Publication name: Stochastic simulation of daily streamflow sequences using a hidden Markov model
Authors names: Douglas Pender, Sandhya Patidar, Gareth Pender and Heather Haynes

Journal Name: Hydrology Research
Date of Acceptance and Publication: April, 2015; May 2015  

Figure 6(i): Probability density (HMM-GP) of observed discharges and range of synthetic sequences of River Dee 

Outputs: Probability density (HMM-GP) of observed discharge and range of synthetic sequences 


Methodology: Stochastic modelling by Hidden Markov Model (HMM) with generalised pareto distribution (GP), 
here referred as HMM-GP (Coles, 2001; and Eq. 5 in the paper)


Input data/source: Observed daily discharge (Q) from following gauging station:

Gauging station ID: 
River Dee: 12001; Station name: Woodend

Gauge maintained by: 
Scottish Environment Protection Agency (http://www.sepa.org.uk/)

Output description:
Column 1: Logarithm (10-base) of daily discharge in m3/s
Column 2: Probability density (HMM-GP) of daily recorded discharge of River Dee
Column 3 to 102: Probability density (HMM-GP) of synthetic discharges of 100 sequences