Click for new scientific resources and news about Corona[COVID-19]

Paper Information

Journal:   JOURNAL OF WATERSHED MANAGEMENT RESEARCH   FALL 2015-WINTER 2016 , Volume 6 , Number 12; Page(s) 139 To 153.
 
Paper: 

SPATIAL-TEMPORAL MODELING OF OCCURRENCE AND AMOUNT OF WINTER RAINFALL USING HIDDEN MARKOV MODEL

 
 
Author(s):  GHAMGHAMI MEHDI, GHAHREMAN NOZAR*, BAZRAFSHAN JAVAD
 
* UNIVERSITY OF TEHRAN
 
Abstract: 

Multi-site modeling of rainfall is one of the most important issues in environmental sciences especially in watershed management. For this purpose, different statistical models have been developed which involve spatial approaches in simulation and modeling of daily rainfall values. The hidden Markov is one of the multi-site daily rainfall models which in addition to simulation of daily rainfall values, explores the spatial and temporal pattern of rainfall events. In this study, the winter (January to April) rainfall pattern of 130 rain gauges have been modeled using hidden Markov approach during a 21 years period (1990-2010). The aim of this study was finding temporal and spatial distribution of weather patterns and stochastic simulation of occurrence and amount of rainfall, simultaneously. To achieve this goal, different hidden Markov algorithms including, Viterbi decoding algorithm, Expectation-Maximization (EM) algorithm and a stochastic simulation approach with the probability transformation were applied. It is expected that extracted patterns, using hidden Markov model, are consistent with synoptic patterns and accordingly eight different weather pattern as the definite set of possible cases were recognized. The most frequent rainfall pattern extracted from hidden Markov model was the dry pattern (stable condition) in which the rainfall occurrence probability is low in most of the stations. This pattern has the maximum initial probability of 0.429 and maximum Markov transfer probability of 0.637 Besides, multi-site simulation of winter rainfall keeping the basic statistic of mean, standard deviation of total seasonal rainfall and percentile values in each station and also spatial correlation of occurrence or nonoccurrence of rainfall produced reasonable result. In general this approach can be recommended for regional studies.

 
Keyword(s): HIDDEN MARKOV MODEL, WINTER RAINFALL, SPATIAL PATTERNS, SIMULATION
 
 
References: 
  • Not Registered.
  •  
  •  
 
Citations: 
  • Not Registered.
 
+ Click to Cite.
APA: Copy

GHAMGHAMI, M., & GHAHREMAN, N., & BAZRAFSHAN, J. (2016). SPATIAL-TEMPORAL MODELING OF OCCURRENCE AND AMOUNT OF WINTER RAINFALL USING HIDDEN MARKOV MODEL. JOURNAL OF WATERSHED MANAGEMENT RESEARCH, 6(12), 139-153. https://www.sid.ir/en/journal/ViewPaper.aspx?id=508587



Vancouver: Copy

GHAMGHAMI MEHDI, GHAHREMAN NOZAR, BAZRAFSHAN JAVAD. SPATIAL-TEMPORAL MODELING OF OCCURRENCE AND AMOUNT OF WINTER RAINFALL USING HIDDEN MARKOV MODEL. JOURNAL OF WATERSHED MANAGEMENT RESEARCH. 2016 [cited 2021August03];6(12):139-153. Available from: https://www.sid.ir/en/journal/ViewPaper.aspx?id=508587



IEEE: Copy

GHAMGHAMI, M., GHAHREMAN, N., BAZRAFSHAN, J., 2016. SPATIAL-TEMPORAL MODELING OF OCCURRENCE AND AMOUNT OF WINTER RAINFALL USING HIDDEN MARKOV MODEL. JOURNAL OF WATERSHED MANAGEMENT RESEARCH, [online] 6(12), pp.139-153. Available: https://www.sid.ir/en/journal/ViewPaper.aspx?id=508587.



 
 
Persian Abstract Yearly Visit 33
 
 
Latest on Blog
Enter SID Blog