• Atmosphere
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• v.29 no.4
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• pp.391-401
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• 2019

This study first investigates the changes of the mean and extreme temperatures and precipitation in East Asia (EA) under stabilized 1.5℃ and 2℃ warming conditions above preindustrial levels provided by HAPPI project. Here, five model with 925 members for 10-year historical period (2006~2015) and 1.5/2.0℃ future warming scenarios (2091~2100) have been used and monthly based data have been analyzed. The results show that the spatial distribution fields over EA and domain averaged variables in HAPPI 1.5/2.0℃ hindcast simulations are comparable to observations. It is found that the magnitude of mean temperature warming in EA and Korea is similar to the global mean, but for extreme temperatures local higher warming trend for minimum temperature is significant. In terms of precipitation, most subregion in EA will see more increased precipitation under 1.5/2.0℃ warming compared to the global mean. These attribute for probability density function of analyzed variables to get wider with increasing mean values in 1.5/2.0℃ warming conditions. As the result of vulnerability of 0.5℃ additional warming from 1.5 to 2.0℃, 0.5℃ additional warming contributes to the increases in extreme events and especially the impact over South Korea is slightly larger than EA. Therefore, limiting global warming by 0.5℃ can help avoid the increases in extreme temperature and precipitation events in terms of intensity and frequency.

• Journal of Korea Water Resources Association
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• v.41 no.9
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• pp.907-917
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• 2008

This study investigates differences in hydrological responses to the climatic scenarios resulting from the use of different three hydrological models, PRMS, SLURP, and SWAT. First, the capability of the three models in simulating the present climate water balance components is evaluated at Andong-dam watershed. And then, the results of the models in simulating the impact using hypothetical climate change scenarios are analyzed and compared. The results show that three models have similar capabilities in simulating observed data. However, greater differences in the model results occur when the models are used to simulate the hydrological impact under hypothetical climate change. According as temperature change grows, the differences between model results is increasing because of differences of the evapotranspiration estimation methods. The results suggest that technique that consider the uncertainty by using different hydrological models will be needed when climate change impact assessment on water resources.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.5
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• pp.77-87
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• 2014

The impacts of climate change on upland crops is great significance for water resource planning, estimating crop water demand and irrigation scheduling. The objective of this study is to predict upland crop evapotranspiration, effective rainfall and net irrigation requirement for upland under climate change, and changes in the temporal trends in South Korea. The changes in consumptive use and net irrigation requirement in the six upland crops, such as Soybeans, Maize, Potatoes, Red Peppers, Chinese Cabbage (spring and fall) were determined based on the soil moisture model using historical meteorological data and climate change data from the representative concentration pathway (RCP) scenarios. The results of this study showed that the average annual upland crop evapotranspiration and net irrigation requirement during the growing period for upland crops would increase persistently in the future, and were projected to increase more in RCP 8.5 than those in RCP 4.5 scenario, while effective rainfall decreased. This study is significant, as it provides baseline information on future plan of water resources management for upland crops related to climate variability and change.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.1
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• pp.71-79
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• 2017

Climate change phenomenon is posing a serious threat to sustainable corn production in Ghana. This study investigated the impacts of climate change on the rain-fed corn yield in the Dangme East district, Ghana by using Aquacrop model with a daily weather data set of 22-year from 1992 to 2013. Analysis of the weather data showed that the area is facing a warming trend as the numbers of years hotter and drier than the normal seemed to be increasing. Aquacrop model was assessed using the limited observed data to verify model's sufficiency, and showed credible results of $R^2$ and Nash-Sutcliffe efficiency (NSE). In order to simulate the corn yield response to climate variability four climate change scenarios were designed by varying long-term average temperature in the range of ${\pm}1^{\circ}C{\sim}{\pm}3^{\circ}C$ and average annual rainfall to ${\pm}5%{\sim}{\pm}30%$, respectively. Generally, the corn yield was negatively correlated to temperature rise and rainfall reduction. Rainfall variations showed more prominent impacts on the corn yield than that of temperature variations. The reduction in average rainfall would instantly limit the crop growth rate and the corn yield irrespective of the temperature variations.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.4
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• pp.99-110
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• 2020

