• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.273-277
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• 2010

This research was performed to examine changes in the timing of the growth of crops along with changes in temperatures due tochanges and to analyze the change of water-supply-reliability by adding an analysis of the change of agricultural water supply patterns in the basin area of Miryang dam in Korea. Had-CM3 model from U.K. was the tool adopted for the GCM model, a stochastic, daily-meteorology-generation-model called LARS-WG was alsoused for downscaling and for the climate change scenario (A1B) which represents Korea's circumstances best. First of all, to calculate changes in the timing of the growth of crops during this period, the theory of GDD was applied. Except for the period of transplanting and irrigation, there was no choice but to find the proper accumulated temperature by comparing actual temperature data and the supply pattern of agricultural use due to limited temperature data. As a result, proper temperatures were found for each period. $400^{\circ}C$ for the preparation period of a nursery bed, $704^{\circ}C$ for a nursery bed's period, $1,295^{\circ}C$ for the rice-transplanting period, $1,744^{\circ}C$ for starting irrigation, and $3,972^{\circ}C$ for finishing irrigation. To analyze future agricultural supply patter changes, the A1B scenario of Had-CM3 model was adopted, and then Downscaling was conducted adopting LARS-WG. To conduct a stochastical analysis of LARS-WG, climate scenarios were generated for the periods 2011~2030, 2046~2065, 2080~2099 using the data of precipitation andMax/Min temperatures collected from the Miryang gauging station. Upon reviewing the result of the analysis of accumulated temperatures from 2011~2030, the supply of agricultural water was 10 days earlier, and in the next periods-2046~2065, 2080~2099 it also was 10 days earlier. With these results, it is assumed that the supply of agricultural water should be about 1 month ahead of the existing schedule to meet the proper growth conditions of crops. From the results of the agricultural water supply patterns should be altered, but the reliability of water supply becomes more favorable, which is caused from the high precipitation change. Furthermore, since the unique characteristics of precipitation in Korea, which has high precipitation in the summer, water-supply-reliability has a pattern that the precipitation in September could significantly affect the chances of drought the following winter and spring. It could be more risky to make changes to the constant supply pattern under these conditions due to the high uncertainty of future precipitation. Although, several researches have been conducted concerning climate changes, in the field of water-industry, those researches have been solely dependent on precipitation. Even so, with the high uncertainty of precipitation, it is difficult for it to be reflected in government policy. Therefore, research in the field of water-supply-patterns or evapotranspiration according to the temperature or other diverse effects, which has higher reliability on anticipation, could obtain more reliable results in the future and that could result in water-resource maintenance to be safer and a more advantageous environment.

• Journal of Korea Water Resources Association
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• v.51 no.spc
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• pp.1079-1089
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• 2018

The majority of existing studies for quantifying uncertainties in climate change impact assessments suggest only the uncertainties of each stage, and not the total uncertainty and its propagation in the whole procedure. Therefore, this study has proposed a new method, the Uncertainty Delta Method (UDM), which can quantify uncertainties using the variances of projections (as the UDM is derived from the first-order Taylor series expansion), to allow for a comprehensive quantification of uncertainty at each stage and also to provide the levels of uncertainty propagation, as follows: total uncertainty, the level of uncertainty increase at each stage, and the percentage of uncertainty at each stage. For quantifying uncertainties at each stage as well as the total uncertainty, all the stages - two emission scenarios (ES), three Global Climate Models (GCMs), two downscaling techniques, and two hydrological models - of the climate change assessment for water resources are conducted. The total uncertainty took 5.45, and the ESs had the largest uncertainty (4.45). Additionally, uncertainties are propagated stage by stage because of their gradual increase: 5.45 in total uncertainty consisted of 4.45 in emission scenarios, 0.45 in climate models, 0.27 in downscaling techniques, and 0.28 in hydrological models. These results indicate the projection of future water resources can be very different depending on which emission scenarios are selected. Moreover, using Fractional Uncertainty Method (FUM) by Hawkins and Sutton (2009), the major uncertainty contributor (emission scenario: FUM uncertainty 0.52) matched with the results of UDM. Therefore, the UDM proposed by this study can support comprehension and appropriate analysis of the uncertainty surrounding the climate change impact assessment, and make possible a better understanding of the water resources projection for future climate change.

