Forecasting flows in Apalachicola River using neural networks

Hydrological Processes

Volumn 18, Issue 13, 2004, Pages 2545-2564

  Huang, Wenrui ^a   Xu, Bing ^a   Chan Hilton, Amy ^a  

^a FLORIDA STATE UNIVERSITY   (United States)

Author keywords

ANN; ARIMA; Flow forecasting; Neural network; River

Indexed keywords

ALGORITHMS; FLOW CONTROL; MATHEMATICAL MODELS; RIVERS; STRATEGIC PLANNING; WATER RESOURCES;

ANN MODEL; CORRELATION COEFFICIENTS; FORECASTING MODFELS; RIVER FLOW;

NEURAL NETWORKS;

ARTIFICIAL NEURAL NETWORK; FLOOD FORECASTING; FORECASTING METHOD; RIVER FLOW; WATER MANAGEMENT;

APALACHICOLA RIVER; FLORIDA; NORTH AMERICA; UNITED STATES;

EID: 4644299731     PISSN: 08856087     EISSN: None     Source Type: Journal    
DOI: 10.1002/hyp.1492     Document Type: Article

References (22)

1. Box GEP, Jenkins GM. 1976. Time Series Analysis: Forecasting and Control. Holden-Day: Oakland, CA.
2. Cameron MZ, Burn DH, Simonovic S. 1999. Short term streamflow forecasting using artificial neural networks. Journal of Hydrology 214(1-4): 32-48.
3. Coulibaly P, Anctil F, Bobee B. 2000. Daily reservoir inflow forecasting using artificial neural networks with stopped training approach. Journal of Hydrology 230(3-4): 244-257.
4. Deo MC, Naidu DS. 1997. Real time wave forecasting using neural networks. Ocean Engineering 26: 191-203.
5. Dibike YB, Solomatine DP. 1999. River flow forecasting using artificial neural networks. Journal of Physics and Chemistry of the Earth 26: 1-8.
6. Fitch JP, Lehman SK, Dowla FU, Lu SK, Johansson EM, Goodman DM. 1991. Ship wake detection procedure using conjugate gradient trained artificial neural network. IEEE Transactions on Geosciences and Remote Sensing 9(5): 718-725.
7. French MN, Krajewski WF, Cuykendall RR. 1992. Rainfall forecasting in space and time using a neural network. Journal of Hydrology 137: 1-31.
8. Gautam MR, Watanabe K, Saegusa H. 2000. Runoff analysis in humid forest catchment with artificial neural network. Journal of Hydrology 235(1-2): 117-136.
9. Hagan MT, Demuth HB, Beale M. 1996. Neural Network Design. PWS Publishing Company: Biston, MA, USA.
10. Hamilton JD. 1994. Time Series Analysis. Princeton University Press: Princeton, NJ; 820 pp.
11. Hayes MJ, Wilhite DA, Svoboda MD, Smith KH. 1996. Drought management: crisis vs. risk management. In Proceedings of the 1996 International Conference and Exposition on Natural Disaster Reduction. American Society of Civil Engineers: Washington, DC; 371-372.
12. Haykin S. 1999. Neural Networks, a Comprehensive Foundation. Prentice Hall: Upper Saddle River, NJ, USA; 842 pp.
13. Hsu KL, Gupta HV, Sorooshian S. 1995. Artificial neural network modeling of the rainfall-runoff process. Water Resources Research 31: 2517-2530.
14. Huang W, Foo S. 2002. Neural network modeling of salinity in Apalachicola River. Water Resources Research 36: 356-362.
15. Kim G, Barrros AP. 2001. Quantitative flood forecasting using multi-sensor data and neural networks. Journal of Hydrology 246(1-4): 45-62.
16. Livingston RJ, Niu X, Lewis FG, Woodsum GC. 1997. Freshwater input to a Gulf estuary: Long-term control of trophic organization. Ecological Applications 7: 277-299.
17. Moller MF. 1993. A scaled conjugate gradient algorithm for fast supervised learning. Neural Networks 6: 525-533.
18. Obeysekera JA, Trimble P, Cadavid L, Santee R, White C. 1999. Use of Climate Outlook for Water Management in South Florida, USA. South Florida Water Management District: West Palm Beach, FL.
19. Toth E, Brath A, Montanari A. 2000. Comparison of short-term rainfall prediction models for real-time flood forecasting. Journal of Hydrology 239(1-4): 132-147.
20. Zhang GP. 2001. An investigation of neural networks for linear time-series forecasting. Computers and Operations Research 28: 1183-1202.
21. SFWMD (South Florida Water Management District), Water Shortage Report: http://www.sfwmd.gov/curre/watshort/watcondarchive.html.
22. Southeast Regional Climate Center, South Carolina Department of Natural Resources 1201 Main Street, Suite 1100 Columbia, South Carolina 29201