Winter Wheat-summer Maize Research Articles

The Study of Various Regression Models Establishment to Identify Farmland Soil Moisture Content at Different Depths Using Unmanned Aerial Vehicle Multispectral Data: A Case in North China Plain

Soil moisture content is one of the most important soil indices for agriculture production. With the increasing food requirement and limited irrigation water sources, it is of great significance to accurately and quickly measure the soil moisture content for precision irrigation, especially in deficient agricultural areas, such as North China Plain. To achieve this goal, more attention was paid to the application of unmanned aerial vehicle multispectral reflectance technology. However, it was urgent to enhance the regression models between spectral data and soil realistic moisture content, and there were limited studies about the regression research on deep soil layers. Thus, the farmland of winter wheat–summer maize double cropping at Yongnian District, Hebei, North China, was selected as the study area. A six-band multispectral camera mounted on a low-altitude unmanned aerial vehicle (UAV) was used to obtain the field spectral reflectance with bands from 470~810 nm, and meanwhile, soil moisture content at different depths (10, 20, 30, 40, 50, and 60 cm) was measured after maize sowing. Unary linear regression (ULR), multivariate linear regression (MLR), ridge regression (RR), and an artificial neural network (ANN) were employed to establish regression models. The results demonstrated that the sensitive bands of spectral reflectance were 690 nm, 470 nm, and 810 nm. Those models all established significant regression at the depths of 0–20 cm and 40–60 cm, particularly at 10, 50, and 60 cm soil layers. However, for a depth of 20–40 cm, the prediction accuracy was generally lower. Among MLR, RR, and BP models, the MLR exhibited the highest identification accuracy, which was most recommended for the application. The findings of this study provide technical guidance and effective regression for the multispectral reflectance on the farmland of North China Plain, especially for deep soil layer moisture prediction.

Optimal allocation of soil and water resources in agriculture under the total regional evapotranspiration indicator: A case study in Guangping, China

There is a mismatch between crop water demand, the spatial and temporal distribution of natural rainfall, surface water sources, and arable land resources in the North China Plain. This has been compensated for by massive groundwater exploitation, and as a result, ground water levels have continuously declined and groundwater landing funnels have formed in some areas. Consequently, there is an urgent need for the rational allocation of soil and water resources. In this study, regional soil types and the corresponding crops in Guangping County, Hebei Province, China, alongside the regional annual average total water consumption were used to determine reasonable allocations for crop planting structures, with an aim of maximizing the water utilization efficiency and economic benefits while also achieving a regional groundwater dynamic equilibrium. Daily meteorological data from 1973 to 2021, including precipitation, temperature, sunshine hours, wind speed, and humidity, as well as crop data, including irrigation systems and crop growth status, were collected. Water consumption models for eight soil types and seven typical crops forming 56 calculation partitions were established to obtain annual average water consumption values for the different crops. The maximum economic benefit and water-use efficiency were then used as the objective functions and total water consumption as the control condition for the non-dominated sorted genetic algorithm-Ⅱ (NSGA-II), to optimize the allocation of soil and water resources in the region; the adjusted quantities for the different crops cultivated under different soil types in the study area were obtained. The areas growing sweet potato and vegetable-fruits were found to increase by 0.5255 km2 and 4.4452 km2, respectively, when compared to the pre-optimization period, whereas the areas with winter wheat-summer maize, millet, peanut, cotton, and summer maize decreased by 1.3481 km2, 0.1812 km2, 0.7316 km2, 2.0896 km2, and 0.62 km2, respectively. The economic benefit increased from 810.37 to 853.64 million yuan, while the water-use efficiency increased from 1.5426 kg/m3 to 1.5859 kg/m3. The results provide a basis for soil and water resource management in the region and a technical reference for similar areas to improve agricultural water-use efficiency and economic benefits.

Enhanced nitrogen fertilizer combined with straw incorporation can reduce global warming potential with higher carbon sequestration in a summer maize-winter wheat rotation system

