Autorun persistence of the Great Salt Lake water level fluctuations

Planning, design, construction and operation of lakeshore structures require information about the future likely extremes of the lake levels at a given risk percentage. The estimation of average return periods of hydrological events and the corresponding risks of failure of hydraulic structures that are associated with such events are important aspects in many water resources studies. Small changes in the elevation of the lake surfaces can lead to enormous changes in the amount of land surface lost when the lake level rises or exposed when lake level falls. Persistence is the most important property in any hydrologic design concerning the storage capacity of reservoirs, average return periods, failure risks, drought properties. Its consideration in analytical derivations of design criteria presents difficulties and for this reason most often the analytical expressions are obtained on the basis of non-persistent (independent) hydrological processes. Both return period and risk of failure can be easily calculated assuming the lake levels are independent. But it is well known that persistence is more important for lake level fluctuations. By using autorun function which is probability distribution free and robust parameter, return period and risk is determined. The application of the methodology is presented for the Great Salt Lake monthly water level data in western US.