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The increasing global warming trend has resulted in the mass loss of most glaciers. The Urumqi Vally, located in the dry and cold zone of China, and its widely dispersed glaciers are significant to the regional ecological environment, oasis economic development, and industrial and agricultural production. This is representative of glaciers in Middle Asia and represents one of the world's longest observed time series of glaciers, beginning in 1959. The Urumqi Headwater Glacier No. 1 (UHG-1) has a dominant presence in the World Glacier Monitoring Service (WGMS). This paper supplies a comprehensive analysis of past studies and future modeling of glacier changes in the Urumqi Valley. It has received insufficient attention in the past, and the mass balance of UHG-1 was used to verify that the geodetic results and the OGGM model simulation results are convincing. The main conclusions are: The area of 48.68 ± 4.59 km2 delineated by 150 glaciers in 1958 decreased to 21.61 ± 0.27 km2 delineated by 108 glaciers in 2022, with a reduction of 0.47 ± 0.04 km2·a−1 (0.96% a−1 in 1958–2022). The glacier mass balance by geodesy is −0.69 ± 0.11 m w.e.a−1 in 2000–2022, which is just deviating from the measured result (−0.66 m w.e.a−1), but the geodetic result in this paper can be enough to reflect the glacier changes (−0.65 ± 0.11 m w.e.a−1) of the URB in 2000–2022. The future loss rate of area and volume will undergo a rapid and then decelerating process, with the fastest and slowest inflection points occurring around 2035 and 2070, respectively. High temperatures and large precipitation in summer accelerate glacier loss, and the corresponding lag period of glacier change to climate is about 2–3 years. [ABSTRACT FROM AUTHOR]

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Copyright of Journal of Irrigation & Drainage is the property of Journal of Irrigation & Drainage Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The agro-pastoral transitional zone in northern China is an important agricultural and pastoral production base. This study focuses on the eastern section of the agro-pastoral transitional zone in northern China. Combined with spatio-temporal analysis, stepwise regression, and gray relation analysis, we analyzed the average annual growth rate, spatio-temporal changes, and influencing factors of agricultural and pastoral production in the study area during 2000–2020. The results show that, in the past 20 years, the agricultural and pastoral production of the 50 municipal districts and counties has significantly changed, among which the agricultural production of 38 municipal districts and counties has shown an extremely significant increase. Generally, the growth rate of agricultural production is higher than that of pastoral production. Agricultural and pastoral production in the study area is influenced by socio-economic and land use/cover factors, with an average correlation degree of 0.79 and 0.88, respectively. Climate change affects agricultural production in agricultural counties, with a correlation degree of 0.85. The results of this research provide valuable insights into understanding the long-term temporal and spatial changes in agricultural and pastoral production and help to develop sound agriculture and pastoral management practices in the eastern section of the agro-pastoral transitional zone in Northern China. [ABSTRACT FROM AUTHOR]

This study explores the intricate relationship between agricultural productivity and the pursuit of a just energy transition in China. As the world's largest emitter of greenhouse gases and a nation grappling with environmental degradation and socio-economic disparities, China faces the imperative to transition toward a more sustainable and equitable energy system. This paper investigates the role of agriculture in this transition, recognizing its pivotal position as a significant emitter of greenhouse gases while also being vulnerable to the impacts of climate change. By examining the potential synergies and conflicts between agricultural productivity enhancement and the goals of reducing emissions and promoting social justice, this study aims to shed light on strategies that can effectively align agricultural development with the objectives of a just energy transition. The result indicates substantial internal disparities and strong agglomeration effects (referring to areas with similar agricultural total factor productivity) within China's agricultural total factor productivity distribution. Over the past 17 years (2005–2021), the average agricultural productivity has shown a commendable upward trend, marking a 2.8% growth rate. This increase signifies ongoing efforts and advancements in the agricultural sector, leading to improved productivity levels. Our results also show a significant positive spatial correlation in agricultural total factor productivity, suggesting a tendency for spatial agglomeration. The years 2005 and 2021 stand out as periods marked by significant adverse effects resulting from the interplay of diverse factors on agricultural productivity. By integrating findings from various sectors, this study provides insights into the complex interplay between agriculture and energy transition, emphasizing the need for integrated, holistic approaches that prioritize sustainability, fairness, and resilience in China's pursuit of a just energy future. • This study explores the relationship between agricultural productivity and energy transition. • Our aim is to align agricultural development with the objectives of energy transition. • The analysis connects productivity and equity. • We emphasize sustainability and resilience in China's pursuit of a just energy future. [ABSTRACT FROM AUTHOR]

