### 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)

ti_fails = ti_fails.filter(TaskFail.task_id.in_([t.task_id for t in dag.tasks]))
        tasks = []
        for ti in tis:
            if not dag.has_task(ti.task_id):
                continue
            
            
            
            try_count = ti.prev_attempted_tries if ti.prev_attempted_tries != 0 else ti.try_number
            task_dict = alchemy_to_dict(ti)
            task_dict["end_date"] = task_dict["end_date"] or timezone.utcnow()
            task_dict["extraLinks"] = dag.get_task(ti.task_id).extra_links
            task_dict["try_number"] = try_count
            task_dict["execution_date"] = dttm.isoformat()
            task_dict["run_id"] = dag_run_id
            tasks.append(task_dict)
        tf_count = 0
        try_count = 1
        prev_task_id = ""
        for failed_task_instance in ti_fails:
            if not dag.has_task(failed_task_instance.task_id):
                continue
            if tf_count != 0 and failed_task_instance.task_id == prev_task_id:
                try_count += 1
            else:
                try_count = 1
            prev_task_id = failed_task_instance.task_id
            tf_count += 1
            task = dag.get_task(failed_task_instance.task_id)
            task_dict = alchemy_to_dict(failed_task_instance)