# Future warming increases the chance of success of maize-wheat double cropping in Europe

Yang Su, Ronny Lauerwald, David Makowski, Nicolas Viovy, Nicolas Guilpart, Peng Zhu, Benoit Gabrielle, Philippe Ciais

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Yang Su, Ronny Lauerwald, David Makowski, Nicolas Viovy, Nicolas Guilpart, et al. Future warming increases the chance of success of maize-wheat double cropping in Europe. European Journal of Agronomy, 2025, 170, pp.127723. 10.1016/j.eja.2025.127723. hal-05202940

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# Future warming increases the chance of success of maize-wheat double cropping in Europe

Yang Su<sup>a,b,c,*</sup>, Ronny Lauerwald<sup>c,●</sup>, David Makowski<sup>d</sup>, Nicolas Viovy<sup>b</sup>, Nicolas Guilpart<sup>e,●</sup>, Peng Zhu<sup>b,f</sup>, Benoit Gabrielle<sup>c</sup>, Philippe Ciais<sup>b</sup>

## ARTICLE INFO

### Keywords:

- Double cropping

- Crop rotation

- Crop caloric yield

- Climate change

- Food security

## ABSTRACT

Double cropping can help reduce the risk of food insecurity by harvesting two crops each year instead of one. By increasing the rate of plant development and shortening growing seasons, global warming is likely to favour this type of system in areas where it is not yet being applied. Here we assess the probability of successful implementation of double cropping maize and wheat in Europe under global warming. We compare the caloric productivity of this double cropping system with that of conventional single cropping systems with maize and wheat in rotation, using a hybrid modelling approach combining a process-based model and machine learning. Our results indicate that the decline in caloric productivity of simple maize and wheat cropping systems due to climate change could be offset by the adoption of a double cropping system. By 2100, the area in Europe suitable for successful double cropping is projected to expand by a factor of 3.6, driven by warming under the RCP8.5 scenario. This expansion is expected to significantly boost caloric yield across the continent. In Southern Europe specifically, caloric yield could rise by 29 % compared to single cropping—20 % from maize and 9 % from wheat. These findings provide valuable guidance for policymakers and farmers, positioning double cropping as a strategic solution to safeguard food production while promoting climate adaptation and sustainable agriculture in Europe's changing agroecosystems.

## 1. Introduction

### 1.1. Global perspectives on double cropping systems

Global food demand is projected to rise significantly in the coming decades (Mbow et al., 2022), requiring robust and sustainable agricultural practices to ensure food security. Double cropping, a farming practice where two crops are harvested on the same piece of land in a single year (Calviño and Monzon, 2009; Waha et al., 2020a), is a common and widely used cropland management technique in tropical and subtropical low-land regions (Waha et al., 2020a; Andrade and Satorre, 2015), and it is also being increasingly recognized as an emerging adaptation strategy in Mediterranean regions (Meza et al., 2008). Double cropping has been reported to increase total annual crop yield (Xu

et al., 2021; Elobeid et al., 2019), improve farm profitability and cash flow stability (Calviño and Monzon, 2009), and optimize land use efficiency (Waha et al., 2020b). Additionally, it contributes to crop diversification, prevents soil erosion by maintaining longer periods of soil cover (Snapp et al., 2005), and enhances soil fertility by increasing root biomass inputs (Fronning et al., 2008; Dale et al., 2010). By intensifying land use, it can also help spare land elsewhere for biodiversity conservation or other ecological services (Phalan et al., 2016).

However, studies have pointed out that if not properly managed, double cropping can lead to accelerated depletion of soil nutrients (Ranck et al., 2020; Heggenstaller et al., 2008), especially when the same crops are planted in the same field in the long run. Double cropping also requires more water than growing a single crop per season, which is problematic in areas with limited water resources (Brar et al.,

<footnote><sup>a</sup> CNRS & Département d'Informatique, École Normale Supérieure - PSL, 45 Rue d'Ulm, Paris 75005, France</footnote>

<footnote><sup>b</sup> Laboratoire des Sciences du Climat et de l'Environnement, CEA CNRS UVSQ Orme des Merisiers, Gif-sur-Yvette 91190, France</footnote>

<footnote><sup>c</sup> Université Paris-Saclay, AgroParisTech, INRAE, UMR ECOSYS, Palaiseau 91120, France</footnote>

<footnote><sup>d</sup> Université Paris-Saclay, AgroParisTech, INRAE, Unit Applied Mathematics and Computer Science (MIA 518), Palaiseau 91120, France</footnote>

<footnote><sup>e</sup> Université Paris-Saclay, AgroParisTech, INRAE, UMR Agronomie, Palaiseau 91120, France</footnote>

<footnote><sup>f</sup> Department of Geography, The University of Hong Kong, Hong Kong SAR</footnote>

<footnote>* Corresponding author at: CNRS & Département d'Informatique, École Normale Supérieure - PSL, 45 Rue d'Ulm, Paris 75005, France.
E-mail address: yang.su@ens.fr (Y. Su).</footnote>
2022a). These challenges underscore the need for regionally adapted approaches and careful management when implementing double cropping systems (Yan et al., 2020), particularly in areas with limited water resources or degraded soils.

