• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1095-1107
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• 2020

Flood monitoring using satellite data has been constrained by obtaining satellite images for flood peak and accurately extracting flooded areas from satellite data. Deep learning is a promising method for satellite image classification, yet the potential of deep learning-based flooded area extraction using SAR data remained uncertain, which has advantages in obtaining data, comparing to optical satellite data. This research explores the performance of SegNet and U-Net on image segmentation by extracting flooded areas in the Khorat basin, Mekong river basin, and Cagayan river basin in Thailand, Laos, and the Philippines from Sentinel-1 A/B satellite data. Results show that Global Accuracy, Mean IoU, and Mean BF Score of SegNet are 0.9847, 0.6016, and 0.6467 respectively, whereas those of U-Net are 0.9937, 0.7022, 0.7125. Visual interpretation shows that the classification accuracy of U-Net is higher than SegNet, but overall processing time of SegNet is around three times faster than that of U-Net. It is anticipated that the results of this research could be used when developing deep learning-based flood monitoring models and presenting fully automated flooded area extraction models.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.176-176
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• 2023

The Tonle Sap is the richest and diverseness of freshwater ecosystem in Southeast Asia, receiving nurturing water flows from the Mekong and its immediate basin. In addition, the rapid development in the Tonle Sap Lake (TSL) Basin, and flood inundation may threaten the natural diversities and characteristics. The impacts of flood inundation in 11 sub-basins contributing to the Tonle Sap Lake were assessed using the Rainfall-Runoff-Inundation (RRI) model to quantify the potential magnitude and extent of the flooding. The RRI model is set up by using gauged rainfall data to simulate the information of river discharge and flood inundation of huge possible flood events. Moreover, two satellite precipitation products (SPPs), CHIRPS and GSMaP, within respectively spatial resolutions of 0.05° and 0.1°, are utilized as an input for the RRI model to simulate river discharge, flood depth, and flood extent for the great TSL Basin of Cambodia. This study used statistical indicators such as NSE, PBIAS, RSR, and R2 as crucial indices to evaluate the performance of the RRI model. Therefore, the findings of this study could provide promising guidance in hydrological modeling and the significant implications for flood risk management and disaster preparedness in the region.

• Journal of Korea Water Resources Association
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• v.51 no.7
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• pp.565-574
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• 2018

High population density in deltaic settings, especially in Asia, tends to increase and causes coastal flood risk because of lower elevations and significant subsidence. Large flood annually causes numerous deaths and huge economic losses. In this paper, an innovative technology of spatial satellite imagery has been used as tool to analyze the socio-economic flood-related damage in Mekong river basin. The relationship between nightlight intensity and flood damages has been determined for the period of 1992-2013 with a spatial resolution of 30 arc sec ($0.0083^{\circ}$), which is nearly one kilometer at the equator. Flow path distance was calculated to identify the distance of each cell to river network and to examine how nightlight intensity correlate to the area close to and far from river network. Statistical analysis results highlight the significant correlation between nocturnal luminosity intensity and flood-related damages in countries along the Mekong river (i.e., Cambodia, China, Lao PDR, Thailand, and Vietnam). This result reveals that the areas close to the river network correspond to high human distribution and causes huge damage during flooding. The result may provide key information to the region with respect to decisions, attentions, and mitigation strategies.

• Journal of Korea Water Resources Association
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• v.56 no.2
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• pp.75-89
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• 2023

