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Several nonparametric methods are gaining popularity in their use alongside traditional parametric approaches for stochastic simulation of hydrologic variables. However, these stochastic simulations, and the simulation statistics using the nonparametric methods are strongly impacted by two factors: (1) sample size of the historical data, and (2) number of simulations. Theory is well established in traditional parametric statistics to quantify the role of sample and simulation sizes on hydrologic simulation uncertainty. But, there has not been much research in the data-driven nonparametric realm. This research will evaluate the power and uncertainty associated with sample size and number of simulations in nonparametric...
Categories: Project;
Types: ScienceBase Project;
Tags: Science,
climate change,
non-parametric approaches,
statistical analysis,
streamflow forecasts
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