Drought is generally defined as a condition of water scarcity, originating from a complex interaction between atmospheric, hydrological, and socio-economic factors. Therefore, sufficient rainfall is not the only requirement for avoiding drought, but effective water resource management and policy for the entire watershed must also be implemented (Booker et al., 2005; Khan et al., 2016; Palazzo et al., 2017). Recent climate change has produced unprecedented drought events with abnormal severity and duration (Trenberth et al., 2014).
Khan et al. (2016) highlighted the importance of a proper water policy to consider water resources that impact economic growth. According to Booker et al. (2005), water use, regions, and drought control strategies have economic trade-offs. It focused on the importance of political and institutional jurisdictions for water resource managmenet. Palazzo et al. (2017) emphasized the necessity of considering biophysical, demographic, ecological, and economic principles for managing water resources efficiently.
To manage water resources efficiently with a policy to reduce drought damage, it is necessary to analyze the drought in administrative divisions. Many studies have been conducted on the drought analysis of several watersheds (Maity et al., 2013; Kallache et al., 2013; Malik et al.,2019), but drought studies focusing on administrative divisions are insufficient.
Most disaster management actions (mitigation, preparedness, response, and recovery) are adopted and applied in administrative systems and divisions. For example, implementing structural/nonstructural measures and checking and quantifying drought damage costs are often completed within administrative boundaries. However, few efforts have been devoted to identifying the critical impact factors of drought with respect to administrative divisions in a country.
The severity of drought changes depending on the duration and regional characteristics. Drought indices, such as the standardized precipitation index (SPI), can be utilized to quantify drought. Many drought indices have been proposed and applied, including the SPI (Mckee et al., 1993) and the Palmer Drought Severity Index (PDSI; Palmer., 1965). SPI is based on precipitation and has been utilized in many studies due to its simplicity (Kallache et al., 2013; Tsakiris & Vangelis., 2004; Livada & Assimakopoulos., 2007; Guttman., 1998). The PDSI describes the moisture conditions and is widely used to measure the cumulative water balance. According to Guttman (1998), PDSI lacks consistency in spatial distribution and is inappropriate for drought analysis that determines spatial variability. However, SPI is determined to be suitable for analysis due to spatial variation, and it has been widely applied to spatial analysis (Tsakiris & Vangelis., 2004; Livada & Assimakopoulos., 2007).
To develop proactive drought risk management, the cause-and-effect relationship between drought occurrence and hydrometeorological factors should be identified. Maity et al. (2013) found that a drought event was triggered by hydrometeorological factors in two watersheds in Indiana, USA. According to Maity et al., soil moisture, precipitation, and runoff can be used as drought triggers with a 1 month lead time. It is possible to access the conditions of water resources in areas with data on hydrometeorological factors. SPI (Mckee et al., 1993) is the drought index, which represents drought severity based on precipitation. Through the relationship between hydrometeorological factors and SPI, drought impact factors (DIF) can be identified, and various statistical methods can be utilized to do that.
Interpreting the results from diverse perspectives, information about the impact on the occurrence and mechanism of drought can be found. An approach with spatio-temporal analysis is required to determine the drought impact due to the characteristics of the area. Haslinger and Blöschl (2017) identified atmospheric drought events based on drought duration, intensity, and severity. Using the proposed method, the analysis focused on determining the trends and characteristics of drought due to space-time patterns. Kallache et al. (2013) analyzed dry spells and spatial patterns using a multivariate extreme value model. The results indicated that the dry spells in subbasin are influenced by the topography and spatial distance from other subbassins. Livada and Assimakopoulos (2007) attributed the drought in Greece to spatiotemporal variability using 51 years of precipitation data. So far, studies have evaluated drought trends in relation to spatio-temporal variability, but analysis of the relationship between specific spatio-temporal characteristics and drought is lacking.
Scenarios can be utilized to determine future development processes in systems with various uncertainties. It is possible to combine several types of system information to establish a plan. Due to the features that reflect changing conditions, a flexible response is possible. To establish the scenario in the context of uncertainty, we first need to recognize the problem. Next, we identify the factors that affect the problem and rank them to determine the importance and degree of uncertainty. The determined uncertainty axis was utilized to construct the scenario and named accordingly. A previous study has suggested to decide the possible future or direction of the scenario and identify the common aspects of various scenarios (Kang & Lansey., 2014). In this study, the severity of drought and changes in hydrological and meteorological factors are uncertain. Herman et al. (2016) developed a bottom-up method for synthetic streamflow generation by increasing the frequency and severity of droughts. According to the study, this method is a simple way to determine the effects of frequency and magnitude. Conversely, a scenario based on the top -down method using a general circulation model (GCM) to regional climate models (RCM) was developed (Ghosh & Mujumdar., 2007). However, covering all hydrologic status in a district is needed to help decision -makers be ready for an unprecedented drought. In this study, the drought scenario describes the condition of water resources in the each area that can be developed when a future drought occurs. It is possible to explain future water resource conditions specifically through drought scenarios and propose effective precautions and responses.
The novelty of this study is the identification of DIF and the construction of drought scenarios in administrative divisions. First, the DIF for each administrative division was derived using principal component analysis (PCA) with hydrometeorological factors as input and SPI as the output. The results of PCA are analyzed to determine spatiotemporal variability and are utilized in the construction of drought scenarios. Figure 1 illustrates the framework of the study. The results of this study can be used to manage water resource policies for reducing drought damage.