Suggestion of Classification Method for Agricultural Drought Using Groundwater Level Change

Abstract

Since weather factors such as precipitation and temperature etc. show repeated patterns every year, it can be said that future changes can be predicted by analyzing past weather data. Therefore, when a drought occurs, the groundwater level is also lowered, so it can be seen that a change in the groundwater level can represent a drought. Like precipitation, groundwater level changes also have a high correlation with drought, so many researchers use SGI (standardized groundwater level index) to which the SPI (standardized precipitation index) method is applied to evaluate the severity of drought and predict trends. However, these approaches have the limitations to indicate the real groundwater system because the drought grades for the entire area are defined with the observation data of a single monitoring well without surrounding influences. When analyzing groundwater level fluctuations to understand the correlation with drought, it is necessary to calculate and apply the actual groundwater level that reflects groundwater use interference. Therefore, in this study, based on the long-term groundwater level data at 162 monitoring well installed before 2015 in Korea, the characteristics of groundwater level changes were analyzed and compared with the period of agricultural drought over the past five years. From the results, it can be confirmed that agricultural drought in regions is classified using the percentile of the SPI method by conducting a frequency analysis that the current groundwater level increase or decrease compared to the past average groundwater level.