The sequential cropping index of arable land is important agricultural information. The aim of this article is to monitor and analyze the parameter, and offer reference for agricultural production. The cropping index ...The sequential cropping index of arable land is important agricultural information. The aim of this article is to monitor and analyze the parameter, and offer reference for agricultural production. The cropping index of arable land in Zhejiang Province, China from 2001 to 2004 was calculated using the second order difference based MODIS (moderate resolution imagine spectroradimeter) vegetation data from NASA (National Aeronautic and Space Administration) in America and the land use map with a scale of 1:25 000. It was found that the peak of the time series of the NDVI curve indicated that the ground biomass of crops reached the maximum, and fluctuated with the crops growing processes such as sowing, seeding, heading, ripeness, and harvesting within one year. Thus, the sequential cropping index was defined as the number of peaks of the time series of the NDVI curve. The sequential cropping index of all cities in Zhejiang Province, China was worked out. It is seen from the spatial distribution that the cropping index in the southwest Zhejiang Province is larger than that in the northeast. As for the temporal distribution, the sequential cropping index decreased from 2001 to 2003, whereas it increased slightly from 2003 to 2004. However, the index of arable land was relatively low, as far as the geographic position and climatic resource were concerned, and the potential of the sequential cropping index was great.展开更多
There is evindence showing that stress susceptibility index(SSI)(1一Yd/Yp)/(1—(?)d/(?)p)used as a measure of drought resistance of crop on the field is an altered form of droughtresistance coefficient(DRC)(Yd/Yp).The...There is evindence showing that stress susceptibility index(SSI)(1一Yd/Yp)/(1—(?)d/(?)p)used as a measure of drought resistance of crop on the field is an altered form of droughtresistance coefficient(DRC)(Yd/Yp).The correlative coefficient SSI and DRC is r=-1.Therefore,the SSI doesn’t improve the defect of the DRC.After two years experiments per-formed by using thirty winter wheat varieties as trial materials,the concept of drought resistanceindex in crops was put forward.Its expressing equation is:the yield in drylan×drought resis-tance coefficient/average yield in dryland.It makes the drought resistance coefficient(physicalindex)correlate well with the yield in dryland(agronomy index)and is suitable for breeder.展开更多
In this paper,a methodology for Leaf Area Index(LAI) estimating was proposed by assimilating remote sensed data into crop model based on temporal and spatial knowledge.Firstly,sensitive parameters of crop model were c...In this paper,a methodology for Leaf Area Index(LAI) estimating was proposed by assimilating remote sensed data into crop model based on temporal and spatial knowledge.Firstly,sensitive parameters of crop model were calibrated by Shuffled Complex Evolution method developed at the University of Arizona(SCE-UA) optimization method based on phenological information,which is called temporal knowledge.The calibrated crop model will be used as the forecast operator.Then,the Taylor′s mean value theorem was applied to extracting spatial information from the Moderate Resolution Imaging Spectroradiometer(MODIS) multi-scale data,which was used to calibrate the LAI inversion results by A two-layer Canopy Reflectance Model(ACRM) model.The calibrated LAI result was used as the observation operator.Finally,an Ensemble Kalman Filter(EnKF) was used to assimilate MODIS data into crop model.The results showed that the method could significantly improve the estimation accuracy of LAI and the simulated curves of LAI more conform to the crop growth situation closely comparing with MODIS LAI products.The root mean square error(RMSE) of LAI calculated by assimilation is 0.9185 which is reduced by 58.7% compared with that by simulation(0.3795),and before and after assimilation the mean error is reduced by 92.6% which is from 0.3563 to 0.0265.All these experiments indicated that the methodology proposed in this paper is reasonable and accurate for estimating crop LAI.展开更多
