Climate change threatens agriculture, altering growing seasons and challenging viticulture in traditionally suitable regions. Grape quality, essential for good wine, depends on proper management and suitable territories. In Northern Italy's Oltrepò Pavese region, enhancing wine production and economic stability for farmers is crucial. Moreover, detection of problematic vineyards is also a key point to enhance wine production. To address them, a PhD project is co-funded by Confagricoltura Pavia, Sezione Vino, and PNRR’s NODES Spoke 6 VINO.
Abandoned vineyards harbour diseases like flavescence dorée: an incurable phytoplasma disease, spread by the vector Scaphoideus titanus that infects nearby fields annually. Control relies on insecticides and uprooting of infected vines, making abandoned vineyards persistent reservoirs of infection. Identifying such vineyards is challenging due to legal complications for owners.
This study employs the YOLOv8 deep learning model to detect active and abandoned vineyards using high-resolution satellite imagery. A custom dataset was created from Google Earth Pro imagery of the Lombardy region in Italy, comprising 188 images of abandoned vineyards and 178 images of active vineyards. Pre-processing techniques, including auto-orientation, static cropping with 25–75% horizontal and vertical regions, resizing to 640×640 pixels, and adaptive equalization for contrast adjustment, were applied to enhance image quality. Augmentation technique was also applied on the dataset to increase the overall dataset size.
Preliminary results show the YOLOv8 model detects accurately (F1 score = 58%) active and abandoned vineyards, providing a reliable, systematic tool for vineyard management. This approach addresses a critical gap in regional viticulture, aiding in the mitigation of disease spread and supporting sustainable agricultural practices. The research results proved that the proposed method has strong generalization and good detection performance for identifying vineyard abandonment using satellite images and machine learning. This work can contribute as part of the economic stability and sustainability of wine grape production in Oltrepò Pavese.
This work was funded by the European Union - NextGenerationEU, Mission 4 Component 1.5 - ECS00000036 - CUP F17G22000190007.
How to cite: Anwar, S., Marchese, G., Toffanin, C., and Vaglia, V.: Vineyard condition detection method using Google Earth Images and the YOLOv8 model in Northern Italy, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-981, https://doi.org/10.5194/egusphere-egu25-981, 2025.
In many hilly and mountainous regions worldwide, the construction technique of dry-stone walls constitutes tangible evidence of the close connection between traditional knowledge and sustainable land management, which has been recognized as an Intangible Cultural Heritage of Humanity by UNESCO. Since ancient times, dry-stone walls have been essential to facilitate cultivation of rugged environments by creating terraces that optimized land management, improved water management, prevented erosion and supported the needs of local communities.
However, the gradual abandonment of agricultural practices, mainly attributable to the intrinsic difficulties of cultivation in these areas and socio-economic changes, has triggered a progressive and widespread degradation of the dry-stone wall terrace complexes. This process can be further exacerbated by the effects of high-intensity rainfall events, which can accelerate the degradation of terraced slopes, increasing the frequency and magnitude of slope instability phenomena, also involving extensive dry-stone wall collapses. These phenomena have generated significant fertile soil losses along with economic and cultural impacts, threatening the preservation of an invaluable heritage.
The primary objective of this study is to analyse the influence of different land management practices on the hydromechanical characteristics of terraced soils and, consequently, on gaining insights into the factors controlling the occurrence of rainfall-induced instability processes of terraced slopes, such as shallow landslides. The research activities are in the framework of the project Stonewalls4life, a LIFE EU-project focused on the role of drystone walls in increasing the resilience of rural territories and in counteracting the impacts of climate change. The investigation is conducted at two monitoring sites situated along a terraced slope in the Manarola area, which is located within the Cinque Terre National Park (Liguria Region, NW Italy), where terraces constitute a characteristic feature of the local landscape and cultural heritage.
The selected monitoring sites consist of terraces having different land uses, namely currently cultivated vineyard and abandoned vineyard since several decades. To achieve the research purposes, hydrological monitoring instruments have been installed at both sites to monitor soil-water interactions, specifically measuring soil moisture content, soil temperature and suction during rainfall events. The monitoring network also includes a complete weather station to collect meteorological data (e.g., rainfall intensity, air humidity, air pressure, wind speed). In this contribute, the multi-sensor hydrological data acquired over a period longer than 2 years are presented along with the investigation of the hydrological response of the monitoring sites to rainfall at different time scales (i.e., seasonal and single rainstorm).
The obtained results will be useful in the frame of hydrological modelling of terraced slopes, allowing to identify the areas most prone to instability. Eventually, the research activities will represent a useful guide for the formulation of targeted strategies aimed at improving the management of agricultural terraces in the study area.
