To efficiently manage droughts, a rapid change in crisis management is required from rehabilitation to preparedness. The objectives of this study are to analyze drought characteristics by investigating the trends of droughts and to develop a drought m...
To efficiently manage droughts, a rapid change in crisis management is required from rehabilitation to preparedness. The objectives of this study are to analyze drought characteristics by investigating the trends of droughts and to develop a drought monitoring method which also takes into consideration water supply systems of study area through water management organizations. Additionally, a drought outlook method has been developed which calculates SPI and PDSI as a meteorological drought index, taking advantage of an ensemble of techniques in climate models using mid and long-term weather forecasting dataacquired from APCC. Through the development of a drought monitoring and drought outlook method, damages due to droughts can be reduced and disasters can be prevented.
Using monthly SPI data from the period of 1980∼2009, annual, seasonal, and monthly trends have been estimated by applying the Mann-Kendall method to the Han River, Geum River, Nakdong River, Youngsan River and Sumjin River Basins. With the results from SPI(3), SPI(6) and a trend analysis, drought characteristics of river basins can be understood.
This study also evaluates droughts using SPI, PDSI, and MSWSI, which are used worldwide, referring specifically to 1994, 1995 and 2001 drought damage surveys. In conclusion, the SPI and PSDI methods do not consider water supplies through water supply infrastructures such as dams and reservoirs. Though the MSWSI method considers water supply infrastructure, this method is difficult to apply in real drought situation because of its lack of accuracy and complexity in calculating rainfall, reservoir storage, stream flow and groundwater levels.
This study established the importance of a drought index which can be used in real drought disaster situations and the study also emphases ways to find drought threshold factors depending on each region and area under consideration.
Finally, this study developed a concept of drought monitoring in which the region is divided into areas with municipal water supply, areas with agriculture water supply, areas with groundwater effects, areas with stream flow effects and areas with no effects. This study also suggests the use of an appropriate drought index according to the classification of the region. This drought monitoring method makes use of information obtained through TM from measurement stations like multipurpose-dams, agricultural dams, weather stations, rainfall stations, groundwater stations and water level stations. From now on, it is possible to accurately predict droughts by specifying trigger levels at monitoring points through continuous monitoring.
For predicting droughts, it is important to acquire reliable weather forecasting data to ensure better and more accurate drought analyses. According to similar studies, drought forecasting used past weather data, scenario assumptions, El-Nino, etc., to predict droughts. At present, most climate prediction models do not have good predictive capabilities for abnormal weather phenomena such as floods and droughts. So, establishment of reliable weather prediction techniques and drought outlook methods is imperative.
When dam operators make plans for dam operations and countermeasures for droughts, they take into consideration the average precipitation by frequency and inflow. But the use of past recurring data might not be reliable because of climate changes and abnormal weather events which could have different patterns in the future. A Drought Outlook Map, therefore, with meteorological drought prospects was made by analyzing SPI and PDSI through the acquisition of downscaled weather data at observatory points, which is used for generating mid and long-term data (1∼3 months) by APCC.
Drought monitoring and outlook techniques used in this study are more sophisticated drought evaluation techniques. But we need more detailed information and analysis that is reliable and accurate in real situations for disaster management of problems such as droughts. In the future, it is important to prepare for droughtsby developing a rainfall runoff watershed model which considers a drought information system.