This work presents the results of the analysis of meteorological variables applying the modeling Ion-Wavelets in a hypothetical manner. In this case the Morlet wavelet transform is used, which is the result of a huge ...This work presents the results of the analysis of meteorological variables applying the modeling Ion-Wavelets in a hypothetical manner. In this case the Morlet wavelet transform is used, which is the result of a huge number of researches made in the80’s and applied to various physical phenomena derived from natural chaotic processes;the data were processed using the phenomenon “El Nino” and CO2 (Carbon dioxide) due to the fact that these are the meteorological phenomena which best adapt to our object of study correlating with distribution of Gauss and Morlet during the study period in the Puebla Valley.展开更多
基于2000-2020年生长季(4-10月)的MODIS-NDVI、LST影像,以植被供水指数(Vegetation Supply Water Index,VSWI)为干旱监测指标,利用小波分析、线性倾向率、重心迁移模型等方法分析贵州省干旱强度和干旱频率特征,并探讨农业干旱与土壤水...基于2000-2020年生长季(4-10月)的MODIS-NDVI、LST影像,以植被供水指数(Vegetation Supply Water Index,VSWI)为干旱监测指标,利用小波分析、线性倾向率、重心迁移模型等方法分析贵州省干旱强度和干旱频率特征,并探讨农业干旱与土壤水分和降雨量的关系,为贵州省农业干旱监测、抗旱提供参考依据。结果表明:(1)贵州省2000-2020年生长季(4-10月)VSWI整体上呈缓慢增加趋势,表明干旱有所缓解;干旱频率呈“西高东低”空间分布,干旱等级呈现黔西南州—安顺市—贵阳市—遵义市的干旱带,干旱程度由此轴线向西北和东南方向递减。轻旱面积多且呈减少趋势,中旱面积呈减少-增加-减少趋势,重旱面积少且波动较小。(2)农业干旱有两个主要振荡周期,第一个周期为7~9 a,振荡中心在2005年;第二个周期为15~18 a,基本贯穿整个研究期,振荡中心在2011年。贵州省农业干旱存在8和16 a左右的周期。(3)贵州省21年平均干旱重心位于黔西南州兴义市(104.99°E,25.03°N),月干旱重心和逐年干旱重心集中在贵阳市(106.73°E,26.58°N)、毕节市(105.28°E,27.30°N)和兴义市(104.90°E,25.08°N)。(4)VSWI与土壤水分的空间关系较复杂,但总体呈正相关关系,即土壤水分越低,VSWI越低,干旱越严重;同时降雨量与农业干旱的关系并不是完全为正相关,整体上两者的变化趋势具有相似性。展开更多
文摘This work presents the results of the analysis of meteorological variables applying the modeling Ion-Wavelets in a hypothetical manner. In this case the Morlet wavelet transform is used, which is the result of a huge number of researches made in the80’s and applied to various physical phenomena derived from natural chaotic processes;the data were processed using the phenomenon “El Nino” and CO2 (Carbon dioxide) due to the fact that these are the meteorological phenomena which best adapt to our object of study correlating with distribution of Gauss and Morlet during the study period in the Puebla Valley.