The transportation sector contributes significantly to global greenhouse gas emissions, so it is crucial to assess and measure the sustainability of transportation systems. In this context, this study was conducted to develop an integrated index through the use of the multi‐criteria decision analysis method. The method combines existing discrete indexes into one comprehensive evaluation of public transportation, resulting in the sustainable transport planning index (STPI). In the STPI model, sustainability of transportation systems is assessed based on social, economic, and environmental factors that support the implementation of zero emission busses. The weight of each indicator is determined through the analytical hierarchy process, where expert judgment is used to assess the relative importance of each indicator. Normalization of indicators is performed to ensure comparability and consistency. The final STPI index is calculated as the weighted average of the normalized indicators. The STPI model reduces bias in the decision‐making process by considering multiple aspects and utilizing a structured approach to transport planning. The results of this method can provide valuable insights for decision‐makers, public transport agencies, government ministries, the private sector, and other stakeholders. As case study model, the STPI model was applied to the public transport system of the United Kingdom from 2007 to 2019, however; the methodology and lessons learned are applicable to all countries that are in the process of assembling data sets to weigh trade‐offs and inclusions in relation to sustainable transit such as accessibility and health impacts.

In this study, the spatial and temporal trends of reference evapotranspiration (ET_o) and its components consisting of the energy term (EN_o) and the aerodynamic term (AE_o) were considered over the Korean Peninsula. The T-test and Mann–Kendall (MK) test were used to detect parameter trends after removing the effect of serial correlation from annual and seasonal time series between 1980 and 2017. Due to the lack of solar-radiation data for North Korea (NK), a regionally calibrated model based on South Korea (SK) weather data was developed to estimate daily solar radiation in NK. The results showed that spatial distribution of the ET_o increased southward in the range from 705 mm/year in the northeast to 1195 mm/year in the southeast of the Korean Peninsula. The spatial patterns of the EN_o and AE_o varied from the minimum in the north and increased southward, reaching their maximum values in the southern parts of the Korean Peninsula. The mean annual ET_o values of SK and NK were also compared. Over the 37-year period, mean annual evapotranspiration in SK was approximately 18% higher than that in NK. Moreover, mean areal EN_o and AE_o in SK were higher than in NK. The trend of the EN_o on annual and seasonal scales was also upward. In contrast, the trend of the AE_o decreased over the Korean Peninsula through all seasons and annual scales. These opposite trends in the EN_o and AE_o parameters mitigated the significant trends of the ET_o. Finally, the stronger significant upward trend of the energy term led to significant increasing trends of ET_o on the Korean Peninsula, with EN_o being the dominant component in the increase of the ET_o.

It is critical to understand how meteorological variables impact reference evapotranspiration $\left({\mathrm{ET}}_{\mathrm{o}}\right)$ since meteorological variables have a different effect on ${\mathrm{ET}}_{\mathrm{o}}$. This study examined the impact of meteorological variables on ${\mathrm{ET}}_{\mathrm{o}}$ on the Korean Peninsula under complex climatic and geographic conditions in order to understand how ${\mathrm{ET}}_{\mathrm{o}}$ and meteorological variables have changed over the past 42 years. Different geographical conditions were analyzed, including plains, mountains, and coastal areas on a seasonal and annual basis. ${\mathrm{ET}}_{\mathrm{o}}$ was estimated using the Penman-Monteith method by the Food and Agriculture Organization (FAO) using daily relative humidity $\left(\mathrm{RH}\right)$, solar radiation $\left({\mathrm{R}}_{\mathrm{s}}\right)$, maximum temperature $\left({\mathrm{T}}_{\max }\right)$, minimum temperature $\left({\mathrm{T}}_{\min }\right)$, and wind speed $\left({\mathrm{W}}_{\mathrm{s}}\right)$. According to the results, the maximum mean seasonal and annual ${\mathrm{ET}}_{\mathrm{o}}$ occurred on the southern coast, while the minimum occurred in the mountainous area and along the east coast. Seasonal ${\mathrm{ET}}_{\mathrm{o}}$ is highest in summer, and is lowest in winter for all regions. The investigation of meteorological variables on ${\mathrm{ET}}_{\mathrm{o}}$ revealed that the response varied by area, and the magnitudes of sensitivity varied by location and season. RH is the most critical meteorological variable to affect ${\mathrm{ET}}_{\mathrm{o}}$ in all seasons, except summer, when ${\mathrm{T}}_{\min }$ is the most sensitive parameter. The results revealed that different regions showed different responses to the change in ${\mathrm{ET}}_{\mathrm{o}}$ by changing the meteorological variables. Meteorological variables affecting ${\mathrm{ET}}_{\mathrm{o}}$ differ with different geologic conditions and seasons. in mountainous areas revealed almost similar responses to the change in RH, ${\mathrm{R}}_{\mathrm{s}}$, and ${\mathrm{T}}_{\max }$ (±10% change in ${\mathrm{ET}}_{\mathrm{o}}$) during the spring season. However, for other regions, RH and ${\mathrm{T}}_{\max }$ caused changes to ${\mathrm{ET}}_{\mathrm{o}}$ throughout, ranging from −15% to +20% in the plain area, −20% to +15% in the west and east coast, and −20% to +10% in the south coast. In addition, there were significant differences in parameter responses between regions and seasons, which was confirmed by the results.

