Risk of Spill Information for the Goulburn system

Friday 1 July, 2016

The risk of spill in the Goulburn system at  1 July 2016: 7.3%.

This value represents the percentage of years that spills occur from Lake Eildon taking into account the current storage volume, storage releases, inflows and evaporation from the storage using the historic data available.

Note: 10% or lower is the threshold for a declaration that would return water quarantined in spillable water accounts to allocation bank accounts.

Volume needed to fill Lake Eildon at 1 July 2016: 2,142,989 ML

Click here to find the current volumes in Goulburn system spillable water accounts.

 

Inflow for the April – June 2016 period is indicated by the red line: 177,960 ML

 

The volume difference at Lake Eildon between full supply and the storage volume on 1 July is indicated by the green line: 2,142,989 ML

Notes for charts:

There are 124 years of historic inflow data available for Lake Eildon (inflow data for the period before the construction of the dam are based on modeled inflows). The first chart displays the volume of inflow to Lake Eildon for the period 1 April to 30 June in each of those 124 years. The volumes of inflow shown are ranked in order from lowest to highest with the red line representing the volume of inflow recorded for the period in the current year (2016).

The second chart displays the volume of inflow to Lake Eildon for the period 1 July to 31 December in each of the 124 years of historic data. The volumes of inflow shown are ranked in order from lowest to highest. The volume difference at Lake Eildon between full supply and the storage volume on 1 July is indicated by the green line.

Probability of exceedance: Probability that the volume of inflow will be equal to or greater than a specified volume in any given year. For example, in the first chart above, the probability that inflows to Lake Eildon from 1 April to 30 June will be greater than 200,000 ML in any given year is 35%. 

Additional notes:

• Current year inflows are based on operational data.