Urbanization has resulted in growing ecological pressures on cities,necessitating assessments of urban ecological quality.Long-term characterization of regional dynamics and drivers is critical for environmental man-a...Urbanization has resulted in growing ecological pressures on cities,necessitating assessments of urban ecological quality.Long-term characterization of regional dynamics and drivers is critical for environmental man-agement.This study proposes an enhanced ecological quality model(MRSEI)incorporating vegetation cover and EVI rather than just NDVI.The MRSEI model was applied to analyse ecological quality in Yulin City during 2000-2018 using Landsat TM/OLI data on Google Earth Engine.Geographic detectors also quantified anthropo-genic and environmental influences on the study area.The results are summarized as follows:(1)MRSEI showed an average correlation coefficient of 0.840 with other indices,demonstrating higher representativeness than indi-vidual components.The principal component analysis indicated a 12.88%increase in explained variance.MRSEI also exhibited significantly improved identification of roads,villages,and unused lands over RSEI,better matching ground conditions,and suitability for regional ecological assessment.(2)During 2000-2020,the average MRSEI in Yulin City was 0.481,peaking at 0.518 in 2018,indicating general ecological improvement over time.Spatially,conditions were better in the southeast than northwest.While 38.81%of the area showed significant improvement,10.15%exhibited significant deterioration,concentrated in western Dingbian and Jingbian counties,highlighting areas requiring enhanced protection.(3)Ecological conditions in Yulin City remained stable over time.High-high clusters were concentrated in eastern counties(Qingjian,Wubao,Jia,Fugu)and central lower-altitude areas near Yokoyama and Zizhou.Low-low clusters predominated in the northern Yuyang desert and high-altitude western Dingbian regions.(4)Enhanced vegetation cover had the greatest influence in improving Yulin’s ecological quality.Rainfall was the most impactful environmental driver,while precipitation and land use change interactions showed the strongest combined effects.In contrast,air quality had minimal explanatory power in Yulin City.(5)The MRSEI model significantly impacts the ecological assessment of urban areas,thereby enhancing urban ecological moni-toring accuracy.Moreover,our analysis demonstrates applicability to watershed regions,facilitating comprehensive regional ecological assessment and monitoring.展开更多
With an increase in population and economic development,water withdrawals are close to or even exceed the amount of water available in many regions of the world.Modelling water withdrawals could help water planners im...With an increase in population and economic development,water withdrawals are close to or even exceed the amount of water available in many regions of the world.Modelling water withdrawals could help water planners improve the efficiency of water use,water resources allocation,and management in order to alleviate water crises.However,minimal information has been obtained on how water withdrawals have changed over space and time,especially on a regional or local scale.This research proposes a data-driven framework to help estimate county-level distribution of water withdrawals.Using this framework,spatial statistical methods are used to estimate water withdrawals for agricultural,industrial,and domestic purposes in the Huaihe River watershed in China for the period 1978–2018.Total water withdrawals were found to have more than doubled,from 292.55×10^(8)m^(3) in 1978 to 642.93×10^(8)m^(3) in 2009,and decreased to 602.63×10^(8)m^(3) in 2018.Agricultural water increased from 208.17×10^(8)m^(3) in 1978 to 435.80×10^(8)m^(3) in 2009 and decreased to 360.84×10^(8)m^(3) in 2018.Industrial and domestic water usage constantly increased throughout the 1978–2018 period.In 1978,industrial and domestic demands were 20.35×10^(8)m^(3) and 60.04×10^(8)m^(3),respectively,and up until 2018,the figures were 105.58×10^(8)m^(3) and 136.20×10^(8)m^(3).From a spatial distribution perspective,Moran’s I statistical results show that the total water withdrawal has significant spatial autocorrelation during 1978–2018.The overall trend was a gradual increase in 1978–2010 with withdrawal beginning to decline in 2010–2018.The results of Getis-Ord G_(i)^(*)statistical calculations showed spatially contiguous clusters of total water withdrawal in the Huaihe River watershed during1978–2010,and the spatial agglomeration weakened from 2010 to 2018.This study provides a data-driven framework for assessing water withdrawals to enable a deeper understanding of competing water use among economic sectors as well as water withdrawal modelled with proper data resource and method.展开更多
