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Incorporating uncertainty into climate variability

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• In the Simulation toolbar, change the analysis option to Stochastic Analysis; and
• From the main toolbar, click Prepare to Run. The Stochastic Analysis window opens (Figure 91).
• Define the Start and End years;
• Specify the number of replicates to run. The default is 20;
• Click OK; and
• In the Simulation toolbar, click Run. The Stochastic Analysis tool will automatically load the rainfall data that is being used by the scenario, and then stochastically generate rainfall replicates for each sub-catchment.

Figure 1. Stochastic analysis set up

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The Stochastic Analysis tool may take some time to complete, depending on the number of sub-catchments, replicates, number of recorded variables and type of rainfall data used in the scenario. Generally, the more complex the model or scenario, the longer the stochastic generation of rainfall data will be.

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A list of all available statistics is displayed in the top, middle window under Statistics. To view a particular statistic, select it under Statistics to view the data as a box and whisker plot, which shows the spread of data. Figure 10 2 shows the monthly mean plot for one of the nodes in the model.

Figure 11 3 shows how a box and whisker plot represents the distribution of data.

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3. Box and whisker plot

A new screen appears with the stochastically generated flow and constituents replicates and statistical outputs (Figure 124).

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4. Stochastically generated flow replicates

Limitations and cautionary notes

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A basic understanding of stochastic climate data is required to properly use stochastic data with hydrological and ecological models to quantify uncertainty in environmental systems associated with climate variability. The user should consider the following questions when designing a stochastic and hydrological modelling study:   Is there a need for stochastic simulations? Is the hydrological model used for the particular application appropriate/reliable? Are the historical data reliable (note that stochastic data do not improve poor records, but improve the design made with whatever reliable historical records that are available)? Is the stochastic and hydrological modelling methodology appropriate? Do the statistics in the stochastically-generated climate data match those of the historical data?

The Stochastic Analysis tool can take a long time to run, particularly when applied to large catchments and when you have specified many replicates (ie over 100). Such applications can take several hours to run. Therefore, when first designing a scenario with stochastically-generated rainfall data, keep the following in mind:

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