Book contents
- Frontmatter
- Contents
- List of Authors
- Preface
- I INTRODUCTION
- II FACETS OF UNCERTAINTY
- III NOVEL APPROACHES TO UNCERTAINTY: FRACTALS, FUZZY SETS AND PATTERN RECOGNITION, NON-PARAMETRIC METHODS
- IV RANDOM FIELDS
- V TIME SERIES AND STOCHASTIC PROCESSES
- 1 Prediction uncertainty in seasonal partial duration series
- 2 A daily streamflow model based on a jump-diffusion process
- 3 The influence of time discretization on inferred stochastic properties of point rainfall
- 4 The distribution of the l-day total precipitation amount
- 5 Analysis of outliers in Norwegian flood data
- 6 Stochastic modelling of the operation of hydrants in an irrigation network
- 7 Order and disorder in hydroclimatological processes
- 8 Towards the physical structure of river flow stochastic process
- VI RISK, RELIABILITY AND RELATED CRITERIA
3 - The influence of time discretization on inferred stochastic properties of point rainfall
Published online by Cambridge University Press: 07 May 2010
- Frontmatter
- Contents
- List of Authors
- Preface
- I INTRODUCTION
- II FACETS OF UNCERTAINTY
- III NOVEL APPROACHES TO UNCERTAINTY: FRACTALS, FUZZY SETS AND PATTERN RECOGNITION, NON-PARAMETRIC METHODS
- IV RANDOM FIELDS
- V TIME SERIES AND STOCHASTIC PROCESSES
- 1 Prediction uncertainty in seasonal partial duration series
- 2 A daily streamflow model based on a jump-diffusion process
- 3 The influence of time discretization on inferred stochastic properties of point rainfall
- 4 The distribution of the l-day total precipitation amount
- 5 Analysis of outliers in Norwegian flood data
- 6 Stochastic modelling of the operation of hydrants in an irrigation network
- 7 Order and disorder in hydroclimatological processes
- 8 Towards the physical structure of river flow stochastic process
- VI RISK, RELIABILITY AND RELATED CRITERIA
Summary
ABSTRACT The influence of time discretization on inferred stochastic properties of the point rainfall process was investigated through analysis of its eight characteristics (number of rain spells in a given time interval, ΔN; duration of dry spell, Td; time interval between the beginnings of successive rainfalls, Tb; total depth of rainfall, H; duration of rainfall, T; average, Ia, and maximum rainfall intensity, Im; relative duration of rainfall, Tr = T/Tb) at time scale Δt ranging from 5 minutes to 24 hours. The analysis, based on 25-year continuous records from a daily pluviograph, showed that the process ΔN can be described by the negative binomial distribution (NBD) for Δt≤60 min and by the Poisson distribution for Δt > 60 min. All remaining processes considered were found independent with the log-normal probability distribution function rendering the best fit at each Δt. Rainfall and dry spell durations behave differently. For Δ t > 180 min they have to be treated as discrete ones with the NBD. About one third of all correlations for the seven processes is strongly affected by Δt causing change of their significance.
INTRODUCTION
The uncertainty accompanying all hydrologic processes is particularly visible in the case of the atmospheric precipitation.
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- New Uncertainty Concepts in Hydrology and Water Resources , pp. 230 - 237Publisher: Cambridge University PressPrint publication year: 1995