High-precision polar motion prediction is of great significance for deep space exploration and satellite navigation.Polar motion is affected by a variety of excitation factors,and nonlinear prediction methods are more...High-precision polar motion prediction is of great significance for deep space exploration and satellite navigation.Polar motion is affected by a variety of excitation factors,and nonlinear prediction methods are more suitable for polar motion prediction.In order to explore the effect of deep learning in polar motion prediction.This paper proposes a combined model based on empirical wavelet transform(EWT),Convolutional Neural Networks(CNN)and Long Short Term Memory(LSTM).By training and forecasting EOP 20C04 data,the effectiveness of the algorithm is verified,and the performance of two forecasting strategies in deep learning for polar motion prediction is explored.The results indicate that recursive multi-step prediction performs better than direct multi-step prediction for short-term forecasts within 15 days,while direct multi-step prediction is more suitable for medium and long-term forecasts.In the 365 days forecast,the mean absolute error of EWT-CNN-LSTM in the X direction and Y direction is 18.25 mas and 15.78 mas,respectively,which is 23.5% and 16.2% higher than the accuracy of Bulletin A.The results show that the algorithm has a good effect in medium and long term polar motion prediction.展开更多
High-resolution deep-learning-based remote-sensing imagery analysis has been widely used in land-use and crop-classification mapping. However, the influence of composite feature bands, including complex feature indice...High-resolution deep-learning-based remote-sensing imagery analysis has been widely used in land-use and crop-classification mapping. However, the influence of composite feature bands, including complex feature indices arising from different sensors on the backbone, patch size, and predictions in transferable deep models require further testing. The experiments were conducted in six sites in Henan province from2019 to 2021. This study sought to enable the transfer of classification models across regions and years for Sentinel-2 A(10-m resolution) and Gaofen PMS(2-m resolution) imagery. With feature selection and up-sampling of small samples, the performance of UNet++ architecture on five backbones and four patch sizes was examined. Joint loss, mean Intersection over Union(m Io U), and epoch time were analyzed, and the optimal backbone and patch size for both sensors were Timm-Reg Net Y-320 and 256 × 256, respectively. The overall accuracy and Fscores of the Sentinel-2 A predictions ranged from 96.86% to 97.72%and 71.29% to 80.75%, respectively, compared to 75.34%–97.72% and 54.89%–73.25% for the Gaofen predictions. The accuracies of each site indicated that patch size exerted a greater influence on model performance than the backbone. The feature-selection-based predictions with UNet++ architecture and upsampling of minor classes demonstrated the capabilities of deep-learning generalization for classifying complex ground objects, offering improved performance compared to the UNet, Deeplab V3+, Random Forest, and Object-Oriented Classification models. In addition to the overall accuracy, confusion matrices,precision, recall, and F1 scores should be evaluated for minor land-cover types. This study contributes to large-scale, dynamic, and near-real-time land-use and crop mapping by integrating deep learning and multi-source remote-sensing imagery.展开更多
As total nitrogen(TN)and total phosphorus(TP)pollution is the main source of water pollution in the Huaihe River watershed in China,it is important to understand how TN and TP pollution affect the relationship between...As total nitrogen(TN)and total phosphorus(TP)pollution is the main source of water pollution in the Huaihe River watershed in China,it is important to understand how TN and TP pollution affect the relationship between water supply and demand.Quantifying their impacts and describing the spatiotemporal distribution of these relationships are necessary for furtherly deepening the theory of TN and TP pollution on water bodies,and this information is also particularly essential for managing water resources regionally.In this study,based on the potential water supply,the water demand and the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST)water purification models,we estimated the TN and TP pollution from agricultural fertilizer,livestock and poultry breeding,and rural residents in the Huaihe River watershed and simulated TN and TP impacts on the relationship between water supply and demand.We found that if the impact of TN and TP pollution on water supply was not taken into account,on average,there was excess water supply in 79.20%of the watershed and excess demand in 20.80%of the rest during 1980–2018.Under the TN concentration limit,Grade-Ⅱ(The water quality meets the secondary level of water body qualified in GB3838–2002,classified as Grade-II)water was the main watersupply type in 1980–2018,followed by Grade-Ⅰ and Grade-Ⅲ water.The total water shortage showed an inverted V-shaped trend:first increasing and then decreasing at the same period.The proportion of the water shortage of Grade-I water in the total water shortage was the largest,followed by Grade-Ⅱ and Grade-III water.Areas with excess demand were located on the north bank of