Forecasting weekly evapotranspiration with ARIMA and artificial neural network models

Journal of Irrigation and Drainage Engineering

Volumn 135, Issue 3, 2009, Pages 323-334

  Landeras, Gorka ^a   Ortiz Barredo, Amaia ^a   López, José Javier ^b  

^a NEIKER and a Vaccine producing Commercial Company CZVSL   (Spain)

^b PUBLIC UNIVERSITY OF NAVARRE   (Spain)

Author keywords

Evapotranspiration; Forecasting; Neural networks; Time series analysis; Water management; Water resources

Indexed keywords

ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORK MODELS; BASQUE COUNTRY; KEY FACTORS; MODEL-BASED; PREDICTION MODEL; REFERENCE EVAPOTRANSPIRATION; ROOT MEAN SQUARE DIFFERENCES; STANDARD DEVIATION; WATER RESOURCE SYSTEMS; WATER RESOURCES AVAILABILITY;

BACKPROPAGATION; EVAPOTRANSPIRATION; FORECASTING; NEURAL NETWORKS; PLANNING; TIME SERIES; WATER ANALYSIS; WATER MANAGEMENT; WATER SUPPLY;

TIME SERIES ANALYSIS;

ARTIFICIAL NEURAL NETWORK; EVAPOTRANSPIRATION; FORECASTING METHOD; IRRIGATION; TIME SERIES ANALYSIS; WATER MANAGEMENT; WATER PLANNING; WATER RESOURCE;

BASQUE COUNTRY; EURASIA; EUROPE; SOUTHERN EUROPE; SPAIN;

EID: 66449088932     PISSN: 07339437     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)IR.1943-4774.0000008     Document Type: Article

References (40)

