Simulations of runoff and evapotranspiration in Chinese fir plantation ecosystems using artificial neural networks

Ecological Modelling

Volumn 226, Issue , 2012, Pages 71-76

  Liu, Zelin ^a   Peng, Changhui ^a,b   Xiang, Wenhua ^a   Deng, Xiangwen ^a   Tian, DaLun ^a   Zhao, Meifang ^a   Yu, Guirui ^c  

^a CENTRAL SOUTH UNIVERSITY OF FORESTRY AND TECHNOLOGY   (China)

^b UNIVERSITÉ DU QUÉBEC À MONTRÉAL   (Canada)

^c INSTITUTE OF GEOGRAPHIC SCIENCES AND NATURAL RESOURCES RESEARCH   (China)

Author keywords

Back propagation neural network; Genetic neural network; Model validation; Nonlinear problem; Watersheds

Indexed keywords

BACK PROPAGATION NEURAL NETWORKS; CHINESE FIR; FOREST ECOSYSTEM; GENETIC NEURAL NETWORK; HUNAN PROVINCE , CHINA; KEY VARIABLES; METEOROLOGICAL DATA; MODEL SIMULATION; MODEL VALIDATION; MULTIVARIATE STATISTICS; NATIONAL FORESTS; NONLINEAR PROBLEM; SIMULATED RESULTS; WATER BUDGET;

BACKPROPAGATION; DYNAMICS; ECOSYSTEMS; EVAPOTRANSPIRATION; FORESTRY; METEOROLOGY; MULTIVARIANT ANALYSIS; NEURAL NETWORKS; RUNOFF; WATER SUPPLY; WATERSHEDS;

COMPUTER SIMULATION;

ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; CONIFEROUS FOREST; EVAPOTRANSPIRATION; FOREST ECOSYSTEM; HYDROMETEOROLOGY; MODEL VALIDATION; MULTIVARIATE ANALYSIS; NONLINEARITY; PLANTATION; RUNOFF; SPATIOTEMPORAL ANALYSIS; WATER BUDGET; WATERSHED;

ECOSYSTEMS; FORESTRY; METEOROLOGY; NEURAL NETWORKS; PROBLEM SOLVING; RUNOFF; SIMULATION; WATER SHEDS; WATER SUPPLY;

CHINA; HUITONG; HUNAN;

CUNNINGHAMIA LANCEOLATA;

EID: 84455200563     PISSN: 03043800     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ecolmodel.2011.11.023     Document Type: Article

References (30)

