Xuebiao Pan

The arid and semi-arid region of Northwest China plays a significant role in potato production, yet yields are often hampered by drought due to limited precipitation and irrigation water. The ridge–furrow rainwater-harvesting technology is an efficient and widely used technique to relieve drought impact and improve crop yield by changing the micro-topography to harvest rainwater to meet the water demand of crops. An analysis of precipitation, water demand, and runoff data spanning 30 years guided the selection of suitable rainwater-harvesting methods tailored to meteorological conditions. The results showed that potato water demand exceeded precipitation in the region. The mulching approach performed best in the western arid region with the most significant increase in yield and water use efficiency (WUE) and was suitable for the western semi-arid region and the agro-pastoral ecotone. In the potato dryland farming areas, the water deficit increased from southeast to northwest. Specifically, northern Gansu, northern Ningxia, and midwestern Inner Mongolia experienced a water deficit of over 200 mm, and rainwater harvesting combined with irrigation was recommended. Conversely, regarding deficits below 200 mm in southern Gansu, Ningxia, and central Inner Mongolia, a 1:1 or 2:1 pattern of ridges could be applied, and mulching was needed only in the necessary areas. For the southern Qinghai, Shaanxi, and eastern Inner Mongolia regions, ridge–furrow rainwater harvesting could be replaced by flat potato cropping. In summary, rainwater harvesting addresses water deficits, aiding climate adaptation in Northwest China’s arid and semi-arid regions. The implementation of mulching and ridge–furrow technology must be location-specific.

Quantification of the trade-offs among greenhouse gas (GHG) emissions, yield, and farmers’ incomes is essential for proposing economic and environmental nitrogen (N) management strategies for optimizing agricultural production. A four-year (2017–2020) field experiment (including four treatments: basic N fertilizer treatment (BF), suitable utilization of fertilization (SU), emission reduction treatment (ER), and high fertilization (HF)) was conducted on maize (Zea mays L.) in the North China Plain. The Life Cycle Assessment (LCA) method was used in this study to quantify the GHG emissions and farmers’ incomes during the whole maize production process. The total GHG emissions of BF, SU, ER, and HF treatments in the process of maize production are 10,755.2, 12,908.7, 11,950.1, and 14,274.5 kg CO₂-eq ha⁻¹, respectively, of which the direct emissions account for 84.8%, 76.8%, 74.9%, and 71.0%, respectively. Adding inhibitors significantly reduced direct GHG emissions, and the N₂O and CO₂ emissions from the maize fields in the ER treatment decreased by 30.0% and 7.9% compared to those in the SU treatment. Insignificant differences in yield were found between the SU and ER treatments, indicating that adding fertilizer inhibitors did not affect farmers’ incomes while reducing GHG emissions. The yield for SU, ER, and HF treatments all significantly increased by 12.9–24.0%, 10.0–20.7%, and 2.1–17.4% compared to BF, respectively. In comparison with BF, both SU and ER significantly promoted agricultural net profit (ANP) by 16.6% and 12.2%, with mean ANP values of 3101.0 USD ha⁻¹ and 2980.0 USD ha⁻¹, respectively. Due to the high agricultural inputs, the ANP values in the HF treatment were 11.2%, 16.6%, and 12.4% lower than those in the SU treatment in 2018–2020. In conclusion, the combination of N fertilizer and inhibitors proved to be an environmentally friendly, high-profit, and low-emissions production technology while sustaining or even increasing maize yields in the North China Plain, which was conducive to achieving agricultural sustainability.

Quantification of the trade-offs among greenhouse gas (GHG) emissions, yield and farmers’ incomes is essential for proposing economic and environment nitrogen (N) management strategies for optimizing agricultural production. A four-year (2017–2020) field experiment (including four treatments: control experiment (CK), suitable utilization of fertilization (SU), emission reduction treatment (ER), and high fertilization (HF)) was conducted on maize (Zea mays L.) in the North China Plain. The Life Cycle Assessment (LCA) method was used in this study to quantify the GHG emissions and farmers’ incomes during the whole maize production process. The total GHG emissions of CK, SU, ER and HF treatments in the process of maize production are 10,755.2, 12,908.7, 11,950.1, and 14,274.5 kg CO2-eq ha−1 respectively, of which the direct emissions account for 84.8%, 76.8%, 74.9%, and 71.0%, respectively. Adding inhibitor significantly reduced direct GHG emissions, and the N2O and CO2 emissions from the maize fields in the ER treatment decreased by 30.0% and 7.9% compared to those in the SU treatment. Insignificant differences in yield were found between the SU and ER treatments, indicating that adding fertilizer inhibitors did not affect farmers’ incomes while reducing GHG emissions. The yield for SU, ER and HF treatments all significantly increased by 12.9%–24.0%, 10.0%–20.7% and 2.1%–17.4% compared to CK, respectively. In comparison with CK, both SU and ER significantly promoted agricultural net profit (ANP) by 16.6% and 12.2% with the mean ANP values of 3,101.0 USD ha-1 and 2,980.0 USD ha-1, respectively. Due to the high agricultural inputs, the ANP values in the HF treatment was 11.2%, 16.6% and 12.4% lower than those in the SU treatment in 2018–2020. In conclusion, the combination of N fertilizer and inhibitors was proved to be an environmentally friendly, high-profit and low-emissions production technology while sustaining or even increasing maize yields in the North China Plain, which was conducive to achieving agricultural sustainability.

