Fractal analysis of the hydrological information obtained from high-spatial resolution dems: application in terroir zoning of d.o. campo de Borja (Spain)

Farming management practices aiming at conserving soil moisture have been developed in arid and semiarid-areas facing water scarcity problems. Organic mulching is an effective method to manipulate the crop-growing microclimate increasing crop yield by controlling soil temperature, and retaining soil moisture by reducing soil evaporation. In this sense, the effectiveness of different organic mulching materials (straw mulch and grapevine pruning debris) applied within the row of a vineyard was evaluated on the soil and on the vine in a Tempranillo vineyard located in La Rioja (Spain). Organic mulches were compared with a traditional bare soil management technique (based on the use of herbicides to avoid weed incidence). Mulching coverages favourably influenced the soil water retention throughout all the grapevine vegetative cycle. However, the soil-moisture variation was not the same under different mulching materials, being the straw mulch (SM) the one that retained more water in comparison with grapevine pruning debris (GPD) based-cover. The changes of soil moisture in the upper surface layer (0–10 cm) were highly dynamic, probably due to water vapour fluxes across the soil-atmospheric interface. However, both, SM and GPD reduced these fluctuations as compared with bare soils. A similar trend occurred with soil temperature. Both organic mulches altered soil temperature in comparison with bare soil by reducing soil temperature in summer and raising it in winter. Moreover, the same buffering effect for the temperature on the covered soil also remains in the deeper layers. To conclude, we could see that organic mulching had a positive impact on soil-moisture storage and soil temperature and the extent of this effect depends on the type of mulching materials. These changes led to higher rates of photosynthesis and stomatal conductivity compared to bare soils, also favouring crop growth and grape yields.

Climate change impacts regional and local climates, which in turn affects the world’s wine regions. In the short term, these modifications rises issues about maintaining quality and style of wine, and in a longer term about the suitability of grape varieties and the sustainability of traditional wine regions. Thus, adaptation to climate change represents a major challenge for viticulture. In this context, island and coastal vineyards could become coveted areas due to their specific climatic conditions. In regions subject to warming, the proximity of the sea can moderate extremes temperatures, which could be an advantage for wine. However, coastal and island areas are particular prized spaces and subject to multiple pressures that make the establishment or extension of viticulture complex.
In this perspective, it seems relevant to assess the potentialities of coastal and island areas for viticulture. This contribution will present a spatial optimization model that tends to characterize most suitable agroclimatic patterns in historical or emerging vineyards according to different scenarios. Thanks to an in-depth bibliography a global inventory of coastal and insular vineyards on a worldwide scale has been realized. Relevant criteria have been identified to describe the specificities of these vineyards. They are used as input data in the optimization process, which will optimize some objectives and spatial aspects. According to a predefined scenario, the objectives are set in three main categories associated with climatic characteristics, vineyards characteristics and management strategies. At the end of this optimization process, a series of maps presents the different spatial configurations that maximize the scenario objectives.

This work is a first step to make a map of vineyard soils. The characterization of the soils of the Protected Designation of Origin (D.P.O.) Valdepeñas will allow to group the studied profiles according to their physico-chemical characteristics and the concentrations of most relevant chemical elements. 90 soil profiles were analysed throughout the territory and the soils were sampled and described according to FAO (2006) and classified according to and Soil Taxonomy (2014). All samples were air dried, sieved and some physico-chemical parameters were determined following standard protocols. Also, major and trace elements were analysed by X-ray fluorescence. The statistically study was made using the SPSS program. Trend maps were made using the ArcGIS program. The studied soils have the following average properties: pH, 8.3; electrical conductivity, 0,20 dS/m (low); clay, 18.8% (medium) and CaCO3, 17.1% (high). In the study for the major elements. The major elements of these soils are Si, followed by Ca and Al, with an average content of 203.7 g/kg, 105.5 g/kg and 74.0 g/kg respectively. On the other hand, 27 trace elements have been studied. Of all of them, it can be highlighted the average values of Ba (361.8 mg/kg), Sr (129.3 mg/kg), Rb (83.4 mg/kg), V (74.2 mg/kg) and Ce (70.6 mg/kg). Ba, V and Ce values are higher and the values of Sr and Rb are lower to those found in the literature. The discriminant analysis shows a percentage of grouping of 91%. The content of chemical elements together with the physico-chemical characteristics allows grouping the soils in 4 group according to their order in the classification to Soil Taxonomy; due to the importance of the Calcisols in Castilla-La Mancha, it has been decided to establish them as their own group even if they do not appear in Soil Taxonomy classification.

A large varietal collection including over 1700 varieties was maintained in Conegliano, ITA, since the 1950s. Phenological data on a subset of 400 grape varieties including wine grapes, table grapes, and raisins were acquired at bud break, flowering, veraison, and ripening since 1964. Despite the efforts in maintaining and acquiring data over such an extensive collection, the data set has varying degrees of missing cases depending on the variety and the year. This is ubiquitous in phenology datasets with significant size and length. In this work, we evaluated four state-of-the-art methods to estimate missing values in this phenological series: k-Nearest Neighbour (kNN), Multivariate Imputation by Chained Equations (mice), MissForest, and Bidirectional Recurrent Imputation for Time Series (BRITS). For each phenological stage, we evaluated the performance of the methods in two ways. 1) On the full dataset, we randomly hold-out 10% of the true values for use as a test set and repeated the process 1000 times (Monte Carlo cross-validation). 2) On a reduced and almost complete subset of varieties, we varied the percentage of missing values from 10% to 70% by random deletion. In all cases, we evaluated the performance on the original values using normalized root mean squared error. For the full dataset we also obtained performance statistics by variety and by year. MissForest provided average errors of 17% (3 days) at budbreak, 14% (4 days) at flowering, 14.5% (7 days) at veraison, and 17% (3 days) at maturity. We completed the imputations of the Conegliano dataset, one of the world’s most extensive and varied phenological time series and a steppingstone for future climate change studies in grapes. The dataset is now ready for further analysis, and a rigorous evaluation of imputation errors is included.

To digitally record and present all the origins of Austrian wines in the same perfect and clear way was the motivation for the Austrian Wine Marketing Board (Austrian Wine) to start with the project in 2018. In June 2021 the results were presented to the public in an online viewer showing all the designations of Austrian wine, available at https://austrianvineyards.com in a largely barrier-free manner. The online viewer provides tailored individual maps fitted to the respective zoom level. The smallest unit of wine-origins in Austria is called Ried and is displayed in a plot-specific manner highlighting areas under vine. Information on the Ried include administrative district, winegrowing municipality, cadastral municipality, large collective vineyard site, specific winegrowing region, generic winegrowing region, winegrowing area and, in many cases, an illustrative picture. Complementary data on the size, elevation (minimum-maximum), orientation (in 8 sectors plus flat) and gradient (minimum, maximum, average) are based on the area under vine according to the EU’s Integrated Administration and Control System. Additional information covers climate data. The diagrams are taken from the monthly breakdown of data in the annals of the Central Institute for Meteorology and Geodynamics, Austria provide a display of values for air temperature, precipitation, and sunshine hours for the reference year and the long-term average. Seasonal aggregated data on temperature, precipitation, and sunshine hours complete the display. Short descriptions with emphasis on geology and soil, field name in historical maps, etymology of the denomination, and main planted variety complements the available information for the main designations in the online viewer. These descriptions are compiled by winegrowers, geologists, historians, and journalists. All the information and data can be extracted to a pdf-file. Printed vineyard maps are also available. Missing content regarding wine origins in Styria will be completed in winter 2021/22.