Search Results (8)

In the coming decades, crop production in regions such as the Mediterranean Basin is expected to be influenced by climate change. This study evaluates the impacts of climate change on maize yield and irrigation water in Northern Greece for the mid-21st century and late 21st century using CropSyst, a cropping systems simulation model. Data from a two-year field experiment with maize, in 2016 and 2017, were used to calibrate and validate CropSyst. RCP4.5 and RCP8.5 climate change scenarios were employed, derived from three Regional Climate Models (RCMs), for two future periods (2030–2050 and 2080–2100) and the baseline period (1980–2000). The RCMs used in this study were derived from the Rossby Centre regional atmospheric model (RCA4), which downscaled three General Circulation Models (GCMs), CNRM-CM5, CM5A-MR, and HadGEM2-ES, as part of the Coordinated Regional Climate Downscaling Experiment (EURO-CORDEX) for the European domain. Results indicate that changes in climate variables will exert potential pressure on full irrigation water requirements, leading to both increases and decreases in irrigation amounts, with varying magnitudes of change. Yield impacts vary depending on the climate change scenario and climate model, with CropSyst predictions indicating both positive and negative effects on maize yield under full irrigation. The combined effects of increased temperatures, reduced precipitation, and elevated CO₂ concentrations under the high-emission scenario RCP8.5 by the late 21st century resulted in substantial declines in maize yields. The study identifies the key factor influencing maize yield in future periods as the combined changes in climate variables under CO₂ concentration enrichment, which lead to alterations in full irrigation water requirements, highlighting the multiparameter nature of impact assessment on agricultural production in Northern Greece under various future climate scenarios. Full article

Modeling approaches have emerged to address uncertainties arising from N₂O emissions variability, representing a powerful methodology to investigate the two emitting processes (i.e., nitrification and denitrification) and to represent the interconnected dynamics among soil, atmosphere, and crops. This work offers an extensive overview of the widely used models simulating N₂O under different cropping systems and management practices. We selected process-based models, prioritizing those with well-documented algorithms found in recently published scientific articles or having published source codes. We reviewed and compared the algorithms employed to simulate N₂O emissions, adopting a unified symbol system. The selected models (APSIM, ARMOSA, CERES-EGC, CROPSYST, CoupModel, DAYCENT, DNDC, DSSAT, EPIC, SPACSYS, and STICS) were categorized by the approaches used to model nitrification and denitrification processes, discriminating between implicit or explicit consideration of the microbial pool and according to the formalization of the main environmental drivers of these processes (soil nitrogen concentration, temperature, moisture, and acidity). Models’ setting and performance assessments were also discussed. From the appraisal of these approaches, it emerged that soil chemical–physical properties and weather conditions are the main drivers of N cycling and the consequent gaseous emissions. Full article

Due to the sensitivity of kiwifruit to soil water and nutrient availability, kiwi production is often associated with over-watering and over-fertilization, especially with nitrogen (N), resulting in increased environmental risks. Crop models are powerful tools for simulating crop production and environmental impact of given management practices. In this study, the CropSyst model was applied to estimate soil N budget and environmental effects of kiwi production, with particular regard to N losses, in two grower-managed kiwi orchards in northern Greece, involving two seasons and different management practices. Management options included N fertilization and irrigation. Model estimates were compared with yield and soil mineral N content (0–90 cm depths) measured three times within the growing season. Agri-environmental indicators were calculated based on the N budget simulation results to assess the environmental consequences (focusing on N losses and water use efficiency) of the different management practices in kiwi production. According to model simulation results, kiwifruit yield and N uptake were similar in both orchards. N losses to the environment, however, were estimated on average to be 10.3% higher in the orchard with the higher inputs of irrigation water and N fertilizer. The orchard with the lower inputs showed better water and N use efficiency. N leaching losses were estimated to be higher than 70% of total available soil N in both study sites, indicating potential impact on groundwater quality. These findings demonstrate the necessity for improved irrigation and N fertilization management in kiwi production in the area. Full article

Irrigated durum wheat is a staple food crop that occupies important areas in Tunisia. However, its performance remains weak, with an average national yield of no more than 3.6 tons ha⁻¹ and low profitability. Overall, on-farm wheat production will need to increase considerably to meet future demand and ensure minimum profitability for farmers. To this end, this study aims to identify the main levers for improving durum wheat crop performance. For this purpose, we have developed a regional bio-economic model by linking a biophysical model (CROPSYST) with an economic optimization model (MORBIT). CROPSYST was used to establish a database with a view to determining the relationships between farming practices, durum wheat yields, and water productivity within a context of high climate variability. The database was then integrated into a MORBIT model that analyzed the effects of farming practices on durum wheat performance and regional profits. Three scenarios related to irrigation control and the increase in durum wheat prices were developed. The results showed that reconciling irrigation practices with economic policies is the best alternative to improve durum wheat performance and increase profits at a regional level. Full article

Future changes in crop evapotranspiration (ETc) are of interest to water management stakeholders. However, long-term projections are complex and merit further investigation due to uncertainties in climate data, differential responses of crops to climate and elevated atmospheric CO₂, and adaptive agricultural management. We conducted factor-control simulation experiments using the process-based CropSyst model and investigated the contribution of each of these factors. Five major irrigated crops in the Columbia Basin Project area of the USA Pacific Northwest were selected as a case study and fifteen general circulation models (GCM) under two representative concentration pathways (RCP) were used as the climate forcing. Results indicated a wide range in ETc change, depending on the time frame, crop type, planting dates, and CO₂ assumptions. Under the 2090s RCP8.5 scenario, ETc changes were crop-specific: +14.3% (alfalfa), +8.1% (potato), −5.1% (dry bean), −8.1% (corn), and −12.5% (spring wheat). Future elevated CO₂ concentrations decreased ETc for all crops while earlier planting increased ETc for all crops except spring wheat. Changes in reference ET (ETo) only partially explains changes in ETc because crop responses are an important modulating factor; therefore, caution must be exercised in interpreting ETo changes as a proxy for ETc changes. Full article

