Integrating Climate and Geographic Information Systems (GIS) Modelling as Key Factors in Determining Cultivar Suitability and Adaption to a Specific Environment


Project Number
AS DVO 06

Project Title
Integrating climate and geographic information systems (GIS) modelling as key factors in determining cultivar suitability and adaption to a specific environment

Project Leader
Strever, A E

Institution
Stellenbosch University. Department of Viticulture and Oenology

Team Members
Mehmel, T O
Hunter, J J
Zorer, R
Neteler, M
Bonnardot, V M F
Volschenk, N

Completion date
2016

Project Description
In the context of climate change, factors such as seasonal variability and limitations of available water resources, have increased pressures on the production of table wines, and could continue to do so without effective adaptive strategies.
The classification of the climate in the Western Cape as well as long term and in-season monitoring are complicated due to the difficulties in accessing climate data, quality of the data is not assured, and limitations due to the sparse spatial distribution of currently logging weather stations. Reliable climate data can be costly, and currently requires intensive data validation; hence the study aimed to find an alternative resource to quantify the climate over the spatial extent of the Western Cape, for possible semi-real time applications. Temperature is one of the main climatic variables driving grapevine response; hence this study validated the use of freely available remote sensing land surface temperature images – a collection of daily maximum and minimum temperature layers. The aims of the study were to quantify climate change and seasonal variability in the Western Cape with the best station network possible within the limits of the spatial and temporal resolution availability.
The study included extreme climatic conditions by selecting sites over a climatic band, and multiple factor analysis was used to evaluate the interaction of climate with grapevine phenology, growth, ripening and wine attributes. This was done to highlight the possible driving factors that can be used in future climatic modelling. Methodology was also put in place to acquire remote sensing layers and relate the data to existing climate data and other site data layers.
For the estimation of mean weather station temperature, the results from the PhD study can be considered promising, given the simplicity of the statistical models employed, the robustness of the resampling techniques and the high accuracy achieved under these limitations. The weather station mean temperature can be supplemented/predicted using mean land surface temperatures, with a calibration error of 2.4°C and a prediction error of 2.6°C. The daily mean land surface temperature and weather station temperature data exhibited a strong linear relationship (r = 0.86, p < 0.001, and N = 29), and good prediction accuracy. These land surface temperature maps are intrinsically spatialised, providing daily temperature values that in the past would have only been possible by spatial interpolation of sparse weather station networks, which could only be as accurate as the input data.
Seasonal variability was prominent in the sites studied, driving grapevine response. The variability was seemingly intensified by extreme climate events such as extreme wind, rainfall or higher temperatures earlier in growing season as well as during the ripening period. This confirmed the difficulty to predict seasonal conditions in the context of climate change. Seasonal variability and grapevine responses could better be described with finer scale analysis of the climate profile, considering and accounting for the amount of hours in specific temperature, wind and relative humidity ranges. This was a novel approach, as it allowed analysis of the climate data without preconceived ideas around specified thresholds.
Grapevine phenological stages seemed to be more affected by temperatures outside of the growing season, which highlighted a need for reviewing the current climatic indices used to describe the growing season. Temperatures throughout the year, with the exception of August and September, seemed to affect flowering. The summer months (December, January and February) with more observed hours between 30-35°C and 35-40°C, had a negative correlation with flowering date as days after 1 September (the flowering and vintage precocity indices were earlier). In this study, the date of flowering was most affected by temperature and tended to “set the pace” for phenology in the season. Flowering date as days after budburst could also potentially be used to predict harvest date for Cabernet Sauvignon over sites with an accuracy of only a few days.
