Allen, R.G, Pereira, L.S, Raes, D., Smith, M., 1998. Crop evapotranspiration guidelines for computing crop water requirements. FAO Irrigation and drainage paper 56. Food and Agriculture Organization, Rome, Italy.

Behmanesh, J., Jabari, A., Montaseri M., Rezaei, H., 2014. Comparing AWBM and SimHyd models in rainfall-runoff modeling (Case study: Nazlou Chay catchment in west Azarbijan). 24th Year, 52(4). (In Persian).

Beven, K., Binley, A., 2014. GLUE: 20 years on. HYDROLOGICAL PROCESSES Hydrol.Process. 28, 5897–5918.

Bormann, B., Breuer, L., Giertz, S., Huisman, J.A., Viney, N.R., 2009. Uncertainties in Environmental Modelling and Consequences for Policy Making Part of the series NATO Science for Peace and Security Series C: Environmental Security.  Chapter: Spatially explicit versus lumped models in catchment hydrology – experiences from two case studies, 3-26.

Boughton, W., 2002. AWBM Catchment Water Balance Model, Calibration and Operation Manual, 30p.

Burnash, R.J.C., 1995. The NWS river forecasting-catchment modeling. In: Singh, V.J. (Ed.), Computer Models of Watershed Hydrology. Water Resources Publication, Highlands Ranch, Colorado, 311–366.

Burnash, R.J.C., Ferral, R.L., McGuire, R.A., 1973. Joint Federal-State River Forecast Center,. A Generalized Streamflow Simulation System; Conceptual Modeling for Digital Computers. US Dept. of Commerce National Weather Service and State of California Dept. of Water Resources, Sacramento. p. 204.

Chai, T., Draxler, R. R., 2014. Root mean square error (RMSE) or mean absolute error (MAE)? Arguments against avoiding RMSE in the literature. Journal of Geoscience, Model Development 7, 1247–1250.

Chen, J., Adams. B.J., 2006. Integration of artificial neural networks with conceptual models in rainfall-runoff modeling. J Hydrol 318, 232-249.

Chiew, F.H.S., Peel, M.C., Western, A.W., 2002. Application and testing of the simple rainfall-runoff model SIMHYD. In: Mathematical Models of Watershed Hydrology, Water Resources Publication, and Littleton. Colorado.

Collopy, F., Armstrong, J. S., 1992. Rule-based forecasting: development and validation of an expert Systems approach to combining time series extrapolations. Management Science 38, 1394–1414.

Downer, C., Ogden, F., Martin, W., Harmon, R., 2002. Theory, development, and applicability of the surface water hydrologic model CASC2D. Hydrol. Process 16(2), 255-275.

Duan, Q., 2003. Global optimization for watershed model calibration. In:  Calibration of Watershed Models (ed. by Q. Duan, H. V. Gupta, S. Sorooshian, A. N. Rousseau & R. Turcotte), 89–104. Water Science and Application 6,  Am. Geophys. Union, Washington DC, USA.

Ekenberg, M., 2016. Using a lumped conceptual hydrological model for five different catchments in Sweden. Master’s thesis Physical Geography and Quaternary Geology, University of Stockholm.

FAO. 1996. Irrigation and Drainage paper, Guideline for predicting Crop water Requirements. Food and Agriculture Arganization of the United Nations, Rome. 154p.

Goldberg, D. E., 1989. Genetic Algorithms in Search, Optimization, and Machine Learning. Addison Wesley, Boston, USA.

Goodarzi M. R., Zahabiyoun, B., Massah Bavani, A. R., Kamal .A. R., 2012. Performance comparison of three hydrological models SWAT, IHACRES and SIMHYD for the runoff simulation of Gharesou basin. Water and Irrigation Management, 2(1). Spring 2012.( In Persian).

Gooijer, J. G D., Hyndman, R. J., 2006. 25 Years of Time Series Forecasting. International journal of forecasting 22, 443-473.

Goswami, M., o’Connor, K, M., 2007. Comparative assessment of six automatic optimization techniques for calibration of a conceptual rainfall—runoff model, Hydrological Sciences Journal 52:3, 432-449.

Hashemi, M., Mehrabi, H., 2007. Developing a rainfall-runoff model using GISConference of Geomatics.

Haydon, S., Deletic, A., 2007. Sensitivity testing of a coupled Escherichia coli – Hydrologic catchment model. Hydrology 338, 161-173.

Heryansyah, A., 2001. Application of tank model on runoff and water quality for land uses management in Cidanau watershed. Master’s Thesis. Bogor Agricultural University. Bogor. Indonesia.

Holland, J. H., 1975. Adaptation in Natural and Artificial Systems. The University of Michigan Press, Ann Arbor, USA.

Khakbaz, B., Imam, B., Hsu, K., Sorooshian, S., 2012. From lumped to distributed via semi-distributed: Calibration strategies for semi-distributed hydrologic models. Journal of Hydrology 418–419, 61–77.

