Developing an Analysis Program to Estimate and Prediction Groundwater Droughts in Korea from Groundwater Time-Series Data.

Abstract:

This study is aimed at developing process to analyze and predict groundwater drought potentials for Winter and Spring droughts in Korea using a long-term groundwater monitoring data. So far, most drought researches have been focused on precipitation and stream-flow data, although these data are considered to be non-linear. Subsequently, the prediction of drought events has been very difficult in practice. In this study, we targets to analyze the groundwater system as an intermediate stage between precipitation and stream-flow, but still has semi-linear characteristics. By the analysis of past trends of groundwater time-series compared with drought events, we will identify characteristics of fluctuation between groundwater-level and precipitation of the year before the droughts. Then, the characteristics will be tested with recent drought events in Korea. For this analysis, The updated ATGT (Analysis Tool for Groundwater Time-series data program version 1.0 based on JAVA), that was developed for analyzing and presenting groundwater time-series data, basically to identify abnormal changes in groundwater fluctuations, will be presented with additional functions including cross-correlation between groundwater and drought based on the PYTHON language.