准确估算区域尺度冬小麦产量对掌握粮食生产情况和保证国家粮食安全十分重要。但目前精确的水资源和区域灌溉信息难以获取，基于遥感模拟区域尺度冬小麦产量的年际和空间变化仍存在较大误差。为此，本研究以中国冬小麦主产区华北平原（NCP）为研究区，发展基于灌溉模式参数（IPPs，即灌溉频率和灌溉时期）近似估计冬小麦灌溉信息的新方法，并将其耦合到一个新发展的遥感过程模型（PRYM–Wheat），以更准确模拟NCP冬小麦产量。本研究使用NCP各县市参考年份（2010–2015）的统计产量确定IPPs的最优值，然后在站点和区域尺度验证耦合了最优IPPs的PRYM–Wheat模拟冬小麦的精度。结果显示，耦合了最优IPPs的PRYM–Wheat模拟参考年份冬小麦产量的相关系数R提升了0.15（37%），均方根误差RMSE减少了0.90 t/hm²（41%）；模拟验证年份（2001–2009和2016–2019）站点尺度、河北省县级尺度、河南省县级尺度和山东省市级尺度的R（RMSE）分别为0.80（0.62 t/hm²）、0.51（0.95 t/hm²）、0.72（1.18 t/hm²）和0.42（0.72 t/hm²）。总体来看，IPPs可以有效提升基于遥感模拟灌溉区区域尺度冬小麦产量的精度，耦合了IPPs的PRYM–Wheat模型可为估算区域冬小麦多年产量提供稳定可靠的方法，为确保区域粮食安全提供科学依据。

理解作物产量差（YG）的空间分布对提高作物产量至关重要。目前的研究通常集中在站点尺度上，当扩展到域尺度上可能会导致相当大的不确定性。为了解决这一问题，本研究采用基于改进北方生态系统生产力模拟器（BEPS）的遥感驱动过程冬小麦作物产量模型（PRYM-Wheat），模拟了2015-2019年华北平原冬小麦的产量差。通过统计产量数据进行产量验证，表明PRYM-Wheat模型在模拟冬小麦实际产量（Ya）方面具有良好的性能。研究区Ya的分布差异较大，由东南向西北呈下降趋势。遥感估算结果表明，研究区域的平均YG为6400.6 kg ha^-1。江苏省YG产量最大，为7307.4 kg ha^-1。安徽YG最小，为5842.1 kg ha^-1。通过分析YG对环境因素的响应，发现YG与降水之间没有明显的相关性，而YG与累积温度之间存在较弱的负相关关系；此外，YG与海拔升高呈正相关。总的来说，研究作物产量差（YG）可以为今后提高作物产量提供方向。

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.