As the Mekong River basin is a nationally shared river, it is difficult to collect precipitation data, and the quantitative and qualitative quality of the data sets differs from country to country, which may increase the uncertainty of hydrological analysis results. Recently, with the development of remote sensing technology, it has become easier to obtain grid-based precipitation products(GPPs), and various hydrological analysis studies have been conducted in unmeasured or large watersheds using GPPs. In this study, rainfall-runoff simulation in the Mekong River basin was conducted using the SWAT model, which is a quasi-distribution model with three satellite GPPs (TRMM, GSMaP, PERSIANN-CDR) and two GPPs (APHRODITE, GPCC). Four water level stations, Luang Prabang, Pakse, Stung Treng, and Kratie, which are major outlets of the main Mekong River, were selected, and the parameters of the SWAT model were calibrated using APHRODITE as an observation value for the period from 2001 to 2011 and runoff simulations were verified for the period form 2012 to 2013. In addition, using the ConvAE, a convolutional neural network model, spatio-temporal correction of original satellite precipitation products was performed, and rainfall-runoff performances were compared before and after correction of satellite precipitation products. The original satellite precipitation products and GPCC showed a quantitatively under- or over-estimated or spatially very different pattern compared to APHPRODITE, whereas, in the case of satellite precipitation prodcuts corrected using ConvAE, spatial correlation was dramatically improved. In the case of runoff simulation, the runoff simulation results using the satellite precipitation products corrected by ConvAE for all the outlets have significantly improved accuracy than the runoff results using original satellite precipitation products. Therefore, the bias correction technique using the ConvAE technique presented in this study can be applied in various hydrological analysis for large watersheds where rain guage network is not dense.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.207-207
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• 2021

The Vietnamese Mekong Delta(VMD) covers an area of 62,250 km² in the lowest basin of the Mekong Delta where more than half of the country's total rice production takes place. In 2016, an estimated 1.29 million tonnes of Vietnam's rice were lost to the country's biggest drought in 90 year and particularly in VMD, at least 221,000 hectares of rice paddies were hit by the drought and related saltwater intrusion from the South China Sea. In this study, 3D numerical simulations using Delft3D hydrodynamic models with calibration and validation process were performed to examine flow characteristics, climate change scenarios, water level changes, and salinity concentrations in the nine major estuaries and coastal zones of VMD during the 21^st century. The river flows and their interactions with ocean currents were modeled by Delft3D and since the water levels and saltwater intrusion in the area are sensitive to the climate conditions and upstream dam operations, the hydrodynamic models considered discharges from the dams and climate data provided by the Coupled Model Intercomparison Project Phase 6(CMIP6). The models were calibrated and verified using observational water levels, salinity distribution, and climate change data and scenarios. The results agreed well with the observed data during calibration and validation periods. The calibrated models will be used to make predictions about the future salinity intrusion events, focusing on the impacts of sea level rise due to global warming and weather elements.

• Journal of Korea Port Economic Association
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• v.32 no.4
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• pp.193-209
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• 2016

The Mekong River is a river in the south-eastern part of the continent of Aisa. It flows through the countries of Thailand, Lao PDR, Cambodia, Myanmar, and Vietnam that are located in Indochina and are members of ASEAN. These countries are growing rapidly and many others have entered into these markets. As the number of manufactures has increased, logistics markets become very attractive to our logistics companies that want to expand their business. This study focuses on four countries, Lao PDR, Cambodia, Myanmar, and Vietnam, which have potential economic growth and shows the environment of logistics with current logistics infrastructure and related investment law and system. The goal of this study to provide, with strength, weakness, opportunities, and threats(SWOT) analysis, some strategies to enter 4 countries' logistics market with SWOT and the strategies are as follows; First, foreign direct investment in logistics is linked with logistics infrastructure projects. Our government should strengthen its role to find cooperation programs that make connect with logistics business. Second, a logistics company is better off in a consortium with other manufacturers or other logistics companies to ensure minimum cargo and reduce entry risks. Finally, the four countries' roles as a logistics bases need to divided according to their environments, to benefits of logistics connecting between India and China.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.43-43
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• 2021