Phosphorus (P) risk indices are commonly used in the USA to estimate the field-scale risk of agricultural P runoff. Because the Ohio P Risk Index is increasingly being used to judge farmer performance, it is important...Phosphorus (P) risk indices are commonly used in the USA to estimate the field-scale risk of agricultural P runoff. Because the Ohio P Risk Index is increasingly being used to judge farmer performance, it is important to evaluate weighting/scoring of all P Index parameters to ensure Ohio farmers are credited for practices that reduce P runoff risk and not unduly penalized for things not demonstrably related to runoff risk. A sensitivity analysis provides information as to how sensitive the P Index score is to changes in inputs. The objectives were to determine 1) which inputs are most highly associated with P Index scores and 2) the relative impact of each input variable on resultant P Index scores. The current approach uses simulations across 6134 Ohio point locations and five crop management scenarios (CMSs), representing increasing soil disturbance. The CMSs range from all no-till, which is being promoted in Ohio, rotational tillage, which is a common practice in Ohio to full tillage to represent an extreme practice. Results showed that P Index scores were best explained by soil test P (31.9%) followed by connectivity to water (29.7%), soil erosion (13.4%), fertilizer application amount (11.3%), runoff class (9.5%), fertilizer application method (2.2%), and finally filter strip (2.0%). Ohio P Index simulations across CMSs one through five showed that >40% scored <15 points (low) while <1.5% scored >45 points (very high). Given Ohio water quality problems, the Ohio P Index needs to be stricter. The current approach is useful for Ohio P Index evaluations and revision decisions by spatially illustrating the impact of potential changes regionally and state-wide.展开更多
Yunnan province in China is a high background area of soil heavy metals, and agricultural planting and industrial and mining activities are relatively frequent, which aggravate soil heavy metal pollution. However, at ...Yunnan province in China is a high background area of soil heavy metals, and agricultural planting and industrial and mining activities are relatively frequent, which aggravate soil heavy metal pollution. However, at present, there are few reports on the overall or large-scale soil-crop pollution and risk assessment of heavy metals in Yunnan Province. This study through 11 cities in Yunnan province of China farmland soil-crop systems of heavy metal lead, cadmium content, enrichment coefficient is analyzed, and using the method of potential ecological harm index, index of compressive quality to evaluate heavy metal pollution soil-crop system risk. Results showed that the average content of soil heavy metal Cd and Pb were 1.31 mg/kg, 64.17 mg/kg, which are higher than the background value of Yunnan province. The average contents of Pb and Cd in the edible parts of crops were 0.20 mg/kg, 0.08 mg/kg. The average content of heavy metals in crops in Diqing (Pb) and Nujiang (Cd) was 0.72 mg/kg and 0.148 mg/kg. The enrichment coefficients of heavy metals in edible parts of crops were the largest in Diqing (Pb) and Zhaotong (Cd). The average value of ecological risk index of Pb element in soil is 2.79, which indicates that the study area is in a slight ecological hazard, the average value of the ecological risk index of Cd in soil is 126.43. The average value of the comprehensive quality impact index (IICQ) is 4.27, which indicates that the study area is moderately polluted. In this study, the contents of heavy metals Cd and Pb in soils and crops in different administrative regions were determined, and the heavy metals Pb and Cd in soil-crop system of Yunnan province, China were evaluated, it is expected to have important scientific and theoretical significance for the safe use of cultivated land to export safe agricultural products and promote the sustainable development of agriculture in Yunnan Plateau.展开更多
