• Journal of Korea Water Resources Association
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• v.52 no.11
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• pp.917-929
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• 2019

Denitrification in streams is of great importance because it is essential for amelioration of water quality and accurate estimation of $N_2O$ budgets. Denitrification is a major biological source or sink of $N_2O$, an important greenhouse gas, which is a multi-step respiratory process that converts nitrate ($NO_3{^-}$) to gaseous forms of nitrogen ($N_2$ or $N_2O$). In aquatic ecosystems, the complex interactions of water flooding condition, substrate supply, hydrodynamic and biogeochemical properties modulate the extent of multi-step reactions required for $N_2O$ flux. Although water flow in streambed and residence time affect reaction output, effects of a complex interaction of hydrodynamic, geomorphology and biogeochemical controls on the magnitude of denitrification in streams are still illusive. In this work, we built a two-dimensional water flow channel and measured $N_2O$ flux from channel sediment with different bed geomorphology by using static closed chambers. Two independent experiments were conducted with identical flume and geomorphology but sediment with differences in dissolved organic carbon (DOC). The experiment flume was a circulation channel through which the effluent flows back, and the size of it was $37m{\times}1.2m{\times}1m$. Five days before the experiment began, urea fertilizer (46% N) was added to sediment with the rate of $0.5kg\;N/m^2$. A sand dune (1 m length and 0.15 m height) was made at the middle of channel to simulate variations in microtopography. In high- DOC experiment, $N_2O$ flux increases in the direction of flow, while the highest flux ($14.6{\pm}8.40{\mu}g\;N_2O-N/m^2\;hr$) was measured in the slope on the back side of the sand dune. followed by decreases afterward. In contrast, low DOC sediment did not show the geomorphological variations. We found that even though topographic variation influenced $N_2O$ flux and chemical properties, this effect is highly constrained by carbon availability.

• Journal of agriculture & life science
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• v.50 no.1
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• pp.167-178
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• 2016

This study was conducted to estimate genetic parameters for milk production and linear type traits in Holstein dairy cattle in Korea. The data including milk yields, fat yields, protein yields, fat percent, protein percent, somatic score and 15 linear type traits for 10,218 first parity cows collected by Dairy Cattle Improvement Center, National Agricultural Cooperative, Korea, which were calving from January 2009 to April 2013. Genetic and error (co)variances between two traits selected form 19 traits were estimated using bi-trait pairwise analyses with WOMBAT package. The estimated heritabilities for milk yield(MY), fat yield(FY), protein yield(PY), fat percent(FP), protein percent(PP), somatic cell score(SCS), udder depth(UD), udder texture(UT), median suspensory(MS), fore udder attachment(FUA), front teat placement (FTP), rear attachment height(RAH), rear attachment width(RAW), rear teat placement(RTP), front teat length(FTL), foot angle(FA), heel depth(HD), bone quality(BQ), rear legs side view(RLSV), rear legs rear view(RLRV) and locomotion(LC) were 0.128, 0.144, 0.100, 0.273, 0.333, 0.090, 0.179, 0.066, 0.104, 0.109, 0.127, 0.099, 0.059, 0.069, 0.154, 0.014, 0.010, 0.052, 0.065, 0.175 and 0.031, respectively. Among the genetic correlations, UD, UT, FTP, RAW, FTL, FA and RLSV with MY were -0.334, 0.271, 0.445, 0.544, 0.076, -0.281 and -0.228, respectively, and MS, FTP, RTP, FTL, FA, BQ, RLSV, RLRV and LC with PP were -0.147, -0.182, -0.262, -0.136, 0.355, 0.311, 0.135, 0.233 and 0.143, respectively. Especially, MY had the highest positive genetic correlation with RAW (0.544), while SCS had the highest negative genetic correlation with LC (-0.603). FP had negative genetic correlation with most udder traits, whereas, FP had positive genetic correlation with leg and hoof traits (0.056 - 0.355).

