Uses of Precipitation-Based Climate Indices in Drought Characterization
This article has a reply.
VIEW THE REPLYThis article has a reply.
VIEW THE REPLYPublication: Journal of Hydrologic Engineering
Volume 22, Issue 8
Abstract
The standardized precipitation index (SPI) is widely used in meteorological drought classification on a monthly or seasonal scale. A new monthly drought classification scheme using daily precipitation–based climate indices—consecutive two dry days (CDD2), maximum one-day rainfall (RX1), and maximum five-day rainfall (RX5)—is attempted in this study. A rule was created to derive the drought class from climate indices using northwest Indiana regional rainfall. The U.S. Drought Monitor, which uses the SPI for drought classification, was compared with the proposed new drought classification scheme. The SPIs derived using monthly data do not have a bearing on extreme precipitation indices because of lumping. This study hypothesizes that the climate indices can improve drought classification on a monthly/seasonal scale. The results are validated using the northwest Upper Mississippi and northeastern Indiana regions. The new classification and the SPI are very similar in most of the months, when the indices and monthly rainfall deviate similarly from normal values. The proposed reclassification incorporates stress to the watershed system when a major portion of the monthly rainfall is due to one or two events. It also captures deviations in the climate indices from normal values and uses them in the classification.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The authors acknowledge the Illinois Indiana Sea Grant College Program for providing the funds to support this research. The authors also acknowledge the anonymous reviewers for their valuable suggestions.
References
Almedeij, J. (2014). “Drought analysis for Kuwait using standard precipitation index.” ⟨https://doi.org/10.1155/2014/451841⟩ (Mar. 2015).
Bartholy, J., and Pongracz, R. (2007). “Regional analysis of extreme temperature and precipitation indices for the Carpathian Basin from 1946 to 2001.” Global Planet. Change, 57(1), 83–95.
Bonaccorso, B., Peres, D. J., Castano, A., and Cancelliere, A. (2014). “SPI-based probabilistic analysis of drought areal extent in Sicily.” Water Resour. Manage., 29(2), 459–470.
Cancelliere, A., Mauro, G. D., Bonaccorso, B. G., and Rossi, G. (2007). “Drought forecasting using the standardized precipitation index.” Water Resour. Manage., 21(5), 801–809.
Chanda, K., and Maity, R. (2015). “Meteorological drought quantification with standardized precipitation anomaly index for the regions with strongly seasonal and periodic precipitation.” J. Hydrol. Eng., 06015007.
Chandramouli, V., Mohammad, K., and Teegavarappu, R. (2013). “Examining climate indices in the midwest region to examine droughts.” Proc., World Environmental Water Resources Congress, ASCE, Reston, VA, 1157–1163.
Colorado State University. (2005). “Colorado climate center.” ⟨http://ccc.atmos.colostate.edu/pub/spi.pdf⟩.
Edwards, D. C., and McKee, T. B. (1997). “Characteristics of 20th century drought in the United States at multiple time scales.”, Colorado State Univ., Fort Collins, CO.
Gocic, M., and Trajkovic, S. (2014). “Spatiotemporal characteristics of drought in Serbia.” J. Hydrol., 510, 110–123.
Guttman, N. B. (1998). “Comparing the Palmer drought index and the standardized precipitation index.” J. Am. Water Resour. Assoc., 34(1), 113–121.
Hao, C., Zhang, J., and Yao, F. (2015). “Combination of multi-sensor remote sensing data for drought monitoring over Southwest China.” Int. J. App. Earth Obs. Geoinf., 35, 270–283.
Hayes, M. J., Svoboda, M. D., Wilhite, D. A., and Vanyarkho, O. V. (1999). “Monitoring the 1996 drought using the standardized precipitation index.” Bull. Am. Meteorol. Soc., 80(3), 429–438.
Kao, S. C., and Govindaraju, R. S. (2010). “A copula-based joint deficit index for droughts.” J. Hydrol., 380(1), 121–134.
Lloyd-Hughes, B., and Saunders, M. A. (2002). “A drought climatology for Europe.” Int. J. Climatol., 22(13), 1571–1592.
Mallya, G., Tripathi, S., Kirshner, S., and Govindaraju, R. S. (2013). “Probabilistic assessment of drought characteristics using hidden Markov model.” J. Hydrol. Eng., 834–845.
Mays, L. W. (2005). Water resources engineering, Wiley, New York.
McKee, T. B., Doesken, N. J., and Kleist, J. (1993). “The relationship of drought frequency and duration of time scales.” Proc., 8th Conf. on Applied Climatology, American Meteorological Society, Anaheim, CA, 179–186.
Mishra, A. K., and Singh, V. P. (2010). “A review of drought concepts.” J. Hydrol., 391(1), 202–216.
NOAA (National Oceanic and Atmospheric Administration). (2005). “National climatic data center (NCDC).” ⟨https://www.ncdc.noaa.gov/⟩.
Núñez, J., Rivera, D., Oyarzún, R., and Arumí, J. L. (2014). “On the use of standardized drought indices under decadal climate variability: Critical assessment and drought policy implications.” J. Hydrol., 517, 458–470.
Palmer, W. C. (1965). Meteorological drought, U.S. Weather Bureau, Washington, DC.
Palmer, W. C. (1968). “Keeping track of crop moisture conditions, nationwide: The new crop moisture index.” Weatherwise, 21(4), 156–161.
Rhee, J., Im, J., and Carbone, G. J. (2010). “Monitoring agricultural drought for arid and humid regions using multi-sensor remote sensing data.” Remote Sens. Environ., 114(12), 2875–2887.
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., Int. Western Snow Conf., Colorado State Univ., Fort Collins, CO, 164–175.
Svaboda, M., et al. (2002). “The drought monitor.” Am. Meteorol. Soc., 83(8), 1181–1190.
Teegavarapu, R. S. V., and Chandramouli, V. (2005). “Improved weighing methods, deterministic and stochastic data driven models for estimation of missing precipitation records.” J. Hydrol., 312(1), 191–206.
Teegavarapu, R. S. V., Goly, A., Chandramouli, V., and Behera, P. (2012). “Precipitation extremes and climate change: Evaluation using descriptive WMO indices.” Proc., World Environmental Water Resources Congress, ASCE, Reston, VA, 1927–1936.
Thom, H. C. S. (1966). Some methods of climatological analysis, World Meteorological Organization, Geneva, 53.
Tsakiris, G., and Vangelis, H. (2004). “Towards a drought watch system based on spatial SPI.” Water Res. Manage., 18(1), 1–12.
University of Nebraska Lincoln. (2005). “National drought mitigation center (NDMC).” ⟨http://drought.unl.edu/MonitoringTools/DownloadableSPIProgram.aspx⟩.
WGA (Western Governors’ Association). (2004). Creating a drought early warning system for the 21st century—The national integrated drought information system, Denver.
Wilhite, D. A., and Glantz, M. H. (2009). “Understanding the drought phenomenon: The role of definitions.” Water Int., 10(3), 111–120.
WMO (World Meteorological Organization). (2012). “Standardized precipitation index, user guide.” WMO. No. 1090, Geneva.
Zarch, M. A. A., Sivakumar, B., and Sharma, A. (2015). “Drought in a warming climate: A global assessment of standard precipitation index (SPI) and reconnaissance drought index (RDI).” J. Hydrol., 526, 183–195.
Information & Authors
Information
Published In
Copyright
©2017 American Society of Civil Engineers.
History
Received: Apr 16, 2015
Accepted: Feb 22, 2017
Published online: May 13, 2017
Published in print: Aug 1, 2017
Discussion open until: Oct 13, 2017
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.