以陕西1961—2010近50 a 22个站点的逐日气象数据为基础资料,计算其冬小麦生育期各旬需水量(ETi)以及作物缺水指数(CWDI),并根据农业干旱等级计算出研究区干旱频率,分析陕西冬小麦各生育期内干旱指数时空分布特征。结果表明:陕西冬小麦...以陕西1961—2010近50 a 22个站点的逐日气象数据为基础资料,计算其冬小麦生育期各旬需水量(ETi)以及作物缺水指数(CWDI),并根据农业干旱等级计算出研究区干旱频率,分析陕西冬小麦各生育期内干旱指数时空分布特征。结果表明:陕西冬小麦各生育期干旱频率为拔节抽穗期>灌浆成熟期>返青期>冬前生长期>越冬期;冬小麦重旱以上频率的空间分布由北向南逐渐减少;冬小麦干旱指数的年代际变化呈上升趋势,20世纪70年代和90年代干旱指数较高,1968年为突变年份。展开更多
为建立东北地区春玉米干旱灾变过程动态监测方法体系,跟踪反馈干旱时空特征和发展趋势,该文在采用作物水分亏缺指数CWDI(crop water deficit index)作为干旱监测指标的基础上,针对分区域和特定生育期内传统作物系数(Kc)值的固定化设置现...为建立东北地区春玉米干旱灾变过程动态监测方法体系,跟踪反馈干旱时空特征和发展趋势,该文在采用作物水分亏缺指数CWDI(crop water deficit index)作为干旱监测指标的基础上,针对分区域和特定生育期内传统作物系数(Kc)值的固定化设置现状,首先采用分段函数对作物系数(Kc)进行逐日估算,进而计算逐日CWDI;其次对干旱等级的临界阈值进行逐日估算,构建随春玉米发育进程变化的干旱等级动态划分标准。在此,该文以东北地区2018年春玉米干旱为例,基于逐日平均温度、最高温度、最低温度、降水、气压、风速、日照时数、相对湿度以及春玉米关键生育期数据等,分别计算了逐日和8 d合成的CWDI与改进CWDI,通过地面干旱调查数据对二者的监测结果进行检验,对其监测精度和空间连续性进行了比较和分析;利用改进CWDI对东北地区2018年春玉米干旱灾变过程进行动态监测,揭示了其时空特征及演变趋势。结果表明:1)基于改进CWDI的春玉米干旱监测结果与地面调查结果具有较高吻合度,整体判对率达到了75.7%,比CWDI监测的干旱判对率提高了8.1%;CWDI监测的干旱程度在不同行政区域交界处出现了明显突兀的变化,而改进CWDI则表现出良好的空间连续性,适用于春玉米干旱灾变过程动态监测之目的。2)2018年东北地区主要发生5月的春旱和7月下旬到8月中旬的伏旱,春旱从吉林西部开始发生并向西南方向不断扩展,消退方向与发展方向保持一致。伏旱从内蒙古东部、辽宁西部等地区向东部不断发展,之后由东、西两侧向中部不断消退。并且在玉米整个生育期内,均有一定程度的干旱发生。3)改进CWDI可以很好的反映出2018年5月22日前后大范围降水过程所引起的春旱面积减小、程度降低的过程,对降水因子敏感,可以实时表征逐日尺度降水增多引起的干旱强度变化。展开更多
[目的]分析陕西省不同粮烟种植模式下的作物需水量及水分亏缺指数,筛选出高水分利用、免/低灌溉需水的粮烟种植模式。[方法]基于联合国粮食和农业组织(Food and Agriculture Organization of the United Nations,FAO)推荐的作物系数法,...[目的]分析陕西省不同粮烟种植模式下的作物需水量及水分亏缺指数,筛选出高水分利用、免/低灌溉需水的粮烟种植模式。[方法]基于联合国粮食和农业组织(Food and Agriculture Organization of the United Nations,FAO)推荐的作物系数法,并运用水分亏缺指数模型(Crop water deficit index,CWDI),结合2014—2023年的气象、土壤数据和区域作物种植生育资料,分析陕北、关中和陕南地区烤烟、夏播大豆、甘薯和夏玉米单作及与烤烟间套作的作物系数、需水特性、水分亏缺及空间分布规律。[结果]生长初期作物系数(K_(cini))表现为陕南>关中>陕北,生长中期作物系数(K_(cmid))和生长末期作物系数(K_(cend))则相反。烤烟需水量最高,夏玉米最低;烤烟单作较烤烟间套作夏播大豆、夏玉米需水量增加,陕北分别增加10.63%、23.85%,关中分别增加9.38%、22.18%,陕南分别增加9.24%、19.85%。间套作模式可降低夏玉米和夏播大豆的水分亏缺(陕北夏玉米CWDI降低9.89%),但增加甘薯的亏缺(陕北甘薯CWDI增加4.28%)。[结论]陕西省粮烟复合种植制度的优化能够改善降水利用效率,减少农业灌溉用水。陕南适宜烟—薯间套作,陕北和关中地区均建议优先采用烤烟与夏玉米间套作,其次为烤烟与夏播大豆间套作。烤烟与夏玉米间套作较烤烟单作可减少约20%需水量,减少灌溉需求,有效缓解区域水资源短缺,为农业节水和气候变化背景下的可持续种植提供科学依据。展开更多
Crop water stress index(CWSI)is widely used for efficient irrigation management.Precise canopy temperature(T_(c))measurement is necessary to derive a reliable CWSI.The objective of this research was to investigate the...Crop water stress index(CWSI)is widely used for efficient irrigation management.Precise canopy temperature(T_(c))measurement is necessary to derive a reliable CWSI.The objective of this research was to investigate the influences of atmospheric conditions,settled height,view angle of infrared thermography,and investigating time of temperature measuring on the performance of the CWSI.Three irrigation treatments were used to create different soil water conditions during the 2020-2021 and 2021-2022 winter wheat-growing seasons.The CWSI was calculated using the CWSI-E(an empirical approach)and CWSI-T(a theoretical