Modeling the daily suspended sediment concentration in a hyperconcentrated river on the Loess Plateau, China, using the Wavelet-ANN approach

Geomorphology

Volumn 186, Issue , 2013, Pages 181-190

  Liu, Qian Jin ^a,c   Shi, Zhi Hua ^a,b   Fang, Nu Fang ^b   Zhu, Hua De ^a   Ai, Lei ^a  

^a HUAZHONG AGRICULTURAL UNIVERSITY   (China)

^b INSTITUTE OF SOIL AND WATER CONSERVATION   (China)

^c LINYI UNIVERSITY   (China)

Author keywords

Artificial neural network; Hyperconcentrated flow; River discharge; Suspended sediment concentration; Wavelet analysis

Indexed keywords

ARTIFICIAL NEURAL NETWORK; CATCHMENT; CONCENTRATION (COMPOSITION); ERROR CORRECTION; NUMERICAL MODEL; RIVER DISCHARGE; SUSPENDED SEDIMENT; WAVELET ANALYSIS;

CHINA; LOESS PLATEAU; YELLOW RIVER;

EID: 84873742567     PISSN: 0169555X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.geomorph.2013.01.012     Document Type: Article

References (61)

1. Alp M., Cigizoglu H.K. Suspended sediment load simulation by two artificial neural network methods using hydrometeorological data. Environmental Modeling and Software 2007, 22(1):2-13.
2. Altun H., Curtis K.M., Yalcinoz T. Neural learning for articulatory speech synthesis under different statistical characteristics of acoustic input patterns. Computers and Electrical Engineering 2003, 29:687-702.
3. Altun H., Bilgil A., Fidan B.C. Treatment of multi-dimensional data to enhance neural network estimators in regression problems. Expert Systems with Applications 2007, 32(2):599-605.
4. Anctil F., Tape G.D. An exploration of artificial neural network rainfall runoff forecasting combined with wavelet decomposition. Journal of Environmental Engineering and Science 2004, 3:121-128.
5. ASCE Task Committee on Application of Artificial Neural Networks in Hydrology Artificial neural networks in hydrology: 2. Hydrology applications. Journal of Hydrologic Engineering 2000, 5:124-136.
6. ASCE Task Committee on Application of Artificial Neural Networks in Hydrology Artificial neural networks in hydrology: 1. Hydrology application. Journal of Hydrologic Engineering 2000, 5(2):124-137.
7. Asselman N.E.M. Suspended sediment dynamics in a large drainage basin: the River Rhine. Hydrological Processes 1999, 13(10):1437-1450.
8. Bai Y.C., Xu H.J. Hydrodynamic instability of hyperconcentrated flows of the Yellow River. Journal of Hydraulic Research 2010, 48(6):742-753.
9. Bandyopadhyay G., Chattopadhyay S. Single hidden layer artificial neural network models versus multiple linear regression model in forecasting the time series of total ozone. International journal of Environmental Science and Technology 2007, 14(1):141-149.
10. Beale M.H., Hagan M.T., Demuth H.B. Neural Network Toolbox™ User's Guide 2012, 64-65. MathWorks, Inc., Natick.
11. Bishop C.M. Neural Networks for Pattern Recognition 1995, 371-377. Clarendon Press, Oxford, UK.
12. Brasington J., Richards K. Turbidity and suspended sediment dynamics in small catchments in the Nepal Middle Hills. Hydrological Processes 2000, 14(14):2559-2574.
13. Cannas B., Fanni A., See L., Sias G. Data preprocessing for river flow forecasting using neural networks: wavelet transforms and data partitioning. Physics and Chemistry of the Earth 2006, 31(18):1164-1171.
14. Daubechies I. The wavelet transform, time-frequency localization and signal analysis. IEEE Transactions on Information Theory 1990, 36(5):6-7.
15. Fang H.Y., Cai Q.G., Chen H., Li Q.Y. Temporal changes in suspended sediment transport in a gullied loess basin: the lower Chabagou creek on the Loess Plateau in China. Earth Surface Processes and Landforms 2008, 33(13):1977-1992.
16. Fang N.F., Shi Z.H., Li L., Jiang C. Rainfall, runoff, and suspended sediment delivery relationships in a small agricultural watershed of the Three Gorges area, China. Geomorphology 2011, 135(1-2):158-166.
17. Guldal V., Muftuoglu R.F. 2D unit sediment graph theory. Journal of Hydrologic Engineering 2001, 6(2):132-140.
