Grapevines are cultivated on 6 out of 7 continents, between latitudes 4° and 51° in the Northern Hemisphere (NH) and between 6° and 45° in the Southern Hemisphere (SH) across a large diversity of climates (Tonietto and Carbonneau, 2004). Accordingly, the range and magnitude of environmental factors and the principal environmental constraints differ considerably from region to region. Wine grapes are traditionally grown in geographical regions where the growing season (April–October for the NH) mean temperature is within the range of 12–22°C (Jones, 2006). Warming during the growing season has been observed in all studied wine regions over the past 50–60 years (i.e., Schultz, 2000; Jones et al., 2005a; Webb et al., 2007, 2011; Santos et al., 2012). Observed and predicted changes in temperature have a pronounced effect on the geographical distribution of where grapevines can be grown (Kenny and Harrison, 1992; Jones et al., 2005b; Schultz and Jones, 2010; Santos et al., 2012). Observed advancement in phenological events and specifically maturity have recently also been correlated to a continuous reduction in soil water content as a co-factor to temperature (Webb et al., 2012). Within the existing production areas, water shortage is probably the most dominant environmental constraint (Williams and Matthews, 1990) and even in moderate temperate climates, grapevines often face some degree of drought stress during the growing season (Morlat et al., 1990; van Leeuwen and Seguin, 1994; Gaudillère et al., 2002; Gruber and Schultz, 2005).

Recent projections for the major world grape growing areas using various model approaches driven by 17 global climate models (GCMs) projected substantial reductions in suitable area for Viticulture largely due to changes in water availability related to shifts in precipitation rate and/or distribution, increases in evaporative demand and in many cases reduced access to water for irrigation (Hannah et al., 2013). Most European grape growing areas are non-irrigated and there is a rising concern if this is sustainable in the future. Additionally, many of the most valuable areas in terms of quality and reputation are located on steep slopes which may exacerbate the impact of climate change due to a reduced potential for adaptation (high labor costs, technical challenges, access to water a.s.o). Southern Germany has many examples for these landscapes since wine-growing regions are mainly located in river valleys where Viticulture has been practized on steep slopes for hundreds sometimes several thousand years (Weeber, 1993). Mean annual precipitation (530–750 mm) is generally low in these regions and soil water holding capacity (SWC) is very heterogeneous, with the percentage of vineyards with low SWC being relatively high (example Rheingau region; SWC < 125 mm for nearly 50% of steep slope areas, Löhnertz et al., 2004). Therefore, risk assessment of possible consequences of climate change on soil and plant water budget needs to be on a finer scale and requires a functional plant or vineyard model, respectively, which can be scaled up from vineyard plots to entire regions.

There are several approaches which have been taken previously to model the water budget of vineyards and the use of crop coefficients is the most widely spread (Allen et al., 1998). However, grapevine canopies represent a large array of possible structures (shape, leaf/fruit/stem distribution, density) imbedded in an equally large spectrum of possible vineyard geometries (distances between and within rows) which in conjunction with a variety of management practices and soil properties affect vineyard transpiration and render the use of standard crop coefficients (K_c) difficult (Williams and Ayars, 2005; Fandiño et al., 2012). These difficulties are also reflected in other approaches based on the Shuttleworth and Wallace (1985) model which could separate between vine transpiration and soil evaporation, by applying individual evapotranspiration controlling resistances to plants or the soil and combining one dimensional models of crop transpiration and soil evaporation. This model proved to be very sensitive to the parameterization of the leaf area index (LAI, used to model net energy separation) and canopy resistance, and might be combined with a more detailed model to separate net radiation on plants or soil in order to apply the model to complete growing regions (Ortega-Farias et al., 2007, 2010; Poblete-Echeverría and Ortega-Farias, 2009).