How to cite: De Simone, A., Pepe, G., Guerriero, L., Russo, G., Raso, E., Tarantino, A., Vitale, E., Scarpellini, P., Calcaterra, D., and Cevasco, A.: Hydrological monitoring of agricultural terraces in different land use conditions at the Cinque Terre National Park (NW Italy), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20203, https://doi.org/10.5194/egusphere-egu25-20203, 2025.
Soils rich in expansive clay minerals undergo significant soil structures and volume changes due to moisture fluctuations, swelling when absorbing water and shrinking as they dry. The volume changes can lead to structural damage in buildings and land degradation, and cause the formation of deep, polygonal cracks on the surface during dry periods. This affects water retention, infiltration, and root development, and leads to issues in hydrological modelling since the soil's response to water content changes is nonlinear and site-specific.
The aim of the study is to quantify soil volume changes by combining field measurements (soil water content) with laboratory analysis (HYPROP), correlating soil water content with volume changes over time at different soil depths. The time series of volume changes are then compared with Advanced Differential Interferometric Synthetic Aperture Radar (A-DInSAR) displacement time series.
The study focuses on Oltrepò Pavese, an agricultural area and one of the largest wine-producing regions in Lombardy, northwestern Italy. In this area, a monitoring system comprising meteorological and hydrological probes has been installed in the soil since 2021 as part of the Drive Life project (https://www.drive-life.it/) and now it is managed in the framework of the NODES project, financed by MUR – M4C2 1.5 of PNRR, funded by the European Union's NextGenerationEU (Grant agreement no. ECS00000036).
The quantification of the soil volume changes under varying soil water contents can enhance the accuracy of hydrological models.
How to cite: Pedretti, L., Lexmond, B., Stouthamer, E., and Meisina, C.: Quantifying soil volume changes in vineyards: a study of expansive clay soils in Oltrepò Pavese, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16070, https://doi.org/10.5194/egusphere-egu25-16070, 2025.
The actual and projected climate change with extreme weather events can increase in frequency and intensity land degradation phenomena, such as soil erosions and shallow landslides, with consequence to soil and fertility loss as a major threat, and a significant environmental problem for the agroecosystems where farming is executed on sloping soil (e.g. vineyards, olive groves, etc.), thus bringing to a land abandonment. Another factor to take into consideration in affecting significantly the land degradation, is soil tillage and agricultural practices. If these are uncontrolled or incorrect, they can accelerate the development of land degradation processes. In this framework, it is important and necessary applying in agroecosystems effective solutions for disaster risk reduction (DRR) which, at the same time, help to promote biodiversity by reducing the use of pesticides (or fertilizer) and are economically sustainable for farmers.
The Nature-based Solutions (NbS), as conservative agricultural practices (e.g., agroforestry or cover cropping), are funded by countries or the union of countries, such as the European Union or the United Nations, and can help address all these challenges helping to slow global warming by reducing its risk, frequency, and intensity. However, NbS are little promoted by local governments and applied by farmers, favoring to counter land degradation, gray infrastructure measures that sometimes or often, are only applicable at a small scale, proving ineffective in achieving land degradation neutrality.
The study area corresponds to a sector of Oltrepò Pavese (Northen Italy), an area purely devoted to viticulture where more than 2000 shallow landslides were triggered in the last 15 years, in consequence of intense rainfall events, with a density of distribution which reached more than 40% of the territory cultivated with grapevines. In this area, since 2021, two representative demo farms have been equipped with hydrometeorological monitoring stations, to measure the soil water content every 10 minutes for 90 cm depth. Measurements are taken in correspondence of different NbS as: cover crop types (spontaneous grass cover, cereal-based mixture and legumes-based mixture) and different management techniques (Green manuring, Between-row mulching, Piling of grass under the row).
The aim of this work is to provide a framework of the NbS analyzed in the study, taking into consideration the hydrological monitoring carried out, to observe the differences on soil water content trends in different seasons along the year. The outcomes of this monitoring can reveal different responses in terms of water stress and vulnerability to land degradation processes.
The work is a PNRR-funded PhD project in partnership with seven municipalities, focusing on identifying technically and economically viable NbS for the area. The scientific outcomes will be incorporated into municipal planning and rural police regulations to prevent shallow landslides.
How to cite: Gambarani, A., Vercesi, A., Bordoni, M., Giganti, M., Vivaldi, V., Gatti, M., and Meisina, C.: Nature-based Solutions and Hydrological monitoring in vineyards of Oltrepò Pavese (Northern Italy): a framework for land degradation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13150, https://doi.org/10.5194/egusphere-egu25-13150, 2025.
Farm-scale spatial variability of grapevine yield and related berry quality traits can potentially cause decreasing profitability. Marginal land often presents degraded soils at variable extents, which might differently respond to changing climatic conditions. Hence, analyzing the relationship between relevant soil properties and berry quality on the vineyard spatial scale, as well as the grape response to different climates might help to optimize management practices and precision agriculture interventions.