The study proved that within a general warming trend, the climate in the Western Cape could be both warming and cooling, depending on the area or months in the context of the long term mean. This emphasises the need for continuous semi-real time climate data, such as the daily land surface temperature layers that can be used as an alternative to supplement weather station networks using a regression model to account for the remote sensing imaging. The acquisition and processing of the land surface temperature layers can be automated and extended to other crops cultivated in South Africa. Some insights were gained to understand cultivating Cabernet Sauvignon in the context of warmer and cooler climatic conditions. Almost every response of the grapevine was affected by climate. It was shown that grapevine growth tempo and final shoot length were sensitive to seasonal variability and water constraints and indirectly affected leaf area per vine that in turn could alter ripening tempo and final wine quality. The seasonal climatic conditions could be masked with more detailed viticultural management practices to ensure a balanced grapevine through the selection of trellis system, pruning and canopy management. In the context of climate change, the aim is to match the cultivar growth and ripening response to the climatic conditions of a site. Finer scale analysis of the climate using hourly frequency data approaches may aid in improving adaptive strategies for the future. This is especially relevant in the context of climate change and the complex terrain of the Western Cape affecting the diurnal shifts of climate over seasons and short distances. The study showed that warm to moderate climatic conditions where grapevines experience moderate water constraints tended to be more balanced in terms of growth and ripening, yielding complex wines with favourable attributes for Cabernet Sauvignon.
Prospective future work would include the integration of climate maps in the context of grapevine modelling along with a spatial view of the seasonal shifts. This could help with improved management and adaptation. This further emphasises the need for within season monitoring of temperature, plant water status as well as other environmental parameters. It can also be further unlocked by remote sensing products, also in the context of water management in the future.
The study provided some foundations for a larger database of climate, land surface temperature and phenology for the identification of cultivar distributions compared to more ideal cultivar distribution in the context of a warmer future with possibly more limited water resources.
Currently projects are linked to the outputs of this study, namely the DST project (DVO9) as well as a pilot study in collaboration with the Centre for Geographical Analysis, Stellenbosch University. Throughout the project some new problems became clear, the accessibility and integrity of climate data, continuation of the project through collaboration with CSIR.
Main summarised conclusions:
· Weather station mean temperature can be supplemented/predicted using mean land surface temperatures (Satellite data), with a calibration error of 2.4°C and a prediction error of 2.6°C. (r = 0.86, p < 0.001, and N = 29)
· These land surface temperature maps are intrinsically spatialised, providing daily temperature values that in the past would have only been possible by spatial interpolation of sparse weather station networks, which could only be as accurate as the input data.
· Seasonal variability was prominent in the sites studied, driving grapevine response. The variability was seemingly intensified by extreme climate events such as extreme wind, rainfall or higher temperatures earlier in growing season as well as during the ripening period. This confirmed the difficulty to predict seasonal conditions in the context of climate change.
· Grapevine phenological stages seemed to be more affected by temperatures outside of the growing season, which highlighted a need for reviewing the current climatic indices used to describe the growing season. Temperatures throughout the year, with the exception of August and September, seemed to affect flowering. The summer months (December, January and February) with more observed hours between 30-35°C and 35-40°C, had a negative correlation with flowering date as days after 1 September (the flowering and vintage precocity indices were earlier). Flowering date was most affected by temperature and tended to “set the pace” for phenology in the season. Flowering date as days after budburst could also potentially be used to predict harvest date for Cabernet Sauvignon over sites with an accuracy of only a few days. The study proved that within a general warming trend, the climate in the Western Cape could be both warming and cooling, depending on the area or months in the context of the longterm mean. This emphasises the need for continuous semi-realtime climate data, such as the daily land surface temperature layers that can be used as an alternative to supplement weather station networks using a regression model to account for the remote sensing imaging.
· The seasonal climatic conditions could be masked with more detailed viticultural management practices to ensure a balanced grapevine through the selection of trellis system, pruning and canopy management. In the context of climate change, the aim is to match the cultivar growth and ripening response to the climatic conditions of a site.
· Finer scale analysis of the climate using hourly frequency data approaches may aid in improving adaptive strategies for the future. This is especially relevant with complex terrain of the Western Cape affecting the diurnal shifts of climate over seasons and short distances.
· Prospective future work includes the integration of climate maps in the context of grapevine modelling along with a spatial view of the seasonal shifts.
· Currently projects are linked to the outputs of this study, namely the DST project (DVO9) as well as a pilot study in collaboration with the Centre for Geographical Analysis, Stellenbosch University. Throughout the project some new problems became clear, the accessibility and integrity of climate data, continuation of the project through collaboration with CSIR.