This study investigates the future long-term variation of the runoff coefficient during dry and wet seasons in five major basins in South Korea. The variation is estimated from the Soil and Water Assessment Tool (SWAT) model outputs based on an ensemble of 13 different Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs) in representative concentration pathway (RCP) 4.5 and RCP 8.5 scenarios. The estimates show a temporal non-considerable increase rate of the runoff coefficient during the 21st century in both RCPs, in which the trend and uncertainty of the runoff coefficient in the dry season is projected as higher than that in the wet season. A sharp contrast between the trends of the two components of the runoff coefficient is found during the dry and wet seasons. Over the five major basins, a higher increase rate of runoff coefficient is projected in the northeastern part of the Han River basin and most of the area of the Nakdong River basin. The spatial variation in the runoff coefficient change also represents a relationship with the change in the percentage of each land cover/land use type over 109 subbasins, where the correlation of the wet-season runoff coefficient is calculated as higher than that of the dry season. This relationship is expected to vary with changes in temperature and precipitation during both seasons in three future periods.

This study conducts a comprehensive analysis of the impacts of climate change on South Korea’s climate and hydrology, utilizing a Multi-Model Ensemble (MME) approach with thirteen Climate Model Intercomparison Project Phase 5 (CMIP5) models under two Representative Concentration Pathways, RCP4.5 and RCP8.5. We observed an average temperature increase of up to 3.5 °C under RCP8.5 and around 2.0 °C under RCP4.5. Precipitation patterns showed an overall increase, particularly during the summer months, with increases up to 20% under RCP8.5 and 15% under RCP4.5, characterized by more intense and frequent rainfall events. Evapotranspiration rates are projected to rise by approximately 5–10% under RCP8.5 and 3–7% under RCP4.5. Runoff is expected to increase significantly, particularly in the summer and autumn months, with increases up to 25% under RCP8.5 and 18% under RCP4.5. This research focuses on employing the Precipitation Runoff Modeling System (PRMS) to project future streamflow across South Korea, with an emphasis on both monthly and seasonal scales to understand the varying impacts of climate change on different river basins. These climatic changes have profound implications for agriculture, urban water management, and ecosystem sustainability, stressing the need for dynamic and region-specific adaptation measures. This study emphasizes the critical role of localized factors, such as topography, land use, and basin-specific characteristics, in influencing the hydrological cycle under changing climatic conditions.

This study assesses changes in low flow seasonality in response to climate change using Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models. The precipitation‐runoff modelling system (PRMS) model was applied to project future streamflow using 13 global climate models (GCMs) under two emissions scenarios (representative concentration pathway [RCP] 4.5 and RCP8.5). Then, daily projected streamflows for each month in the reference and future periods were used to assess the monthly variation in low flows in Korean river basins. The results showed that high seasonal variation exists in low flows during the wet and dry seasons, including increasing low flows during the dry season and decreasing low flows during the wet season. The low flows are projected to decrease during the wet season by −6.48% in the 2025 period and by −2.59% in the 2085 period under RCP4.5. Under RCP8.5, the low flow is projected to decline in the wet season by −1.72% in 2025 and −4.35% in 2085. However, during the dry season, the low flow is projected to decrease slightly in the 2025 period (−0.49%) but increase significantly in the 2085 period (12.87%) under RCP4.5. Additionally, the low flow is projected to increase in the near future under RCP8.5 (1.87%). The results reveal that under RCP4.5, most Korean river basins are projected to shift from winter low flows to summer low flows. However, under RCP8.5, except for the Han River basin, which is projected to shift from winter low flows to summer low flows, other basins are expected to retain winter low flows. The findings of this study reveal that more consideration of future low flow conditions is needed, and a robust need exists for the preparation of an adaptation plan to ensure a sustainable water supply to prevent severe water shortages during low flows.