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.2
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• pp.89-102
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• 2024

Land Surface Phenology (LSP) plays a crucial role in understanding vegetation dynamics. The near-infrared reflectance of vegetation (NIRv) has been increasingly adopted in LSP studies, being recognized as a robust proxy for gross primary production (GPP). However, NIR v is sensitive to the terrain effects in mountainous areas due to artifacts in NIR reflectance cannot be canceled out. Because of this, estimating phenological metrics in mountainous regions have a substantial uncertainty, especially in the end of season (EOS). The topographically corrected NIRv (TCNIRv) employs the path length correction (PLC) method, which was deduced from the simplification of the radiative transfer equation, to alleviate limitations related to the terrain effects. TCNIRv has been demonstrated to estimate phenology metrics more accurately than NIRv, especially exhibiting improved estimation of EOS. As the topographic effect is significantly influenced by terrain properties such as slope and aspect, our study compared phenology metrics estimations between south-facing slopes (SFS) and north-facing slopes (NFS) using NIRv and TCNIRv in two distinct mountainous regions: Gwangneung Forest (GF) and Odaesan National Park (ONP), representing relatively flat and rugged areas, respectively. The results indicated that TCNIR v-derived EOS at NFS occurred later than that at SFS for both study sites (GF : DOY 266.8/268.3 at SFS/NFS; ONP : DOY 262.0/264.8 at SFS/NFS), in contrast to the results obtained with NIRv (GF : DOY 270.3/265.5 at SFS/NFS; ONP : DOY 265.0/261.8 at SFS/NFS). Additionally, the gap between SFS and NFS diminished after topographic correction (GF : DOY 270.3/265.5 at SFS/NFS; ONP : DOY 265.0/261.8 at SFS/NFS). We conclude that TCNIRv exhibits discrepancy with NIR v in EOS detection considering slope orientation. Our findings underscore the necessity of topographic correction in estimating photosynthetic phenology, considering slope orientation, especially in diverse terrain conditions.

• Proceedings of the KOR-KST Conference
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• 1995.02a
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• pp.101-113
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• 1995

