• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.419-419
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• 2023

하천의 최종 유출부와 해양이 만나는 지점을 하구라고 하며, 우리나라는 주로 서해안 지역에 하구 방조제 건설에 따른 담수호가 조성되어 다양한 목적으로 수자원이 활용되고 있다. 이러한 하구 담수호는 바다로 유입되기 직전의 물을 저류시켜 수자원 확보에 긍정적이나, 일반적으로 유역의 최하류에 위치해 있어 오염물질 유입, 부영양화, 염분 침출로 인한 오염물질 용출 등에 취약하다. 따라서 담수호의 회복탄력성 향상과 지속가능한 수자원 관리를 위해서는 미래 기후변화에 따른 영향 분석이 필수적이다. 특히 기후변화는 거대규모의 홍수과 같은 자연재난, 농업가뭄 및 식생가뭄 등의 증가로 이어질 수 있으므로, 이에 효과적으로 대비하기 위해서는 미래 기후조건에 따른 하천의 미래 유출량 변화 예측이 수행되어야 한다. 본 연구에서는 불확실한 미래 수문변화를 예측하기 위해 CMIP6(Coupled Model Intercomparison Project Phase 6) GCMs(Global Climate Models)의 SSP(Shared Socioeconomic Pathways) 시나리오를 유역 유출모델에 적용하여 기후변화에 따른 미래 유출특성의 변화를 예측하였다. 충청남도 서산시에 위치한 간월호 유역을 대상유역으로 선정하고, HSPF(Hydrological Simulation Program-FORTRAN) 모형을 적용하여 상류유역의 과거 및 미래 장기유출량 모의를 수행하였다. 모의된 시나리오별 유출량을 기반으로 최빈유량곡선법을 적용하여 미래의 기준유량 발생시점 및 지속기간의 변화를 분석하였으며, CVDs(Center-of-volume dates)의 변화를 통해 기후변화에 따른 홍수기의 시기적 변화 양상을 파악하고자 하였다. 본 연구의 결과는 미래 유역 환경변화를 고려한 담수호의 수자원 보전관리계획 수립에 있어 기초자료로 활용될 수 있을 것으로 기대된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.42-42
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• 2023

최근 IPCC 6차 보고서에서는 전 지구의 온도가 0.5℃가 증가할 때마다 기상학적 가뭄 지역이 증가하며, 인위적 강제력은 가뭄 현상의 강도와 빈도를 증가하는 것으로 밝혔다. 봄철(3월-5월) 동남아시아(남중국, 필리핀 등)에 비해 상대적으로 건조한 동북아시아(동중국, 한반도, 일본) 지역은 가뭄에 취약하며 기후 변화에 따라 가뭄으로 인한 피해가 커질 것으로 전망된다. 그러므로 이 지역은 봄철 가뭄으로 인한 피해를 완화하기 위해 봄철 강수량에 대한 신뢰할 만한 계절적 예보 기술이 꼭 필요하다. 본 연구에서는 1992-2022년 봄철의 Standardized Precipitation Index(SPI) 값을 기준으로 2001년과 2011년 동북아시아 가뭄이 발생한 것을 확인하였으며, 각 해의 3월에 관측된 기상학적 초기 조건으로부터 다중 기후 예보 모델들의 봄철 강수량의 계절적 예측성을 정량적으로 평가하였다. 관측자료로부터 2001년 가뭄은 동북아시아 대기 상층의 저기압성 순환의 강화로 인한 제트류(Jet stream)의 강화와 연관되어 있었으며, 2011년 가뭄은 제트류 강화와 함께 태평양 열대 지역 기류 강화가 동반되어 발생하였음을 알 수 있었다. North American Multi-Model Ensemble 기후 예보 모델들은 2011년 가뭄에 비해 2001년 가뭄에 대한 예측성이 높았으며, 그 이유로는 대기 상층 순환의 예측성과 연관이 있음을 밝혔다. 또한, 봄철 대기-해양 상호 패턴을 관측과 유사하게 재현한 GFDL-SPEARS 모델이 가뭄 해의 대기 상층 저기압성 순환과 강수 예측성이 가장 높은 것을 보였다. 본 연구의 결과들을 통해 동북아시아 봄철 가뭄과 같은 극한 기상의 강수량 예측성 향상에 있어서 기후 예보 모델들의 현실적인 대기-해양 결합 과정 모사 능력의 중요성을 밝혔다. 본 연구에서 제안된 방안들은 기후 예측 모델 개선을 위한 전략적인 정보를 제공할 것으로 보인다.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.27 no.1
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• pp.45-54
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• 2024

This study developed a model to evaluate the co-benefits and trade-off effects between biodiversity and carbon storage capacity based on the implementation locations of nature-based solutions. The model aims to propose optimal implementation locations by using the conceptual idea of edge effects for carbon storage and connectivity for biodiversity. The co-benefits were considered by simultaneously taking into account two effects rather than a single effect. Trade-off effects were observed among optimal plans through a comparison of benefits. The NSGA-II multi-objective optimization algorithm was utilized, confirming the identification of Pareto-optimal solutions. The implementation patterns of Pareto-optimal solutions for green areas were examined. This study holds significance in proposing optimal locations by evaluating various co-benefits and trade-off effects of nature-based solutions. By advancing models based on this evaluation framework, it is anticipated that the assessment of co-benefits and trade-off effects among various benefits of nature-based solutions, such as climate change mitigation, enhancement of biodiversity, and provision of ecosystem services, can be accomplished.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.42 no.5
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• pp.579-596
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• 1997