To test the above relationships, a two-year (2023 and 2024) experiment was conducted in a commercial vineyard (Vitis vinifera L, cv Chardonnay/1103P, 0.9 × 2.7 m) located in a 16% sloping hill in Southern Italy (80 m asl, 40°08’29”N and 16°37’06”). Meteorological variables were recorded throughout the season by means of a standard weather station located ~ 0.3 km far from the vineyard. Soil zoning at vineyard scale was obtained by performing a proximal soil survey with an electro-magnetic induction (EMI) sensor. Georeferenced measures of the apparent electrical conductivity (ECa) were processed using Ordinary Kriging implemented in the QGIS software to produce continuous maps of ECa. The EMI maps, associated with the aspect and slope maps, were used as input for a clustering algorithm to identify homogeneous zones (HZs) within the vineyard. The results of the K-means clustering enabled the identification of 3 HZs that were analysed for soil properties, plant and grape characteristics. Fifty-two soil samples, collected at , were analysed for the assessment of the main chemical and physical properties (i.e., pH, organic carbon content, total carbonates, texture, cation exchange capacity, exchangeable bases, etc). Significant correlations were found between EMI data and several soil properties (including fine sand, Na and Mg exchangeable content, cation exchange capacity, pH), supporting soil zoning based on the ECa values. Over the two surveyed years, shoot and cluster number and mass, as well as pruning mass data were collected. At harvest (16th and 8th of August in 2023 and 2024, respectively), yield was determined on a total of 45 vines (15 per HZ), and then berry subsamples (~ 40 per vine) were used for grape quality traits determination (berry fresh mass, total soluble solids-TSS, pH and titratable acidity-TA). A factorial ANOVA was performed considering the grape characteristics as dependent variables and both the HZs and vintages as categorial factors. Over the two years, results highlight significant differences in grape characteristics among the HZs, in terms of cluster mass, grape pH, TSS and TA, while only for cluster mass and pH the differences were significant also between the vintages. Calculation of the percentage of variance of the grape quality attributable to HZs, vintage and HZs x vintage interaction enabled the recognition of the HZs as explaining from the 58 to 67% of the grape quality variability.
This study was carried out within the Agritech National Research Center and received funding from the European Union Next-Generation EU (PIANO NAZIONALE DI RIPRESA E RESILIENZA (PNRR) – MISSIONE 4 COMPONENTE 2, INVESTIMENTO 1.4 – D.D. 1032 17/06/2022, CN00000022) (T7.1.1, T2.3.1).
How to cite: Vingiani, S., Biglia, A., Carlomagno, A., Nuzzo, V., Perreca, C., Pasquale, R., and Giuseppe, M.: Spatial variability of soil degradation and yield quality traits in a marginal vineyard in Southern Italy. , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12995, https://doi.org/10.5194/egusphere-egu25-12995, 2025.
Vineyards cultivated on steep terrains are widespread worldwide and serve as both a dominant landscape feature and the primary economic activity in many regions. These vineyards may face a variety of issues, including shallow slope instabilities, which can be triggered by intense thunderstorms or prolonged periods of heavy rainfall. Shallow landslides can cause significant damage to vineyards, resulting in a loss of soil fertility and biodiversity. It is crucial to characterize the slopes where vineyards are planted to assess potential instability risks and better understand how different inter-row management practices might influence the likelihood of slope failures.
The aim of this study is to present a multidisciplinary approach for estimating the susceptibility of shallow slope instabilities in steep terrain vineyards. The method follows several key steps: i) a preliminary characterization of the slope's geological and geomorphological conditions using UAV surveys, soil trenches, and monitoring of soil water content with in-situ probes (TDR, Tensiometers); ii) the slope hydrogeological assessment throughout geophysical approaches such as the Electrical Resistivity Tomography (ERT), iii) the assessment of grapevine root density and reinforcement in inter-rows with different soil management practices (e.g., conventional tillage versus sustainable approaches).
This approach was applied to different test sites in the Oltrepò Pavese (northern Italian Apennines), an important Italian wine regions prone to water stress and slope instabilities. The findings of this study can help identify conditions that lead to shallow failures in vineyards on steep terrains and highlight the positive impact of soil management practices, particularly in the context of climate change.
This conference abstract is part of the project NODES which has received funding from the MUR – M4C2 1.5 of PNRR funded by the European Union - NextGenerationEU (Grant agreement no. ECS00000036).
How to cite: Vivaldi, V., Bordoni, M., Torrese, P., Crozi, M., and Meisina, C.: Hydrogeological characterization of steep vineyard slopes through a combined approach for shallow slope failures susceptibility estimation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10441, https://doi.org/10.5194/egusphere-egu25-10441, 2025.