There has been substantial progress in the description of grape canopy structure and its effect on light interception using two-dimensional modeling (Schultz, 1995) and later three-dimensional digitizing technology (Mabrouk et al., 1997; Sinoquet et al., 1998; Louarn et al., 2007) which consequently lead to the development of complex three-dimensional models of plant architecture on an organ scale (Louarn et al., 2008a; López-Lozano et al., 2009; Iandolino et al., 2013). Beside of many applications of functional-structural models of this detail in assessing plant architecture effects on radiative transfer and whole plant gas exchange (Louarn et al., 2008b; López-Lozano et al., 2011; Prieto et al., 2012) they remain difficult to parameterize and have not yet been scaled up to asses for vineyard water use. Lebon et al. (2003) have used a somewhat intermediate approach between simplistic and highly complex to describe the light interception inside of a vineyard in order to separate the evapotranspiration fluxes of grapevines or bare soil and validated the model for different vineyard sites. Celette et al. (2010) extended the model to account for changes in water use by the presence of cover crops. In principle, the model goes back to a geometrical vineyard model of radiation interception and distribution proposed by Riou et al. (1989) with the basic assumption that these are the key drivers of transpiration and evaporation. The model was then extended to include soil water reservoirs (Riou et al., 1994), to account for the feedback of water stress on transpiration (Lebon et al., 2003), to simulate meaningful physiological plant parameters describing the level of water deficit such as predawn water potential (Schultz and Lebon, 2005) and to characterize the radiative balance within important parts of a vineyard canopy such as the fruiting zone (Pieri, 2010a,b). However, the model has never been used to describe radiation interception, and consequently, the water budget in sloped vineyards, where slope and azimuth in conjunction with the degree of latitude have substantial impact on the received solar radiation (Geiger, 1980) and their partitioning on vines or soil, nor has it been coupled to regionalized climate models in order to project changes in vineyard water balance possibly brought about by climate change under these situations.

We therefore had several key objectives:

The revised and amended model to simulate vineyard water balance is an example for a “sandwich” approach to couple a canopy-based plant water relations model to soil characteristics and climate projections in order to provide a risk assessment for different vineyard sites. The adaptation of the radiation module using a Monte Carlo numerical simulation overcame one of the shortcomings of the original approach of Riou et al. (1989) to treat all horizontal faces of the canopy as opaque which overestimated radiation interception and thus water consumption especially in closely spaced vineyards (Lebon et al., 2003; Figure 4). With this adaptation a new and improved estimation of canopy porosity, p(x), was introduced and experimentally verified which made porosity dependent on the distance a solar beam travels inside of the canopy. This however, will still need adaptation to different canopy forms where leaf area density may be lower than in the VSP systems used in the vineyards of this study, and where thus beam attenuation may follow a different pattern (Poni et al., 1996). Additionally, under prolonged and severe water deficit, leaf drop will increase p(x), and thus reduce transpiration. Nevertheless, sensitivity analyses of previous model versions showed, that a 10% change in p(x) only decreased water loss by 1.6% (Trambouze and Voltz, 2001).

At the current state the model does not include stomatal responses to elevated CO₂ concentrations, which would be important for a more precise impact estimation of future climates on vineyard water relations (Yin, 2013). A general survey of the response of stomatal aperture to an increase to 560 μmol mol⁻¹ in CO₂-concentration (from 380 μmol mol⁻¹, Ainsworth and Rogers, 2007) across a variety of plant species showed an approximate reduction of about 20%. Experiments on grapevines have confirmed this value (Schultz and Stoll, 2010) but a reduction in stomatal conductance and possibly the threshold value of FTSW to water deficit do not consider possible changes in VPD due to climate change. Recent results from models including the physiological impact of CO₂ on plants (i.e., reduced stomatal conductance) suggest that rising CO₂ will increase the temperature driven water evaporation from oceans resulting in increased absolute water vapor content of the air. However, the decrease in evapotranspiration over land (because stomatal conductance is decreasing) would still lead to an overall decrease in relative humidity and an increased evaporative demand (Boucher et al., 2009).

Since many vineyard areas in Europe are on slopes with shallow soils more prone to water deficit, the model was adapted to account for the changed radiation budget of sloped vineyards with its consequences on vineyard water relations. A recent study on possible effects of climate change on regional vineyard water budgets did not include inclined surfaces and assumed bare soils (Pieri and Lebon, 2014) which is sufficient for a rough estimate but does not account for large intra-regional variations.

