This study developed a multi-criteria approach to spatially assess the robust water resource vulnerability in sub-basins and applied it to the Han River basin. The Intergovernmental Panel on Climate Change (IPCC) suggested three factors of vulnerability; namely, exposure, sensitivity and adaptive capacity were used in this study with respect to water quantity and quality. In this study, 16 water quantity indicators and 13 water quality indicators were selected to identify the vulnerability using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. Environmental and socioeconomic data were obtained from the national statistics database, and hydrological data were simulated using the calibrated Soil and Water Assessment Tool (SWAT) model. Expert surveys and Shannon entropy method were used to determine subjective and objective weights for all indicators, individually. As a result, water quantity-vulnerable sub-basins were associated with high water use and water leakage ratios. Water quality-vulnerable sub-basins were associated with relatively high values of maximum consecutive dry days and heatwave days. The water quantity indices of both weighting methods showed relatively similar spatial distributions, while the distribution of water quality indices was distinct. These results suggest that considering different weighting methods is important for assessing the robust water resource vulnerability of sub-basins.

The consequence of climate variations on hydrology remains the greatest challenging aspect of managing water resources. This research focused on the quantitative approach of the uncertainty in variations of climate influence on drought pattern of the Cheongmicheon watershed by assigning weights to General Circulation Models (GCMs) based on model performances. Three drought indices, Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Precipitation Index (SPI) and Streamflow Drought Index (SDI) are used for three durations 3-, 6-and 9-months. This study included 27 GCMs from Coupled Model Intercomparison Project 5 (CMIP5) and considered three future periods (2011-2040, 2041-2070 and 2071-2100) of the concentration scenario of Representation Concentration Pathway (RCP) 4.5. Compared to SPEI and SDI, SPI identified more droughts in severe or extreme categories of shorter time scales than SPEI or SDI. The results suggested that the discrepancy in temperature plays a significant part in characterizing droughts. The Reliability Ensemble Averaging (REA) technique was used to give a mathematical approximation of associated uncertainty range and reliability of future climate change predictions. The uncertainty range and reliability of Root Mean Square Error (RMSE) varied among GCMs and total uncertainty ranges were between 50% and 200%. This study provides the approach for realistic projections by incorporating model performance ensemble averaging based on weights from RMSE.Sustainability 2019, 11, 4283 2 of 20 used in management of water resources because of the existence of uncertainties in both future climate change projections from GCMs and assessments of climate variation effects on hydrology.This study used 27 GCM data to quantify model uncertainty in three future periods to assess annual precipitation in the Cheongmicheon watershed in South Korea. Established from a physical theory, GCMs replicate observed characteristics of the recent climate, which are important mechanisms to predict future climate involving temperature and extreme precipitation for uncertainty [8]. Describing and quantifying uncertainty in climate variation predictions is crucial not only for the sole aim of observation and acknowledgement but also for key perspectives to climate adaptation. The authors [9,10] pointed out that uncertainty occurs in climate models predictions as a result of the uncertainty in predicting anthropogenic forcing (that is, the emissions scenarios or scenario uncertainty) and intermodal variations in physical parameterization process due to random differences and dependence on fundamental conditions. Hence, the precariousness on various factors should be scrutinized in a quantitative assessment.Some studies on hydrologic impacts due to climate change have concluded that the choice of GCMs has a bigger impact on the hydrologic output compared to the choice of emission pathway [11,12]. Moreover, the structural component of the hydrologic models is a vital part in the projected changes. Thus, the meth...

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