Soil erosion in viticulture significantly exceeds the natural soil formation rate of 1.4 t ha⁻1
yr⁻1 for mineral soils in Europe and poses a major challenge, particularly in vineyards situated
on steep slopes. While numerous studies have quantified erosion in European vineyards,
particularly in Western, Central, and Mediterranean Europe, focused erosion research in
Austrian vineyards is rare. Despite accounting for only 0.25% of agricultural land, Austrian
vineyards experience high erosion rates, with estimates averaging 21.2 t ha⁻1ˆ yr⁻-1, according
to RUSLE-based modeling.
Traditional erosion estimation methods, including the stock unearthing method (SUM) and its
improved version (ISUM), offer cost-effective approaches for assessing vineyard erosion.
However, both approaches are based on limited Gnss measurements, which neglect terrain
irregularities and underestimate the erosion volume. Recent advances in Structure-from-
Motion (SfM) photogrammetry using unmanned aerial vehicles (UAVs) allow for highresolution
digital elevation models (DEMs), providing enhanced spatial accuracy and multitemporal
surface analysis.
This study introduces and evaluates the airSUM method, which integrates UAV-based SfM
with SUM to improve erosion estimates in a Viennese vineyard. Erosion patterns, modeled
surface runoff, and total soil loss were assessed using recent DEMs generated by each
method and validated against external GNSS RTK measurements. When applied to an area of
700 m2, airSUM detected approximately 32.7 +/- 17.5 m3 of soil erosion over the past eight
years, which is equivalent to about 84.1 +/- 45 tons per hectare per year. The airSUM approach,
leveraging SfM’s ability to capture detailed micro-topography, achieves a more precise
representation of erosion dynamics and enables cost-effective long-term monitoring. These
results illustrate the potential of airSUM to refine erosion assessments in viticulture in order to
implement targeted soil protection measures and promote the sustainable management of
vineyards.
How to cite: Kanta, R. and Kraushaar, S.: airSUM: Enhancing Erosion Modeling in Viennese Vineyards with Structure from Motion andStock Unearthing Methods, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18519, https://doi.org/10.5194/egusphere-egu25-18519, 2025.
Rainfall-induced shallow landslides affect buildings, roads, facilities, cultivations, provoking significant damages to people, economy and territory. The change in climatic conditions may impact the temporal probability of occurrence of these phenomena in a particular territory, in terms of both number of events per year and volumes of mobilized materials in a particular triggering event. For these reasons, it becomes fundamental the application of methodologies able to predict scenarios of temporal occurrence of shallow failures according to forecasted trends of the triggering parameters. In this framework, this work investigates the possible modification of the temporal probability of occurrence of shallow landslides in a prone area, passing from the actual climatic conditions to the projected climatic changes up to 2070. This approach was applied in Oltrepò Pavese (northern Italian Apennines), where several triggering events occurred since 2009. Temporal probability of occurrence was estimated applying a data-driven method based on rainfall and soil water content conditions at daily resolution, allowing to predict the possibility that shallow landslides could occur in a particular day. This model was applied using actual climatic conditions, since the use of field meteorological data of last 20 years, and projected future climatic conditions up to 2070, derived from climatic projections available in the study area. The results of this work allow to estimate the future changes in the probability of occurrence of shallow failures in this area than the actual conditions, both at yearly and seasonal scales, furnishing an important tool for the implementation of solution to reduce the future risk and to make effective land planning strategies. This work is part of the project NODES which has received funding from the MUR – M4C2 1.5 of PNRR funded by the European Union - NextGenerationEU (Grant agreement no. ECS00000036).
How to cite: Bordoni, M., Zangenehpour, M., Vivaldi, V., and Meisina, C.: Reconstruction of scenarios of actual and future probability of occurrence to shallow landslides in a prone area of Northern Italy, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9439, https://doi.org/10.5194/egusphere-egu25-9439, 2025.
Soil moisture content (SWC) has a major impact on soil quality and plant health. Climate change affects soil moisture conditions in agricultural ecosystems, due to changes in precipitation amount and intensity. The aim of present study was to investigate the effect of different inter-row management techniques as effective nature-based solutions on soil moisture in vineyard ecosystems based on own and literature data. The main focus was on SWC data, while available datasets on soil organic carbon (SOC), bulk density, penetration resistance, and saturated hydraulic conductivities were further studied.
We found 70 data sets concerning soil water content (SWC) in non-irrigated vineyards involving tillage and green cover. The data revealed that SWC enhancement depends on the type of green cover, as perennial grass (GC) tended to increase SWC on average by 15%, whereas cover crops (CC) decreased overall SWC on average by 20% compared to control or tilled (T) inter-row management. Sub-humid climates showed 35%–73% higher SWC compared to semi-arid research sites. Studying data divided into different temperature zones also revealed that the lower (<12°C) average annual air temperature sites had the highest SWC in vineyards.
