Spatiotemporal Comparison of Drought in Shaanxi–Gansu–Ningxia from 2003 to 2020 Using Various Drought Indices in Google Earth Engine

环境科学 中国 农业 植被(病理学) 索引(排版) 自然地理学 地理 医学 计算机科学 万维网 病理 考古
作者
Xiaoyang Zhao,Haoming Xia,Baoying Liu,Wenzhe Jiao
出处
期刊:Remote Sensing [MDPI AG]
卷期号:14 (7): 1570-1570 被引量:25
标识
DOI:10.3390/rs14071570
摘要

As a common natural disaster, drought can significantly affect the agriculture productivity and human life. Compared to Southeast China, Northwest China is short of water year-round and is the most frequent drought disaster area in China. Currently, there are still many controversial issues in drought monitoring of Northwest China in recent decades. To further understand the causes of changes in drought in Northwest China, we chose Shaanxi, Gansu, and Ningxia provinces (SGN) as our study area. We compared the spatiotemporal characteristics of drought intensity and frequency in Northwest China from 2003 to 2020 showed by the Standardized Precipitation Index (SPI), Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Vegetation Health Index (VHI), Normalized Vegetation Supply Water Index (NVSWI), Soil Moisture Condition Index (SMCI), and Soil Moisture Agricultural Drought Index (SMADI). All of these indices showed a wetting trend in the SGN area from 2003 to 2020. The wetting trend of the VCI characterization is the most obvious (R2 = 0.9606, p < 0.05): During the period 2003–2020, the annual average value of the VCI in the SGN region increased from 28.33 to 71.61, with a growth rate of 153.57%. The TCI showed the weakest trend of wetting (R2 = 0.0087), with little change in the annual average value in the SGN region. The results of the Mann–Kendall trend test of the TCI indicated that the SGN region experienced a non-significant (p > 0.05) wetting trend between 2003 and 2020. To explore the effectiveness of different drought indices, we analyzed the Pearson correlation between each drought index and the Palmer Drought Severity Index (PDSI). The PDSI can not only consider the current water supply and demand situation but also consider the impact of the previous dry and wet conditions and their duration on the current drought situation. Using the PDSI as a reference, we can effectively verify the performance of each drought index. SPI-12 showed the best correlation with PDSI, with R values greater than 0.6 in almost all regions and p values less than 0.05 within one-half of the study area. SMADI had the weakest correlation with PDSI, with R values ranging −0.4~−0.2 and p values greater than 0.05 in almost all regions. The results of this study clarified the wetting trend in the SGN region from 2003 to 2020 and effectively analyzed the differences in each drought index. The frequency, duration, and severity of drought are continuously reduced; this helps us to have a more comprehensive understanding of the changes in recent decades and is of significance for the in-depth study of drought disasters in the future.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
刚刚
宗磬完成签到,获得积分10
1秒前
NexusExplorer应助搞怪不言采纳,获得10
2秒前
科研通AI5应助一天八杯水采纳,获得10
3秒前
3秒前
3秒前
4秒前
大模型应助琪琪扬扬采纳,获得10
5秒前
丘比特应助琪琪扬扬采纳,获得10
5秒前
共享精神应助琪琪扬扬采纳,获得10
5秒前
JamesPei应助dafwfwaf采纳,获得10
5秒前
叶子完成签到,获得积分10
5秒前
xuyun完成签到,获得积分10
5秒前
脑洞疼应助木棉采纳,获得10
5秒前
GGG发布了新的文献求助10
5秒前
zena92完成签到,获得积分10
6秒前
6秒前
听风发布了新的文献求助10
7秒前
一一发布了新的文献求助10
7秒前
CC完成签到,获得积分20
8秒前
9秒前
时生111完成签到 ,获得积分10
9秒前
kb发布了新的文献求助10
10秒前
dafwfwaf完成签到,获得积分20
10秒前
Snow完成签到 ,获得积分10
11秒前
11秒前
CC发布了新的文献求助10
11秒前
小苏打完成签到,获得积分10
12秒前
Xiaoxiao应助程琳采纳,获得10
12秒前
ycc完成签到 ,获得积分10
12秒前
畏寒的北完成签到,获得积分10
13秒前
爆米花应助单纯的雅香采纳,获得10
13秒前
俭朴的玉兰完成签到 ,获得积分10
13秒前
14秒前
14秒前
15秒前
15秒前
15秒前
adazbd发布了新的文献求助10
15秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527961
求助须知:如何正确求助?哪些是违规求助? 3108159
关于积分的说明 9287825
捐赠科研通 2805882
什么是DOI,文献DOI怎么找? 1540070
邀请新用户注册赠送积分活动 716926
科研通“疑难数据库(出版商)”最低求助积分说明 709808