• Title/Summary/Keyword: Snow depletion

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Extraction of Snowmelt Parameters using NOAA AVHRR and GIS Technique for 5 River Basins in South Korea (NOAA AVHRR 영상 및 GIS 기법을 이용한 국내 5대강 유역의 융설 매개변수 추출)

  • Shin, Hyung-Jin;Park, Geun-Ae;Kim, Seong-Joon
    • Korean Journal of Remote Sensing
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    • v.23 no.2
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    • pp.119-124
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    • 2007
  • The few observed data related snowmelt was the major cause of difficulty in extracting snowmelt factors such as snow cover area, snow depth and depletion curve. Remote sensing technology is very effective to observe a wide area. Although many researchers have used remote sensing for snow observation, there were a few discussions on the characteristics of spatial and temporal variation. Snow cover maps were derived from NOAA AVHRR images for the winter seasons from 1997 to 2006. Distributed snow depth was mapped by overlapping between snow cover maps and interpolated snowfall maps from 69 meteorological observation stations. Model parameters (Snow Cover Area: SCA, snow depth, Snow cover Depletion Curve: SDC) building for 5 major watersheds in South Korea. Especially SDC is important parameter of snowmelt model.

Study of Snow Depletion Characteristics at Two Mountainous Watersheds Using NOAA AVHRR Time Series Data

  • Shin, Hyungjin;Park, Minji;Chae, Hyosok;Kim, Saetbyul;Kim, Seongjoon
    • Korean Journal of Remote Sensing
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    • v.29 no.3
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    • pp.315-324
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    • 2013
  • Spatial information of snow cover and depth distribution is a key component for snowmelt runoff modeling. Wide snow cover areas can be extracted from NOAA AVHRR or Terra MODIS satellite images. In this study eight sets of annual snow cover data (1997-2006) in two mountainous watersheds (A: Chungju-Dam and B: Soyanggang-Dam) were extracted using NOAA AVHRR images. The distribution of snow depth within the Snow Cover Area (SCA) was generated using snowfall data from ground meteorological observation stations. Snow depletion characteristics for the two watersheds were analyzed snow distribution time series data. The decreased pattern of SCA can be expressed as a logarithmic function; the determination coefficients were 0.62 and 0.68 for the A and B watersheds, respectively. The SCA decreased over 70% within 10 days from the time of maximum SCA.

Assessment of Snowmelt Impact on Chungju Dam Watershed Inflow Using Terra MODIS Data and SWAT Model (Terra MODIS 위성영상과 SWAT 모형을 이용한 융설이 충주댐 유입량에 미치는 영향 평가)

  • Kim, Saet Byul;Ahn, So Ra;Shin, Hyung Jin;Kim, Seong Joon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.2
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    • pp.457-467
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    • 2014
  • This study is to evaluate the snowmelt impact on dam inflow for the Chungju Dam watershed $6,642.0km^2$ using Terra MODIS (Moderate-Resolution Imaging Spectroradiometer) and Soil and Water Assessment Tool (SWAT). To determine the SWAT snowmelt parameter; snow cover depletion curve (SCDC) the snow depth distribution (SDD) using Terra MODIS was used, the snow depth was spatially interpolated using snowfall data of ground meteorological stations. For 10 sets (2000-2010) data during snowmelt period (November-April), the sno50cov parameter, that is, the 50% coverage at a fraction of SCDC which determines the shape of snow depletion process, showed the values of 0.4 to 0.7. The SWAT model was calibrated with average $R^2$ of 0.54 using the sno50cov of each year. The 10 years average streamflow during snowmelt period was 104.3 mm which covers 12.0% of the annual streamflow.

Extraction of Snowmelt Factors using NOAA Satellite Images and Meteorological Data (NOAA위성영상 및 기상자료를 이용한 융설 관련 매개변수 추출)

  • Kang, Su-Man;Shin, Hyung-Jin;Kwon, Hyung-Joong;Kim, Seong-Joon
    • Journal of Korea Water Resources Association
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    • v.39 no.10 s.171
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    • pp.845-854
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    • 2006
  • Establishment of snowmelt factors is necessary to simulate stream flow using snowmelt models during snowmelt periods. The few observed data related snowmelt was the major cause of difficulty in extracting snowmelt factors such as snow cover area, snow depth and depletion curve. The objective of this study was to extract snowmelt factors using RS, GIS technique and meteorological data. Snow cover maps were derived from NOAA/AVHRR images for the winter seasons from 1997 to 2003. Distributed snow depth was mapped by overlapping between snow cover maps and interpolated snowfall maps from 69 meteorological observation station. Depletion curves of snowmelt area were described from the linear regression equations of each year between the average temperature and snow cover area in Soyanggang-dam and chungju-dam watershed.

