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Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
8.1K
A new drought index and its application based on geographically weighted regression (GWR) model and multi-source
Wei Wei1, Xing Zhang2, Chunfang Liu3,4
1College of Geography and Environmental Science, Northwest Normal University, Lanzhou, 730070, Gansu, China.
Environmental Science and Pollution Research International
|October 6, 2022
Summary
A new Geographically Integrated Dryness Index (GIDI) accurately monitors droughts. This index reveals 2007, 2009, and 2011 as major drought years in China, with spring and March most affected.
Area of Science:
- Environmental Science
- Climate Science
- Hydrology
Background:
- Drought is a major global natural disaster, necessitating accurate regional monitoring.
- Existing drought indices vary in scope and timescale, creating a need for integrated approaches.
Purpose of the Study:
- To develop and validate the Geographically Integrated Dryness Index (GIDI) for comprehensive drought monitoring.
- To analyze drought situations and trends in China from 2001 to 2019 using the new GIDI.
Main Methods:
- Integrated multiple indices (PCI, TCI, SMCI, VCI, SPEI) using geographically weighted regression.
- Developed the Geographically Integrated Dryness Index (GIDI).
- Analyzed spatial and temporal drought characteristics and trends in China.
Main Results:
- GIDI demonstrated excellent performance in monitoring medium- and long-term droughts.
- Identified 2003, 2016, and 2019 as wet years and 2007, 2009, 2011 as major drought years.
- Spring and March were identified as the most frequent drought season and month, respectively. Most regions in China show a fluctuating dry trend, except for some areas tending towards wetter conditions.
Conclusions:
- The GIDI offers a scientifically robust method for evaluating drought spatial and temporal distribution.
- The study highlights the dynamic nature of drought in China, with regional variations in trends.
- The integrated approach accounts for drought formation mechanisms and development timescales, enhancing monitoring capabilities.
Keywords:
ChinaDrought monitoringGeographically weighted regressionHot spot analysisSpatiotemporal data miningMore Related Videos
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