Research on drought prediction model of LSTM with elevation of water

Abstract

The Drought is one of the most widespread and damaging natural phenomena in the world and have been increasing around the world in recent years. A drought is a persistent shortage of water caused by an imbalance in water supply and demand. The water shortage can be manifested as insufficient precipitation, lack of soil moisture or low elevation of water of rivers and lakes. So, in this paper, according to the recent drought period and the elevation of water data of Lake Mead, the drought prediction model of the elevation of water used long short-term memory (LSTM) neural network was established to predict the elevation of water of Lake Mead in 2025, 2030, and 2050 and drought prediction respectively. The results show that the drought prediction model of the elevation of water used LSTM has the high accuracy in the data set.

Keywords

• elevation of water
• lake mead
• lstm
• drought prediction