• Journal of Korean Society on Water Environment
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• v.23 no.4
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• pp.490-497
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• 2007

A Combined sewer overflows (CSOs) are themselves a significant source of water pollution. Therefore, the control of urban drainage for CSOs reduction and receiving water quality protection is needed. Examples in combined sewer systems include downstream storage facilities that detain runoff during periods of high flow and allow the detained water to be conveyed by an interceptor sewer to a centralized treatment plant during periods of low flow. The design of such facilities as stormwater detention storage is highly dependant on the temporal variability of storage capacity available (which is influenced by the duration of interevent dry periods) as well as the infiltration capacity of soil and recovery of depression storage. As a result, a continuous approach is required to adequately size such facilities. This study for the continuous long-term analysis of urban drainage system used analytical probabilistic model based on derived probability distribution theory. As an alternative to the modeling of urban drainage system for planning or screening level analysis of runoff control alternatives, this model have evolved that offer much ease and flexibility in terms of computation while considering long-term meteorology. This study presented rainfall and runoff characteristics of the subject area using analytical probabilistic model. This study presented the average annual COSs and number of COSs when the interceptor capacity is in the range $3{\times}DWF$ (dry weather flow). Also, calculated the average annual mass of pollutant lost in CSOs using Event Mean Concentration. Finally, this study presented a decision of storage volume for CSOs reduction and water quality protection.

• Atmosphere
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• v.31 no.4
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• pp.461-472
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• 2021

Yeongdong has frequently suffered from severe snowstorms, which generally give rise to societal and economic damages to the region in winter. In order to understand its mechanism, there has been a long-term measurement campaign, based on the rawinsonde measurements for every snowfall event at Gangneung since 2014. The previous observations showed that a typical heavy snowfall is generally accompanied with northerly or northeasterly flow below the snow clouds, generated by cold air outbreak over the relatively warmer East Sea. An intensive and multi-institutional measurement campaign has been launched in 2019 mainly in collaboration with Gangwon Regional Office of Meteorology and National Institute of Meteorological Studies of Korean Meteorological Administration, with a special emphasis on winter snowfall and spring windstorm altogether. The experiment spanned largely from February to April with comprehensive measurements of frequent rawinsonde measurements at a super site (Gangneung) with continuous remote sensings of wind profiler, microwave radiometers and weather radar etc. Additional measurements were added to the campaign, such as aircraft dropsonde measurements and shipboard rawinsonde soundings. One of the fruitful outcomes is, so far, to identify a couple of cold air damming occurrences, featuring lowest temperature below 1 km, which hamper the convergence zone and snow clouds from penetrating inland, and eventually make it harder to forecast snowfall in terms of its location and timing. This kind of comprehensive observation campaign with continuous remote sensings and intensive additional measurement platforms should be conducted to understand various orographic precipitation in the complex terrain like Yeongdong.

• Korean Journal of Agricultural and Forest Meteorology
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• v.5 no.2
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• pp.70-80
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• 2003

We report the first direct measurement of $CO_2$ flux over Kwangneung broadleaf deciduous forest, one of the tower flux sites in KoFlux network. Eddy covariance system was installed on a 30 m tower along with other meteorological instruments from June to August in 2002. Although the study site was non-ideal (with valley-like terrain), turbulence characteristics from limited wind directions (i.e., 90$\pm$45$^{\circ}$) was not significantly different from those obtained at simple, homogeneous terrains with an ideal fetch. Despite very low rate of data retrieval, preliminary results from our analysis are encouraging and worthy of further investigation. Ignoring the role of advection terms, the averaged net ecosystem exchange (NEE) of $CO_2$ ranged from -1.2 to 0.7 mg m$^{-2}$ s$^{-1}$ from June to August in 2002. The effect of weak turbulence on nocturnal NEE was examined in terms of friction velocity (u*) along with the estimation of storage term. The effect of low uf u* NEE was obvious with a threshold value of about 0.2 m s$^{-1}$ . The contribution of storage term to nocturnal NEE was insignificant; suggesting that the $CO_2$ stored within the forest canopy at night was probably removed by the drainage flow along the hilly terrain. This could be also an artifact of uncertainty in calculations of storage term based on a single-level concentration. The hyperbolic light response curves explained ＞80% of variation in the observed NEE, indicating that $CO_2$ exchange at the site was notably light-dependent. Such a relationship can be used effectively in filling up the missing gaps in NEE data through the season. Finally, a simple scaling analysis based on a linear flow model suggested that advection might play a significant role in NEE evaluation at this site.

