Agrometeorological disasters severely impact agriculture in Heilongjiang Province.Flood is one of the main agrometeorological disasters in Heilongjiang Province.The temporal change in flood events in Heilongjiang Prov...Agrometeorological disasters severely impact agriculture in Heilongjiang Province.Flood is one of the main agrometeorological disasters in Heilongjiang Province.The temporal change in flood events in Heilongjiang Province from 1986to 2015 was studied using Mann-Kendall and Morlet wavelet methods,respectively.The results of Mann-Kendall analysis showed that the disaster rates of flood gradually stabilized from 1986 to 2015 with a confidence level of 99%.The Morlet wavelet variance analysis revealed that disaster rates of flood changed periodically at time scales of 3a,7a and 18a in Heilongjiang Province during1986-2015.The dominant period of the variation of flood disaster rate was about 18a over the past 30 years.The flood disaster rates were indicated in a positive phase during the period of 2016-2020 by the fitting curve of Morlet wavelet analysis.The annual average flood disaster indexes of single station,during 1986-2015 years were calculated,according to the precipitation data at 31 stations in Heilongjiang Province and the GIS software was used to analyze the spatial change in flood disasters in Heilongjiang Province from1986-2015.The results demonstrated that the southwest area of Heilongjiang Province was highly hazardous region of flood.The flood indices in the northern part of Songnen Plain and southwest of Heilongjiang Province presented the increment trends.展开更多
[目的]研究中部地区农业水土资源开发利用过程中能源消耗碳排放的时空格局演变规律,揭示其主要驱动因素,为助推中部地区农业低碳化绿色转型发展和实现“双碳”目标提供理论和数据参考。[方法]基于2010—2022年中部地区6省的社会经济数据...[目的]研究中部地区农业水土资源开发利用过程中能源消耗碳排放的时空格局演变规律,揭示其主要驱动因素,为助推中部地区农业低碳化绿色转型发展和实现“双碳”目标提供理论和数据参考。[方法]基于2010—2022年中部地区6省的社会经济数据,考察农业水土资源利用中能源消耗的碳排放,采用IPCC碳排放系数法测算2010—2022年中部地区农业碳排放量,借助Kaya恒等式和完全分解方法LMDI(logarithmic mean divisia index)加法形式,探讨农业碳排放的驱动因素及其贡献值,运用ArcGIS可视化深入剖析中部各省农业碳排放在时空维度上的演变趋势,并探析水土资源匹配度与农业碳排放之间的关系。[结果]①2010—2022年中部地区农业碳排放总量呈现先快速上升后波动下降的趋势。农业碳排放的环比增长率经历了阶段性下降演变过程。②农业碳排放强度是促使中部地区农业碳减排的最主要因素,农业水资源经济产出则是导致农业碳排放增长的第一大要素。2010—2022年研究区累计农业碳排放贡献值达562.28×10^(4) t。农业水资源经济产出因素和单位播种面积的农业用水量因素对中部地区农业碳排放的贡献存在正负两个方向的变动。③提高农业水土资源匹配度有助于抑制农业碳排放,但对各省的农业碳排放影响程度存在差异。[结论]未来应关注水土资源时空匹配问题及其生态环境效应,因地制宜采取差别化的耕作模式,优化配置和改善农业水土资源开发利用方式,促进农业低碳化转型。展开更多
目的为探究大气污染物与植被生长状况之间的相互影响,方法基于美国国家航空航天局(national aeronautics and space adminidtration,NASA)提供的归一化植被指数(normalized difference vegetation index,NDVI)与空气质量在线监测分析平...目的为探究大气污染物与植被生长状况之间的相互影响,方法基于美国国家航空航天局(national aeronautics and space adminidtration,NASA)提供的归一化植被指数(normalized difference vegetation index,NDVI)与空气质量在线监测分析平台提供的空气质量指数(air quality index,AQI),采用Kriging插值、一元线性回归和相关性分析等方法,对黄河中下游地区的河南省、山东省、山西省、陕西省,海河流域的河北省和重要城市(北京市和天津市)的AQI与NDVI时空分布特征进行解释,并分析其相关性。结果结果表明:(1)2014—2016年,AQI年均值呈显著下降趋势,每年AQI数值冬季最高,春秋相对较低,夏季最低,且呈现明显的区域差异性,出现中间高两侧低的“中心-外围”结构;2017年后,夏季AQI反而高于春秋季的。(2)2014—2020年,NDVI波动上升,上升斜率为0.0041/a。总体上,NDVI上升的面积占研究区总面积的93.76%,且极显著和显著上升趋势的面积分别占16.32%和12.09%。结论黄河中下游地区和海河流域AQI与NDVI时空格局及相关分析结果可以为气候变化对环境的影响研究提供理论基础。展开更多
