• Title/Summary/Keyword: Water Disaster Management

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Assessment of Ecosystem services under changing climate in the Bagmati Basin of Nepal

  • Bastola, Shiksha;Seong, Yeon-Jeong;Lee, Sanghyup;Jung, Younghun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2019.05a
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    • pp.148-148
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    • 2019
  • The 2006 Millennium Ecosystem Assessment (MA) defines ecosystem services (ES) as "the benefits people obtain from ecosystems". Identifying where ES originates, whom it benefits and how it is changing over a period of time is critical in rapidly developing country like Nepal, where the risk of ES loss is high. In the context of various ecosystem services provided by watershed, this study, particularly deals with water yield, Soil loss and Carbon sequestration computation and evaluation in Bagmati Basin of Nepal. As Bagmati Basin incorporates capital city Kathmandu of nepal, land use change is significant over decades and mapping of ES is crucial for sustainable development of Basin in future. In this regard, the objectives of this study are 1) To compute the total and sub-watershed scale water yield of the basin, 2) Computation of soil loss and sediment retention in the basin, and 3) Computation of carbon sequestration in the basin. Integrated Valuation of Environmental Services and Tradeoffs (InVEST), a popular model for ecosystem service assessment based on Budyko hydrological method is used to compute Ecosystem services. The scenario of ES in two periods of time can be referenced for various approaches of prioritization and incorporation of their value into local and regional decision making for management of basin.

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Establishment of flood forecasting and warning system in the un-gauged small and medium watershed through ODA (ODA사업을 통한 미계측 중소하천 유역 홍수예경보시스템 구축)

  • Koh, Deuk-Koo;Lee, Chihun;Jeon, Jeibok;Go, Sukhyon
    • Journal of Korea Water Resources Association
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    • v.54 no.6
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    • pp.381-393
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    • 2021
  • As part of the National Disaster Management Research Institute's Official Development Assistance (ODA) projects for transferring new technologies in the field of disaster-safety management, a flood forecasting and warning system was established in 2019 targeting the Borikhan in the Namxan River Basin in Bolikhamxai Province, Laos. In the target area, which is an ungauged small and medium river basin, observation stations for real-time monitoring of rainfall and runoff and alarm stations were installed, and a software that performs real-time data management and flood forecasting and warning functions was also developed. In order to establish a flood warning standard and develop a nomograph for flood prediction, hydraulic and hydrological analysis was performed based on the 30-year annual maximum daily rainfall data and river morphology survey results in the target area. This paper introduces the process and methodology used in this study, and presents the results of the system's applicability review based on the data observed and collected in 2020 after system installation.

Performance Comparison of Machine Learning Models for Grid-Based Flood Risk Mapping - Focusing on the Case of Typhoon Chaba in 2016 - (격자 기반 침수위험지도 작성을 위한 기계학습 모델별 성능 비교 연구 - 2016 태풍 차바 사례를 중심으로 -)

  • Jihye Han;Changjae Kwak;Kuyoon Kim;Miran Lee
    • Korean Journal of Remote Sensing
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    • v.39 no.5_2
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    • pp.771-783
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    • 2023
  • This study aims to compare the performance of each machine learning model for preparing a grid-based disaster risk map related to flooding in Jung-gu, Ulsan, for Typhoon Chaba which occurred in 2016. Dynamic data such as rainfall and river height, and static data such as building, population, and land cover data were used to conduct a risk analysis of flooding disasters. The data were constructed as 10 m-sized grid data based on the national point number, and a sample dataset was constructed using the risk value calculated for each grid as a dependent variable and the value of five influencing factors as an independent variable. The total number of sample datasets is 15,910, and the training, verification, and test datasets are randomly extracted at a 6:2:2 ratio to build a machine-learning model. Machine learning used random forest (RF), support vector machine (SVM), and k-nearest neighbor (KNN) techniques, and prediction accuracy by the model was found to be excellent in the order of SVM (91.05%), RF (83.08%), and KNN (76.52%). As a result of deriving the priority of influencing factors through the RF model, it was confirmed that rainfall and river water levels greatly influenced the risk.

An Assessment of Flooding Risk Using Flash Flood Index in North Korea - Focus on Imjin Basin - (돌발홍수 지수를 이용한 북한 홍수 위험도 평가 - 임진강 유역을 중심으로 -)

  • Kwak, Chang Jae;Choi, Woo Jung;Cho, Jae Woong
    • Journal of Korea Water Resources Association
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    • v.48 no.12
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    • pp.1037-1049
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    • 2015
  • The most of natural disasters that occur in North Korea are flood, typhoon and damage from heavy rain. The damage caused by those disasters since the mid-1990s is aggravating North Korea's economic difficulties every year. By recognizing the seriousness of the damages from the floods, the North Korean government has carried out the river maintenance, farmland restoration, land readjustment and afforestation projects since the last-1990s, but it has failed preventing the damages. In order to estimate the degree of flood risk regarding damage from chronic floods that occur inveterately in North Korea, this research conducted an additional simulation for rainfall-runoff analysis to reflect the characteristics of the ungauged area that make foreign countries hard to obtain the hydrological data and do not open the topographical data to public. In addition, this research estimates the degree of flood risk by selecting the factors of the hazard, exposure and vulnerability by following the standards of the Intergovernmental Panel on Climate Change (IPCC).

