LSTM Target Is Also One of It's Inputs? I have two input arrays that include both historical and forecasted data, and one input array that is only historical. I'm trying to predict (or &quot;forecast&quot;) the latter array given the forecasts of the first two arrays.
Inputs:

Rainfall (historical and forecast)
Air temp (historical and forecast)
Water volume (historical)

Training target:

Water volume (historical)

Desired model output:

Water volume (forecast)

I'm still a bit of a noob, and lost as to how this would work. None of the examples I've found take the target's previous state as input. The crux of the problem is that I could do a vanilla multivariate LSTM with only rainfall and air temp as inputs, but it would not take into account the starting condition of water in the container.
Doing some further searching, I found a nice post by Jason Brownlee that has helped me better understand the problem and one potential solution:

a multi-input model with an LSTM input for the historical data and a
vector input for expected conditions.

Furthermore, Keras' Functional API (https://keras.io/guides/functional_api/) will help me build such a model.