## 1.2. Status and potential of double cropping in Europe

In Europe, double cropping is currently limited but gaining growing interest as an emerging strategy to enhance food security and climate resilience, particularly in the context of global warming (Estel et al., 2016). In southern Europe, especially Italy and Spain, some farmers have already implemented double cropping systems, typically combining winter cereals such as wheat or barley with summer crops like grain maize, silage maize, or sunflower (Joint Research Centre et al., 2019; Magnolo et al., 2021). However, in much of Europe, this practice remains uncommon, partly due to climatic constraints and economic considerations.

At present, European double cropping systems are generally designed with the first crop for human consumption, while the second crop is primarily used for livestock feed or bioenergy production (Magnolo et al., 2021; Schmidt et al., 2023). Even so, studies have shown that such systems can already provide yield stability (Schmidt et al., 2023) and generate additional economic returns from the second crop (Zabala et al., 2023). Nevertheless, its broader role in enhancing food security relative to single cropping systems warrants further research.

Furthermore, with ongoing climate change expected to shorten crop growing cycles and expand the potential growing window (Porter, 2005; Zhao et al., 2017; Zhang et al., 2023), there is a need to evaluate the feasibility of implementing double cropping systems in various regions throughout Europe, taking into account the climatic suitability under future conditions.

# 2. Materials and methods

To address these knowledge gaps, here we estimated the feasibility of double cropping with two major crops - maize and wheat - across Europe under current (2009–2020) and future (2089–2100) climate conditions and compared the caloric yield under double cropping with maize and wheat in rotation versus single cropping with maize and wheat in rotation, a common rotation practice in Europe. Feasibility was defined as the probability of successful implementation, calculated as the number of years where both crops could be harvested within a year divided by the total number of simulated years (ten years). Given the complexity of simulating diverse agronomic and climatic contexts, we applied a hybrid modeling approach combining a process-based crop model with machine learning for enhanced prediction accuracy. The cropping schemes are illustrated in Supplementary Figure 1.

## 2.1. Datasets description

### 2.1.1. Phenology data

We extracted maize and wheat phenological stages—latitude, longitude, planting date, flowering date, harvest date—from the Deutscher Wetterdienst (DWD) dataset for Germany (CDC, 2020) and the Pan European Phenology database (PEP725) (PEP725, 2023). Data were filtered using a rainfed-dominant crop mask (Supplementary Figure 2). To correct for sampling imbalance, we randomly selected 10 % of German records (Singh, 2003) and combined them with other countries’ records (Supplementary Figure 3a). The combined phenology dataset spans from 1930 to the present, with the majority of records concentrated after the 1980s.

### 2.1.2. Yield data

For information on maize and wheat yield, we extracted the latitude, longitude, planting year, and crop yield from a global dataset (Iizumi

and Sakai, 2020), which estimated the historical grid-cell yield using the satellite-derived crop-specific vegetation index (Zhu et al., 2013) and FAO-reported country annual yield statistics (FAO, 2019). Yield data were also filtered using a rainfed-dominant crop mask (Supplementary Figure 2). Supplementary figure 3b showed how we split the dataset into sub-datasets for ORCHIDEE calibration, ORCHIDEE correction and Final testing.

We observed a historical upward trend (Iizumi and Sakai, 2020) in maize and wheat yield from 1983 to 2016 (Supplementary figure 4), that could be attribute to the technical progress, including the improved crop cultivars (Taube et al., 2020; Khush, 2001) combined with the application of improved agronomic practices (Khush, 2001). To assess the possible effects of a continuing trend of yield increase from agronomic innovations in the future, we developed two scenarios: one that accounts for the yield trend and one that excludes it.