Publications
Jarmain C., Strever A. and Southey T. 2013. Fruitlook Data Validation Report submitted to the Western Cape provincial Department of Agriculture. Appendix to the report “Fruitlook: An operational service to improve crop water and nitrogen management in grapes and other deciduous fruit trees using satellite technology for the season of 2012-13”. 23 pages.

Jarmain C., Strever A. and Southey T. 2014. FRUITLOOK 2013-14 VALIDATION OF SPATIAL PRODUCTS. Report submitted to the Western Cape Provincial Department of Agriculture,20 March 2014, 6 pages.

Jarmain C., Strever A., Southey T., Venter T. And Kotze C. 2014. Fruitlook 2013-14 Validation report. Final report to the Western Cape Provincial Department of Agriculture. 58 pages.

Southey, TO, 2017. “Integrating climate and satellite remote sensing to assess the reaction of Vitis vinifera L. cv. Cabernet Sauvignon to a changing environment”. Ph.D.Agric., Thesis, Stellenbosch University. (http://scholar.sun.ac.za/handle/10019.1/101124).

Strever, A.E., Jarmain, C., Southey T.O. and Hunter, J.J., 2015. Validating satellite data products for monitoring growth and water status of wine grape vineyards. Wineland, Feb 2015.

Presentations

Southey, T.O. & Strever, A.E., 2014. Summary and comparison of seasonal weather data compared to long term climate data for five selected regions of interest. Vinpro annual meeting, 9 May 2014.

Southey, T.O. & Strever, A.E., 2014. Literature Review: what do we know about Cold units? Vinpro Information day on dormancy and budburst, 28 May 2014.

Goudriaan, C Jarmain, A Strever, N Kapp, T Southey. 2014. “FruitLook: Improving Farming Practices with Satellite Information” (poster). 37th SASEV Conference, Lord Charles, Somerset West.

Mehmel (Southey), T.O., Hunter, J.J., Zorer, R. & Strever, A.E., 2012. Integrating climate and GIS as key factors in the modelling of cultivar suitability to a specific environment. In: Proc. 34th SASEV Conference, 14-16 November, Allee Bleue, Groot Drakenstein.

Moffat, T.F., Hunter, J.J., Zorer, R., Strever, A.E., 2013. Assessment of grape bunch temperature variability in Vitis vinifera L. cv. Shiraz. Proc. 18th Int. Symp. GiESCO, Porto, Portugal, pp. 759 – 764.

Moffat, T.F., Hunter, J.J., Zorer, R., Mehmel, T.O. & Strever, A.E., 2012. Assessment of grape bunch light environment and temperature variability in Vitis vinifera cv. Shiraz. In: Proc. 34th SASEV Conference, 14-16 November, Allee Bleue, Groot Drakenstein.

Neteler, M., Rocchini, D., Zorer, R., Delucchi, L. & Metz, M., 2012. Creating a gap-free time series of daily MODIS Land Surface Temperature maps for viticulture. In: Proc. 34th SASEV Conference, 14-16 November, Allee Bleue, Groot Drakenstein.

Southey, T.O., Hunter, J.J. & Strever, A.E., 2012. Integrating climate and GIS modelling as key factors in determining cultivar suitability and adaption to a specific environment. In: TERROIR IDENTIFICATION AND UTILISATION THEREOF THROUGH ADAPTED VITICULTURE PRACTICES, 35th SASEV Conference, 13-15 November, Lord Charles, Somerset West.

Southey, J.J Hunter, A Strever. 2014. “Influence of short-term climatic patterns on phenological events of Vitis vinifera grapevines”. 37th SASEV Conference, Lord Charles, Somerset West.

Southey, R Zorer, JJ Hunter, A Kunneke, A Strever. 2014. ”Evaluating the integrity of available climate layers using weather station data with focus on grape growing areas of the Western Cape”. 37th SASEV Conference, Lord Charles, Somerset West.

Southey, T. O. & Strever, A. (2017). Integrating climate and satellite remote sensing to assess the reaction of Vitis vinifera L. to a changing environment in the Western Cape, South Africa. Congress presentation of 20th Giesco International conference, 5-10 November 2017, Mendoza, Argentina.

Strever, A.E. & Hunter, J.J., 2013. Canopy age of Vitis vinifera L. cv. Shiraz derived from the modelling of logistic shoot growth and/or plastochron index. Proc. 18th Int. Symp. GiESCO, Porto, Portugal, pp. 608 – 613.

Strever, T Southey, C Jarmain, JJ Hunter., 2014. “Some perspectives on climate change and viticultural sustainability in South African wine regions – will vineyards disappear by 2050?”. 37th SASEV Conference, Lord Charles, Somerset West.

Zorer, R., Rocchini, D., Delucchi, L., Metz, M. & Neteler, M., 2012. Application of daily MODIS Land Surface Temperature data in viticulture. In: Proc. 34th SASEV Conference, 14-16 November, Allee Bleue, Groot Drakenstein.

Zorer, R., Moffat, T., Strever, A.E. & Hunter, J.J., 2013. Hourly simulation of grape bunch light microclimate using hemispherical photography. Proc. 17th Int. Symp. GiESCO, Porto, Portugal, pp. 1031 – 1034.

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