For several hydrological modelling tasks precipitation time series with a high (sub-daily) resolution are indispensable. This data is, however, not always available and thus replaced by model data. A canonical class of stochastic models for sub-daily precipitation is the class of Poisson cluster processes, e.g. the Bartlett-Lewis rectangular pulse model (BLRPM). The BLRPM has been shown to be able to well reproduce certain characteristics found in observations. Our focus is on intensity-duration relationship which are of particular importance in the context of hydrological modelling. We analyse several high resolution precipitation time series (5min) from Berlin and derive empirical intensity-duration relations for several return l...
Rainfall intensity-duration-frequency (IDF) relationships describe rainfall intensity as a function ...
Supported by the National Aeronautics and Space Administration. NAS 5-31721The parameters of two sto...
Point process theory has been widely used to model the stochastic structure of rainfall occurrences,...
For several hydrological modelling tasks, precipitation time-series with a high (i.e. sub- daily) re...
For several hydrological modelling tasks, precipitation time-series with a high (i.e. sub-daily) res...
In a recent development in the literature, a new temporal rainfall model, based on the Bartlett-Lewi...
In a recent development in the literature, a new temporal rainfall model, based on the Bartlett-Lewi...
To simulate the impacts of within-storm rainfall variabilities on fast hydrological processes, long ...
Description These data were used in the study "Flexible and Consistent Quantile Estimation for Inte...
Assessment of climate change on any hydrological system requires higher temporal resolution at hourl...
The Bartlett-Lewis Rectangular Pulse Modified (BLPRM) model simulates the precipitous slide in the h...
Assessing the relationship between the intensity, duration, and frequency (IDF) of extreme precipita...
A cluster point process model is considered for the analysis of fine-scale rainfall time series. The...
Many hydrological applications, such as flood studies, require the use of long rainfall data at fine...
Stochastic rainfall models are widely used in hydrological studies because they provide a framework ...
Rainfall intensity-duration-frequency (IDF) relationships describe rainfall intensity as a function ...
Supported by the National Aeronautics and Space Administration. NAS 5-31721The parameters of two sto...
Point process theory has been widely used to model the stochastic structure of rainfall occurrences,...
For several hydrological modelling tasks, precipitation time-series with a high (i.e. sub- daily) re...
For several hydrological modelling tasks, precipitation time-series with a high (i.e. sub-daily) res...
In a recent development in the literature, a new temporal rainfall model, based on the Bartlett-Lewi...
In a recent development in the literature, a new temporal rainfall model, based on the Bartlett-Lewi...
To simulate the impacts of within-storm rainfall variabilities on fast hydrological processes, long ...
Description These data were used in the study "Flexible and Consistent Quantile Estimation for Inte...
Assessment of climate change on any hydrological system requires higher temporal resolution at hourl...
The Bartlett-Lewis Rectangular Pulse Modified (BLPRM) model simulates the precipitous slide in the h...
Assessing the relationship between the intensity, duration, and frequency (IDF) of extreme precipita...
A cluster point process model is considered for the analysis of fine-scale rainfall time series. The...
Many hydrological applications, such as flood studies, require the use of long rainfall data at fine...
Stochastic rainfall models are widely used in hydrological studies because they provide a framework ...
Rainfall intensity-duration-frequency (IDF) relationships describe rainfall intensity as a function ...
Supported by the National Aeronautics and Space Administration. NAS 5-31721The parameters of two sto...
Point process theory has been widely used to model the stochastic structure of rainfall occurrences,...