Rivers play a crucial role as sources of freshwater worldwide. The Yangtze and Yellow rivers, often regarded as the lifelines of China, significantly contribute to the nation's economy through their abundant water resources. Maintaining the quality of water in these river basins is essential for both human health and a thriving ecological system. This study intended to assess the historical water quality of China's two mother river basins including the Yangtze River, and the Yellow River. This assessment analyzes the historical dissolved oxygen, Ammonium nitrogen, and permanganate, and calculates comprehensive water quality identification (CWQII) values to find the trend and predict future values using a Machine learning model. To evaluate the stationarity of historical data, different tests and measures have been taken such as ADF and KSPP to test stationarity. Autocorrelation and partial autocorrelation also have been performed to understand the nature of the data. According to the SARIMA model, the Mean Absolute Percentage Error (MAPE) for the CWQII was 9.1% for the Yangtze and 13.3% for the Yellow River. In contrast, the LSTM model yielded MAPE values of 7% and 14%, respectively. For Dissolved Oxygen (DO) prediction, the SARIMA model showed MAPEs of 8.9% for the Yangtze and 9.87% for the Yellow River, while the LSTM model resulted in 8% and 16%, respectively. The current and future forecasting of CWQII values suggest that, based on model forecasts, the water quality in the Yellow River basin may be poorer compared to the Yangtze River basin This study might help the government, researchers, and other stakeholders to take proper steps to develop water pollution control strategy.