The combined effects of nitrogen (N) fertilizers and straw incorporation (SI) on GHG emissions, crop yields, and net ecosystem carbon budget (NECB) in summer maize-winter wheat rotation systems are still uncertain. We conducted a two-year field experiment to evaluate the effects of SI combined with different N fertilization practices on soil N2O emissions, ecosystem respiration (Re), NECB, grain yields, net global warming potential (NGWP), and greenhouse gas intensity (GHGI). In total, five treatments were considered, namely conventional urea-N application (FP), optimal urea-N fertilizer (OPT) with and without SI (S+OPT and OPT), and enhanced-efficiency N fertilizers (equivalent to OPT) with and without SI (S+EENF and EENF). The results showed significantly decreased average annual N2O emissions under the OPT and EENF treatments by 22.70 and 51.35% (P < 0.05), respectively, compared with that under the FP treatment. However, no significant differences in the annual Re emissions, NECB values, and crop yields were observed between the N fertilizer treatments (P > 0.05). The SI significantly increased the average annual N2O emissions, annual Re emissions, and annual grain yields by 36.01, 27.94, and 11.54% (P < 0.05), respectively, compared to no-straw treatments. The annual NECB values under the SI and no-straw treatments ranged from 1.19 to 1.94 t C ha−1 yr−1 and −1.89 to −1.19 t C ha−1 yr−1, respectively. The lower NGWP and GHGI values were observed in the S+EENF plots. The results suggest that the practice of enhanced-efficiency N fertilizers coupled with SI could improve crop yields and reduce NGWP and GHGI values in summer maize-winter wheat rotation systems.

Groundwater Depletion and Degradation in the North China Plain: Challenges and Mitigation Options

Groundwater is an important natural resource in the North China Plain (NCP) with high economic benefits and social significance. It fulfills 60% of drinking and 70% of irrigation water requirements. In this review, the information is retrieved from high-quality articles published in MEDLINE and other sources. We saw that groundwater is declining faster (&gt;1 m yr−1) and polluting with NO3− (&gt;30 mg L−1) due to excessive water pumping and application of a nitrogen (N) fertilizer, respectively. The water pumping (&gt;600 mm ha−1 yr−1) for agricultural purposes in the region is higher than the recharge amount (&lt;200 mm yr−1). The low recharge is the result of low rainfall (&lt;600 mm yr−1), and high evapotranspiration (&gt;800 mm yr−1) under the impact of dominant vegetative characteristics of winter wheat–summer maize (WW-SM) rotations, covering &gt;80% of the land. Furthermore, N application exceeds the crop assimilation capacity (&gt;250 kg ha−1 yr−1) and leach deep down (&gt;50 kg ha−1) as well as loss in the atmosphere. Presently, Beijing, Tianjin, and Hebei are ecologically the most affected areas. We suggest that excessive water and N fertilizer use for intensive cropping systems should be controlled by paying high attention to groundwater-friendly farming practices. In addition, artificial groundwater recharge options and their safe utilization would be explored across the region to replenish aquifers. This literature review contributes valuable insights to the knowledge bank and offers a foundation for further research and policy development.

Ammoniated straw returning: A win-win strategy for increasing crop production and soil carbon sequestration

Increasing crop production and soil carbon sequestration is critical for sustainable agricultural development. Straw returning, a common agricultural practice, positively affects grain yield and soil organic carbon. Nevertheless, the slow decomposition rate and high carbon-to-nitrogen ratio of straw are significant obstacles to its effectiveness. Ammonifying straw using urea and calcium hydroxide may be a promising solution, whereas limited information is available on the impacts of ammoniated straw returning on crop production and soil carbon sequestration. Therefore, in a winter wheat-summer maize rotation system, we conducted an experiment with three straw returning treatments (T1, straw removal; T2, traditional straw returning; T3, ammoniated straw returning) to investigate their impacts on crop growth, grain yield and yield components, carbon inputs and outputs, and net ecosystem carbon budget (NECB). The results showed that T3 outperformed T2 regarding increasing leaf area index and aboveground biomass. Ear density and thousand kernel weight of winter wheat and hundred kernel weight of summer maize were ranked T1 < T2 < T3, with no significant differences between treatments for other grain yield components. Consequently, winter wheat, summer maize, and annual grain yields were the highest under T3, followed by T2 and T1. In comparison with T1, T2 and T3 increased annual total carbon inputs by 5463 and 7271 kg C ha–1, respectively, due to the increased carbon inputs from returned straw and net primary productivity. Annual carbon total outputs, primarily from aboveground biomass removal at harvest and carbon respiration, increased by 3305 kg C ha–1 under T2 and 4264 kg C ha–1 under T3, compared with T1. Balancing annual total carbon inputs and outputs, T1, T2, and T3 had annual NECB values of –1215, 944, and 1793 kg C ha–1, respectively. Therefore, the T1 agroecosystem acted as a carbon source, whereas the T2 and T3 agroecosystems, particularly T3, acted as a carbon sink on an annual scale. These results suggest that ammoniated straw returning may be a superior straw application practice for increasing crop production and soil carbon sequestration simultaneously.