## 2.2. Model framework

We used the ORCHIDEE-CROP (Wu et al., 2016; Müller et al., 2019, 2017; IPSL, 2023; Wang et al., 2017; Yin et al., 2020; Fu et al., 2023), a version of ORCHIDEE land surface model (IPSL, 2023) which incorporates basic modules from the STICS crop model (INRAE, 2023; Brisson et al., 2003, 2009). Both models are extensively used in climate and agricultural research. Supplementary figure 5 (Wu et al., 2016) illustrates how ORCHIDEE and STICS models are coupled together. The crop development module from STICS (Brisson et al., 2009) is incorporated into the STOMATE module within the ORCHIDEE framework (Krinner et al., 2005). The ORCHIDEE-CROP model was initially calibrated based on a large crop phenology dataset in Germany (CDC, 2020), to ensure its accuracy in simulating the growth stages of maize and wheat under varying soil and climate conditions. This involved the fine-tuning of model parameters related to crop growth to better align the maize and wheat growth dynamics with the observed phenological patterns in diverse agricultural environments. While ORCHIDEE-CROP effectively represents the fundamental growth processes, the model was not designed to capture the growth of different crop cultivars under different forms of managements. Therefore, to enhance its effectiveness across distinct European countries, where crop cultivars and practices differ (ILKER et al., 2018), we integrated phenology data from multiple European countries (CDC, 2020; PEP725, 2023) and employed machine learning models to refine the predictions of crop phenological stages. The machine learning models used here are reinforced random forest models (RRF) (Zhang et al., 2019), which combine random forest models with generalized linear models and give a good overall accuracy. These models are able to capture the spatial and climatic patterns of different cultivars and farming practices, enhancing the predictions of phenological stages over direct ORCHIDEE-CROP application across Europe. After the calibration of crop phenology, we performed calibration of crop yield using a reference crop yield dataset (Iizumi and Sakai, 2020) in regions where rainfed crop dominants (Portmann et al., 2010) (Supplementary figure 2). RRF was used here as well to take into account the variability in cultivars and management practices across Europe.

Further details on the calibration procedures and tests of the hybrid models for crop phenology and yield are provided in the supplementary materials under the “Model Details” section and illustrated in Supplementary figure 6–11.

## 2.3. Simulation design

We tested two cropping schemes across European regions where maize and wheat are both cultivated (Portmann et al., 2010; Su et al., 2021):

* Double Cropping (Maize–wheat):
* For initialize the simulation experiment, maize was planted based on the crop calendars of Sacks et al. (2010).

* Wheat was planted 14 days after maize harvest if the maize harvesting day is earlier than Julian day 335 (Dec 1). If not, the field remained fallow for winter.

* After wheat harvest, maize was planted again after 14 days.

* If double cropping was not feasible (maize harvested too late), wheat was not planted, and maize was resown the next year (Supplementary Figure 1a–b).

* **Single Cropping (Maize-wheat in rotation):**

* A maize-wheat rotation was simulated: maize grown in year one, followed by wheat in year two, with fallow periods in between (Supplementary Figure 1c).

After each round of crop growth, the predictions from ORCHIDEE-CROP were refined by the corresponding machine learning models. The refined predictions were then prescribed in ORCHIDEE-CROP, which was subsequently re-run from the same initial point to ensure that the simulations remained consistent with the predictions of the machine learning models. Finally, all the related parameters, including the soil moisture, soil nutrients, climatic variables, etc. were passed to simulation for the next crop. Note that when there was no crop planted on the field, we set the field as bare soil. The spatial resolution of the simulation was 1° latitude × 1° longitude.

### 2.3.1. Climate forcing and scenarios

* Historical (2009–2020) and future (2089–2100) climate conditions were driven by the RCP8.5 scenario from the IPSL-CM5A-LR model (IPSL, 2024).

* Sensitivity tests included RCP2.6 and RCP6.0, and additional GCMs: HadGEM2 (UK Meteorological Office, 2024), GFDL-ESM2M (National Oceanic and Atmospheric Administration, 2024), and MIROC5 (ISIMIP, 2024) (see Figs. 1–2, Supplementary figure 13–15).

All GCM data were bias-corrected using the delta change method (Navarro-Racines et al., 2020; Hawkins et al., 2013) against CRU JRA historical reanalysis data (Harris, 2021, 2023; KOBAYASHI et al., 2015; Harris et al., 2020).

### 2.3.2. Regional aggregation

Results were aggregated by UN geoscheme into Western, Eastern, Southern, and Northern Europe (United Nations Statistics Division,

1999) (Supplementary figure 16). Northern Europe was restricted to regions where maize and wheat are both cultivated (Portmann et al., 2010; Su et al., 2021), and it only includes the UK, Ireland and a few areas in Denmark and Lithuania.

## 3. Results

### 3.1. Model performance

The performances of our hybrid models for maize and wheat phenology (harvest date) and yield are presented in Supplementary figure 7. The performance of the models was assessed by R-squared (R²), root mean squared error (RMSE) and relative error ($RE = \frac{RMSE}{\text{observed mean}}$).

