Integrated Drought Monitoring and Evaluation through Multi-Sensor Satellite-Based Statistical Simulation

Jong-Suk Kim,Joo-Heon Lee,Tae-Woong Kim,Si Chen,Seo-Yeon Park,Jie Chen

doi:10.3390/rs13020272

Jong-Suk Kim, Joo-Heon Lee + Show 4 more

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https://doi.org/10.3390/rs13020272

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Abstract

To proactively respond to changes in droughts, technologies are needed to properly diagnose and predict the magnitude of droughts. Drought monitoring using satellite data is essential when local hydrogeological information is not available. The characteristics of meteorological, agricultural, and hydrological droughts can be monitored with an accurate spatial resolution. In this study, a remote sensing-based integrated drought index was extracted from 849 sub-basins in Korea’s five major river basins using multi-sensor collaborative approaches and multivariate dimensional reduction models that were calculated using monthly satellite data from 2001 to 2019. Droughts that occurred in 2001 and 2014, which are representative years of severe drought since the 2000s, were evaluated using the integrated drought index. The Bayesian principal component analysis (BPCA)-based integrated drought index proposed in this study was analyzed to reflect the timing, severity, and evolutionary pattern of meteorological, agricultural, and hydrological droughts, thereby enabling a comprehensive delivery of drought information.

Highlights

State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Department of Civil and Environmental Engineering, Hanyang University (ERICA), Abstract: To proactively respond to changes in droughts, technologies are needed to properly diagnose and predict the magnitude of droughts
We proposed an integrated drought assessment method to comprehensively convey drought information to the public and conducted statistical simulations to determine spatial sensitivity to various types of droughts to provide tailored information on local drought responses in a changing climate
The standardized precipitation index (SPI) is a drought index developed with the idea that it is initiated by a decrease in precipitation, thereby causing water shortage

Summary

Introduction

The characteristics of meteorological, agricultural, and hydrological droughts can be monitored with an accurate spatial resolution. A remote sensing-based integrated drought index was extracted from 849 sub-basins in Korea’s five major river basins using multi-sensor collaborative approaches and multivariate dimensional reduction models that were calculated using monthly satellite data from 2001 to 2019. The Bayesian principal component analysis (BPCA)-based integrated drought index proposed in this study was analyzed to reflect the timing, severity, and evolutionary pattern of meteorological, agricultural, and hydrological droughts, thereby enabling a comprehensive delivery of drought information. Many researchers have been trying to monitor and predict droughts accurately, and the development of drought monitoring techniques based on satellite remote sensing (RS) data (as a representative method) has garnered special interest in recent years [4,5,6,7,8,9].

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