**Apache Airflow version**: 2.0.0


**Kubernetes version (if you are using kubernetes)** (use `kubectl version`): N/A

**Environment**: 

- **Cloud provider or hardware configuration**: local/aws
- **OS** (e.g. from /etc/os-release): Ubuntu 18.04.5 LTS
- **Kernel** (e.g. `uname -a`): 5.4.0-1032-aws
- **Install tools**: pip
- **Others**:

**What happened**:
I did a fresh Airflow 2.0.0 install. With this version, when I manually trigger a DAG, Airflow skips the next scheduled run.
<!-- (please include exact error messages if you can) -->

**What you expected to happen**:
Manual runs do not interfere with the scheduled runs prior to Airflow 2. 
<!-- What do you think went wrong? -->

**How to reproduce it**:
Create a simple hourly DAG. After enabling it and the initial run, run it manually. It shall skip the next hour. Below is an example, where the manual run with execution time of 08:17 causes the scheduled run with execution time of 08:00 to skip. 
![image](https://user-images.githubusercontent.com/26160471/103457719-c7193480-4d12-11eb-82cb-42efaedc9ef4.png)


airflow/models/dag.py
creating_job_id: Optional[int] = None,
    ):
        """
        Creates a dag run from this dag including the tasks associated with this dag.
        Returns the dag run.
        :param run_id: defines the run id for this dag run
        :type run_id: str
        :param run_type: type of DagRun
        :type run_type: airflow.utils.types.DagRunType
        :param execution_date: the execution date of this dag run
        :type execution_date: datetime.datetime
        :param state: the state of the dag run
        :type state: airflow.utils.state.State
        :param start_date: the date this dag run should be evaluated
        :type start_date: datetime
        :param external_trigger: whether this dag run is externally triggered
        :type external_trigger: bool
        :param conf: Dict containing configuration/parameters to pass to the DAG
        :type conf: dict
        :param creating_job_id: id of the job creating this DagRun
        :type creating_job_id: int
        :param session: database session
        :type session: sqlalchemy.orm.session.Session
        :param dag_hash: Hash of Serialized DAG
        :type dag_hash: str
        """
        if run_id and not run_type:
            if not isinstance(run_id, str):
                raise ValueError(f"`run_id` expected to be a str is {type(run_id)}")
            run_type: DagRunType = DagRunType.from_run_id(run_id)