Research on Water Level Changes in Lake Mead

Abstract

Lake Mead, the largest reservoir in the U.S., assumes a pivotal role in the water supply. However, in recent years, the reservoir's water volume has gradually decreased, and many states have cut back on water supply. Therefore, it is crucial to explore the pattern of water level changes in Lake Mead and thereby find ways to alleviate water shortage. We first discussed the pattern of development of historical water levels in Lake Mead. We classified the annual minimum and maximum water level data of Lake Mead using hierarchical clustering, and determined the group of clusters using the Elbow Method to perform the analysis, obtaining the best result. We then classified the historical water levels into early drought periods, non-drought periods, and recent drought periods based on the clustering results. Two models were also built to predict future Lake Mead water level changes. To facilitate the overall analysis, we drew scatterplots of the maximum and minimum water levels concerning time and found that the data of the first model is more consistent and regular, so we predicted the data using Linear Fitting-based time series analysis. However, the data needed since 2005 in model 2 showed a very obvious segmentation in roughly 2011, as seen from the scatterplot. We built a breakpoint regression model to make the prediction.