Articles | Volume 15, issue 11
https://doi.org/10.5194/hess-15-3327-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.Simplifying a hydrological ensemble prediction system with a backward greedy selection of members – Part 2: Generalization in time and space
Related subject area
Subject: Global hydrology | Techniques and Approaches: Mathematical applications
Projecting end-of-century climate extremes and their impacts on the hydrology of a representative California watershed
Integrating process-related information into an artificial neural network for root-zone soil moisture prediction
Coherence of global hydroclimate classification systems
Design flood estimation for global river networks based on machine learning models
Attributing correlation skill of dynamical GCM precipitation forecasts to statistical ENSO teleconnection using a set-theory-based approach
Hydrol. Earth Syst. Sci., 26, 3589–3609,
2022Hydrol. Earth Syst. Sci., 26, 3263–3297,
2022Hydrol. Earth Syst. Sci., 25, 6173–6183,
2021Hydrol. Earth Syst. Sci., 25, 5981–5999,
2021Hydrol. Earth Syst. Sci., 25, 5717–5732,
2021Cited articles
Alpaydin, E.: Introduction to Machine Learning. Adaptive Computation and Machine Learning, 2nd Edn., The MIT Press, Cambridge, 2010.
Beven, K. and Binley, A.: The future of distributed models: Model calibration and uncertainty prediction, Hydrol. Process., 6, 279–298, https://doi.org/10.1002/hyp.3360060305, 1992.
Bishop, C. M.: Pattern Recognition and Machine Learning (Information Science and Statistics), ISBN0387310738, Springer-Verlag New York, Inc., Secaucus, NJ, USA,2006.
Boucher, M.-A., Perreault, L., and Anctil, F.: Tools for the assessment of hydrological ensemble forecasts obtained by neural networks, J. Hydroinform., 11, 297–307, https://doi.org/10.2166/hydro.2009.037, 2009.
Bougeault, P., Toth, Z., Bishop, C., Brown, B., Burridge, D., Chen, D. H., Ebert, B., Fuentes, M., Hamill, T. M., Mylne, K., Nicolau, J., Paccagnella, T., Park, Y.-Y., Parsons, D., Raoult, B., Schuster, D., Dias, P. S., Swinbank, R., Takeuchi, Y., Tennant, W., Wilson, L., and Worley, S.: The THORPEX Interactive Grand Global Ensemble, B. Am. Meteorol. Soc., 91, 1059–1072, https://doi.org/10.1175/2010BAMS2853.1, 2010.