A simulation study was carried out to delineate potential effects of the lake-induced climate change on crop productivity around Lake Imha which was formed after a multi-purpose dam construction in Andong, Korea. Twenty seven cropping zones were identified within the 30 km by 25 km study area. Five automated weather stations were installed within the study area and operated for five years after the lake formation. A geostatistical method was used to calculate the monthly climatological normals of daily maximum and minimum temperature, solar radiation and precipitation for each cropping zone before and after the dam construction. Daily weather data sets for 30 years were generated for each cropping zone from the monthly normals data representing "No lake" and "After lake" climatic scenarios, respectively. They were fed into crop models (ORYZA1 for rice, SOYGRO for soybean, CERES-maize for corn) to simulate the yield potential of each cropping zone. Calculated daily maximum temperature was higher after the dam construction for the period of October through March and lower for the remaining months except June and July. Decrease in daily minimum temperature was predicted for the period of April through August. Monthly total radiation was predicted to decrease after the lake formation in all the months except February, June, and September and the largest drop was found in winter. But there was no consistent pattern in precipitation change. According to the model calculation, the number of cropping zones which showed a decreased yield potential was 2 for soybean and 6 for corn out of 27 zones with a 10 to 17% yield drop. Little change in yield potential was found at most cropping zones in the case of paddy rice, but interannual variation was predicted to increase after the lake formation. the lake formation.

• Journal of Korea Water Resources Association
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• v.57 no.1
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• pp.59-72
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• 2024

Agricultural reservoirs supply water for various purposes such as irrigation, maintenance, and living. Since agricultural reservoirs respond sensitively to seasonal and climate changes, it is essential to estimate supply and inflow for efficient operation, and water management should be done based on these data. However, in the case of agricultural reservoirs, the measurement of supply and inflow is relatively insufficient compared to multi-purpose dams, and inflow-supply analysis in agricultural reservoirs through water balance analysis is necessary for efficient water management. Therefore, rainfall-runoff analysis models such as ONE model and Tank model have been developed and used for reservoir water balance analysis, but the applicability analysis for ungauged watersheds is insufficient. The ONE model is designed for daily runoff calculation, and the model has one parameter, which is advantageous for calibration and ungauged watershed analysis. In this study, the water balance was analyzed through the ONE model and the Tank model for 15 watersheds upstream of dams, and R² and NSE were used to quantitatively compare the performance of the two models. The simulation results show that the ONE model is suitable for predicting the inflow of agricultural reservoirs with the ungauged watershed

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1255-1272
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• 2023

Satellite-based chlorophyll-a concentration, produced as a long-term time series, is crucial for global climate change research. The production of data without gaps through the merging of time-synthesized or multi-satellite data is essential. However, studies related to satellite-based chlorophyll-a concentration in the waters around the Korean Peninsula have mainly focused on evaluating seasonal characteristics or proposing algorithms suitable for research areas using a single ocean color sensor. In this study, a merging dataset of remote sensing reflectance from the geostationary sensor GOCI-II and polar-orbiting sensors (MODIS, VIIRS, OLCI) was utilized to achieve high spatial coverage of chlorophyll-a concentration in the waters around the Korean Peninsula. The spatial coverage in the results of this study increased by approximately 30% compared to polar-orbiting sensor data, effectively compensating for gaps caused by clouds. Additionally, we aimed to quantitatively assess accuracy through comparison with global chlorophyll-a composite data provided by Ocean Colour Climate Change Initiative (OC-CCI) and GlobColour, along with in-situ observation data. However, due to the limited number of in-situ observation data, we could not provide statistically significant results. Nevertheless, we observed a tendency for underestimation compared to global data. Furthermore, for the evaluation of practical applications in response to marine disasters such as red tides, we qualitatively compared our results with a case of a red tide in the East Sea in 2013. The results showed similarities to OC-CCI rather than standalone geostationary sensor results. Through this study, we plan to use the generated data for future research in artificial intelligence models for prediction and anomaly utilization. It is anticipated that the results will be beneficial for monitoring chlorophyll-a events in the coastal waters around Korea.

• Journal of Korea Water Resources Association
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• v.52 no.5
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• pp.337-347
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• 2019

This study proposes the framework to select the representative general circulation model (GCM) for climate change projection. The grid-based results of GCMs were transformed to all considered meteorological stations using inverse distance weighted (IDW) method and its results were compared to the observed precipitation. Six quantile mapping methods and random forest method were used to correct the bias between GCM's and the observation data. Thus, the empirical quantile which belongs to non-parameteric transformation method was selected as a best bias correction method by comparing the measures of performance indicators. Then, one of the multi-criteria decision techniques, TOPSIS (Technique for Order of Preference by Ideal Solution), was used to find the representative GCM using the performances of four GCMs after the bias correction using empirical quantile method. As a result, GISS-E2-R was the best and followed by MIROC5, CSIRO-Mk3-6-0, and CCSM4. Because these results are limited several GCMs, different results will be expected if more GCM data considered.