The R² values for maize and wheat harvest dates are 0.20 and 0.58, and the RMSE values of maize and wheat harvest dates are 12 days and 9 days, respectively, with a relatively low relative error of 4% for both crops. This is especially noteworthy as our model is designed to estimate harvest dates across a broad range of cultivars, planting days, climate, and soil conditions throughout Europe. As for the yield models, without accounting for the yield increasing trend, the R² and RMSE values for maize yield were 0.78 and 1.7 t ha⁻¹ yr⁻¹ (RE = 24%), respectively, while those for wheat yield were 0.87 and 0.8 t ha⁻¹ yr⁻¹ (RE = 17%), respectively. When taking into account the yield increasing trend, the R² value and RMSE for maize yield were 0.91 and 1.0 t ha⁻¹ yr⁻¹ (RE = 15%), respectively. While for wheat, these criteria were 0.93 and 0.6 t ha⁻¹ yr⁻¹ (RE = 12%), respectively.

We evaluated the model's accuracy across different European countries. We compared our predicted harvesting day with the observed data in the datasets (CDC, 2020; PEP725, 2023), and found no significant spatial error patterns across countries for the harvesting day of maize (-8% to +3%, Supplementary figure 8) and wheat (-3% to +3%, Supplementary figure 9), indicating the capability of our hybrid modeling approach to effectively capture spatial phenology patterns and account for variations in cultivars and farming practices. When comparing the predicted rainfed maize yield with the FAOSTAT data (FAO, 2019) in 2009, we show that the error is within ± 20% across most of Europe, while in Spain and Greece, we observed larger errors (from -30% to -50%, Supplementary figure 8). This is mainly due to the high prevalence of maize irrigation in those countries as shown in Supplementary figure 2, while our predictions were produced for rainfed crops. This discrepancy between the rainfed and irrigated maize yield are in line with the trends revealed in previous study (Wang et al., 2021). The rainfed wheat yield predictions did not exhibit clear spatial

<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Probability of successful implementation of double cropping of maize and wheat in Europe under rainfed condition. Plot a is based on the climate conditions over the period 2009–2020. Plot b is based on the climate conditions over the period 2089–2100 simulated by the Ipsl-cm5a-lr climate model and RCP 8.5 scenario. The reddish color indicates that there is less chance of successful implementation of double cropping, while the bluish color indicates that there is higher chance of successful implementation of double cropping. Plot c is the accumulated number of grid cells with the probability of successful implementation of double cropping systems higher than the value indicated on the x-axis. The black line is the probability under current condition (2009–2020), the red, green, and blue line represents the future condition under RCP 2.6, RCP 6.0, and RCP 8.5 scenarios, respectively. The highest value on y-axis represents the total number of grid cells in which both maize and wheat are currently being cultivated (Sacks et al., 2010). The probability of successful implementation of double cropping equals the number of years of successful double cropping divided by the maximum allowable double cropping years (ten years) during the period of simulation, which are expressed as fractions without specific units.</figcaption></figure>
<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Annual caloric yield difference of double cropping under RCP 6.0/ RCP 8.5 scenarios versus RCP 2.6 scenario under future climate. Plot a represents the annual caloric yield difference of double cropping under RCP 6.0 versus RCP 2.6 scenario. Plot b represents the annual caloric yield difference of double cropping under RCP 8.5 versus RCP 2.6 scenario. All results are from the yield model without considering the yield increasing trend. The bluish color indicates that the annual caloric yield from RCP 6.0 or RCP 8.5 is higher, while the reddish color indicates that the annual caloric yield from RCP 6.0 or RCP 8.5 is lower compared to RCP 2.6 scenario. The units are in kcal/ha.</figcaption></figure>

error patterns across Europe (from -20-20 %, Supplementary figure 11) when comparing with the wheat yield data from FAOSTAT dataset (FAO, 2019) in 2020, further affirming the effectiveness of our models in considering the effects of regional differences in cultivars and farming practices.

Our hybrid models showed improved performance compared to the traditional STICS model, particularly in predicting maize and wheat yields. The root mean square error (RMSE) of STICS was 2.4 t ha⁻¹ and 1.6 t ha⁻¹ (Brisson et al., 2002), while our hybrid models achieved lower RMSE values for both crops (1.0–1.7 t ha⁻¹ for maize, and 0.6–0.8 t ha⁻¹ for wheat, Supplementary figure 4). When compared to other crop models such as WOFOST (ref (Cheng et al., 2016; Zhuo et al., 2023).) and APSIM (ref (Zhou et al., 2022; Kumar et al., 2023).), our hybrid modeling approach also appears to achieve similar or higher R² values with regard to reproducing observed maize and wheat yields. Our modeling strategy may thus be of interest for the global community of researchers in agronomy beyond the scope of our study's objectives.

