Western drought began since 2000 caused sharp decrease by about 100 feet in the largest reservoir of North America, Lake Mead due to the precipitation pattern shift in the upstream lower Virgin River Basin. Oceans play an important role on earth’s climate via oceanic-atmospheric interactions known as climate teleconnections, which deeply affect the terrestrial precipitation patterns. This issue signifies the necessity of developing a modern hydroinformatics tool - precipitation forecasting model - to account for teleconnection signals from climate change and mitigate drought hazards impact on lake water, quantitatively and qualitatively, which cannot be achieved by using traditional Global Circulation Model. Therefore, understanding the relationship between precipitation and teleconnection patterns could initial step for precipitation forecasting. However, highly nonlinear and non-stationary nature of teleconnection patterns result in large uncertainties in estimates, since simple linear analyses failed to capture underlying trends at sub-continental scales. For this purpose, the integrated high-resolution remote sensing imagery, spectral analysis techniques, and wavelet analysis were integrated to explore the nonstationary and nonlinear behavior of teleconnection signals between the Pacific and Atlantic sea surface temperature (SST) on a long-term basis (30 years) from which the precipitation pattern shift in the lower Virgin River Basin can be elucidated. These processes lead to the creation of linear-lagged correlation maps which specify index regions within the Atlantic and Pacific Oceans where SST anomaly can be statistically significant in correlation with terrestrial precipitation. These indexed regions delivering some kind of memory effects of SST were extracted to be inputs into an Artificial Neural Network (ANN). Advances in wavelet-based ANN (WEOF-ANN) model for rainfall prediction assists in local water management agencies to mitigate the drought impact and obtain sustainable development strategies 3-6 months ahead of the time in urban drinking water infrastructure assessment plan around Lake Mead area.
Imen, Sanaz; Chang, Ni-Bin; and Yang, Y. Jeffrey, "Precipitation Forecasting With Wavelet-Based Empirical Orthogonal Function And Artificial Neural Network (WEOF-ANN) Model" (2014). CUNY Academic Works.