Accurate estimation of regional winter wheat yields is essential for understanding the food production status and ensuring national food security.  However, using the existing remote sensing-based crop yield models to accurately reproduce the inter-annual and spatial variations in winter wheat yields remains challenging due to the limited ability to acquire irrigation information in water-limited regions.  Thus, we proposed a new approach to approximating irrigations of winter wheat over the North China Plain (NCP), where irrigation occurs extensively during the winter wheat growing season.  This approach used irrigation pattern parameters (IPPs) to define the irrigation frequency and timing.  Then, they were incorporated into a newly-developed process-based and remote sensing-driven crop yield model for winter wheat (PRYM–Wheat), to improve the regional estimates of winter wheat over the NCP.  The IPPs were determined using statistical yield data of reference years (2010–2015) over the NCP.  Our findings showed that PRYM–Wheat with the optimal IPPs could improve the regional estimate of winter wheat yield, with an increase and decrease in the correlation coefficient (R) and root mean square error (RMSE) of 0.15 (about 37%) and 0.90 t ha^–1 (about 41%), respectively.  The data in validation years (2001–2009 and 2016–2019) were used to validate PRYM–Wheat.  In addition, our findings also showed R (RMSE) of 0.80 (0.62 t ha^–1) on a site level, 0.61 (0.91 t ha^–1) for Hebei Province on a county level, 0.73 (0.97 t ha^–1) for Henan Province on a county level, and 0.55 (0.75 t ha^–1) for Shandong Province on a city level.  Overall, PRYM–Wheat can offer a stable and robust approach to estimating regional winter wheat yield across multiple years, providing a scientific basis for ensuring regional food security.

Understanding the spatial distribution of the crop yield gap (YG) is essential for improving crop yields.  Recent studies have typically focused on the site scale, which may lead to considerable uncertainties when scaled to the regional scale.  To mitigate this issue, this study used a process-based and remote sensing driven crop yield model for winter wheat (PRYM-Wheat), which was derived from the boreal ecosystem productivity simulator (BEPS), to simulate the YG of winter wheat in the North China Plain from 2015 to 2019.  Yield validation based on statistical yield data revealed good performance of the PRYM-Wheat Model in simulating winter wheat actual yield (Ya).  The distribution of Ya across the North China Plain showed great heterogeneity, decreasing from southeast to northwest.  The remote sensing-estimated results show that the average YG of the study area was 6 400.6 kg ha^–1.  The YG of Jiangsu Province was the largest, at 7 307.4 kg ha^–1, while the YG of Anhui Province was the smallest, at 5 842.1 kg ha^–1.  An analysis of the responses of YG to environmental factors showed no obvious correlation between YG and precipitation, but there was a weak negative correlation between YG and accumulated temperature.  In addition, the YG was positively correlated with elevation.  In general, studying the specific features of the YG can provide directions for increasing crop yields in the future

Cropland productivity has been significantly impacted by soil acidification resulted from nitrogen (N) fertilization, especially as a result of excess ammoniacal N input. With decades’ intensive agricultural cultivation and heavy chemical N input in the Huang-Huai-Hai Plain, the impact extent of induced proton input on soil pH in the long term was not yet clear. In this study, acidification rates of different soil layers in the soil profile (0–120 cm) were calculated by pH buffer capacity (pHBC) and net input of protons due to chemical N incorporation. Topsoil (0–20 cm) pH changes of a long-term fertilization field (from 1989) were determined to validate the predicted values. The results showed that the acid and alkali buffer capacities varied significantly in the soil profile, averaged 692 and 39.8 mmolc kg–1 pH–1, respectively. A significant (P<0.05) correlation was found between pHBC and the content of calcium carbonate. Based on the commonly used application rate of urea (500 kg N ha–1 yr–1), the induced proton input in this region was predicted to be 16.1 kmol ha–1 yr–1, and nitrification and plant uptake of nitrate were the most important mechanisms for proton producing and consuming, respectively. The acidification rate of topsoil (0–20 cm) was estimated to be 0.01 unit pH yr–1 at the assumed N fertilization level. From 1989 to 2009, topsoil pH (0–20 cm) of the long-term fertilization field decreased from 8.65 to 8.50 for the PK (phosphorus, 150 kg P2O5 ha–1 yr–1; potassium, 300 kg K2O ha–1 yr–1; without N fertilization), and 8.30 for NPK (nitrogen, 300 kg N ha–1 yr–1; phosphorus, 150 kg P2O5 ha–1 yr–1; potassium, 300 kg K2O ha–1 yr–1), respectively. Therefore, the apparent soil acidification rate induced by N fertilization equaled to 0.01 unit pH yr–1, which can be a reference to the estimated result, considering the effect of atmospheric N deposition, crop biomass, field management and plant uptake of other nutrients and cations. As protons could be consumed by some field practices, such as stubble return and coupled water and nutrient management, soil pH would maintain relatively stable if proper management practices can be adopted in this region.