Handbook of engineering hydrology : modeling, climate by Saeid Eslamian

By Saeid Eslamian

''This complete guide covers a number of facets of hydrology and with a brand new method. different books at the topic deal ordinarily with classical facets of hydrology--particularly floor and flooring water--and actual and chemical toxins. This quantity covers administration issues together with water shortage, water protection, water coverage and governance, and extra. It highlights the environmental points of hydrology such Read more...

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Extra resources for Handbook of engineering hydrology : modeling, climate change, and variability

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12) C (z , z )² The full double integral is a probability weighted average of C(u, v). To compare this, the partial integral has to be divided by the weights, thus the first power of C(z,z) is the denominator. This quotient gives the average value of C(u, v), which increases as a function of z. The second C(z, z) divisor expresses this average relative to C(z, z). It should be that J(1) = τ. 13) n z i × I{ui < zetv i < z }, with I is the indicator function. where I(z) is defined by I (z ) = 1/n i =1 M(z) function is the cumulative conditional mean defined by z Verifying M(1) = 1/2.

Journal of Hydrology 405: 451–461. 2. , 2006. Copula-based geostatistical models for groundwater quality parameters. 1029/2005WR004754, 12pp. 3. , 2006. Fuzzy unit hydrograph. 1029/2004WR003751, 10pp. 4. Chebana, F. , 2009. Multivariate quantiles in hydrological frequency analysis. Environmetrics 22: 63–78. 5. Ellouze-Gargouri, E. , 2006. Prédétermination des débits maximaux de crue par simulation Monte-Carlo de la pluie nette. Revue des Sciences de l’Eau 19(4): 327–345. 6. , 2003. Modelling dependence with copulas and applications to risk management.

A critical first step in developing a robust and accurate ANN model is identifying the critical input or predictor variables necessary for predicting the system states of interest. One frequent criticism of ANN models is that they are “black boxes” that do not explicitly account for the physics of the system of interest. While this is true, in order to develop a robust model capable of accurately predicting system behavior of interest, a strong conceptual if not theoretical understanding of the system is necessary.

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