• Korean Journal of Agricultural and Forest Meteorology
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• v.10 no.3
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• pp.82-93
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• 2008

In order to ensure a standardized data analysis of the eddy covariance measurements, Hong and Kim's quality control program has been updated and used to process eddy covariance data measured at two levels on the main flux tower at Gwangneung site from January to May in 2005. The updated program was allowed to remove outliers automatically for $CO_2$ and latent heat fluxes. The flag system consists of four quality groups(G, D, B and M). During the study period, the missing data were about 25% of the total records. About 60% of the good quality data were obtained after the quality control. The number of record in G group was larger at 40m than at 20m. It is due that the level of 20m was within the roughness sublayer where the presence of the canopy influences directly on the character of the turbulence. About 60% of the bad data were due to low wind speed. Energy balance closure at this site was about 40% during the study period. Large imbalance is attributed partly to the combined effects of the neglected heat storage terms, inaccuracy of ground heat flux and advection due to local wind system near the surface. The analysis of wind direction indicates that the frequent occurrence of positive momentum flux was closely associated with mountain valley wind system at this site. The negative $CO_2$ flux at night was examined in terms of averaging time. The results show that when averaging time is larger than 10min, the magnitude of calculated $CO_2$ fluxes increases rapidly, suggesting that the 30min $CO_2$ flux is influenced severely by the mesoscale motion or nonstationarity. A proper choice of averaging time needs to be considered to get accurate turbulent fluxes during nighttime.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.2
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• pp.149-158
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• 2018

Agriculture is strongly influenced by climate change such as increased temperature and carbon dioxide ($CO_2$). This study describes the effects of climate change elevated $CO_2$, temperature, and relative drought on growth responses and yield in potato (Solanum tuberosum L.). The assessment was conducted for spring seasons in Soil-Plant-Atmosphere Research (SPAR) chamber at National Institute of Crop Science (NICS). Potatoes exhibit a positive response to $CO_2$ enrichment but water stress primarily reduces potato canopy and tuber yield. Elevated $CO_2$ and temperature increased both dry weight and tuber yield. Elevated $CO_2$ and temperature influenced SPAR 2 plants to a larger, and tuber increased yield up to 28% of than in SPAR 1(30-year average temperature at 450 ppm of $CO_2$). Our study findings indicate that tuber yield increase in potato under high $CO_2$ concentration was due to an increase in the size of individual tubers rather than in the number of the tubers per plant. On other hand, SPAR 3(30-year average temperature $+2.8^{\circ}C$ at 700 ppm of $CO_2$ under water stress) was lower than SPAR 2(30-year average temperature $+2.8^{\circ}C$ at 700 ppm of $CO_2$) nearly 56% of tuber yield due to drought. The results confirm potato drought sensitivity in terms of yield response. The experiment also showed that, in the conditions of climate change, climate change scenarios that improve cropping systems with potato.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.3
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• pp.135-142
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• 2001

This study attempts to categorizes the factors of forest fire occurrences based on regional meteorologic data and general forest no characteristics of 18 cities and guns in Kangwon province. lo accomplish this goal, some statistical analyses such as analysis of variance, correspondence analysis and multidimensional scaling were adopted. To reveal the forest fires pattern of study region, a categorization process was conducted by employing the quantification approach which modified and quantified the metric-data of fire occurrence dates. Also, The fire occurrence similarity was compared by using multidimensional scaling for each study region. The major results are summarized as follows: It was found that the meteorological factors emerged as different to each region are average and maximum temperature, minimum dew point temperature and average and maximum wind speed. In the result of correspondence analysis representing relationships between fire causes and study regions, Kangrung is caused by arsonist, Chulwon, Hwachen and Yanggu caused by military factor, Sokcho and Chunchen caused by the debris burning, and Samchuk caused by general man-caused fires, respectively. Finally, the forest fire occurrence pattern of this study regions were divided into five areas such as, group I including Samchuk, Kangryung, Chunchen, Wonju, Hongchen and Hhoingsung, group II including Donghae, Taebaek, Yangyang and Pyongchang, group III including Jungsun, Chulwon and Whachen, group Ⅵ including Gosung, Injae and Yanggu, and group V including Shokcho and Youngwol.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.1
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• pp.11-22
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• 2010

According to IPCC 4th Assessment Report, concentration of carbon dioxide has been increasing by 30% since Industrial Revolution. Most of IPCC $CO_2$ emission scenarios estimate that the concentration will reach up to double of its present level within 100-year if the current tendency continues. The global warming has resulted in the agro-climate change over the Korean Peninsula as well. Accordingly, it is necessary to understand the future agro-climate induced by the increase of greenhouse gases in terms of the agro-climatic indices in the Korean peninsula. In this study, the future climate is simulated by an atmosphere/ocean/land surface/sea ice coupled general circulation climate model, Pusan National University Coupled General Circulation Model(hereafter, PNU CGCM), and by a regional weather prediction model, Weather Research and Forecasting Model(hereafter, WRF) for the purpose of a dynamical downscaling. The changes of the vegetable period and the crop growth period, defined as the total number of days of a year exceeding daily mean temperature of 5 and 10, respectively, have been analyzed. Our results estimate that the beginning date of vegetable and crop growth periods get earlier by 3.7 and 17 days, respectively, in spring under the $CO_2$-doubled climate. In most of the Korean peninsula, the predicted frost days in spring decrease by 10 days. Climatic production index (CPI), which closely represent the productivity of rice, tends to increase in the double $CO_2$ climate. Thus, it is suggested that the future $CO_2$ doubled climate might be favorable for crops due to the decrease of frost days in spring, and increased temperature and insolation during the heading date as we expect from the increased CPI.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.183-193
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• 2020

