A system-theory-based model for monthly river runoff forecasting: model calibration and optimization

Abrahart, R.J., See, L., 2002. Multi-model data fusion for river flow forecasting: an evaluation of six alternative methods based on two contrasting catchments. Hydrol. Earth Syst. Sc. 6, 4, 655-670.10.5194/hess-6-655-2002Search in Google Scholar

Adrien, N.G., 2004. Computational Hydraulics and Hydrology: An Illustrated Dictionary. CRC Press, New York.Search in Google Scholar

Al-Taiee, T.M., 2008. Statistical prediction of Tigris River levels at Mosul hydrological station, north IRAQ. J. Hydrol. Hydromech., 56, 4, 272-279.Search in Google Scholar

An, Y.H., Tang, G.Y., Zhang, F.C., Yao, X.J., 2005. Application of systematic theory and frequency analytic approach on water resource evaluation. Site Investigation Science and Technology, 5, 38-40 (in Chinese.) Search in Google Scholar

Atiya, A.F., El-Shoura, S.M., Shaheen, S.I., El-Sherif, M.S., 1999. A Comparison Between Neural-Network Forecasting Techniques-Case Study: River Flow Forecasting. IEEE Transactions on Neural Networks, 10, 2, 402-409.10.1109/72.750569Search in Google Scholar

Bertalanffy, L.V., 1950. An outline of general system theory. Brit. J. Philos. Sci., 1, 2, 134-165.10.1093/bjps/I.2.134Search in Google Scholar

Deng, J.L., 1982. Control problems of grey systems. Systems and Control Letters, 5, 288-294.10.1016/S0167-6911(82)80025-XSearch in Google Scholar

Dibike, Y.B., Solomatine, D.P., 2001. River Flow Forecasting Using Artificial Neural Networks. Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere, 26, 1, 1-7.10.1016/S1464-1909(01)85005-XSearch in Google Scholar

Guo, J.J., Wu, J.Y., Wang, R.Z., 2011. A new approach to energy consumption prediction of domestic heat pump water heater based on grey system theory. Energ. Buildings, 43, 1273-1279.10.1016/j.enbuild.2011.01.001Search in Google Scholar

Hang, Q.F., Pan, D.H., 2010. Daily flow prediction of Taidong River based on genetic algorithm and the least square support vector machine (SVM). Pearl River, 4, 6-7, 21. (in Chinese.) Search in Google Scholar

Hu, T.S., Lam, K.C., Ng, S.T., 2001. River flow time series prediction with a range-dependent neural network. Hydrological Sciences-Journal-des Sciences Hydrologiques, 46, 5, 729-145.10.1080/02626660109492867Search in Google Scholar

Huang, J.C., 2011. Application of grey system theory in telecare. Computers in Biology and Medicine, 41, 302-306.10.1016/j.compbiomed.2011.03.00721492833Search in Google Scholar

Janál, P., Starý, M., 2009. Fuzzy model use for prediction of the state of emergency of river basin in the case of flash flood. J. Hydrol. Hydromech., 57, 3, 145-153.10.2478/v10098-009-0013-1Search in Google Scholar

Janál, P., Starý, M., 2012. Fuzzy model use for prediction of the state of emergency of river basin in the case of flash flood- Part 2. J. Hydrol. Hydromech., 60, 3, 162-173.10.2478/v10098-012-0014-3Search in Google Scholar

Jeníček, M., 2009. Runoff changes in areas differing in landuse in the Blanice river basin-application of the deterministic model. J. Hydrol. Hydromech., 57, 3, 154-161.10.2478/v10098-009-0014-0Search in Google Scholar

Kayacan, E., Ulutas, B., Kaynak, O., 2011. Grey system theorybased models in time series prediction. Expert Systems with Applications, 37, 1784-1789.10.1016/j.eswa.2009.07.064Search in Google Scholar

Kişi, Ö., 2007. Streamflow Forecasting Using Different Artificial Neural Network Algorithms. J. Hydrol. Eng., 12, 5, 532-539.10.1061/(ASCE)1084-0699(2007)12:5(532)Search in Google Scholar

Kliment, Z., Matoušková, M., Ledvinka, O., Královec, V., 2011. Trend analysis of rainfall-runoff regimes in selected headwater areas of the Czech Republic. J. Hydrol. Hydromech., 59, 1, 36-50.10.2478/v10098-011-0003-ySearch in Google Scholar

