干旱区生态环境知识资源中心(Arid): Spatiotemporal drought monitoring using bottom-up precipitation dataset (SM2RAIN-ASCAT) over different regions of Iran

Arid

DOI	10.1016/j.scitotenv.2021.146535
	Spatiotemporal drought monitoring using bottom-up precipitation dataset (SM2RAIN-ASCAT) over different regions of Iran
	Koohi, Sakine; Azizian, Asghar; Brocca, Luca
通讯作者	Azizian, A (corresponding author), Imam Khomeini Int Univ, Water Engn Dept, Qazvin, Iran.
来源期刊	SCIENCE OF THE TOTAL ENVIRONMENT
ISSN	0048-9697
EISSN	1879-1026
出版年	2021
卷号	779
英文摘要	Drought is a natural phenomenon that can significantly impacts on water resources studies, agricultural and environmental societies around the world, hence, accurate spatio-temporal monitoring of drought is very important. In this research, a comparative analysis of a newly developed precipitation dataset, SM2RAIN-ASCAT (which is based on bottom-up approach), with 40 ground-measured Iranian Meteorological Organization (IMO) precipitation data are performed to estimate the precipitation and monitor the drought events over diverse climate regions of Iran. The SPI index, as a widely used drought index, at the temporal resolution ranging from one month to one year is used to this aim, and the outputs are analyzed based on the statistical and categorical metrics. Results indicated that the highest correlation coefficient (CC) and lowest root mean square error (RMSE) between SM2RAIN-ASCAT and in situ observations are found at 10-day and monthly time scales. Analyzing both datasets using FAR and POD indices in the mid and long-term time scales indicated that the SM2RAINASCAT has a good performance in detecting rainy days. This product overestimate the precipitation values in extra-arid regions, while in humid and per-humid climate areas it tends to underestimation. Moreover, assessing the reliability of this product for drought monitoring showed that the SPI at 1, 3 and 6 month time scales are in good agreement with ground-based observations over different climate regions of Iran. At these temporal resolutions, the CC value between SPIs calculated based on in situ observations and SM2RAIN-ASCAT is higher than 0.7 in more than 75% of the meteorological stations. The efficiency of SM2RAIN-ASCAT in detecting drought periods in extra-arid and arid zones is relatively better than that of in humid and per-humid climates. In addition, the performance of this product for capturing wet periods in extra-arid to semi-arid regions is better than that of in Mediterranean and humid zones. Overall, the outcomes of this study demonstrated that SM2RAIN-ASCAT, despite poor performance in estimating precipitation in some regions, can be considered as a complementary to ground-gauge observations or an appropriate alternative dataset for drought analysis, especially in arid and semi-arid regions which include most parts of the world. (c) 2021 Elsevier B.V. All rights reserved.
英文关键词	Drought analysis Precipitation Remote sensing Standardized Precipitation Index Soil moisture
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000655686900001
WOS关键词	SOIL-MOISTURE ; RAINFALL ; INDEX ; SATELLITE ; PERFORMANCE ; CLIMATE
WOS类目	Environmental Sciences
WOS研究方向	Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/351665
作者单位	[Koohi, Sakine; Azizian, Asghar] Imam Khomeini Int Univ, Water Engn Dept, Qazvin, Iran; [Brocca, Luca] Res Inst Geohydrol Protect IRPI, Perugia, Italy
推荐引用方式 GB/T 7714	Koohi, Sakine,Azizian, Asghar,Brocca, Luca. Spatiotemporal drought monitoring using bottom-up precipitation dataset (SM2RAIN-ASCAT) over different regions of Iran[J],2021,779.
APA	Koohi, Sakine,Azizian, Asghar,&Brocca, Luca.(2021).Spatiotemporal drought monitoring using bottom-up precipitation dataset (SM2RAIN-ASCAT) over different regions of Iran.SCIENCE OF THE TOTAL ENVIRONMENT,779.
MLA	Koohi, Sakine,et al."Spatiotemporal drought monitoring using bottom-up precipitation dataset (SM2RAIN-ASCAT) over different regions of Iran".SCIENCE OF THE TOTAL ENVIRONMENT 779(2021).