### 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(None, [record["start_date"], ti_summary.start_date]), default=None
                    )
                    record["end_date"] = max(
                        filter(None, [record["end_date"], ti_summary.end_date]), default=None
                    )
                    record["mapped_states"][ti_summary.state] = ti_summary.state_count
                if record:
                    set_overall_state(record)
                    yield record
            if isinstance(item, MappedOperator) or is_parent_mapped:
                instances = list(_mapped_summary(grouped_tis.get(item.task_id, [])))
            else:
                instances = list(map(_get_summary, grouped_tis.get(item.task_id, [])))
            return {
                "id": item.task_id,
                "instances": instances,
                "label": item.label,
                "extra_links": item.extra_links,
                "is_mapped": isinstance(item, MappedOperator) or is_parent_mapped,
                "has_outlet_datasets": any(isinstance(i, Dataset) for i in (item.outlets or [])),
                "operator": item.operator_name,
            }
        
        task_group = item
        group_is_mapped = isinstance(task_group, MappedTaskGroup)
        children = [
            task_group_to_grid(child, grouped_tis, is_parent_mapped=group_is_mapped)
            for child in task_group.topological_sort()
        ]
        def get_summary(dag_run: DagRun):