2023
DOI: 10.3390/rs15184484
|View full text |Cite
|
Sign up to set email alerts
|

Copula-Based Joint Drought Index Using Precipitation, NDVI, and Runoff and Its Application in the Yangtze River Basin, China

Hongfei Wei,
Xiuguo Liu,
Weihua Hua
et al.

Abstract: Drought monitoring ensures the Yangtze River Basin’s social economy and agricultural production. Developing a comprehensive index with high monitoring precision is essential to enhance the accuracy of drought management strategies. This study proposes the standardized comprehensive drought index (SCDI) using a novel approach that utilizes the joint distribution of C-vine copula to effectively combine three critical drought factors: precipitation, NDVI, and runoff. The study analyzes the reliability and effecti… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
4
1

Relationship

0
5

Authors

Journals

citations
Cited by 6 publications
(1 citation statement)
references
References 45 publications
(46 reference statements)
0
1
0
Order By: Relevance
“…Furthermore, mutual feedback and time lag between vegetation and dry conditions are crucial for the construction of a drought index. Vegetation changes reflect the wet and dry conditions of the region, as well as the relationship between soil, atmosphere, and water [5,[26][27][28][29]. The Normalized Difference Vegetation Index (NDVI), land surface temperature (LST), precipitation (PRE), evapotranspiration (ET), and soil moisture (SM) were selected as independent variables to construct a remote sensing drought monitoring model.…”
Section: Characteristic Variablementioning
confidence: 99%
“…Furthermore, mutual feedback and time lag between vegetation and dry conditions are crucial for the construction of a drought index. Vegetation changes reflect the wet and dry conditions of the region, as well as the relationship between soil, atmosphere, and water [5,[26][27][28][29]. The Normalized Difference Vegetation Index (NDVI), land surface temperature (LST), precipitation (PRE), evapotranspiration (ET), and soil moisture (SM) were selected as independent variables to construct a remote sensing drought monitoring model.…”
Section: Characteristic Variablementioning
confidence: 99%