The grapevine downy mildew (Plasmopara viticola) represents the most important disease of the grapevine in Friuli-Venezia Giulia Region (Italy). The development of this disease depends from the meteorological conditions and particularly by air humidity, rain and leaf wetness (LW here after). Forecast models can help the technicians of the extension services to predict the timing and the best technique to use in operative programs. Unfortunately these models require data, coming from meteorological stations which are often variable in space (e.g. rain, leaf wetness) and hardly spatializable. In the first part of this work, a case study is presented to show the great difference between maps of daily rain duration, obtained by radar, and those created by spatialization of data and obtained by weather stations. Then the possibility to use the radar rain maps appears very interesting to estimate LW over a large area. LW and daily rain measurements, obtained by 14 weather stations of Friuli-Venezia Giulia plain (Italy), are compared with rain maps obtained by polarimetric radar GPM-500 placed in Fossalon di Grado (Friuli-Venezia Giulia, Italy). The reference measurements are made during two periods: from 1/4/2000 to 30/9/2000 and from 1/4/2001 to 30/9/2001. From radar maps rain measurements estimated are extracted above each weather station and these data are integrated for every hour. These radar data of hourly rain are compared to the corresponding measurementes of LW and rain obtained by weather stations. From this analysis it appears that there is a good correlation between the number of rain hours estimated by radar and the number of LW hours measured by stations: in the observed cases, the error found is lower than 2%; then radar has a good precision to estimate LW due to rain. Therefore the use of Radar is foretold to give meteorological inputs in simulation models that can work to evaluate the development of fungal diseases. In the second part a model to daily display the infections of downy mildew all over the plain of Friuli-Venezia Giulia is described. Elements of this model are: o the creation of a daily grid of rain estimated by a meteorological polarimetric radar (GPM-500) located in Fossalon di Grado; o the creation of a daily grid of temperature, air humidity, solar radiation, wind speed using data coming from 14 synoptic meteorological stations located in the plain of the region; o the creation of a daily grid of leaf-wetness computed using the SWEB model for the data measured or estimated in the previous point; o the estimation of the P. viticola infection level using a forecast model (in this case Goidanich). o The daily graphical output in every point of the grid is: number of the actual cycles of P. viticola infections; number of days required for the next infection; annual amount of infective cycles. The model has been checked in a limited area (about 200 km2) with an high presence of grapevine (DOC Aquileia) in the period from may 2000 to september 2000. In this area the data from eight meteorological automatic stations installed for diseases-defence purposes are used as test, and has been calculated the downy mildew infections using the Goidanich model. These grids have been compared with the maps calculated using data coming from meteorological radar and synoptic stations. The outputs are similar and the proposed method can be considered a good approach in the operative use of radar in the crop protection.
Use of meteorological radar to estimate leaf wetness as data input for application of territorial epidemiological model (downy mildew--Plasmopara viticola)
S Dietrich;
2004
Abstract
The grapevine downy mildew (Plasmopara viticola) represents the most important disease of the grapevine in Friuli-Venezia Giulia Region (Italy). The development of this disease depends from the meteorological conditions and particularly by air humidity, rain and leaf wetness (LW here after). Forecast models can help the technicians of the extension services to predict the timing and the best technique to use in operative programs. Unfortunately these models require data, coming from meteorological stations which are often variable in space (e.g. rain, leaf wetness) and hardly spatializable. In the first part of this work, a case study is presented to show the great difference between maps of daily rain duration, obtained by radar, and those created by spatialization of data and obtained by weather stations. Then the possibility to use the radar rain maps appears very interesting to estimate LW over a large area. LW and daily rain measurements, obtained by 14 weather stations of Friuli-Venezia Giulia plain (Italy), are compared with rain maps obtained by polarimetric radar GPM-500 placed in Fossalon di Grado (Friuli-Venezia Giulia, Italy). The reference measurements are made during two periods: from 1/4/2000 to 30/9/2000 and from 1/4/2001 to 30/9/2001. From radar maps rain measurements estimated are extracted above each weather station and these data are integrated for every hour. These radar data of hourly rain are compared to the corresponding measurementes of LW and rain obtained by weather stations. From this analysis it appears that there is a good correlation between the number of rain hours estimated by radar and the number of LW hours measured by stations: in the observed cases, the error found is lower than 2%; then radar has a good precision to estimate LW due to rain. Therefore the use of Radar is foretold to give meteorological inputs in simulation models that can work to evaluate the development of fungal diseases. In the second part a model to daily display the infections of downy mildew all over the plain of Friuli-Venezia Giulia is described. Elements of this model are: o the creation of a daily grid of rain estimated by a meteorological polarimetric radar (GPM-500) located in Fossalon di Grado; o the creation of a daily grid of temperature, air humidity, solar radiation, wind speed using data coming from 14 synoptic meteorological stations located in the plain of the region; o the creation of a daily grid of leaf-wetness computed using the SWEB model for the data measured or estimated in the previous point; o the estimation of the P. viticola infection level using a forecast model (in this case Goidanich). o The daily graphical output in every point of the grid is: number of the actual cycles of P. viticola infections; number of days required for the next infection; annual amount of infective cycles. The model has been checked in a limited area (about 200 km2) with an high presence of grapevine (DOC Aquileia) in the period from may 2000 to september 2000. In this area the data from eight meteorological automatic stations installed for diseases-defence purposes are used as test, and has been calculated the downy mildew infections using the Goidanich model. These grids have been compared with the maps calculated using data coming from meteorological radar and synoptic stations. The outputs are similar and the proposed method can be considered a good approach in the operative use of radar in the crop protection.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