Wang-Beng,Yishuhe,and Huxi regions,although the water in these sub-watersheds met the water quality standards of Grade-Ⅰ water.Under the TP concentration limit,Grade-Ⅱ and Grade-Ⅰ water were the main water-supply types.The overall water shortage trend first increased and then decreased,exhibiting an inverted V-shape from 1980 to 2018.The water shortages of Grade-Ⅰ and Grade-Ⅱ water showed similar inverted V-shape trend over time.Areas that met the water quality standard of Grade-Ⅰ included the north banks of Wang-Beng and Huxi regions,where there was a surplus of demand.This paper suggests a way to analyze the interaction between water pollutants and the water supply-demand ratio as the example of TN and TP pollution at a watershed scale,which can broaden water pollution theory for relative water resources departments when water supply and demand will be evaluated.展开更多
The thermal expansion of radio telescopes has been recognized as a significant systematic error in Very Long Baseline Interferometry(VLBI) data analysis. Although the thermal expansion model recommended by Internation...The thermal expansion of radio telescopes has been recognized as a significant systematic error in Very Long Baseline Interferometry(VLBI) data analysis. Although the thermal expansion model recommended by International Earth Rotation Service(IERS) Conventions 2010 can achieve millimeter accuracy for the International VLBI Service for Geodesy and Astrometry(IVS) routine telescopes, both the International Terrestrial Reference Frame 2020(ITRF2020) in preparation and the VLBI2010 project encourage the scientific community to reconsider its modeling. To this end, we developed a monitoring system for the Tianma 13.2 m VLBI Global Observing System(VGOS) telescope. Based on the observed data, we refined the IERS expansion model, with results showing that the accuracy of our modified model was improved by 1.9 times. It suggested that the IERS thermal expansion model can achieve the declared millimeter accuracy, and refining its modeling can meet the requirement of 0.3 mm rms stability of the VGOS antenna reference point for the VLBI2010 project.展开更多
Implementation of payments for watershed services(PWS) has been regarded as a promising approach to coordinating the interests of upstream and downstream ecosystem services stakeholders. There is growing concern about...Implementation of payments for watershed services(PWS) has been regarded as a promising approach to coordinating the interests of upstream and downstream ecosystem services stakeholders. There is growing concern about whether PWS programs have achieved their original environmental goals of improving water quality and quantity, as well as the ancillary objective of increasing the welfare of local people. We start with an overview of PWS schemes and focus on their particularity and implementation mechanisms in China. We proceed to review 62 active PWS cases and examine their environmental performance in detail. The resulting findings show that PWS schemes have been able to reduce water pollution to some extent by establishing collaborative upstream/downstream watershed management policies, thereby improving water quality and quantity, as well as by making government officials more responsible for water resource management. In addition, their continued effectiveness in light of present challenges such as water-quality data availability is discussed. Chinese PWS schemes and their implementation mechanisms also provide information useful in monitoring environmental outcomes and guiding future designs of PWS programs in other regions.展开更多
A strongly declining aerosol radiative effect has been observed in China since 2013 after implementing the clean air action,yet its impact on wheat(Triticum aestivum L.)production remains unclear.We use satellite meas...A strongly declining aerosol radiative effect has been observed in China since 2013 after implementing the clean air action,yet its impact on wheat(Triticum aestivum L.)production remains unclear.We use satellite measures and a biophysical crop model to assess the impact of aerosol-induced radiative perturbations on winter wheat production in the agricultural belt of Henan province from 2013 to 2018.After calibrating parameters with the extended Fourier Amplitude Sensitivity Test(EFAST)and the generalized likelihood uncertainty estimation(GLUE)method,the DSSAT CERES-Wheat model was able to simulate crop biomass and yield more accurately.We found that the aerosol negatively impacted wheat biomass by 21.87%and yield by 22.48%from 2006 to 2018,and the biomass effects from planting to anthesis were more significant compared to anthesis to maturity.Due to the strict clean air action,under all-sky conditions,the surface solar shortwave radiation(SSR)in 2018 increased by about 7.08%over 2006-2013 during the wheat growing seasons.As a result of the improvement of crop photosynthesis,winter wheat biomass and yield increased by an average of 5.46%and 2.9%,respectively.Our findings show that crop carbon uptake and yield will benefit from the clean air action in China,helping to ensure national food and health security.展开更多