【目的】干旱是影响中国农业生产的主要自然灾害之一。东北地区作为中国最大的玉米生产基地,气候变化背景下干旱频发重发严重影响玉米的高产稳产。评估未来气候情景下东北地区春玉米干旱发生风险及其空间格局变化,为该地区春玉米防旱避...【目的】干旱是影响中国农业生产的主要自然灾害之一。东北地区作为中国最大的玉米生产基地,气候变化背景下干旱频发重发严重影响玉米的高产稳产。评估未来气候情景下东北地区春玉米干旱发生风险及其空间格局变化,为该地区春玉米防旱避灾以及保障其高产稳产提供科学依据。【方法】选取东北地区春玉米潜在种植区为研究区域,基于ISIMIP输出的SSP1-2.6、SSP3-7.0和SSP5-8.53种气候情景的1981—2060年逐日气象资料以及53个农业气象观测站1981—2014年春玉米生育期资料,选取作物水分亏缺指数(crop water deficit index,CWDI)为农业干旱指标,分析东北地区春玉米不同生育时期不同等级干旱时空分布特征,选择最优概率理论分布函数进行干旱指数序列的概率估算,基于信息扩散理论估算得到各点春玉米不同等级干旱风险,构建干旱风险指数,评估未来不同气候情景下东北地区春玉米干旱发生风险及未来各等级风险区的空间格局变化。【结果】(1)1981—2014年东北地区春玉米全生育期干旱指数总体呈西南高东北低的特征,表现为内蒙古东四盟(57.3%)>黑龙江省(40.6%)>辽宁省(39.5%)>吉林省(38.9%)。(2)研究区域春玉米生育中期干旱指数整体高于生育前期和生育后期。其中,2030s和2050s研究区域春玉米生育前期干旱风险概率为轻旱>中旱≈重旱>特旱,生育中期干旱风险概率为特旱>重旱>轻旱≈中旱,生育后期干旱风险概率轻旱>中旱>重旱>特旱。(3)1981—2060年,SSP1-2.6低排放情景下,东北地区春玉米较高等级干旱风险发生概率将减少,极高和较高干旱风险区明显向西南收缩,2030s和2050s面积占比分别减少5.4%和9.6%、0.8%和2.5%;而SSP3-7.0和SSP5-8.5两个高排放情景下,较高等级干旱风险发生概率增加,且较高干旱风险区向东北扩张,2050s面积占比分别增加8.5%和9.7%。【结论】基于干旱风险指数的未来干旱风险时空分布格局中,东北春玉米干旱风险呈现由西南向东北减少的特征,且未来SSP3-7.0和SSP5-8.5情景下,较高干旱风险区向东北方向扩张,需关注作物关键生育时期提出针对性的防御措施。展开更多
【目的】探究马铃薯的叶气温差与环境因子的关系,进一步优化马铃薯水分胁迫指数模型。【方法】在河南农业大学林学院试验基地进行马铃薯盆栽试验,选择晴朗天气测定不同土壤含水率下马铃薯的叶气温差随太阳辐射和大气饱和水汽压差(VPD)...【目的】探究马铃薯的叶气温差与环境因子的关系,进一步优化马铃薯水分胁迫指数模型。【方法】在河南农业大学林学院试验基地进行马铃薯盆栽试验,选择晴朗天气测定不同土壤含水率下马铃薯的叶气温差随太阳辐射和大气饱和水汽压差(VPD)的变化规律,确定作物水分胁迫指数(crop water stress index,CWSI)的上下基线,进一步试验后得到优化后的马铃薯CWSI经验模型,并对相关模型进行验证。【结果】马铃薯的叶气温差随着土壤含水率的降低而升高;当土壤含水率较低(7.28%)时,马铃薯的叶气温差随太阳辐射的增大而增大,呈显著线性关系;当土壤含水率较高(15.85%)时,马铃薯的叶气温差随VPD的增大而减小,呈显著线性关系;构建出马铃薯CWSI的上基线为y=0.0098Q-0.68[Q为太阳辐射强度/(W·m^(-2))],下基线为y=-1.67V+3.75(V为大气饱和水汽压差/kPa);将优化的CWSI模型验证后得知,随着土壤含水率的减少,CWSI值增加,且CWSI同土壤含水量呈极显著负相关关系(p<0.01)。【结论】马铃薯的最大叶气温差与太阳辐射的线性关系作为马铃薯水分胁迫指数的上基线是可行的,该研究对传统CWSI经验模型进行改进,进一步优化了CWSI经验模型。展开更多
This study explored spatial explicit multiple cropping efficiency (MCE) of China in 2005 by coupling time series remote sensing data with an econometric model - stochastic frontier analysis (SFA). We firstly extra...This study explored spatial explicit multiple cropping efficiency (MCE) of China in 2005 by coupling time series remote sensing data with an econometric model - stochastic frontier analysis (SFA). We firstly extracted multiple cropping index (MCI) on the basis of the close relationship between crop phenologies and moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index (EVI) value. Then, SFA model was employed to calculate MCE, by considering several indicators of meteorological conditions as inputs of multiple cropping systems and the extracted MCI was the output. The result showed that 46% of the cultivated land in China in 2005 was multiple cropped, including 39% double- cropped land and 7% triple-cropped land. Most of the multiple cropped land was distributed in the south of Great Wall. The total efficiency of multiple cropping in China was 87.61% in 2005. Southwestern China, Ganxin Region, the middle and lower reaches of Yangtze River and Huanghuaihai Plain were the four agricultural zones with the largest rooms for increasing MCI and improving MCE. Fragmental terrain, soil salinization, deficiency of water resources, and loss of labor force were the obstacles for MCE promotion in different zones. The method proposed in this paper is theoretically reliable for MCE extraction, whereas further studies are need to be done to investigate the most proper indicators of meteorological conditions as the inputs of multiple cropping systems.展开更多
