### Apache Airflow version

2.2.1

### Operating System

Linux 5.4.149-73.259.amzn2.x86_64

### Versions of Apache Airflow Providers

default for 2.2.1

### Deployment

Other 3rd-party Helm chart

### Deployment details

aws eks using own-developed helm chart

### What happened

When trying to open log from gantt view - receiving an exception
```
  File "/home/airflow/.local/lib/python3.9/site-packages/pendulum/parsing/__init__.py", line 177, in _parse_common
    return date(year, month, day)
ValueError: year 0 is out of range
```

due to incorrect query parameter push: no value for `execution_date` pushed
```
/log?dag_id=report_generator_daily&task_id=check_quints_earnings&execution_date=
```

### What you expected to happen

Logs should be available

### How to reproduce

Open dag's `gantt` chart
click on task ribbon
click on `log`
observe an error

### 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)

airflow/www/views.py
dag = dag.partial_subset(task_ids_or_regex=root, include_downstream=False, include_upstream=True)
        num_runs = request.args.get('num_runs', type=int)
        if num_runs is None:
            num_runs = conf.getint('webserver', 'default_dag_run_display_number')
        try:
            base_date = timezone.parse(request.args["base_date"])
        except (KeyError, ValueError):
            base_date = dag.get_latest_execution_date() or timezone.utcnow()
        with create_session() as session:
            dag_runs = (
                session.query(DagRun)
                .filter(DagRun.dag_id == dag.dag_id, DagRun.execution_date <= base_date)
                .order_by(DagRun.execution_date.desc())
                .limit(num_runs)
                .all()
            )
            dag_runs.reverse()
            encoded_runs = [wwwutils.encode_dag_run(dr) for dr in dag_runs]
            dag_run_dates = {dr.execution_date: alchemy_to_dict(dr) for dr in dag_runs}
            min_date = min(dag_run_dates, default=None)
            tis = dag.get_task_instances(start_date=min_date, end_date=base_date, session=session)
            data = {
                'groups': task_group_to_tree(dag.task_group, dag, dag_runs, tis),
                'dag_runs': encoded_runs,
            }
        
        return htmlsafe_json_dumps(data, separators=(',', ':'))
    @expose('/robots.txt')
    @action_logging
    def robots(self):