• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1107-1118
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• 2021

Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.41 no.1
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• pp.35-46
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• 2023

This study investigated and analyzed ancient records on the type, planting background, and construction process of Gwanbang forest(關防林) planned for military defense during the Joseon Dynasty to find out the purpose, location, and planting species of Gwanbang forest. The research results were as follows. During the Joseon Dynasty, Gwanbang forests were created around various government facilities(關防施設), such as Eupseong(邑城), major government offices, camps, and fortifications, for the purpose of defending against enemies. Gwanbang forest includes Yeongaeglim(嶺阨林), which was created on the crest of a strategically important hill, and Military Forest created for military purposes. Most of the spirit forest was designated as Geumsan(禁山) and protected and managed, and the Gwanbang forest was created for various purposes such as shielding, flood damage and river bank erosion prevention as well as external defense. In addition, in order to continuously and efficiently produce wood, which is a material for ships, buildings, and agricultural tools, in most cases, large areas were created as mixed forests. As for the species constituting the Gwanbang forest, there are records of tangerine tree, which is effective for defense because it has thorns, and deciduous broad-leaved trees such as zelkova, elm, willow, david hemiptelea, and oak appear. In the case of Ganghwa island, which served as the defense of the capital and the royal family during the Joseon Dynasty, several records have confirmed that a forest densely planted with trifoliate orange was created for the purpose of Gwanbang forest to reinforce the defense of the outer fortress. Based on historical research in the literature, assuming that the natural monument 'Gapgotri tangerine tree in Ganghwa Island' was planted in the 30th year of King Sukjong(1704), the first record of planting trifoliate orange in Ganghwa Island, the maximum age is estimated to be more than 319 years.

• Korean Journal of Mineralogy and Petrology
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• v.36 no.2
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• pp.135-145
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• 2023

Aggregate is used to produce stable materials like concrete and asphalt and is fundamental to meet the social needs of housing, industry, road, energy and health. A total of 42.35 billion tons of aggregate were produced in 2021 worldwide, an increase of 0.91% compared to the previous year. Among them, 2 billion tons were produced in China, India, European Union and United States, making up to 71.75% of the share. South Korea has witnessed a constant increase in aggregate production, overtaking Mexico and Japan for seventh place with 390 million tons and 0.85% of the share. The industrial sand and gravel produced globally amounted to 352.66 million tons. The top seven countries with the highest production were China, United States, Netherlands, Italy, India, Turkey and France, and their production exceeded 10 million tons and held a share of 74.69%. Exports of natural rock recorded $21.68 billion in 2021, increased by $2.3 billion compared to the previous year, while exports of artificial rock increased by $2.66 billion to $13.59 billion. Exports of sand reached $1.71 billion with United States, Netherlands, Germany and Belgium being the four countries with the highest exports of sand. The four countries exported more than $100 million in sand and took up 57.70% of the total amount. Exports of gravel totaled $2.75 billion, with China, Norway, Germany, Belgium, France and Austria in the lead, making up to 48.30% of the total share. The aggregate quarry started to surge in the 1950s due to the change in people's lifestyle such as population growth, urbanization and infrastructure delvelopment. Demand for aggregate is also skyrocketing to prevent land reclamation and flood caused by sea-level rise. Demand for aggregate, which was around 24 gigatons in 2011, is expected to double to 55 gigatons in 2060. However, it is likely that aggregate extraction will heavily damage the ecosystem and the world will eventually face a shortage of aggregate followed by tense social conflict.