文摘The sequential cropping index of arable land is important agricultural information. The aim of this article is to monitor and analyze the parameter, and offer reference for agricultural production. The cropping index of arable land in Zhejiang Province, China from 2001 to 2004 was calculated using the second order difference based MODIS (moderate resolution imagine spectroradimeter) vegetation data from NASA (National Aeronautic and Space Administration) in America and the land use map with a scale of 1:25 000. It was found that the peak of the time series of the NDVI curve indicated that the ground biomass of crops reached the maximum, and fluctuated with the crops growing processes such as sowing, seeding, heading, ripeness, and harvesting within one year. Thus, the sequential cropping index was defined as the number of peaks of the time series of the NDVI curve. The sequential cropping index of all cities in Zhejiang Province, China was worked out. It is seen from the spatial distribution that the cropping index in the southwest Zhejiang Province is larger than that in the northeast. As for the temporal distribution, the sequential cropping index decreased from 2001 to 2003, whereas it increased slightly from 2003 to 2004. However, the index of arable land was relatively low, as far as the geographic position and climatic resource were concerned, and the potential of the sequential cropping index was great.
文摘There is evindence showing that stress susceptibility index(SSI)(1一Yd/Yp)/(1—(?)d/(?)p)used as a measure of drought resistance of crop on the field is an altered form of droughtresistance coefficient(DRC)(Yd/Yp).The correlative coefficient SSI and DRC is r=-1.Therefore,the SSI doesn’t improve the defect of the DRC.After two years experiments per-formed by using thirty winter wheat varieties as trial materials,the concept of drought resistanceindex in crops was put forward.Its expressing equation is:the yield in drylan×drought resis-tance coefficient/average yield in dryland.It makes the drought resistance coefficient(physicalindex)correlate well with the yield in dryland(agronomy index)and is suitable for breeder.
基金Under the auspices of Major State Basic Research Development Program of China(No.2007CB714407)National Natural Science Foundation of China(No.40801070)Action Plan for West Development Program of Chinese Academy of Sciences(No.KZCX2-XB2-09)
文摘In this paper,a methodology for Leaf Area Index(LAI) estimating was proposed by assimilating remote sensed data into crop model based on temporal and spatial knowledge.Firstly,sensitive parameters of crop model were calibrated by Shuffled Complex Evolution method developed at the University of Arizona(SCE-UA) optimization method based on phenological information,which is called temporal knowledge.The calibrated crop model will be used as the forecast operator.Then,the Taylor′s mean value theorem was applied to extracting spatial information from the Moderate Resolution Imaging Spectroradiometer(MODIS) multi-scale data,which was used to calibrate the LAI inversion results by A two-layer Canopy Reflectance Model(ACRM) model.The calibrated LAI result was used as the observation operator.Finally,an Ensemble Kalman Filter(EnKF) was used to assimilate MODIS data into crop model.The results showed that the method could significantly improve the estimation accuracy of LAI and the simulated curves of LAI more conform to the crop growth situation closely comparing with MODIS LAI products.The root mean square error(RMSE) of LAI calculated by assimilation is 0.9185 which is reduced by 58.7% compared with that by simulation(0.3795),and before and after assimilation the mean error is reduced by 92.6% which is from 0.3563 to 0.0265.All these experiments indicated that the methodology proposed in this paper is reasonable and accurate for estimating crop LAI.
