Floods are one of the greatest natural disasters, especially in arid land ecosystems. These phenomena damage fragile ecosystems and human societies. If construction of various structures and the development of towns and villages are based on flood forecasting and information, the risk of damage from flooding can be reduced to a large extent. We analyzed the frequency of flooding in the Loot Basin, central Iran, using annual peak discharge series and the method of maximum L‐moment. We found that the distribution based on the H test was homogeneous and the ZDIST statistic selected a regional Log Pearson Type III (LPIII) distribution. The results also showed a high correlation coefficient between the return period and flood discharge, and it was possible to estimate the relationship between flood discharge and area parameters. These methods can be used for areas which lack observational data or statistics.
Recommendations for Resource Managers
Floods are one of the most destructive of natural phenomena, especially in arid and semiarid regions. It is important to be aware of the flood peaks in areas without statistics.
In arid and semiarid regions, there is always a lack of information. Frequency analysis methods are useful in these areas.
The method of L‐moments is one of the most widely used methods for analyzing the frequency of floods. This method predicts the future behavior of data using statistical distributions.
In areas without observational data or statistics, such as the Loot River Basin, Iran, the method of L‐moments can be used to predict floods by using the physical characteristics of the watersheds.
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