The Log-Pearson Type III Outlier Detection Method is a key tool in hydrology used to identify unusually high or low flood events that deviate significantly from the normal flow record. Based on Bulletin 17B guidelines, this statistical method evaluates annual peak discharge data using logarithmic transformations and parameters such as the mean, standard deviation, and skew coefficient of the data series.
By detecting and appropriately treating outliers, analysts can ensure that flood frequency analyses remain accurate and not distorted by extreme or erroneous values. The procedure computes critical thresholds for high and low outliers, allowing hydrologists to differentiate between true extreme events and statistical anomalies in a river basin dataset.
If you’re interested in understanding how this method works in practical flood analysis, watch the detailed explainer video here: Introduction to Log Pearson Type III Outlier Detection Method.
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