resolve bunch of deprecated code

[elbeejay]

Aims to address #58 but does not solve all warnings.

The below warnings still pop up when running the test suite:

tests/test_synthetic.py: 4 warnings
  /home/jayh/anaconda3/envs/rivgraph/lib/python3.8/site-packages/pandas/core/dtypes/cast.py:1981: DeprecationWarning: An exception was ignored while fetching the attribute `__array_interface__` from an object of type 'Polygon'.  With the exception of `AttributeError` NumPy will always raise this exception in the future.  Raise this deprecation warning to see the original exception. (Warning added NumPy 1.21)
    result[:] = values

tests/test_synthetic.py: 4 warnings
  /home/jayh/anaconda3/envs/rivgraph/lib/python3.8/site-packages/geopandas/array.py:93: DeprecationWarning: An exception was ignored while fetching the attribute `__array_interface__` from an object of type 'Polygon'.  With the exception of `AttributeError` NumPy will always raise this exception in the future.  Raise this deprecation warning to see the original exception. (Warning added NumPy 1.21)
    aout[:] = out

tests/test_verbosity.py: 88762 warnings
  /home/jayh/anaconda3/envs/rivgraph/lib/python3.8/site-packages/scipy/spatial/distance.py:308: DeprecationWarning: scipy.spatial.distance metrics ignoring length-1 dimensions is deprecated in SciPy 1.7 and will raise an error in SciPy 1.9.
    warnings.warn(

tests/test_synthetic.py::test_get_islands
  /home/jayh/anaconda3/envs/rivgraph/lib/python3.8/site-packages/numpy/core/fromnumeric.py:1970: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.
    result = asarray(a).shape

tests/test_synthetic.py::test_assigning_inletshore
  /home/jayh/anaconda3/envs/rivgraph/lib/python3.8/site-packages/geopandas/geoseries.py:118: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.
    s = pd.Series(data, index=index, name=name, **kwargs)

But given that many of these relate to the synthetic simple test case, it may also be that the setup / simplifications in that example are creating unusual scenarios that result in warnings.