基金Supported by China Clean Development Mechanism Project(2014101)。
文摘Agrometeorological disasters severely impact agriculture in Heilongjiang Province.Flood is one of the main agrometeorological disasters in Heilongjiang Province.The temporal change in flood events in Heilongjiang Province from 1986to 2015 was studied using Mann-Kendall and Morlet wavelet methods,respectively.The results of Mann-Kendall analysis showed that the disaster rates of flood gradually stabilized from 1986 to 2015 with a confidence level of 99%.The Morlet wavelet variance analysis revealed that disaster rates of flood changed periodically at time scales of 3a,7a and 18a in Heilongjiang Province during1986-2015.The dominant period of the variation of flood disaster rate was about 18a over the past 30 years.The flood disaster rates were indicated in a positive phase during the period of 2016-2020 by the fitting curve of Morlet wavelet analysis.The annual average flood disaster indexes of single station,during 1986-2015 years were calculated,according to the precipitation data at 31 stations in Heilongjiang Province and the GIS software was used to analyze the spatial change in flood disasters in Heilongjiang Province from1986-2015.The results demonstrated that the southwest area of Heilongjiang Province was highly hazardous region of flood.The flood indices in the northern part of Songnen Plain and southwest of Heilongjiang Province presented the increment trends.
文摘[目的]研究中部地区农业水土资源开发利用过程中能源消耗碳排放的时空格局演变规律,揭示其主要驱动因素,为助推中部地区农业低碳化绿色转型发展和实现“双碳”目标提供理论和数据参考。[方法]基于2010—2022年中部地区6省的社会经济数据,考察农业水土资源利用中能源消耗的碳排放,采用IPCC碳排放系数法测算2010—2022年中部地区农业碳排放量,借助Kaya恒等式和完全分解方法LMDI(logarithmic mean divisia index)加法形式,探讨农业碳排放的驱动因素及其贡献值,运用ArcGIS可视化深入剖析中部各省农业碳排放在时空维度上的演变趋势,并探析水土资源匹配度与农业碳排放之间的关系。[结果]①2010—2022年中部地区农业碳排放总量呈现先快速上升后波动下降的趋势。农业碳排放的环比增长率经历了阶段性下降演变过程。②农业碳排放强度是促使中部地区农业碳减排的最主要因素,农业水资源经济产出则是导致农业碳排放增长的第一大要素。2010—2022年研究区累计农业碳排放贡献值达562.28×10^(4) t。农业水资源经济产出因素和单位播种面积的农业用水量因素对中部地区农业碳排放的贡献存在正负两个方向的变动。③提高农业水土资源匹配度有助于抑制农业碳排放,但对各省的农业碳排放影响程度存在差异。[结论]未来应关注水土资源时空匹配问题及其生态环境效应,因地制宜采取差别化的耕作模式,优化配置和改善农业水土资源开发利用方式,促进农业低碳化转型。
文摘目的为探究大气污染物与植被生长状况之间的相互影响,方法基于美国国家航空航天局(national aeronautics and space adminidtration,NASA)提供的归一化植被指数(normalized difference vegetation index,NDVI)与空气质量在线监测分析平台提供的空气质量指数(air quality index,AQI),采用Kriging插值、一元线性回归和相关性分析等方法,对黄河中下游地区的河南省、山东省、山西省、陕西省,海河流域的河北省和重要城市(北京市和天津市)的AQI与NDVI时空分布特征进行解释,并分析其相关性。结果结果表明:(1)2014—2016年,AQI年均值呈显著下降趋势,每年AQI数值冬季最高,春秋相对较低,夏季最低,且呈现明显的区域差异性,出现中间高两侧低的“中心-外围”结构;2017年后,夏季AQI反而高于春秋季的。(2)2014—2020年,NDVI波动上升,上升斜率为0.0041/a。总体上,NDVI上升的面积占研究区总面积的93.76%,且极显著和显著上升趋势的面积分别占16.32%和12.09%。结论黄河中下游地区和海河流域AQI与NDVI时空格局及相关分析结果可以为气候变化对环境的影响研究提供理论基础。