Extraction of Snowmelt Parameters using NOAA AVHRR and GIS Technique for 7 Major Dam Watersheds in South Korea (NOAA AVHRR 영상 및 GIS 기법을 이용한 국내 주요 7개 댐 유역의 융설 매개변수 추출)

  • Shin, Hyung Jin;Kim, Seong Joon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.2B
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    • pp.177-185
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    • 2008
  • Accurate monitoring of snow cover is a key component for studying climate and global as well as for daily weather forecasting and snowmelt runoff modelling. The few observed data related to snowmelt was the major cause of difficulty in extracting snowmelt factors such as snow cover area, snow depth and depletion curve. Remote sensing technology is very effective to observe a wide area. Although many researchers have used remote sensing for snow observation, there were a few discussions on the characteristics of spatial and temporal variation. Snow cover maps were derived from NOAA AVHRR images for the winter seasons from 1997 to 2006. Distributed snow depth was mapped by overlapping between snow cover maps and interpolated snowfall maps from 69 meteorological observation stations. Model parameters (Snow Cover Area: SCA, snow depth, Snow cover Depletion Curve: SDC) were built for 7 major watersheds in South Korea. The decrease pattern of SCA for time (day) was expressed as exponentially decay function, and the determination coefficient was ranged from 0.46 to 0.88. The SCA decreased 70% to 100% from the maximum SCA when 10 days passed.

Extraction of Snow Cover Area and Depth Using NOAA/AVHRR Images (NOAA/AVHRR 영상을 이용한 적설분포 및 적설심 추출)

  • Kang, Su-Man;Kwon, Hyung-Joong;Kim, Seong-Joon
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 2005.10a
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    • pp.254-259
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    • 2005
  • The shape of a streamflow hydrograph is very much controlled by the area and depth of snow cover in mountain area. The purpose of this study is to suggest extraction methods for snow cover area and depth using NOAA/AVHRR images in Soyanggang watershed. Snow cover area maps ware derived form channel 1, 3, 4 images of NOAA/AVHRR based on threshold value. In order to extract snow cover depth, snow cover area maps were overlaid daily snow depth data form 7 meteorological observation stations. Snow cover area and depth was mapped for period of Dec. 2002 and Mar. 2003. For evaluating snowmelt changes, depletion curve was created using daily snow cover area in the same period. It is necessary to compare these results with observed data and check the applicability of the suggested method in snowmelt simulation.

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Assessment of climate change impact on Hydrology and water quality by snowmelt (기후변화를 고려한 미래 융설이 수문-수질에 미치는 영향 평가)

  • Kim, Saet-Byul;Ha, Rim;Yu, Yung-Seok;Yi, Jae-Eung;Kim, Seong-Joon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2012.05a
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    • pp.126-126
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    • 2012
  • 기후변화는 전 세계적으로 다양한 영향을 미치고 있으며 특히, 홍수나 대설로 인한 수문변화에 영향을 준다. 본 연구는 준분포형 연속 모형인 SWAT (Soil and Water Assessment Tool)모형을 이용하여 우리나라 3대 대설지역에 속하는 다목적댐인 충주댐유역(6642.0 m)의 기후변화에 따른 융설이 수문과 수질에 미치는 영향을 분석하고자 한다. 먼저, 융설 모형의 매개변수인 적설분포면적감소곡선 (Snow Cover Depletion Curve; SCDC)을 구축하기 위하여 10년(2000-2010)동안의 Terra MODIS (MODerate resolution Imaging Spectroradiometer) 위성영상자료와 6개 기상관측소(충주, 제천, 원주, 영월, 대관령, 태백)의 최심적설자료를 이용하여 연도별 SCDC을 구축하였다. 구축 결과, 눈이 50% 피복 일 때 snow volume은 연 평균 0.47로 분석되었다. 이를 SWAT 모형에 적용하여 수문과 수질에 대한 적용성 평가를 실시한 결과, 유출의 경우 NSE는 융설기간 동안 평균 0.8, 전체기간은 평균 0.6으로 나타났으며 수질(Sediment, T-N, T-P)의 경우 각각 평균 0.72, 0.70, 0.85을 나타내었다. 미래 기후자료는 IPCC(Intergovernmental Panel on Climate Change)에서 제공하는 SRES(Special Report on Emission Scenarios) A1B, B1 기후변화시나리오의 HadCM3 모델의 결과 값을 이용하였으며 기간은 과거 30년 기후자료(1981-2010, baseline)를 바탕으로 2040s(2020-2059), 2080s(2060-2099)의 두 기간으로 나누어 각각 분석하였으며 기후변화 결과 값의 불확실성을 줄이고자 과거 자료와 GCM의 1981년에서 2000년까지의 값을 비교하여 온도와 강수량의 보정을 실시한 후 LARS-WG를 이용하여 온도와 강수량 자료를 구축하였다. SWAT 모형을 적용한 결과, 평균 1.92 증가한 것으로 나타났으며 유출은 융설기간(Nov-Apr)이 비융설기간(May-Oct)보다 10% 더 증가하였다. 본 연구에서는 SWAT 모형을 통한 유출 및 환경부하량 전망을 목표로 하여 미래 기후변화를 고려한 융설이 다목적댐에서의 유출과 수질 (Sediment, Total Nitrogen, Total Phosphorus)에 미치는 영향을 평가해 보고자 한다.

