Hydrologic Synthesis Using Entropy Theory: Review

By Vijay P. Singh. 2011

130 citations recorded by the source corpus.

Subfields: Ocean Engineering, Statistical and Nonlinear Physics, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/b6a087ec82f91e358d8d2923bcc1343908460f2d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ocean Engineering

1. Y. P. Li
2. Hoshin V. Gupta
3. Jasper A. Vrugt
4. Thorsten Wagener
5. M. Clark

In Statistical and Nonlinear Physics

1. Ilias Pechlivanidis
2. Hoshin V. Gupta
3. B. Jackson
4. Hilary K. McMillan

In Water Science and Technology

1. Hilary K. McMillan
2. B. Jackson
3. Ilias Pechlivanidis
4. Y. P. Li
5. Y. Fan
6. G. H. Huang
7. Hoshin V. Gupta
8. Xiang-Ming Kong

Citations in the corpus

• Maximum entropy-Gumbel-Hougaard copula method for simulation of monthly streamflow in Xiangxi river, China (2015, background): “…simulation, mean, standard deviation, skewness and kurtosis can be regarded as constraints for deriving the distribution of streamflow (Hao and Singh 2011), which can be stated as: C0 ¼ Z b a f xð Þdx ¼ 1 ð2Þ Ci ¼ Z b a hi xð Þf xð Þdx ¼ hi xð Þ i ¼ 1; 2; . . .;m ð3Þ where x are the…”
• Use of an entropy‐based metric in multiobjective calibration to improve model performance (2014, background): “This and further related measures have found scientific application in a range of problems in hydrology and water resources [Koutsoyiannis, 2005a, 2005b; Maruyama et al., 2005; Hejazi et al., 2008; Ruddell and Kumar, 2009; Singh, 2010]; see Singh [2011] for an extensive review.”