Sesan강과 Srepok강은 베트남, 캄보디아, 라오스가 공유하는 3S강 유역 (Sesan강, Srepok강, Sekong강)의 일부로 국제 공유하천으로 관리되고 있다. 3S강 유역은 Mekong강의 중요한 지류이며 Mekong강 유역의 상당 부분을 구성한다(Mekong강 유역 면적의 10%, 연간 총 유출량의 20%). 베트남에 속해 있는 Sesan강 유역면적은 11,255km², Srepok강 유역면적은 18,162km²이다. Sesan강과 Srepok강의 상류는 베트남 중부 고원의 긴 산맥에 위치하고 있으며, 하류는 캄보디아에 위치해 있어 상·하류간 긴밀한 협력이 필요하다. Sesan강과 Srepok강 유역은 기후변화에 따른 홍수, 가뭄, 수력발전소 건설로 인한 유출량 변동에 따른 상·하류 분쟁, 사면침식 및 퇴적 등 많은 문제와 도전에 직면할 것으로 예측되고 있다. 본 연구에서는 World Bank의 "Viet Nam Mekong Integrated Water Resources Management (M-IWRM) Project의 일환으로 베트남 정부 차원에서 처음으로 구축한 수자원관리 의사결정지원시스템인 "DSS-2S"를 활용하여, Sesan-Srepok강 유역의 수자원 계획을 수립하였다. DSS-2S는 MIKE Hydro Basin을 기반으로 SWAT모델 등과 연계 하여 구축되었다. DSS-2S는 2S 유역의 모든 주요 하천과 지류를 반영하였으며. 여기에는 17개의 수력발전 댐과 주요 지류에서 용량이 3백만 m³ 이상인 기타 저수지가 포함되었다. 이 보다 작은 용량의 저수지는 대표적인 저수지로 그룹화 되어 반영되었다. 기후변화 및 사회-경제적 발전계획 등을 반영하여, 2030년과 2050년을 목표연도로 생활, 공업, 농업, 관광, 유지용수 등 용수 수요를 추정하였다. 50% 및 85% 빈도의 공급 가능성을 고려하여 물 배분은 물 수요를 충족하고 지하수 개발 최소화를 기준으로 고려되었다. 분석 결과에 의하면 2S강 유역의 총 수자원은 32.2억 m³으로 그중 지표수자원은 29.2억 m³, 안정적으로 이용 가능한 지하수자원은 2.97억 m³으로 분석 되었으며, 지표수와 지하수 연계를 고려하면 전체 2S 강 유역에 물 부족하지는 않으나, 개별 공급 지점을 고려할 때 4월과 5월에 일부 지역에서 물 부족이 나타날 것으로 예측 된다. 장래 물 부족 해결을 위한 대안들을 제시하였으며, 본 성과는 베트남 중앙 정부의 장기수자원 종합계획 수립의 기본 자료로 활용 될 예정이다.

• Journal of the Korean Geographical Society
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• v.51 no.6
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• pp.779-797
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• 2016

A calibrated hydrological model is a useful tool for quantifying the impacts of the climate variations and land use/land cover changes on sediment load, water quality and runoff. In the rainy season each year, the Xe Bang Fai river basin is provisionally flooded because of typhoons, the frequency and intensity of which are sensitive to ongoing climate change. Severe heavy rainfall has continuously occurred in this basin area, often causing severe floods at downstream of the Xe Bang Fai river basin. The main purpose of this study is to investigate the climate change impact on river discharge using a Soil and Water Assessment Tool (SWAT) model based on future climate change scenarios. In this study, the simulation of hydrological river discharge is used by SWAT model, covering a total area of $10,064km^2$ in the central part of country. The hydrological model (baseline) is calibrated and validated for two periods: 2001-2005 and 2006-2010, respectively. The monthly simulation outcomes during the calibration and validation model are good results with $R^2$ > 0.9 and ENS > 0.9. Because of ongoing climate change, three climate models (IPSL CM5A-MR 2030, GISS E2-R-CC 2030 and GFDL CM3 2030) indicate that the rainfall in this area is likely to increase up to 10% during the summer monsoon season in the near future, year 2030. As a result of these precipitation increases, the SWAT model predicts rainy season (Jul-Aug-Sep) river discharge at the Xebangfai@bridge station will be about $800m^3/s$ larger than the present. This calibrated model is expected to contribute for preventing flood disaster risk and sustainable development of Laos

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.194-194
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• 2022

