000			02808cam a22002895i 4500
001			10888
003			IN-BhIIT
005			20240802195222.0
008			161026s2017 gw |||| o |||| 0|eng
020			_a9783319828558
040			_aIN-BhIIT
041			_aeng
082	0	4	_a551.48 _bNAG/F
245	0	0	_aFundamentals of statistical hydrology / _cedited by Mauro Naghettini.
260			_aSwitzerland : _bSpringer, _c2017.
300			_axi, 660 p. : _bill. ; _c24 cm.
504			_aIncludes bibliographical references and index.
505	0		_aChapter 1: Introduction to Statistical Hydrology -- Chapter 2: Preliminary Analysis of Hydrological Data -- Chapter 3: Elementary Theory of Probability -- Chapter 4: Discrete Random Variables: Distributions and Applications -- Chapter 5: Continuous Random Variables: Distributions and Applications -- Chapter 6: Parameter Estimation -- Chapter 7: Hypothesis Testing -- Chapter 8: At-Site Frequency Analysis of Hydrological Variables -- Chapter 9: Correlation and Regression -- Chapter 10: Regional Frequency Analysis of Hydrological Variables -- Chapter 11: Introduction of Bayesian Analysis and Its Applications in Hydrology -- Chapter 12: Introduction to the Analysis and Modelling of Nonstationary Hydrological Series.
520			_aThis textbook covers the main applications of statistical methods in hydrology. It is written for upper undergraduate and graduate students but can be used as a helpful guide for hydrologists, geographers, meteorologists and engineers. The book is very useful for teaching, as it covers the main topics of the subject and contains many worked out examples and proposed exercises. Starting from simple notions of the essential graphical examination of hydrological data, the book gives a complete account of the role that probability considerations must play during modelling, diagnosis of model fit, prediction and evaluating the uncertainty in model predictions, including the essence of Bayesian application in hydrology and statistical methods under nonstationarity. The book also offers a comprehensive and useful discussion on subjective topics, such as the selection of probability distributions suitable for hydrological variables. On a practical level, it explains MS Excel charting and computing capabilities, demonstrates the use of Winbugs free software to solve Monte Carlo Markov Chain (MCMC) simulations, and gives examples of free R code to solve nonstationary models with nonlinear link functions with climate covariates.
650		0	_aGeosciences. _923809
650		0	_aHydrology. _924272
650		0	_aMeteorology. _95982
650		0	_aStatistics. _93485
650	2	4	_aStatistics for Engineering _xChemistry and Earth Sciences. _923810
700	1		_aNaghettini, Mauro. _eeditor. _923811
942			_cTRB _01
999			_c13879 _d13879