Characteristics and Influence Factors of Soil Water and Salt Movement in the Yellow River Irrigation District

Climate change and human activities lead to freshwater shortage, soil salinization, and food security crises in arable land. To explore the natural and irrigation factors on soil water and salt movement, this study quantitatively analyzed the dynamic characteristics of soil water and salt movement under precipitation, groundwater irrigation, and brackish water irrigation conditions for the next 30 years using Hydrus-1D model-based parameters obtained from the winter wheat–summer maize rotation experiments in the Yellow River Irrigation District. The results showed that precipitation was the key factor of climate change affecting soil water and salt migration, especially in the 0–20 cm soil layer. Under both SSP585 and SSP245 climate scenarios, rainfall in normal and wet years promoted salt leaching up to 1 m below the surface soil. But in dry years, salt washing treatment was required for the tillage layer to prevent salt accumulation. The higher the groundwater level was, the higher the soil water and salt content was in the 0–100 cm soil layer. In this soil layer, a 2 m groundwater level contributed 30% to wheat water needs, while a 3 m groundwater level contributed 18%, and no significant contribution was observed for a 4 m groundwater level. The salinity of the soil profile showed an overall increasing trend with irrigation using 1–3 g/L brackish water for 30 years. However, the salinity in the 0–100 cm soil layer was below the salt tolerance threshold of winter wheat and summer maize with salts accumulated in the 1–2 m soil layer. Considering the salinization of the root zone and crop water needs, it is recommended that the safe groundwater level for brackish water irrigation should be 3 m in the study region. This study provides scientific reference for groundwater–farmland ecosystems to utilize brackish water and treat saline–alkali lands.

Variations in crop yield caused by different ratios of organic substitution are closely related to microbial ecological clusters in a fluvo-aquic soil

ContextPartial substitution of chemical fertilizer with organic fertilizer (PSCFOF) can improve soil quality and reduce the overreliance of crop yield on chemical fertilizers. However, the relationship between alterations in crop yield and soil microbial community in response to various substitution ratios is not comprehensively understood. ObjectivesThis study aimed to investigate the impact of PSCFOF on soil nutrient supply, enzyme activity, bacterial and fungal community, and crop yield. MethodsAn 11-year (2009 – 2021) field experiment was carried out in a winter wheat–summer maize double-cropping system with four fertilization regimes (no fertilizer, NF; pure chemical fertilizer, NPK; 30% organic substitution, NPKLM; and 50% organic substitution, NPKHM). Co-occurrence network analysis was applied to examine the importance of ecological clusters and keystone species in controlling microbial activities and crop yields. ResultsThere were no significant differences in soil nutrient contents and annual crop yield between the NPK and NPKLM treatments. However, the NPKHM treatment resulted in significant reductions in crop yield by 9.49%− 16.78%, despite increasing soil organic matter (SOM), total nitrogen (TN), available nitrogen (AN), and available phosphorus (AP) by 9.05%, 7.26%, 11.67%, and 26.62%, respectively. This contrasting effect was primarily attributed to the influence of a specific ecological cluster (module 2), rather than the entire microbial community. Long-term 50% organic substitution would suppress keystone species within module 2, such as Aggregatilinea, Luteimonas, Usitatibacter and Microvirga. These species were specifically correlated with soil carbon enzyme activities, including β-glucosidase, invertase, and dehydrogenase, and contributed significantly and positively to crop yield. ConclusionsOrganic substitution at different ratios altered soil nutrient content, enzyme activities and microbial community in different intensities and directions. Long-term 30% organic substitution could preserve soil fertility and microbial community, leading to stable crop yield; whereas 50% organic substitution could inhibit keystone species, reduce extracellular enzyme activity and ultimately lead to a decrease in crop yield. ImplicationsOur results highlight the importance of ecological clusters within soil microbial co-occurrence network in regulating crop yield, presenting a new perspective on the variations in crop yield resulting from varying ratios of organic substitution.