1. Bauer R.J. Genetic Algorithms and Investment Strategies, Wiley Finance Editions 1994, John Wiley and Sons, New York, pp. 55-94.
2. Chen Y.H., Chang F.J. Evolutionary artificial neural networks for hydrological systems forecasting. Journal of Hydrology 2009, 367:125-137.
3. Clair T.A., Ehrman J.M. Using neural networks to assess the influence of changing seasonal climates in modifying discharge, dissolved organic carbon, and nitrogen export in eastern Canadian rivers. Water Resources Research 1998, 34(3):447-455.
4. Davis L. Genetic algorithms and financial applications. Trading on the Edge 1994, 133-147. G.J. Deboeck (Ed.).
5. Deng X., Kang W., Tian D., et al. Runoff changes in Chinese fir plantations at different age classes, Huitong, Hunan Province. Scientia Silvae Sinicae 2007, 43(6):1-6.
6. Hsu K., Gupta H.V., Sorooshian S. Artificial neural network modeling of the rainfall-runoff process. Water Resources Research 1995, 31(10):2517-2530.
7. Hu C.H., Hao Y.H., Pang B., et al. Simulation of spring flows from a karst aquifer with an artificial neural network. Hydrological Processes 2008, 22:596-604.
8. Jain S.K., Nayak P.C., Sudheer K.P. Models for estimating evapotranspiration using artificial neural networks, and their physical interpretation. Hydrological Processes 2008, 22(13):2225-2234.
9. Johnson C.E., Driscoll C.T., Siccama T.G., Likens G.E. Element and landscape position in a Northern Hardwood forest watershed ecosystem. Ecosystems 2000, 3:159-184.
10. Kang W., Tian D., Wen S., et al. Studies on water balance and laws of evapotranspiration in a Chinese fir plantation. Acta Phytoecologica/Geobotanica Sinica 1992, 16:187-196. (in Chinese).
11. Kisi O. Modeling monthly evaporation using two different neural computing techniques. Irrigation Science 2009, 27:417-430.
12. Kumar M., Raghuwanshi N.S., Singh R., Wallender W.W., Pruitt W.O. Estimating evapotranspiration using artificial neural network. Journal of Irrigation and Drainage Engineering 2002, 128(4):224-233.
13. Liu Z., Peng C., Xiang W., et al. Application of artificial neural networks in global climate change and ecological research: an overview. Chinese Science Bulletin 2010, 55:2987-2997.
14. Li M., Kang W. A study of hydrological process of secondary-generation Chinese fir plantation. Journal of Central South University of Forestry and Technology 2007, 27:17-21.
15. Likens G.E., Bormann F.H. Biogeochemistry of a Forested Ecosystem 1995, Springer-Verlag, New York, p. 159.
16. Liong S.Y., Khu S.T., Chan W.T. Derivation of Pareto front with genetic algorithm and neural network. Journal of Hydrologic Engineering 2001, 6(1):52-61.
17. Nash J.E., Sutcliffe J.V. River flow forecasting through conceptual models. Journal of Hydrology 1970, 10:282-290.
18. Pan W., Tian D., Chen X., et al. Hydrological process and nutrient dynamics of a subtropical Chinese fir plantation ecosystem. Journal of Central South Forestry College 1989, 19:1-9.
19. 2O emissions from a temperate grassland ecosystem. Ecological Modeling 2004, 175:189-194.
20. Tian D., He B., Xu H. Study on hydrology effect by artificial disturbance in Chinese fir plantation ecosystem. Long Term Located Reach On Forest Ecosystem 1993, 187-193. Chinese Forestry Press, Beijing. Liu Xuanzhang (Ed.).
21. Tian D., Xiang W. Nutrient characteristics in hydrological processes of Chinese fir plantation ecosystem. Acta Ecologica Sinica 2003, 23:1369-1376. (in Chinese).
22. Tian D. Research Methods of Chinese Fir Plantation Ecosystem 2004, Science Press, Beijing, pp. 320-341 (in Chinese).
23. Tian D. The Function Process of Chinese Fir Plantation Ecosystem 2005, Science Press, Beijing, pp. 36-49 (in Chinese).
24. Trajkovic S., Todorovic B., Stankovic M. Forecasting of reference evapotranspiration by artificial neural network. Journal of Irrigation and Drainage Engineering 2003, 129(6):454-457.
25. Traore S., Wang Y.M., Kerh T. Artificial neural network for modeling reference evapotranspiration complex process in Sudano-Sahelian zone. Agricultural Water Management 2010, 97(5):707-714.
26. Wong F., Tan C. Hybrid neural, genetic, and fuzzy systems. Trading on the Edge 1994, 243-261. G.J. Deboeck (Ed.).
27. Yuksel N., Turkoglu M., Baykara T. Modelling of the solvent evaporation method for the preparation of controlled release acrylic microspheres using neural networks. Journal of Microencapsulation 2000, 17(5):541-551.
28. Zanetti S.S., Sousa E.F., Oliveira V.P.S., Almeida F.T., Bernardo S. Estimating evapotranspiration using artificial neural network and minimum climatological data. Journal of Irrigation and Drainage Engineering 2007, 133(2):83-89.
29. Zhao M., Xiang W., Peng C., et al. Simulating age-related changes in carbon storage and allocation in a Chinese fir plantation growing in southern China using the 3-PG model. Forest Ecology and Management 2009, 257:1520-1531.
30. Zhen S., Li Y., Mu C. Review on forest hydrology research. World Forestry Research 2009, 22:28-33.