### Apache Airflow version

2.5.0

### What happened

Open url `dags/gate/graph?dag_run_id=8256-8-1670328803&execution_date=2022-12-06T12%3A13%3A23.174592+00%3A00`
The graph is displaying a completely different dagrun. 
![image](https://user-images.githubusercontent.com/89977373/205916845-8acdf310-6073-46f9-aea3-8e144f6e4fba.png)
If you are not careful to review all the content, you might continue looking at the wrong results, or worse cancel a run with Mark failed.

I got the link from one of our users, so not 100% sure if it was the original url. I believe there could be something wrong with the url-encoding of the last `+` character. In any case, if there are any inconsistencies in the URL parameters vs the found dagruns, it should not display another dagrun, rather redirect to grid-view or error message.


### What you think should happen instead

* dag_run_id should be only required parameter, or have precedence over execution_date
* Provided dag_run_id should always be the same run-id that is displayed in graph
* Inconsistencies in any parameters should display error or redirect to grid view.

### How to reproduce

_No response_

### Operating System

Ubuntu 22.04

### Versions of Apache Airflow Providers

_No response_

### Deployment

Other Docker-based deployment

### Deployment details

_No response_

### Anything else

_No response_

### Are you willing to submit PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

.filter(DagRun.dag_id == dag.dag_id)
            .group_by(_convert_to_date(session, DagRun.execution_date), DagRun.state)
            .order_by(_convert_to_date(session, DagRun.execution_date).asc())
            .all()
        )
        data_dag_states = [
            {
                
                
                "date": dr.date if isinstance(dr.date, str) else dr.date.isoformat(),
                "state": dr.state,
                "count": dr.count,
            }
            for dr in dag_states
        ]
        if dag_states and dag_states[-1].data_interval_start and dag_states[-1].data_interval_end:
            last_automated_data_interval = DataInterval(
                timezone.coerce_datetime(dag_states[-1].data_interval_start),
                timezone.coerce_datetime(dag_states[-1].data_interval_end),
            )
            year = last_automated_data_interval.end.year
            restriction = TimeRestriction(dag.start_date, dag.end_date, False)
            dates = collections.Counter()
            if isinstance(dag.timetable, CronMixin):
                
                dates_iter: Iterator[datetime | None] = croniter(
                    dag.timetable._expression,
                    start_time=last_automated_data_interval.end,
                    ret_type=datetime,
                )