In order to minimize the damages caused by long-term drought, appropriate drought management plans of the basin should be established with the drought forecasting technology. Further, in order to build reasonable adaptive measurement for future drought, the duration and severity of drought must be predicted quantitatively in advance. Thus, this study, attempts to forecast drought in Korea by using an Artificial Neural Network Model, and drought index, which are the representative statistical approach most frequently used for hydrological time series forecasting. SPI (Standardized Precipitation Index) for major weather stations in Korea, estimated using observed historical precipitation, was used as input variables to the MLP (Multi Layer Perceptron) Neural Network model. Data set from 1976 to 2000 was selected as the training period for the parameter calibration and data from 2001 to 2010 was set as the validation period for the drought forecast. The optimal model for drought forecast determined by training process was applied to drought forecast using SPI (3), SPI (6) and SPI (12) over different forecasting lead time (1 to 6 months). Drought forecast with SPI (3) shows good result only in case of 1 month forecast lead time, SPI (6) shows good accordance with observed data for 1-3 months forecast lead time and SPI (12) shows relatively good results in case of up to 1~5 months forecast lead time. The analysis of this study shows that SPI (3) can be used for only 1-month short-term drought forecast. SPI (6) and SPI (12) have advantage over long-term drought forecast for 3~5 months lead time.
The objective of this study is to standardize the calculation method of Palmer Drought Severity Index (PDSI) for the three Drought Management Agencies (DMA) in south Korea, and to evaluate the PDSI applicability. For comparison and review of the method, the code and input data of PDSI are collected from each DMA. The calculation method is the same, but the used input data (number of meteorological stations, normal year period, Available Water Capacity (AWC) of the soil) are different. Through discussions with drought experts and literature review, the standardized method is determined. 61 stations which have the data period more than 30 years are selected. Also the normal year is fixed for 30 years and updated every 10 years. The observed AWC is utilized using GIS data. Empirical equation of PDSI is re-estimated according to domestic climate characteristics. For evaluating the standardized PDSI, past drought events are investigated and drought indices including the existing SPI and PDSI are used for comparative analysis. As results, although the accuracy of standardized PDSI through ROC analysis is lower than SPI, the newly standardized PDSI is better than existing PDSI from DMA, Also it reasonably explain the spatial drought situation through the spatial analysis.
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