1. Allen, R. G., Pereira, L. S., Raes, D., and Smith, M. (1998). "Crop evapotranspiration-Guidelines for computing crop water requirements." FAO Irrigation and Drainage Paper No. 56, FAO, Rome, Italy.
2. Allen, R. G., Smith, M., Perrier, A., and Pereira, L. S. (1994). "An update for the calculation of reference evapotranspiration." ICID Bull. IIDBAS0300-2810, 43(2), 35-92.
3. Box, G. E. P., and Cox, D. R. (1964). "An analysis of transformations." J. R. Stat. Soc. Ser. B (Methodol.) JSTBAJ0035-9246, 26(2), 211-252.
4. Box, G. E. P., and Jenkins, G. M. (1976). Time series analysis, forecasting and control, Holden-Day Inc., San Francisco.
5. Cigizoglu, H. K. (2003a). "Estimation, forecasting and extrapolation of flow data by artificial neural networks." Hydrol. Sci. J.HSJODN0262-666710.1623/hysj.48.3.349.45288, 48(3), 349-361.
6. Cigizoglu, H. K. (2003b). "Incorporation of ARMA models into flow forecasting by artificial neural networks." Environmetrics ENVCEE1180-400910.1002/env.596, 14(4), 417-427.
7. Cigizoglu, H. K. (2004). "Estimation and forecasting of daily suspended sediment data by multi layer perceptrons." Adv. Water Resour. AWREDI0309-170810.1016/j.advwatres.2003.10.003, 27, 185-195.
8. Cigizoglu, H. K. (2005). "Generalized regression neural network in monthly flow forecasting." Civ. Eng. Environ. Syst. ZZZZZZ1028-6628, 22(2), 71-84.
9. Cigizoglu, H. K., and Alp, M. (2006). "Generalized regression neural network in modelling river sediment yield." Adv. Eng. Software AESODT0965-997810.1016/j.advengsoft.2005.05.002, 37(2), 63-68.
10. Dickey, D. A., and Fuller, W. A. (1981). "Likelihood ratio statistics for autoregressive time series with a unit root." Econometrica ECMTA70012-9682, 49(4), 1057-1072.
11. Droogers, P., and Allen, R. G. (2002). "Estimating reference evapotranspiration under inaccurate data conditions." Irrig. Drain. Syst. IDRSEG0168-629110.1023/A:1015508322413, 16(1), 33-45.
12. Hargreaves, G. H., and Samani, Z. A. (1985). "Reference crop evapotranspiration from temperature." Appl. Eng. Agric. ZZZZZZ0883-8542, 1(2), 96-99.
13. Karamouz, M., Razavi, S., and Araghinejad, S. (2005). "Application of temporal neural networks in long-lead rainfall forecasting." Proc., Impacts of Global Climate Change, ASCE, Reston, Va., 173(40792), 266.
14. Kenward, T. C., Eng, P., and Howard, C. D. D. (2004). "Forecasting for urban water demand management." Proc., WRPMD' 99-Preparing for the 21st Century, ASCE, Reston, Va., 102(40430), 245.
15. Kim, J. H., Hwang, S. H., and Shin, H. S. (2004). "An optimal neural network model for daily water demand forecasting." Proc., WRPMD '99-Preparing for the 21st Century, ASCE, Reston, Va., 102(40430), 236.
16. Kim, S., and Kim, H. S. (2008). "Neural networks and genetic algorithm approach for nonlinear evaporation and evapotranspiration modeling." J. Hydrol. JHYDA70022-1694, 351(3-4), 299-317.
17. Kisi, O. (2006a). "Evapotranspiration estimation using feed-forward neural networks." Nord. Hydrol. NOHYBB0029-1277, 37(3), 247-260.
18. Kisi, O. (2006b). "Generalized regression neural networks for evapotranspiration modelling." Hydrol. Sci. J. HSJODN0262-666710.1623/hysj.51.6.1092, 51(6), 1092-1105.
19. Kisi, O. (2007). "Evapotranspiration modelling from climatic data using a neural computing technique." Hydrolog. Process. HYPRE30885-608710.1002/hyp.6403, 21, 1925-1934.
20. Kisi, O., and Ozturk, O. (2007). "Adaptive neuro-fuzzy computing technique for evapotranspiration estimation." J. Irrig. Drain. Eng.JIDEDH0733-943710.1061/(ASCE)0733-9437(2007)133:4(368), 133(4), 368-379.
21. Kumar, M., Raghuwanshi, N. S., Singh, R., Wallender, W. W., and Pruitt, W. O. (2002). "Estimating evapotranspiration using artificial neural network." J. Irrig. Drain. Eng. JIDEDH0733-943710.1061/ (ASCE)0733-9437(2002)128:4(224), 128(4), 224-233.
22. Landeras, G., Ortiz-Barredo, A., and López, J. J. (2008). "Comparison of artificial neural network models and empirical and semi-empirical equations for daily reference evapotranspiration estimation in the Basque Country (Northern Spain)." Agric. Water Manage. AWMADF0378-3774, 95(5), 553-565.
23. Ljung, G. M., and Box, G. E. P. (1978). "On a measure of lack of fit in time series models." Biometrika BIOKAX0006-344410.1093/ biomet/65.2.297, 65(2), 297-303.
24. Marquardt, D. W. (1963). "An algorithm for least-squares estimation of nonlinear parameters." J. Soc. Ind. Appl. Math. JSIMAV0368-424510.1137/0111030, 11(2), 431-441.
25. Papamichail, D. M., and Georgiou, P. E. (2001). "Seasonal ARIMA inflow models for reservoir sizing." J. Am. Water Resour. Assoc. JWRAF51093-474X, 37(4), 877-885.
26. Peña, D. (2005). "Análisis de series temporales." Alianza Editorial.
27. Phillips, P. C. B., and Perron, P. (1988). "Testing for a unit root in time series regression." Biometrika BIOKAX0006-344410.1093/ biomet/75.2.335, 75(2), 335-346.
28. Pulido-Calvo, I., Roldán, J., López-Luque, R., and Gutiérrez-Estrada, J. C. (2003). "Demand forecasting for irrigation water distribution systems." J. Irrig. Drain. Eng. JIDEDH0733-943710.1061/(ASCE)0733-9437(2003)129:6(422), 129(6), 422-431.
29. Quantitative Micro Software. (2004). "Eviews 5.0 (computer program)." Quantitative Micro Software, Irvine, Calif., 〈http://www.eviews.com〉.
30. SPSS. (2006). "SPSS 15.0 (computer program)." SPSS Inc., Chicago, 〈http://www.spss.com〉.
31. StatSoft. (1999). "Statistical neural networks release 4.1 (computer program)." StatSoft Inc., Tulsa, Okla., 〈http://www.statsoft.com〉.
32. Sudheer, K. P., Gosain, A. K., and Ramasastri, K. S. (2003). "Estimating actual evapotranspiration from limited climatic data using neural computing technique." J. Irrig. Drain. Eng. JIDEDH0733-943710.1061/(ASCE)0733-9437(2003)129:3(214), 129(3), 214-218.
33. Tahir, S. A. (1998). "Estimating potential evaporation using artificial neural network." Water and land resources development and management for sustainable use: 2.
34. Trajkovic, S. (2005). "Temperature-based approaches for estimating reference evapotranspiration." J. Irrig. Drain. Eng. JIDEDH0733-943710.1061/(ASCE)0733-9437(2005)131:4(316), 131(4), 316-323.
35. Trajkovic, S., Todorovic, B., and Stankovic, M. (2003). "Forecasting of reference evapotranspiration by artificial neural networks." J. Irrig. Drain. Eng. JIDEDH0733-943710.1061/ (ASCE)0733-9437(2003)129:6(454), 129, 454-457.
36. Vaziri, M. (1997). "Predicting Caspian sea surface water level by ANN and ARIMA models." J. Waterway, Port, Coastal, Ocean Eng. JWPED50733-950X10.1061/(ASCE)0733-950X(1997)123:4(158), 123(4), 158-162.
37. Verma, M. K., and Shrivastava, R. K. (2002). "Application of real-time reservoir operation model to Mahanadi Reservoir project." Proc., ACE 2002: Int. Conf. on Advances in Civil Engineering, 251-259.
38. Wanakule, N., and Aly, A. (2005). "Using groundwater artificial neural network models for adaptive water supply management." Proc., Impacts of Global Climate Change, ASCE, Reston, Va., 173(40792), 89.
39. Zanetti, S. S., Sousa, E. F., and Oliveira, V. P. S. (2007). "Estimating evapotranspiration using artificial neural network and minimum climatological data." J. Irrig. Drain. Eng. JIDEDH0733-943710.1061/(ASCE)0733-9437(2007)133:2(83), 133(2), 83-89.
40. Zwiers, F., and Von Storch, H. (1990). "Regime-dependent autoregressive time series modelling of the southern oscillation." J. Clim. JLCLEL0894-8755, 3(12), 1347-1363.