Suitable sowing dates are crucial in plant production to cope with climate change and ensure high-quality crop production. We hypothesize that the analysis of the effect of sowing date and climatic resources on maize kernel nutritional quality (KNQ) (crude fiber, starch, crude fat, and crude protein) might contribute to selecting appropriate sowing dates according to different production requirements and meteorological conditions. The study was based on five main local varieties in three experimental stations (early-maturing variety: Zengyu1317, Hongshuo298, Keyu15; medium-maturing variety: Xianyu335; late-maturing variety: Danyu405) in Northeast China from 2018 to 2021. The results showed that: (1) the average starch content (67.7%) and crude protein content (9.1%) of early-maturing variety maize and the crude fiber content (3.3%) and crude fat content (3.6%) of late-maturing variety maize were the highest in Northeast China; (2) the sowing date had no significant effect on the starch content, but significantly affected the crude protein and crude fiber contents, the kernel protein content of early-maturing variety maize was the highest when the sowing date was delayed for 5 days (9.8%), and the crude fiber content of medium-maturing and late-maturing variety maize (4.3% and 5.39%, respectively) was the highest when the sowing date was advanced by 10 days; (3) during the reproductive growth stage, the more light and heat resources, the less starch content and crude protein content and the more crude fat content; when the diurnal temperature range increased by 1 °C, the crude fat content decreased by 0.28%, and the crude protein content increased by 0.77%; for every 100 mm more precipitation, crude fiber and crude protein content decreased by 0.68% and 0.73%, respectively, and fat content increased by 0.15%. Our results provide a meaningful reference for maize production to cope with climate change and improve kernel quality.

Xinjiang is currently the most dominant cotton (Gossypium hirsutum L.)‐growing region in China and possesses abundant radiation resource. The cultivation techniques such as wide and narrow row‐spacing and high density are widely adopted to obtain high cotton yield in the region. However, the region is facing some problems including poor light transmittance in the field and low exploitation for light resources under the current planting pattern which impedes further growth in cotton yields. Therefore, it is essential to develop some cultivation practices to increase radiation use efficiency (RUE) and cotton yields in Xinjiang. Here we conducted a field experiment to quantify the effects of row spacing pattern and plant density on RUE, intercepted photosynthetically active radiation from May to August (IRAR_5–8), and lint yield during 2017 and 2018. In this study, we designed two row‐spacing configurations (R₁, wide and narrow configuration, 66 cm + 10 cm; R₂, uniform row‐spacing configuration, 76 cm) and six plant densities (4.5, 9.0, 13.5, 18.0, 22.5, and 27.0 plants m⁻²). The RUE, lint yield, and number of bolls were higher in R₂ than R₁ by 4.1–5.9, 2.5–4.8, and 9.1–14.2%, respectively. The RUE significantly increased with plant density, but lint yield stabilized at 18.0 plants m⁻². Moreover, RUE had more significant positive effects on boll number and lint yield. Overall, we found that R₂ combined with optimal plant densities (13.5–18.0 plants m⁻²) would be an effective strategy to achieve higher RUE and yields in the Xinjiang cotton system.

Ridge–furrow planting is often applied in semi-arid regions to reduce the drought risk on crop yield under rain-fed conditions. Sunflower (Helianthus annuus L.) is widely planted in northern China and how to reduce the drought risk on sunflower production remains a significant issue. A three-year field experiment with seven treatments (a flat plot without mulching, three plastic film-mulching treatments and three non-film-mulching treatments with different ridge–furrow ratios (1.0 m:1.0 m, 1.0 m:0.5 m and 0.5 m:1.0 m)) was conducted to study the effects of the ridge–furrow rainwater harvesting system on the rain-fed sunflower. The results showed that the sunflowers in the film-mulched treatment with the larger ridge–furrow ratio (1.0 m:0.5 m) (M1R2) had greater growth advantage under drought conditions. In the dry year, M1R2 improved the yield and water use efficiency by 11.9%–107.5% and 13.8%–120.6%, respectively, and reduced the blight grain rate by 21.5%–32.5% with less evapotranspiration (ET) compared to other treatments. Based on the historical climatological data, the guarantee rate of sunflower water requirement for M1R2 was about 75%, while the guarantee rates for the other two film-mulched treatments were only about 40% and 50%. Based on the effects of drought resilience and the characteristics of precipitation, M1R2 is recommended to be the relatively optimal treatment for sunflower production in regions with similar climatic conditions to Wuchuan County in northern China.