The quest to eradicate poverty, central to the United Nations Sustainable Development Goals (SDGs), poses a significant global challenge. Advancement in sustainable rural development is critical to this effort, requiring the seamless integration of environmental, economic, and governmental elements. Previous research often omits the complex interactions among these factors. Addressing this gap, this study evaluates sustainable rural development in China by examining the interconnection between agricultural production and government-led poverty reduction, with annual rainfall considered an influential factor of climate change impacts on these sectors and overall sustainability. Utilizing a Meta-frontier entropy network dynamic Directional Distance Function (DDF) within an exogenous Data Envelopment Analysis (DEA) model, we categorize China's 27 provinces into southern and northern regions according to the Qinling-Huaihe line for a comparative study of environmental, economic, and governmental efficiency. This innovative approach overcomes the limitations of previous static analyses. The findings reveal: (1) Rainfall, as an exogenous variable, significantly affects agricultural production efficiency. (2) The overall efficiency in both southern and northern regions increases when accounting for rainfall. (3) Government effectiveness in poverty reduction is comparatively lower in the northern region than in the southern region when rainfall is considered. These insights underscore the importance of including climatic variables in sustainable development policies and emphasize the need for region-specific strategies to bolster resilience against climatic challenges. [ABSTRACT FROM AUTHOR]

Northeast China (NEC) is the most prominent grain‐producing region in China. However, it is currently facing significant impacts from climate change. Since the climate‐related impacts on crop yield in this region are a major concern for society in the future, quantifying climate change impacts on crop yields in NEC is essential to ensure future food security. This study aimed to quantify the effects of future climate change on crop yields in NEC and explore adaptation strategies using the Crop Growth Model (PCSE) driven by downscaled CMIP6 climate projections under four Shared Socioeconomic Pathways (SSPs) scenarios during 2015–2100. Results showed that there could be average reductions in crop yields of 21.4% for maize and 4.2% for soybean by the year 2100 under SSP585 compared to the 2015 baseline. The increasing temperature was the dominant factor in reducing yields, although elevated CO2 and precipitation offered partial compensation. The optimized planting date brought noticeable benefits for rice and soybean but had limited effects on maize due to heat stress. Relocating rice expansion eastward and implementing earlier planting increased yields by up to 50% but adversely decreased soybean and maize due to competition. This study enriches our comprehension of climate change impacts on NEC agriculture, while also quantifying potential benefits and constraints of evaluated adaptations. The proposed adaptations may help mitigate projected yield declines in other key agricultural regions across the globe. Adjusting crop management practices to capitalize on changing climate factors shows promise as a strategy for sustaining production globally. Plain Language Summary: Northeast China (NEC) is essential for achieving food accessibility and food security in China, but its agricultural production is seriously threatened by climate change. This study investigated how climate change could impact maize, rice, and soybean crop yields in this region from 2015 to 2100, using the PCSE crop model and forcing from the international Coupled Model Intercomparison Project 6 (CMIP6) climate projections. Simulation results suggested rising temperatures would negatively affect crop yields, especially for maize. Increased carbon dioxide and rainfall partially offset these losses. By 2100, average declines were projected for maize (−21%) and soybeans (−4%), respectively. Altering planting dates to match crop needs was an effective adaptation to boost yields, with rice benefiting the most. Relocating rice production eastward and expanding its area substantially increased simulated rice yields (+62%) but decreased other crops due to competition (−32% maize, −28% soybeans). Even with adaptations, some areas still showed yield declines, indicating extra measures may be needed to maintain production. Overall, this study suggests significant risks to crop yields from climate change in Northeast China, with adaptations like optimized planting and strategic crop relocation able to mitigate some but not all of the projected impacts. Key Points: Rising temperatures negatively impacted simulated future crop yields, especially for maizeAdjusting planting dates boosted yields for rice and soybeans but had limited benefits for maizeRelocating and expanding the rice area increased yields substantially [ABSTRACT FROM AUTHOR]

