Release Notes
Date: 11/2/07
Water surface model: Version 1
Surface dates: 1/1/00 - 9/30/07

ACCURACY OF GAGE DATA - Gage data are used by the EDEN water surface model
to create daily surfaces of water level throughout the Everglades. The
accuracy of the surface depends, in part, on the accuracy and completeness
of the gage data. The Daily Median Output files provide a list of gages and
their values for each daily surface. Some surfaces are marked PROVISIONAL
to indicate that all or some of the gage data has not been finalized by the
operating agencies. When all the gage data are finalized the surfaces will
be rerun and will replace the PROVISIONAL surfaces.

DRY CONDITIONS AT GAGES - Limited or no information exists on the depth of
the gaging wells below ground at most gages, therefore when water level
drops below ground at a gage, the recorded stage is of uncertain quality.
Because the reliability of the gage below ground is unknown, the accuracy
of the EDEN water surface is these "dry" areas is unknown. Future versions
of the model may address shallow subsurface flow conditions in the
wetlands.

MODEL CONFIDENCE NEAR CANALS - The canal and levee boundaries act as major
discontinuities in the EDEN area, and water levels from one section have
minimal or no influence into adjacent sections. Steep changes in elevation
can occur between areas at these levees. Since stratification of the data
is not feasible due to the limited number of water gages, boundary
conditions were simulated by linearly interpolating along both sides of
levels in the canals using head and tail stage data. Simulated data at
these pseudo-stations were re-sampled every 200 m and re-introduced into
the interpolation exercise. The marsh gage data together with
the interpolated data along canals represent the new extended data used for
water surface modeling. In this way, data from the marsh in one
conservation area would not influence the values in the marsh across a
canal in a different area. Even though track data (very densely sampled
preferential lines) alone may be problematic for interpolation, our mixture
of track data along canals and levees, plus randomly distributed stage
data, and the provision to use only the closest data point to the
interpolated location in each of the 8 sectors of a search neighborhood
overcomes some of the problems. Nevertheless, we still place a
reduced confidence in the interpolated surface close to canal data.