This study was conducted to evaluate the effect of environment factors on the growth of autumn season cultivation of Kimchi cabbage using the big data in terms of public open data(weather, soil information, and growth of crop, etc.). The growth data and the environment data such as temperature, daylength, and rainfall from 2010 to 2019 were collected. As a result of composing the correlation matrix, the height and leaf number showed high correlation in growing degree days(GDDs) and daylength, and the yield showed negative correlation in growing degree days and the concentration of clay. GDDs and daylength explained about 89% and 84% of variation in height, respectively. These two environmental factors also explained about 85% and 79% of variation in leaf numbers, respectively. In contrast, the coefficient of determination was low for yield when GDDs and concentration of clay was used. The outcome of regional statistical analysis indicated that relationship between yield and sum of sand and silt were high in Haenam and Jindo areas. Hierarchical cluster analysis, which was performed to verify the association of yield, GDDs, and concentration of clay, showed that Haenam and Jindo were clustered together. Although GDDs and yield vary by year and region, and there are regions with similar concentration of clays, observation data are grouped as the result. These suggests that GDDs and soil texture are expected to be related to yield. The cluster analysis results can be used for further data analysis and agricultural policy establishment.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.327-336
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• 2019

Soybean is one of the most important crops of which the grains contain high protein content and has been consumed in various forms of food. Soybean plants are generally cultivated on the field and their yield and quality are strongly affected by climate change. Recently, the abnormal climate conditions, including heat wave and heavy rainfall, frequently occurs which would increase the risk of the farm management. The real-time assessment techniques for quality and growth of soybean would reduce the losses of the crop in terms of quantity and quality. The objective of this work was to develop a simple model to estimate the growth of soybean plant using a multispectral sensor mounted on a rotor-wing unmanned aerial vehicle(UAV). The soybean growth model was developed by using simple linear regression analysis with three phenotypic data (fresh weight, dry weight, leaf area index) and two types of vegetation indices (VIs). It was found that the accuracy and precision of LAI model using GNDVI (R²= 0.789, RMSE=0.73 ㎡/㎡, RE=34.91%) was greater than those of the model using NDVI (R²= 0.587, RMSE=1.01 ㎡/㎡, RE=48.98%). The accuracy and precision based on the simple ratio indices were better than those based on the normalized vegetation indices, such as RRVI (R²= 0.760, RMSE=0.78 ㎡/㎡, RE=37.26%) and GRVI (R²= 0.828, RMSE=0.66 ㎡/㎡, RE=31.59%). The outcome of this study could aid the production of soybeans with high and uniform quality when a variable rate fertilization system is introduced to cope with the adverse climate conditions.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.2
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• pp.86-96
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• 2006

Ecoclimap-1, a new complete surface parameter global database at a 1-km resolution, was previously presented. It is intended to be used to initialize the soil-vegetation- atmosphere transfer schemes in meteorological and climate models. Surface parameters in the Ecoclimap-1 database are provided in the form of a per-class value by an ecoclimatic base map from a simple merging of land cover and climate maps. The principal objective of this ecoclimatic map is to consider intra-class variability of life cycle that the usual land cover map cannot describe. Although the ecoclimatic map considering land cover and climate is used, the intra-class variability was still too high inside some classes. In this study, a new strategy is defined; the idea is to use the information contained in S10 NDVI SPOT/VEGETATION profiles to split a land cover into more homogeneous sub-classes. This utilizes an intra-class unsupervised sub-clustering methodology instead of simple merging. This study was performed to provide a new ecolimatic map over Northeast Asia in the framework of Ecoclimap-2 global database construction for surface parameters. We used the University of Maryland's 1km Global Land Cover Database (UMD) and a climate map to determine the initial number of clusters for intra-class sub-clustering. An unsupervised classification process using six years of NDVI profiles allows the discrimination of different behavior for each land cover class. We checked the spatial coherence of the classes and, if necessary, carried out an aggregation step of the clusters having a similar NDVI time series profile. From the mapping system, 29 ecosystems resulted for the study area. In terms of climate-related studies, this new ecosystem map may be useful as a base map to construct an Ecoclimap-2 database and to improve the surface climatology quality in the climate model.