Response of net water productivity to climate and edaphic moisture in wheat-maize rotation system

Comprehending the mechanisms underlying the response of water productivity to changing climate is essential for developing effective strategies that can maintain sustainable agricultural productivity and ecological stability amidst water scarcity and climate change. This study aimed to clarify the effects of climate and associated biologic and abiotic factors on the net water productivity (NWP) in the winter wheat—summer maize rotation system within the North China Plain (NCP), through integrating spatial-temporal pattern analysis, the Optimal Parameter-based Geographical Detector model, Random Forest, and Structural Equation Modeling. Despite climate warming and water scarcity, the NWP in the vast majority of rotation systems within the NCP exhibited an increasing trend between 2000 and 2019, which was anticipated to persist in the future. From 2000–2019, the impact of climate on the NWP exerted a fluctuating diminishment, besides the influence of WS. It is essential to add adaptive strategies that can cope with WS fluctuation in future management, to better tackle climate variability. Apart from direct effects, meteorological factors indirectly induced NWP variation primarily by influencing edaphic moisture dynamic and crop growth factors. In the paths underlying the effect of climate change on NWP, positive and negative effects coexisted. Edaphic moisture within the 40–100 cm layer played an important role in affecting NWP throughout rotation systems. To sustainably improve NWP, it was advisable to adopt deeper-rooting crop varieties in conjunction with moderate deficit irrigation and improving topsoil water retention capability. Overall, we incorporated soil and crop factors into the framework of climate impact research, providing a systematic elucidation for the mechanisms through which climate change affects NWP. Additionally, the conclusions were based on a continuous spatiotemporal framework that accounted for the geospatial heterogeneity of variables, thereby giving conclusions ample regional universality.

Grain yield estimation of wheat-maize rotation cultivated land based on Sentinel-2 multi-spectral image: A case study in Caoxian County, Shandong, China

Establishing the remote sensing yield estimation model of wheat-maize rotation cultivated land can timely and accurately estimate the comprehensive grain yield. Taking the winter wheat-summer maize rotation cultivated land in Caoxian County, Shandong Province, as test object, using the Sentinel-2 images from 2018 to 2019, we compared the time-series feature classification based on QGIS platform and support vector machine algorithm to select the best method and extract sowing area of wheat-maize rotation cultivated land. Based on the correlation between wheat and maize vegetation index and the statistical yield, we screened the sensitive vegetation indices and their growth period, and obtained the vegetation index integral value of the sensitive spectral period by using the Newton-trapezoid integration method. We constructed the multiple linear regression and three machine learning (random forest, RF; neural network model, BP; support vector machine model, SVM) models based on the integral value combination to get the best and and optimized yield estimation model. The results showed that the accuracy rate of extracting wheat and maize sowing area based on time-series features using QGIS platform reached 94.6%, with the overall accuracy and Kappa coefficient were 5.9% and 0.12 higher than those of the support vector machine algorithm, respectively. The remote sensing yield estimation in sensitive spectral period was better than that in single growth period. The normalized differential vegetation index and ratio vegetation index integral group of wheat and enhanced vegetation index and structure intensify pigment vegetable index integral group of maize could more effectively aggregate spectral information. The optimal combination of vegetation index integral was difference, and the fitting accuracy of machine learning algorithm was higher than that of empirical statistical model. The optimal yield estimation model was the difference value group-random forest (DVG-RF) model of machine learning algorithm (R2=0.843, root mean square error=2.822 kg·hm-2), with a yield estimation accuracy of 93.4%. We explored the use of QGIS platform to extract the sowing area, and carried out a systematical case study on grain yield estimation method of wheat-maize rotation cultivated land. The established multi-vegetation index integral combination model was effective and feasible, which could improve accuracy and efficiency of yield estimation.

Optimized planting structures maintain system yield and economic benefits with less nitrogen footprint

ContextsThe Huang-Huai-Hai Plain in China relies heavily on the winter wheat-summer maize rotation for grain production. However, this cropping system faces challenges regarding its sustainability due to significant environmental costs. ObjectivesThis study aims to evaluate the nitrogen footprint of different cropping systems, compare their economic benefits, and identify alternative summer crops that can optimize system yield, economic advantages, and environmental impact. MethodsA three-year field experiment was conducted to compare the economic and environmental impacts of three cropping systems: winter wheat-summer maize (W-M), winter wheat-summer soybean (W-S), and winter wheat-sweet potato (W-SP). The experiment involved assessing yield, inputs, and outputs, and conducting a comprehensive nitrogen footprint analysis for each system. ResultsOver the three experimental years, the W-S system showed the highest yield improvement for winter wheat. The W-SP system had the highest annual maize equivalent yield and total income but incurred the highest total annual cost compared to the other two systems. However, the W-SP system demonstrated the highest annual average economic profit performance, nearly double that of the other two systems. The nitrogen footprint analysis revealed that both the W-S and W-SP systems reduced reactive nitrogen emissions compared to the W-M system. Notably, the W-S system managed to reduce the nitrogen footprint by 34%. The average nitrogen footprint emissions scores for W-M, W-S, and W-SP systems were 2.1, 2.3, and 3.5, respectively. ConclusionsAmong the three systems, the W-SP system achieved the highest economic benefits but also had the greatest negative environmental impact. The W-S system demonstrated a significant reduction in reactive nitrogen loss while maintaining productivity, indicating its potential for mitigating negative environmental impacts. SignificanceOur three-year field study highlights the advantages of the W-S system in reducing the nitrogen footprint and its potential contribution to sustainable agricultural development in the Huang-Huai-Hai Plain.