One of the further goals is a scale-up approach to estimate the water budget of entire wine regions based on existing maps of soil water content (i.e., Löhnertz et al., 2004). So far mostly meteorological approaches have been used in studies of climate change effects on Viticulture, where changes in regional water budgets have been either predicted based on extremely rough soil water data with very low spatial resolution (i.e., Malheiro et al., 2010 based on Tonietto and Carbonneau, 2004), used fixed SWC values (Pieri, 2012; Pieri and Lebon, 2014) for all regions, or based their estimations on sub models creating water stress indices which have never been proved to be applicable to vineyard situations (Hannah et al., 2013 based on Alcamo et al., 2003 and Pfister et al., 2009).

We tried to validate the calculated water fluxes through vine canopies by direct measurements of sap flow. However, the model only correlated with sap flow data when a grapevine transpiration coefficient k_c,v of 0.56 was introduced. Only then was the seasonal dynamic of FTSW accurately simulated. In all previous cases where the original (Lebon et al., 2003) and adapted versions of the model (i.e., Pellegrino et al., 2005; Celette et al., 2010) were compared to measured soil water content (not sap flow), the correlations were excellent without a transpiration coefficient, whether the soil was bare (Lebon et al., 2003; Pellegrino et al., 2005) or had different degrees and/or different types of cover crops (Celette et al., 2010). Explanations for these differences might be that Lebon et al. (2003) used a very low value for the REW in their bare soil sub model, possibly indicating an underestimation of bare soil evaporation compensated by an overestimation of grapevine transpiration and Pellegrino et al. (2005) as well as Celette et al. (2010) did their field trials in vineyards with wide row spacings (>2.30 m), where the overall fraction of grapevine transpiration on total evapotranspiration is comparably small (Figure 6). Additionally, as compared to Mediterranean type climates (Pellegrino et al., 2005; Celette et al., 2010) vineyard cover crops in temperate, summer rainfall areas have a larger contribution to whole vineyard evapotranspiration due to less frequent water deficits (Uliarte et al., 2013).

Partitioning of water fluxes between soil, cover crop and grapevines showed that different components dominated during different parts of the season and that soil management had a large impact on flux partitioning. Simulated evaporation levels from soil and transpiration from cover crops were in agreement with direct measurements conducted in the same area (Uliarte et al., 2013) and agreed with those by Celette et al. (2010) for a vineyard with a permanent intercrop and the same row distance when water was not limiting. The rapid decline of bare soil evaporation within a few days after precipitation events simulated by the model was also observed by Uliarte et al. (2013) under similar weather conditions.

The low values in sap flow were surprising but are roughly in line with previous measurements on the same variety (Schmid, 1997). The technique used to measure sap flow was first adopted for grapevines by Braun and Schmid (1999b) and was validated by independent methods at the time (i.e., weighing of large pots). One important restriction of that method, as with any sap flow estimation, is that severe pruning wounds at the trunk can cause large inhomogeneities of the water flux density over the cross sectional area of the trunk (Braun and Schmid, 1999a). This could lead to an overestimation of sap flow if the heating probe is within areas of high flux densities and to an underestimation if the heating probe is located near or in necrotic areas (Schmid, 1997). Since the likelihood of uneven flux density increases with vine age, this may have been part of the reason for the larger confidence intervals of sap flow data for BU and WI, the two older vineyards.