In general, the highest average SWC in GC also included the highest soil organic carbon (SOC) content and the lowest average bulk density (1.41 g cm−3) in the data set. However, changes in overall bulk density values were not significant among inter-row soil management. We found that green cover generally increases penetration resistance (22% for GC and 61% for CC) and reduces the saturated hydraulic conductivities of the soils (i.e. 30% for GC and 79% for CC). Our data set shows that vegetation present in the inter-row is likely to decrease overall SWC, however, many studies showed the opposite results. Nevertheless, there are numerous benefits of green cover use in vineyard inter-rows, site-specific assessment is highly recommended prior to making changes in management practices.
Acknowledgments: This material is based upon work supported by the Hungarian National Research Fund (OTKA/NKFI) project OTKA FK-131792. The research presented in the article was carried out within the framework of the Széchenyi Plan Plus program with the support of the RRF 2.3.1 21 2022 00008 project. This research was funded by the Hungarian National Research Fund project number 2023-1.2.4-TÉT-2023-00090 entitled ’Soil health indicators and their relation to soil physical, chemical characteristics, and plant indices’
How to cite: Zsigmond, T., Bakacsi, Z., and Horel, Á.: Tillage, cover crops, and grass cover related soil water changes in vineyards, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9362, https://doi.org/10.5194/egusphere-egu25-9362, 2025.
Piceno is a viticultural region located in central Italy and suitable for producing high-quality wines, marked by the DOs Offida and Rosso Piceno. Steep slopes and heavy soils characterize the studied region, making it vulnerable to intense soil erosion. In order to limit soil erosion in vineyards, specific soil management practices are required, including the use of cover crops. Nevertheless, cover crops involve extensive water use at vineyard level, competing with grapevine for hydric and mineral resources. Due to the limited water availability during summer, the competition between vine and cover crops can increase the vine water stress and consequently reduce grape yield and quality. These negative conditions can be enhanced by the increased drought frequency, currently affecting the Mediterranean area. Thus, innovative soil management systems able to limit both soil erosion and drought risks are crucial for a sustainable viticulture in the Piceno region.
The aim of this study is to develop a Geographical Decision Support System (GDSS) for assisting Piceno winegrowers in soil management, able to i) support site-specific selection of the most appropriate cover crop models, and to ii) provide directions for the dynamic management of the adopted cover crops, based on seasonal meteorological trend.
The GDSS was developed based on data collected from 2019 to 2021 in six vineyards, representative of different environmental conditions. The two main grapevine varieties grown in the region were considered, i.e. Montepulciano e Pecorino. Five soil management systems based on cover crops were tested, including one spontaneous and four artificial grassing. The latter was realized using three different single species and one mix. Cover crop biomass production and composition were assessed, as well as vine water status, vigor, yield and grape quality.
GDSS inputs include vineyard geographical information, i.e. altitude, slope, aspect, soil texture, and daily meteorological data. Daily soil water content (SWC) is modelled through a mass soil water balance, and SWC dynamic is predicted based on meteorological forecast. GDSS was parametrized to optimize the competition between vines and cover crops, defining thresholds for different varieties and phenological stages. GDSS is currently under validation in 4 different vineyards, and the same parameters analyzed for the calibration stage have been measured since 2024. Additionally, vineyard’s status is monitored using images from Sentinel-2 satellite.
Results of the study highlighted a strict relation between cover crop biomass and grapevine water status, yield and quality parameters, independently from type or composition of the cover crop. On this basis, the competition between vine and cover crop was modelled in GDSS. The use of low-biomass cover crops under water limiting conditions allowed to increase yield and titratable acidity of grapes. Furthermore, interrupting cover crops through soil tillage when severe water stress was predicted allowed to maximize grape production.
The developed GDSS represents an innovative tool for driving sustainable soil management in the challenging viticultural environment of Piceno, concurrently limiting soil erosion and drought risks.
How to cite: Bianchi, D., Bolognini, M., Eccheli, G., Zeppilli, P., Coviello, L., Perathoner, L., Cola, G., and Brancadoro, L.: Development of a Geographical Decision Support System for driving soil management in Piceno vineyards, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8683, https://doi.org/10.5194/egusphere-egu25-8683, 2025.