• Journal of Korea Water Resources Association
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• v.46 no.12
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• pp.1141-1155
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• 2013

A number of studies have been performed to analyze climate change impacts of water resources system. In this study, a coordinated dam operation is compared with an existing operation strategy for coping with projected future runoff scenarios. GCMs (Global Circulation Models) and the LARS-WG downscaling method was used to project future climate scenarios. The water balance model called abcd was employed to estimate future runoff scenarios. The existing dam operation comes from the national dam construction guideline, which is called the "level-operation method." The alternative coordinated dam operation are constructed as a linear programming using New York City rule for refill and drawdown seasons. The results of annual total inflow in future is projected to decrease to 72.81% for Andong dam basin and 65.65% for Imha dam basin. As a result of applying future runoff scenarios into the dam operation model, the reliability of coordinated dam operation, 62.22%, is higher than the reliability of single dam operation, 46.55%. Especially, the difference gets larger as the reliability is low because of lack of water. Therefore, the coordinated operation in the Andong & Imha dams are identified as more appropriate alternative than the existing single operation to respond to water-level change caused by climate change.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.189-193
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• 2008

본 연구는 충주댐 유역을 대상으로 미래의 기후변화, 그에 따른 식생상태, 그리고 미래의 토지이용 변화를 고려한 상태에서 SWAT-K 모형에 의한 수문순환인자들의 변화가 댐의 유입량에 미치는 영향을 파악하고자 한다. SWAT 모형의 검보정은 6년간($2000{\sim}2006$, 2001년 제외)의 댐유입량 자료를 이용하여 실시하였으며, Nash_Sutcliffe 모형효율은 $0.52{\sim}0.88$의 범위로 검보정되었다. 기후변화 시나리오는 IPCC에서 제공하고 있는 GCM들 중에서 CCCma CGCM2의 A2, B2 시나리오를 이용하였으며, 댐유역의 기후변화를 모의하기 위하여 과거 30년간($1977{\sim}2006$)의 기상자료 통계정보를 기준으로 Change Factor Downscaling 기법을 적용하여 2030년, 2060년, 2090년 전후의 각 30년간의 미래 정보를 재생산하였다. 미래의 식생정보는 7년($2000{\sim}2006$)간의 MODIS 위성 영상에 의한 엽면적 지수를 월단위로 구축하여 엽면적 지수와 평균기온간의 상관회귀식을 도출하여 미래 기후변화에 따른 식생의 활력도를 예측하였다. 미래의 토지이용 변화는 CA-MArkov 기법을 개선, 적용하여 총 9개의 토지이용 항목에 대하여 각 항목별 예측을 실시하였다. 2000년의 기상자료 및 댐유입량을 기준으로 이상의 미래기후, 식생, 토지이용 에측 정보를 적용하여 미래의 댐유입량을 모의한 결과를 분석하였다. 그 결과 강수량 및 온도의 변동이 가장 크게 영향을 주어 유입량의 변화가 모의되었으며, 이에 따른 수문인자의 변동은 2000년 기준으로 증발산량, 토양수분의 변동을 분석하였다. 미래의 수문순환에 가장 큰 영향을 주는 수문인자는 토양수분으로 나타나, 미래에는 산림지역 및 토지이용 개발에 따른 토양수분의 함양량 유지를 위한 유역관리가 중요한 요인이 될 것으로 나타났다.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.529-533
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• 2008

본 연구는 미래기후변화가 공간해상도(5, 10, 30m)에 따른 토양유실량의 변화에 미치는 영향을 분석하고 자하였다. 연구대상지역은 경안천 최상류에 위치한 $1.16km^2$의 농촌 소유역을 대상으로 공간해상도별(5, 10, 30m) RS 및 GIS 자료를 생성하고, GIS 기반의 RUSLE(Revised Universal Soil Loss Equation) 모형을 채택하여 토양유실량을 분석하였다. 기후변화 시나리오는 IPCC(Intergovernmental Panel on Climate Change)에 서 제공하는 GCM(Global climate model) 중에서 MIROC3.2 hire의 A1B, B1 시나리오를 이용하였으며, 과거 30년간(1977-2006)의 기상자료 통계정보를 기준으로 Change Factor Downscaling 기법을 적용하여 2020s년 (2010-2039), 2050s년(2040-2069), 2080s년(2069-2099) 전후의 각 30년간의 미래 강우량을 재생산하여 사용하였다. 그 결과 강수량은 2080s년에 A1B 시나리오의 경우 연평균 강수량은 270.37mm, 최대 강수량은 65.71mm 증가하였고, B1 시나리오의 경우 연평균 강수량은 37.11mm, 최대 강수량은 48.46mm 증가하는 것으로 나타났다. 구축한 미래 강우량을 RUSLE 인자 중 R 인자에 적용하여 2020s년, 2050s년, 2080s년의 토양유실량을 분석한 결과, 미래강수량이 증가함에 따라 공간해상도별 토양유실량도 증가하는 것으로 분석되었다. 평균토양유실량을 시나리오별로 보면, A1B 시나리오의 경우 2080s을 기준으로 1/5,000 scale에서는 약 0.18 ton/ha/year, 1/25,000 scale에서는 약 0.07 ton/ha/year, 1/50,000 scale에서는 약 0.07 ton/ha/year의 유실량이 각 공간해상도별로 증가하였다. B1 시나리오의 경우 2080s을 기준으로 1/5,000 scale에서는 약 0.03 ton/ha/year, 1/25,000 scale에서는 약 0.01 ton/ha/year, 1/50,000 scale에서는 약 0.01 ton/ha/year의 토양유실량이 증가한 것으로 분석되었다.