18. Hessel R. Modelling soil erosion in a small catchment on the Chinese Loess Plateau: applying LISEM to extreme conditions. Netherlands Geographical Studies 2002, 307:1-21.
19. Jain S.K. Development of integrated sediment rating curves using ANNs. Journal of Hydraulic Engineering ASCE 2001, 127(1):30-37.
20. Kim T.W., Valdes J.B. Nonlinear model for drought forecasting based on a conjunction of wavelet transforms and neural networks. Journal of Hydrologic Engineering 2003, 6:319-328.
21. Kisi O. Multi-layer perceptions with Levenberg-Marquardt training algorithm for suspended sediment concentration prediction and estimation. Hydrological Sciences Journal 2004, 49:1025-1040.
22. Kisi O. Daily suspended sediment estimation using neuro-wavelet models. International Journal of Earth Sciences 2010, 99:1471-1482.
23. Kisi O., Karahan M.E., Sen Z. River suspended sediment modelling using a fuzzy logic approach. Hydrological Processes 2006, 20:4351-4362.
24. Koutsoyiannis D. Discussion of "Generalized regression neural networks for evapotranspiration modelling". Hydrological Sciences Journal 2007, 52(4):832-835.
25. Labat D., Ababou R., Mangin A. Wavelet analysis in karstic hydrology 2nd part: rainfall-runoff cross-wavelet analysis. Comptes Rendus de l'Academie des Sciences Series IIA Earth and Planetary Science Letters 1999, 329:881-887.
26. Labat D., Ababou R., Mangin A. Rainfall-runoff relation for karstic spring. Part 2: continuous wavelet and discrete orthogonal multi resolution analyses. Journal of Hydrology 2000, 238:149-178.
27. Legates D.R., McCabe G.J. Evaluating the use of "goodness-of-fit" measures in hydrologic and hydroclimatic model validation. Water Resources Research 1999, 35(1):233-241.
28. Ministry of Water Conservancy and Electric Power, PRC National Standards for Hydrological Survey 1962, vols. 1-7. China Industry Press, Beijing, (in Chinese).
29. Nagy H.M., Watanabe K., Hirano M. Prediction of sediment load concentration in rivers using artificial neural network model. Journal of Hydraulic Engineering ASCE 2002, 128(6):588-595.
30. Nourani V., Komasi M., Mano A. A multivariate ANN-wavelet approach for rainfall-runoff modeling. Water Resources Management 2009, 23:2877-2894.
31. Partal T., Cigizoglu H.K. Estimation and forecasting of daily suspended sediment data using wavelet-neural networks. Journal of Hydrology 2008, 358:317-331.
32. Pasquini A., Depetris P. Discharge trends and flow dynamics of South American rivers draining the southern Atlantic seaboard: an overview. Journal of Hydrology 2007, 333:385-399.
33. Phillips J.M., Walling D.E. The particle size characteristics of fine-grained channel deposits in the River Exe Basin, Devon, UK. Hydrological Processes 1999, 13(1):1-19.
34. Rajaee T. Wavelet and ANN combination model for prediction of daily suspended sediment load in rivers. Science of the Total Environment 2011, 409:2917-2928.
35. Rajaee T., Mirbagheri S.A., Zounemat-Kermani M., Nourani V. Daily suspended sediment concentration simulation using ANN and neuro-fuzzy models. Science of the Total Environment 2009, 407:4916-4927.
36. Rajaee T., Mirbagheri S.A., Nourani V., Alikhani A. Prediction of daily suspended sediment load using wavelet and neuro-fuzzy combined model. International journal of Environmental Science and Technology 2010, 7(1):93-110.
37. Rene E.R., Kim J.H., Park H.S. An intelligent neural network model for evaluating performance of immobilized cell biofilter treating hydrogen sulphide vapors. International journal of Environmental Science and Technology 2008, 5(3):287-296.
38. Saco P., Kumar P. Coherent modes in multiscale variability of streamflow over the United States. Water Resources Research 2000, 36:1049-1068.
39. Saito Y., Wei H.L., Zhou Y.Q., Nishimara A., Sato Y., Yokta S. Delta propagation and chenier formation in the Huanghe (Yellow River) delta, China. Journal of Asian Earth Sciences 2000, 18(4):489-497.
40. Sang Y.F., Wang D., Wu J.C., Zhu Q.P., Qang L. The relation between periods' identification and noises in hydrologic series data. Journal of Hydrology 2009, 368:165-177.
