• Magazine of the Korean Society of Agricultural Engineers
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• v.22 no.3
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• pp.75-87
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• 1980

Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.

• Korean Journal of Ecology and Environment
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• v.44 no.2
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• pp.195-202
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• 2011

This study analyzed and modeled the relationships between the probabilities of two exotic species occurrence (i.e. largemouth bass and blue gill) and environmental factors such as climatic and geographical variables using Generalized Additive Models (GAM), Generalized Liner Models and Classification Tree Analysis (CTA). The most moderate occurrence probability of largemouth bass was predicted using GAM with an area under the curve (ADC) of 0.88 and Kappa of 0.42, while those of blue gill was suggested by using CTA with an AUC of 0.92 and Kappa of 0.44. The most significant environmental variable in terms of changes in deviance for both species was the annual air temperature for the occurrence probability. Dams had stronger effect on the occurrence of largemouth bass than blue gill. Model development and prediction for the occurrence probability of fish species and richness are necessary to prevent further spread of exotic fishes such as largemouth bass and blue gill because they can threaten habitats of native river ecosystem through various mechanisms.

• Journal of Life Science
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• v.21 no.7
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• pp.1060-1066
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• 2011

In order to investigate the variations on the ratio of mannose to galactose in the seeds of Phaseolus angularis, 17 local strains (Yangyang, Pyeongchang, Ganghwa, Pocheon, Geumsan, Seocheon, Jincheon, Danyang, Tongyeong, Sancheong, Gumneung, Wolseong, Wando, Gokseong, Okgu, Jangsu, Bukjeju), which are located from $33^{\circ}15'N$ to $38^{\circ}11'N$, were selected according to their latitudes and geographical distances. The seeds of these strains were collected and their contents of mannose and galactose were analyzed. Mannose contents in the seeds were variable, ranging from 17.071 mg/g at its highest (Jangsu) and 6.488 mg/g at its lowest (Geumsan). The contents of galactose also showed remarkable differences, ranging from 9.477 mg/g (Wolseong) to 19.877 mg/g (Jangsu). The local strains were classified into 3 variation types - coastal type I (Wando, Okgu, Bukjeju), the inland type (Jangsu, Weolseong, Danyang, Geumneung, Pyeongchang, Sancheong) and coastal type II (Ganghwa, Seocheon, Tongyeong, Jincheon), as well as 4 strange strains (Gokseong, Yangyang, Pocheon, Geumsan) according to the geographical climatic type and the ratio of mannose to galactose, which indicate the hardness of seeds in Leguminosae and ranged from 0.64 to 1.22. The variation types are very significant genecologically as evidence for microevolution related to natural and artificial selection in cultivated plants.

• Korean Journal of Environment and Ecology
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• v.25 no.3
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• pp.295-301
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• 2011

In order to investigate the geographical variation of Glycine max distributed in southern area of Korean peninsula, 19 local strains(Goseng, Pyeongchang, Ganghwa, Pocheon, Geumsan, Seocheon, Jincheon, Danyang, Tongyeong, Sancheong, Gumneung, Wolseong, Woolneung, Wando, Naju, Gochang, Jangsu, Jeju, Bukjeju), which located from $33^{\circ}15'N$ to $38^{\circ}11'N$, were selected according to their latitudes and geographical distances. The seeds of these strains were collected and their contents of mannose and galactose were investigated. Mannose contents in the seeds were variable in the range between the highest 12.207mg/g(Gochang) and the lowest 6.648mg/g(Geumsan). The contents of galactose were represented remarkable differences from 9.967mg/g(Danyang) to 16.949mg/g(Bukjeju) also. The local strains were classified into 4 variation types such as the inland type I(Wolseong, Jangsu, Danyang), the coastal type I(Gochang, Naju, Jeju, Goseng, Woolneung, Bukjeju, Ganghwa, Seocheon, Tongyeong), the inland type II(Geumsan, Pocheon, Pyeongchang) and the coastal type II(Wando, Jincheon) and 2 strange strains(Gumneung, Sancheong) according to the geographical climatic type and the ratio of mannose/galactose, which indicate the hardness of seeds in Leguminosae, ranged from 0.63 to 0.78. The variation types are very significant genecologically as an evidence for microevolution related to speciation in cultivated plants.