정확한 강우-유출 해석은 하천 홍수예경보, 댐 유입량 산정 및 방류량 결정 등 수자원 관리 및 계획수립에 있어 중요하며 밀도높은 관측망(raingauge network)으로 부터 수집된 강우 자료는 강우-유출 해석의 가장 중요한 기초 자료로 활용된다. 본 연구 대상 지역인 메콩강 유역은 국가공유하천(6개국: 중국, 라오스, 태국, 미얀마, 베트남, 캄보디아)은 기초 자료 수집이 어렵고, 구축된 자료의 양적, 질적 품질이 국가별로 상이하여 수문해석 결과의 불확실성을 높일 우려가 있다. 최근 원격탐사 기술의 발달로 격자형 글로벌 강수자료의 획득이 용이해졌으며, 이를 활용한 다양한 연구들이 수행된 바 있다. 이에 본 연구에서는 준 분포모형인 SWAT (Soil & Water Assessment Tool) 모형을 활용하여 격자형 위성 강수 자료(TRMM, GSMaP, PERSIANN-CDR)와 격자형 지점 강수 자료(APHRODITE, GPCC)의 메콩강 유역 강우-유출 모의에 대한 성능을 평가하였다. 유출량 산정을 위한 관측소로는 Luang Prabang, Pakse, Stung Treng, Prek Kdam 관측소를 선정하였으며 지점강수량 정보가 비교적 충분한 2000-2007년을 대상으로 매개변수 보정(2000-2003) 및 유출모의 검증(2004-2007)을 수행하였다. 격자형 강우를 이용한 유출분석 결과, APHRODITE, GPCC 및 TRMM이 다른 격자형 강수 자료(GSMaP, PERSIANN-CDR)보다 우수한 성능을 보였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.37-37
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• 2018

메콩강 유역은 중국, 미얀마, 라오스, 태국, 캄보디아 및 베트남의 6개국이 공유하는 국제하천으로 각국의 안보, 경제성장 및 발전 등에 밀접한 영향을 주며 유역의 개발과정에서 국가별 개발전략 및 경제발전의 차이, 환경문제에 대한 입장의 차이로 인한 다양한 문제가 발생하고 있다. 특히 상류인 중국의 댐 건설 이후 갈수기에 메콩 강 하류지역의 수위가 매년 하락하는 현상이 발생하면서 중국의 수자원 무기화에 대한 우려가 심화되고 있다. 이와 같은 수자원의 통제는 메콩 강 하류 국가의 홍수나 가뭄조절에 대한 대응을 어렵게 하며 최근 급격한 기후변화로 인한 재난위험의 증가는 이에 대한 우려를 심화시키고 있다. 이에 대한 대응으로 하류 국가들 또한 메콩 강 곳곳에 댐을 건설하려는 계획을 수립하고 있어 메콩 강 유역의 무분별한 댐 건설에 대한 문제들이 제기되고 있다. 이러한 문제의 해결방안 마련을 위해서는 기후변화 또는 유역개발이 사회 경제 및 환경에 미치는 영향에 대한 사전분석이 매우 중요하며 기본적으로 강우-유출해석 시스템의 구축을 통한 사회 경제적 영향에 대한 예측 및 검토는 정책결정 및 수자원관리측면에서 매우 중요한 요소이다. 본 연구에서는 메콩강 유역을 대상으로 준 분포형 모형인 SWAT 모형에 전 세계적으로 구축되어 제공되는 범용 공간정보자료 및 기후변화 시나리오를 이용하여 강우-유출해석 시스템을 구축하고 메콩강 유역의 2100년까지의 미래 유출변화를 분석하였다. 이를 위해 메콩강유역을 총 33개의 소유역으로 분할하고 HadGEM의 RCP45 및 RCP85 기후변화시나리오를 소유역별 과거자료를 이용한 임의보정의 과정을 거쳐 적용하였다. 본 연구의 결과는 미래 메콩강 유역개발 및 수자원 관리 및 다양한 시나리오 적용을 위한 기초자료로 유용하게 활용될 수 있을 것으로 판단되며, 앞서 밝힌바와 같이 현재 메콩 강은 댐에 의한 수자원 통제의 영향이 커지고 있음에도 불구하고 방류데이터 등의 비공개로 이에 대한 영향은 고려하지 못하는 한계가 존재하기에 향후 이와 관련한 시나리오의 적용 등 추가적인 연구 또한 필요하다고 판단된다.