Spatial dynamics of crop yield provide useful information for improving the production. High sensitivity of crop growth models to uncertainties in input factors and parameters and relatively coarse parameterizations i...Spatial dynamics of crop yield provide useful information for improving the production. High sensitivity of crop growth models to uncertainties in input factors and parameters and relatively coarse parameterizations in conventional remote sensing(RS) approaches limited their applications over broad regions. In this study, a process-based and remote sensing driven crop yield model for maize(PRYM–Maize) was developed to estimate regional maize yield, and it was implemented using eight data-model coupling strategies(DMCSs) over the Northeast China Plain(NECP). Simulations under eight DMCSs were validated against the prefecture-level statistics(2010–2012) reported by National Bureau of Statistics of China, and inter-compared. The 3-year averaged result could give more robust estimate than the yearly simulation for maize yield over space. A 3-year averaged validation showed that prefecture-level estimates by PRYM–Maize under DMCS8, which coupled with the development stage(DVS)-based grain-filling algorithm and RS phenology information and leaf area index(LAI), had higher correlation(R, 0.61) and smaller root mean standard error(RMSE, 1.33 t ha^(–1)) with the statistics than did PRYM–Maize under other DMCSs. The result also demonstrated that DVS-based grain-filling algorithm worked better for maize yield than did the harvest index(HI)-based method, and both RS phenology information and LAI worked for improving regional maize yield estimate. These results demonstrate that the developed PRYM–Maize under DMCS8 gives reasonable estimates for maize yield and provides scientific basis facilitating the understanding the spatial variations of maize yield over the NECP.展开更多
SWAT model is one of the primary tools for assessing irrigation district water management and water-saving measures.However,its incapacity to consider the diverse growth and water requirements of paddy during various ...SWAT model is one of the primary tools for assessing irrigation district water management and water-saving measures.However,its incapacity to consider the diverse growth and water requirements of paddy during various growth stages,as well as the insufficient availability of external water sources.This study introduces the Penman-Monteith equation and Jensen model into the SWAT framework,setting crop coefficients,crop base coefficients,and growth stage sensitivity indices based on the different growth stage.Additionally,modifications are made to the external water source available for irrigation and paddyfield leakage modules,establishing a distributed agricultural hydrological model suitable for accurately simulating water balance elements and paddy yield in multi-source irrigation districts.The Yangshudang watershed in the Zhanghe irrigation district is chosen for the evaluation of the modified model's simulation performance,with a quantitative assessment of water-saving and yield-increasing effects.The results demonstrate that the modified model effectively meets the requirements for simulating paddy evapotranspiration of various growth stages,yield,agricultural irrigation water consumptions,and runoff,exhibiting a notable enhancement in performance.As two common water-saving measures in irrigation areas,inter-mittent irrigation and irrigation district renovation were used as two water-saving scenarios in the simulation of the modified SWAT model.Under intermittent irrigation,the watershed experiences a 6.58%reduction in net irrigation water use.In the scenario with irrigation district renovation,the water resources in the watershed are utilized more efficiently.The modified model from this study can be applied for assessing the synergistic effects of irrigation district water-saving and yield-increasing measures,providing crucial insights for the formulation of irri-gation district water-saving strategies and water resource optimization plans.展开更多