文摘Phosphorus (P) risk indices are commonly used in the USA to estimate the field-scale risk of agricultural P runoff. Because the Ohio P Risk Index is increasingly being used to judge farmer performance, it is important to evaluate weighting/scoring of all P Index parameters to ensure Ohio farmers are credited for practices that reduce P runoff risk and not unduly penalized for things not demonstrably related to runoff risk. A sensitivity analysis provides information as to how sensitive the P Index score is to changes in inputs. The objectives were to determine 1) which inputs are most highly associated with P Index scores and 2) the relative impact of each input variable on resultant P Index scores. The current approach uses simulations across 6134 Ohio point locations and five crop management scenarios (CMSs), representing increasing soil disturbance. The CMSs range from all no-till, which is being promoted in Ohio, rotational tillage, which is a common practice in Ohio to full tillage to represent an extreme practice. Results showed that P Index scores were best explained by soil test P (31.9%) followed by connectivity to water (29.7%), soil erosion (13.4%), fertilizer application amount (11.3%), runoff class (9.5%), fertilizer application method (2.2%), and finally filter strip (2.0%). Ohio P Index simulations across CMSs one through five showed that >40% scored <15 points (low) while <1.5% scored >45 points (very high). Given Ohio water quality problems, the Ohio P Index needs to be stricter. The current approach is useful for Ohio P Index evaluations and revision decisions by spatially illustrating the impact of potential changes regionally and state-wide.
文摘Yunnan province in China is a high background area of soil heavy metals, and agricultural planting and industrial and mining activities are relatively frequent, which aggravate soil heavy metal pollution. However, at present, there are few reports on the overall or large-scale soil-crop pollution and risk assessment of heavy metals in Yunnan Province. This study through 11 cities in Yunnan province of China farmland soil-crop systems of heavy metal lead, cadmium content, enrichment coefficient is analyzed, and using the method of potential ecological harm index, index of compressive quality to evaluate heavy metal pollution soil-crop system risk. Results showed that the average content of soil heavy metal Cd and Pb were 1.31 mg/kg, 64.17 mg/kg, which are higher than the background value of Yunnan province. The average contents of Pb and Cd in the edible parts of crops were 0.20 mg/kg, 0.08 mg/kg. The average content of heavy metals in crops in Diqing (Pb) and Nujiang (Cd) was 0.72 mg/kg and 0.148 mg/kg. The enrichment coefficients of heavy metals in edible parts of crops were the largest in Diqing (Pb) and Zhaotong (Cd). The average value of ecological risk index of Pb element in soil is 2.79, which indicates that the study area is in a slight ecological hazard, the average value of the ecological risk index of Cd in soil is 126.43. The average value of the comprehensive quality impact index (IICQ) is 4.27, which indicates that the study area is moderately polluted. In this study, the contents of heavy metals Cd and Pb in soils and crops in different administrative regions were determined, and the heavy metals Pb and Cd in soil-crop system of Yunnan province, China were evaluated, it is expected to have important scientific and theoretical significance for the safe use of cultivated land to export safe agricultural products and promote the sustainable development of agriculture in Yunnan Plateau.
