Evaluation of statistical rainfall disaggregation methods using Rain-Gauge information for West-Central Florida

Journal of Hydrologic Engineering

Volumn 13, Issue 12, 2008, Pages 1158-1169

  Zhang, Jing ^a,b   Murch, Renee R ^c   Ross, Mark A ^d   Ganguly, Auroop R ^e   Nachabe, Mahmood ^d  

^a CAPITAL NORMAL UNIVERSITY   (China)

^b UNIVERSITY OF SOUTH FLORIDA   (United States)

^c Water Resource Engineer Intera Inc   (United States)

^d University of South Florida   (United States)

^e OAK RIDGE NATIONAL LABORATORY   (United States)

Author keywords

Florida; Hydrologic models; Neural networks; Parameters; Rainfall; Statistics; Stochastic processes

Indexed keywords

COMPUTATIONAL METHODS; FLOODS; FORECASTING; GAGES; HYDRAULIC MODELS; METEOROLOGICAL INSTRUMENTS; NEURAL NETWORKS; PRECIPITATION (METEOROLOGY); RAIN GAGES; SORTING; STATISTICAL METHODS; STATISTICS; STOCHASTIC MODELS; THICKNESS MEASUREMENT; VEGETATION;

FLORIDA; HYDROLOGIC MODELS; PARAMETERS; RAINFALL; STOCHASTIC PROCESSES;

RAIN;

ARTIFICIAL NEURAL NETWORK; COMPUTER SIMULATION; FLASH FLOOD; FLOOD FORECASTING; HYDROLOGICAL MODELING; PARAMETERIZATION; PRECIPITATION ASSESSMENT; RAINGAUGE; STATISTICAL ANALYSIS;

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

HORTONIA;

EID: 56449090642     PISSN: 10840699     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)1084-0699(2008)13:12(1158)     Document Type: Article

References (56)