The possible influence of global climate changes on agricultural production is becoming increasingly significant, necessitating greater attention to improving agricultural production in response to temperature rises and precipitation variability. As one of the main winter wheat-producing areas in China, the temporal and spatial distribution characteristics of precipitation, accumulated temperature, and actual yield and climatic yield of winter wheat during the growing period in Shanxi Province were analysed in detail. With the utilisation of daily meteorological data collected from 12 meteorological stations in Shanxi Province in 1964–2018, our study analysed the change in winter wheat yield with climate change using GIS combined with wavelet analysis. The results show the following: (1) Accumulated temperature and precipitation are the two most important limiting factors among the main physical factors that impact yield. Based on the analysis of the ArcGIS geographical detector, the correlation between the actual yield of winter wheat and the precipitation during the growth period was the highest, reaching 0.469, and the meteorological yield and accumulated temperature during this period also reached its peak value of 0.376. (2) The regions with more suitable precipitation and accumulated temperature during the growth period of winter wheat in the study area had relatively high actual winter wheat yields. Overall, the average actual yield of the entire region showed a significant increasing trend over time, with an upward trend of 47.827 kg ha−1 yr−1. (3) The variation coefficient of winter wheat climatic yield was relatively stable in 2008–2018. In particular, there were many years of continuous reduction in winter wheat yields prior to 2006. Thereafter, the impact of climate change on winter wheat yields became smaller. This study expands our understanding of the complex interactions between climate variables and crop yield but also provides practical recommendations for enhancing agricultural practices in this region [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Agricultural production depends on local agroclimatic conditions to a great extent, affected by ENSO and other ocean-atmospheric climate modes. This paper analyzed the spatio-temporal distributions of climate elements in the Jianghan Plain (JHP), Central China, and explored the impacts from teleconnection patterns, aimed at providing references for dealing with climate change and guiding agricultural activities. Both linear and multifactorial regression models were constructed based on the frequentist quantile regression and Bayesian quantile regression method, with the daily meteorological data sets of 17 national stations in the plain and teleconnection climate characteristic indices. The results showed that precipitation in JHP had stronger spatial variability than evapotranspiration. El Niño probably induced less precipitation in summer while the weakening Arctic Oscillation might lead to more summertime precipitation. The Nash-Sutcliffe efficiency (NSE) of the multifactorial and linear regression model at the median level were 0.42–0.56 and 0.12–0.18, respectively. The mean relative error (MRE) ranged −2.95–−0.26% and −7.83–0.94%, respectively, indicating the much better fitting accuracy of the multiple climatic factors model. Meanwhile it confirmed that the agricultural climate in JHP was under the influence from multiple teleconnection patterns. [ABSTRACT FROM AUTHOR]

The increased frequency of climate extremes associated with ongoing climate change has the potential for significant impacts on maize grain yield in maize-producing regions worldwide. In this study, we used a modeling approach to investigate the effects of different types of climatic extremes on maize grain yield in Northeast China. We combined annual mean air temperature and accumulated precipitation data and divided the climate years into 9 categories, using the 10th and 90th percentiles as extreme thresholds. The climate data were represented by 1 normal climate type, 4 individual climate extremes, and 4 combined climate extremes. Changes in the frequencies of climate extremes and their impacts on maize grain yields were analyzed for two 30-year periods (period I: 1960–1989; period II: 1990–2019) using the Agricultural Production Systems sIMulator (APSIM-Maize). Compared with period I, the occurrences of the normal climate and all 3 cold-related climate extremes (i.e., cold-normal, cold-humid, and cold-dry) decreased during period II, while occurrences of the other climate extremes increased. Moreover, according to the APSIM-Maize model, the estimated yield in the years with a normal climate decreased by 4.01%; the 3 cold-related climate extremes increased yields by 26.56%, 12.10%, and 6.68%, respectively; the 2 warm-related climate extremes (warm-normal and warm-dry) and normal-humid years decreased estimated yields by 6.39%, 24.12%, and 5.10%, respectively. The increase in the occurrence of warm-humid years increased the estimated yield by 11.69%. This work confirms the adverse effects of warmer temperatures in the absence of excess rainfall on grain yield and highlights the importance of extremely dry or wet conditions under normal temperature conditions. [ABSTRACT FROM AUTHOR]