基金The High-Resolution Satellite Project of the State Administration of Science,Technology,and Industry for National Defense of the PRC (80Y50G19-9001-22/23)The Major Research Projects of the Ministry of Education (16JJD770019)+1 种基金The Henan Provincial Key R&D and Promotion Special Project (Science and Technology Research)(242102321122)The National Natural Science Foundation of China (U21A2014)。
文摘Urbanization has resulted in growing ecological pressures on cities,necessitating assessments of urban ecological quality.Long-term characterization of regional dynamics and drivers is critical for environmental man-agement.This study proposes an enhanced ecological quality model(MRSEI)incorporating vegetation cover and EVI rather than just NDVI.The MRSEI model was applied to analyse ecological quality in Yulin City during 2000-2018 using Landsat TM/OLI data on Google Earth Engine.Geographic detectors also quantified anthropo-genic and environmental influences on the study area.The results are summarized as follows:(1)MRSEI showed an average correlation coefficient of 0.840 with other indices,demonstrating higher representativeness than indi-vidual components.The principal component analysis indicated a 12.88%increase in explained variance.MRSEI also exhibited significantly improved identification of roads,villages,and unused lands over RSEI,better matching ground conditions,and suitability for regional ecological assessment.(2)During 2000-2020,the average MRSEI in Yulin City was 0.481,peaking at 0.518 in 2018,indicating general ecological improvement over time.Spatially,conditions were better in the southeast than northwest.While 38.81%of the area showed significant improvement,10.15%exhibited significant deterioration,concentrated in western Dingbian and Jingbian counties,highlighting areas requiring enhanced protection.(3)Ecological conditions in Yulin City remained stable over time.High-high clusters were concentrated in eastern counties(Qingjian,Wubao,Jia,Fugu)and central lower-altitude areas near Yokoyama and Zizhou.Low-low clusters predominated in the northern Yuyang desert and high-altitude western Dingbian regions.(4)Enhanced vegetation cover had the greatest influence in improving Yulin’s ecological quality.Rainfall was the most impactful environmental driver,while precipitation and land use change interactions showed the strongest combined effects.In contrast,air quality had minimal explanatory power in Yulin City.(5)The MRSEI model significantly impacts the ecological assessment of urban areas,thereby enhancing urban ecological moni-toring accuracy.Moreover,our analysis demonstrates applicability to watershed regions,facilitating comprehensive regional ecological assessment and monitoring.
基金Under the auspices of the National Natural Science Foundation of China(No.71203200)the National Social Science Fund Project(No.20&ZD138)+1 种基金the National Science and Technology Platform Construction Project(No.2005DKA32300)the Major Research Projects of the Ministry of Education(No.16JJD770019)。
文摘With an increase in population and economic development,water withdrawals are close to or even exceed the amount of water available in many regions of the world.Modelling water withdrawals could help water planners improve the efficiency of water use,water resources allocation,and management in order to alleviate water crises.However,minimal information has been obtained on how water withdrawals have changed over space and time,especially on a regional or local scale.This research proposes a data-driven framework to help estimate county-level distribution of water withdrawals.Using this framework,spatial statistical methods are used to estimate water withdrawals for agricultural,industrial,and domestic purposes in the Huaihe River watershed in China for the period 1978–2018.Total water withdrawals were found to have more than doubled,from 292.55×10^(8)m^(3) in 1978 to 642.93×10^(8)m^(3) in 2009,and decreased to 602.63×10^(8)m^(3) in 2018.Agricultural water increased from 208.17×10^(8)m^(3) in 1978 to 435.80×10^(8)m^(3) in 2009 and decreased to 360.84×10^(8)m^(3) in 2018.Industrial and domestic water usage constantly increased throughout the 1978–2018 period.In 1978,industrial and domestic demands were 20.35×10^(8)m^(3) and 60.04×10^(8)m^(3),respectively,and up until 2018,the figures were 105.58×10^(8)m^(3) and 136.20×10^(8)m^(3).From a spatial distribution perspective,Moran’s I statistical results show that the total water withdrawal has significant spatial autocorrelation during 1978–2018.The overall trend was a gradual increase in 1978–2010 with withdrawal beginning to decline in 2010–2018.The results of Getis-Ord G_(i)^(*)statistical calculations showed spatially contiguous clusters of total water withdrawal in the Huaihe River watershed during1978–2010,and the spatial agglomeration weakened from 2010 to 2018.This study provides a data-driven framework for assessing water withdrawals to enable a deeper understanding of competing water use among economic sectors as well as water withdrawal modelled with proper data resource and method.