Global warming and dimming/brightening have significant implications for crop systems and exhibit regional variations. It is important to clarify the changes in regional thermal and solar radiation resources and estimate the impacts on potential crop production spatially and temporally. Based on daily observation data during 1961–2015 in the North China Plain (NCP), the impacts of climate change associated with climate warming and global dimming/brightening on potential light–temperature productivity (PTP) of summer maize were assessed in this study. Results show that the NCP experienced a continuous warming and dimming trend in maize growing season during the past 55 years, and both ATT10 and solar radiation had an abrupt change in the mid-1990s. The period of 2000–2015 was warmer and dimmer than any other previous decade. Assuming the maize growing season remains unchanged, climate warming would increase PTP of summer maize by 4.6% over the period of 1961–2015, which mainly occurred in the start grain filling–maturity stage. On the other hand, as negative contribution value of solar radiation to the PTP was found in each stage, dimming would offset the increase of PTP due to warming climate, and lead to a 15.6% reduction in PTP in the past 55 years. This study reveals that the changes in thermal and solar radiation have reduced the PTP of summer maize in the NCP. However, the actual maize yield could benefit more from climate warming because solar radiation is not a limiting factor for the current low production level.

Based on 541 Landsat images between 1988 and 2016, the normalized difference vegetation indices (NDVIs) of the wetland vegetation at Xitugou (XTG) and Wowachi (WWC) inside the Dunhuang Yangguan National Nature Reserve (YNNR) in northwest China were calculated for assessing the impacts of climate change on wetland vegetation in the YNNR. It was found that the wetland vegetation at the XTG and WWC had both shown a significant increasing trend in the past 20–30 years and the increase in both the annual mean temperature and annual peak snow depth over the Altun Mountains led to the increase of the wetland vegetation. The influence of the local precipitation on the XTG wetland vegetation was greater than on the WWC wetland vegetation, which demonstrates that in extremely arid regions, the major constraint to the wetland vegetation is the availability of water in soils, which is greatly related to the surface water detention and discharge of groundwater. At both XTG and WWC, the snowmelt from the Altun Mountains is the main contributor to the groundwater discharge, while the local precipitation plays a lesser role in influencing the wetland vegetation at the WWC than at the XTG, because the wetland vegetation grows on a relatively flat terrain at the WWC, while it grows on a stream channel at the XTG.

Understanding the impacts of future climate change on the grassland ecosystems of Inner Mongolia is important for adaptation of natural resource planning, livestock industries and livelihoods. The CENTURY model was validated against observed climate data from 1981 to 2010 for 16 sites. It simulated grass productivity and soil fertility with acceptable agreement, with the coefficient of the root-mean-square error calculated as 41.0% for biomass and 19.5% for soil organic carbon. The model was then used to assess changes to 2100 in aboveground biomass and soil organic carbon under two different climate-change scenarios that were developed for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. The first scenario, RCP4.5 is an intermediate scenario for climate change, incorporating policies and technologies that stabilise growth in greenhouse-gas emissions. The second, RCP8.5, assumes continuing, high demand for energy and increasing greenhouse-gas emissions. Aboveground biomass of meadow and desert steppes responded positively to both scenarios, whereas the typical steppe showed a negative response to RCP4.5 but a positive response to RCP 8.5. Soil organic carbon showed a negative response for all steppe types. The simulations indicated that aboveground biomass and soil organic carbon of Inner Mongolian steppes were sensitive to projected emission scenarios. The CENTURY model predicted aboveground biomass to be 8.5% higher in the longer term (2081–2100) than baseline (1986–2005) under RCP4.5, and 24.3% higher under RCP8.5. Soil organic carbon was predicted to undergo small but significant decreases on average across all sites (1.2% for RCP4.5. 2.9% for RCP8.5). Our results could help decision makers to appreciate the consequences of climate change and plan adaptation strategies.

Extreme weather frequently causes torrential rains and flooding in modern cities, e.g., Beijing, which are much sensitive and fragile to flooding disasters because of high population density. In this study, we aimed to quantify the temporal and spatial distribution of extreme precipitation in Qinghe Basin in Beijing and to develop optimal flood management thresholds by using precipitation records from 1986 to 2014 in two sites of the region. The time that maximum precipitation occurs in a year differed temporally and spatially and mainly concentrated in July and August. Extreme precipitation amount covered 41.7% of total precipitation in a month during flood season. Rain days of rainstorms were on average 1.7 d and 87% of them concentrated in July and August and were more in upstream than that in downstream. Precipitation intensity (SDII) during flood season was on average 11.7 mm d^–1 and highest (15.1 mm d^–1) in July. SDII during critical flood control period increased in upstream during recent 30 years and implied a high flood risk in the future. The spatial distribution of precipitation intensity was significantly different. Our results at basin level would help city authorities designing optimal flood control constructions, drainage facilities, and warning systems.