Vietnam is a country that has a long coastline, stretching from its North to its South. This has many advantage for aquaculture and fisheries, however, the Global climate change and water pollution have caused problems to the farmers in fish/shrimp raising. Tackling the problem of monitoring and managing quality of the water to help the farmers is very necessary. By monitoring the real-time indicators of salinity, temperature, pH, and dissolved oxygen which are produced by sensor networks, and forecasting them to get early warning, we can help the farmers in shrimp/fish raising. In this work, we propose model for forecasting the water quality indicators by using deep learning (Long-Short Term Memory) with Multivariate Time Series. Experimental results on several data sets show that the proposed approach works well and can be applied to real systems.