文摘【目的】干旱是影响中国农业生产的主要自然灾害之一。东北地区作为中国最大的玉米生产基地,气候变化背景下干旱频发重发严重影响玉米的高产稳产。评估未来气候情景下东北地区春玉米干旱发生风险及其空间格局变化,为该地区春玉米防旱避灾以及保障其高产稳产提供科学依据。【方法】选取东北地区春玉米潜在种植区为研究区域,基于ISIMIP输出的SSP1-2.6、SSP3-7.0和SSP5-8.53种气候情景的1981—2060年逐日气象资料以及53个农业气象观测站1981—2014年春玉米生育期资料,选取作物水分亏缺指数(crop water deficit index,CWDI)为农业干旱指标,分析东北地区春玉米不同生育时期不同等级干旱时空分布特征,选择最优概率理论分布函数进行干旱指数序列的概率估算,基于信息扩散理论估算得到各点春玉米不同等级干旱风险,构建干旱风险指数,评估未来不同气候情景下东北地区春玉米干旱发生风险及未来各等级风险区的空间格局变化。【结果】(1)1981—2014年东北地区春玉米全生育期干旱指数总体呈西南高东北低的特征,表现为内蒙古东四盟(57.3%)>黑龙江省(40.6%)>辽宁省(39.5%)>吉林省(38.9%)。(2)研究区域春玉米生育中期干旱指数整体高于生育前期和生育后期。其中,2030s和2050s研究区域春玉米生育前期干旱风险概率为轻旱>中旱≈重旱>特旱,生育中期干旱风险概率为特旱>重旱>轻旱≈中旱,生育后期干旱风险概率轻旱>中旱>重旱>特旱。(3)1981—2060年,SSP1-2.6低排放情景下,东北地区春玉米较高等级干旱风险发生概率将减少,极高和较高干旱风险区明显向西南收缩,2030s和2050s面积占比分别减少5.4%和9.6%、0.8%和2.5%;而SSP3-7.0和SSP5-8.5两个高排放情景下,较高等级干旱风险发生概率增加,且较高干旱风险区向东北扩张,2050s面积占比分别增加8.5%和9.7%。【结论】基于干旱风险指数的未来干旱风险时空分布格局中,东北春玉米干旱风险呈现由西南向东北减少的特征,且未来SSP3-7.0和SSP5-8.5情景下,较高干旱风险区向东北方向扩张,需关注作物关键生育时期提出针对性的防御措施。
文摘【目的】探究马铃薯的叶气温差与环境因子的关系,进一步优化马铃薯水分胁迫指数模型。【方法】在河南农业大学林学院试验基地进行马铃薯盆栽试验,选择晴朗天气测定不同土壤含水率下马铃薯的叶气温差随太阳辐射和大气饱和水汽压差(VPD)的变化规律,确定作物水分胁迫指数(crop water stress index,CWSI)的上下基线,进一步试验后得到优化后的马铃薯CWSI经验模型,并对相关模型进行验证。【结果】马铃薯的叶气温差随着土壤含水率的降低而升高;当土壤含水率较低(7.28%)时,马铃薯的叶气温差随太阳辐射的增大而增大,呈显著线性关系;当土壤含水率较高(15.85%)时,马铃薯的叶气温差随VPD的增大而减小,呈显著线性关系;构建出马铃薯CWSI的上基线为y=0.0098Q-0.68[Q为太阳辐射强度/(W·m^(-2))],下基线为y=-1.67V+3.75(V为大气饱和水汽压差/kPa);将优化的CWSI模型验证后得知,随着土壤含水率的减少,CWSI值增加,且CWSI同土壤含水量呈极显著负相关关系(p<0.01)。【结论】马铃薯的最大叶气温差与太阳辐射的线性关系作为马铃薯水分胁迫指数的上基线是可行的,该研究对传统CWSI经验模型进行改进,进一步优化了CWSI经验模型。
基金supported by the National Natural Science Foundation of China (41001277)the National 973 Program of China (2010CB95090102)
文摘This study explored spatial explicit multiple cropping efficiency (MCE) of China in 2005 by coupling time series remote sensing data with an econometric model - stochastic frontier analysis (SFA). We firstly extracted multiple cropping index (MCI) on the basis of the close relationship between crop phenologies and moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index (EVI) value. Then, SFA model was employed to calculate MCE, by considering several indicators of meteorological conditions as inputs of multiple cropping systems and the extracted MCI was the output. The result showed that 46% of the cultivated land in China in 2005 was multiple cropped, including 39% double- cropped land and 7% triple-cropped land. Most of the multiple cropped land was distributed in the south of Great Wall. The total efficiency of multiple cropping in China was 87.61% in 2005. Southwestern China, Ganxin Region, the middle and lower reaches of Yangtze River and Huanghuaihai Plain were the four agricultural zones with the largest rooms for increasing MCI and improving MCE. Fragmental terrain, soil salinization, deficiency of water resources, and loss of labor force were the obstacles for MCE promotion in different zones. The method proposed in this paper is theoretically reliable for MCE extraction, whereas further studies are need to be done to investigate the most proper indicators of meteorological conditions as the inputs of multiple cropping systems.