• Korean Journal of Ecology and Environment
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• v.54 no.4
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• pp.363-373
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• 2021

An ecological niche is defined as the specific role of a species influenced by time, space, and other resources. By investigating overlaps between ecological niches of different species, we could estimate the degrees of interspecific competition. Such studies often use geographic information systems (GIS) to discover niche overlaps between species. In this study, we used GIS to estimate the spatial niches of two Korean frog species(Pelophylax nigromaculatus and P. chosenicus). This enabled us to predict their geographic distributions in order to identify their coexistence regions and distribution patterns. The results confirmed that altitude was an important variable for predicting their distribution, with a correlation with their climatic range. Spatial distributions of the two frog species were highly overlapped, as the distribution range for P. nigromaculatus included most of the range of P. chosenicus, showing a sympatric distribution pattern. Within the coexisting regions, however, the presence sites for the two species did not overlap, implying weak competition. To confirm the principal factors influencing their competitive relationship and reasons for their sympatric distribution pattern, we need more detailed in-depth studies on the diverse environmental variables within the regions where the two species coexist. By doing so, we would be able to identify various mechanisms for avoiding competition in sympatric frog species.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.3
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• pp.155-163
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• 2022

The optimization of long-range ensemble climate prediction for rice phenology model with advanced bias correction method is conducted. The daily long-range forecast(6-month) of mean/ minimum/maximum temperature and observation of January to October during 1991-2021 is collected for rice phenology prediction. In this study, the concept of "buffer period" is newly introduced to reduce the problem after bias correction by quantile mapping with constructing the transfer function by month, which evokes the discontinuity at the borders of each month. The four experiments with different lengths of buffer periods(5, 10, 15, 20 days) are implemented, and the best combinations of buffer periods are selected per month and variable. As a result, it is found that root mean square error(RMSE) of temperatures decreases in the range of 4.51 to 15.37%. Furthermore, this improvement of climatic variables quality is linked to the performance of the rice phenology model, thereby reducing RMSE in every rice phenology step at more than 75~100% of Automated Synoptic Observing System stations. Our results indicate the possibility and added values of interdisciplinary study between atmospheric and agriculture sciences.

• Journal of Ecology and Environment
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• v.46 no.4
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• pp.316-323
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• 2022

Background: We developed a habitat suitability index (HSI) model for Pedicularis hallaisanensis, a Grade II Endangered Species in South Korea. To determine the habitat variables, we conducted a literature review on P. hallaisanensis with a specific focus on the associated spatial factors, climate, topography, threats, and soil factors to derive five environmental factors that influence P. hallaisanensis habitats. The specific variables were defined based on the collected data and consultations with experts in the field, with the validity of each variable tested through field studies. Results: Mt. Seorak had a suitable habitat area of 2.48 km² for sites with a score of 1 (0.62% of total area) and 0.01 km² for sites with a score of 0.9. Mt. Bangtae had a suitable habitat area of 0.03 km² for sites with a score of 1 (0.02% of total area) and 0 km² for sites with a score of 0.9. Mt. Gaya showed 0.13 km² of suitable habitat for sites with a score of 1 (0.17% of total area) and 0 km² for sites with a score of 0.9. Lastly, Mt. Halla showed 3.12 km² of suitable habitat related to sites with a score of 1 (2.04% of total area) and 4.08 km² of sites with a score of 0.9 (2.66% of total area). Mt. Halla accounts for 73.1% of the total core habitat area. Considering the climatic, soil, and forest conditions together with standardized collection sites, our results indicate that Mt. Halla should be viewed as a core habitat of P. hallaisanensis. Conclusions: The findings in this study provide useful data for the identification of core habitat areas and potential alternative habitats to prevent the extinction of the endangered species, P. hallaisanensis. Furthermore, the developed HSI model allows for the prediction of suitable habitats based on the ecological niche of a given species to identify its unique distribution and causal factors.