Projected climate change is affecting the environmental suitability of a territory towards a particular cultivation. This will be of particular importance especially in correspondence of territories which are currently marginal in the biogeographic distribution of a cultivated plant typical of the Mediterranean zone, as olive trees, but they will become more adapt due to the projected future climatic scenarios. In this framework, this work aims to reconstruct different scenarios of environmental suitability of olive trees under current and future climatic conditions. The study area corresponds to a current marginal area for the distribution of this plant, namely an Italian Apennines territory (Oltrepò Pavese). Suitability scenarios were obtained applying a data-driven method based on predictors representative of the main geological, geomorphological, climatic and plant ecology variables influencing olive trees presence in a territory. The results of this work show that the future projections at different periods (short-term, at 2050; medium-term at 2070; long-term at 2100) suggest an increase in the suitable areas for olive trees, due especially to an increase in air temperature and a parallel decrease in the number of frost days projected for the future scenarios. This can guarantee a rise in suitable areas for olive trees especially in those sectors located at higher latitudes and altitudes than the ones currently more suitable to olive trees. This study represents a first attempt to assess the possible evolution of the suitability of one of the most important Mediterranean crop tree in a current marginal area located northern, representing also a useful basis to implement effective strategies of land planning and of mitigation measures to limit the impacts of the climate change effects on cultivation. This work is part of the project NODES which has received funding from the MUR – M4C2 1.5 of PNRR funded by the European Union - NextGenerationEU (Grant agreement no. ECS00000036).
How to cite: Zangenehpour, M., Bordoni, M., Gambarani, A., Giganti, M., Vivaldi, V., Rossi, G., Bazzano, P., and Meisina, C.: Current and projected future suitability to olive trees in a present marginal territory of Northern Italy, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16265, https://doi.org/10.5194/egusphere-egu25-16265, 2025.
Posters virtual: Tue, 29 Apr, 14:00–15:45 | vPoster spot 3
EGU25-20915 | Posters virtual | VPS14
Obtaining the Winkler Index for agricultural applications: a three-fold Assessment involving ground monitored data, MODIS-derived models and Copernicus-supplied dataTue, 29 Apr, 14:00–15:45 (CEST) | vP3.10
This study focuses on the estimation of the Winkler Index by several sources in the Oltrepò Pavese (Northern Italy) region, identified as the study area of the NODES project. The Winkler Index, also known as Thermal Sum, is useful for assessing grape ripening: the index, based exclusively on temperature, is traditionally derived from in-situ air temperature measurements.
Within the NODES Project, rather than focusing on a few sites, which could be monitored locally, we are interested in the analysis of large-scale areas. For this reason, we took into consideration global Land Surface Temperature derived from satellite data.
Three data sources are focused, in this paper:
- Air temperature observations from the ARPA monitoring stations (ARPA is the Environmental Protection Agency of the Lombardy Region), which despite their dense temporal granularity have a low spatial resolution (about one station every 92 km2 in the study area).
- Land Surface Temperature (LST) data from MODIS TERRA and AQUA satellite imagery, which provide a pixel-averaged Land Surface Temperature/Emissivity over 8 days with a spatial resolution of 1 km2.
- Daily Copernicus air temperature data, which have a spatial resolution of 0.1° x 0.1° (approximately 11 km x 8 km).
Our main objective was to develop a robust methodology to estimate air temperature from MODIS Land Surface Temperature and then evaluate the applicability of this approach to calculate the Winkler Index, using ARPA temperature data as ground truth for calibration and validation.
MODIS satellite-derived LST data were processed to derive estimated air temperatures via regression-based calibration techniques: the calibrated models were validated using statistical metrics, including root mean square error (RMSE) and p-values, to verify the accuracy and reliability of the estimates.
Lastly, we used Copernicus air temperature data to directly compute the Winkler Index.
The Winkler Index was calculated for the study area over the years 2018-2022, capturing interannual variability and trends influenced by climate conditions.
The Winkler Indices derived from MODIS-calibrated air temperatures showed a strong overall agreement with those obtained from ARPA data, demonstrating the potential of this approach for areas without dense meteorological networks. On the other hand, the Winkler Indices calculated from Copernicus are not always in excellent agreement with the ones evaluated from monitoring stations, considered as true.
The results of this study highlight the feasibility of leveraging satellite-based datasets to complement traditional meteorological observations for agricultural and climate research. By combining MODIS and Copernicus data with in-situ measurements, the study provides a scalable and cost-effective framework to estimate air temperature and calculate the Winkler Index over large spatial extents.
This approach has significant implications beyond viticulture, enabling more precise assessments of regional suitability and supporting adaptive management strategies in the context of climate change
How to cite: Rocca, M. T. and Casella, V. M.: Obtaining the Winkler Index for agricultural applications: a three-fold Assessment involving ground monitored data, MODIS-derived models and Copernicus-supplied data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20915, https://doi.org/10.5194/egusphere-egu25-20915, 2025.