基金supported by the National Natural Science Foundation of China(NSFC)under grant No.42304044the Natural Science Foundation of Henan,China under grant No.222300420385。
文摘High-precision polar motion prediction is of great significance for deep space exploration and satellite navigation.Polar motion is affected by a variety of excitation factors,and nonlinear prediction methods are more suitable for polar motion prediction.In order to explore the effect of deep learning in polar motion prediction.This paper proposes a combined model based on empirical wavelet transform(EWT),Convolutional Neural Networks(CNN)and Long Short Term Memory(LSTM).By training and forecasting EOP 20C04 data,the effectiveness of the algorithm is verified,and the performance of two forecasting strategies in deep learning for polar motion prediction is explored.The results indicate that recursive multi-step prediction performs better than direct multi-step prediction for short-term forecasts within 15 days,while direct multi-step prediction is more suitable for medium and long-term forecasts.In the 365 days forecast,the mean absolute error of EWT-CNN-LSTM in the X direction and Y direction is 18.25 mas and 15.78 mas,respectively,which is 23.5% and 16.2% higher than the accuracy of Bulletin A.The results show that the algorithm has a good effect in medium and long term polar motion prediction.
基金supported by the National Science and Technology Platform Construction (2005DKA32300)the Major Research Projects of the Ministry of Education (16JJD770019)the Open Program of Collaborative Innovation Center of Geo-Information Technology for Smart Central Plains Henan Province (G202006)。
文摘High-resolution deep-learning-based remote-sensing imagery analysis has been widely used in land-use and crop-classification mapping. However, the influence of composite feature bands, including complex feature indices arising from different sensors on the backbone, patch size, and predictions in transferable deep models require further testing. The experiments were conducted in six sites in Henan province from2019 to 2021. This study sought to enable the transfer of classification models across regions and years for Sentinel-2 A(10-m resolution) and Gaofen PMS(2-m resolution) imagery. With feature selection and up-sampling of small samples, the performance of UNet++ architecture on five backbones and four patch sizes was examined. Joint loss, mean Intersection over Union(m Io U), and epoch time were analyzed, and the optimal backbone and patch size for both sensors were Timm-Reg Net Y-320 and 256 × 256, respectively. The overall accuracy and Fscores of the Sentinel-2 A predictions ranged from 96.86% to 97.72%and 71.29% to 80.75%, respectively, compared to 75.34%–97.72% and 54.89%–73.25% for the Gaofen predictions. The accuracies of each site indicated that patch size exerted a greater influence on model performance than the backbone. The feature-selection-based predictions with UNet++ architecture and upsampling of minor classes demonstrated the capabilities of deep-learning generalization for classifying complex ground objects, offering improved performance compared to the UNet, Deeplab V3+, Random Forest, and Object-Oriented Classification models. In addition to the overall accuracy, confusion matrices,precision, recall, and F1 scores should be evaluated for minor land-cover types. This study contributes to large-scale, dynamic, and near-real-time land-use and crop mapping by integrating deep learning and multi-source remote-sensing imagery.
基金Under the auspices of the National Natural Science Foundation of China(No.71203200)the National Social Science Fund Project(No.20&ZD138)+1 种基金the National Science and Technology Platform Construction Project(No.2005DKA32300)Major Research Projects of the Ministry of Education(No.16JJD770019)。
文摘As total nitrogen(TN)and total phosphorus(TP)pollution is the main source of water pollution in the Huaihe River watershed in China,it is important to understand how TN and TP pollution affect the relationship between water supply and demand.Quantifying their impacts and describing the spatiotemporal distribution of these relationships are necessary for furtherly deepening the theory of TN and TP pollution on water bodies,and this information is also particularly essential for managing water resources regionally.In this study,based on the potential water supply,the water demand and the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST)water purification models,we estimated the TN and TP pollution from agricultural fertilizer,livestock and poultry breeding,and rural residents in the Huaihe River watershed and simulated TN and TP impacts on the relationship between water supply and demand.We found that if the impact of TN and TP pollution on water supply was not taken into account,on average,there was excess water supply in 79.20%of the watershed and excess demand in 20.80%of the rest during 1980–2018.Under the TN concentration limit,Grade-Ⅱ(The water quality meets the secondary level of water body qualified in GB3838–2002,classified as Grade-II)water was the main watersupply type in 1980–2018,followed by Grade-Ⅰ and Grade-Ⅲ water.The total water shortage showed an inverted V-shaped trend:first increasing and then decreasing at the same period.The proportion of the water shortage of Grade-I water in the total water shortage was the largest,followed by Grade-Ⅱ and Grade-III water.Areas with excess demand were located on the north bank of Wang-Beng,Yishuhe,and Huxi regions,although the water in these sub-watersheds met the water quality standards of Grade-Ⅰ water.Under the TP concentration limit,Grade-Ⅱ and Grade-Ⅰ water were the main water-supply types.The overall water shortage trend first increased and then decreased,exhibiting an inverted V-shape from 1980 to 2018.The water shortages of Grade-Ⅰ and Grade-Ⅱ water showed similar inverted V-shape trend over time.Areas that met the water quality standard of Grade-Ⅰ included the north banks of Wang-Beng and Huxi regions,where there was a surplus of demand.This paper suggests a way to analyze the interaction between water pollutants and the water supply-demand ratio as the example of TN and TP pollution at a watershed scale,which can broaden water pollution theory for relative water resources departments when water supply and demand will be evaluated.
