Overall Conclusion and Discussion - Response of Flood Events to Land Use and Climate Change - page 220

wrong path. As an overall result, it was concluded that the interpolation tech-
niques were not successful in creating a perfect DEM more accurate than the
original DEM. Consequently, the first assumption is rejected. Therefore, in the
hydrodynamic simulation the original DEM was applied. The quality of DEM
was also tested hydrologically using the drainage enforcement algorithm to
recognize that each spurious sink is surrounded by a drainage divide containing
at least one saddle point.
• The second assumption was that the original DEM is included in observed
elevation data points with 100 % accuracy. Therefore, it was used as a correct
source to test the different interpolation methods. The idea behind this
assumption was to find the best interpolation technique which represents the best
agreement with the observed elevation of the data point set. As a general
conclusion, the results of analysis showed that all DEMs derived from different
interpolation techniques were statistically significant. Going into the details in
terms of RMSE, R-square, maximum absolute error and frequency analysis,
better results in model accuracy were obtained when Exponential, Gaussian,
Stable, and Spherical models were used instead of Circular, IDW, Topo to
Raster, and Spline. Therefore, as an overall result, it could be concluded that
Geostatistic techniques show the strongest results compared to deterministic. In
between, the Spherical showed better agreement with the observed data and
represents the smoothest and the most accurate DEM. The Q-Q plot was also
applied to quantify and represent the estimated variable's distribution against
the original values more consistent for Geostatistic techniques. It could be
concluded that in Geostatistic methods the distribution of a variable matches
very strongly with the observed or original data distribution. On the other hand,
the points cluster around a straight line. ''Residuals'' analysis showed that the
best results also belong to Geostatistic-Spherical methods, which achieved the
most accurate results with a value of\.001. Consequently, it could be concluded
that Geostatistic techniques show the strongest results compared to the deter-
ministic. In between, the Spherical and Gaussian showed better agreement with
the observed data and represents the smoothest and more accurate DEM. In
terms of spatial analysis, the standard residual diagnosis graphs shows that the
best results in terms of normal distribution belongs to Gaussian method because
all scattered values spread close to zero (skewness is 0.071) between the ranges
of -0.5-0.5. As an overall conclusion the residuals data set in Gaussian method
obeys a normal distribution. The results of Moran's I investigation showed
Gaussian and Stable showing perfect dispersion in the first distance. On the
other hand, the Moran's I value for IDW, Topo to Raster, Spline, Circular,
Exponential, and Spherical represent perfect correlation in the first distance.
Inbetween the lowest Moran's I value of 0.013 belongs to Spherical. To com-
pare the accuracy of the interpolated DEMs, the stream network for each surface
was derived using ArcGIS. The modeled stream network was compared with the
stream network digitized from topographic maps (''true'' data). By reviewing
the figure it seems that the overlay of (b) IDW, (c) Spline, (d) Kriging, Circular,
(g) Kriging, Exponential and (h) Kriging, Stable produced the weakest results,