湖北农业科学2025，Vol.64Issue(1)：23-27,34,6.DOI:10.14088/j.cnki.issn0439-8114.2025.01.004
基于遥感与同化数据的干旱特征与水循环要素时空演变特征
Drought characteristics and spatio-temporal evolution characteristics of water cycle factors based on remote sensing and assimilation data
摘要
Abstract
Based on the Global Land Data Assimilation System as the data source,the temperature vegetation drought index was im-proved.On this basis,the drought characteristics were analyzed.The four assimilation data including evapotranspiration,groundwater runoff,precipitation and soil water storage were selected as water cycle elements,and the spatio-temporal evolution of water cycle ele-ments was analyzed using wavelet transform.The results showed that the correlation between the improved temperature vegetation drought index(TVDI)and soil moisture data had been improved.When the soil depth was between 0 cm and 10 cm,the correlation be-tween TVDI and soil moisture was the highest except for individual climatic regions.The correlation between TVDI and soil moisture in the warm season was better than that in the cold season except for the Northwest Desert region and the Inner Mongolia grassland areas.The annual precipitation in China was concentrated between 600 mm and 700 mm,with evapotranspiration below 500 mm.The annual groundwater runoff in China ranged from 100 mm to 250 mm,and the annual soil water storage capacity ranged from 460 mm to 540 mm.The annual evapotranspiration and annual precipitation in the Northwest Desert region,Tibetan Plateau and Northeast China showed a significant increase trend,and the annual soil water storage and annual groundwater runoff in the Northwest Desert region and North-east China showed a significant downward trend.关键词
干旱特征/水循环要素/时空演变/遥感/同化数据/温度植被干旱指数Key words
drought characteristics/water cycle elements/spatio-temporal evolution/remote sensing/assimilating data/tempera-ture vegetation drought index分类
天文与地球科学引用本文复制引用
刘艳群,王敏,黄观荣,李丽芳,李曹明..基于遥感与同化数据的干旱特征与水循环要素时空演变特征[J].湖北农业科学,2025,64(1):23-27,34,6.基金项目
韶关市科学技术局项目(230616148033947) （230616148033947）