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Quantification of Total Mercury in Antarctic Surface Snow using ICP-SF-MS: Spatial Variation from the Coast to Dome Fuji

  • Han, Yeong-Cheol;Huh, Young-Sook;Hong, Sung-Min;Hur, Soon-Do;Motoyama, Hideaki;Fujita, Shuji;Nakazawa, Fumio;Fukui, Kotaro
    • Bulletin of the Korean Chemical Society
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    • v.32 no.12
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    • pp.4258-4264
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    • 2011
  • The total mercury concentration ($Hg_T$) of surface snow samples collected along a ~1500 km transect in east Queen Maud Land was determined using inductively coupled plasma sector field mass spectrometry to address the behavior of Hg on the Antarctic Plateau. Due to the volatile nature of mercury, measures were taken against Hg loss from standard solutions by choosing appropriate container material and stabilizing agents. Glass bottles with Teflon-lined caps were superior to Teflon and polyethylene containers in protecting against Hg loss, but addition of gold chloride ($AuCl_3$) or bromine chloride (BrCl) was necessary to ensure preservation of Hg. As Hg loss was also observed in snowmelt samples, our analysis may underestimate the actual amount of HgT in the snow. Even so, the measured HgT was still very low (< 0.4-10.8 pg $g^{-1}$, n = 44) without a signal of depositional enhancement accompanying photo-oxidation of atmospheric elemental mercury in austral midsummer. Moreover, the dynamic variation along the traverse implies spatial and temporal heterogeneity in its source processes.

Extraction of Snowmelt Parameters using NOAA AVHRR and GIS Technique for 5 River Basins in South Korea (NOAA AVHRR 영상 및 GIS 기법을 이용한 국내 5대강 유역의 융설 매개변수 추출)

  • Shin, Hyung-Jin;Park, Geun-Ae;Kim, Seong-Joon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2007.05a
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    • pp.194-198
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    • 2007
  • 융설 모형의 중요 매개변수인 적설분포면적은 실제 우리나라에서 적설과 관련한 관측 자료의 부족으로 인해 매개변수 추정이 어렵다. 이러한 문제점 해결을 위해 원격탐사기법을 활용하여 적설분포면적을 추출하였다. 본 연구에서는 1997년부터 2006년까지의 겨울철 NOAA (National Oceanic and Atmospheric Administration)의 AVHRR(Advanced Very High Resolution Radiometer) 위성영상의 8 sets의 총 108개 영상을 이용하여 적설분포면적을 추출하였고, 기상청의 지상기상관측소의 최심적설심 자료를 이용하여 GIS 자료를 구축함으로써 적설심의 공간적 분포를 추출하였다. 이를 국내 5대유역인 한강, 낙동강, 금강, 영산강, 섬진강 유역에 대하여 융설모형의 주요 매개변수인 적설분포면적, 유역 평균, 최대 적설심과 적설분포감소비곡선을 구축하였다. 그 중 적설분포면적감소곡선 (SDC : Snow cover Depletion Curve)는 적설분포면적의 감소형태를 나타내주는 지표로써 융설의 가장 민감한 매개변수이다. 이를 국내 5대강 유역에 대해 구축하여 정량화하였다.

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Assessment of fishing power and fishing capacity of the snow crab (Chionoecetes opilio) gillnet fishery in the East Sea (동해안 대게 자망어업의 어획 성능 및 어획 능력 평가)

  • Lee, Kyoung-Hoon;Kim, Pyung-Kwan;Kim, Do-Hoon;An, Heui-Chun;Lee, Chun-Woo
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.48 no.1
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    • pp.29-39
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    • 2012
  • Currently, environment-friendly and sustainable fisheries are one of the major issues among fisheries authorities. A variety of alternative management policies and projects are going on to enhance fisheries management systems and fishery resources such as a TAC management program and a VDS (Vessel Day Scheme) management scheme for distant water fishing nations in Western and Central Pacific Fisheries Commission (WCPFC) convention area. These kinds of efforts among fisheries management authorities are aimed at limiting fishing capacity or fishing power. In terms of fisheries management, Fishing capacity and fishing power have increased the importance of the impact on a fishery and level of the resources. Increased fishing capacity and fishing power have caused not only depletion of fisheries resource, but also additional fishing cost. therefore, there is a clear need for authorities to manage fishing capacity and fishing power. It is also help ensure the conservation and sustainability of the fishery resources. Because of lack of data, absolute fishing power is difficulty to measure. The notion of relative fishing power is frequently used. In this study, relative fishing power was assessed using Mastuda (1991) method for fishing power index. The raw data for assessment was based on fishermen's logbook data from sampled fishing vessels in coastal snow crab gillnet fishery. Data Envelopment Analysis (DEA) method was used to assess fishing capacity. DEA is a linear programming methodology to measure the efficiency of a set of entities called Decision-Making Units (DMUs). It was recommended by FAO for assessing capacity in fisheries.