• Title/Summary/Keyword: land change modeling

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Assessment of Hydrological Impact by Long-Term Land Cover Change using WMS HEC-1 Model in Gyeongan-cheon Watershed (WMS HEC-1 모형을 이용한 경안천 유역의 경년 수문변화 분석)

  • Lee, Jun-Woo;Kwon, Hyung-Joong;Shin, Sha-Chul;Kim, Seong-Joon
    • Journal of the Korean Association of Geographic Information Studies
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    • v.6 no.1
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    • pp.107-118
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    • 2003
  • The purpose of this study is to assess the hydrological impact on a watershed from long-term land cover changes. Gyeongan-cheon watershed($558.2km^2$) was selected and WMS(watershed modeling system) HEC-1 model was adopted as an evaluation tool. To identify land cover changes, five Landsat images(1980/2/15, 1986/4/15, 1990/4/26, 1996/4/26, 2000/5/17) were selected and analyzed using maximum likelihood method. As a result, urban areas have increased by 5.6% and forest areas have decreased by 6.1% between 1980 and 2000. SCS curve number increased by 9.8. To determine model parameters and evaluate HEC-1 model, five storm events(1998/5/2, 1998/8/23, 1998/9/30, 1999/5/3, 2000/7/29) were used. The simulated stream flow agreed well with the observed one with relative errors ranging from 9% to 36%. For 254 mm daily rainfall of 30 years frequency, due to the increase of urban areas peak flow increased by $455m^3/sec$ and the time of peak flow reduced about four hours for 20 years land cover changes.

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Environmental Impact Assessment of Nuclear Power Plant Accident using Spatial Information Modeling: A Case Study of Chernobyl (공간정보 모델링을 이용한 원전 사고의 환경 영향 평가: 체르노빌 사례연구)

  • Lee, Sang-Won;Song, Ah-Ram;Park, No-Wook
    • Korean Journal of Remote Sensing
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    • v.28 no.1
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    • pp.129-143
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    • 2012
  • This paper demonstrates the effectiveness of advanced spatial modeling techniques for environmental monitoring and impact assessment through a case study of Chernobyl nuclear accident occurred in 1986. Land-cover types changed after the accident are analysed by a post classification comparison method using bi-temporal Landsat TM data acquired in 1986 and 1992 near the accident site. Spatial modeling including various kriging algorithms are also applied to analyze the relationships between Cesium concentrations in soil and thyroid cancer incidence rates in Belarus, which was greatly damaged by the accident. The change detection results clearly showed the decrease of croplands and the increase of abandoned lands, and concrete structures were newly built around the nuclear plant to prevent the spread of radioactive contamination. In Belarus, high Cesium concentrations were observed in southern areas with high thyroid cancer risk estimated by Poisson kriging. Geographically weighted regression, which could account for geographic variations of independent variables including Cesium concentrations and distances from the Chernobyl nuclear power plant, was applied to extract the relationships between the independent variables and the thyroid cancer risk. The estimated risk values showed a correlation coefficient value of 0.98 with respect to the thyroid cancer risk values, which implied that the thyroid cancer risk in Belarus was affected by the accident. In conclusion, it is expected that advanced spatial modeling techniques applied in this study would be useful for environmental impact assessment and public health research.

Restoration of the Stream Runoff by the Physical Deterministic Modeling and Formulation of Water Balance for the Catchment of Byungchun River in Chungcheong Province in Korea (물리 결정 모델링에 의한 충청도 병천천 유역의 하천 유출량 복원과 물 수지 수립)

  • KIM, Man-Kyu
    • Journal of The Geomorphological Association of Korea
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    • v.15 no.2
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    • pp.37-53
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    • 2008
  • This study has developed a water balance model for the catchment of Byungchun river using a BROOK90 4.4e physical deterministic water balance model with the long-term meterological data and stream run off data obtained from the basin of Byungchun river in Korea. It is intended that the validation model with calibrated model fitting parameter can build a long-term water balance plan for a period when meterological data are available but stream runoff data are not. Results of this study have satisfied the first expectation as an experiment for water balance modeling since measured stream runoff data have turned out to be very similar to simulated stream runoff data. Through the confirmation of model fitting parameters and validated simulation, water balance for the period of 1998 to 2006 has been restored. Unless the conditions of geomophology, vegetation, soil and land use change, meterological data alone can produce various hydrometeorological data related to stream runoff amount, soil water amount, and evapotranspiration. This study opens up a new horizon in restoring water balance in the past as well planning water balance in the present. The obtained results from this study are expected to be used in predicting future water balance in the wake of the changes in climate and vegetation in Korea.

