Terroir 2020 banner
IVES 9 IVES Conference Series 9 Methodology of climate modelling using land surface temperature downscaling: case study case of Gironde (France)

Methodology of climate modelling using land surface temperature downscaling: case study case of Gironde (France)

Abstract

Aim: Climate modelling in viticulture introduced new challenges such as high spatio-temporal monitoring and the use of dependable time series and robustness modelling methods. Land surface temperature (LST) is widely used and particularly MODIS thermal satellite images due to their high temporal resolution (four images per day). However, this data is not completely adapted to regional scale with its medium spatial resolution (1-km). Downscaling methods can improve spatial resolution using machine learning algorithms implementing multiple predictors as topographical variables and vegetation indices. In the last decades, classical bioclimatic temperature-based indices showed a specific spatial distribution depending on topographical variables and at once a significantly non-correlation with vegetation growing trend.  

Methods and Results: In the current study, an assessment of SVM Machine learning method was used to downscaling daily LST using topographical variables and vegetation indices as predictors at multiple spatial resolution. The aims of this study were to (1) evaluate daily LST time series through 2012-2018 period, (2) assess the impact of topographical variables and evolution of vegetation indices during vegetative season and (3) calculation of bioclimatic indices on the wine-growing area of the Gironde The dataset included: 1) daily time series of MODIS LST at 1-km (MOD11A1 and MYD11A1) and 2) topographical variables derived from Digital Elevation Model at 500 m (GMTED10). The first step was the pre-processing and reconstruction of time series. The second step was the downscaling of LST using SVM with topographical variables as predictors. For each day, a model was calibrated and validated to predict daily LST at finer spatial scale. The third step was the calculation of bioclimatic indices (Winkler and Huglin). The methodology was applied for the fourth LST MODIS products acquired at different times. For example, for the 2012 wine growing season Huglin index and Winkler index were calculated with the daily predicted LST (without vegetation indices as predictors but only topographical variables) on the Gironde area and have a globally similar spatial structure. The lowest values (≈ 1900°C for Huglin and 1340°C for Winkler) are concentrated on the coastline to the west and south of the Gironde. The highest index values (> 2000°C for Huglin and > 1700°C for Winkler) are located from the centre of the Gironde to the north-east. These warmer sectors are concentrated in the valley bottoms of the Dordogne and Gironde with higher values in the south of Libourne. LST predictions should be downscaled for the whole period (2012-2019) and the second experiment of the downscaling method includes vegetation indices as predictors.

Conclusion: 

The advantage of LST is their temporal and spatial covers in all the areas. However, data availability and bias must be taken into account and minimized. 

Significance and Impact of the Study:  At the scale of Gironde region, this downscaling method has been tested for the first time with MODIS Land Surface Temperature derived from thermal satellite images in a wine-growing context.

DOI:

Publication date: March 17, 2021

Issue: Terroir 2020

Type: Video

Authors

Gwenaël Morin1*, Renan Le Roux2, Pierre-Gilles Lemasle1 and Hervé Quénol1

1LETG-Rennes, UMR 6554 CNRS – Université Rennes 2, Place du Recteur Henri Le Moal, Rennes – France 
2CIRAD, Forêts et Sociétés, F-34398 Montpellier, France

Contact the author

Keywords

Climate modelling, topographical downscaling, thermal satellite imagery, bioclimatic indices, Gironde

Tags

IVES Conference Series | Terroir 2020

Citation

Related articles…

Modelling vine water stress during a critical period and potential yield reduction rate in European wine regions: a retrospective analysis

Most European vineyards are managed under rainfed conditions, where seasonal water deficit has become increasingly important. The flowering-veraison phenophase represents an important period for vine response to water stress, which is seldomly thoroughly evaluated. Therefore, we aim to quantify the flowering-veraison water stress levels using Crop Water Stress Indicator (CWSI) over 1986–2015 for important European wine regions, and to assess the respective potential Yield Lose Rate (YLR). Additionally, we also investigate whether an advanced flowering-veraison phase may help alleviating the water stress with improved yield. A process-based grapevine model STICS is employed, which has been extensively calibrated for flowering and veraison stages using observed data at 38 locations with 10 different grapevine varieties. Subsequently, the model is being implemented at the regional level, considering site-specific calibration results and gridded climate and soil datasets. The findings suggest wine regions with stronger flowering-veraison CWSI tend to have higher potential YLR. However, contrasting patterns are found between wine regions in France-Germany-Luxembourg and Italy-Portugal-Spain. The former tends to have slight-to-moderate drought conditions (CWSI<0.5) and a negligible-to-moderate YLR (<30%), whereas the latter possesses severe-to-extreme CWSI (>0.5) and substantial YLR (>40%). Wine regions prone to a high drought risk (CWSI>0.75) are also identified, which are concentrated in southern Mediterranean Europe. An advanced flowering-veraison phase may have benefited from cooler temperatures and a higher fraction of spring precipitation in wine regions of Italy-Portugal-Spain, resulting in alleviated CWSI and moderate reductions of YLR. For those of France-Germany-Luxembourg, this can have reduced flowering-veraison precipitation, but prevalent alleviations of YLR are also found, possibly because of shifted phase towards a cooler growing season with reduced evaporative demands. Overall, such a retrospective analysis might provide new insights towards better management of seasonal water deficit for conventionally vulnerable Mediterranean wine regions, but also for relatively cooler and wetter Central European regions.