approach)based on the T_(c).Weather conditions were recorded continuously throughout the experimental period.The results showed that atmospheric conditions influenced the estimation of the CWSI;when the vapor pressure deficit(VPD)was>2000 Pa,the estimated CWSI was related to soil water conditions.The height of the installed infrared thermograph influenced the T_(c)values,and the differences among the T_(c)values measured at height of 3,5,and 10 m was smaller in the afternoon than in the morning.However,the lens of the thermometer facing south recorded a higher T_(c)than those facing east or north,especially at a low height,indicating that the direction of the thermometer had a significant influence on T_(c).There was a large variation in CWSI derived at different times of the day,and the midday measurements(12:00-15:00)were the most reliable for estimating CWSI.Negative linear relationships were found between the transpiration rate and CWSI-E(R^(2)of 0.3646-0.5725)and CWSI-T(R^(2)of 0.5407-0.7213).The relations between fraction of available soil water(FASW)with CWSI-T was higher than that with CWSI-E,indicating CWSI-T was more accurate for predicting crop water status.In addition,The R^(2)between CWSI-T and FASW at 14:00 was higher than that at other times,indicating that 14:00 was the optimal time for using the CWSI for crop water status monitoring.Relative higher yield of winter wheat was obtained with average seasonal values of CWSI-E and CWSI-T around 0.23 and 0.25-0.26,respectively.The CWSI-E values were more easily influenced by meteorological factors and the timing of the measurements,and using the theoretical approach to derive the CWSI was recommended for precise irrigation water management.展开更多
文摘以陕西1961—2010近50 a 22个站点的逐日气象数据为基础资料,计算其冬小麦生育期各旬需水量(ETi)以及作物缺水指数(CWDI),并根据农业干旱等级计算出研究区干旱频率,分析陕西冬小麦各生育期内干旱指数时空分布特征。结果表明:陕西冬小麦各生育期干旱频率为拔节抽穗期>灌浆成熟期>返青期>冬前生长期>越冬期;冬小麦重旱以上频率的空间分布由北向南逐渐减少;冬小麦干旱指数的年代际变化呈上升趋势,20世纪70年代和90年代干旱指数较高,1968年为突变年份。
文摘为建立东北地区春玉米干旱灾变过程动态监测方法体系,跟踪反馈干旱时空特征和发展趋势,该文在采用作物水分亏缺指数CWDI(crop water deficit index)作为干旱监测指标的基础上,针对分区域和特定生育期内传统作物系数(Kc)值的固定化设置现状,首先采用分段函数对作物系数(Kc)进行逐日估算,进而计算逐日CWDI;其次对干旱等级的临界阈值进行逐日估算,构建随春玉米发育进程变化的干旱等级动态划分标准。在此,该文以东北地区2018年春玉米干旱为例,基于逐日平均温度、最高温度、最低温度、降水、气压、风速、日照时数、相对湿度以及春玉米关键生育期数据等,分别计算了逐日和8 d合成的CWDI与改进CWDI,通过地面干旱调查数据对二者的监测结果进行检验,对其监测精度和空间连续性进行了比较和分析;利用改进CWDI对东北地区2018年春玉米干旱灾变过程进行动态监测,揭示了其时空特征及演变趋势。结果表明:1)基于改进CWDI的春玉米干旱监测结果与地面调查结果具有较高吻合度,整体判对率达到了75.7%,比CWDI监测的干旱判对率提高了8.1%;CWDI监测的干旱程度在不同行政区域交界处出现了明显突兀的变化,而改进CWDI则表现出良好的空间连续性,适用于春玉米干旱灾变过程动态监测之目的。2)2018年东北地区主要发生5月的春旱和7月下旬到8月中旬的伏旱,春旱从吉林西部开始发生并向西南方向不断扩展,消退方向与发展方向保持一致。伏旱从内蒙古东部、辽宁西部等地区向东部不断发展,之后由东、西两侧向中部不断消退。并且在玉米整个生育期内,均有一定程度的干旱发生。3)改进CWDI可以很好的反映出2018年5月22日前后大范围降水过程所引起的春旱面积减小、程度降低的过程,对降水因子敏感,可以实时表征逐日尺度降水增多引起的干旱强度变化。
