CDLSTM: A Novel Model for Climate Change Forecasting

Water received in rainfall is a crucial natural resource for agriculture, the hydrological cycle, and municipal purposes. The changing pattern an essential aspect of assessing impact climate change on water resources planning management. Climate affected entire world, specifically India’s fragile Himalayan mountain region, which has high significance due to being climatic indicator. coming from rivers 1.4 billion people living downstream. Earlier studies either modeled temperature or area; however, combined influence both long-term analysis was not performed utilizing Deep Learning (DL). present investigation attempted analyze time series correlation (1796–2013) changes (1901–2015) over states India. Long Short-Term Memory (CDLSTM) model developed optimized forecast all states’ values. Facebook’s Prophet (FB-Prophet) implemented assess performance CDLSTM model. models assessed based various metrics shown significantly higher accuracies low error rates.