One of the advantages of the formulation of potential grapevine transpiration T_0,v in form of Equation (1) is, that different radiation distributions caused by differences in vineyard geometries and vine training systems are considered and, therefore, ratios for T_a,v/T_0,v can be directly compared to values from the literature where sap flow has also been estimated. Riou et al. (1994) and Trambouze and Voltz (2001) found ratios which would have been equivalent to k_c,v values of 1.25 and 1.12 for a typical vineyard in Bordeaux and 18-year old Shiraz vines in Southern France, respectively. In both cases, the stem heat balance method was used to measure T_a,v as described by Valancogne and Nasr (1993). However, Braun and Schmid (1999a) reported that the heat balance system might overestimate actual sap flow by 50–100% at high flow rates in older grapevines. Using heat pulse sensors, Yunusa et al. (2004) found a ratio of T_a/ET₀ of 0.17 for non-stressed drip irrigated Sultana vines in Australia. Considering the fractions of shortwave radiation intercepted by the vine canopy for two periods during the growing season in their study resulted in k_c,v values of 0.38 and 0.46 which are in the range of our findings. Nevertheless, with the same technique Intrigliolo et al. (2009) found a ratio of T_a/ET₀ of 0.49 and a k_c,v of 1.6 for 2-year old Riesling vines when sap flow readings were recalibrated with canopy gas exchange measurements (which roughly doubled the calculated transpiration rates). Since sap flow values were similar for all experimental sites under conditions without water deficit in our study and clearly responded to deficit situations, they reflected actual vine responses despite uncertainties with respect to their absolute quantitative accuracy.

One additional aspect of these discrepancies is the large spectrum of stomatal sensitivity to alterations of environmental variables between cultivars and cultivar/rootstock combinations for grapevines (Schultz, 2003; Soar et al., 2006; Williams and Baeza, 2007; Poni et al., 2009; Collins et al., 2010). It is therefore unlikely that a universally valid k_c,v exists. Even though k_c,v values were similar for the three sites in this study, there were notable differences in the response of T_a,v/T_0,v to increasing evaporative demand (Figure 8). Although only periods were considered where a priori soil water was not limiting (FTSW > 0.4), the reduction in T_a,v/T_0,v with increasing ET₀ for the two drier vineyard sites might have been a response to vapor pressure deficit, VPD. High VPD in the atmosphere can cause a decline in stomatal conductance in grapevines to control water loss (Soar et al., 2006; Poni et al., 2009; Rogiers et al., 2011) and soil water deficit can exacerbate this response (Soar et al., 2006; Pou et al., 2008; Rogiers et al., 2011; Zhang et al., 2012). Whether this reaction is driven by some factors residing close to the stomatal pores (Peak and Mott, 2011) or depends on hormonal (Soar et al., 2006; Rogiers et al., 2011) or hydraulic long distance signaling (Christmann et al., 2013) inducing stomatal closure is unknown. However, since the driest sites experienced the strongest reduction in the transpiration to evapotranspiration ratio with increasing evaporative demand, it is likely that some form of root-to-shoot signaling was involved. This may have been related to parts of the grapevine root system being located in dry soil, due to inhomogeneous distribution of soil water which has been shown to induce stomatal closure and modulate the response to VPD (Poni et al., 2009). Both hormonal and hydraulic limitations have been incorporated into a conceptual water consumption model responsive to VPD (Tardieu and Simonneau, 1998) but it seems difficult to fit this into the current framework of the grapevine model although approaches relating the VPD response to soil water content parameters similar to the FTSW concept may make this possible (Oren et al., 1999; Rogiers et al., 2011). Since ET₀ increases substantially with the degree of slope (Table 5), it is necessary to incorporate these aspects into a more widely applicable model in the future in order to evaluate the propensity of drought risk on a regional scale.

Lebon et al. (2003) also discussed the roles of interception water and surface run-off as possible sources for errors. Run-off is usually negligible for soils with cover crops and small individual precipitation rates, which are dominant in the experimental area (Emde, 1992). To account for the direct interception of water the approach to introduce a skin layer in the bare soil model of Allen (2011) from which water evaporates after precipitation events was applied but that generated only small reductions in soil water content, could not be resolved by the accuracy of the soil water data and was limited to situations where rain fell on dry soils.

As a further adaptation to our climatic conditions, growing stages were introduced to describe the development of the cover crops during the year (Allen et al., 1998). The approach of Celette et al. (2010) to model cover crop development by changes in LAI, was not suitable for our conditions, because the model approach they used (Cros et al., 2003; Duru et al., 2009) did not take into account the destroying impact of frost in cold winters. Calculations assuming that the cover crops are active throughout the year, led to substantial overestimations of vineyard transpiration rates in spring (data not shown).