文摘[目的]分析陕西省不同粮烟种植模式下的作物需水量及水分亏缺指数,筛选出高水分利用、免/低灌溉需水的粮烟种植模式。[方法]基于联合国粮食和农业组织(Food and Agriculture Organization of the United Nations,FAO)推荐的作物系数法,并运用水分亏缺指数模型(Crop water deficit index,CWDI),结合2014—2023年的气象、土壤数据和区域作物种植生育资料,分析陕北、关中和陕南地区烤烟、夏播大豆、甘薯和夏玉米单作及与烤烟间套作的作物系数、需水特性、水分亏缺及空间分布规律。[结果]生长初期作物系数(K_(cini))表现为陕南>关中>陕北,生长中期作物系数(K_(cmid))和生长末期作物系数(K_(cend))则相反。烤烟需水量最高,夏玉米最低;烤烟单作较烤烟间套作夏播大豆、夏玉米需水量增加,陕北分别增加10.63%、23.85%,关中分别增加9.38%、22.18%,陕南分别增加9.24%、19.85%。间套作模式可降低夏玉米和夏播大豆的水分亏缺(陕北夏玉米CWDI降低9.89%),但增加甘薯的亏缺(陕北甘薯CWDI增加4.28%)。[结论]陕西省粮烟复合种植制度的优化能够改善降水利用效率,减少农业灌溉用水。陕南适宜烟—薯间套作,陕北和关中地区均建议优先采用烤烟与夏玉米间套作,其次为烤烟与夏播大豆间套作。烤烟与夏玉米间套作较烤烟单作可减少约20%需水量,减少灌溉需求,有效缓解区域水资源短缺,为农业节水和气候变化背景下的可持续种植提供科学依据。
基金supported by the Project of State Grid Hebei Electric Power Co.,Ltd.(SGHEYX00SCJS2100077).
文摘Crop water stress index(CWSI)is widely used for efficient irrigation management.Precise canopy temperature(T_(c))measurement is necessary to derive a reliable CWSI.The objective of this research was to investigate the influences of atmospheric conditions,settled height,view angle of infrared thermography,and investigating time of temperature measuring on the performance of the CWSI.Three irrigation treatments were used to create different soil water conditions during the 2020-2021 and 2021-2022 winter wheat-growing seasons.The CWSI was calculated using the CWSI-E(an empirical approach)and CWSI-T(a theoretical approach)based on the T_(c).Weather conditions were recorded continuously throughout the experimental period.The results showed that atmospheric conditions influenced the estimation of the CWSI;when the vapor pressure deficit(VPD)was>2000 Pa,the estimated CWSI was related to soil water conditions.The height of the installed infrared thermograph influenced the T_(c)values,and the differences among the T_(c)values measured at height of 3,5,and 10 m was smaller in the afternoon than in the morning.However,the lens of the thermometer facing south recorded a higher T_(c)than those facing east or north,especially at a low height,indicating that the direction of the thermometer had a significant influence on T_(c).There was a large variation in CWSI derived at different times of the day,and the midday measurements(12:00-15:00)were the most reliable for estimating CWSI.Negative linear relationships were found between the transpiration rate and CWSI-E(R^(2)of 0.3646-0.5725)and CWSI-T(R^(2)of 0.5407-0.7213).The relations between fraction of available soil water(FASW)with CWSI-T was higher than that with CWSI-E,indicating CWSI-T was more accurate for predicting crop water status.In addition,The R^(2)between CWSI-T and FASW at 14:00 was higher than that at other times,indicating that 14:00 was the optimal time for using the CWSI for crop water status monitoring.Relative higher yield of winter wheat was obtained with average seasonal values of CWSI-E and CWSI-T around 0.23 and 0.25-0.26,respectively.The CWSI-E values were more easily influenced by meteorological factors and the timing of the measurements,and using the theoretical approach to derive the CWSI was recommended for precise irrigation water management.