An analytical framework to site-specifically study climate influence on grapevine involving the functional and Bayesian exploration of farm data time series synchronized using an eGDD thermal index

Climate influence on grapevine physiology is prevalent and this influence is only expected to increase with climate change. Although governed by a general determinism, climate influence on grapevine physiology may present variations according to the terroir. In addition, these site-specific differences are likely to be enhanced when climate influence is studied using farm data. Indeed, farm data integrate additional sources of variation such as a varying representativity of the conditions actually experienced in the field. Nevertheless, there is a real challenge in valuing farm data to enable grape growers to understand their own terroir and consequently adapt their practices to the local conditions. In such a context, this article proposes a framework to site-specifically study climate influence on grapevine physiology using farm data. It focuses on improving the analysis of time series of weather data. The analytical framework includes the synchronization of time series using site-specific thermal indices computed with an original method called Extended Growing Degree Days (eGDD). Synchronized time series are then analyzed using a Bayesian functional Linear regression with Sparse Steps functions (BLiSS) in order to detect site-specific periods of strong climate influence on yield development. The article focuses on temperature and rain influence on grape yield development as a case study. It uses data from three commercial vineyards respectively situated in the Bordeaux region (France), California (USA) and Israel. For all vineyards, common periods of climate influence on yield development were found. They corresponded to already known periods, for example around veraison of the year before harvest. However, the periods differed in their precise timing (e.g. before, around or after veraison), duration and correlation direction with yield. Other periods were found for only one or two vineyards and/or were not referred to in literature, for example during the winter before harvest.

Underpinning terroir with data: rethinking the zoning paradigm

Agriculture, natural resource management and the production and sale of products such as wine are increasingly data-driven activities. Thus, the use of remote and proximal crop and soil sensors to aid management decisions is becoming commonplace and ‘Agtech’ is proliferating commercially; mapping, underpinned by geographical information systems and complex methods of spatial analysis, is widely used. Likewise, the chemical and sensory analysis of wines draws on multivariate statistics; the efficient winery intake of grapes, subsequent production of wines and their delivery to markets relies on logistics; whilst the sales and marketing of wines is increasingly driven by artificial intelligence linked to the recorded purchasing behaviour of consumers. In brief, there is data everywhere!

Opinions will vary on whether these developments are a good thing. Those concerned with the ‘mystique’ of wine, or the historical aspects of terroir and its preservation, may find them confronting. In contrast, they offer an opportunity to those interested in the biophysical elements of terroir, and efforts aimed at better understanding how these impact on vineyard performance and the sensory attributes of resultant wines. At the previous Terroir Congress, we demonstrated the potential of analytical methods used at the within-vineyard scale in the development of Precision Viticulture, in contributing to a quantitative understanding of regional terroir. For this conference, we take this approach forward with examples from contrasting locations in both the northern and southern hemispheres. We show how, by focussing on the vineyards within winegrowing regions, as opposed to all of the land within those regions, we might move towards a more robust terroir zoning than one derived from a mixture of history, thematic mapping, heuristics and the whims of marketers. Aside from providing improved understanding by underpinning terroir with data, such methods should also promote improved management of the entire wine value chain.

Influence of weather and climatic conditions on the viticultural production in Croatia

The research includes an analysis of the impact of weather conditions on phenological development of the vine and grape quality, through monitoring of four experimental cultivars (Chardonnay, Graševina, Merlot and Plavac mali) over two production years. In each experimental vineyard, which were evenly distributed throughout the regions of Slavonia and The Croatian Danube, Croatian Uplands,

Differential responses of red and white grape cultivars trained to a single trellis system – the VSP

Commercial grape production relies on training grapevine cultivars onto a variety of trellis systems. Training allows for well-lit leaves and clusters, maximizing fruit quality in addition to facilitating cultivation, harvesting, and diseases control. Although grapevines can be trained onto an infinite variety of trellis systems, most red and white cultivars are trained to the standard VSP (Vertical Shoot Positioning) system. However, red and white cultivars respond differently to VSP in fruit composition and growth characteristics, which are yet to be fully understood. Therefore, the objective of this study was to examine the influence of the VSP trellis system on fruit composition of three red, Cabernet Sauvignon, Merlot and Syrah, and three white, Chardonnay, Riesling, and Gewurztraminer cultivars grown under uniform growing conditions in the same vineyard. All cultivars were monitored for maturity and harvested at their physiologically maximum possible sugar concentration to compare various fruit quality attributes such as Brix, pH, TA, malic and tartaric acids, glucose and fructose, potassium, YAN, and phenolic compounds including total anthocyanins, anthocyanin profile, and tannins. A distinct pattern in fruit composition was observed in each cultivar. In regards to growth characteristics, Syrah grew vigorously with the highest cluster weight. Although all cultivars developed pyriform seeds, the seed size and weight varied among all cultivars. Also varied were mesocarp cell viability, brush morphology, and cane structure. This knowledge of the canopy architectural characteristics assessed by the widely employed fruit compositional attributes and growth characteristics will aid the growers in better management of the vines in varied situations.