The objective of this study is to analyze the trend of changes in the water circulation rates under climate change by adopting the concept of WCR defined by the Ministry of Environment. With the need for sound water circulation recovery, the MOE proposed the idea of WCR as (1-direct flow/precipitation). The guideline for calculating WCR suggests the SCS method, which is only suitable for short term rainfall events. However, climate change, which affects WCR significantly, is a global phenomenon and happens gradually over a long period. Therefore, long-term trends in WCRs should also be considered when analyzing changes in WCR due to climate change. RCP (Representative Concentration Pathway) 4.5 and 8.5 scenarios were used to simulate future runoff. SWAT (Soil and Water Assessment Tool) was run under the future daily data from GCMs (General Circulation Models) after the calibration. In 2085s, monthly WCR decreased by 4.2-9.9% and 3.3-8.7% in April and October. However, the WCR in the winter increased as the precipitation during the winter decreased compared to the baseline. In the aspect of yearly WCR, the value showed a decrease in most GCMs in the mid-long future. In particular, in the case of the RCP 8.5 scenario, the WCR reduced 2-3 times rapidly than the RCP 4.5 scenario. The WCR of 2055s did not significantly differ from the 2025s, but the value declined by 0.6-2.8% at 2085s.

• Atmosphere
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• v.29 no.2
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• pp.165-181
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• 2019

In this study, the regional climate model, RegCM4.0 (25 km), with the HadGEM2-AO data as boundary conditions, was used to simulate the mean climate changes in the mid and late 21st century for CORDEX Phase 2 East Asian region. 122 years (1979~2100) of simulation were performed, and RCP 4.5 and RCP 8.5 were used for the simulation of future climate. In the mid-21st century, the temperature is expected to increase by about 0.5 to $3.0^{\circ}C$ in all regions of East Asia, regardless of season and scenario. The increase in temperature is greater in summer and winter, especially in the northern part of simulation domain. Interannual variability (IAV) is expected to decrease by 25% in summer for RCP 8.5, while it is expected to increase by more than 30% in autumn for both scenarios. Regardless of the scenario, the precipitation in South Korea is expected to increase in late June but decrease in mid-July, with an increase in precipitation greater than $100mm\;day^{-1}$. In RCP 4.5 of the late 21st century, relatively uniform temperature increase ($1.0{\sim}2.5^{\circ}C$) is expected throughout the continent, while RCP 8.5 shows a very diverse increase ($3.0{\sim}6.0^{\circ}C$) depending on season and geographical location. In addition, the IAV of temperature is expected to decrease by more than 35% in both scenarios in the summer. In most of the Northwest Pacific region, precipitation is expected to decrease in all seasons except for the summer, but in South Korea, it is projected to increase by about 10% in all seasons except autumn.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.48-48
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• 2023

The intensified droughts under climate change are expected to threaten stable water resource availability. Droughts exceeding the magnitude of historical variability could occur increasingly frequently under future climate conditions. It is crucial to understand how drought will evolve over time because the assumption of hydrological stationarity of the past decades would be inappropriate for future water resources management. However, the timing of the emergence of unprecedented drought conditions under climate change has rarely been examined. Here, using multimodel hydrological simulations, we investigate the changes in the frequency of hydrological drought (defined as abnormally low river discharge) under high and low greenhouse gas concentration scenarios and with existing water resources management and estimate the timing of the first emergence of unprecedented regional drought conditions that persist for over several consecutive years. This new metric enables a new quantification of the urgency of adaptation and mitigation with regard to drought under climate change. The times are detected for several sub-continental-scale regions, and three regions, namely, southwestern South America, Mediterranean Europe, and northern Africa, exhibit particularly robust and earlier critical times under the high-emission scenario. These three regions are expected to confront unprecedented conditions within the next 30 years with a high likelihood, regardless of the emission scenarios. In addition, the results obtained herein demonstrate the benefits of the lower-emission pathway in reducing the likelihood of emergence. The Paris Agreement goals are shown to be effective in reducing the likelihood to the unlikely level in most regions. Nevertheless, appropriate and prior adaptation measures are considered indispensable to when facing unprecedented drought conditions. The results of this study underscore the importance of improving drought preparedness within the considered time horizons.

• Advances in Energy Research
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• v.8 no.1
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• pp.73-93
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• 2022

Focus on climate change and extreme weather conditions has received considerable attention in recent years. Civil engineers are now focusing on designing buildings that are more eco-friendly in the face of climate change. This paper describes the research conducted to assess the impact of future climate change on energy usage and carbon emissions in a typical supermarket at multiple locations across the UK. Locations that were included in the study were London, Manchester, and Southampton. These three cities were compared against their building performance based on their respective climatic conditions. Based on the UK Climatic Projections (UKCP09), a series of energy modelling simulations which were provided by the Chartered Institute of Building Service Engineers (CIBSE) were conducted on future weather years for this investigation. This investigation ascertains and quantifies the annual energy consumption, carbon emissions, cooling, and heating demand of the selected supermarkets at the three locations under various climatic projections and emission scenarios, which further validates annual temperature rise as a result of climatic variation. The data showed a trend of increasing variations across the UK as one moves southwards, with London and Southampton at the higher side of the spectrum followed by Manchester which has the least variability amongst these three cities. This is the first study which investigates impact of the climate change on the UK supermarkets across different regions by using the real case scenarios.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.5
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• pp.25-35
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• 2023

