Abstract
Droughts affect economic, social, and environmental aspects in regions such as the Korean Peninsula, where more than 70% of the area comprises forests; hence, their monitoring is imperative. Despite the many indices and methodologies developed for monitoring, diagnosing droughts using reanalysis data is challenging as the data are characterized by low resolution and simplified vegetation classification. This study utilized a recently released ERA5 reanalysis dataset and its vegetation type information to derive indices that represent meteorological drought. Furthermore, their accuracy in South Korea, based on observation data, was evaluated. The spatio-temporal variability of droughts was analyzed using various factor and correlation analysis methods considering different atmospheric variables and soil moisture. The validity of the method was verified by comparing the observed and obtained data. Soil moisture in the first and second soil layers was sensitive to droughts in low-vegetation areas, thus requiring relatively frequent monitoring of precipitation and evapotranspiration near the topsoil. High-vegetation areas were most affected in the third layers one month after the drought. Hence, forest drought monitoring should consider precipitation, evapotranspiration, and runoff one month in advance. The results obtained herein can be used for forest drought monitoring one month before its occurrence.
Highlights
Despite the many indices and methodologies developed for monitoring, diagnosing droughts using reanalysis data is challenging as the data are characterized by low resolution and simplified vegetation classification
It was observed that severe droughts occurred in South Korea in 2013 and 2017 [14,15,25], and all seven drought indices correctly judged these cases as droughts
The Standardized Precipitation Index (SPI) and Rainfall Anomaly Index (RAI) exhibited different drought severity levels for each vegetation type with respect to the drought cases that were observed in 2017, and their simulation performances were considered excellent for South Korea
Summary
Despite the many indices and methodologies developed for monitoring, diagnosing droughts using reanalysis data is challenging as the data are characterized by low resolution and simplified vegetation classification. This study utilized a recently released ERA5 reanalysis dataset and its vegetation type information to derive indices that represent meteorological drought. Their accuracy in South Korea, based on observation data, was evaluated. Recently released reanalysis data were used to derive various indices that represent meteorological drought, and their accuracies in South Korea based on. The over 41.5-year spatio-temporal variability of droughts in South Korea was analyzed using various factor and correlation analysis methods These methods were used for high-resolution forest drought monitoring based on observations and modeling
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