• Journal of Korean Society of Rural Planning
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• v.23 no.4
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• pp.153-168
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• 2017

The main objective of this study was to assess reference evapotranspiration based on multiple GCMs (General Circulation Models) and estimation methods. In this study, 10 GCMs based on the RCP (Representative Concentration Pathway) 4.5 scenario were used to estimate reference evapotranspiration. 54 ASOS (Automated Synoptic Observing System) data were constructed by statistical downscaling techniques. The meteorological variables of precipitation, maximum temperature and minimum temperature, relative humidity, wind speed, and solar radiation were produced using GCMs. For the past and future periods, we estimated reference evapotranspiration by GCMs and analyzed the statistical characteristics and analyzed its uncertainty. Five methods (BC: Blaney-Criddle, HS: Hargreaves-Samani, MK: Makkink, MS: Matt-Shuttleworth, and PM: Penman-Monteith) were selected to analyze the uncertainty by reference evapotranspiration estimation methods. We compared the uncertainty of reference evapotranspiration method by the variable expansion and analyzed which variables greatly influence reference evapotranspiration estimation. The posterior probabilities of five methods were estimated as BC: 0.1792, HS: 0.1775, MK: 0.2361, MS: 0.2054, and PM: 0.2018. The posterior probability indicated how well reference evapotranspiration estimated with 10 GCMs for five methods reflected the estimated reference evapotranspiration using the observed data. Through this study, we analyzed the overall characteristics of reference evapotranspiration according to GCMs and reference evapotranspiration estimation methods The results of this study might be used as a basic data for preparing the standard method of reference evapotranspiration to derive the water management method under climate change.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.17-17
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• 2019

IPCC (Intergovernmental Panel on Climate Change) 기후변화 전망보고서에 따르면 RCP 4.5 시나리오 기준, 21세기 전 지구 평균기온은 $2.5^{\circ}C$ 상승(한반도 $+3.0^{\circ}C$)하며, 전 지구 평균강수량은 4.1% 증가(한반도 +16.0%)할 것이라 전망하고 있다(기상청, 2012). 최근 기후변화와 기상이변에 따른 도심지 폭우특성이 변화하고 있음을 많은 연구결과에서 말해주고 있으며, 그 발생 빈도와 강도가 점차 증가하고 있는 추세이다. 특히, 서울시의 경우 인구와 재산이 밀집해 있어 폭우 발생에 의한 시민의 인명과 재산 피해 우려가 크다. 따라서 본 연구에서는 서울시를 대상으로 근미래(~2050년) 기후변화 하에서의 재현기간에 따른 확률강우량 변화 특성을 분석하여 비교 평가한 후 설계 강우량 산정에 활용하고자 하였다. 관측자료 기반 강수량의 변동 특성 분석과 Non-stationary GEV방법을 이용한 비정상성 빈도해석을 수행하였으며, 근미래 폭우특성 변화분석을 위하여 CMIP5 (Coupled Model Intercomparison Project 5)에 참여한 GCMs(General Circulation Models)을 활용한 강우빈도해석을 수행하였다. Mann-Kendall Test와 Quantile Regression을 통한 서울지점 여름철 강수량(June to September)과 기준강수량 초과 강수(30, 50, 80, 100mm/hr), 연간 10th 최대 강수량(Annual Top 10th Precipitation) 등을 분석한 결과 최근 증가 경향이 뚜렷하게 나타났으며, 비정상성 빈도해석에 의한 확률강우량 분석의 가능성과 신뢰성을 확인하였다. 또한 19-GCMs을 통하여 모의된 일(Daily) 단위 강수량자료를 비모수통계적 상세화(Nonparametric Temporal Downscaling) 기법을 적용하여 시간(Hourly) 강우로 다운스케일링하였으며, 서울시 미래 확률강우량에 대한 IDF 곡선(Intensity-Duration-Frequency Curve)을 작성하여 비교?분석한 결과 지속시간 1시간 강우에 대하여 재현기간 30년, 100년 조건에서 확률강우량이 약 4%~11% 수준에서 증가하고 있음을 확인하였다. 본 연구의 결과는 도심지 수공구조물의 설계빈도 영향을 진단하고, 근미래 발생가능한 확률강우량 변화에 따른 시간당 목표 강우량설정의 방법론을 제시하였다는데 의의가 있으며, 서울시의 방재성능목표 설정과 침수취약지역 해소를 위한 기후변화에 따른 수공구조물 설계 시 활용이 가능할 것으로 기대된다.