Li, Cz., Hao, W., Jia, L., Yan, Dh.,Yu, Fl., Zhang, Lu., 2010. Effect of calibration data series length on performance and optimal parameters of hydrological model. Water Science and Engineering 3(4), 378-393.

Markstrom, S.L., Regan, R.S., Hay, L.E., Viger, R.J., Webb, R.M.T., Payn, R.A., LaFontaine, J.H., 2015. PRMS-IV, the precipitation-runoff modeling system, version 4: U.S. Geological Survey Techniques and Methods, book 6, chap. B7, 158 p.

Nash, J. E., Sutcliffe, J. V., 1970. River flow forecasting through conceptual models, Part 1, A discussion of principles. J. Hydrol 10, 282–290.

Peel, M.C., .Chiew, F.H.S., Western, A.W., McMahon, TA., 2000. Extension of Unimpaired Monthly Streamflow Data and Regionalisation of Parameter Values to Estimate Streamflow in Ungauged Catchments, Report prepared for the National Land and Water Resources Audit, In Australian Natural Resources Atlas. 37 p.

Podger, G., 2005. Rainfall Runoff Library (RRL). Catchment Modeling Toolkit prepared by the © CRC for Catchment Hydrology, Australia. Pp: 110.

Reed, S., Koren, V., Smith, M., Zhang, Z., Moreda, F., Seo, D.J., 2004. Overall distributed model intercomparison project results. Journal of Hydrology 298 (1–4), 27–60.

Rostami Khalaj, M., Moghadam Nia, A., Salmani, H., Sepahvand, A., 2016. Comparison investigation of Tank, Smar, SIMHYD, Sacramento and AWBM rainfall-runoff model performance. Journal of Natural Ecosystem of IRAN 7(2), 47-63.

Rouhani, H., Farahi Moghadam, M., 2013. Automatic calibration of Tank and SIMHYD rainfall-runoff models using genetic alghoritm. Journal of Range and Watershed 66(4), 521-533.

Salmani, H., Bahremand, A., Saberchenari, K., Rostmi Khalaj, M., 2014. Investigation of Tank, Sacramento and AWBM rainfall-runoff model performance in simulation of Araz-Kouseh runoff. Journal of ecohydrology 1(3), 207-221 (in Persian).

Setiawan, B. I., yanto, R., Ilstedt, U., Malmer, A., 2007.  Optimization of Hydrologic Tank Model’s Parameters. Swedish University of Agricultural Sciences, Department of Forest Ecology, Umeå, Sweden.

Sharifi, F., Boyd, M.J., 1994. A Comparision of the SFB and AWBM Rainfall-Runoff Models, 25th Congress of the International Assosiation of Hydrologeologists/ International Hydrology & Water Resources Symposium of the Insitution of Engineers, Australia. ADELAIDE. 21-25 November, 491-495.

Sheikh Goodarzi, M., 2013. General review of ecosystem based hydrological modeling technics. PhD Seminar, Department of Environment, University of Tehran, Iran. 59p.

Sugawara, M., Watanabe, I., Ozaki, E., Katsuyama, Y., 1984. Tank Model with Snow Component. Research note no, 65. National Research Center for Disaster Preventation, Japan. 293p.

Tahmasebi, R., Sharifi, F., Kaveh, F., Tavassoli, A., 2010. Designing of Rainwater Collecting Systems in Micro Catchment by Using AWBM Model for Cultivating of Forage Maize SC704. Journal of Range and Watershed Management, Iranian Journal of Natural Resources 63(3), 359—373 (In Persian).

USGS. 2008. Calculating Flow-Duration and Low-Flow Frequency Statistics at Streamflow-Gaging Stations. U.S. Department of the Interior, Scientific investigation report 2008-5126.

Verstraeten, W.W., Muys, B., Feyen, J., Veroustraete, F., Minnaert, M., Meiresonne, L., De Schrijver, A., 2005. Comparative analysis of the actual evapotranspiration of Flemish forest and cropland, using the soil water balance model WAVE. Hydrol Earth Syst Sci 9, 225–241.

Viglione, A., Parajka, J., Rogger, M., Salinas, J. L., Laaha, G., Sivapalan, M., Bl¨oschl, G., 2013. Comparative assessment of predictions in ungauged basins – Part 3: Runoff signatures in Austria. Journal of Hydrol. Earth Syst. Sci 17, 2263–2279.

Willmott , C., Matsuura, K., 2005. Advantages of the Mean Absolute Error (MAE) over  the Root Mean Square Error (RMSE) inassessingaveragemodelperformance,Clim.Res 30,79–82.

Yokoo, Y., Kazama, S., Sawamoto, M., Nishimura, H., 2001. Regionalization of lumped water balance model parameters based on multiple regression. J Hydrol 246, 209-222.

Zarin, H., Moghaddamnia, A.R., Nam Dorost, J., Mosaedi, A., 2013. Simulation of outlet runoff in ungauged catchments by using AWBM Rainfall-Runoff Model. J. of Water and Soil Conservation 20(2), (In Persian).