Composite model for seawater intrusion in groundwater and soil salinization due to sea level rise (해수면 상승으로 인한 지하수 해수침투 및 토양 염류화 합성 평가모델)

  • Jung, Euntae;Park, Namsik;Cho, Kwangwoo
    • Journal of Korea Water Resources Association
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    • v.50 no.6
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    • pp.387-395
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    • 2017
  • Sea level rise, accompanied by climate change, is expected to exacerbate seawater intrusion in the coastal groundwater system. As the salinity of saturated groundwater increases, salinity can increase even in the unsaturated soil above the groundwater surface, which may cause crop damage in the agricultural land. The other adverse impact of sea level rise is reduced unsaturated soil thicknesses. In this study, a composite model to assess impacts of sea level rise in coastal agricultural land is proposed. The composite model is based on the combined applications of a three dimensional model for simulating saltwater intrusion into the groundwater and a vertical one dimensional model for simulating unsaturated zone flow and transport. The water level and salinity distribution of groundwater are calculated using the three dimensional seawater intrusion model. At some uppermost nodes, where salinity are higher than the reference value, of the 3D mesh one dimensional unsaturated zone modeling is conducted along the soil layer between the ground water surface and the ground surface. A particular location is judged salinized when the concentration at the root-zone depth exceeds the tolerable salinity for ordinary crops. The developed model is applied to a hypothetical agricultural reclamation land. IPCC RCP 4.5 and 8.5 scenarios were used as sea level rise data. Results are presented for 2050 and 2100. As a result of the study, it is predicted that by 2100 in the climate change scenario RCP 8.5, there will be 7.8% increase in groundwater saltwater-intruded area, 6.0% increase of salinized soil area, and 1.6% in increase in water-logging area.

Production of Farm-level Agro-information for Adaptation to Climate Change (기후변화 대응을 위한 농장수준 농업정보 생산)

  • Moon, Kyung Hwan;Seo, Hyeong Ho;Shin, Min Ji;Song, Eung Young;Oh, Soonja
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.21 no.3
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    • pp.158-166
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    • 2019
  • Implementing proper land management techniques, such as selecting the best crops and applying the best cultivation techniques at the farm level, is an effective way for farmers to adapt to climate change. Also it will be helpful if the farmer can get the information of agro-weather and the growth status of cultivating crops in real time and the simulated results of applying optional technologies. To test this, a system (web site) was developed to produce agro-weather data and crop growth information of farms by combining agricultural climate maps and crop growth modeling techniques to highland area for summer-season Chinese cabbage production. The system has been shown to be a viable tool for producing farm-level information and providing it directly to farmers. Further improvements will be required in the speed of information access, the microclimate models for some meteorological factors, and the crop growth models to test different options.

Modeling water supply and demand under changing climate and socio-economic growth over Gilgit-Baltistan of Pakistan using WEAP

  • Mehboob, Muhammad Shafqat;Panda, Manas Ranjan;Kim, Yeonjoo
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.116-116
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    • 2020
  • Gilgit-Baltistan (GB) is a highly mountainous and remote region covering 45% of Upper Indus Basin (UIB) with around 1.8 million population is vulnerable to climate change and socio-economic growth makes water resources management and planning more complex. To understand the water scarcity in the region this study is carried out to project water supply and demand for agricultural and domestic sector under various climate-socio-economic scenarios in five sub catchments of GB i.e., Astore, Gilgit, Hunza, Shigar and Shyok for a period of 2015 to 2050 using Water Evaluation and Planning (WEAP) model. For climate change scenario ensembled mean of three global climate models (GCMs) was used under three different Representative Concentration Pathway (RCP) scenarios (RCP2.6, RCP6.0 and RCP8.5). The Shared Socioeconomic Pathways (SSPs) and agricultural Land Development (LD) scenarios were combined with climate scenarios to develop climate-socio-economic scenario. Our results indicate that the climate change and socio-economic growth would create a gap between supply and demand of water in the region, with socio-economic growth (e.g. agricultural and population) as dominant external factor that would reduce food production and increase poverty level in the region. Among five catchments only Astore and Gilgit will face shortfall of water while Shyoke would face shortfall of water only under agricultural growth scenarios. We also observed that the shortfall of water in response to climate-socio-economic scenarios is totally different over two water deficient catchments due to its demography and geography. Finally, to help policy makers in developing regional water resources and management policies we classified five sub catchments of UIB according to its water deficiency level.

