Probabilistic assessment of drought characteristics using hidden markov model

Journal of Hydrologic Engineering

Volumn 18, Issue 7, 2013, Pages 834-845

  Mallya, Ganeshchandra ^a   Tripathi, Shivam ^b   Kirshner, Sergey ^c   Govindaraju, Rao S ^d  

^a PURDUE UNIVERSITY   (United States)

^b INDIAN INSTITUTE OF TECHNOLOGY KANPUR   (India)

^c PURDUE UNIVERSITY   (United States)

^d PURDUE UNIVERSITY   (United States)

Author keywords

Drought index; Droughts; Hidden markov models; Probabilistic assessment

Indexed keywords

CLASSIFICATION RESULTS; DROUGHT CHARACTERISTICS; DROUGHT CLASSIFICATIONS; DROUGHT INDICES; HYDROLOGICAL VARIABLES; MODEL UNCERTAINTIES; PROBABILISTIC ASSESSMENTS; PROBABILISTIC CLASSIFICATION;

HIDDEN MARKOV MODELS; STREAM FLOW; UNCERTAINTY ANALYSIS;

DROUGHT;

DROUGHT; MARKOV CHAIN; NUMERICAL MODEL; PRECIPITATION (CLIMATOLOGY); PROBABILITY; SPATIOTEMPORAL ANALYSIS; STREAMFLOW;

INDIANA; UNITED STATES;

EID: 84881344718     PISSN: 10840699     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)HE.1943-5584.0000699     Document Type: Article

References (32)

1. Bowman, A. W., and Azzalini, A. (1997). Applied smoothing techniques for data analysis, Oxford University Press, New York.
2. Cover, T. M., and Thomas, J. A. (2001). Elements of information theory, Wiley-Interscience, New York.
3. Dai, A. (2011). "Drought under global warming: A review." Clim. Change, 2(1), 45-65.
4. Dracup, J. A., Lee, K. S., and Paulson, E. G. P., Jr. (1980). "On the definition of droughts." Water Resour. Res., 16(2), 297-302.
5. FEMA. (1995). National mitigation strategy, Washington, DC.
6. Friedman, D. G. (1957). "The prediction of long-continuing drought in south and southwest Texas." Occasional Papers Meteorology, No. 1, The Travelers Weather Research Center, Hartford, CT, 182.
7. Guttman, N. B. (1999). "Accepting the standardized precipitation index: A calculation algorithm." J. Am. Water Resour. Assoc., 35(2), 311-322.
8. Hao, Z., and Singh, V. P. (2012). "Entropy based method for bivariate drought analysis." J. Hydrol. Eng., 1(1), 425.
9. Hayes, M. J., Wilhelmi, O. V., and Knutson, C. L. (2004). "Reducing drought risk: Bridging theory and practice." Nat. Hazards Rev., 5(2), 106-113.
10. Heim, R. R. (2002). "A review of twentieth-century drought indices used in the United States." Bull. Am. Meteorol. Soc., 83(8), 1149.
11. Kao, S.-C., and Govindaraju, R. S. (2010). "A copula-based joint deficit index for droughts." J. Hydrol., 380(1-2), 121-134.
12. Kim, T.-W., and Valdés, J. B. (2003). "Nonlinear model for drought forecasting based on a conjunction of wavelet transforms and neural networks." J. Hydrol. Eng., 8(6), 319-328.
13. Kim, T.-W., Valdés, J. B., and Yoo, C. (2006). "Nonparametric approach for bivariate drought characterization using Palmer drought index." J. Hydrol. Eng., 11(2), 134-143.
14. Lloyd-Huges, B., and Saunders, M. A. (2002). "A drought climatology for Europe." Int. J. Climatol., 22(13), 1571-1592.
15. Madadgar, S., and Moradkhani, H. (2012). "Drought analysis under climate change using copula." J. Hydrol. Eng., 1(1), 357.
16. Mallya, G. (2011). Hidden Markov model based probabilistic assessment of droughts, Purdue Univ., West Lafayette, IN.
17. Mallya, G., Tripathi, S., and Govindaraju, R. S. (2010). "Assessment of drought characteristics using graphical models." Frontiers of interface between statistics and sciences, CR Rao Advanced Institute of Mathematics, Statistics & Computer Science, University of Hyderabad, Hyderabad, AP, 565-575.
18. McKee, T. B., Doesken, N. J., and Kleist, J. (1993). "The relationship of drought frequency and duration to time scales." Proc., 8th Conf. of Applied Climatology, American Meteorological Society, Anaheim, CA, 179-184.
19. Mishra, A. K., Desai, V. R., and Singh, V. P. (2007). "Drought forecasting using a hybrid stochastic and neural network model." J. Hydrol. Eng., 12(6), 626-638.
20. Mishra, A. K., and Singh, V. P. (2010). "A review of drought concepts." J. Hydrol., 391(1-2), 202-216.
21. Rabiner, L. R. (1989). "A tutorial on hidden Markov models and selected applications in speech recognition." Proc. IEEE, 77(2), 257-286.
22. Reynolds, D. A., and Rose, R. C. (1995). "Robust text-independent speaker identification using Gaussian mixture speaker models." IEEE Trans. Speech Audio Process., 3(1), 72-83.
23. Robertson, A. W., Kirshner, S., and Smyth, P. (2003). "Hidden Markov models for modeling daily rainfall occurrence over Brazil." Technical Report UCI-ICS, 3-27.
24. Robertson, A. W., Kirshner, S., and Smyth, P. (2004). "Downscaling of daily rainfall occurrence over northeast Brazil using a hidden Markov model." J. Clim., 17(22), 4407-4424.
25. Shannon, C. E., and Weaver, W. (1949). The mathematical theory of communication, University of Illinois Press, Urbana, IL.
26. Shin, H.-S., and Salas, J. D. (2000). "Regional drought analysis based on neural networks." J. Hydrol. Eng., 5(2), 145-155.
27. Shukla, S., and Wood, A. W. (2008). "Use of a standardized runoff index for characterizing hydrologic drought." Geophys. Res. Lett., 35(2), L02405.
28. Svoboda, M., et al. (2002). "The drought monitor." Bull. Am. Meteorol. Soc., 83(8), 1181-1190.
29. Thyer, M., and Kuczera, G. (2003). "A hidden Markov model for modelling long-term persistence in multi-site rainfall time series 1. Model calibration using a Bayesian approach." J. Hydrol., 275(1-2), 12-26.
30. Tripathi, S., and Govindaraju, R. S. (2009). "On the identification of intra-seasonal changes in the Indian summer monsoon." Proc., 3rd Int. Workshop on Knowledge Discovery from Sensor Data, Sensor KDD '09, Association for Computing Machinery, New York, 62-70.
31. Vicente-Serrano, S. (2006). "Differences in spatial patterns of drought on different time Scales: An analysis of the Iberian peninsula." Water Resour. Manage., 20(1), 37-60.
32. Wong, G., et al. (2010). "Drought analysis using trivariate copulas conditional on climatic states." J. Hydrol. Eng., 15(2), 129-141.