EGU25-19693 | Posters virtual | VPS14
Arthropod, bacterial and fungal communities in vineyards with different soils and management in Oltrepò Pavese (Italy): a multidisciplinary approachTue, 29 Apr, 14:00–15:45 (CEST) | vP3.11
Soils are a key reservoir of global biodiversity, and their fundamental role is to support soil functions and ecosystem services. Biodiversity is part of the complexity and is linked to other parameters that characterise soils, and changes in soil health status influence the provision of goods and services to its beneficiaries. Knowing the biodiversity of a soil in vineyard systems and trying to relate it to other soil characteristics helps to improve soil health, apply the more suitable NBS to reduce land degradation, to improve the ecosystem services provided by the soil and to make viticulture more sustainable.
Six vineyards were selected in Oltrepò Pavese, one of the most important high-quality wines areas in Northern Italy, in different geological contexts soils with different inter-row management techniques: permanent grass cover, tillage and alternate tillage. Soil samples were collected in each vineyard, where a 1.0 m × 2.0 m trench was dug, in order to determine the geological, chemical, agronomic and physical properties. With a multidisciplinary approach, these properties were compared with the fungal, bacterial and arthropod communities.
Environmental DNA (eDNA) was extracted, and bacterial and fungal communities were detected by NGS analysis of 16S and ITS1 DNA barcodes, respectively. Arthropod communities were described by soil biological quality (QBS-ar) and biodiversity indices, after morphological identification of the different biological forms detected.
Inter-row management techniques and geological characteristics affect bacterial, fungal and arthropod communities’ composition. Soil managed with permanent grass cover are in general richer of fungal and bacterial biodiversity. Arthropods seem to be more influenced by soil texture and consequently by the chemical and physical characteristics of the soil than by tillage or grassing in the dry season. A positive correlation was found between Fungi and Bacteria orders, a negative correlation between Arthropods and Fungi orders and a weak and not significant correlation between Arthropods and Bacteria orders. The composition of the bacterial community was radically different in soil under repeated tillage and mineral fertilisation where Bacteroidia, Bacilli, Clostridia and Fusobacteria prevailing, in permanent grass cover soils the classes Alphaproteobacteria, above all, Acidobacteria-6 and Actinobacteria prevailed. Repeated tillage results in a different composition of the prevalent fungal Classes, with a predominance of Malasseziomycetes, which are not present in permanent grass cover soils. Fungi showed a positive correlation with water content, nitrogen and organic matter, while bacteria have a positive correlation with plastic limit and pH.
The results of the study can be used to helps farmers in the selection of the best inter-row management techniques in vineyards in order to reduce the effects of climate change and mitigate the effects of erosion.
How to cite: Reguzzi, M. C., Vercesi, A., Cusaro, C. M., Mazzoni, E., Bertonazzi, M. C., Ganimede, C., Bordoni, M., Maerker, M., Capelli, E., and Meisina, C.: Arthropod, bacterial and fungal communities in vineyards with different soils and management in Oltrepò Pavese (Italy): a multidisciplinary approach, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19693, https://doi.org/10.5194/egusphere-egu25-19693, 2025.
EGU25-12158 | ECS | Posters virtual | VPS14
Cultivating Insights: Unsupervised Mapping of Inter-row Management inVineyards Using Bezier Curve Properties on Sentinel-2 Time SeriesTue, 29 Apr, 14:00–15:45 (CEST) | vP3.12
Inter-row management of vineyards has various implications including on soil stability, and thus geo-
risk[2]. Two prominent classes of inter-row management are permanent grass cover (PGC), and total
tillage (TT), where the inter-row spaces are tilled to keep the soil bare. Which practice is used impacts
soil stability, and very few papers explored large-scale mapping using remotely sensed data[1]. In multi-
spectral acquisitions, reflection from vine leaves and from inter-row responses mix together, challenging
to distinguish vineyard foliage from possible inter-row vegetation. It has been indeed observed that
PGC and TT are likely more distinguishable in winter, when vines shed most of their leaves or are left
bare[1]. This increases the weight of inter-row vegetation in the spectral mix. Based on the above, here
we propose some novel discriminating features by treating the Sentinel-2 time series in winter as the
Bezier curves, which appear to increase separability.
The method has been tested on reference data collected in N-W Italy by a previous project. Data
from 130 and 141 ground truth polygons, representing PGC - and TT -managed vineyards respectively,
were collected from 10 wineries in 2015 and 2022. Sentinel-2 data from November to March with < 20%
cloud cover and ground truth for 2015 were primarily used in this work. Monthly NDVI and NDWI
data were generated using the earliest suitable S-2 acquisition each month, and their sequences of values
were used to form B`ezier curves. 5 features were considered for each index time series: arc length, area
of the bounding box, centroid of the bounding box, curvature, mean and standard deviation.
Different clustering strategies including K-Means, DBSCAN, Mean-shift, Hierarchical, and Gaussian
Mixture Model were employed. Accuracy and adjusted rand index (ARI) were used as performance
metrics. ARI ranges between [−1,1], where higher values mean better separation.
