• Journal of Korean Society for Geospatial Information Science
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• v.16 no.3
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• pp.79-85
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• 2008

This study aims to derive a practical coordinate transformation method for the existing geographic information database. After analyzing the status and problems of existing 1/1,000 digital base map and GIS application database, the transformation parameters are estimated and the accuracy of the transformation is determined based on the transformed coordinates. We analyzed the accuracy of a transformation using the published national transformation coefficients as well as the estimated local transformation coefficients using national and urban control points in a study area. In addition, the 1/1,000 digital base map from aerial triangulation is compared with respect to the coordinates of urban control points. Based on the comparison, the biases on the national control points which were used at the time of digital map generation was analyzed. Then, the accuracy of transformed coordinates based on the world geodetic system using local transformation coefficients estimated from urban control points are determined. We also analyzed the transformation accuracy of underground infrastructure database using the same transformation method as the case of 1/1,000 digital base map. Through this study, it was found that the estimation of transformation coefficients by Molodensky-Badekas using urban control points was suitable for a local government. Furthermore, it was obvious that the accuracy of a 2-dimensional affine transformation was comparable to that of 7 parameter transformation for a local area. Applying the coordinate transformation and bias correction, we could transform GIS application database which was built by an offset surveying based on digital base map within the transformation accuracy of 10 cm. Therefore, it was judged that there will not be a big problem on the transformation of the GIS DB to the world geodetic system.

• Journal of Korea Water Resources Association
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• v.46 no.6
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• pp.569-583
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• 2013

This study is to evaluate the future climate change impact on hydrological components in the Seolmacheon ($8.54km^2$) mixed forest catchment located in the northwest of South Korea using SWAT (Soil and Water Assessment Tool) model. To reduce the uncertainty, the model was spatially calibrated (2007~2008) and validated (2009~2010) using daily observed streamflow, evapotranspiration, and soil moisture data. Hydrological predicted values matched well with the observed values by showing coefficient of determination ($R^2$) from 0.74 to 0.91 for streamflow, from 0.56 to 0.71 for evapotranspiration, and from 0.45 to 0.71 for soil moisture. The HadGEM3-RA future weather data of Representative Concentration pathway (RCP) 4.5 and 8.5 scenarios of the IPCC (Intergovernmental Panel on Climate Change) AR5 (Assessment Report 5) were adopted for future assessment after bias correction of ground measured data. The future changes in annual temperature and precipitation showed an upward tendency from $0.9^{\circ}C$ to $4.2^{\circ}C$ and from 7.9% to 20.4% respectively. The future streamflow showed an increase from 0.6% to 15.7%, but runoff ratio showed a decrease from 3.8% to 5.4%. The future predicted evapotranspiration about precipitation increased from 4.1% to 6.8%, and the future soil moisture decreased from 4.3% to 5.5%.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.2
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• pp.69-81
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• 2011

The soil moisture data of the National Aeronautics and Space Administration(NASA) and the Vrije Universiteit Amsterdam(VUA) in collaboration with NASA, retrieved from Advanced Microwave Scanning Radiometer-Earth observing system(AMSR-E) brightness temperature, were collected to evaluate the applicability of the remote sensed soil moisture in South Korea. The averages of the soil moisture by in-situ sensors, by NASA and by VUA-NASA are approximately 0.218, 0.119, and $0.402m^3/m^3$, respectively. This indicates that the soil moisture of NASA was underestimated and that of VUA-NASA was overestimated. The soil moisture products of VUA-NASA showed a better relationship with the in-situ data than that of NASA data. However, there are still limitations of C-band soil moisture measurements. To improve the applicability of satellite soil moisture measurements, bias correction and other post processings are essential using in-situ soil moisture measurements at various surface conditions.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.1
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• pp.156-169
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• 2015

This study was to evaluate the RCP climate change impact on hydrological components in the Imha-Dam watershed using SWAT(Soil and Water Assessment Tool) Model. The model was calibrated for six year(2002~2007) and validated for six year(2008~2013) using daily observed streamflow data at three watershed stations. The overall simulation results for the total released volume at this point appear reasonable by showing that coefficient of determination($R^2$) were 0.70~0.85 and Nash-Sutcliffe model efficiency(NSE) were 0.67-0.82 for streamflow, respectively. For future hydrologic evaluation, the HadGEM3-RA climate data by scenarios of Representative Concentration Pathway(RCP) 4.5 and 8.5 of the Korea Meteorological Administration were adopted. The biased future data were corrected using 34 years(1980~2013, baseline period) of weather data. Precipitation and temperature showed increase of 10.8% and 4.9%, respectively based on the baseline data. The impacts of future climate change on the evapotranspiration, soil moisture, surface runoff, lateral flow, return flow and streamflow showed changes of +11.2%, +1.9%, +10.0%, +12.1%, +18.2%, and +11.2%, respectively.