Adaptation to future climate change with limited water resources is a major global challenge to sustainable and sufficient crop production. However, the large-scale responses of the crop water footprint and its associated benchmarks under various irrigation regimes to future climate change scenarios remain unclear. The present study quantified the responses of the maize and wheat water footprint (WF) per unit yield (m 3 t -1) as well as the corresponding WF benchmarks under two Representative Concentration Pathway (RCP) scenarios, RCP2.6 and RCP8.5, in the 2030s, 2050s, and 2080s at a 5 arcmin grid level in China. The AquaCrop model with the outputs of six global climate models from Phase 5 of the Coupled Model Intercomparison Project (CMIP5) as its input data was used to simulate the WFs of maize and wheat. The differences among rain-fed wheat and maize and furrow-, micro-, and sprinkler-irrigated wheat and maize were identified. Compared with the baseline year (2013), the maize WF will increase under both RCP2.6 and RCP8.5 (by 17 % and 13 %, respectively) until the 2080s. The wheat WF will increase under RCP2.6 (by 12 % until the 2080s) and decrease (by 12 %) under RCP8.5 until the 2080s, with a higher increase in the wheat yield and a decrease in the wheat WF due to the higher CO 2 concentration in 2080s under RCP8.5. The WF will increase the most for rain-fed crops. Relative to rain-fed crops, micro-irrigation and sprinkler irrigation result in the smallest increases in the WF for maize and wheat, respectively. These water-saving management techniques will mitigate the negative impact of climate change more effectively. The WF benchmarks for maize and wheat in the humid zone (an approximate overall average of 680 m 3 t -1 for maize and 873 m 3 t -1 for wheat at the 20th percentile) are 13 %–32 % higher than those in the arid zone (which experiences an overall average of 601 m 3 t -1 for maize and 753 m 3 t -1 for wheat). The differences in the WF benchmarks among various irrigation regimes are more significant in the arid zone, where they can be as high as 57 % for the 20th percentile: WF benchmarks of 1020 m 3 t -1 for sprinkler-irrigated wheat and 648 m 3 t -1 for micro-irrigated wheat. Nevertheless, the WF benchmarks will not respond to climate changes as dramatically as the WF in the same area, especially in areas with limited agricultural development. The present study demonstrated that the observed different responses to climate change in terms of crop water consumption, water use efficiency, and WF benchmarks under different irrigation regimes cannot be ignored. It also lays the foundation for future investigations into the influences of irrigation methods, RCPs, and crop types on the WF and its benchmarks in response to climate change in all agricultural regions worldwide. [ABSTRACT FROM AUTHOR]

Efficient utilization of light and heat resources is an important part of cleaner production. However, exploring the changes in light and heat resources utilization potential in paddy under future climate change is essential to make full use of the potential of rice varieties and ensure high-efficient, high-yield, and high-quality rice production, which has been seldom conducted. In our study, a process-based crop model (CERES-Rice) was calibrated and validated based on experiment data from the Songnen Plain of China, and then driven by multiple global climate models (GCMs) from the coupled model inter-comparison project (CMIP6) to predict rice growth period, yield, and light and heat resources utilization efficiency under future climate change conditions. The results indicated that the rice growth period would be shortened, especially in the high emission scenario (SSP585), while rice yield would increase slightly under the low and medium emission scenarios (SSP126 and SSP245), it decreased significantly under the high emission scenario (SSP585) in the long term (the 2080s) relative to the baseline of 2000–2019. The light and temperature resources utilization (ERT), light utilization efficiency (ER), and heat utilization efficiency (HUE) were selected as the light and heat resources utilization evaluation indexes. Compared with the base period, the mean ERT in the 2040s, 2060s, and 2080s were −6.46%, −6.01%, and −6.03% under SSP126, respectively. Under SSP245, the mean ERT were −7.89%, −8.41%, and −8.27%, respectively. Under SSP585, the mean ERT were −6.88%, −13.69%, and −28.84%, respectively. The ER would increase slightly, except for the 2080s under the high emission scenario. Moreover, the HUE would reduce as compared with the base period. The results of the analysis showed that the most significant meteorological factor affecting rice growth was temperature. Furthermore, under future climate conditions, optimizing the sowing date could make full use of climate resources to improve rice yield and light and heat resource utilization indexes, which is of great significance for agricultural cleaner production in the future. [ABSTRACT FROM AUTHOR]

The past few decades of extreme drought and flooding caused by changing climate conditions have significantly affected agricultural production globally. This study focuses on two vital crops in China—maize and rice—and provides a comprehensive analysis of how these crops are affected by climate change-induced factors over the periods 1978Q1–2015Q4. Four key findings were obtained. First, using a nonparametric approach to estimate actual and observed trends of climatic variables, the results show a significant positive trend in average temperature from February to October. On the other hand, seasonal temperature increases during spring, summer, and autumn. Second, the results show no significant change in the monthly, seasonal, and annual rainfall patterns when examined over the study period. Third, using an autoregressive distributed lag (ARDL) model, we find that while temperature and rainfall do not significantly support rice production in the long and short run, they play a substantial role in maize production in China. Finally, we find no significant difference in the results for rice when the quantile regression (QR) technique that controls for distributional asymmetry effects is employed. However, the impact of temperature on maize decreases at higher quantiles. Given the outcomes of our study, we argue that an advanced irrigation system is crucial and must be encouraged to minimize the effects of climate change on crop production. [ABSTRACT FROM AUTHOR]