## 3.2. Sensitivity tests

The sensitivity of our simulations was tested against different general circulation models (GCMs), including IPSL-CM5A-LR (IPSL, 2024), HadGEM2 (UK Meteorological Office, 2024), GFDL-ESM2M (National Oceanic and Atmospheric Administration, 2024), MIROC5 (ISIMIP, 2024) (Supplementary figure 15). We re-run the future scenarios based on the corresponding climatic data from each GCM. The analysis indicated that the results from the IPSL-CM5A-LR and HadGEM2 models, developed in France and the UK respectively, were quite similar. In contrast, the GFDL-ESM2M and MIROC5 models, from the US and Japan, suggested a lower likelihood of successful double cropping in regions outside Southern Europe. The variation in results could be attributed to different GCMs modelled certain processes and feedback differently (IPCC, 2024). For this study, we will focus exclusively on the results obtained from the IPSL-CM5A-LR model.

## 3.3. Double cropping in Europe under current and future scenarios

Our analysis shows that under current rainfed or limited water conditions, it is already possible to successfully implement double cropping with maize and wheat (where maize and wheat are harvested the same year) in most of Southern Europe, with a probability of up to 60 % (this implies a six-year successful double cropping within the ten-

year timeframe we considered). While in other parts of Europe, it is currently unlikely to implement double cropping (Fig. 1a). Interestingly, our results show that, at the end of the 21st century, the area where a double cropping system could be applied will expand 3.6 times under the high-warming scenario RCP8.5 compared to current level (Fig. 1c). Under this scenario, there is a chance up to 40 % successfully implementing double cropping in both Western and Eastern Europe (Fig. 1b).

In order to assess the sensitivity of our results to different levels of warming, we ran additional simulations of double cropping under the strong mitigation scenario RCP 2.6, and the intermediate scenario RCP 6.0. We show that the potential area where a double cropping system could be implemented in Europe will expand 1.2 and 1.6 times under RCP 2.6 and RCP 6.0 scenarios, respectively (Fig. 1c). Until the end of 21st century, regions with a chance of at least 40 % of successfully implementing double cropping will expand to the eastern part of Southern Europe under both RCP 2.6 and RCP 6.0 scenarios (Supplementary figure 13a, b), and to the southern part of Western and Eastern Europe under RCP 6.0 (Supplementary figure 13b).

We calculated the caloric yield under different levels of warming (Supplementary figure 14) and compared the annual caloric yield, averaged over 2089–2100, between RCP 6.0, RCP 8.5 and RCP 2.6 (Fig. 2). We showed that the annual caloric yield decreased with the increase warming intensity (considering climate and CO₂ concentration transitioning from RCP 2.6 to RCP 6.0 or RCP 8.5) in most of the regions where the probability of successful implementation of double cropping remains similar under all RCP scenarios (Fig. 2). On the other hand, the annual caloric yield increased in the regions where the probability of successful implementation of double cropping increased (Figs. 1, 2, Supplementary figure 13), which suggests that an increase of the probability of successfully implementing double cropping could compensate for the caloric yield loss induced by the warming effect.

## 3.4. Double cropping system versus single cropping system under current and future scenarios

To estimate how the probability of successful implementation of double cropping could affect the productive performance of double cropping systems compared with single cropping system, we ran the simulation on these two systems in Europe under both current and future (RCP 8.5 scenario) climate conditions. We show that during the years when double cropping is successfully implemented (i.e., both wheat and maize are harvested the same year), the median annual caloric yield of
the double cropping system is 67–128 % higher than the single cropping system (maize or wheat is harvested each year) under RCP8.5 (2089–2100) (Fig. 3a). We found that the individual caloric yields of maize and wheat under double cropping tend to be lower than the caloric yields under single cropping (by –5 % to –20 % for maize, Supplementary figure 17c, and close to zero for wheat, Supplementary figure 17d), but these caloric yield losses are compensated by the double harvest, leading to an overall caloric yield gain when the caloric yields of maize and wheat are added together. Thus, when double cropping can be successfully implemented, the increase in median caloric yield achieved through double cropping is between 127 % and 487 % compared to single wheat harvest (Supplementary figure 17b), but it is comparatively lower compared to single maize harvest (–5 % to +69 % higher caloric yields in double cropping, Supplementary figure 17a). While during the years when double cropping cannot be successfully implemented (when the second season crop cannot be harvested due to a too long growing cycle, see 2.3 and Supplementary figure 1b for the detail definition), the median annual caloric yield of double cropping is up to 15 % lower than single cropping (Fig. 3b). Over all the years (with both success and failure of double cropping), the overall caloric yield gain resulting from double cropping is + 11 to + 32 % when the probability of successful implementation of double cropping reaches 20 %, and this gain becomes stronger when the probability of success increases (Fig. 3c). In contrast, the single cropping system only provides a higher caloric yield when the probability of successful implementation of double cropping remains lower than 20 % (Fig. 3c).