• Journal of Climate Change Research
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• v.9 no.1
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• pp.13-29
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• 2018

This study presented evaluation procedure for selecting appropriate GCMs and downscaling method by focusing on the climate extreme indices suitable for climate change adaptation. The procedure includes six stages of processes as follows: 1) exclusion of unsuitable GCM through raw GCM analysis before bias correction; 2) calculation of the climate extreme indices and selection of downscaling method by evaluating reproducibility for the past and distortion rate for the future period; 3) selection of downscaling method based on evaluation of reproducibility of spatial correlation among weather stations; and 4) MME calculation using weight factors and evaluation of uncertainty range depending on number of GCMs. The presented procedure was applied to 60 weather stations where there are observed data for the past 30 year period on Korea Peninsula. First, 22 GCMs were selected through the evaluation of the spatio-temporal reproducibility of 29 GCMs. Between Simple Quantile Mapping (SQM) and Spatial Disaggregation Quantile Delta Mapping (SDQDM) methods, SQM was selected based on the reproducibility of 27 climate extreme indices for the past and reproducibility evaluation of spatial correlation in precipitation and temperature. Total precipitation (prcptot) and annual 1-day maximum precipitation (rx1day), which is respectively related to water supply and floods, were selected and MME-based future projections were estimated for near-future (2010-2039), the mid-future (2040-2069), and the far-future (2070-2099) based on the weight factors by GCM. The prcptot and rx1day increased as time goes farther from the near-future to the far-future and RCP 8.5 showed a higher rate of increase in both indices compared to RCP 4.5 scenario. It was also found that use of 20 GCM out of 22 explains 80% of the overall variation in all combinations of RCP scenarios and future periods. The result of this study is an example of an application in Korea Peninsula and APCC Integrated Modeling Solution (AIMS) can be utilized in various areas and fields if users want to apply the proposed procedure directly to a target area.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.185-185
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• 2019

Sustaining future wheat production is challenged by anthropogenically forced climate warming and drying led by increased concentration of greenhouse gases all around the globe. Warming stresses, originating from the elevated $CO_2$ concentration, are continuously reported to have negative impacts on wheat growth and yield. Yet, elevated $CO_2$ concentration, despite being disparagingly blamed for promoting warming, is also associated with a phenomenon called $CO_2$ enrichment; in which wheat yield can improve due to the enhanced photosynthesis rates and less water loss through transpiration. The conflicting nature of climate warming and $CO_2$ enrichment and their interplay can have specific implications under different environments. It is established form the field and simulation studies that the two contrasting phenomena would act severely in their own respect under arid and semi-arid environments. Wheat is a dietary staple for masses in Pakistan. The country's wheat production system is under constant stress to produce more from irrigated agricultural lands, primarily lying under arid to semi-arid environments, to meet the rapidly growing domestic needs. This work comprehensively examines the warming impacts over wheat yield and water productivity (WP), with and without the inclusion of $CO_2$ enrichment, under semi-arid environment of Punjab which is the largest agricultural province of Pakistan. Future wheat yields and WPs were simulated by FAO developed AquaCrop model v 5.0. The model was run using the bias-correction climate change projections up to 2080 under two representative concentration pathways (RCP) scenarios: 4.5 and 8.5. Wheat yield and WPs decreased without considering the $CO_2$ enrichment effects owing to the elevated irrigation demands and accelerated evapotranspiration rates. The results suggested that $CO_2$ enrichment could help maintain the current yield and WPs levels during the 2030s (2021-2050); however, it might not withhold the negative climate warming impacts during the 2060s (2051-2080). Furthermore, 10 - 20 day backward shift in sowing dates could also help ease the constraints imposed by climate warming over wheat yields and WPs. Although, $CO_2$ enrichment showed promises to counteract the adverse climate warming impacts but the interactions between climate warming and $CO_2$ concentrations were quite uncertain and required further examination.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.416-416
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• 2015