1. Bardossy, A. (1997). "Disaggregation of daily precipitation." Proc., Workshop on Ribamod River basin modeling, management and flood mitigation: Concerted action, R. Casale, M. Borga, E. Baltas, and P. Samuels, eds., Monselice, European Commission: Environment and Climate Programme, Padua, Italy, 25-26 September, 1997, 40-53.
2. Bekele, Debele B., Srinivasan, R., and Parlange, J. Y. (2007). "Accuracy evaluation of weather data generation and disaggregation methods at finer timescales." Adv. Water Resour. AWREDI0309-1708, 30(5), 1286-1300.
3. Bishop, C. M. (1995). Neural networks for pattern recognition, Oxford University Press, Oxford, U.K.
4. Bosch, D. D., Sheridan, J. M., and Davis, F. M. (1999). "Rainfall characteristics and spatial correlation for the Georgia coastal plain." Trans. ASAE TAAEAJ0001-2351, 42(6), 1637-1644.
5. Bowden, G. J., Maier, H. R., and Dandy, G. C. (2002). "Optimal division of data for neural network models in water resources applications." Water Resour. Res. WRERAQ0043-1397, 38(2), 1-2.11.
6. Bras, R. L. (1990). Hydrology: An introduction to hydrologic science, Addison-Wesley, Reading, Mass.
7. Burckhardt-Gammeter, S., and Fankhauser, R. (1998). "Analysis of rainfall time series with regard to temporal disaggregation for the use in urban hydrology." Water Sci. Technol. WSTED40273-122310.1016/ S0273-1223(98)00235-2, 37(11), 65-72.
8. Burian, S. J., Durrans, S. R., Nix, S. J., and Pitt, R. E. (2001). "Training artificial neural networks to perform rainfall disaggregation." J. Hydrol. Eng. JHYEFF1084-069910.1061/ (ASCE)1084-0699(2001)6:1(43), 6(1), 43-51.
9. Burian, S. J., Durrans, S. R., Tomic, S., Pimmel, R. L., and Wai, C. N. (2000). "Rainfall disaggregation using artificial neural networks." J. Hydrol. Eng. JHYEFF1084-069910.1061/ (ASCE)1084-0699(2000)5:3(299), 5(3), 299-307.
10. Connolly, R. D., Schirmer, J., and Dunn, P. K. (1998). "A daily rainfall disaggregation model." Agric. Forest Meteorol. ZZZZZZ0618-1923, 92, 105-117.
11. Cowpertwait, P. S. P. (2006). "A spatial-temporal point process model of rainfall for the Thames catchment, U.K." J. Hydrol. JHYDA70022-1694, 330(3-4), 586-595.
12. Dowla, F. U., and Rogers, L. L. (1995). "Solving problems in environmental engineering and geosciences with artificial neural networks." MIT Press, Cambridge, Mass.
13. Durrans, S. R., Burian, S. J., Nix, S. J., Hajji, A., Pitt, R. E., Fan, C. Y., and Field, R. (1999). "Polynomial-based disaggregation of hourly rainfall for continuous hydrologic simulation." J. Am. Water Resour. Assoc. JWRAF51093-474X, 35(5), 1213-1221.
14. Flitcroft, I. D., McDougall, V., Milford, J. R., and Dugdale, G. (1986). "The calibration and interpretation of METEBSAT-based estimates of Sahelian rainfall." Proc., 6th METEBSAT Scientific Users' Meeting, Amsterdam, November 1986.
15. Freeman, J. A., and Skapura, D. M. (1991). Neural networks: Algorithms, applications, and techniques, Addison-Wesley, Reading, Mass.
16. French, M. N., Krajewski, W. F., and Cuykendall, R. R. (1992). "Rainfall forecasting in space and time using a neural network." J. Hydrol. JHYDA70022-169410.1016/0022-1694(92)90046-X, 137, 1-31.
17. Ganguly, A. R. (2002). "A hybrid approach to improving rainfall forecasts." Comput. Sci. Eng. CSENFA1521-961510.1109/ MCISE.2002.1014976, 4(4), 14-21.
18. Ganguly, A. R., and Bras, R. L. (2003). "Distributed quantitative precipitation forecasting combining information from radar and numerical weather prediction model outputs." J. Hydrometeor. ZZZZZZ1525-7541, 4(6), 1168-1180.
19. Gaume, E., Mouhous, N., and Andrieu, H. (2007). "Rainfall stochastic disaggregation models: Calibration and validation of a multiplicative cascade model." Adv. Water Resour. AWREDI0309-1708, 30(5), 1301-1319.
20. Geurink, J. S., Nachabe, M., Ross, M., and Tara, P. (2000). "Surface water model development, calibration and recharge estimates." Water Resource Rep. No. CMHAS.SWFWMD.00.03, Prepared for the Southwest Florida Water Management District, Brooksville, Fla.
21. Glasby, C. A., Cooper, G., and McGechan, M. B. (1995). "Disaggregation of daily rainfall by condition simulation from a point-process model." J. Hydrol. JHYDA70022-169410.1016/ 0022-1694(94)02598-6, 165, 1-9.
22. Green, W. H., and Ampt, G. A. (1911). "Studies on soil physics." J. Agric. Sci. JASIAB0021-8596, 4(1), 1-24.
23. Gutierrez-Magness, A. L., and McCuen, R. H. (2004). "Accuracy evaluation of rainfall disaggregation methods." J. Hydrol. Eng. JHYEFF1084-069910.1061/(ASCE)1084-0699(2004)9:2(71), 9(2), 71-78.
24. Gyasi-Agyei, Y. (2005). "Stochastic disaggregation of daily rainfall into one-hour time scale." J. Hydrol. JHYDA70022-169410.1016/j.jhydrol.2004.11.018, 309(1-4), 19, 178-190
25. Hansen, J. W., and Ines, A. V. M. (2005). "Stochastic disaggregation of monthly rainfall data for crop simulation studies." Agric. Forest Meteorol. ZZZZZZ0618-1923, 131(3-4), 233-246.
26. Hernandez, T., Nachabe, M., and Ross, M. (2003). "Modeling runoff from variable source in humid, shallow water table environments." J. Am. Water Resour. Assoc. JWRAF51093-474X10.1111/ j.1752-1688.2003.tb01562.x, 39(5), 75-85.
27. Hershenhorn, J., and Woolhiser, D. A. (1987). "Disaggregation of daily rainfall." J. Hydrol. JHYDA70022-169410.1016/ 0022-1694(87)90008-4, 95, 299-322.
