Filters: Tags: indicator species (X) > Types: Citation (X)
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The cascade of uncertainty that underscores climate impact assessments of regional hydrology undermines their value for long-term water resources planning and management. This study presents a statistical framework that quantifies and propagates the uncertainties of hydrologic model response through projections of future streamflow under climate change. Different sources of hydrologic model uncertainty are accounted for using Bayesian modeling. The distribution of model residuals is formally characterized to quantify predictive skill, and Markov chain Monte Carlo sampling is used to infer the posterior distributions of both hydrologic and error model parameters. Parameter and residual error uncertainties are integrated...
Categories: Data,
Publication;
Types: Citation;
Tags: AQUATIC ECOSYSTEMS,
AQUATIC SCIENCES,
CLIMATE CHANGE IMPACT ASSESSMENT MODELS,
CONSERVATION,
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