Traditional time series features such as mean, variance, maximum, average slope, ... achieve lower
accuracy levels. It can be observed from results that DBSCAN performs better with the
properties of Bezier curves in terms of accuracy and ARI. DBSCAN seems thus to be more effective at
identifying clusters of varying densities, and it is robust to noise. Hence, the proposed features generate
well-defined density-based clusters that other algorithms struggle to identify. Traditional clustering
algorithms typically assume clusters of elliptical shapes. This high disparity suggests non-spherical or
irregularly shaped clusters, where DBSCAN performs better.
This publication is part of the project NODES which has received funding from the MUR–M4C2 1.5 of PNRR funded
by the European Union-NextGenerationEU(Grant agreement no. ECS00000036).
[1] C. Garau, D. Marzi, M. Bordoni, and F. Dell’Acqua. Satellite detection of inter-row management
practices in a north-italy vineyard: Preliminary results. In IGARSS 2024-2024 IEEE International
Geoscience and Remote Sensing Symposium, pages 4325–4328. IEEE, 2024.
[2] C. Meisina, M. Bordoni, A. Vercesi, M. Maerker, C. Ganimede, M. C. Reguzzi, E. Capelli, E. Mazzoni,
S. Simoni, and E. Gagnarli. Effects of vineyard inter-row management on soils, roots and shallow
landslides probability in the apennines, lombardy, italy. In Proceedings, volume 30, page 41. MDPI,
2019.
How to cite: Dell'Acqua, F. and Mukherjee, J.: Cultivating Insights: Unsupervised Mapping of Inter-row Management inVineyards Using Bezier Curve Properties on Sentinel-2 Time Series, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12158, https://doi.org/10.5194/egusphere-egu25-12158, 2025.
EGU25-5910 | Posters virtual | VPS14
Assessment of soil erosion areas using a process-based overland flow modelling approachTue, 29 Apr, 14:00–15:45 (CEST) | vP3.13
Soil erosion is a complex process driven by the interaction between climatic factors, soil properties, topography, vegetation, and land use. It involves detachment, transportation, and deposition of soil particles due to surface runoff and wind, causing severe environmental and economic challenges. To manage erosion, several models ranging from empirical to process-based and hybrid approaches have been developed. For example, the most widely used empirical models is the Revised Universal Soil Loss Equation (RUSLE) which estimates long-term erosion rates but not reliable in short-term assessments. Process-based models, such as the Water Erosion Prediction Project (WEPP) and the European Soil Erosion Model (EUROSEM), simulate physical erosion mechanisms but require extensive data. Hybrid models like the Sediment Delivery Distributed (SEDD) and the Limburg Soil Erosion Model (LISEM) balance usability and mechanistic accuracy but face challenges in data-scarce or complex landscapes.
This study applied a hydraulic Overland Flow (OF) model to the Oltrepò Pavese region in north-western Italy, a geologically and hydrologically diverse area influenced by natural processes and human activities. In particular, the model was applied for a rainfall event with a return period of two year in three representative mountain catchments of the region: Scuropasso, Versa, and Ardivestra, characterised by mild to steep slopes, forested areas, rural settlements and vineyards. The OF model, based on the resolution of the Shallow Water Equations (2D-SWEs) calculates hydrodynamic variables such as flow depth and velocity. Erosion-prone areas were identified through literature empirical equations employed by using the OF model output, incorporating shear stress, stream power, and sediment transport capacity. To validate the OF model, the results were compared to those generated by the RUSLE. The comparative analysis was conducted to assess spatial overlap in erosion-prone areas between the two models. To ensure consistency, minimum erosion thresholds were applied to exclude areas non-relevant to erosion, such as water bodies, rocky areas, infrastructures, and forested zones which showed negligible erosion. The thresholds optimized the alignment of erosion-prone area estimations between the two models, revealing a significant degree of overlap and demonstrating the reliability of the OF model in determine prone-erosion areas. In addition, despite uncertainties in empirical formulations, the hydraulic OF model provided prone-erosion areas by using less input information than RUSLE. This study highlights the potential of integrating hydrodynamic modelling and empirical approaches to improve soil erosion assessments. Future advancements in model dynamics, land-use representation, and climate impact analysis are essential for addressing soil conservation challenges in diverse landscapes.
Acknowledgement: This study is part of the project NODES which has received funding from the Italian Ministry of University and Research (MUR) – M4C2 1.5 of PNRR funded by the European Union - NextGenerationEU (Grant agreement no. ECS00000036).
How to cite: Ravazzolo, D., Persi, E., Fenocchi, A., Petaccia, G., Costabile, P., Costanzo, C., Ennouini, W., and Sibilla, S.: Assessment of soil erosion areas using a process-based overland flow modelling approach, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5910, https://doi.org/10.5194/egusphere-egu25-5910, 2025.