Australia's Water Management Policies and Implications in Response to Climate Change (기후변화에 대응한 호주의 물관리 정책과 시사점)

  • Lee, Jong Wook;Park, Tae Sun;Lee, Seung Yeon;Lee, Seung Oh
    • Journal of Korean Society of Disaster and Security
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    • v.13 no.4
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    • pp.1-12
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    • 2020
  • Recently, as the extreme drought continued due to the reckless development and the dramatical climate change, national concern about the water management issues has been increased rapidly around the world, especially in Korea. Meanwhile, it is necessary to analyze and review the related cases in Australia, where they have developed the consistently, eco-friendly and systematically management from the national level, which is similar to that of Korea in difficult circumstances. Australia has been suffered by repeated droughts and floods due to low rainfall and dryness, and water disputes were begun with immigrant settlement in the 1890s. In the early days, water management agreements for efficient distribution of water resources, water use regulation programs, and federal water laws were enacted, and now the established water management system in which development and conservation are assumed to be well balanced. In Korea, however, in the past, the Ministry of Environment was responsible for water quality issues while the quantity was managed by the Ministry of Land, Infrastructure and Transport, and the main local departments for water management were divided. Therefore, it was difficult to manage the integrated water management due to problems such as duplicated works, excessive investments, and inefficiency. To resolve this situation, in 2018, all water management functions were unified, such as enacting the fundamental water-related laws, thereby laying the foundation for the integrated water management system for each basin. From 2019, even the integrated water management system was implemented, we are promoting the effect of sustainable water resource management. In order to establish a management policy for efficient and eco-friendly water management, the IWRM (Integrated Water Resource Management) of Australia, which has been devised in various ways, was analyzed and compared with the present situations and cases occurred in Korea, and the implications from this study would be suggested the future of IWRM in Korea.

Integrated Flood Risk Management through Modelling of Nature Based Solutions

  • Bastola, Shiksha;Kareem, Kola Yusuff;Park, Kiddo;Jung, Younghun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.160-160
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    • 2022
  • Floods are the most common natural disasters and are annually causing severe destructions worldwide. Human activities, along with expected increased extreme precipitation patterns as a result of climate change enhance the future potential of floods. There are proven evidence that infrastructure based responses to flood disaster is no longer achieving optimum mitigation and have created a false sense of security. Nature-based solutions(NBS) is a widely accepted sustainable and efficient approach for disaster risk reduction and involves the protection, restoration, or management of natural and semi-natural ecosystems to tackle the climate and natural crisis. Adoption of NBS in decision-making, especially in developing nations is limited due to a lack of sufficient scenario-based studies, research, and technical knowledge. This study explores the knowledge gap and challenges on NBS adoption with case study of developing nation, specially for flood management, by the study of multiple scenario analysis in the context of climate, land-use change, and policies. Identification and quantification of the strength of natural ecosystems for flood resilience and water management can help to prioritize NBS in policymaking leading to sustainable measures for integrated flood management.

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Development of an integrated platform for flood analysis in the smart city (스마트시티 홍수분석 연계플랫폼 개발)

  • Koo, Bonhyun;Oh, Seunguk;Koo, Jaseob;Shim, Kyucheoul
    • Journal of Korea Water Resources Association
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    • v.54 no.1
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    • pp.61-69
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    • 2021
  • In this study, in order to efficiently perform smart city river management, we developed an integrated platform that connects flood analysis models on the web and provides information by converting input and output data into a database. In the integrated platform, a watershed analysis model, a river flow analysis model and an urban runoff analysis model were applied to perform flood analysis in smart city. This platform is able to obtain more reliable results by step-by-step approach to urban runoff that may occur in smart city through the applied model. In addition, since all analysis processes such as data collection, input data generation and result storage are performed on the web, anyone in an environment that can access the web without special equipment or tools can perform analysis and view results. Through this, it is expected that smart city managers can efficiently manage urban runoff and nearby rivers, and can also be used as educational materials for urban outflows.

Water yield estimation of the Bagmati basin of Nepal using GIS based InVEST model (GIS기반 InVEST모형을 이용한 네팔 Bagmati유역의 물생산량 산정)

  • Bastola, Shiksha;Seong, Yeon Jeong;Lee, Sang Hyup;Jung, Younghun
    • Journal of Korea Water Resources Association
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    • v.52 no.9
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    • pp.637-645
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    • 2019
  • Among various ecosystem services provided by the basin, this study deals with water yield (WY) estimation in the Bagmati basin of Nepal. Maps of where water used for different facilities like water supply, irrigation, hydropower etc. are generated helps planning and management of facilities. These maps also help to avoid unintended impacts on provision and production of services. Several studies have focused on the provision of ecosystem services (ES) on the basin. Most of the studies have are primarily focused on carbon storage and drinking water supply. Meanwhile, none of the studies has specifically highlighted water yield distribution on sub-basin scale and as per land use types in the Bagmati basin of Nepal. Thus, this study was originated with an aim to compute the total WY of the basin along with computation on a sub-basin scale and to study the WY capacity of different landuse types of the basin. For the study, InVEST water yield model, a popular model for ecosystem service assessment based on Budyko hydrological method is used along with ArcGIS. The result shows water yield per hectare is highest on sub-basin 5 ($15216.32m^3/ha$) and lowest on sub-basin 6 ($10847.15m^3/ha$). Likewise, built-up landuse has highest WY capacity followed by grassland and agricultural area. The sub-basin wise and LULC specific WY estimations are expected to provide scenarios for development of interrelated services on local scales. Also, these estimations are expected to promote sustainable land use policies and interrelated water management services.