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Detection and Correction of Noisy Pixels Embedded in NDVI Time Series Based on the Spatio-temporal Continuity (시공간적 연속성을 이용한 오염된 식생지수(GIMMS NDVI) 화소의 탐지 및 보정 기법 개발)

  • Park, Ju-Hee;Cho, A-Ra;Kang, Jeon-Ho;Suh, Myoung-Seok
    • Atmosphere
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    • v.21 no.4
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    • pp.337-347
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    • 2011
  • In this paper, we developed a detection and correction method of noisy pixels embedded in the time series of normalized difference vegetation index (NDVI) data based on the spatio-temporal continuity of vegetation conditions. For the application of the method, 25-year (1982-2006) GIMMS (Global Inventory Modeling and Mapping Study) NDVI dataset over the Korean peninsula were used. The spatial resolution and temporal frequency of this dataset are $8{\times}8km^2$ and 15-day, respectively. Also the land cover map over East Asia is used. The noisy pixels are detected by the temporal continuity check with the reference values and dynamic threshold values according to season and location. In general, the number of noisy pixels are especially larger during summer than other seasons. And the detected noisy pixels are corrected by the iterative method until the noisy pixels are completely corrected. At first, the noisy pixels are replaced by the arithmetic weighted mean of two adjacent NDVIs when the two NDVI are normal. After that the remnant noisy pixels are corrected by the weighted average of NDVI of the same land cover according to the distance. After correction, the NDVI values and their variances are increased and decreased by 5% and 50%, respectively. Comparing to the other correction method, this correction method shows a better result especially when the noisy pixels are occurred more than 2 times consistently and the temporal change rates of NDVI are very high. It means that the correction method developed in this study is superior in the reconstruction of maximum NDVI and NDVI at the starting and falling season.

Habitat Distribution Change Prediction of Asiatic Black Bears (Ursus thibetanus) Using Maxent Modeling Approach (Maxent 모델을 이용한 반달가슴곰의 서식지 분포변화 예측)

  • Kim, Tae-Geun;Yang, DooHa;Cho, YoungHo;Song, Kyo-Hong;Oh, Jang-Geun
    • Korean Journal of Ecology and Environment
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    • v.49 no.3
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    • pp.197-207
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    • 2016
  • This study aims at providing basic data to objectively evaluate the areas suitable for reintroduction of the species of Asiatic black bear (Ursus thibetanus) in order to effectively preserve the Asiatic black bears in the Korean protection areas including national parks, and for the species restoration success. To this end, this study predicted the potential habitats in East Asia, Southeast Asia and India, where there are the records of Asiatic black bears' appearances using the Maxent model and environmental variables related with climate, topography, road and land use. In addition, this study evaluated the effects of the relevant climate and environmental variables. This study also analyzed inhabitation range area suitable for Asiatic black and geographic change according to future climate change. As for the judgment accuracy of the Maxent model widely utilized for habitat distribution research of wildlife for preservation, AUC value was calculated as 0.893 (sd=0.121). This was useful in predicting Asiatic black bears' potential habitat and evaluate the habitat change characteristics according to future climate change. Compare to the distribution map of Asiatic black bears evaluated by IUCN, Habitat suitability by the Maxent model were regionally diverse in extant areas and low in the extinct areas from IUCN map. This can be the result reflecting the regional difference in the environmental conditions where Asiatic black bears inhabit. As for the environment affecting the potential habitat distribution of Asiatic black bears, inhabitation rate was the highest, according to land coverage type, compared to climate, topography and artificial factors like distance from road. Especially, the area of deciduous broadleaf forest was predicted to be preferred, in comparison with other land coverage types. Annual mean precipitation and the precipitation during the driest period were projected to affect more than temperature's annual range, and the inhabitation possibility was higher, as distance was farther from road. The reason is that Asiatic black bears are conjectured to prefer more stable area without human's intervention, as well as prey resource. The inhabitation range was predicted to be expanded gradually to the southern part of India, China's southeast coast and adjacent inland area, and Vietnam, Laos and Malaysia in the eastern coastal areas of Southeast Asia. The following areas are forecast to be the core areas, where Asiatic black bears can inhabit in the Asian region: Jeonnam, Jeonbuk and Gangwon areas in South Korea, Kyushu, Chugoku, Shikoku, Chubu, Kanto and Tohoku's border area in Japan, and Jiangxi, Zhejiang and Fujian border area in China. This study is expected to be used as basic data for the preservation and efficient management of Asiatic black bear's habitat, artificially introduced individual bear's release area selection, and the management of collision zones with humans.

