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To this end, the stochastic generation of continuous rainfall sequences is often coupled with the continuous hydrological modelling.
Continuous rainfall sequences are often used as inputs in hydrologic modeling, particularly where a probabilistic assessment is required.
Continuous rainfall sequences provide a means for accounting of all aspects of rainfall that produce flooding, for example, not just the design rainfall event but also the rainfall prior to the extreme rainfall event.
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This paper describes an algorithm for disaggregating daily rainfall into sub-daily rainfall 'fragments' (fine-resolution rainfall sequences) under a future, warmer climate.
Poisson cluster stochastic rainfall generators (e.g., modified Bartlett-Lewis rectangular pulse, MBLRP) have been widely applied to generate synthetic sub-daily rainfall sequences.
Incorporation of an inter-event (I) sub-model completed the continuous rainfall simulation scheme.
Given these demonstrated changes to extreme rainfall with temperature rise, there is a need to modify continuous rainfall generators to account for current and likely future changes in temperature.
During heavy rainfall, continuous rainfall infiltration can generate a wet front in the soil slope and in turn form a saturated zone above the potential sliding surface.
During heavy rainfall, continuous rainfall infiltration can generate a wet front in the soil layer, and in turn forms a saturated zone above the potential sliding surface.
A continuous rainfall event is considered to begin when hourly rainfall surpasses 4 mm and ends when hourly rainfall decreases below 4 mm over the next six consecutive hours (e.g., Chang et al. 2011).
Steady southeasterly breezes brought in tropical moisture, which for days caused almost continuous rainfall over Southern California.
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