Additional errors might be introduced by subsurface lateral water flows, because the model does consider vertical flows only. By the occurrence of relief precipitation the variability of rainfall distribution is generally high in regions with slopes. For instance, only a few kilometers north of the Rheingau grape growing region toward the Taunus mountain range the mean annual rainfall is about 250 mm higher. Some but not all soil water access tubes showed an increase of soil water content at certain times in particular layers, which might have been the result of water moving laterally downslope. However, this only occurred during the replenishment stage in winter or spring but not during summer and it cannot be distinguished between vertical or lateral water movements. Also, the increase was restricted to distinct layers and after saturation of the layer the lateral water flow is likely to be through flow. Therefore, the overall error is assumed to be small, but might be an explanation of the underestimation of soil water content by the model for WI in spring.

FTSW is strongly correlated with ψ_pd (Lebon et al., 2003; Pellegrino et al., 2004; Schultz and Lebon, 2005) which could also be confirmed in the present study (data not shown). This correlation allows the calculation of a water deficit indicator under any environmental situation for scenarios of future climate projections. The approach is appealing since it can serve in several ways to use the model as a tool in climate change research. First, ψ_pd can not only be related to physiological processes such as photosynthesis and stomatal conductance but also to the synthesis of grape compositional factors such as anthocyanins and tannins (i.e., Ojeda et al., 2001, 2002). Second, with databases of soil properties, water storage capacities, and rooting depths, available for certain wine regions (Löhnertz et al., 2004), it would be possible to estimate vineyard soil water balance on a regional scale for the next decades. Third, such a model could then be used to identify adaptation possibilities, such as changes in canopy or vineyard characteristics (van Leeuwen et al., 2010), varieties (Schultz and Stoll, 2010) or to recommend/not recommend the installation of irrigation systems (Gaudin and Gary, 2012).

Whereas the dynamic climate models proposed a moderate increase in the number of drought days for all vineyard sites (Figure 12), the statistical model WETTREG2010 projected a much larger effect. This is probably due to the fact, that WETTREG2010 not only projects an increase in temperature and a decrease in precipitation rate, but also a strong increase in global radiation (Kreienkamp, CEC-Potsdam, personal communication) leading to more frequent hot and dry weather conditions during the second half of the century. Nevertheless, the dynamic models CLM and REMO have been shown to be sensitive to the “windward- lee effect,” i.e., an under– or overestimation of precipitation at mountain ranges demonstrated for the South of Germany, thus may have actually underestimated the number of drought days for the Rheingau region (Warrach-Sagi et al., 2013). We have observed such a bias in the precipitation grid data both for runs with the ECHAM5/OM and HadCM3 GCMs.

A risk analysis of probable water shortage in the future can only be as good as the regionalized model predictions of individual meteorological parameters driving the “sandwich” or crop models. Specifically with relation to the future development in summer precipitation and its variability, there is considerable disagreement between individual GCM's (Maraun et al., 2010). Recent analyses of the propensity for drought events in different parts of Europe showed, that the historic patterns observed across Europe were related to shifts in the North Atlantic summer storm tracks which so far are largely unpredictable (Dong et al., 2013).

Despite uncertainties in the projected regionalised precipitation rates, the model will contribute to enlarge the value of more statistical attempts to estimate changes in plant phenology and, thus, the dynamics of grapevine development which is important for water use (Bock et al., 2011; Urhausen et al., 2011).

We have coupled a soil water balance model with a numerical simulation approach to simulate the distribution of absorbed radiation in vineyards, also accounting for sparse canopies. Sub models, describing the influence of steep slopes, the use of cover crops, and bare soil cultivation on vineyard evapotranspiration were added or replaced to improve the model and simplify its parameterization with the aim to make the model applicable to complete growing regions. The model was validated against soil water and sap flow measurements over two years in three vineyards. Compared to former model approaches, a grapevine transpiration coefficient had to be introduced to accurately simulate measured grapevine transpiration rates. Soil water dynamics in the rooting profile could be adequately described throughout different seasons with different proportions of water loss through bare soil, cover crops or vines. Model runs with data of different RCMs projected an increase of future drought stress occurrence for all sites but varied largely with respect to the absolute number of expected drought days. Similar analyses are needed on a regional scale to develop adaptation scenarios.