We investigate the dependency of strain rate,temperature and size on yield strength of hexagonal close packed（HCP） nanowires based on large-scale molecular dynamics（MD） simulation.A variance-based analysis has bee...We investigate the dependency of strain rate,temperature and size on yield strength of hexagonal close packed（HCP） nanowires based on large-scale molecular dynamics（MD） simulation.A variance-based analysis has been proposed to quantify relative sensitivity of the three controlling factors on the yield strength of the material.One of the major drawbacks of conventional MD simulation based studies is that the simulations are computationally very intensive and economically expensive.Large scale molecular dynamics simulation needs supercomputing access and the larger the number of atoms,the longer it takes time and computational resources.For this reason it becomes practically impossible to perform a robust and comprehensive analysis that requires multiple simulations such as sensitivity analysis,uncertainty quantification and optimization.We propose a novel surrogate based molecular dynamics（SBMD）simulation approach that enables us to carry out thousands of virtual simulations for different combinations of the controlling factors in a computationally efficient way by performing only few MD simulations.Following the SBMD simulation approach an efficient optimum design scheme has been developed to predict optimized size of the nanowire to maximize the yield strength.Subsequently the effect of inevitable uncertainty associated with the controlling factors has been quantified using Monte Carlo simulation.Though we have confined our analyses in this article for Magnesium nanowires only,the proposed approach can be extended to other materials for computationally intensive nano-scale investigation involving multiple factors of influence.展开更多
Due to the current water scarcity in the world,it is extremely important to improve the use of this natural and exhaustible resource in agriculture,by contributing to increase agricultural production and sustainabilit...Due to the current water scarcity in the world,it is extremely important to improve the use of this natural and exhaustible resource in agriculture,by contributing to increase agricultural production and sustainability.Several models of crop growth simulation were developed to predict the edaphoclimatic effects on crop yield.These models are calibrated and validated for a given region using the data generated from field experiments.Therefore,the objective of this study was to calibrate and validate the FAO AquaCrop model for yacon(Smallanthus sonchifolius)crop in a tropical climate.The experiment was conducted in an experimental area located in the municipality of Ibatiba,state of Espírito Santo(Brazil)during the years of 2013 and 2014.The calibration was done using the Autumn planting and validation with the Winter and Spring plantings.For the statistical analysis,the coefficient of determination,Willmott concordance index,bias for the systematic error,root mean square error and the mean absolute error to test the model performance were used.In general,the FAO AquaCrop model predicted the root yield,total biomass and harvest index with acceptable accuracy,and with deviations of less than 6%for total and root biomass.Late planting of yacon showed a reduction in yield as well as total biomass.展开更多
基金supported by the National Key Research and Development Program of China(2016YFD0300101,and 2016YFD0300110)the National Natural Science Foundation of China(41871253 and 31671585)+1 种基金the“Taishan Scholar”Project of Shandong Province,Chinathe Key Basic Research Project of Shandong Natural Science Foundation,China(ZR2017ZB0422)。
文摘Spatial dynamics of crop yield provide useful information for improving the production. High sensitivity of crop growth models to uncertainties in input factors and parameters and relatively coarse parameterizations in conventional remote sensing(RS) approaches limited their applications over broad regions. In this study, a process-based and remote sensing driven crop yield model for maize(PRYM–Maize) was developed to estimate regional maize yield, and it was implemented using eight data-model coupling strategies(DMCSs) over the Northeast China Plain(NECP). Simulations under eight DMCSs were validated against the prefecture-level statistics(2010–2012) reported by National Bureau of Statistics of China, and inter-compared. The 3-year averaged result could give more robust estimate than the yearly simulation for maize yield over space. A 3-year averaged validation showed that prefecture-level estimates by PRYM–Maize under DMCS8, which coupled with the development stage(DVS)-based grain-filling algorithm and RS phenology information and leaf area index(LAI), had higher correlation(R, 0.61) and smaller root mean standard error(RMSE, 1.33 t ha^(–1)) with the statistics than did PRYM–Maize under other DMCSs. The result also demonstrated that DVS-based grain-filling algorithm worked better for maize yield than did the harvest index(HI)-based method, and both RS phenology information and LAI worked for improving regional maize yield estimate. These results demonstrate that the developed PRYM–Maize under DMCS8 gives reasonable estimates for maize yield and provides scientific basis facilitating the understanding the spatial variations of maize yield over the NECP.
