Bivariate stochastic modelling of ephemeral streamflow
- 7 February 2002
- journal article
- research article
- Published by Wiley in Hydrological Processes
- Vol. 16 (7) , 1451-1465
- https://doi.org/10.1002/hyp.355
Abstract
Streamflow time series in arid and semi‐arid regions can be characterized as a sequence of single discrete flow episodes or clusters of hydrographs separated by periods of zero discharge. Here, two point process models are presented for the joint occurrence of flow events at neighbouring river sites. The first allows for excess clustering by adding autocorrelated errors to an empirically derived seasonally varying probability of an event and is extended to the case of the joint occurrence of flow events in two catchments. The second approach is to explicitly model the occurrences of clusters of events and the bivariate point process of event occurrences within them at both sites. For the two models, the magnitude of event peaks are assumed to be drawn from continuous distributions with seasonally varying parameters. Rises and recessions in discharge are interpolated between the peaks using regression estimates of hydrographs. The models are fitted to mean daily flows at two sites in Namibia and demonstrated to provide realistic simulations of the hydrology. Copyright © 2002 John Wiley & Sons, Ltd.Keywords
This publication has 16 references indexed in Scilit:
- A Poisson-cluster model of rainfall: some high-order moments and extreme valuesProceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 1998
- MODELLING OF RAINFALL TIME-SERIES USING THE BARTLETT-LEWIS MODEL.Proceedings of the Institution of Civil Engineers - Water, Maritime and Energy, 1995
- A generalized spatial-temporal model of rainfall based on a clustered point processProceedings of the Royal Society of London. Series A: Mathematical and Physical Sciences, 1995
- Non-negative time series models for dry river flowJournal of Applied Probability, 1990
- Application of Discrete Autoregressive Moving Average models for estimation of daily runoffJournal of Hydrology, 1987
- Some models for rainfall based on stochastic point processesProceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences, 1987
- Ground‐Water Dams for Rural‐Water Supplies in Developing CountriesGroundwater, 1986
- A stochastic cluster model of daily rainfall sequencesWater Resources Research, 1981
- Stochastic generation of monthly flows for ephemeral streamsJournal of Hydrology, 1980
- Computer‐oriented Wilson‐Hilferty transformation that preserves the first three moments and the lower bound of the Pearson type 3 distributionWater Resources Research, 1972