Implementing a space-time rainfall model for the Sydney region

Water Science and Technology

Volumn 55, Issue 4, 2007, Pages 39-47

  Leonard, M ^a   Metcalfe, A ^a   Lambert, M ^a   Kuczera, G ^b  

^a UNIVERSITY OF ADELAIDE   (Australia)

^b UNIVERSITY OF NEWCASTLE   (Australia)

Author keywords

Continous simulation; Neyman Scott; Space time rainfall

Indexed keywords

COMPUTER SIMULATION; INTERPOLATION; LEAST SQUARES APPROXIMATIONS; STATISTICAL METHODS; STORMS;

CONTINOUS SIMULATION; SPATIAL NEYMAN - SCOTT RECTANGULAR PULSE;

RAIN;

RAIN;

COMPUTER SIMULATION; INTERPOLATION; LEAST SQUARES APPROXIMATIONS; RAIN; STATISTICAL METHODS; STORMS;

COMPUTER SIMULATION; LEAST SQUARES METHOD; MODEL; PRECIPITATION ASSESSMENT; RAINFALL;

AUSTRALIA; CALIBRATION; CONFERENCE PAPER; CONTROLLED STUDY; PARAMETER; REGRESSION ANALYSIS; SIMULATION; STATISTICAL MODEL; TIME;

AUSTRALIA; COMPUTER SIMULATION; GEOGRAPHY; MODELS, THEORETICAL; RAIN; WATER MOVEMENTS;

AUSTRALASIA; AUSTRALIA; NEW SOUTH WALES; SYDNEY;

EID: 33947645951     PISSN: 02731223     EISSN: None     Source Type: Book Series    
DOI: 10.2166/wst.2007.093     Document Type: Conference Paper

References (17)

1. Chaubey, I., Haan, C.T., et al. (1999). Uncertainty in the model parameters due to spatial variability of rainfall. Journal of Hydrology, 220(1-2), 48-61.
2. Cowpertwait, P.S.P. (1995). A Generalized Spatial-Temporal Model of Rainfall Based on a Clustered Point Process. Proceedings of the Royal Society of London Series a- Mathematical and Physical Sciences, 450(1938), 163-175.
3. Cowpertwait, P.S.P., Kilsby, C.G. et al. (2002). A space-time Neyman-Scott model of rainfall: Empirical analysis of extremes. Water Resources Research, 38(8), art. no.-1131.
4. Crane, R.K. (1990). Space-Time Structure of Rain Rate Fields. Journal of Geophysical Research. Atmospheres, 95(D3), 2011-2020.
5. Frost, A.J., Srikanthan, R. et al. (2004). Stochastic generation of point rainfall data at subdaily timescales: a comparison of DRIP and NSRP, Cooperative Research Centre for Catchment Hydrology.
6. Gutierrez-Magness, A.L. and McCuen, R.H. (2004). Accuracy evaluation of rainfall disaggregation methods. Journal of Hydrologic Engineering, 9(2), 71-78.
7. Heneker, T.M., Lambert, M.F. et al. (2001). A point rainfall model for risk-based design. Journal of Hydrology, 247(1-2), 54-71.
8. Mellor, D. (1996). The Modified Turning Bands (MTB) model for space-time rainfall .1. Model definition and properties. Journal of Hydrology, 175(1-4), 113-127.
9. Northrop, P. (1998). A clustered spatial-temporal model of rainfall. Proceedings of the Royal Society of London Series a-Mathematical Physical and Engineering Sciences, 454(1975), 1875-1888.
10. Onof, C., Chandler, R.E. et al. (2000). Rainfall modelling using Poisson-cluster processes: a review of developments. Stochastic Environmental Research and Risk Assessment, 14(6), 384-411.
11. Pegram, G.G.S. and Clothier, A.N. (2001). High resolution space-time modelling of rainfall: the "String of Beads" model. Journal of Hydrology, 241(1-2), 26-41.
12. Seed, A.W., Srikanthan, R. et al. (1999). A space and time model for design storm rainfall. Journal of Geophysical Research-Atmospheres, 104(D24), 31623-31630.
13. Shah, S.M.S., Oconnell, P.E. et al. (1996a). Modelling the effects of spatial variability in rainfall on catchment response .1. Formulation and calibration of a stochastic rainfall field model. Journal of Hydrology, 175(1-4), 67-88.
14. Shah, S.M.S., Oconnell, P.E. et al. (1996b). Modelling the effects of spatial variability in rainfall on catchment response .2. Experiments with distributed and lumped models. Journal of Hydrology, 175(1-4), 89-111.
15. Srikanthan, R. and McMahon, T.A. (2001). Stochastic generation of annual, monthly and daily climate data: A review. Hydrology and Earth System Sciences, 5(4), 653-670.
16. Willems, P. (2001a). A spatial rainfall generator for small spatial scales. Journal of Hydrology, 252(1-4), 126-144.
17. Willems, P. (2001b). Stochastic description of the rainfall input errors in lumped hydrological models. Stochastic Environmental Research and Risk Assessment, 15(2), 132-152.