41. Sedimentation Commission of Chinese Society of Hydraulic Engineering Handbook of Sedimentation 1992, Publishing House for Environmental Sciences, Beijing, (in Chinese).
42. Shiri J., Kisi O. Short-term and long-term streamflow forecasting using a wavelet and neuro-fuzzy conjunction model. Journal of Hydrology 2010, 394:486-493.
43. Solomatine D.P., Ostfeld A. Data-driven modelling: some past experiences and new approaches. Journal of Hydroinformatics 2008, 10(1):3-22.
44. Sui J., He Y., Karney B.W. Flow and high sediment yield from the Huangfuchuan watershed. International journal of Environmental Science and Technology 2008, 5(2):149-160.
45. Sui J., He Y., Liu C. Changes in sediment transport in the Kuye River in the Loess Plateau in China. International Journal of Sediment Research 2009, 24:201-213.
46. Tiwari M.K., Chatterjee C. Development of an accurate and reliable hourly flood forecasting model using wavelet-bootstrap-ANN (WBANN) hybrid approach. Journal of Hydrology 2010, 394:458-470.
47. Walling D.E. Suspended sediment and solute response characteristics of the river Exe, Devon, England. Research in Fluvial Systems 1978, 169-197. Geoabstracts, Norwich, UK. R. Davidson-Arnott, W. Nickling (Eds.).
48. Wang W., Ding J. Wavelet network model and its application to the prediction of the hydrology. Nature and Science 2003, 1(1):67-71.
49. Webber J.R., Gupta Y.P. A closed-loop cross-correlation method for detecting model mismatch in MIMO model-based controllers. ISA Transactions 2008, 47:395-400.
50. Wei A.L., Zeng G.M., Huang G.H., Liang J., Li X.D. Modeling of a permeate flux of cross-flow membrane filtration of colloidal suspensions: a wavelet network approach. International journal of Environmental Science and Technology 2009, 6(3):395-406.
51. Wu C.L., Chau K.W., Li Y.S. Methods to improve neural network performance in daily flows prediction. Journal of Hydrology 2009, 372:80-93.
52. Xu J.X. Erosion caused by hyperconcentrated flow on the Loess Plateau. Catena 1999, 36:1-19.
53. Xu J.X. Implication of relationships among suspended sediment size, water discharge and suspended sediment concentration: the Yellow River basin, China. Catena 2002, 49:289-307.
54. Xu J.X. Hyperconcentrated flows in the slope-channel systems in gullied hilly areas on the Loess Plateau, China. Geografiska Annaler Series, A-Physical Geography 2004, 86(4):349-366.
55. Xu J.X., Wang H.B. Influence of soil and water conservation measures on reducing frequency of hyperconcentrated flows in the Wudinghe River basin. Environmental Earth Sciences 2011, 62:1513-1520.
56. Yan Y.X., Xu J.X. Spatial variation of hyperconcentrated flow frequency and its relationship with specific sediment yield in the high-intensity coarse sediment producing area of the Loess Plateau, China. Journal of Sediment Research 2010, (3):9-16. (in Chinese).
57. Zhang N. Prediction of urban stormwater runoff in Chesapeake bay using recurrent neural networks. Advances in Neural Networks-ISNN 2011 2011, 27-36. Springer, Berlin Heidelberg, GER. D.R. Liu, H.G. Zhang, M. Polycarpou, C. Alippi, H.B. He (Eds.).
58. Zhang O.Y., Ma H.B., Zhang H.W., Dong Z.D., Xu X.Z. Experimental study on influences of sediment-laden flow with wide sediment concentration range on channel metamorphosis. Advances in Water Science 2005, 16(1):1-6. (in Chinese).
59. Zhao X.K., Wang J.S., Fan X.L. Analysis on the change trend of runoff and influence factors in Kuye River basin from 1954 to 1993. Journal of Water Resources & Water Engineering 2010, 21(5):32-36. (in Chinese).
60. Zheng M.G., Qin F., Sun L.Y., Qi D., Cai Q.G. Spatial scale effects on sediment concentration in runoff during flood events for hilly areas of the Loess Plateau, China. Earth Surface Processes and Landforms 2011, 36(11):1499-1509.
61. Zhu Y.M., Lu X.X., Zhou Y. Suspended sediment flux modeling with artificial neural network, an example of the Longchuanjiang River in the upper Yangtze catchment, China. Geomorphology 2007, 84:111-125.