• Ocean and Polar Research
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• v.23 no.1
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• pp.51-62
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• 2001

The Arctic consists of numerous sedimentary basins containing voluminous natural resources and two of the world's major oil and gas producing areas. The western Siberia Basin in the Arctic region has the largest petroliferous province with an area of 800 ${\times}$ 1,200 km and produces more than 60% of total Russian oil production. The North Slope of Alaska produces about 20% of the U.S. output, i.e., 11% of the total U.S. consumption. Being small compared to those regions, the Canadian Northwest Territories and the Pechora Basin in Russia produce only fair amount of oil and natural gas. There are also many promising areas in the northern continental shelf of Russia. In addition to Russia, Svalbard and Greenland have been investigated for oil and gas. Gas hydrates are widespread in both permafrost regions and arctic continental shelf areas. The reserves of gas hydrates in the Arctic Ocean are about 20${\sim}$32% of total estimated amounts of gas hydrates in the world ocean. Mineral mining is well developed, especially in Russia. The major centers are located around the Kuznetsk Basin and Noril'sk. They are major suppliers of gold, tin, nickel, copper, platinum, cobalt, iron ore, coal as well as apatite. There are also some minings of lead-zinc in Alaska and Arctic Canada.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.3
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• pp.164-169
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• 2004

A spatial interpolation scheme incorporating local geographic potential for cold air accumulation (TOPSIM) was used to test the feasibility of operational frost warning in Chatancheon basin in Yeoncheon County, where the introduction of new crops including temperate zone fruits is planned. Air temperature from April to June 2003 was measured at one-minute intervals at four locations within the basin. Cold-air accumulation potentials (CAP) at 4 sites were calculated for 3 different catchment scales: a rectangular area of 65 x 55 km which covers the whole county, the KOWACO (Korea Water Corporation) hydrologic unit which includes all 4 sites, and the sub-basins delineated by a stream network analysis of the digital elevation model. Daily minimum temperatures at 4 sites were calculated by interpolating the perfect prognosis (i.e., synoptic observations at KMA Dongducheon station) based on TOPSIM with 3 different CAPs. Mean error, mean absolute error, and root mean square error were calculated for 45 days with no precipitation to test the model performance. For the 3 flat locations, little difference was detected in model performance among 3 catchment areas, but the best performance was found with the CAPs calculated for sub-basins at one site (Oksan) on complex terrain. When TOPSIM loaded with sub-basin CAPs was applied to Oksan to predict frost events during the fruit flowering period in 2004, the goodness of fit was sufficient for making an operational frost warning system for mountainous areas.

• Proceedings of the Korean Geotechical Society Conference
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• 2002.03a
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• pp.111-118
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• 2002

Recent study of soft clay of Nakdong-River basin has been taken correlation between soil properties by regression analysis without distribution whether the sample is disturbed or not, or treated as a whole area without proposing local correlation equation to Jang-U or Dae-Joe which has a specific locality. Accordingly, Those tendency cause the reliability of correlation between compression index and void ratio low and then design underestimate and uncertain eventually. In this study, Distributing the soft clay of Nakdong-River basin with failure strain of 6%, the suggestion by Skempton(1957), TakeNaka(1966)-the more sample is undisturbed, the more the ratio of E$\_$50/ and ｑ$\_$u/, ${\alpha}$ = E$\_$50//(q$\_$u//2) = 1/$\varepsilon$$\_$50/ is high-is satisfied with the value of which ${\alpha}$ is 50 and It could be taken enough data in the condition of domestic. Besides other indices also make the distribution suitable. In conclusion, This study is supposed to propose the locally subdivided regression equation between compression index and void ratio considering the sample disturbance.

• Geosciences Journal
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• v.22 no.6
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• pp.1027-1039
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• 2018

Seismic attributes are often used to identify lithology and evaluate reservoir properties. However, interpretation based only on structural attributes and without knowledge of the Vp/Vs ratio can limit the ability to evaluate changes in heavy oil reservoirs. These limitations are often due to less obvious impedance differences. In order to investigate pieces of evidence of a heavy-oil shaly-sand reservoir from seismic data, besides geochemistry, we studied seismic attributes and characterized the reservoir using seismic stack data and well logging data. The study area was the Muglad rift basin in South Sudan. We conducted a seismic complex analysis to evaluate the target reservoir. To delineate the frequency responses of the different lithological units, we applied the spectral decomposition method to the target reservoir. The most unexpected result was continuous bands of strong seismic reflectors in the target reservoir, which extended across the borehole. Spectral decomposition analysis showed that the low-frequency zone of 25 Hz dominant frequency was consistent with instantaneous attributes. This approach can identify lithology, reveal frequency anomalies, and filter the stacked section into low- and high-frequency bands. The heavy-oil reservoir zones exhibited velocity attenuation and the amplitude was strongly frequency dependent.

• Journal of The Geomorphological Association of Korea
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• v.23 no.3
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• pp.13-25
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• 2016

The purpose of this study is to investigate the location characteristics in which 'large Jar coffin' (hereinafter referred to as 'Jar coffin') distributed in the Yeongsan river basin area in Jeonnam province by means of topographic analysis. 75 Jar coffins (74.3%) in 19 relics (90.5% of total) were found in hill and 26 Jar coffins (25.7%) of two consumption relics (9.5%) were found in floodplain. Among them, 34 (45.3% of total) and 41 (54.7% of total) Jar coffins were found in the Crest surface and Sideslope of hills, respectively. In particular, 26 (34.7%) Jar coffins are mostly located in the Crest flat. This result implies that people at that might be consider the river inundation, and mostly choose hill rather than floodplain when building the Jar coffin. therefore amongtherefore among micro-landform units of the hill, it seems that the 'Crest flat' was the preferred place for the building the Jar coffin at that time.

