I find the existing answers unsatisfying, as the OP asked specifically about Anaconda but the answers are just pip installs.

You can list the available versions for install doing

conda search tensorflow-gpu

which should give you some output that looks like

Loading channels: done
# Name                       Version           Build  Channel             
tensorflow-gpu                 1.4.1               0  pkgs/main           
tensorflow-gpu                 1.5.0               0  pkgs/main           
tensorflow-gpu                 1.6.0               0  pkgs/main           
tensorflow-gpu                 1.7.0               0  pkgs/main           
tensorflow-gpu                 1.8.0      h7b35bdc_0  pkgs/main           
tensorflow-gpu                 1.9.0      hf154084_0  pkgs/main           
tensorflow-gpu                1.10.0      hf154084_0  pkgs/main           
tensorflow-gpu                1.11.0      h0d30ee6_0  pkgs/main           
tensorflow-gpu                1.12.0      h0d30ee6_0  pkgs/main           
tensorflow-gpu                1.13.1      h0d30ee6_0  pkgs/main           
tensorflow-gpu                1.14.0      h0d30ee6_0  pkgs/main           
tensorflow-gpu                1.15.0      h0d30ee6_0  pkgs/main           
tensorflow-gpu                 2.0.0      h0d30ee6_0  pkgs/main           
tensorflow-gpu                 2.1.0      h0d30ee6_0  pkgs/main           
tensorflow-gpu                 2.2.0      h0d30ee6_0  pkgs/main

If you need to specify a particular channel, the -c/--channel option is your friend, for example:

conda search -c conda-forge tensorflow-gpu

Then you can select your version by passing it to the install command, for example:

conda install tensorflow-gpu==2.0.0

If you needed the channel option in your search, you should add the same option to the conda install command. Note this will work the same for tensorflow (i.e. not the GPU version), just change the package name accordingly.

YAML Configuration

If you use YAML environment configuration files, you can do the same thing:

# environment.yaml
name: my_conda_env
channels:
  - conda-forge
dependencies:
  - tensorflow-gpu=2.0.0

Create your environment with command:

conda env create -f environment.yaml

or if you change the version of an already created environment:

conda env update -f environment.yaml

To install specific version of python, tensorflow while creating conda environment: conda create -n python=3.6 tensorflow=1.12.0

I have a older project which has dependency to run on:

Python: 3.7 
Tensorflow: 1.13.1

For this I create a virutal environment using anancoda like:

conda create -n tf python=3.7 tensorflow=1.13.1 
// here more modules with specific version can be added 

After that we to activate env:

conda activate tf

after this ouput was:

(tf) D:\ff\testM>

Environment changed from (base) --> (tf)

(base) D:\ff\testM>

I have a older project which has dependency to run on:

Python: 3.7 
Tensorflow: 1.13.1

To create i used ananconda:

conda create -n tf python=3.7 tensorflow=1.13.1 
// here more modules with specific version can be added 

conda activate tf //Activate environment

(base) D:\ff\testM>  --> (tf) D:\ff\testM> 
// environment changes from base to tf