The gains induced by double cropping are contrasted between geographical regions. Our simulation results show that the highest caloric yield levels are expected to occur in Western Europe for both single cropping and double cropping systems under both current and future climates (Supplementary figure 18). In this region, single cropping tends to outperform double cropping by 5.8 % on average under current conditions, while the double cropping system tends to outperform the single cropping system in Southern Europe (with an overall increase of 15.5 %, 13.0 % for maize and 2.5 % for wheat) (Fig. 4a). Due to climate change, the annual caloric yield in single cropping will decrease across most of Europe in the future compared with the current level, with decreases reaching 6.5 % and 9.5 % in Southern Europe and Western Europe, respectively (Fig. 4b), which is consistent with a previous study (Carozzi et al., 2022), similar pattern is also observed for double cropping systems in areas where the probability of successful implementation remains unchanged (Supplementary figure 19). In the future, double cropping could outperform single cropping, especially in Southern Europe, with an increase of 29.0 % on annual caloric yield in this region (Fig. 4d). Notably, some regions in Western and Southern Europe may achieve even greater gains, with localized caloric yield improvements reaching 35–40 % (Fig. 4d). A large-scale

implementation of double systems could thus compensate for the caloric yield decrease in single cropping due to climate change in most of Europe except the northern part of Western Europe (Fig. 4b-d).

### 3.5. Effects of technical progress

When assuming a continuous yield increasing trend in the future from technical progress (Supplementary figure 4), the relative difference of caloric yield between double cropping and single cropping is similar to the value obtained without considering any yield increasing trend (Supplementary figure 20a, b, Fig. 4a, d), which indicates that the relative effects of double cropping compared to single cropping are insensitive to the assumption we made on future yield trends from the technical progress. When assuming a yield increasing trend, we show that the annual caloric yield in the future increased a lot for both single cropping (1.3–1.8 times) and double cropping (1.32–1.81 times) systems compared with the yield without considering the yield increasing trend (Supplementary figure 18, Supplementary figure 21, Supplementary figure 22), which suggests that technical progress could compensate for the negative impact of climate change on caloric yield.

We demonstrated that our main conclusions were insensitive to the assumed long-term yield trend. Nevertheless, our results confirm that the yield of individual crops would decrease in the future (in both single and double cropping systems) in many regions of Europe (Webber et al., 2018; Peichl et al., 2019), except for Northern Europe (Zydelis et al., 2021) (Figs. 2, 4b) unless new genetic or management improvements are made (Supplementary figure 22). Our results suggest that the caloric yield could double across the whole Europe if the yield increasing trend continues like in the last 40 years (Food and Agriculture Organization of the United Nations, 2022) (Supplementary figure 4, Supplementary figure 18, Supplementary figure 20, Supplementary figure 22), which could compensate for the caloric yield decrease due to climate change (Hampf et al., 2020). Therefore, our findings emphasize the importance of ongoing investments in developing new cultivars and management practices, particularly with the enhanced tolerance to heat and drought (Zhang et al., 2023; Taube et al., 2020; Tigchelaar et al., 2018).

## 4. Discussion

### 4.1. The potential of double cropping in a warming Europe

Our analysis reveals a clear latitudinal progression in double cropping suitability under climate change. Under current conditions (Fig. 1), viable maize-wheat double cropping is largely confined to southern Europe. While climate warming will significantly expand this geographic suitability northward to around 55°N, where thermal constraints currently limit adoption. The projected northward expansion