Managing nitrogen for sustainable crop production with reduced hydrological nitrogen losses under a winter wheat-summer maize rotation system: an eight-season field study.

Excessive nitrogen (N) application in wheat-maize cropping systems was adjusted towards more sustainable practices to reduce hydrological N losses while maintaining crop yield. In comprehensive quantification of N management effects on crop yield, N use efficiency (NUE), hydrological N losses, and soil nitrate residual across eight seasons, we have added to growing evidence of strategies beneficial for sustainable crop production with lower hydrological N losses. The results show that adjusted N practices enhanced crop yield and NUE, as compared to farmer's practices, but benefits varied with N rates and types. Optimized N treatment (OPT, 180 kg N ha-1 in both maize and wheat seasons) with or without straw returning produced the most crop yield. They increased maize yield by 5.5% and 7.3% and wheat yield by 6.2% and 3.2% on average, as compared to farmer's practice with huge N application (FP, 345 kg N ha-1 and 240 kg N ha-1 in maize and wheat). Regulation of N release through amendment with controlled release urea at a rate of 144 kg N ha-1 crop-1 (CRU treatment) obtained 4.4% greater maize yield than FP, and sustained a similar wheat yield with less N input, resulting in the highest crop NUE. Additionally, CRU was most effective in mitigating hydrological N loss, with 39.5% and 45.5% less leachate N and 31.9% and 35.9% less runoff N loss than FP in maize and wheat seasons. Synthetic N input correlated significantly and positively with runoff and leachate N losses, indicating it was one of the dominant factors driving hydrological N losses. Moreover, compared to OPT, additional straw returning (STR) or substituting 20% of the nutrients by duck manure (DMS) further reduced runoff N discharges due to the fact that organic matter incorporation increased resilience to rainfall. N over-application in FP caused considerable nitrate accumulation in the 0-90-cm soil profile, while the adjusted N practices, i.e., OPT, STR, CRU, and DMS treatments effectively controlled it to a range of 79.6-92.9 kg N ha-1. This study suggests that efforts using optimized N treatment integrated with CRU or straw returning should be encouraged for sustainable crop production in this region.

Optimizing irrigation strategies for sustainable crop productivity and reduced groundwater consumption in a winter wheat-maize rotation system

Inefficient irrigation practices have hindered crop yields, wasted irrigation water resources, and posed threats to groundwater levels and agricultural sustainability. This study evaluated different irrigation strategies for a winter wheat-summer maize rotation system to identify sustainable practices for maintaining yields while reducing groundwater depletion. A two-year field experiment was conducted, implementing three optimized irrigation strategies during the winter wheat season: I-4 (irrigated until the soil water content (SWC) of the 40 cm soil layer reaches 60% of field capacity (FC), I-6 (irrigated until the SWC of the 60 cm soil layer reaches 80% FC), and a rainfed (R) as control. Irrigation was repeated when the SWC dropped to the specified level. No irrigation level was used during the summer maize season, except for irrigation after sowing that ensuring the normal emergence of maize. WHCNS (Water Heat Carbon Nitrogen Simulator) model was developed to simulate soil water dynamics, field water consumption, and yield of both crops. The result indicated WHCNS model accurately simulated water dynamics, consumption, and grain yield. Compared to R treatment, the I-4 treatment significantly increased annual crop yield by 19.83%–28.65% (p < 0.05), while maintaining similar crop water productivity. Furthermore, the I-4 treatment achieved comparable yields to the I-6 treatment, but with a 33.91% reduction in irrigation water use, resulting in a 33.46% increase in crop water productivity and a 90.53% increase in irrigation water productivity. From a sustainable perspective, the I-4 treatment effectively reduced field water losses and maintained relatively high soil water storage, particularly in the topsoil, which was beneficial for the early growth of subsequent crops. The R treatment greatly contributed to groundwater recharge when precipitation was sufficient, while it led to severe yield losses. Overall, under the condition of annual rotation planting systems, the I-4 treatment sustainably maintained yields with less irrigation, decreasing groundwater consumption. This approach could conserve regional water resources and groundwater table while upholding agricultural productivity and achieving system sustainable water use.