• Korean Journal of Breeding Science
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• v.43 no.1
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• pp.68-80
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• 2011

This study was conducted to investigate characteristics and variations of rice panicle traits for breeding temperate japonica varieties adapted to tropical environment. Eleven panicle traits were investigated from nine Korean rice varieties cultivated in Korea and wet season of the Philippines. Tested cultivars were composed of six temperate japonica varieties, three Tongil-type varieties, and one indica variety bred in the Philippines. The number of spikelets on secondary rachis branches (SRBs) was the most variable trait in both environments, while the mean number of spikelets on a primary rachis branch (PRB) was the least variable. Compared with PRB-related traits, SRB traits showed higher correlation with the number of spikelets per panicle. Compared with the plants grown in Korea, the number of spikelets on SRBs, the number of SRBs, spikelets, and rachis branches per panicle were decreased more than other traits in the Philippines. According to path analysis, the number of spikelets on SRBs per panicle affects the number of spikelets per panicle more than the number of spikelets on PRBs per panicle. Climatic factors such as growth duration, cumulative mean temperature, and integrated solar radiation were highly correlated with the relative rate of number of spikelets per panicle. To breed temperate japonica rice varieties adapted to tropical environment, it would be important to select lines which maintain proper growth duration and spikelets on SRBs in target region.

• Journal of Bio-Environment Control
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• v.21 no.3
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• pp.243-246
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• 2012

The study was aimed at the development of the simple linear regression model to estimate the fruit yield of sweet pepper and to support decision-making management for growing sweet pepper crop in Korea. For quantitative analysis of relationship between environmental data and periodical yield of sweet pepper the data obtained from the commercial Venlo-type glasshouse for 2 years. Obtained periodical yield data of five different cultivars and radiation data were accumulated and fitted by linear regression. A significant linear relationship was found between radiation integral and fruit yield, whereas the production per unit of radiation was different between cultivars. The slope of linear regression could indicate as light use efficiency for fruit production ($LUE_F$, $g{\cdot}MJ^{-1}$). $LUE_F$ of 'Ferrari' was $5.85g{\cdot}MJ^{-1}$, 'Fiesta' 5.32 for first year and $4.75g{\cdot}MJ^{-1}$ and for second year, 'President' was $4.66g{\cdot}MJ^{-1}$, 'Cupra' was $3.86g{\cdot}MJ^{-1}$, and 'Boogie' was $6.48g{\cdot}MJ^{-1}$. The amount of light requirement for the unit gram of fruit was between $25.88J{\cdot}g^{-1}$, for 'Cupra' and $15.42J{\cdot}g^{-1}$ for 'Boogie'. Although we found the linear relationship between radiation and fruit yield, $LUE_F$ was varied between cultivars and as well as year. The linear relationship could describe the fruit yield as function of radiation, but it needed more variable to generalization of the production, such as cultivar specifications, temperature, and number of fruits set per plant or unit of ground.

• Journal of Wetlands Research
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• v.16 no.4
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• pp.303-318
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• 2014

Baseflow gives a significant contribution to stream function in the regions where climatic characteristics are seasonally distinct. In this regard, variable baseflow can make it difficult to maintain a stable water supply, as well as causing disruption to the stream ecosystem. Changes in land use can affect both the direct flow and baseflow of a stream, and consequently, most other components of the hydrologic cycle. Baseflow estimation depends on the observed streamflow in gauge watersheds, but accurate predictions of streamflow through modeling can be useful in determining baseflow data for ungauged watersheds. Accordingly, the objectives of this study are to 1) improve predictions of SWAT by applying the alpha factor estimated using RECESS for calibration; 2) estimate baseflow in an ungauged watershed using the WHAT system; and 3) evaluate the effects of changes in land use on baseflow characteristics. These objectives were implemented in the Gapcheon watershed, as an ungauged watershed in South Korea. The results show that the alpha factor estimated using RECESS in SWAT calibration improves the prediction for streamflow, and, in particular, recessions in the baseflow. Also, the changes in land use in the Gapcheon watershed leads to no significant difference in annual baseflow between comparable periods, regardless of precipitation, but does lead to differences in the seasonal characteristics observed for the temporal distribution of baseflow. Therefore, the Guem River, into which the stream from the Gapcheon watershed flows, requires strategic seasonal variability predictions of baseflow due to changes in land use within the region.