Articles | Volume 14, issue 7
https://doi.org/10.5194/nhess-14-1641-2014
https://doi.org/10.5194/nhess-14-1641-2014
Research article
 | 
02 Jul 2014
Research article |  | 02 Jul 2014

Streamflow simulation methods for ungauged and poorly gauged watersheds

A. Loukas and L. Vasiliades

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Cited articles

Abrahart, R. J., Anctil, F., Coulibaly, P., Dawson, C. W., Mount, N. J., See, L. M., Shamseldin, A. Y., Solomatine, D. P., Toth, E., and Wilby, R. L.: Two decades of anarchy? Emerging themes and outstanding challenges for neural network river forecasting, Prog. Phys. Geog., 36, 480–513, 2012.
Abrahart, R. J., See, L. M., Dawson, C. W., Shamseldin, A. Y., and Wilby, R. L.: Nearly two decades of neural network hydrologic modeling, in: Advances in Data-Based Approaches for Hydrologic Modeling and Forecasting, edited by: Sivakumar, B. and Berndtsson, R., World Scientific Publishing, Hackensack, NJ, 267–346, 2010.
Abrahart, R. J., Kneale, P. E., and See, L. M. (Eds.): Neural Networks for Hydrological Modelling, Taylor and Francis Group plc, London, UK, 2004.
Ahmad, Z., Hafeez, M., and Ahmad, I.: Hydrology of mountainous areas in the upper Indus Basin, Northern Pakistan with the perspective of climate change, Environ. Monit. Assess., 184, 5255–5274, 2012.
Anctil, F., Michel, C., Perrin, C., and Adreassian, V.: A soil moisture index as an auxiliary ANN input for stream flow forecasting, J. Hydrol., 286, 155–167, 2004a.
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