Bayesian methods in hydrology: a review.

Ríos Insua, David, Montes Díez, Raquel, and Palomo Martínez, Jesús. "Bayesian methods in hydrology: a review.." RACSAM 96.3 (2002): 461-479. <http://eudml.org/doc/40946>.

@article{RíosInsua2002,
abstract = {Hydrology and water resources management are inherently affected by uncertainty in many of their involved processes, including inflows, rainfall, water demand, evaporation, etc. Statistics plays, therefore, an essential role in their study. We review here some recent advances within Bayesian statistics and decision analysis which will have a profound impact in these fields.},
author = {Ríos Insua, David, Montes Díez, Raquel, Palomo Martínez, Jesús},
journal = {RACSAM},
keywords = {Análisis bayesiano; Procesos de decisión; Modelos matemáticos; Hidrología; Recursos hídricos; Gestión del agua; spatial regression; water resources; spatial models; simulation; water management; dynamic linear models; forecasting nonlinear series; Markov chains Monte Carlo; extreme values; decision support systems},
language = {eng},
number = {3},
pages = {461-479},
title = {Bayesian methods in hydrology: a review.},
url = {http://eudml.org/doc/40946},
volume = {96},
year = {2002},
}

TY - JOUR
AU - Ríos Insua, David
AU - Montes Díez, Raquel
AU - Palomo Martínez, Jesús
TI - Bayesian methods in hydrology: a review.
JO - RACSAM
PY - 2002
VL - 96
IS - 3
SP - 461
EP - 479
AB - Hydrology and water resources management are inherently affected by uncertainty in many of their involved processes, including inflows, rainfall, water demand, evaporation, etc. Statistics plays, therefore, an essential role in their study. We review here some recent advances within Bayesian statistics and decision analysis which will have a profound impact in these fields.
LA - eng
KW - Análisis bayesiano; Procesos de decisión; Modelos matemáticos; Hidrología; Recursos hídricos; Gestión del agua; spatial regression; water resources; spatial models; simulation; water management; dynamic linear models; forecasting nonlinear series; Markov chains Monte Carlo; extreme values; decision support systems
UR - http://eudml.org/doc/40946
ER -