基金funded by the National Natural Science Foundation of China (NSFCGrant Nos. 11080922 and 12103077)。
文摘The thermal expansion of radio telescopes has been recognized as a significant systematic error in Very Long Baseline Interferometry(VLBI) data analysis. Although the thermal expansion model recommended by International Earth Rotation Service(IERS) Conventions 2010 can achieve millimeter accuracy for the International VLBI Service for Geodesy and Astrometry(IVS) routine telescopes, both the International Terrestrial Reference Frame 2020(ITRF2020) in preparation and the VLBI2010 project encourage the scientific community to reconsider its modeling. To this end, we developed a monitoring system for the Tianma 13.2 m VLBI Global Observing System(VGOS) telescope. Based on the observed data, we refined the IERS expansion model, with results showing that the accuracy of our modified model was improved by 1.9 times. It suggested that the IERS thermal expansion model can achieve the declared millimeter accuracy, and refining its modeling can meet the requirement of 0.3 mm rms stability of the VGOS antenna reference point for the VLBI2010 project.
基金Under the auspices of National Natural Science Foundation of China(No.71203200,41671455)National Science and Technology Platform Construction Project(No.2005DKA32300)Major Research Projects of the Ministry of Education(No.16JJD770019)
文摘Implementation of payments for watershed services(PWS) has been regarded as a promising approach to coordinating the interests of upstream and downstream ecosystem services stakeholders. There is growing concern about whether PWS programs have achieved their original environmental goals of improving water quality and quantity, as well as the ancillary objective of increasing the welfare of local people. We start with an overview of PWS schemes and focus on their particularity and implementation mechanisms in China. We proceed to review 62 active PWS cases and examine their environmental performance in detail. The resulting findings show that PWS schemes have been able to reduce water pollution to some extent by establishing collaborative upstream/downstream watershed management policies, thereby improving water quality and quantity, as well as by making government officials more responsible for water resource management. In addition, their continued effectiveness in light of present challenges such as water-quality data availability is discussed. Chinese PWS schemes and their implementation mechanisms also provide information useful in monitoring environmental outcomes and guiding future designs of PWS programs in other regions.
基金supported by the Joint Funds of the National Natural Science Foundation of China(No.U21A2014)the Science and Technology Development Program of Henan Province(No.232102321032)the support from the Henan Dabieshan National Field Observation and Research Station of Forest Ecosystem。
文摘A strongly declining aerosol radiative effect has been observed in China since 2013 after implementing the clean air action,yet its impact on wheat(Triticum aestivum L.)production remains unclear.We use satellite measures and a biophysical crop model to assess the impact of aerosol-induced radiative perturbations on winter wheat production in the agricultural belt of Henan province from 2013 to 2018.After calibrating parameters with the extended Fourier Amplitude Sensitivity Test(EFAST)and the generalized likelihood uncertainty estimation(GLUE)method,the DSSAT CERES-Wheat model was able to simulate crop biomass and yield more accurately.We found that the aerosol negatively impacted wheat biomass by 21.87%and yield by 22.48%from 2006 to 2018,and the biomass effects from planting to anthesis were more significant compared to anthesis to maturity.Due to the strict clean air action,under all-sky conditions,the surface solar shortwave radiation(SSR)in 2018 increased by about 7.08%over 2006-2013 during the wheat growing seasons.As a result of the improvement of crop photosynthesis,winter wheat biomass and yield increased by an average of 5.46%and 2.9%,respectively.Our findings show that crop carbon uptake and yield will benefit from the clean air action in China,helping to ensure national food and health security.
