Abstract
This study developed a hydrological drought forecasting framework linked to the meteorological model and land surface model (LSM) considering hydrologic facilities and evaluated the feasibility of the Modified Surface Water Supply Index (MSWSI) for drought forecasts in South Korea. The Global Seasonal Forecast System version 5 (GloSea5) and variable infiltration capacity (VIC) models were adapted for meteorological and hydrological models for ensemble weather forecasts and corresponding hydrologic river and dam inflow forecasts, respectively. Instead of direct use for weather and runoff forecasts, the anomaly between the ensemble forecast and hindcast data for each month was computed. Then, the monthly forecasted weather and runoff were obtained by adding this anomaly and the statistical nominal values obtained from the average monthly runoff during the last 30 years. For the selection of drought index duration, past historical observation data and drought records were used, and the 3-month period of the MSWSI outperformed any other durations in the study area. In addition, the simulated monthly river and dam inflows agreed well with the observed inflows; therefore, the model-driven runoff data from the VIC model were usable for hydrological drought forecasts. A case study result for the 2015–2016 drought event demonstrated that the hydrological drought forecasting framework suggested in this study is reliable for drought forecasting up to a 2-month forecast lead time. It is therefore concluded that the proposed framework linked with GloSea5, the VIC model and MSWSI(3) provides useful information for supporting decision-making related to water supply and management.
Highlights
Drought forecasting is one of the most important natural disaster problems that humans must deal with, and various methods have been developed by many countries
The precipitation basins are affected by precipitation only, while the river and dam basins are affected by runoff and dam inflows in addition to precipitation, respectively
A hydrologic drought forecasting framework that coupled the meteorological Global Seasonal Forecast System version 5 (GloSea5) model and hydrological variable infiltration capacity (VIC) model was developed in this study and we evaluated the performance in South
Summary
Drought forecasting is one of the most important natural disaster problems that humans must deal with, and various methods have been developed by many countries. Center (CPC) has provided various kinds of meteorological forecasting information using the Climate. For meteorological drought forecasting, the forecasted precipitation and temperature data for mid- to long-term durations were used as input data for meteorological drought indices, such as the Standardized Precipitation Index (SPI) and Palmer. Drought Severity Index (PDSI) e.g., [1,2,3,4,5]. Hydrological droughts occur due to a lack of runoff, surface water and groundwater, and they represent the current natural hydrological conditions. Various hydrological drought indices have been used to quantitatively assess hydrological drought conditions e.g., [6,7,8,9].
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