Geostatistical modelling of climate parameters as a first step in aiding producers determine suitable mitigation strategies in Langhe growing region

Abstract

Introduction: Meso-climatic variation increases in hilly terrain, influenced by changes in elevation, slope gradient and slope aspect (Ferretti, 2021). This can lead to variation in wine grape maturity and exposure to disease. The ability to extrapolate point data for bioclimatic indexes over a broader area can help to identify areas within a vineyard that may have greater exposure to heat or humidity (Bois et al., 2018). This can better help producers make strategic management decisions regarding implementation of disease prevention practices, and application of climate risk related mitigation actions. The project “Producers in a Network for Shared Weather Monitoring for the Benefit of Sustainable Viticulture” aims to conduct a geolocalized census of private and public weather stations in a very heterogeneous hilly viticulture area within Langhe territory (Mania et al., 2021), and to produce maps of bioclimatic indexes as a tool to better understand the meteorological variability of the area and to aid in increased precision of vineyard management practices.

Materials and Methods: A network of 40 producers of wine grapes provided data from a total of 50 public and private weather stations distributed within a 100 km² area. From this data 7 different bioclimatic and climatic indexes were calculated: Average Maximum Annual Temperature (MaxT), Average Minimum Annual Temperature (MinT), Average Annual Temperature (AvgT), Absolute Maximum Temperature (AbsT), Average Annual Diurnal Range (DR), Annual Total Precipitation (Precip), Growing Degree Days (GDD). The geostatistical method of universal kriging was used to create a model to extrapolate point data over the entire region using topographically related covariates (elevation, slope gradient and slope aspect) (Hudson & Wackernagel, 1994; Sluiter, 2008). From the resultant model, maps were developed covering the region at a 10 m resolution mirroring the resolution of the digital elevation model (DEM) from which the covariates were extracted. This mapping was done for the year 2024 and by month groupings for spring (March to May), summer (June to August) and autumn (September to November).

Conclusion: This low cost approach to mesoscale climate analysis offers producers a visual aid to observe multi-year climate patterns which can help to implement mitigation strategies more precisely within vineyards and between vineyards. The next step of this project will be to provide the maps online for ease of access to producers.

References

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Mania, E., Petrella, F., Giovannozzi, M., Piazzi, M., Wilson, A., & Guidoni, S. (2021). Managing vineyard topography and seasonal variability to improve grape quality and vineyard sustainability. Agronomy, 11(6), 1142. https://doi.org/10.3390/agronomy11061142

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