Thirdly, there is an underlying assumption that the data are normally distributed, which is an assumption used in calculating the confidence and prediction intervals. There were no indications in the model validation that this is not the case, but greater sample sizes would yield greater confidence in this assumption. Lastly, the 95% prediction interval appears to be quite large (±121 days), but if the data are normally distributed, the predictions will be on average much closer to the centre of that range (i.e what the model predicts). A 95% confidence interval provides the range in which 95% of values are expected to fall, that is, throughout that range the model should only be wrong in 5% of predictions. Climatic component The driver for natural water loss in waterholes is a combination of evaporation and groundwater. Discerning which of the two loss factors are most important across the river valleys requires further investigation. Presumably there is some correlation with climate, which is a driver for evaporation, but further investigation is required. Other factors such as wind fetch from river orientation may play a large role as well. Also, the Moonie samples were taken in 2009, while the Culgoa and Narran river systems were sampled in 2015. The model could be impacted because of this difference; it may be different because of different conditions during sampling. It is feasible that the relationship may be stronger had the samples been collected in the same time period. Taking the model further Given the success with which this model can predict persistence across three river valleys, the ease of its use and the broad management implications, it would be worth investigating how this model might apply in a wider range of catchments within the Basin. As more catchments are incorporated into the model, the predictions become more robust and the management implications become exponentially greater as more regions can potentially benefit from the model. In order to investigate the effect of climate, the next catchment to be surveyed would ideally have a similar river system in a climatically different location. It may be that by incorporating an element of climate into the model, its accuracy can be increased as will its area of application, though the corresponding increases in complexity may be prohibitive.
Thirdly, there is an underlying assumption that the data are normally distributed, which is an assumption used in calculating the confidence and prediction intervals. There were no indications in the model validation that this is not the case, but greater sample sizes would yield greater confidence in this assumption. Lastly, the 95% prediction interval appears to be quite large (±121 days), but if the data are normally distributed, the predictions will be on average much closer to the centre of that range (i.e what the model predicts). A 95% confidence interval provides the range in which 95% of values are expected to fall, that is, throughout that range the model should only be wrong in 5% of predictions. Climatic component The driver for natural water loss in waterholes is a combination of evaporation and groundwater. Discerning which of the two loss factors are most important across the river valleys requires further investigation. Presumably there is some correlation with climate, which is a driver for evaporation, but further investigation is required. Other factors such as wind fetch from river orientation may play a large role as well. Also, the Moonie samples were taken in 2009, while the Culgoa and Narran river systems were sampled in 2015. The model could be impacted because of this difference; it may be different because of different conditions during sampling. It is feasible that the relationship may be stronger had the samples been collected in the same time period. Taking the model further Given the success with which this model can predict persistence across three river valleys, the ease of its use and the broad management implications, it would be worth investigating how this model might apply in a wider range of catchments within the Basin. As more catchments are incorporated into the model, the predictions become more robust and the management implications become exponentially greater as more regions can potentially benefit from the model. In order to investigate the effect of climate, the next catchment to be surveyed would ideally have a similar river system in a climatically different location. It may be that by incorporating an element of climate into the model, its accuracy can be increased as will its area of application, though the corresponding increases in complexity may be prohibitive.
FINAL%20Report_Waterholes%20Project%20northern%20Basin.docx