<figure><img src="image_5.png" /><figcaption>**Fig. 3.** Comparison of rainfed caloric yield of double cropping (DC) versus single cropping (SC) under future climate conditions (RCP 8.5) at different success probabilities of double cropping. Plot a: $\Delta$yield (DC vs. SC) in years where DC is successfully implemented. Plot b: $\Delta$yield (DC vs. SC) in years where DC fails. Plot c: $\Delta$yield (DC vs. SC) averaged over all years (2089–2100). The $\Delta$yield = (Yield$_{DC}$ – Yield$_{SC}$) / Yield$_{SC}$.</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>**Fig. 4.** Analysis of the rainfed caloric yield of double cropping (DC) and single cropping (SC) systems in Europe under current (2009–2020) and future climates (RCP 8.5, 2089–2100). Plot a: Relative caloric yield of DC (maize-wheat) vs. SC (maize-wheat in rotation) under current climate, including distributions of grid-cell yield differences and crop-specific (maize/wheat) contributions. Plot b: Relative yield of SC under future vs. current climate. Plot c: Relative yield of DC under future climate vs. SC under current climate. Plot d: Relative yield of DC vs. SC under future climate. All $\Delta$yield calculations compare system or climate-scenario yields (e.g., $\Delta$yield = (Yield1 - Yield2)/Yield2). The bar plot in the second-row shows the number of grid cells as a function of different relative difference of caloric yield. The bar plot in the third-row details the maize/wheat contributions.</figcaption></figure>

could increase annual caloric yield by 30–40 % in newly suitable regions like France (Fig. 4d), helping offset climate-driven caloric yield declines in traditional single cropping systems (Fig. 4b). These findings align with studies demonstrating double cropping’s potential as a climate adaptation strategy (Zhang et al., 2023; Hampf et al., 2020; Kawasaki, 2019; Liang et al., 2023), while providing the first comprehensive assessment specific to European conditions.

This study underscores the potential of double cropping as a crucial adaptation strategy to mitigate the adverse effects of climate change on food security in Europe. Our findings demonstrate that double cropping systems can enhance caloric yield despite rising temperature and offset the expected declines in single cropping systems under climate change. This research provides crucial insights for policymakers and farmers, suggesting that double cropping can be a sustainable and resilient agricultural practice to secure food supply in a warming climate.

## 4.2. Enhancing the feasibility and addressing the challenges of double cropping in Europe

To expand the viability of double cropping systems across Europe, integrated measures addressing agronomic, environmental, and socio-economic barriers are critical. Breeding and adopting fast-maturing, drought-tolerant crop varieties could help synchronize crop cycles with shortened growing windows under climate change, particularly in northern regions where thermal limitations currently restrict double cropping.

One major environmental challenge for expanding double cropping systems in Europe is the significant rise in water demand. We observe an increasing trend on potential evapotranspiration in double cropping comparing with single cropping system (LEWAN, 1993; Fouli et al., 2012) (Supplementary figure 23), ranging from 20 % to 30 % for most of the Western Europe and 60–70 % for most of the Southern Europe under current climate. These demands are expected to intensify further in the future as the likelihood of successful double cropping increases.

Consequently, the adoption of sustainable water resource management practices is pivotal for the long-term viability of these systems (Brar et al., 2022b). Intensifying cropping frequency inherently leads to greater water consumption, yet this can be mitigated through targeted agronomic strategies. Practices such as conservation agriculture, permanent soil cover, and reduced tillage can help retain soil moisture and reduce runoff (LEWAN, 1993; Morillas et al., 2019; Fernández-Ortega et al., 2023) Irrigation remains a key tool to alleviate water stress and enhance productivity, but its application must be optimized. Precision irrigation technologies (Gupta et al., 2023), such as subsurface drip or sprinkler irrigation, combined with advanced soil moisture monitoring (Singh et al., 2020) are essential to maximize water-use efficiency and avoid overexploitation of local water resources.

Beyond water and crop selection, careful scheduling of crop sequences is vital to maximize the success and productivity of double cropping systems. Adjusting planting and harvesting times with precision ensures that both crops can reach their critical growth stages under optimal climatic conditions. This is especially important under increasingly variable weather patterns. In some cases, when climatic constraints prevent the second crop from reaching full maturity, the resulting biomass can still be harvested as animal fodder—for example, using immature maize for silage. This fallback use provides an additional value stream, improving overall resource-use efficiency and helping to buffer against complete economic loss from crop failure, reducing the economic risks associated with climatic variability.

While double cropping offers potential to enhance land-use efficiency and caloric yield, its feasibility cannot be evaluated solely on yield metrics. A key challenge is that the shortened growth periods inherent to double cropping systems may compromise individual crop caloric yields, particularly if climatic conditions or crop maturity windows are suboptimal. Therefore, greater attention must be given to the overall economic performance of double cropping systems, which ultimately determines their attractiveness and scalability for farmers.

The economic viability of double cropping is influenced by several
interlinked factors, including input costs (e.g., seeds, labor, machinery, fertilizers), irrigation requirements, and local market conditions (Kawasaki, 2019). Moreover, profitability hinges on the choice of crop combinations and cultivars, which must be carefully selected not only for their agronomic compatibility and resilience but also for their market value and local demand. Therefore, regional assessments and further research are needed to compare the returns of double versus single cropping.

