Markov chain modeling of precipitation time series: Modeling waiting times between tipping bucket rain gauge tips

Hjalte Jomo Danielsen Sørup; Henrik Madsen; Karsten Arnbjerg-Nielsen

Markov chain modeling of precipitation time series: Modeling waiting times between tipping bucket rain gauge tips

Hjalte Jomo Danielsen Sørup
, Henrik Madsen
, Karsten Arnbjerg-Nielsen

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Abstract

A very fine temporal and volumetric resolution precipitation time series is modeled using Markov models. Both 1st and 2nd order Markov models as well as seasonal and diurnal models are investigated and evaluated using likelihood based techniques. The 2nd order Markov model is found to be insignificant. The 1st order Markov model seems to be the most important, followed by the seasonal and diurnal ones. The final model is a continuous state-space 1st order Markov process with seasonal variation. Inclusion of seasonality in the continuous Markov chain model proved difficult, and with respect to likelihood it actually makes the model fit decrease.

Original language	English
Title of host publication	Proceedings of the 12th International Conference on Urban Drainage
Publication date	2011
Publication status	Published - 2011
Event	12th International Conference on Urban Drainage - Porto Alegre, Brazil Duration: 11 Sept 2011 → 16 Sept 2011 Conference number: 12 http://www.acquacon.com.br/icud2011/en/

Conference

Conference	12th International Conference on Urban Drainage
Number	12
Country/Territory	Brazil
City	Porto Alegre
Period	11/09/2011 → 16/09/2011
Internet address	http://www.acquacon.com.br/icud2011/en/

Keywords

Markov chain modeling
Continuous state-space Markov chain modeling
Seasonal precipitation modeling
Precipitation modeling
Tipping bucket rain gauges
Waiting times

Access to Document

http://www.acquacon.com.br/icud2011/en/

OpenUrl availability

Check availability in DTU Findit

Cite this

@inproceedings{f62fbc5d3845424cb5a5d57806808288,

title = "Markov chain modeling of precipitation time series: Modeling waiting times between tipping bucket rain gauge tips",

abstract = "A very fine temporal and volumetric resolution precipitation time series is modeled using Markov models. Both 1st and 2nd order Markov models as well as seasonal and diurnal models are investigated and evaluated using likelihood based techniques. The 2nd order Markov model is found to be insignificant. The 1st order Markov model seems to be the most important, followed by the seasonal and diurnal ones. The final model is a continuous state-space 1st order Markov process with seasonal variation. Inclusion of seasonality in the continuous Markov chain model proved difficult, and with respect to likelihood it actually makes the model fit decrease.",

keywords = "Markov chain modeling, Continuous state-space Markov chain modeling, Seasonal precipitation modeling, Precipitation modeling, Tipping bucket rain gauges, Waiting times",

author = "S{\o}rup, \{Hjalte Jomo Danielsen\} and Henrik Madsen and Karsten Arnbjerg-Nielsen",

year = "2011",

language = "English",

booktitle = "Proceedings of the 12th International Conference on Urban Drainage",

note = "12th International Conference on Urban Drainage, ICUD ; Conference date: 11-09-2011 Through 16-09-2011",

url = "http://www.acquacon.com.br/icud2011/en/",

}

Markov chain modeling of precipitation time series: Modeling waiting times between tipping bucket rain gauge tips. / Sørup, Hjalte Jomo Danielsen; Madsen, Henrik; Arnbjerg-Nielsen, Karsten.
Proceedings of the 12th International Conference on Urban Drainage. 2011.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

TY - GEN

T1 - Markov chain modeling of precipitation time series: Modeling waiting times between tipping bucket rain gauge tips

AU - Sørup, Hjalte Jomo Danielsen

AU - Madsen, Henrik

AU - Arnbjerg-Nielsen, Karsten

N1 - Conference code: 12

PY - 2011

Y1 - 2011

N2 - A very fine temporal and volumetric resolution precipitation time series is modeled using Markov models. Both 1st and 2nd order Markov models as well as seasonal and diurnal models are investigated and evaluated using likelihood based techniques. The 2nd order Markov model is found to be insignificant. The 1st order Markov model seems to be the most important, followed by the seasonal and diurnal ones. The final model is a continuous state-space 1st order Markov process with seasonal variation. Inclusion of seasonality in the continuous Markov chain model proved difficult, and with respect to likelihood it actually makes the model fit decrease.

AB - A very fine temporal and volumetric resolution precipitation time series is modeled using Markov models. Both 1st and 2nd order Markov models as well as seasonal and diurnal models are investigated and evaluated using likelihood based techniques. The 2nd order Markov model is found to be insignificant. The 1st order Markov model seems to be the most important, followed by the seasonal and diurnal ones. The final model is a continuous state-space 1st order Markov process with seasonal variation. Inclusion of seasonality in the continuous Markov chain model proved difficult, and with respect to likelihood it actually makes the model fit decrease.

KW - Markov chain modeling

KW - Continuous state-space Markov chain modeling

KW - Seasonal precipitation modeling

KW - Precipitation modeling

KW - Tipping bucket rain gauges

KW - Waiting times

M3 - Article in proceedings

BT - Proceedings of the 12th International Conference on Urban Drainage

T2 - 12th International Conference on Urban Drainage

Y2 - 11 September 2011 through 16 September 2011

ER -

Markov chain modeling of precipitation time series: Modeling waiting times between tipping bucket rain gauge tips

Abstract

Conference

Keywords

Access to Document

OpenUrl availability

Fingerprint

Cite this