基金Fundamental Research Funds for Central Public Welfare Research Institutes,Grant/Award Number:CKSA2023479/NYNSFC-MWR-CTGC Joint Yangtze River Water Science Research Project,Grant/Award Number:U2040213+1 种基金Basic Scientific Research Business Funding Projects of Central Public Welfare Research Institutes,Grant/Award Numbers:CKSF2019251/NY,CKSF2021299/NYProjects of International Cooperation and Exchanges NSFC,Grant/Award Number:52211540722。
文摘SWAT model is one of the primary tools for assessing irrigation district water management and water-saving measures.However,its incapacity to consider the diverse growth and water requirements of paddy during various growth stages,as well as the insufficient availability of external water sources.This study introduces the Penman-Monteith equation and Jensen model into the SWAT framework,setting crop coefficients,crop base coefficients,and growth stage sensitivity indices based on the different growth stage.Additionally,modifications are made to the external water source available for irrigation and paddyfield leakage modules,establishing a distributed agricultural hydrological model suitable for accurately simulating water balance elements and paddy yield in multi-source irrigation districts.The Yangshudang watershed in the Zhanghe irrigation district is chosen for the evaluation of the modified model's simulation performance,with a quantitative assessment of water-saving and yield-increasing effects.The results demonstrate that the modified model effectively meets the requirements for simulating paddy evapotranspiration of various growth stages,yield,agricultural irrigation water consumptions,and runoff,exhibiting a notable enhancement in performance.As two common water-saving measures in irrigation areas,inter-mittent irrigation and irrigation district renovation were used as two water-saving scenarios in the simulation of the modified SWAT model.Under intermittent irrigation,the watershed experiences a 6.58%reduction in net irrigation water use.In the scenario with irrigation district renovation,the water resources in the watershed are utilized more efficiently.The modified model from this study can be applied for assessing the synergistic effects of irrigation district water-saving and yield-increasing measures,providing crucial insights for the formulation of irri-gation district water-saving strategies and water resource optimization plans.
基金the financial support from Swansea University through the award of Zienkiewicz Scholarshipthe financial support from The Royal Society of London through the Wolfson Research Merit award
文摘We investigate the dependency of strain rate,temperature and size on yield strength of hexagonal close packed（HCP） nanowires based on large-scale molecular dynamics（MD） simulation.A variance-based analysis has been proposed to quantify relative sensitivity of the three controlling factors on the yield strength of the material.One of the major drawbacks of conventional MD simulation based studies is that the simulations are computationally very intensive and economically expensive.Large scale molecular dynamics simulation needs supercomputing access and the larger the number of atoms,the longer it takes time and computational resources.For this reason it becomes practically impossible to perform a robust and comprehensive analysis that requires multiple simulations such as sensitivity analysis,uncertainty quantification and optimization.We propose a novel surrogate based molecular dynamics（SBMD）simulation approach that enables us to carry out thousands of virtual simulations for different combinations of the controlling factors in a computationally efficient way by performing only few MD simulations.Following the SBMD simulation approach an efficient optimum design scheme has been developed to predict optimized size of the nanowire to maximize the yield strength.Subsequently the effect of inevitable uncertainty associated with the controlling factors has been quantified using Monte Carlo simulation.Though we have confined our analyses in this article for Magnesium nanowires only,the proposed approach can be extended to other materials for computationally intensive nano-scale investigation involving multiple factors of influence.
文摘Due to the current water scarcity in the world,it is extremely important to improve the use of this natural and exhaustible resource in agriculture,by contributing to increase agricultural production and sustainability.Several models of crop growth simulation were developed to predict the edaphoclimatic effects on crop yield.These models are calibrated and validated for a given region using the data generated from field experiments.Therefore,the objective of this study was to calibrate and validate the FAO AquaCrop model for yacon(Smallanthus sonchifolius)crop in a tropical climate.The experiment was conducted in an experimental area located in the municipality of Ibatiba,state of Espírito Santo(Brazil)during the years of 2013 and 2014.The calibration was done using the Autumn planting and validation with the Winter and Spring plantings.For the statistical analysis,the coefficient of determination,Willmott concordance index,bias for the systematic error,root mean square error and the mean absolute error to test the model performance were used.In general,the FAO AquaCrop model predicted the root yield,total biomass and harvest index with acceptable accuracy,and with deviations of less than 6%for total and root biomass.Late planting of yacon showed a reduction in yield as well as total biomass.
