References
- 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. Fao, Rome, 300(9), D05109. http://www.fao.org/docrep/x0490e/x0490e00.htm
- Bautista, F., Bautista, D., & Delgado-Carranza, C. (2009). Calibration of the equations of Hargreaves and Thornthwaite to estimate the potential evapotranspiration in semi-arid and subhumid tropical climates for regional applications. Atmósfera, 22(4), 331–348. http://www.scielo.org.mx/scielo.php?pid=S0187-62362009000400001&script=sci_arttext&tlng=pt
- Beven, K. J. (2000). Uniqueness of place and process representations in hydrological modelling. Hydrology and Earth System Sciences, 4(2), 203–213. https://doi.org/https://doi.org/10.5194/hess-4-203-2000
- Beven, K. J. (2001). Calibration, validation and equifinality in hydrological modelling. In M. G. Anderson & P. D. Bates (Eds.), Validation in hydrological modelling (pp. 43–55). John Wiley and Sons.
- Beven, K. J. (2011). Rainfall-runoff modelling: The primer. John Wiley and Sons.
- Brooks, R., & Corey, T. (1964). Hydraulic properties of porous media (Hydrology Papers). Colorado State University, 24, 37.
- Debele, B., Srinivasan, R., & Gosain, A. K. (2010). Comparison of process-based and temperature-index snowmelt modeling in SWAT. Water Resources Management, 24(6), 1065–1088. https://doi.org/https://doi.org/10.1007/s11269-009-9486-2
- Duan, Q., Gupta, H., Sorooshian, S., Rousseau, M., & Turcotte, R. (2003). Calibration of watershed models: Water Science and Application (Vol. 6). American Geophysical Union.
- Duan, Q., Sorooshian, S., & Gupta, V. (1992). Effective and efficient global optimization for conceptual rainfall-runoff models. Water Resources Research, 28(4), 1015–1031. https://doi.org/https://doi.org/10.1029/91WR02985
- Dümenil, L., & Todini, E. (1992). A rainfall–runoff scheme for use in the Hamburg climate model. In J. P. O'Kane (Ed.), Advances in theoretical hydrology (pp. 129–157). Elsevier.
- Eberhart, R., & Kennedy, J. (1995, October). A new optimizer using particle swarm theory. In MHS’95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science (pp. 39–43). IEEE.
- Franchini, M., & Pacciani, M. (1991). Comparative analysis of several conceptual rainfall-runoff models. Journal of Hydrology, 122(1–4), 161–219. https://doi.org/https://doi.org/10.1016/0022-1694(91)90178-K
- Freer, J., Beven, K., & Ambroise, B. (1996). Bayesian estimation of uncertainty in runoff prediction and the value of data: An application of the GLUE approach. Water Resources Research, 32(7), 2161–2173. https://doi.org/https://doi.org/10.1029/95WR03723
- Liang, X., Lettenmaier, D. P., Wood, E. F., & Burges, S. J. (1994). A simple hydrologically based model of land surface water and energy fluxes for general circulation models. Journal of Geophysical Research: Atmospheres, 99(D7), 14415–14428. https://doi.org/https://doi.org/10.1029/94JD00483
- Lohmann, D., Raschke, E., Nijssen, B., & Lettenmaier, D. P. (1998). Regional scale hydrology: I. Formulation of the VIC-2L model coupled to a routing model. Hydrological Sciences Journal, 43(1), 131–141. https://doi.org/https://doi.org/10.1080/02626669809492107
- Moore, R. J. (2007). The PDM rainfall-runoff model. Hydrology and Earth System Sciences, 11(1), 483–499. https://doi.org/https://doi.org/10.5194/hess-11-483-2007
- Moradkhani, H., & Sorooshian, S. (2009). General review of rainfall-runoff modeling: Model calibration, data assimilation, and uncertainty analysis. In S. Sorooshian, et al. (Eds.), Hydrological modelling and the water cycle (pp. 1–24). Springer.