The estuary reservoir is a major source of agricultural water in Korea; for effective and sustainable water resource management of the estuary reservoir, it is crucial to comprehensively consider various water resource factors, including water supply, flood, and pollutant management, and analyze future runoff changes in consideration of environmental changes such as climate change. The objective of this study is to estimate the impact of future climate change on the runoff characteristics of an estuary reservoir watershed. Climate data on future Shared Socioeconomic Pathway (SSP) scenarios were derived from two Global Climate Models (GCMs) of the Coupled Model Intercomparison Project phase 6 (CMIP6). The Hydrological Simulation Program-Fortran (HSPF) was used to simulate past and future long-term runoff of the Ganwol estuary reservoir watershed. The findings showed that as the impact of climate change intensified, the average annual runoff in the future period was higher in the order of SSP5, SSP3, SSP1, and SSP2, and the ratio of runoff in July decreased while the ratio of runoff in October increased. Moreover, in terms of river flow regime, the SSP2 scenario was found to be the most advantageous and the SSP3 scenario was the most disadvantageous. The findings of this study can be used as basic data for developing sustainable water resource management plans and can be applied to estuary reservoir models to predict future environmental changes in estuary reservoirs.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.18-18
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• 2011

Climate change is impacting and will increasingly impact both the quantity and quality of the world's water resources in a variety of ways. In some areas warming climate results in increased rainfall, surface runoff, and groundwater recharge while in others there may be declines in all of these. Water quality is described by a number of variables. Some are directly impacted by climate change. Temperature is an obvious example. Notably, increased atmospheric concentrations of $CO_2$ triggering climate change increase the $CO_2$ dissolving into water. This has manifold consequences including decreased pH and increased alkalinity, with resultant increases in dissolved concentrations of the minerals in geologic materials contacted by such water. Climate change is also expected to increase the number and intensity of extreme climate events, with related hydrologic changes. A simple framework has been developed in New Zealand for assessing and predicting climate change impacts on water resources. Assessment is largely based on trend analysis of historic data using the non-parametric Mann-Kendall method. Trend analysis requires long-term, regular monitoring data for both climate and hydrologic variables. Data quality is of primary importance and data gaps must be avoided. Quantitative prediction of climate change impacts on the quantity of water resources can be accomplished by computer modelling. This requires the serial coupling of various models. For example, regional downscaling of results from a world-wide general circulation model (GCM) can be used to forecast temperatures and precipitation for various emissions scenarios in specific catchments. Mechanistic or artificial intelligence modelling can then be used with these inputs to simulate climate change impacts over time, such as changes in streamflow, groundwater-surface water interactions, and changes in groundwater levels. The Waimea Plains catchment in New Zealand was selected for a test application of these assessment and prediction methods. This catchment is predicted to undergo relatively minor impacts due to climate change. All available climate and hydrologic databases were obtained and analyzed. These included climate (temperature, precipitation, solar radiation and sunshine hours, evapotranspiration, humidity, and cloud cover) and hydrologic (streamflow and quality and groundwater levels and quality) records. Results varied but there were indications of atmospheric temperature increasing, rainfall decreasing, streamflow decreasing, and groundwater level decreasing trends. Artificial intelligence modelling was applied to predict water usage, rainfall recharge of groundwater, and upstream flow for two regionally downscaled climate change scenarios (A1B and A2). The AI methods used were multi-layer perceptron (MLP) with extended Kalman filtering (EKF), genetic programming (GP), and a dynamic neuro-fuzzy local modelling system (DNFLMS), respectively. These were then used as inputs to a mechanistic groundwater flow-surface water interaction model (MODFLOW). A DNFLMS was also used to simulate downstream flow and groundwater levels for comparison with MODFLOW outputs. MODFLOW and DNFLMS outputs were consistent. They indicated declines in streamflow on the order of 21 to 23% for MODFLOW and DNFLMS (A1B scenario), respectively, and 27% in both cases for the A2 scenario under severe drought conditions by 2058-2059, with little if any change in groundwater levels.