Identifying the Spatio-Temporal Change in Winter Wheat–Summer Maize Planting Structure in the North China Plain between 2001 and 2020

Tracking winter wheat–summer maize distribution is crucial for the management of agricultural water resources in the water-scarce North China Plain (NCP). However, the spatio-temporal change in planting structure that has occurred during the last 20 years remains unclear. Therefore, winter wheat–summer maize distribution between 2001 and 2020 was determined via the maximum likelihood algorithm of supervised classification and a threshold method using the MODIS NDVI product MOD13Q1 and Landsat 5/7 images. The results reveal that dividing distributions into six sample categories—winter wheat–summer maize, winter wheat–rice, spring maize, cotton, other double-cropping systems, and fruit trees—proved to be an efficient way to discriminate winter wheat–summer maize distribution, with R2 and RMSE values ranging from 0.738 to 0.901 and from 179.05 to 215.72 km2, respectively. From 2001 to 2020, the planting area continually expanded, experiencing a significant growth of 3.32 × 104 km2 (23.44%). Specifically, the planting area decreased by 2982.13 km2 (10.06%) in the northern part of the NCP, including the Beijing–Tianjin–Hebei region, while it increased by 3.62 × 104 km2 (32.30%) in the middle and southern parts, encompassing Shandong, Henan, Anhui, and Jiangsu provinces. The stable growing region was primarily concentrated in the middle of the Hebei Plain, along the Yellow River irrigation areas and humid zones of the southwest, accounting for 75–85% of the total NCP planting area. Our results can provide references for adjusting agricultural planting structures, formulating food security strategies, and optimizing the management of water resources in the NCP.

Mixed application of controlled-release urea and normal urea can improve crop productivity and reduce the carbon footprint under straw return in winter wheat-summer maize cropping system

An important goal of sustainable agriculture is reducing the environmental risk while also ensuring food security. The mixed application of controlled-release urea and normal urea (CRUNU) is a potential nitrogen (N) management strategy for achieving this goal. However, few studies have focused on whether optimizing the N application rate of CRUNU can balance crop yield and greenhouse gas emissions, especially when straw is returned. Thus, we conducted a five-year field experiment in a winter wheat–summer maize planting system in Northwest China to determine the effects of different N fertilizer types (NU: normal urea; CRUNU) and N application levels (low N, 135 kg ha–1; medium N, 180 kg ha–1; high N, 225 kg ha–1) with straw return on the crop yield and stability, N fertilizer partial factor productivity (NFPF), and soil organic carbon (SOC). Life cycle assessment was also conducted to quantify the GHG emissions from farmland and carbon footprint (CF). Compared with NU, CRUNU improved the winter wheat and summer maize grain yield, biomass, and NFPF at all three N application levels. The crop grain yields increased significantly as the N application level increased under NU, but the crop grain yields did not differ significantly between the medium and high N application levels under CRUNU (P > 0.05). The SOC contents increased as the duration of straw return increased. Compared with NU, CRUNU significantly increased the SOC content, and correlation analysis showed that this increase was related to the increased amount of returned straw. Compared with NU, CRUNU increased the GHG emissions in the production process but reduced the GHG emissions in the application process, as well as increasing soil CO2 fixation to ultimately reduce the total GHG emissions. CRUNU increased the crop grain yield while also reducing the total GHG emissions, and thus the CF decreased significantly by 14.53–23.03% compared with NU, especially at the medium N application level. Therefore, this comprehensive analysis of the crop productivity and GHG emissions indicates that CRUNU combined with an appropriate N application level can be used as a nitrogen fertilizer management strategy for sustainable winter wheat–summer maize cropping in Northwest China.

Reduce carbon footprint without compromising system productivity: Optimizing crop rotation in the North China plain

