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A Nearest Neighbor Bootstrap For Resampling Hydrologic Time Series
A nonparametric method for resampling scalar or vector-valued time series is introduced. Multivariate nearest neighbor probability density estimation provides the basis for the resampling schemeExpand
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A k‐nearest‐neighbor simulator for daily precipitation and other weather variables
A multivariate, nonparametric time series simulation method is provided to generate random sequences of daily weather variables that "honor" the statistical properties of the historical data of theExpand
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A rainwater harvesting system reliability model based on nonparametric stochastic rainfall generator.
Summary The reliability with which harvested rainwater can be used as a means of flushing toilets, irrigating gardens, and topping off air-conditioner serving multifamily residential buildings in NewExpand
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Streamflow simulation: A nonparametric approach
In this paper kernel estimates of the joint and conditional probability density functions are used to generate synthetic streamflow sequences. Streamflow is assumed to be a Markov process with timeExpand
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Multi-variate flood damage assessment: a tree-based data-mining approach
We apply a group of data-mining techniques, known as tree-structured models, to flood damage assessment to identify the important damage-influencing variables and to derive multi-variate flood damage models. Expand
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Water and economic development : The role of variability and a framework for resilience
The article advances the hypothesis that the seasonal and inter-annual variability of rainfall is a significant and measurable factor in the economic development of nations. An analysis of globalExpand
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Seasonal to interannual ensemble streamflow forecasts for Ceara
[1] A semiparametric approach for forecasting streamflow at multiple gaging locations on a river network conditional on climate precursors is developed. The strategy considers statistical forecastsExpand
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A stochastic nonparametric technique for space‐time disaggregation of streamflows
We present a K-nearest-neighbor approach to resample monthly flows conditioned on an annual value in a temporal disaggregation or multiple upstream locations conditioned on a downstream location for a spatial disaggregation. Expand
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Using Bayesian networks to model watershed management decisions: an East Canyon Creek case study
An approach to developing and using Bayesian networks to model watershed management decisions is presented with a case study application to phosphorus management in Northern Utah, USA. Expand
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Floods in a changing climate: Does the past represent the future?
Hydrologists have traditionally assumed that the annual maximum flood process at a location is independent and identically distributed. While nonstationarities in the flood process due to land useExpand
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