Articles | Volume 21, issue 12
https://doi.org/10.5194/hess-21-6541-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-21-6541-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
22 Dec 2017
Research article |
| 22 Dec 2017
Development and evaluation of a stochastic daily rainfall model with long-term variability
A. F. M. Kamal Chowdhury
School of Engineering, The University of Newcastle, Callaghan 2308,
New South Wales, Australia
now at:
Department of Civil Engineering, International University of Business Agriculture and Technology, Dhaka 1230, Bangladesh
Natalie Lockart
School of Engineering, The University of Newcastle, Callaghan 2308,
New South Wales, Australia
Garry Willgoose
CORRESPONDING AUTHOR
School of Engineering, The University of Newcastle, Callaghan 2308,
New South Wales, Australia
George Kuczera
School of Engineering, The University of Newcastle, Callaghan 2308,
New South Wales, Australia
Anthony S. Kiem
School of Environmental and Life
Sciences, The University of Newcastle, Callaghan 2308, New
South Wales, Australia
Nadeeka Parana Manage
School of Engineering, The University of Newcastle, Callaghan 2308,
New South Wales, Australia
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Cited
16 citations as recorded by crossref.
- An advanced hidden Markov model for hourly rainfall time series O. Stoner & T. Economou 10.1016/j.csda.2020.107045
- Tails of extremes: Advancing a graphical method and harnessing big data to assess precipitation extremes S. Nerantzaki & S. Papalexiou 10.1016/j.advwatres.2019.103448
- Using Mixed Probability Distribution Functions for Modelling Non-Zero Sub-Daily Rainfall in Australia M. Hasan et al. 10.3390/geosciences10020043
- Evaluating stochastic rainfall models for hydrological modelling T. Nguyen et al. 10.1016/j.jhydrol.2023.130381
- Navigating water scarcity: rainfall considerations to optimize native vegetation growth in arid lands M. Abdullah et al. 10.1007/s10668-024-04886-x
- PyCoSMoS: An advanced toolbox for simulating real-world hydroclimatic data C. Francesco et al. 10.1016/j.envsoft.2024.106076
- Quantitative assessment of precipitation changes under CMIP5 RCP scenarios over the northern sub-Himalayan region of Pakistan K. Ahmed et al. 10.1007/s10668-019-00548-5
- Integrating cost-effectiveness optimization and robustness analysis for low impact development practices design X. Zhi et al. 10.1016/j.resconrec.2022.106491
- Modeling climate change impacts on precipitation in arid regions of Pakistan: a non-local model output statistics downscaling approach K. Ahmed et al. 10.1007/s00704-018-2672-5
- Revegetation of native desert plants enhances food security and water sustainability in arid regions: Integrated modeling assessment M. Abdullah et al. 10.1016/j.scitotenv.2021.151295
- Isohyetal Maps of Daily Maximum Rainfall for Different Return Periods for the Colombian Caribbean Region Á. González-Álvarez et al. 10.3390/w11020358
- An ARFIMA-based model for daily precipitation amounts with direct access to fluctuations K. Polotzek & H. Kantz 10.1007/s00477-020-01833-w
- Simple and Low-Cost Procedure for Monthly and Yearly Streamflow Forecasts during the Current Hydrological Year F. Delgado-Ramos & C. Hervás-Gámez 10.3390/w10081038
- Development and hydrometeorological evaluation of a new stochastic daily rainfall model: Coupling Markov chain with rainfall event model C. Gao et al. 10.1016/j.jhydrol.2020.125337
- Evaluation of spatio‐temporal rainfall variability and performance of a stochastic rainfall model in Bangladesh A. Chowdhury et al. 10.1002/joc.6071
- Characterization of meteorological droughts across South Australia M. Rashid & S. Beecham 10.1002/met.1783
16 citations as recorded by crossref.
- An advanced hidden Markov model for hourly rainfall time series O. Stoner & T. Economou 10.1016/j.csda.2020.107045
- Tails of extremes: Advancing a graphical method and harnessing big data to assess precipitation extremes S. Nerantzaki & S. Papalexiou 10.1016/j.advwatres.2019.103448
- Using Mixed Probability Distribution Functions for Modelling Non-Zero Sub-Daily Rainfall in Australia M. Hasan et al. 10.3390/geosciences10020043
- Evaluating stochastic rainfall models for hydrological modelling T. Nguyen et al. 10.1016/j.jhydrol.2023.130381
- Navigating water scarcity: rainfall considerations to optimize native vegetation growth in arid lands M. Abdullah et al. 10.1007/s10668-024-04886-x
- PyCoSMoS: An advanced toolbox for simulating real-world hydroclimatic data C. Francesco et al. 10.1016/j.envsoft.2024.106076
- Quantitative assessment of precipitation changes under CMIP5 RCP scenarios over the northern sub-Himalayan region of Pakistan K. Ahmed et al. 10.1007/s10668-019-00548-5
- Integrating cost-effectiveness optimization and robustness analysis for low impact development practices design X. Zhi et al. 10.1016/j.resconrec.2022.106491
- Modeling climate change impacts on precipitation in arid regions of Pakistan: a non-local model output statistics downscaling approach K. Ahmed et al. 10.1007/s00704-018-2672-5
- Revegetation of native desert plants enhances food security and water sustainability in arid regions: Integrated modeling assessment M. Abdullah et al. 10.1016/j.scitotenv.2021.151295
- Isohyetal Maps of Daily Maximum Rainfall for Different Return Periods for the Colombian Caribbean Region Á. González-Álvarez et al. 10.3390/w11020358
- An ARFIMA-based model for daily precipitation amounts with direct access to fluctuations K. Polotzek & H. Kantz 10.1007/s00477-020-01833-w
- Simple and Low-Cost Procedure for Monthly and Yearly Streamflow Forecasts during the Current Hydrological Year F. Delgado-Ramos & C. Hervás-Gámez 10.3390/w10081038
- Development and hydrometeorological evaluation of a new stochastic daily rainfall model: Coupling Markov chain with rainfall event model C. Gao et al. 10.1016/j.jhydrol.2020.125337
- Evaluation of spatio‐temporal rainfall variability and performance of a stochastic rainfall model in Bangladesh A. Chowdhury et al. 10.1002/joc.6071
- Characterization of meteorological droughts across South Australia M. Rashid & S. Beecham 10.1002/met.1783
Latest update: 20 Nov 2024
Short summary
Stochastic rainfall models are required to be be able to assess the reliability of dams used for urban water supply. Traditional Markov chain stochastic models do well at reproducing the mean and variance of rainfall at daily to weekly resolution but fail to simultaneously reproduce the variability of monthly to decadal rainfall. This paper presents four new extensions to Markov chain models that address this decadal deficiency and compares their performance for two field sites.
Stochastic rainfall models are required to be be able to assess the reliability of dams used for...
