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Various agronomic practices can affect the processes of aboveground dry matter accumulation (source) and grain filling (sink), resulting in yield differences. Improved source‐sink relationships can facilitate the production and accumulation of assimilates to increase the productivity of winter wheat (Triticum aestivumL.). A two‐season field experiment was undertaken on winter wheat during 2020–2021 and 2021–2022. In a split‐split‐plot design with three replicates (randomized blocks), we compared two planting modes (ridge‐furrow planting with plastic mulching [RFPM]; traditional flat planting [TF]), two complementary irrigation levels (I30+30: 30+30 mm; I0: no irrigation), and three planting densities (D1, D2, and D3: 240, 360, and 480 plants m−2). The results showed that RFPMI30+30significantly increased maximum yield by 28.5% compared with TFI0. Although D3increased the number of effective spikes per unit area and duration of grain filling compared to D2, it reduced the number of grains per spike, 1000‐grain weight, and average filling rate. Compared to TF and I0, RFPM and I30+30improved the sink/source ratio by 5.3% and 6.5%, respectively. Grain yield peaked at D2in the RFPM and at D3in the TF. Medium planting density (D2) and complementary irrigation (I30+30) during the wintering and reviving periods under RFPM can achieve better source‐sink balance relationships and the maximum grain yield of winter wheat. Overall, we believe that in most cases, wheat yields are source‐limited and can be improved by ridge‐furrow planting with plastic mulching, complementary irrigation, and planting density regulation. Logistic and β‐sigmoid models well fitted aboveground dry matter accumulation and grain filling processes.Effects of planting modes, complementary irrigation, and planting densities on grain filling were explored.A higher yield was obtained at medium planting density under ridge‐furrow planting with plastic mulching.Irrigation of 30 mm at wintering and reviving periods increased grain yield by an average of 13.5%.

Drought stress parameters in crop models have received little attention in the literature. In this study, a global sensitivity analysis on yield simulation was conducted for the drought stress parameters in the ORYZA (v3) model, and sensitive parameters were identified for double‐season rice (Oryza sativaL.) (early rice and late rice) by using the Extended FAST method in different scenarios involving two N applications, two soil types, and four depths of plough soil layer. An adaptive metropolis algorithm (MCMC‐AM) was used to quantify the uncertainties of these parameters with yield observations under various drought stress conditions. Based on the estimated parameter values, model performance of yield simulation was evaluated for drought stress conditions. Results showed that in a light drought stress situation, the upper limit factor for transpiration decline (FSWTD) was extremely sensitive at low N application, whereas the upper threshold for leaf expansion became more sensitive at high N application. In a moderate drought stress situation, the upper threshold for leaf rolling had high sensitivity under all conditions except for the late rice at low N application. In a heavy drought stress situation, FSWTD always had strong influence on yield, whereas the impacts of other parameters varied under different scenarios. Soil types and plough soil depth had considerable effects on the parameter sensitivities depending on fertilizer application and drought stress level. The empirical posterior distributions of these drought stress parameters for late rice showed very different shapes and variation ranges from that for early rice, and large uncertainties were presented. The yield simulations with a finely calibrated model were overestimated under heavy drought stress, especially for the late rice, which was grown in the dry season. The results highlighted that more attention should be paid for the drought stress parameters in crop models.

Uncertainties in crop model have attracted many attentions in recent years. The Generalized Likelihood Uncertainty Estimation (GLUE) and the Markov Chain Monte Carlo (MCMC) methods have been widely used to quantify model uncertainties for hydrological models. While few papers have focused on the comparison of these two methods for a crop model, in this study the GLUE and MCMC were applied for parameter uncertainty analysis of the rice growth model ORYZA_V3. We examined the influence of subjective factors for the GLUE method, and made a comparison of results for the two methods. In the GLUE method, sample size of parameter sets exceeding 30,000 had negligible effects on the results, whereas the accepted sampling rates (ASR) had a pronounced influence on the posterior parameter distributions and the derived 95% confidence interval (95CI) of biomass simulations. Furthermore, the GLUE method failed to construct the posterior distributions for some less sensitive parameters. Due to the large dependence on ASR, the GLUE method might easily lead to deceptive results, and should be used with caution. Because the MCMC has a well‐documented statistical background and it can obtain clear and stable posterior distributions of parameters, this method is strongly recommended for crop model users in parameter uncertainty analysis.

Alternate wetting and drying irrigation (AWD) has been reported to save water compared with continuous flooding (CF) in rice cultivation. However, the reported effects on yield varied greatly and detailed agro-hydrological characterization is often lacking so that generalizations are difficult to make. Furthermore, it is not known how AWD modifies nutrient use efficiencies and if it requires different N-fertilizer management compared with CF. This study quantified the agro-hydrological conditions of the commonly practiced AWD and compared the impact of AWD and CF irrigations at different N-fertilizer management regimes on rice growth and yield, water productivity, and fertilizer-use efficiencies in five crop seasons in 1999 and 2000 at two typical lowland rice sites in China (Jinhua, Zheijang Province and Tuanlin, Hubei Province), with shallow groundwater tables.Grain yields varied from 3.2 to 4.5 t ha –1with 0 kg N ha –1to 5.3–8.9 t ha –1 with farmers’ N-rates (150 kg N ha –1in Jinhua and 180 in Tuanlin). In both sites, no significant water by nitrogen interaction on grain yields, biomass, water productivity, nutrient uptakes and N-use efficiency were observed. Yield and biomass did not significantly differ ( P >0.05) between AWD and CF and among N timings. The productivity of irrigation water in AWD was about 5–35% higher than in CF, but differences were significant ( P <0.05) only when the rainfall was low and evaporation was high. Increasing the number of splits to 4–6 times increase the total N uptake, but not total P-uptake, and total K-uptake compared with farmers’ practices of two splits. Apparent Nitrogen recovery (ANR) increased as the number of splits increased, but there was no significant difference in ANR between AWD and CF. During the drying cycles of AWD irrigation, the perched water table depths seldom went deeper than – 20 cm and the soil in the root zone remained moist most of the time. The results suggest that in typical irrigated lowlands in China, AWD can reduce water input without affecting rice yields and does not require N-fertilizer management differently from continuous flooding. The results can be applied to many other irrigated lowland rice areas in Asia which have a shallow groundwater table.