• 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.

• Journal of Korea Water Resources Association
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• v.40 no.12
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• pp.921-930
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• 2007

The objective of this study is to present temporal-spatial variation of water resources on climate change impacts using the IPCC SRES A2 scenario and dynamical downscaling of the results (using the MM5 model with a resolution of 27km by 27km) at 139 sub-basins in Korea. The variation of runoff shows differences in the change of rate according to the each sub-basins and analysis durations. It has increased in the sub-basins located in Han river basin and east part of it, the other basins have decreased. In seasonal analysis, runoff in autumn and winter have increased, while in spring and summer have decreased. The results of frequency analyzing classified runoff(Low flow(Q$\leq$5mm), Normal flow(5$\geq$100mm)) show that low flow increase in most of the sub-basins for 2031-2060 and 2061-2090. In the case of high flow, it have higher frequency ranging from -100% to 500% than low flow. Regardless of the variation of mean runoff, maximum discharge appeared to be increase in process of time. The regression method is used to figure out the relationship between the rate of runoff change and mean temperature, mean precipitation under A2 scenario. The mean actual evapotranspirations from the regression equations increased by 3.4$\sim$5.3% for the change of $1^{\circ}C$. Also, for the precipitation change of $\pm$10%, runoff variety range is -18.2$\sim$+12.4% in Han River, -21.6$\sim$+14.6% in Nakdong River, -17.5$\sim$+11.5% in Gum River, -18.4$\sim$+10.6% in Sumjin River, -19.9$\sim$+12.7% Youngsan River basin.

• Journal of Korea Water Resources Association
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• v.51 no.10
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• pp.905-916
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• 2018

The purpose of this study is to evaluate the climate change impact on watershed hydrology and flow duration in Geum River basin ($9,645.5km^2$) especially by extreme scenarios. The rainfall related extreme index, STARDEX (STAtistical and Regional dynamical Downscaling of EXtremes) was adopted to select the future extreme scenario from the 10 GCMs with RCP 8.5 scenarios by four projection periods (Historical: 1975~2005, 2020s: 2011~2040, 2050s: 2041~2070, 2080s: 2071~2100). As a result, the 5 scenarios of wet (CESM1-BGC and HadGEM2-ES), normal (MPI-ESM-MR), and dry (INM-CM4 and FGOALS-s2) were selected and applied to SWAT (Soil and Water Assessment Tool) hydrological model. The wet scenarios showed big differences comparing with the normal scenario in 2080s period. The 2080s evapotranspiration (ET) of wet scenarios varied from -3.2 to +3.1 mm, the 2080s total runoff (TR) varied from +5.5 to +128.4 mm. The dry scenarios showed big differences comparing with the normal scenario in 2020s period. The 2020s ET for dry scenarios varied from -16.8 to -13.3 mm and the TR varied from -264.0 to -132.3 mm respectively. For the flow duration change, the CFR (coefficient of flow regime, Q10/Q355) was altered from +4.2 to +10.5 for 2080s wet scenarios and from +1.7 to +2.6 for 2020s dry scenarios. As a result of the flow duration analysis according to the change of the hydrological factors of the Geum River basin applying the extreme climate change scenario, INM-CM4 showed suitable scenario to show extreme dry condition and FGOALS-s2 showed suitable scenario for the analysis of the drought condition with large flow duration variability. HadGEM2-ES was evaluated as a scenario that can be used for maximum flow analysis because the flow duration variability was small and CESM1-BGC was evaluated as a scenario that can be applied to the case of extreme flood analysis with large flow duration variability.