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Spring frost is an extreme temperature event that poses a significant threat to winter wheat production and consequently jeopardizes food security. In the context of climate change, the accelerated phenology of winter wheat due to global warming advances the frost-sensitive stage, thereby escalating the risk of spring frost damage. Present techniques for monitoring and assessing frost damage heavily rely on meteorological data, controlled field experiments and crop model simulations, which cannot accurately depict the actual disaster situation for winter wheat. In this study, we propose a novel method that utilizes remote sensing index and statistical data to ascertain the spatial distribution of spring frost damage to winter wheat and evaluate the extent of damage. This method was employed to monitor and assess the spring frost damage event that occurred in Shandong province from 3 to 7 April 2018. The result shows that beginning on 3 April, the daily minimum temperature in western Shandong Province dropped significantly (decreased by 17.93 °C), accompanied by precipitation. The daily minimum temperature reached the lowest on 7 April (−1.48 °C). The growth of winter wheat began to be inhibited on 3 April 2018, and this process persisted until 13 April. Subsequently, the impact of spring frost damage on winter wheat ceased and growth gradually resumed. The affected area of winter wheat spanned 545,000 mu with an accuracy rate of 89.72%. Severely afflicted areas are mainly located in the cities of Jining, Zaozhuang, Dezhou, Heze, Liaocheng, Jinan and Tai'an in western Shandong province, and the yield reduction rates were 5.27~12.02%. Our monitoring results were consistent with the distribution of county-level winter wheat yield in 2018 in Shandong province, the daily minimum temperature distribution during spring frost and severely afflicted areas reported by the news. This method proves effective in delineating the spatial distribution of agricultural disasters and monitoring the extent of disaster damage. Furthermore, it can provide reliable information of disaster area and geospatial location for the agricultural department, thereby aiding in disaster damage assessment and post-disaster replanting. [ABSTRACT FROM AUTHOR]

Climate change impacts crop productivity as atmospheric conditions and water supply change, particularly in intensive cropping areas. This study used the validated AquaCrop Model, which was run with downscaled daily climate data produced by SDSM and CanESM2. The changes in the potential grain yield of winter wheat and summer maize and water budget during the cropping seasons were estimated for the Huang-Huai-Hai Plain (3H Plain) under RCP4.5 and RCP8.5 scenarios. The results show that the potential yield of winter wheat is increasing with similar spatial patterns in the 2030s, 2050s, and 2080s, with much of the increase is distributed in Shandong and northeastern parts of Henan. During the winter wheat growth period, the water budget deficit will likely improve from −210 mm in the 2030s to −202 mm in 2080s under RCP4.5 and from −206 mm in the 2030s to −191 mm in 2080s under RCP8.5 across the 3H Plain. The water budget during the winter wheat period will continue to be in deficit in the north 3H Plain and improvements are estimated mostly in the lower southern areas of the Plain. The summer maize potential yield is estimated to increase from the baseline period, but yields will decrease by 0.81%, 1.19%, and 2.10% in the 2030s, 2050s, and 2080s, respectively, under RCP8.5 compared to RCP4.5. During the summer maize growth period, the water budget is also estimated to improve from 109 mm in 2030s to 126 mm in 2080s under RCP4.5 and 107 mm in the 2030s to 163 mm in 2080s under RCP8.5. This increase is mainly estimated in the central and south of the 3H Plain. The estimated ET c of winter wheat shows no significant decrease, while the reduction of 6 mm and 13 mm for summer maize is observed under RCP4.5 and RCP8.5, respectively. The study provides scientific evidence to devise adaptation and mitigation climate change strategies for agricultural productivity and water resource management. • The potential winter wheat yield will increase under RCP4.5 and RCP8.5 scenarios. • The increase in wheat yield follows a similar spatial pattern under both RCP scenarios. • The potential summer maize yield will decrease under RCP8.5 as compared to RCP4.5. • Water deficit for wheat will remain similar to the present with increased temperature. • Water budget during summer will significantly improve in the latter half of this century. [ABSTRACT FROM AUTHOR]

Crop simulation models play an essential role in evaluating irrigation management strategies for improving agricultural water use in crop production. In this study, the AquaCrop model was used to calibrate and validate the grain yield and biomass of 11 cultivars (9 winter wheat and 2 summer maize) under full and water-saving irrigation practices. The model results were verified with the available data from the published literature. Under the full irrigation practice, widely used by farmers in the region for winter wheat, the Normalized Root Mean Square Error (NRMSE) was found to be between 2.00–9.90% for grain yield, 2.40–10.85% for biomass, and 0.42–19.61% for water productivity. Under water-saving irrigation for winter wheat, the NRMSE range was found to be between 5.80–16.00% for grain yield, 3.70–17.30% for biomass, and 3.80–13.79% for water productivity. For summer maize, the NRMSE was 5.95%, 6.08%, and 16.41% under full irrigation, and 9.51%, 8.41%, and 3.60% under water-saving irrigation for grain yield, biomass, and water productivity, respectively. For winter wheat and summer maize, the simulation accuracy of grain yield was high under full irrigation, with percent deviations under ± 11.00%. In this study, the simulation accuracy for winter wheat was low under water-saving irrigation, while the model simulated the yield and biomass for summer maize to acceptable accuracy. The model can be reliably used as a tool to simulate grain yield and biomass across the NCP region for winter wheat and summer maize. However, the limitations of the model must be considered when simulating winter wheat under water-stressed conditions. • AquaCrop is a crop growth model to simulate yield response to water. • The model simulation accuracy was high under full irrigation for wheat and maize. • For water-saving irrigation, model accuracy was high for maize compared to wheat. • The model can be reliably used as a tool to simulate yield and biomass across NCP. [ABSTRACT FROM AUTHOR]