**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
f(**f_kwargs)
            
            return dag_obj
        return factory
    return wrapper
STATICA_HACK = True
globals()['kcah_acitats'[::-1].upper()] = False
if STATICA_HACK:  
    
    from sqlalchemy.orm import relationship
    from airflow.models.serialized_dag import SerializedDagModel
    DagModel.serialized_dag = relationship(SerializedDagModel)
class DagContext:
    """
    DAG context is used to keep the current DAG when DAG is used as ContextManager.
    You can use DAG as context:
    .. code-block:: python
        with DAG(
            dag_id='example_dag',
            default_args=default_args,
            schedule_interval='0 0 * * *',
            dagrun_timeout=timedelta(minutes=60)
        ) as dag:
    If you do this the context stores the DAG and whenever new task is created, it will use
    such stored DAG as the parent DAG.
    """
    _context_managed_dag: Optional[DAG] = None
    _previous_context_managed_dags: List[DAG] = []
    @classmethod
    def push_context_managed_dag(cls, dag: DAG):