The North China Plain (NCP) serves as a crucial production base for wheat and maize in China. However, the intensive winter wheat-summer maize (WM) cropping system has also led to high carbon emissions. It is imperative to optimize crop rotations to reduce greenhouse gas (GHG) emissions while ensuring food security. Thus, we conducted a 6-year field experiment in the NCP to evaluate the productivity, carbon footprint (CF), and sustainability of the five rotation systems. These included four 2-year rotation systems: spring maize → WM (WMME), spring millet → WM (WMML), spring peanut → WM (WMMP), and spring soybean→ WM (WMMS), with WM serving as the control. Our results indicated that the 2-year rotation systems significantly reduced GHG emissions and improved agricultural sustainability. Wheat yield following the spring crops was 38.6%–47.5% higher than that following summer maize. The energy use efficiency, energy productivity, maize economic equivalent yield (MEEY), and net income in WMMP were higher by 9.7%, 51.8%, 4.4%, and 15.5%, respectively, compared to WM. This was mainly attributed to the high yield, price, energy equivalent coefficient, and pre-crop effect of spring peanut. The reduction of N and electricity inputs in the 2-year rotation systems reduced on-farm N2O emissions and indirect emissions by 39.0%–56.2% and 41.9%–42.9%, respectively, thus lowering CF per unit area by 25.7%–36.6% compared with WM. WMMP demonstrated a 38.2% reduction in CF per kg MEEY, 16.1% reduction in CF per unit net energy, and 44.1% reduction in CF per unit net income, while increasing the sustainable evaluation index by 42.9% compared to WM. In conclusion, the 2-year rotation systems can reduce carbon footprint and improve agricultural sustainability in the NCP, among which the introduction of spring peanut into winter wheat-summer maize rotation can simultaneously enhance system productivity.

A dataset of carbon and water fluxes in farmland ecosystems at Gucheng Station (2020–2022)

Hebei Gucheng Agricultural Meteorology National Observation and Research Station (Gucheng Station) is one of the national field scientific observation and research stations approved by the Ministry of Science and Technology (MOST). Located in the irrigated high-yield agricultural area in the northern part of the North China Plain, it is a typical North China winter wheat-summer maize rotation system. Based on the eddy covariance technique, the observation of cropland ecosystem carbon and water fluxes has been carried out at Gucheng Station for a long time. Following the ChinaFLUX data processing protocols, we collected the carbon and water fluxes and auxiliary meteorological environment observations of the winter wheat and summer maize rotation ecosystem at Gucheng Station from 2020 to 2022, and produced a standardized dataset after data quality control and processing. This dataset has important scientific significance and practical application value in the assessment of farmland ecosystem carbon budget, water resources utilization, and the mitigation of the impact of adverse meteorological conditions on farmland ecosystems and agricultural production.

Productivity and water use efficiency of summer soybean-winter wheat rotation system under limited water supply in the North China Plain

Development of novel crop rotations with superior water- and N-use efficiency will be fundamental in the quest for securing sustainable food supplies under environments that are increasingly resource limited. Here, our aim was to examine how replacing maize with soybean as part of winter wheat rotations impacted the nutrient-equivalent yield (EY), evapotranspiration (ET) and water-use efficiency (WUE) of rotation systems. We contrasted summer soybean-winter wheat (SW) and summer maize-winter wheat (MW) cropping systems under three nitrogen (N) fertilization regimes: no, medium, and high nitrogen application rates (0 N, MN, and HN, respectively). Results showed that SW not only resulted in lower annual yields, but also caused more variable inter-annual wheat productivity compared with MW. SW had similar annual productivities to MW in wet (2019–2020) and dry (2020–2021) years, but lower productivity than MW in an average precipitation year (45% reduction, 2018–2019). As well, SW had higher average annual ETs (633–854 mm) than MW, mainly was attributed to higher ETs (268–440 mm) in summer. SW reduced WUEs by 17% and 28% in average (2018–2019) and dry (2020–2021) years, respectively. Regardless of cropping system, N fertilization increased annual EYs and ETs by 10–18% and 5–18% compared with no fertilization, respectively. Together these comparable increments in EY and ET, we found that N fertilization had rare effects on annual WUE of both systems. Overall, our study demonstrated that replacing maize with soybean in winter wheat rotations increased annual ET and neither maintained productivity nor improved water productivity. Thus, we suggest that practitioners explore other drought tolerant grain legumes to generate more reliable yields and less water consumption under legume-based crop rotations.