Influence of Land Cover Map and Its Vegetation Emission Factor on Ozone Concentration Simulation (토지피복 지도와 식생 배출계수가 오존농도 모의에 미치는 영향)

  • Kyeongsu Kim;Seung-Jae Lee
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.25 no.1
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    • pp.48-59
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    • 2023
  • Ground-level ozone affects human health and plant growth. Ozone is produced by chemical reactions between oxides of nitrogen (NOx) and volatile organic compounds (VOCs) from anthropogenic and biogenic sources. In this study, two different land cover and emission factor datasets were input to the MEGAN v2.1 emission model to examine how these parameters contribute to the biogenic emissions and ozone production. Four input sensitivity scenarios (A, B, C and D) were generated from land cover and vegetation emission factors combination. The effects of BVOCs emissions by scenario were also investigated. From air quality modeling result using CAMx, maximum 1 hour ozone concentrations were estimated 62 ppb, 60 ppb, 68 ppb, 65 ppb, 55 ppb for scenarios A, B, C, D and E, respectively. For maximum 8 hour ozone concentration, 57 ppb, 56 ppb, 63 ppb, 60 ppb, and 53 ppb were estimated by scenario. The minimum difference by land cover was up to 25 ppb and by emission factor that was up to 35 ppb. From the modeling performance evaluation using ground ozone measurement over the six regions (East Seoul, West Seoul, Incheon, Namyangju, Wonju, and Daegu), the model performed well in terms of the correlation coefficient (0.6 to 0.82). For the 4 urban regions (East Seoul, West Seoul, Incheon, and Namyangju), ozone simulations were not quite sensitive to the change of BVOC emissions. For rural regions (Wonju and Daegu) , however, BVOC emission affected ozone concentration much more than previously mentioned regions, especially in case of scenario C. This implies the importance of biogenic emissions on ozone production over the sub-urban to rural regions.

Intercomparison of Change Point Analysis Methods for Identification of Inhomogeneity in Rainfall Series and Applications (강우자료의 비동질성 규명을 위한 변동점 분석기법의 상호비교 및 적용)

  • Lee, Sangho;Kim, Sang Ug;Lee, Yeong Seob;Sung, Jang Hyun
    • Journal of Korea Water Resources Association
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    • v.47 no.8
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    • pp.671-684
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    • 2014
  • Change point analysis is a efficient tool to understand the fundamental information in hydro-meteorological data such as rainfall, discharge, temperature etc. Especially, this fundamental information to change points to future rainfall data identified by reasonable detection skills can affect the prediction of flood and drought occurrence because well detected change points provide a key to resolve the non-stationary or inhomogeneous problem by climate change. Therefore, in this study, the comparative study to assess the performance of the 3 change point detection skills, cumulative sum (CUSUM) method, Bayesian change point (BCP) method, and segmentation by dynamic programming (DP) was performed. After assessment of the performance of the proposed detection skills using the 3 types of the synthetic series, the 2 reasonable detection skills were applied to the observed and future rainfall data at the 5 rainfall gauges in South Korea. Finally, it was suggested that BCP (with 0.9 posterior probability) could be best detection skill and DP could be reasonably recommended through the comparative study. Also it was suggested that BCP (with 0.9 posterior probability) and DP detection skills to find some change points could be reasonable at the North-eastern part in South Korea. In future, the results in this study can be efficiently used to resolve the non-stationary problems in hydrological modeling considering inhomogeneity or nonstationarity.