Wet/dry spell characteristics of daily precipitation are of interest for a number of hydrologic applications (e.g., flood forecasting or assessment of erosion potential). Here, we examine issues related to designing an appropriate nonparametric scheme that focuses on spell characteristics for resampling historically daily precipitation data. A subset of the nonparametric wet/dry spell model presented in Lall et al (1993) is tested with synthetic data to justify the strategy proposed for applications. An application of the nonparametric wet/dry spell model to a Utah data set follows. Performance is judged on a set of ...
This paper examines the success of various Markov-chain models of daily precipitation series in repr...
Graduation date: 1986Mathematical models of the precipitation process are needed to\ud effectively u...
A stochastic model is developed for the synthesis of daily precipitation using conditioning by wea...
Wet/dry spell characteristics of daily precipitation are of interest for a number of...
A nonparametric wet/dry spell model is developed for resampling daily precipitation at a site. The m...
A nonparametric wet/dry spell model is developed for describing daily precipitation at a site. The m...
Traditional stochastic approaches for synthetic generation of weather variables often assume a prior...
One major acknowledged challenge in daily precipitation is the inability to model extreme events in ...
A nonparametric resampling technique for generating daily weather variables at a site is presented. ...
In this paper an attempt has been made to develop a discrete precipitation model for the daily serie...
The design of many water resources projects requires knowledge of possible long-term rainfall patter...
Modeling rainfall occurrence is beneficial, particularly for data generation and management of water...
Precipitation is the driving force affecting the temporal and spatial variability of many hydrosyste...
Daily rainfall is a complex signal exhibiting alternation of dry and wet states, seasonal fluctuatio...
Abstract. Generated weather that represents alternative realizations of a particular historical reco...
This paper examines the success of various Markov-chain models of daily precipitation series in repr...
Graduation date: 1986Mathematical models of the precipitation process are needed to\ud effectively u...
A stochastic model is developed for the synthesis of daily precipitation using conditioning by wea...
Wet/dry spell characteristics of daily precipitation are of interest for a number of...
A nonparametric wet/dry spell model is developed for resampling daily precipitation at a site. The m...
A nonparametric wet/dry spell model is developed for describing daily precipitation at a site. The m...
Traditional stochastic approaches for synthetic generation of weather variables often assume a prior...
One major acknowledged challenge in daily precipitation is the inability to model extreme events in ...
A nonparametric resampling technique for generating daily weather variables at a site is presented. ...
In this paper an attempt has been made to develop a discrete precipitation model for the daily serie...
The design of many water resources projects requires knowledge of possible long-term rainfall patter...
Modeling rainfall occurrence is beneficial, particularly for data generation and management of water...
Precipitation is the driving force affecting the temporal and spatial variability of many hydrosyste...
Daily rainfall is a complex signal exhibiting alternation of dry and wet states, seasonal fluctuatio...
Abstract. Generated weather that represents alternative realizations of a particular historical reco...
This paper examines the success of various Markov-chain models of daily precipitation series in repr...
Graduation date: 1986Mathematical models of the precipitation process are needed to\ud effectively u...
A stochastic model is developed for the synthesis of daily precipitation using conditioning by wea...