Sensorfusion: Generate virtual sensor based on analysis of sensorsdata
The first major point here is that you do not have historical water level values. These are the labels that you'd use to teach/train any supervised model. Without labels, you are limited to using unsupervised methods. Have a look at the Wikipedia overview

You could try looking into something like clustering, with k-Means for example, which would be quite fast. Other clustering algorithms like DBSCAN are also very good, but your variables (temperature and pressure) might not necessarily cluster well on their density in the input space (the D in DBSCAN).

There are unsupervised neural network approaches, but these are a bit more involved. Autoencoders might be a good place to start. 

Have a look here for some more ideas on specific models to try out, such as Denoising AutoEncoders, which can use recurrent components (such as LSTMs), which can perform well on time series data.