• Journal of the Korean GEO-environmental Society
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• v.20 no.12
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• pp.33-39
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• 2019

The upsurge of population, internal migration, economic activities and developmental works has brought significant land use and land cover (LULC) change over the period of 1990 and 2010 in the Bagmati basin of Nepal. Along with alteration on various other ecosystem services like water yield, water quality, soil loss etc. carbon sequestration is also altered. This study thus primary deals with evaluation of LULC change and its impact on the soil carbon storage for the period 1990 to 2010. For the evaluation, InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) Carbon model is used. Residential and several other infrastructural development activities were prevalent on the study period and as a result in 2010 major soil carbon reserve like forest area is decreased by 7.17% of its original coverage in 1990. This decrement has brought about a subsequent decrement of 1.39 million tons of carbon in the basin. Conversion from barren land, water bodies and built up areas to higher carbon reserve like forest and agriculture land has slightly increased soil carbon storage but still, net reduction is higher. Thus, the spatial output of the model in the form of maps is expected to help in decision making for future land use planning and for restoration policies.

• Advances in environmental research
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• v.10 no.1
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• pp.43-57
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• 2021

Evaluation of groundwater quality is vital due to its diverse use for several purposes. In the present study, groundwater quality and suitability from the Peshawar basin, Pakistan, were evaluated for drinking and irrigation purposes. The water samples were analysed for major cations (Ca, Mg, Na and K) and anions (chloride, bicarbonate and sulphate) along with other physicochemical parameters (pH, electrical conductivity, total dissolved solids, and total hardness). About 95% of the water samples were found to be within the WHO, US-EPA and Pak-EPA permissible levels for drinking purposes. Seventy percent (70%) of the water samples belonged to the hard water category. Irrigation water quality parameters, such as, chloride, residual sodium bicarbonate, sodium adsorption ratio, percent sodium, magnesium adsorption ratio, Kelly's ration and permeability index were evaluated which demonstrated that the groundwater was highly to moderately suitable for irrigation. A correlation study was conducted to find out the mutual associations among the variables. Piper diagram indicated the overall chemical nature of the study area was calcium-magnesium bicarbonate type. Cluster analysis revealed mutual apportionment of various parameters in the groundwater of the Peshawar basin, Pakistan.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.96-96
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• 2020

In order to establish the risk criteria of inundation due to typhoons or heavy rainfall, research is underway to predict the limit rainfall using basin characteristics, limit rainfall and artificial intelligence algorithms. In order to improve the model performance in estimating the limit rainfall, the learning data are used after the pre-processing. When 50.0% of the entire data was removed as an outlier in the pre-processing process, it was confirmed that the accuracy is over 90%. However, the use rate of learning data is very low, so there is a limitation that various characteristics cannot be considered. Accordingly, in order to predict the limit rainfall reflecting various watershed characteristics by increasing the use rate of learning data, the watersheds with similar characteristics were clustered. The algorithms used for clustering are K-Means, Agglomerative, DBSCAN and Spectral Clustering. The k-Means, DBSCAN and Agglomerative clustering algorithms are clustered at the impervious area ratio, and the Spectral clustering algorithm is clustered in various forms depending on the parameters. If the results of the clustering algorithm are applied to the limit rainfall prediction algorithm, various watershed characteristics will be considered, and at the same time, the performance of predicting the limit rainfall will be improved.

• Journal of The Geomorphological Association of Korea
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• v.27 no.3
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• pp.1-11
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• 2020

A CIA analysis (A-CN-K and A-CNK-FM ternary diagram) indicates that, unlike the general granitic hills of the Korean Peninsula, the chemical weathering of the granitic grus (sandy regolith) in the eastern Jincheon basin is variable in geomorphic site except the Chuncheon basin. In the study area, there are three types of hills, such as; inner hills, linear isolated hills, and outer hills. The weathered mantles of the outer hills and linear isolated hills are weakly altered, whereas the inner hill, the Bonghyeon profile, shows a stronger chemical loss of the compositions approximating saprolite. There are small differences between the outer hills and linear isolated hills. The Geumwang site is considered fresh rock due to a low lever of alteration, although its sampling profile shows sandy weathering mantles. In the profiles of the Masan and Mugeuks sites, the lower part of weathering mantles has not experienced a significant level of component loss, but the upper regoliths have substantially been modified. The alteration of the hills occurs by chemical loss of CaO and Na₂O. K₂O exhibited little variation at all sampling suites and it has not changed into saprolite.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.4
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• pp.51-57
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• 2024

This study was conducted on how to simulate runoff, which was done using existing physical models, using an LSTM (Long Short-Term Memory) model based on deep learning. Tancheon, the first tributary of the Han River, was selected as the target area for the model application. To apply the model, one water level observatory and four rainfall observatories were selected, and hourly data from 2020 to 2023 were collected to apply the model. River water level of the outlet of the Tancheon basin was simulated by inputting precipitation data from four rainfall observation stations in the basin and average preceding 72-hour precipitation data for each hour. As a result of water level simulation using 2021 to 2023 data for learning and testing with 2020 data, it was confirmed that reliable simulation results were produced through appropriate learning steps, reaching a certain mean absolute error in a short period time. Despite the short data period, it was found that the mean absolute percentage error was 0.5544~0.6226%, showing an accuracy of over 99.4%. As a result of comparing the simulated and observed values of the rapidly changing river water level during a specific heavy rain period, the coefficient of determination was found to be 0.9754 and 0.9884. It was determined that the performance of LSTM, which aims to simulate river water levels, could be improved by including preceding precipitation in the input data and using precipitation data from various rainfall observation stations within the basin.