- Saha, S., Moorthi, S., Wu, X., Wang, J., Nadiga, S., Tripp, P., Behringer, D., Hou, Y. T., Chuang, H. Y., Iredell, M., & Ek, M. (2014). The NCEP climate forecast system version 2. Journal of Climate, 27(6), 2185–2208. https://doi.org/https://doi.org/10.1175/JCLI-D-12-00823.1
- Shi, Y., & Eberhart, R. (1998, May). A modified particle swarm optimizer. In 1998 IEEE international conference on evolutionary computation proceedings. IEEE world congress on computational intelligence (Cat. No. 98TH8360) (pp. 69–73). IEEE.
- Sorooshian, S. (1991). Parameter estimation, model identification, and model validation: Conceptual-type models. In D. S. Bowles & P. E. O'Connell (Eds.), Recent advances in the modeling of hydrologic systems (pp. 443–467). Springer.
- Todini, E. (1996). The ARNO rainfall—runoff model. Journal of Hydrology, 175(1–4), 339–382. https://doi.org/https://doi.org/10.1016/S0022-1694(96)80016-3
- Todini, E. (2002). The ARNO model. In V. P. Singh & D. K. Fervert (Eds.), Mathematical models of large watershed hydrology (687–716). Water Resources Publications LLC.
- Todini, E., & Bossi, A. (1986). PAB (Parabolic and Backwater) an unconditionally stable flood routing scheme particularly suited for real time forecasting and control. Journal of Hydraulic Research, 24(5), 405–424. https://doi.org/https://doi.org/10.1080/00221688609499317
- Wagener, T., Lees, M. J., & Wheater, H. S. (2001). A toolkit for the development and application of parsimonious hydrological models. In V. P. Singh & D. K. Fervert (Eds.), Mathematical models of large watershed hydrology (87–136). Water Resources Publications LLC.
- Wagener, T., McIntyre, N., Lees, M. J., Wheater, H. S., & Gupta, H. V. (2003). Towards reduced uncertainty in conceptual rainfall-runoff modelling: Dynamic identifiability analysis. Hydrological Processes, 17(2), 455–476. https://doi.org/https://doi.org/10.1002/hyp.1135
- Wagener, T., Sivapalan, M., Troch, P., & Woods, R. (2007). Catchment classification and hydrologic similarity. Geography Compass, 1(4), 901–931. https://doi.org/https://doi.org/10.1111/j.1749-8198.2007.00039.x
- Wagener, T., Wheater, H., & Gupta, H. V. (2004). Rainfall-runoff modelling in gauged and ungauged catchments. World Scientific.
- Wang, A., Li, K. Y., & Lettenmaier, D. P. (2008). Integration of the variable infiltration capacity model soil hydrology scheme into the community land model. Journal of Geophysical Research, 113(D9). https://doi.org/https://doi.org/10.1029/2007JD009246
- Wood, E. F., Lettenmaier, D. P., & Zartarian, V. G. (1992). A land-surface hydrology parameterization with subgrid variability for general circulation models. Journal of Geophysical Research, 97(D3), 2717–2728. https://doi.org/https://doi.org/10.1029/91JD01786
- Yuan, X., Wood, E. F., Luo, L., & Pan, M. (2011). A first look at Climate Forecast System version 2 (CFSv2) for hydrological seasonal prediction. Geophysical Research Letters, 38(13). https://doi.org/https://doi.org/10.1029/2011GL047792
- Yuan, X., Wood, E. F., Roundy, J. K., & Pan, M. (2013). CFSv2-based seasonal hydroclimatic forecasts over the conterminous United States. Journal of Climate, 26(13), 4828–4847. https://doi.org/https://doi.org/10.1175/JCLI-D-12-00683.1
- Zhao, R. J. (1977). Flood forecasting method for humid regions of China. East China College of Hydraulic Engineering.
- Zhao, R. J. (1992). The Xinanjiang model applied in China. Journal of Hydrology, 135(1–4), 371–381. https://doi.org/https://doi.org/10.1016/0022-1694(92)90096-E
- Zhao, R. J., & Liu, X.-R. (1995). The Xinanjiang model. In V. P. Singh (Ed.), Computer models of watershed hydrology (pp. 215–232). Water Resource Publications.
- Zhao, R. J., Zhuang, Y.-L., Fang, L.-R., Liu, X.-R., & Zhang, Q.-S. (1980). The Xinanjiang model. In Hydrological Forecasting, IAHS Publication No. 129 (pp. 351–356). Int. Assoc. Sci. Hydrol. Press.