Optimal functional forms for estimation of missing precipitation data

Journal of Hydrology

Volumn 374, Issue 1-2, 2009, Pages 106-115

  Teegavarapu, Ramesh S V ^a   Tufail, Mohammad ^b   Ormsbee, Lindell ^b  

^a Florida Atlantic University   (United States)

^b UNIVERSITY OF KENTUCKY   (United States)

Author keywords

Distance weighting methods; Fixed function set genetic algorithm method; Genetic algorithms; Missing precipitation data; Optimal functional forms; Spatial interpolation

Indexed keywords

DISTANCE WEIGHTING METHODS; FIXED FUNCTION SET GENETIC ALGORITHM METHOD; MISSING PRECIPITATION DATA; OPTIMAL FUNCTIONAL FORMS; SPATIAL INTERPOLATION;

ESTIMATION; GAGING; GENETIC ALGORITHMS; INTERPOLATION; OPTIMIZATION; RAIN;

SET THEORY;

DATA ACQUISITION; GENETIC ALGORITHM; INVERSE ANALYSIS; OBSERVATIONAL METHOD; OPTIMIZATION; PARAMETERIZATION; PRECIPITABLE WATER; RAINFALL; RAINGAUGE;

EID: 67650366853     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2009.06.014     Document Type: Article

References (47)

