TY  - JOUR
PB  - Annual Reviews Inc.
Y1  - 2024/03//
A1  - Northrop, Paul J
N2  - Rainfall is the main input to most hydrological systems. To assess flood risk
for a catchment area, hydrologists use models that require long series of subdaily, perhaps even subhourly, rainfall data, ideally from locations that cover
the area. If historical data are not sufficient for this purpose, an alternative
is to simulate synthetic data from a suitably calibrated model. We review
stochastic models that have a mechanistic structure, intended to mimic physical features of the rainfall processes, and are constructed using stationary
point processes.We describe models for temporal and spatial-temporal rainfall and consider how they can be fitted to data. We provide an example
application using a temporal model and an illustration of data simulated from
a spatial-temporal model.We discuss how these models can contribute to the
simulation of future rainfall that reflects our changing climate.
VL  - 11
ID  - discovery10174912
N1  - This version is the author accepted manuscript. For information on re-use, please refer to the publisher?s terms and conditions.
SN  - 2326-8298
JF  - Annual Review of Statistics and Its Application
EP  - 27
AV  - public
UR  - https://doi.org/10.1146/annurev-statistics-040622-023838
SP  - 1
KW  - Climate change
KW  -  flood risk assessment
KW  -  point process
KW  -  Poisson cluster process
KW  -  stochastic-mechanistic model
KW  -  stochastic rainfall generation
TI  - Stochastic models of rainfall
ER  -