Climate change-induced drought poses a serious negative impact on global crop production and food security. The Huang Huai Hai (HHH) Plain, one of the most important grain production areas in China, is heavenly stricken by drought. Motivated by formulating drought risk prevention strategies that adapt to climate change on the HHH Plain, therefore, the present study aims to quantitatively evaluate the winter wheat drought risk under multiple climate scenarios using the Environmental Policy Impact Climate (EPIC) model. Based on the well-validated EPIC model, the drought hazard intensity (dHI), physical vulnerability (pV), and drought risk (dR) of the HHH Plain from 2010 to 2099 are assessed. Temporally, the dR showed an increasing trend in the long term, the high dR areas increased by 0.63% and 1.18% under the RCP4.5 and RCP8.5 scenarios, respectively. Spatially, dR showed a pattern of high in the south and low in the north whether under RCP4.5 or RCP8.5 scenario. Comparatively, the dR was 0.211 under the RCP4.5 scenario which was slightly higher than that under the RCP8.5 scenario, i.e. 0.207. The Huanghuai Plain agricultural subregion will be a high dHI-pV-dR region. The temperature increase might be the main factor affecting the wheat drought risk. [ABSTRACT FROM AUTHOR]

Climate change has and will continue to exert significant effects on social economy, natural environment, and human life. Research on the climatic suitability of crops is critical for mitigating and adapting to the negative impacts of climate change on crop production. In the study, we developed the climate suitability model of maize and investigated the climate suitability of summer maize during the base period (1981–2010) and two future periods of 2031–2060 (2040s) and 2071–2100 (2080s) in the North China Plain (NCP) based on BCC-CSM2-MR model (BCC) from the Coupled Model Comparison Program (CMIP6) under two Shared Socioeconomic Pathways (SSP) 245 and SSP585. The phenological shift of maize under future climate scenarios was simulated by the Agricultural Production Systems Simulator (APSIM). The results showed that the root mean square errors (RMSE) between observations and projections for sunshine suitability (SS), temperature suitability (ST), precipitation suitability (SP), and integrated climate suitability (SZ) during the whole growth period were 0.069, 0.072, 0.057, and 0.040, respectively. Overall, the BCC projections for climate suitability were in suitable consistency with the observations in the NCP. During 1981–2010, the SP, ST, and SZ were high in the north of the NCP and low in the south. The SP, ST, and SZ showed a downward trend under all the future climate scenarios in most areas of NCP while the SS increased. Therein, the change range of SP and SS was 0–0.1 under all the future climate scenarios. The ST declined by 0.1–0.2 in the future except for the decrease of more than 0.3 under the SSP585 scenario in the 2080s. The decrease in SZ in the 2040s and 2080s under both SSP scenarios varied from 0 to 0.2. Moreover, the optimum area decreases greatly under future scenarios while the suitable area increases significantly. Adjusting sowing data (SD) would have essential impacts on climate suitability. To some extent, delaying SD was beneficial to improve the climate suitability of summer maize in the NCP, especially under the SSP585 scenario in the 2080s. Our findings can not only provide data support for summer maize production to adapt to climate change but also help to propose agricultural management measures to cope with future climate change. [ABSTRACT FROM AUTHOR]

Climate change and farmland environmental pollution have put greater pressure on the sustainability of agricultural production. Based on the provincial panel data of mainland China from 1978 to 2018, climate variables such as precipitation, temperature, and sunshine hours are included into the input indicators, and agricultural non-point source pollution and carbon emissions are taken as undesirable outputs, the agricultural production efficiency (APE) under the dual constraints of climate change and the resource environment was estimated by the super slacks-based measure (SBM)-undesirable model. On the basis of the trajectory of the imbalanced spatiotemporal evolution of APE shown by Kernel density estimation and the standard deviational ellipse (SDE)–center of gravity (COG) transfer model, the spatial convergence model was used to test the convergence and differentiation characteristics of APE. Under the dual constraints, APE presents a "bimodal" distribution with a stable increase in fluctuation, but it is still at a generally low level and does not show polarization, among which the APE in the northeast region is the highest. The COG of APE tends to transfer towards the northeast, and the coverage of the SDE is shrinking, so the overall spatial pattern is characterized by a tendency of clustering towards the north in the north-south direction and a tendency of imbalance in the east-west direction. APE has significant spatial convergence, and there is a trend of "latecomer catching-up" in low-efficiency regions. The introduction of spatial correlation accelerates the convergence rate and shortens the convergence period. The convergence rate is the highest in the central and western regions, followed by that in the northeastern region, and the convergence rate is the lowest in the eastern region. In addition, the convergence rate in different time periods has a phase change. The process of improving the quality and efficiency of agricultural production requires enhancing the adaptability of climate change, balancing the carrying capacity of the resource environment, and strengthening inter-regional cooperation and linkage in the field of agriculture. [ABSTRACT FROM AUTHOR]