1. Ahrens B. Distance in spatial interpolation of daily rain gauge data. Hydrology and Earth System Sciences 10 (2006) 197-208
2. ASCE, 1996. Hydrology Handbook, second ed. American Society of Civil Engineers (ASCE), New York.
3. ASCE, 2001a. Task committee on artificial neural networks in hydrology, artificial neural networks in hydrology. I. Preliminary concepts. Journal of Hydrologic Engineering, ASCE 52, 115-123.
4. ASCE, 2001b. Task committee on artificial neural networks in hydrology, artificial neural networks in hydrology. II. Hydrologic Applications. Journal of Hydrologic Engineering, ASCE 52, 124-137.
5. Ashraf M., Loftis J.C., and Hubbard K.G. Application of geostatistics to evaluate partial weather station network. Agricultural Forest Meteorology 84 (1997) 255-271
6. Brimicombe A. GIS, Environmental Modeling and Engineering (2003), Taylor and Francis, London, UK
7. Chang K.-T. Introduction to Geographic Information Systems (2004), McGraw Hill, New York
8. Cybenko G. Approximation by superpositions of a sigmoidal function. Mathematical Control Signals Systems 2 (1989) 303-314
9. Daly C., Neilson R.P., and Phillips D.L. A statistical topographic model for mapping climatological precipitation over mountainous terrain. Journal of Applied Meteorology 33 (1994) 140-158
10. Daly C., Gibson W.P., Taylor G.H., Johnson G.H., and Pasteris P. A knowledge-based approach to the statistical mapping of climate. Climate Research 22 (2002) 99-113
11. Dingman S.L. Physical Hydrology (2002), Prentice Hall, NJ
12. French M.N., Krajewski W.F., and Cuykendal R.R. Rainfall forecasting in space and time using a neural network. Journal of Hydrology 137 (1992) 1-37
13. Giustolisi O., and Savic D.A. A novel genetic programming strategy: evolutionary polynomial regression. In: Liong S.-Y., Phoon K.-K., and Babovic (Eds). Proc. of the 6th International Conference on Hydroinformatics, vol. 1, Singapore, 21-24 June (2004), World Scientific Publications, New Jersey 787-794
14. Giustolisi O., Savic D.A., Doglioni A., and Laucelli D. Knowledge discovery by evolutionary polynomial regression. In: Liong S.-Y., Phoon K.-K., and Babovic (Eds). Proc. of the 6th International Conference on Hydroinformatics, vol. 2, Singapore, 21-24 June (2004), World Scientific Publications, New Jersey 1647-1654
15. Goldberg D.E. Genetic Algorithms in Search Optimization and Machine Learning (1989), Addison-Wesley, New York
16. Govindaraju R.S., and Rao A.R. Neural Networks in Hydrology (2000), Kluwer Academic Publishers, Netherlands
17. Grayson R., and Bloschl G. Spatial Patterns in Catchment Hydrology: Observations and Modeling (2001), Cambridge University Press
18. Hornik K., Stinchcombe M., and White H. Multilayer feedforward networks are universal approximators. Neural Networks 2 5 (1989) 359-366
19. Kanevski M., and Maignan M. Analysis and Modelling of Spatial Environmental Data (2004), EPFL Press, Lausanne, Switzerland
20. Koza J.R. Genetic Programming: On the Programming of Computers by Means of Natural Selection (1992), MIT Press, Cambridge, MA
21. Krajewski W.F. Co-kriging of radar and rain gauge data. Journal of Geophysics Research 92 D8 (1987) 9571-9580
22. Larson L.W., and Peck E.L. Accuracy of precipitation measurements for hydrologic forecasting. Water Resources Research 156 (1974) 1687-1696
23. Loader C. Local Regression and Likelihood (1999), Springer Verlag
24. Regonda S.K., Rajagopalan B., Clark M., and Zagona E. A multi-model ensemble forecast framework: application to spring seasonal flows in the Gunnison River Basin. Water Resources Research 42 9 (2006) W09404
25. Rogers D., and Hopfinger A.J. Application of genetic function approximation to quantitative structure-activity relationships and quantitative structure-property relationships. Journal of Chemical Information and Computer Sciences 34 (1994) 854-866
26. Salas, J.D.-J., 1993. Analysis and modeling of hydrological time series. In: Maidment, D.R. (Ed.), Handbook of Hydrology, vol. 19. McGraw-Hill, NY, pp. 19.1-19.72 (chapter 19).
27. Seo D.-J. Nonlinear estimation of spatial distribution of rainfall - an indicator cokriging approach. Stochastic Hydrology and Hydraulics 10 (1996) 127-150
28. Seo D.J. Real-time estimation of rainfall fields using radar rainfall and rain gage data. Journal of Hydrology 208 (1998) 37-52
29. Seo D.-J., and Smith J.A. Rainfall estimation using rain gauges and radar: a Bayesian approach. Journal of Stochastic Hydrology and Hydraulics 5 1 (1993) 1-14
30. Seo D.-J., Krajewski W.F., and Bowles D.S. Stochastic interpolation of rainfall data from rain gauges and radar using cokriging - 1. Design of experiments. Water Resources Research 26 3 (1990) 469-477
31. Seo D.-J., Krajewski W.F., and Bowles D.S. Stochastic interpolation of rainfall data from rain gauges and radar using cokriging - 2. Results. Water Resources Research 26 5 (1990) 915-924
32. Shi L.M., Fan Y., Myers T.G., O'Connor P.M., Paull K.D., Friend S.H., and Weinstein J.N. Mining the NCI anticancer drug discovery database: genetic function approximation for the QSAR study of anti-cancer ellipticine analogues. Journal of Chemical Information and Computer Sciences 38 (1998) 189-199
33. Simanton J.R., and Osborn H.B. Reciprocal-distance estimate of point rainfall. Journal of Hydraulic Engineering Division 106 HY7 (1980) 1242-1246
34. Singh V.P., and Chowdhury K. Comparing some methods of estimating mean aerial rainfall. Water Resources Bulletin 222 (1986) 275-282
35. Smith J.A. Precipitation. In: Maidment D.R. (Ed). Handbook of Hydrology vol. 3 (1993), McGraw Hill, New York (chapter 3)
36. Sullivan D.O., and Unwin D.J. Geographical Information Analysis (2003), John Wiley & Sons, Inc., NJ
37. Teegavarapu R.S.V. Use of universal function approximation in variance-dependent interpolation technique: An application in hydrology. Journal of Hydrology 332 (2007) 16-29
38. Teegavarapu, R.S.V., 2008. Innovative spatial interpolation methods for estimation of missing precipitation records: concepts and applications. In: Bruthans, J., Kovar, K., Hrkal, Z. (Eds.), Proceedings of HydroPredict 2008, Prague, pp. 79-82.
39. Teegavarapu R.S.V. Estimation of missing precipitation records integrating surface interpolation techniques and spatio-temporal association rules. Journal of Hydroinformatics 11 2 (2009) 133-146
40. Teegavarapu R.S.V., and Chandramouli V. Improved weighting methods, deterministic and stochastic data-driven models for estimation of missing precipitation records. Journal of Hydrology 312 (2005) 191-206
41. Tomczak M. Spatial Interpolation and its uncertainty using automated anisotropic inverse distance weighting (IDW) - cross-validation/jackknife approach. Journal of Geographic Information and Decision Analysis 2 (1998) 18-30
42. Tufail M., and Ormsbee L.E. A fixed functional set genetic algorithm (FFSGAM) approach for functional approximation. IWA Journal of Hydroinformatics 3 (2006) 193-206
43. Tung Y.K. Point rainfall estimation for a mountainous region. Journal of Hydraulic Engineering, American Society of Civil Engineering ASCE 109 10 (1983) 1386-1393
44. Vieux B.E. Distributed Hydrologic Modeling using GIS, Water Science and Technology Library (2001), Kluwer Academic Publishers
45. Wang F. Quantitative Methods and Applications in GIS (2006), CRC Press
46. Wei, T.C., McGuinness, J.L., 1973. Reciprocal Distance Squared Method: A Computer Technique for Estimating Area Precipitation. Technical Report ARS-Nc-8. US Agricultural Research Service, North Central Region, OH, USA.
47. Zurada, J.M., 1992. Introduction to Artificial Neural Systems. Boston, MA, USA.