Geography Reference
In-Depth Information
Depending on the region, the number of MSs ranged from 9 to 29. In
addition, the influence of the distance between radar station and MSs was
analysed.
Furthermore, a leaf wetness simulation model used by ZEPP (Racca,
2001, unpublished) was run on data from both methods of precipitation
measurement and the results were compared.
The parameters for the amount of precipitation, number of hours with
precipitation and calculated leaf wetness showed high correlations between
radar values and measured data. The maximum of the hourly deviation of the
amount of precipitation was 0.06 mm. In hours with rainfall the deviation was
slightly higher (0.36 mm). No correlation could be detected for the distance
between radar stations and MSs.
For hourly rainfall pattern, a correlation of 91.4% between stations and
validation areas was measured. The best correlations were obtained for the leaf
wetness model for which values > 99.9% were achieved.
The results clearly show that the use of radar data as an input parameter in
disease forecast models is valid. By adding data of temperature and relative
humidity with high spatial resolution, an optimal basis for plot-specific
forecasts has been established.
Moreover, this system allows the exact detection of local convective
rainfall events, which at the moment often remain undetected using individual
MSs. Significant improvements of the spatial forecasting by plant disease
simulation models can be expected from the use of radar data.
2.4. Introducing Spatial Risk Maps into Practice (www.isip.de)
ISIP, the Information System for Integrated Plant production www.isip.de,
is a Germany-wide online decision support system. It has been initiated in
2001 by the German Crop Protection Services as a common portal, thus
achieving synergies by pooling existing information.
Target groups are farmers as well as advisors.
Since information transfer is the primary task of extension services, the
system is intended to make this work more efficient by using modern informa-
tion technology. Therefore a bi-directional data flow between the services and
the farmers was developed. By combining general with specific data,
recommendations can be refined from regional to individual.
The information is primarily distributed via HTML pages, thus a browser
is necessary to use the system (Röhrig and Sander, 2004).