To support the adoption of double cropping systems, policymakers could support transitional costs—such as investment in specialized equipment or soil diagnostics—and provide incentives. Farmer-centered initiatives, including regional demonstration farms and peer knowledge networks, can build confidence by sharing economic and risk-reduction benefits of double cropping systems. These practical measures lay the groundwork for broader implementation and serve as an essential foundation for integrating double cropping into Europe's sustainable agricultural transition.

### 4.3. The role of double cropping in Europe's Green Transition

Double cropping holds strategic potential to support the European Green Deal by boosting agricultural productivity without expanding farmland. This approach helps optimize land use, enhance food security, and reduce pressure on natural ecosystems. In contrast to some tropical and subtropical systems where double cropping may involve monoculture (e.g., rice-rice systems) (Liang et al., 2023), long-term reliance on a single crop can degrade biodiversity and soil quality (European Commission - DG ENV, 2010). In Europe, the adoption of crop diversification within double cropping sequences is therefore essential to avoid these pitfalls and promote sustainable intensification.

European agricultural policy, particularly the Common Agricultural Policy (CAP), provides Green Direct Payments that incentivize crop diversification (European Commission, 2023a, 2023b). These mechanisms align with broader EU sustainability goals and support practices that contribute to soil conservation, improved nutrient cycling, and carbon sequestration. Compared with single cropping, double cropping can ensure longer land cover, reduce soil erosion from wind and water, and decrease nitrogen leaching into waterways (Lal, 2017; Li et al., 2021).

Importantly, double cropping is not just a productivity strategy—it also contributes to environmental stewardship. When managed sustainably, it can help reduce deforestation by making better use of existing farmland, preserve biodiversity by supporting varied cropping systems, and free land for ecological restoration. Furthermore, by extending the active growing season, it has the potential to increase biomass accumulation and enhance carbon storage, especially when combining with residue retention (Tang et al., 2024), aligning with the European Commission's Green Transition goals (European Commission, 2024).

Nevertheless, the long-term success of double cropping in this context depends on the adoption of resource-efficient, biodiversity-friendly practices. Careful crop sequencing, diversification (Woźniak, 2019), and sustainable water and nutrient management are indispensable to ensure that intensification does not come at the cost of ecological degradation. As such, double cropping should be viewed not only as a tool for climate adaptation, but as a pillar of Europe's broader agroecological transition.

## 5. Conclusion

This study highlights double cropping as a promising strategy to enhance crop productivity and climate resilience in Europe. While our simulations did not optimize planting dates, doing so could further improve caloric output. Additional gains may be achieved through irrigation, improved crop genotypes, and strategic crop selection based on climate tolerance and market demand. Even in suboptimal years,

harvesting biomass (e.g., silage maize) can provide economic value. By increasing caloric yield without expanding farmland, double cropping offers a practical path toward sustainable intensification and climate adaptation in European agriculture.

### CRediT authorship contribution statement

**Yang Su:** Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Methodology, Investigation, Formal analysis, Data curation, Conceptualization.
**Ronny Lauerwald:** Writing – review & editing, Validation, Supervision, Funding acquisition, Formal analysis, Conceptualization.
**Peng Zhu:** Writing – review & editing, Methodology, Data curation.
**Nicolas Guilpart:** Writing – review & editing, Validation, Supervision, Methodology, Conceptualization.
**Nicolas Viovy:** Writing – review & editing, Supervision, Software, Methodology, Formal analysis, Conceptualization.
**David Makowski:** Writing – review & editing, Validation, Supervision, Project administration, Methodology, Funding acquisition, Formal analysis, Conceptualization.
**Philippe Ciais:** Writing – review & editing, Visualization, Validation, Supervision, Resources, Project administration, Methodology, Investigation, Funding acquisition, Conceptualization.
**Benoit Gabrielle:** Writing – review & editing, Validation, Supervision, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization.

### Code availability statement

All related Fortran (ORCHIDEE-CROP model), R (machine learning model) and MATLAB codes are available online. Link to access ORCHIDEE-CROP model: https://github.com/yangssu/ORCHIDEE-CROP.git, and other R and MARLAB codes: https://doi.org/10.6084/m9 figshare.23736225.

### Declaration of Competing Interest

None declared

### Acknowledgements

This work was supported by the French National Research Agency (ANR) under the "Investissements d'avenir" program with the reference ANR-16-CONV-0003 (CLAND) and by the INRAE meta-program "CLIMAE".

## Appendix A. Supporting information

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.eja.2025.127723.

### Data availability

The data utilized in this study are publicly available at the following DOI: https://doi.org/10.6084/m9 figshare.23736225.

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