Stochastic multi-site generation of daily rainfall occurrence in south Florida

Stochastic Environmental Research and Risk Assessment

Volumn 22, Issue 6, 2008, Pages 705-717

  Kim, Tae woong ^a   Ahn, Hosung ^b   Chung, Gunhui ^c   Yoo, Chulsang ^d  

^a Hanyang University   (South Korea)

^b U S NUCLEAR REGULATORY COMMISSION   (United States)

^c University of Arizona   (United States)

^d Korea University   (South Korea)

Author keywords

Daily rainfall; Markov process; Occurrence; Space time model

Indexed keywords

DAILY RAINFALL; DAILY RAINFALL AMOUNTS; DEPENDENT PROCESS; DIRECT ACYCLIC GRAPH; GAUGING STATIONS; MARKOV PROCESS; MARKOVIAN; MULTI-SITE; OCCURRENCE; OPTIMAL SEQUENCES; SOUTH FLORIDA; SPACE-TIME MODEL; SPATIAL DEPENDENCE; TEMPORAL DEPENDENCE; TIME MODELING;

CHLORINE COMPOUNDS; LEARNING SYSTEMS; MATHEMATICAL MODELS; STOCHASTIC MODELS; STOCHASTIC PROGRAMMING;

RAIN;

MARKOV CHAIN; PRECIPITATION ASSESSMENT; PRECIPITATION INTENSITY; RAINFALL; RAINGAUGE; STOCHASTICITY;

FLORIDA [UNITED STATES]; NORTH AMERICA; UNITED STATES;

EID: 50149102178     PISSN: 14363240     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00477-007-0180-8     Document Type: Article

References (23)

1. Bardossy A, Plate EJ (1992) Space-time model for daily rainfall using atmospheric circulation patterns. Water Resour Res 28(5):1247-1259
2. Cano R, Sordo C, Gutiérrez JM (2004) Applications of Bayesian networks in meteorology. In: Gómez JA, Moral S, Salmerén A (eds) Advances in Bayesian networks, Springer, Heidelberg, pp. 309-328
3. Fowler HJ, Kilsby CG, O'Connell PE, Burton A (2005) A weather-type conditioned multi-site stochastic rainfall model for the generation of scenarios of climatic variability and change. J Hydrol 308:50-66
4. Johnson GL, Hanson CL, Hardegree SP, Ballard EB (1996) Stochastic weather simulation: Overview and analysis of two commonly used models. J Appl Meteorol 35:1878-1896
5. Kim T-W, Valdés JB (2005) Synthetic generation of hydrologic time series based on nonparametric random generation. J Hydrol Eng 10(5):395-404
6. Kyriakidis PC, Miller NL, Kim J (2004) A spatial time series framework for simulating daily precipitation at regional scales. J Hydrol 297:236-255
7. Lal AMW (2001) Modification of canal flow due to stream-aquifer interaction. J Hydraulic Eng 127(7):567-576
8. Lall U, Rajagopalan B, Tarboton DG (1996) A nonparametric wet/dry spell model for resampling daily precipitation. Water Resour Res 32(9):2803-2823
9. Rajagopalan B, Lall U (1999) A k-nearest-neighbor simulator for daily precipitation and other weather variables. Weather Forecast 35(10):3089-3101
10. Rajagopalan B, Lall U, Tarboton DG (1994) A nonparametric renewal model for modeling daily precipitation. In: Hipel KV, Mcleod AI, Panu US, Singh VP (eds) Stochastic and Statistical Methods in Hydrology and Environmental Engineering, vol 3. Time series analysis in hydrology and environmental engineering. Kluwer, Dordrecht, pp. 47-51
11. Rajagopalan B, Lall U, Tarboton DG (1996) Nonhomogeneous Markov model for daily precipitation. J Hydrol Eng 1(1):33-40
12. Richardson CW (1981) Stochastic simulation of daily precipitation, temperature and solar radiation. Water Resour Res 17(1):182-190
13. Roldán J, Woolhiser DA (1982) Stochastic daily precipitation models: 1. A comparison of occurrence processes. Water Resour Res 18(5):1451-1459
14. Scott DW (1992) Multivariate density estimation: Theory, practice and visualization. Wiley, New York, p. 317
15. Seed AW, Srikanthan R, Menabde M (1999) A space and time model for design storm rainfall. J Geophys Res 104(D24): 31623-31630
16. Shami RG, Forbes CS (2000) A structural time series model with Markov switching. Working Paper, Monash University
17. Silverman BW (1986) Density estimation for statistics and data analysis. Chapman and Hall, New York, p. 175
18. Srikanthan R, McMahon TA (2001) Stochastic generation of annual, monthly, and daily climate data: A review. Hydrol Earth Syst Sci 5(4):653-670
19. Tarboton KC, Neidrauer CJ, Santee ER, Needle JC (1999) Regional hydrologic modeling for planning the management of South Florida's water resources through 2050. Paper presented at 1999 Annual International Meeting, ASAE/CSAE, Toronto, Canada, 19-21 July
20. Thyer M, Kuczera G (2000) Modeling long-term persistence in hydroclimatic time series using a hidden state Markov model. Water Resour Res 36(11):3301-3310
21. Wheater HS, Chandler RE, Onof CJ, Isham VS, Bellone E, Yang C, Lekkas D, Lourmas G, Segond M-L (2005) Spatial-temporal rainfall modeling for flood risk estimation. Stochast Environ Res Risk Assess 19:403-416
22. Wilks DS (1998) Multisite generation of a daily stochastic precipitation generation model. J Hydrol 210:178-191
23. Zhang Z, Switzer P (2007) Stochastic space-time regional rainfall modeling adapted to historical rain gauge data. Water Resour Res 43(W03441). doi:10.1029/2005WR004654