干旱区生态环境知识资源中心(Arid): 融合GPM降水数据的土壤干旱遥感监测

Arid

	融合GPM降水数据的土壤干旱遥感监测
其他题名	Remote sensing monitoring of soil drought in Shenmu City, Shaanxi Province integrating GPM precipitation data
	谭惠芝; 尹倩; 姬莉雯; 芦倩; 卢晓宁; 崔林林; 夏志业; 徐维新; 陈军
来源期刊	干旱区研究
ISSN	1001-4675
出版年	2021
卷号	38 期号:2 页码:1001-4675
中文摘要	全球气候变暖导致干旱趋势加重,对西北干旱半干旱区农牧业生产造成严重威胁。考虑到陕西省神木市具有典型的黄土高原地貌特征,以及降水对复杂地貌背景区干旱的决定性作用,本研究应用高精度的GPM(Global Precipitation Measurement)降水数据,建立土壤干旱遥感监测模型,开展能够揭示土壤相对湿度的应用分析研究。结果表明:结合GPM降水数据建立的综合植被、温度和降水的土壤干旱遥感监测模型,能准确的揭示神木市土壤表层10 cm相对湿度,模型中温度和降水的权重较高,体现出温度和降水对区域干旱的主导作用;神木市作物生长季旱情整体处于轻旱强度,平均发生频率为64.44%,且中旱>轻旱>重旱>特旱,干旱强度和发生频率均呈现出西北高东南低的空间分异特征;410月干旱强度整体由轻旱发展至重旱,最后干旱消失。季节上,神木市春旱现象严重,且以中旱发生频率最高。20012019年神木市旱情呈略微减轻趋势,但红碱淖湿地因年均气温和年蒸发量明显上升,干旱情况加剧。
英文摘要	Global warming has aggravated the drought trend, producing a severe threat to agriculture and animal husbandry in the arid and semi-arid regions of northwest China. The existing remote sensing methods for monitoring drought mostly only consider vegetation and temperature, ignoring the role of precipitation. Additionally, most research is limited to the classification of relative drought levels. Our research starts from the typical landform features of the Loess Plateau in Shenmu City, Shaanxi Province, and the severity of drought stress in the Hongjiannao wetland. Considering the decisive role of precipitation on drought, especially in complex geomorphic background areas, we apply higher-precision GPM precipitation data to conduct a comprehensive drought model, which can truly reveal the relative humidity of the soil. The results show that the soil drought remote sensing monitoring model (SMMI=0.384VCI + 0.769TCI + 0.640PCI-0.022), which comprehensively considers vegetation, temperature, and precipitation, can accurately predict the relative humidity within 10 cm of the soil surface in Shenmu. The equal weights of temperature and precipitation in the model indicate that drought in this area is primarily determined by temperature-led evapotranspiration and the water supply of precipitation. The overall crop growth season in Shenmu is in a state of light drought, and the average frequency of drought occurrence is 64.44% (moderate drought > mild drought > severe drought > extraordinary drought). The intensity and frequency of drought present a spatial differentiation characteristic of being higher in northwest and lower in the southeast. Although the frequency of extreme drought is low, the geographical difference is significant. The frequency of mild drought is high, but with a less evident geographical difference. The weakening of the winter monsoon caused a decrease in precipitation. Therefore, the drought intensity of Shenmu gradually developed from a light drought in April to a severe drought between late May and early June. Affected by the southeast monsoon in July, the rainfall increases, and the severity of drought decreases. After mid-August, Shenmu enters into a state dominated by the absence of drought, and into the end of October, there is no drought at all. In terms of seasons, the spring drought is severe, and is characterized by the highest frequency of moderate drought. Although the frequency of summer drought is quite low, the frequency of extreme drought is higher than that of spring. The autumn drought was of the lowest frequency and a light drought dominated. Over 19 years, the drought trend in Shenmu showed a slight reduction, but that of Hongjiannao wetland showed an increase due to the significant increase in annual evaporation.
中文关键词	干旱 ; 土壤相对湿度 ; 神木市
英文关键词	GPM MODIS global precipitation measurement moderate-resolution imaging spectroradiometer drought relative soil humidity Shenmu City
类型	Article
语种	中文
国家	中国
收录类别	CSCD
WOS类目	Agriculture
CSCD记录号	CSCD:6951315
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/354289
作者单位	谭惠芝, 成都信息工程大学资源环境学院, 成都, 四川 610225, 中国.; 尹倩, 成都信息工程大学资源环境学院, 成都, 四川 610225, 中国.; 姬莉雯, 成都信息工程大学资源环境学院, 成都, 四川 610225, 中国.; 卢晓宁, 成都信息工程大学资源环境学院, 成都, 四川 610225, 中国.; 崔林林, 成都信息工程大学资源环境学院, 成都, 四川 610225, 中国.; 夏志业, 成都信息工程大学资源环境学院, 成都, 四川 610225, 中国.; 徐维新, 成都信息工程大学资源环境学院, 成都, 四川 610225, 中国.; 陈军, 成都信息工程大学资源环境学院, 成都, 四川 610225, 中国.; 芦倩, 陕西省神木市气象局, 神木, 陕西 719300, 中国.
推荐引用方式 GB/T 7714	谭惠芝,尹倩,姬莉雯,等. 融合GPM降水数据的土壤干旱遥感监测[J],2021,38(2):1001-4675.
APA	谭惠芝.,尹倩.,姬莉雯.,芦倩.,卢晓宁.,...&陈军.(2021).融合GPM降水数据的土壤干旱遥感监测.干旱区研究,38(2),1001-4675.
MLA	谭惠芝,et al."融合GPM降水数据的土壤干旱遥感监测".干旱区研究 38.2(2021):1001-4675.