기후변화는 미래 강수량 변동을 야기하여 하천유량 관리에 큰 영향을 미칠 것으로 예상하고 있다. 이에 본 연구에서는 기후변화에 따른 중장기 하천유량 관리를 위하여 금호강 유역을 대상으로 SWAT 모형을 이용하여 중장기 하천유량을 예측하였다. 임하댐 상류지역의 2008~2012년 유량자료에 대하여 보정 완료된 SWAT 모형을 기반으로, 지역기후모형(RCM)인 HadGEM3-RA모형을 활용한 IPCC 제5차 보고서 RCP 4.5, RCP 8.5 시나리오를 적용하였다. 금호강 표준유역별 기후변화에 의한 영향을 모의하기 위하여 편이보정(Bias Correction)방법을 적용하였으며, 금호강 유역 내 과거 30년(1975~2005년, Baseline) 기상자료와 비교하여 통계적인 유사성을 가지도록 보정을 실시하였다. 기후변화 시나리오 적용결과는 S1(2011~2040년), S2(2041~2070년), S3(2071~2099년)으로 분할하여 월별, 계절별, 연도별 미래 강수량과 기온을 분석하였다. 분석 결과, RCP 4.5 시나리오의 경우 봄철(3~5월)의 강수량은 기준년도에 비해 약 57%가 증가하였으나, 가을철(6~8월)에는 7.9% 감소하였으며, 첨두 강수시기는 8~9월에서 6~7월로 이동하였다. 평균기온은 각 구분 시기별 $0.2^{\circ}C$, $1.1^{\circ}C$, $1.8^{\circ}C$ 정도 상승할 것으로 예측되었다. RCP 8.5 시나리오에서는 기준년도 대비 강우량은 봄철에 61% 증가, 가을철에는 14.9% 감소하는 것으로 모의되었다. 평균기온은 약 $0.4^{\circ}C$, $2.1^{\circ}C$, $4.2^{\circ}C$ 정도 상승하는 것으로 나타났다. 기후변화에 따른 유출량 결과 비교는 2001~2010년을 기준으로 하였으며, RCP 4.5 시나리오에서는 S1, S2, S3 시기별 각각 -10.9%, -7%, -3.6% 감소하였으며, RCP 8.5 시나리오에서는 약 -12.3%, 4.9%, -1.2% 변동하는 것으로 나타냈다. 금호강 유역 전반에 걸쳐 유출량이 감소하는 추세를 보였으며, 특히 본류에 비해 지류유역의 건천화가 심해지는 양상을 보였다. 또한 현재에 비해 여름철 유출패턴 시기가 앞당겨져 봄철 유량이 증가하고 겨울철에 감소하는 경향을 보이고 있다. 기후변화로 인한 수문패턴의 변화로 현재 하천유량관리의 변화가 필요할 것으로 판단되며, 향후 본 연구결과를 바탕으로 물수지 분석을 추가하여 유지유량 만족을 위한 해당유역의 이수기 유량관리 방안 연구를 수행할 예정이다.

• Journal of Korea Water Resources Association
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• v.54 no.5
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• pp.321-334
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• 2021

A fixed reflectivity-rainfall relationship approach, such as the Marshall-Palmer relationship, for an entire year and different seasons, can be problematic in cases where the relationship varies spatially and temporally throughout a region. From this perspective, this study explores the use of long-term radar reflectivity for South Korea to obtain a nationwide calibrated Z-R relationship and the associated uncertainties within a Bayesian inference framework. A calibrated spatially structured pattern in the parameters exists, particularly for the wet season and parameter for the dry season. A pronounced region of high values during the wet and dry seasons may be partially associated with storm movements in that season. Overall, the radar rainfall fields based on the proposed modeling procedure are similar to the observed rainfall fields. In contrast, the radar rainfall fields obtained from the existing Marshall-Palmer relationship show a systematic underestimation. In the event of high impact weather, it is expected that the value of national radar resources can be improved by establishing an active watershed-level hydrological analysis system.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.201-217
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• 2022

The United States is one of the largest producers of major crops such as wheat, maize, and soybeans, and is a major exporter of these crops. Therefore, it is important to estimate the crop production of the country in advance based on reliable long- term weather forecast information for stable crops supply and demand in Korea. The purpose of this study is to improve the seasonal predictability of the agro-climatic indices over the United States by using regional-scale daily temperature. For long-term numerical weather prediction, a dynamical downscaling is performed using Weather Research and Forecasting (WRF) model, a regional climate model. As the initial and lateral boundary conditions of WRF, the global hourly prediction data obtained from the Pusan National University Coupled General Circulation Model (PNU CGCM) are used. The integration of WRF is performed for 22 years (2000-2021) for period from June to December of each year. The empirical quantile mapping, one of the bias correction methods, is applied to the timeseries of downscaled daily mean, minimum, and maximum temperature to correct the model biases. The uncorrected and corrected datasets are referred WRF_UC and WRF_C, respectively in this study. The daily minimum (maximum) temperature obtained from WRF_UC presents warm (cold) biases over most of the United States, which can be attributed to the underestimated the low (high) temperature range. The results show that WRF_C simulates closer to the observed temperature than WRF_UC, which lead to improve the long- term predictability of the temperature- based agro-climatic indices.

• Journal of Korea Water Resources Association
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• v.56 no.9
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• pp.529-541
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• 2023

Due to the growing concern over forecasting extreme weather events such as droughts caused by climate change, there has been a rising interest in seasonal meteorological forecasts that offer ensemble predictions for the upcoming seven months. Nonetheless, limited research has been conducted in South Korea, particularly in assessing their effectiveness at the catchment-scale. In this study, we assessed the accuracy of ECMWF's seasonal forecasts (including precipitation, temperature, and evapotranspiration) for the period of 2011 to 2020. We focused on 12 multi-purpose reservoir catchments and compared the forecasts to climatology data. Continuous Ranked Probability Skill Score method is adopted to assess the forecast skill, and the linear scaling method was applied to evaluate its impact. The results showed that while the seasonal meteorological forecasts have similar skill to climatology for one month ahead, the skill decreased significantly as the forecast lead time increased. Compared to the climatology, better results were obtained in the Wet season than the Dry season. In particular, during the Wet seasons of the dry years (2015, 2017), the seasonal meteorological forecasts showed the highest skill for all lead times.