Drought is a recurrent phenomenon that may affect several sectors of life and the environment, and can be directly linked to water shortage problems. Drought can be considered as a three-dimensional event characterized by its severity, duration and affect area. One of the most general methods to assess drought is the calculation of drought indices [1
It has not been long since Korea established a national-level center to analyze drought information. There have been no criteria established regarding droughts, due to the lack of systematic drought monitoring and indices for managing droughts through quantitative analysis. In addition, Korea has had to rely on experiences without having established a drought index that fits its characteristics. As droughts have occurred every five years in Korea in recent years, a systematic study is required to mitigate the damages caused by droughts [5
Many definitions of drought have been suggested in the academic field depending on the specific area of interest. Dracup et al. suggested a classification system that defined drought by four criteria: the nature of the water deficit, averaging period, truncation level and method of regionalization [6
]. Wilhite and Glantz classified drought into six categories: meteorological, climatological, atmospheric, agricultural, hydrologic and water-management [7
]. The U.S. Weather Bureau defines drought as “lack of rainfall so great and long continued as to affect injuriously the plant and animal life of a place and to deplete water supplies both for domestic purposes and for the operation of power plants, especially in those regions where rainfall is normally sufficient for such purposes”. Palmer defined a drought period as “an interval of time, generally of the order of months or years in duration, during which the actual moisture supply at a given place rather consistently falls short of the climatically expected or climatically appropriate moisture supply” [8
Diverse drought indices have been developed and used across the globe to assess and monitor droughts. The Standardized Precipitation Index (SPI) is a drought index that was developed recently to improve the Palmer Drought Severity Index (PDSI) in the expression method of wetness and dryness, which is currently used in 40 countries for drought preparedness [9
The Palmer Drought Severity Index (PDSI), Soil Moisture Index (SMI), Standardized Precipitation Index (SPI) and Surface Water Supply Index (SWSI) are the representative drought indices. Each of these indices has strengths and weaknesses, and thus an appropriate index or combination of indices should be selected by considering what index best fits the hydrology of target region, characteristics of weather and water resources supply facilities [10
The SPI was designed by Mckee based on the idea that a reduction in precipitation with respect to the normal precipitation amount is the primary driver of drought, resulting in a successive shortage of water for different natural and human needs. The SPI, setting the time period on a monthly basis, typically 3, 6, 9 or 12 months, calculates the shortage of precipitation and defines drought intensity based on SPI value [11
]. The SPI, as calculated for a different period of time, can be applied to various fields based on the length of the time units. The SPI for short accumulation periods is used for agricultural purposes, while the SPI for relatively long accumulation periods is used for the supply and management of water resources. The calculated SPI enables the determination of precipitation probability necessary for resolving the current drought [12
Yoon et al. modified the PDSI for the Korean climatic environment by analyzing the characteristics of droughts in Korea [13
], Ryu et al. applied typically used drought indices to Nakdong River area and conducted comparative analysis to uncover the drought conditions [14
Dubrovsky et al. suggested, via analysis of the PDSI based on Global Climate Models (GCMs), that global warming will lead to increased drought, while pointing out that the SPI, which is based on precipitation data, does not reveal these climate-change impacts on drought conditions [15
]. This implies that a drought index must contain temperature data to be applied to the future climatic change scenario.
Drought indices are generally used for drought estimation and can help forecast drought caused by global warming [16
Two assumptions are needed to use SPI for drought forecasting. First, drought indicates that the variability of precipitation is more absolute than the variability of temperature and potential evapotranspiration (PET). Second, that temperature and PET are stationary and do not change with time [17
However, many recent studies have suggested problems with assumptions that do not consider variables related to temperature [17
]. Previous studies have already revealed that rising temperature is affecting drought. Various climate change models’ results also predict a greater temperature rise in the 21st century than in the past [22
There is a climate change scenario that acts as a way of predicting future temperatures and precipitation. The Representative Concentration Pathways (RCPs) form a set of greenhouse gas concentration and emissions pathways designed to support research on impacts and potential policy responses to climate change [23
]. As a set, the RCPs cover the range of forcing levels associated with emission scenarios published in the literature. The Representative Concentration Pathway (RCP) 8.5 corresponds to a high greenhouse gas emission pathway compared to the scenario literature [25
], and hence also to the upper bound of the RCPs. RCP 8.5 is a so-called ‘baseline’ scenario that does not include any specific climate mitigation target [27
This study used the temperature and precipitation data from the RCP 8.5 scenario provided by the Korea Meteorological Administration (KMA) to build data for analysis of future droughts. KMA provides point data for the major observatories in Korea based on the results of HadGEM3-RA (Met Office Hadley Centre, Exter, UK).
As a drought index, the reconnaissance drought index (RDI) was proposed by Tsakiris and Vangelis, utilizing the ratios of precipitation over reference crop evapotranspiration (
) for different time scales in order to be representative of the region of interest. The RDI was further investigated by Tsakiris et al. [28
]. One of the advantages of the RDI index is its sensitivity to drought events [30
To form an assessment of drought by climatic change scenario, this study used the SPI and RDI by dividing the periods into 3, 6 and 12 months, and analyzing these drought indices at 73 observatories located around the country.
This study drew the following conclusion from the analysis of meteorological drought based on the RCP 8.5 scenario conducted at nationwide observatories by applying the SPI and RDI.
According to the drought indices estimated at the observatories of Korea from 2011 to 2100, the SPI predicted the trend graph of drought index would be maintained over time. However, the RDI, with evapotranspiration taken into account, predicted the trend graph drought index would gradually decrease over time, meaning it was closer to dry conditions than the wet of the drought index.
The RDI showed the biggest drop at the twelve-month period. The result of comparing the drought indices from 73 observatories revealed that Daegu would be exposed to the risk of drought, as the region would have the highest drought intensity with the most number of extreme dry occurrences.
As a result of comparing the drought index distribution maps, SPI and RDI showed a similar tendency according to area location, but the difference in drought index values due to evapotranspiration increased with the time to 2100. In particular, the average RDI showed less than 0 in 2071–2100, and the probability of extreme drought after 2070 increased. It is predicted that the probability of drought will increase after 2070.
It is considered that the drought intensity will be extreme due to the rise of temperature and the probability that extreme intensity will occur is high according to the analysis of RDI based on the RCP 8.5 scenario. Furthermore, the amount of evapotranspiration is deemed essential for studying the meteorological drought to obtain the diversity of drought prediction.
The RCP 8.5 scenario is an extreme condition in which greenhouse gas mitigation policies are not implemented and greenhouse gases are emitted according to current trends. There is a limitation in that the evapotranspiration can be overestimated under conditions of high temperature increase effect compared to other RCP scenarios. Therefore, a drought index using RDI needs to be analyzed in consideration of this uncertainty.