28. Hertz, J., Krogh, A., and Palmer, R. G. (1991). Introduction to the theory of neural computation, Addison-Wesley, Redwood City, Calif.
29. Hingray, B., and Haha, M. B. (2005). "Statistical performances of various deterministic and stochastic models for rainfall series disaggregation." Atmos. Res. ATREEW0169-809510.1016/ j.atmosres.2004.10.023, 77(1-4), 152-175.
30. Johann, G., Papadakis, I., and Pfister, A. (1998). "Historical precipitation time series for applications in urban hydrology." Water Sci. Technol. WSTED40273-1223, 37(11), 147-153.
31. King, K. W. (2000). "Response of Green-Ampt Mein-Larsen simulated runoff volumes to temporally aggregated precipitation." J. Am. Water Resour. Assoc. JWRAF51093-474X, 36(4), 791-797.
32. Kottegoda, N. T., Natale, L., and Raiteri, E. (2003). "A parsimonious approach to stochastic multisite modeling and disaggregation of daily rainfall." J. Hydrol. JHYDA70022-1694, 274, 47-61.
33. Koutsoyiannis, D. (2003). "Rainfall disaggregation methods: Theory and applications." Proc., Workshop on Statistical and Mathematical Methods for Hydrological Analysis, D. Piccolo, and L. Ubertini, eds., Rome, 1-23, Università degli Studi di Roma "La Sapienza," 2003.
34. Koutsoyiannis, D., and Foufoula-Georgiou, E. (1993). "A scaling model of storm hyetograph." Water Resour. Res. WRERAQ0043-139710.1029/93WR00395, 29(7), 2345-2361.
35. Koutsoyiannis, D., and Onof, C. (2001). "Rainfall disaggregation using adjusting procedures on a Poisson cluster model." J. Hydrol. JHYDA70022-169410.1016/S0022-1694(01)00363-8, 246, 109-122.
36. Koutsoyiannis, D., Onof, C., and Wheater, H. S. (2003). "Multivariate rainfall disaggregation at a fine time scale." Water Resour. Res. WRERAQ0043-139710.1029/2002WR001600, 39(7), 1173.
37. Molnar, P., and Burlando, P. (2005). "Preservation of rainfall properties in stochastic disaggregation by a simple random cascade model." Atmos. Res. ATREEW0169-809510.1016/j.atmosres.2004.10.024, 77(1-4), 137-151.
38. National Oceanic Atmospheric Administration (NOAA). (2004). Advanced warning operations course, 〈https://wdtb.noaa.gov/courses/awoc/ documentation/screen/AWOC_FY06_Individual/ ICSvr1_ic1-lesson5_color.pdf.〉.
39. Olsson, J. (1998). "Evaluation of a cascade model for temporal rainfall disaggregation." Clin. Neurophysiol. ZZZZZZ1388-2457, 2, 19-30.
40. Olsson, J., and Berndtsson, R. (1997). "Temporal rainfall disaggregation based on scaling properties." Proc., 3rd Int. Workshop on Rainfall in Urban Areas: Use of Historical Rainfall Series for Hydrological Modeling, 4-7 December, Pontresina, Switzerland.
41. Onof, C., Townend, J., and Kee, R. (2005). "Comparison of two hourly to 5-min rainfall disaggregators." Atmos. Res. ATREEW0169-8095, 77(1-4), 176-187.
42. Ormsbee, L. (1989). "Rainfall disaggregation model for continuous hydrologic modeling." J. Hydraul. Eng. JHEND80733-9429, 115(4), 507-525.
43. Raman, H., and Sunikumar, N. (1995). "Multivariate modeling of water resources time series using artificial neural networks." Hydrol. Sci. J. HSJODN0262-6667, 40, 145-163.
44. Rodriguez-Iturbe, I., Cox, D. R., and Isham, V. (1988). "A point process model for rainfall: Further developments." Proc. R. Soc. London, Ser. A PRLAAZ1364-5021, 417, 283-298.
45. Rodriguez-Iturbe, I., Cox, D. R., and Isham, V. (1987). "Some models for rainfall based on stochastic processes." Proc. R. Soc. London, Ser. A PRLAAZ1364-5021, 410, 269-288.
46. Segond, M.-L., Onof, C., and Wheater, H. S. (2006). "Spatial-temporal disaggregation of daily rainfall from a generalized linear model." J. Hydrol. JHYDA70022-1694, 331(3-4), 674-689.
47. Singh, V. P., and Woolhiser, D. M. (2002). "Mathematical modeling of watershed hydrology." J. Hydrol. Eng. JHYEFF1084-0699, 270, 270-292.
48. Sivakumar, B. (2001). "Rainfall dynamics at different temporal scales: A chaotic perspective." Clin. Neurophysiol. ZZZZZZ1388-2457, 5(4), 645-651.
49. Sivakumar, B., Sorooshian, S., Gupta, V. J., and Gao, X. (2001). "A chaotic approach to rainfall disaggregation." Water Resour. Res. WRERAQ0043-1397, 37, 61-72.
50. Socolofsky, S., and Adams, E. E. (2001). "Disaggregation of daily rainfall for continuous watershed modeling." J. Hydrol. Eng. JHYEFF1084-069910.1061/(ASCE)1084-0699(2001)6:4(300), 6, 300-309.
51. Stern, R. D., and Coe, R.(1984). "A model fitting analysis of daily rainfall data." J. R. Stat. Soc. Ser. A (Gen.) JSTAAG0035-9238, 147, 1-37.
52. Tara, P., Rokicki, R., and Ross, M. (2002). "Estimating the un-gauged flows in the Alafia River." Water Resource Rep. No. CMHAS.SWFWMD.02.01, prepared for the Southwest Florida Water Management District, Brooksville, Fla.
53. Waymire, E., and Gupta, V. K. (1981). "The mathematical structure of rainfall representations, 1, 2, and 3." Water Resour. Res. WRERAQ0043-1397, 17(5), 1273-1285.
54. Weigend, A. S., and Gershenfeld, N. A., eds. (1994). "Time series prediction: Forecasting the future and understanding the past." Addison-Wesley, Reading, Mass.
55. Zhang, G., Patuwo, B. E., and Hu, M. Y. (1998). "Forecasting with artificial neural networks: The state of the art." Int. J. Forecast. ZZZZZZ0169-2070, 14, 35-62.
56. Zhu, H. J., and Schilling, W. (1996). "Simulation errors due to insufficient temporal rainfall resolution-Annual combined sewer overflow." Atmos. Res. ATREEW0169-809510.1016/0169-8095(95)00050-X, 42, 19-32.