Larsson, P., Dekker, S.W.A., Tingvall, C., 2010. The need for a systems theory approach to road safety. Safety Sci., 48, 1167-1174.10.1016/j.ssci.2009.10.006Search in Google Scholar

Mahabir, C., Hicks, F.E., Fayek, A.R., 2003. Application of fuzzy logic to forecast seasonal runoff. Hydrol. Process., 17, 3749-3762.10.1002/hyp.1359Search in Google Scholar

Sahoo, G.B., Ray, C., 2006. Flow forecasting for a Hawaii stream using rating curves and neural networks. J. Hydrol., 317, 63-80.10.1016/j.jhydrol.2005.05.008Search in Google Scholar

Shahraiyni, H.T., Ghafouri, M.R., Shouraki, S.B., Saghafian, B., Nasseri, M., 2012. Comparison between active learning method and support vector machine for runoff modeling. J. Hydrol. Hydromech., 60, 1, 16-32.10.2478/v10098-012-0002-7Search in Google Scholar

Shen, V.R.L., Chung, Y.F., Chen, T.S., 2009. A novel application of grey system theory to information security (Part I). Computer Standards & Interfaces, 31, 277-281.10.1016/j.csi.2007.11.018Search in Google Scholar

Singh, P., Kumar, A., Kumar, N., Kishore, N., 2010. Hydrometeorological correlations and relationships for estimating streamflow for Gangotri Glacier basin in Western Himalayas. International Journal of Water Resources and Environmental Engineering, 2, 3, 60-69.Search in Google Scholar

Sivakumar, B., Berndtsson, R., Persson, M., 2001. Monthly runoff prediction using phase space reconstruction. Hydrological Sciences-Journal-des Sciences Hydrologiques, 46, 3, 377-387.10.1080/02626660109492833Search in Google Scholar

Song, Y.X., Wu, J.H., Li, P.Y., 2011. Application of System Theory in the Calculation of Groundwater Resources Availability in Balasu Water Source. Proceedings of 2011 IEEE 3rd International Conference on Communication Software and Networks, ICCSN 2011. Xi’an, China, May, 27-29, pp. 707-710.Search in Google Scholar

Trivedi, H.V., Singh, J.K., 2005. Application of Grey System Theory in the Development of a Runoff Prediction Model. Biosystems Engineering, 92, 4, 521-526.10.1016/j.biosystemseng.2005.09.005Search in Google Scholar

Wang, H.X., Yan, T.Z., Tang, H.M., Teng, W.F., 1999. Forecasting and decision-making of systematic theories for engineering geology in environmental geosciences. Journal of China University of Geosciences, 10, 4, 327-328.Search in Google Scholar

Wang, W.D., 2009. Mid-long term average flow forecast of Jiyuan Hydrological Station of Python River. Henan Water Resources & South-to-North Water Diversion, 10, 35-39. (in Chinese.)Search in Google Scholar

Wang, K.C., 2011. A hybrid Kansei engineering design expert system based on grey system theory and support vector regression. Expert Systems with Applications, 38, 8738-8750.10.1016/j.eswa.2011.01.083Search in Google Scholar

Wei, H.S., 2009. System theory. World Book Publishing Company, Beijing. (in Chinese.) Wei, Y.X., Wang, L.X., 2005. Engineering hydrology. China Water Conservancy and Hydropower Press, Beijing. (in Chinese.)Search in Google Scholar

Wu, J.S., Han, J., Annambhotla, S., Bryant, S., 2005. Artificial Neural Networks for Forecasting Watershed Runoff and Stream Flows. J. Hydrol. Eng., 10, 3, 216-222.10.1061/(ASCE)1084-0699(2005)10:3(216)Search in Google Scholar

Yadav, D., Naresh, R., Sharma, V., 2011. Stream flow forecasting using Levenberg-Marquardt algorithm approach. International Journal of Water Resources and Environmental Engineering, 3, 1, aa30-40.Search in Google Scholar

Zhao, Y.J., Liu, X.J., Zhao, Y., 2011. Forecast for construction engineering risk based on fuzzy sets and systems theory. Systems Engineering Procedia, 1, 156-161.10.1016/j.sepro.2011.08.026Search in Google Scholar

Zhang, Q., 2011. Research on the vegetation change and the environmental impact factors in Hailiutu River Basin. Dissertation. China University of Geosciences (Beijing), Beijing. (in Chinese.)Search in Google Scholar