In recent years, there has been an urgent need for local strategies to ensure food sustainability in Tunisia, recognized as a climate change hotspot region. In this context, adaptation measures, including the adoption of high-yielding durum wheat cultivars with adequate agronomical practices, are an important avenue to improving the productivity of the smallholders that represent 80% of Tunisian farmers. Thus, this study highlights the impact of (i) the adoption of the recently marketed durum wheat cultivar ‘Salim’ as compared to the common cultivar ‘Karim’ and the transfer of a technical package to 11 farmers in the Nebeur delegation/Kef-Tunisia (semi-arid region) during the 2013/2014 and 2014/2015 cropping seasons, and (ii) climate change on the expected mean grain yield and biomass by 2070, using the CropSyst agronomic cultivation model based on multi-year crop simulations run with a daily weather series (2020–2070). The adoption of ‘Salim’ with the recommended package, compared to ‘Karim’ with the farmer practices, significantly increased the grain yield (37.84%) and biomass (55.43%). Otherwise, the impact of the 0.8 °C temperature rise on the potential yields and biomass over the next 51 years was positive. Contrary to expectations, the yield increases for the two cultivars were very close, but the yield of ‘Salim’ (36.02 q ha⁻¹) remains much higher than that of ‘Karim’ (23.34 q ha⁻¹). On other hand, ‘Salim’ experienced a higher increase for biomass compared to that of ‘Karim’. These results indicate that the adoption of the ‘Salim’ cultivar with its technical package might be considered as a strategy of adaptation to Nebeur conditions and to future climate change events. Full article

In many areas of the world, water shortages prevail and threaten food production. Deficit irrigation was commonly investigated in dry areas as a precious and sustainable production approach. Using the CropSyst model to simulate the effects of different deficit irrigation treatments could help draw conclusions and save time, effort, and money. Therefore, the aims of this research were (i) to calibrate and validate the CropSyst model for wheat under different sustained and phenological stage-based deficit irrigation treatments, (ii) to simulate the impacts of the latter treatments on limiting wheat yield reduction. Two field experiments were conducted in Nubaria (Egypt), representing an arid environment. They included seven irrigation treatments: (1) 100%, (2) 75%, or (3) 50% of crop evapotranspiration (ETc) during the whole crop cycle; (4) 50% ETc at tillering only, or (5) at booting only, or (6) at grain filling only, or (7) at both tillering and grain filling, with the replenishment of 100% ETc to the treatments (4) to (7) in the remaining phenological stages. The results revealed that phenological stage-based deficit irrigation of wheat resulted in lower yield reduction compared to sustained deficit irrigation treatments, with a 6% yield reduction when 50% ETc was applied at the booting stage. Wheat yield loss was reduced to 4 or 6% when 95 or 90% of ETc were applied, respectively. The CropSyst model accurately simulated wheat grain and total dry matter under deficit irrigation with low RMSE value. In conclusion, the CropSyst model can be reliably used for evaluating the strategy of planned deficit irrigation management in terms of wheat production under the arid environment. Full article

This study compares the performance of the five widely used crop growth models (CGMs): World Food Studies (WOFOST), Coalition for Environmentally Responsible Economies (CERES)-Wheat, AquaCrop, cropping systems simulation model (CropSyst), and the semi-empiric light use efficiency approach (LUE) for the prediction of winter wheat biomass on the Durable Environmental Multidisciplinary Monitoring Information Network (DEMMIN) test site, Germany. The study focuses on the use of remote sensing (RS) data, acquired in 2015, in CGMs, as they offer spatial information on the actual conditions of the vegetation. Along with this, the study investigates the data fusion of Landsat (30 m) and Moderate Resolution Imaging Spectroradiometer (MODIS) (500 m) data using the spatial and temporal reflectance adaptive reflectance fusion model (STARFM) fusion algorithm. These synthetic RS data offer a 30-m spatial and one-day temporal resolution. The dataset therefore provides the necessary information to run CGMs and it is possible to examine the fine-scale spatial and temporal changes in crop phenology for specific fields, or sub sections of them, and to monitor crop growth daily, considering the impact of daily climate variability. The analysis includes a detailed comparison of the simulated and measured crop biomass. The modelled crop biomass using synthetic RS data is compared to the model outputs using the original MODIS time series as well. On comparison with the MODIS product, the study finds the performance of CGMs more reliable, precise, and significant with synthetic time series. Using synthetic RS data, the models AquaCrop and LUE, in contrast to other models, simulate the winter wheat biomass best, with an output of high R² (>0.82), low RMSE (<600 g/m²) and significant p-value (<0.05) during the study period. However, inputting MODIS data makes the models underperform, with low R² (<0.68) and high RMSE (>600 g/m²). The study shows that the models requiring fewer input parameters (AquaCrop and LUE) to simulate crop biomass are highly applicable and precise. At the same time, they are easier to implement than models, which need more input parameters (WOFOST and CERES-Wheat). Full article