol., 2001; 21: 745-758.
ECOPERSIA
Volume 2, Issue 1 - Serial Number 7
March 2014
Pages 441-453