Seasonal variations and driving mechanisms of CO2 fluxes over a winter-wheat and summer-maize rotation cropland in the North China plain

Characterization of crop CO2 fluxes in different growing periods and their corresponding responses to abiotic and biotic factors is essential for the adaption of cropland ecosystem carbon balance to future climate change and management practices. In this study, based on long-term (2003–2018) monitoring of CO2 fluxes, meteorological data and leaf area index (LAI) of a winter wheat-summer maize rotation cropland in the North China Plain, the relationship between CO2 fluxes of different growing periods and the driving factors (i.e., abiotic and biotic factors) was explored to identify the important affecting factors. The Random Forest (RF) algorithm revealed that LAI was the most important driving factor of CO2 fluxes in the wheat season, except for WGPW (from sowing to maturity). Net ecosystem productivity (NEP) had significant positive relationships with LAI, photosynthetically active radiation (PAR) and soil water content (SWC) in four different growing periods. Air temperature (Ta) was positively correlated with ecosystem respiration (ER), and LAI and PAR were positively correlated with gross primary productivity (GPP). In the maize season, the RF algorithm revealed that LAI, PAR and SWC were important drivers of CO2 fluxes. NEP and GPP had significant negative relationships with precipitation (PPT) in RGPM (from tasseling to maturity) and WGPM (from sowing to maturity). Ta was positively correlated with ER, and SWC was positively correlated with NEP and GPP except for VGP2M (from jointing to tasseling). For annual fluxes, the interannual variability (IAV) of NEP, ER and GPP were mainly attributed to IAV of the maximum daily NEP (NEPmax), maximum daily ER (ERmax) and maximum daily GPP (GPPmax), respectively. Our findings provide deep insight into CO2 flux characteristics of wheat-maize rotation systems in different growing periods and their influencing mechanisms, which are crucial for predicting the carbon cycle of cropland ecosystems under climate change.

Spatial-temporal coupling pattern between irrigation demand and soil moisture dynamics throughout wheat-maize rotation system in the North China Plain

Irrigation water requirement (Iwr) and soil moisture (SM) are two essential metrics that guide scientific irrigation and agricultural water-saving practices. Although they have been extensively studied in the North China Plain (NCP), an exploration into their spatial-temporal coupling pattern remains absent. Here, the spatial-temporal coupling pattern underlying the variations of Iwr and SM across the winter wheat–summer maize rotation system within the NCP was elucidated from a geographic perspective, by developing a geo-statistic framework that integrated the global spatial autocorrelation, spatial hot-spot technique, geographically weighted regression, and the optimal parameters-based geographic detector. From 2000–2019, the Iwr and SM exerted a distinct geospatial heterogeneity. Winter wheat demonstrated a spatially descending gradient in Iwr from north to south, while the pattern in summer maize Iwr varied greatly across periods. Generally, winter wheat had a higher Iwr, while the geospatial pattern of summer maize Iwr displayed a greater variability. Spatial pattern of SM in 0–100 cm soil horizon exhibited an approximately inverse trajectory to that of Iwr, while SM in 100–200 cm horizon demonstrated a spatial staggered pattern. In most cases, there existed a notable negative coupling between Iwr and SM at 0–100 cm depth, but not universal at 100–200 cm. Nonetheless, a pronounced reciprocal enhancement mechanism between SM of two layers was confirmed. Between 2000 and 2019, a geospatial decoupling trend was detected between Iwr and SM throughout the NCP. Despite remaining universality, the pattern of high irrigation demand induced by soil moisture deficit was being weakened. Given these, climate-adaptive water-saving strategies were updated, which provide a new implication for regional agricultural water-saving practice and sustainable production.

A distributed agroecosystem model (RegWHCNS) for water and N management at the regional scale: A case study in the North China Plain

Process-based agroecosystem model is difficult to apply at the regional scale due to the complexity of model parameterization and execution efficiency. Thus, developing a regional agroecosystem model is challenging. In this study, a parallel computing framework is introduced to upscale an agroecosystem model (WHCNS model) from field to regional scale by integrating parallel computing, inversing modeling, and spatial calculation. The newly developed model was tested in the North China Plain (NCP) for modeling water consumption, N fate, and crop growth for winter wheat–summer maize rotation system under different water and N management practices. The optimum irrigation water and fertilizer N demands of winter wheat–summer maize system was estimated based on the auto-irrigation and auto-fertilization component in the model. Multisite testing showed that the model well reproduced soil water and N dynamics, crop biomass, LAI, yield, and crop N uptake, with R2 exceeding 0.886. The estimated annual average irrigation water and fertilizer N demands of winter wheat–summer maize rotation system was 395.8 mm and 529.5 kg N ha−1, respectively. Winter wheat was the major consumer of irrigation water and fertilizer N, accounting for 79.2 % and 54.4 % of annual irrigation water and chemical N fertilizer use, respectively. These results suggested that winter wheat was a crop with high water and fertilizer N demand in the NCP. The RegWHCNS model has potential value to assess and optimize regional water and N management for intensive agricultural-production systems. This study can provide as a scientific reference to upscale agroecosystem models from field to region for other agroecosystem models.