The objective of this research is to test the feasibility of developing a statewide truck traffic forecasting methodology for Wisconsin by using Origin-Destination surveys, traffic counts, classification counts, and other data that are routinely collected by the Wisconsin Department of Transportation (WisDOT). Development of a feasible model will permit estimation of future truck traffic for every major link in the network. This will provide the basis for improved estimation of future pavement deterioration. Pavement damage rises exponentially as axle weight increases, and trucks are responsible for most of the traffic-induced damage to pavement. Consequently, forecasts of truck traffic are critical to pavement management systems. The pavement Management Decision Supporting System (PMDSS) prepared by WisDOT in May 1990 combines pavement inventory and performance data with a knowledge base consisting of rules for evaluation, problem identification and rehabilitation recommendation. Without a r.easonable truck traffic forecasting methodology, PMDSS is not able to project pavement performance trends in order to make assessment and recommendations in the future years. However, none of WisDOT's existing forecasting methodologies has been designed specifically for predicting truck movements on a statewide highway network. For this research, the Origin-Destination survey data avaiiable from WisDOT, including two stateline areas, one county, and five cities, are analyzed and the zone-to'||'&'||'not;zone truck trip tables are developed. The resulting Origin-Destination Trip Length Frequency (00 TLF) distributions by trip type are applied to the Gravity Model (GM) for comparison with comparable TLFs from the GM. The gravity model is calibrated to obtain friction factor curves for the three trip types, Internal-Internal (I-I), Internal-External (I-E), and External-External (E-E). ~oth "macro-scale" calibration and "micro-scale" calibration are performed. The comparison of the statewide GM TLF with the 00 TLF for the macro-scale calibration does not provide suitable results because the available 00 survey data do not represent an unbiased sample of statewide truck trips. For the "micro-scale" calibration, "partial" GM trip tables that correspond to the 00 survey trip tables are extracted from the full statewide GM trip table. These "partial" GM trip tables are then merged and a partial GM TLF is created. The GM friction factor curves are adjusted until the partial GM TLF matches the 00 TLF. Three friction factor curves, one for each trip type, resulting from the micro-scale calibration produce a reasonable GM truck trip model. A key methodological issue for GM. calibration involves the use of multiple friction factor curves versus a single friction factor curve for each trip type in order to estimate truck trips with reasonable accuracy. A single friction factor curve for each of the three trip types was found to reproduce the 00 TLFs from the calibration data base. Given the very limited trip generation data available for this research, additional refinement of the gravity model using multiple mction factor curves for each trip type was not warranted. In the traditional urban transportation planning studies, the zonal trip productions and attractions and region-wide OD TLFs are available. However, for this research, the information available for the development .of the GM model is limited to Ground Counts (GC) and a limited set ofOD TLFs. The GM is calibrated using the limited OD data, but the OD data are not adequate to obtain good estimates of truck trip productions and attractions .. Consequently, zonal productions and attractions are estimated using zonal population as a first approximation. Then, Selected Link based (SELINK) analyses are used to adjust the productions and attractions and possibly recalibrate the GM. The SELINK adjustment process involves identifying the origins and destinations of all truck trips that are assigned to a specified "selected link" as the result of a standard traffic assignment. A link adjustment factor is computed as the ratio of the actual volume for the link (ground count) to the total assigned volume. This link adjustment factor is then applied to all of the origin and destination zones of the trips using that "selected link". Selected link based analyses are conducted by using both 16 selected links and 32 selected links. The result of SELINK analysis by u~ing 32 selected links provides the least %RMSE in the screenline volume analysis. In addition, the stability of the GM truck estimating model is preserved by using 32 selected links with three SELINK adjustments, that is, the GM remains calibrated despite substantial changes in the input productions and attractions. The coverage of zones provided by 32 selected links is satisfactory. Increasing the number of repetitions beyond four is not reasonable because the stability of GM model in reproducing the OD TLF reaches its limits. The total volume of truck traffic captured by 32 selected links is 107% of total trip productions. But more importantly, ~ELINK adjustment factors for all of the zones can be computed. Evaluation of the travel demand model resulting from the SELINK adjustments is conducted by using screenline volume analysis, functional class and route specific volume analysis, area specific volume analysis, production and attraction analysis, and Vehicle Miles of Travel (VMT) analysis. Screenline volume analysis by using four screenlines with 28 check points are used for evaluation of the adequacy of the overall model. The total trucks crossing the screenlines are compared to the ground count totals. L V/GC ratios of 0.958 by using 32 selected links and 1.001 by using 16 selected links are obtained. The %RM:SE for the four screenlines is inversely proportional to the average ground count totals by screenline .. The magnitude of %RM:SE for the four screenlines resulting from the fourth and last GM run by using 32 and 16 selected links is 22% and 31 % respectively. These results are similar to the overall %RMSE achieved for the 32 and 16 selected links themselves of 19% and 33% respectively. This implies that the SELINICanalysis results are reasonable for all sections of the state.Functional class and route specific volume analysis is possible by using the available 154 classification count check points. The truck traffic crossing the Interstate highways (ISH) with 37 check points, the US highways (USH) with 50 check points, and the State highways (STH) with 67 check points is compared to the actual ground count totals. The magnitude of the overall link volume to ground count ratio by route does not provide any specific pattern of over or underestimate. However, the %R11SE for the ISH shows the least value while that for the STH shows the largest value. This pattern is consistent with the screenline analysis and the overall relationship between %RMSE and ground count volume groups. Area specific volume analysis provides another broad statewide measure of the performance of the overall model. The truck traffic in the North area with 26 check points, the West area with 36 check points, the East area with 29 check points, and the South area with 64 check points are compared to the actual ground count totals. The four areas show similar results. No specific patterns in the L V/GC ratio by area are found. In addition, the %RMSE is computed for each of the four areas. The %RMSEs for the North, West, East, and South areas are 92%, 49%, 27%, and 35% respectively, whereas, the average ground counts are 481, 1383, 1532, and 3154 respectively. As for the screenline and volume range analyses, the %RMSE is inversely related to average link volume. 'The SELINK adjustments of productions and attractions resulted in a very substantial reduction in the total in-state zonal productions and attractions. The initial in-state zonal trip generation model can now be revised with a new trip production's trip rate (total adjusted productions/total population) and a new trip attraction's trip rate. Revised zonal production and attraction adjustment factors can then be developed that only reflect the impact of the SELINK adjustments that cause mcreases or , decreases from the revised zonal estimate of productions and attractions. Analysis of the revised production adjustment factors is conducted by plotting the factors on the state map. The east area of the state including the counties of Brown, Outagamie, Shawano, Wmnebago, Fond du Lac, Marathon shows comparatively large values of the revised adjustment factors. Overall, both small and large values of the revised adjustment factors are scattered around Wisconsin. This suggests that more independent variables beyond just 226; population are needed for the development of the heavy truck trip generation model. More independent variables including zonal employment data (office employees and manufacturing employees) by industry type, zonal private trucks 226; owned and zonal income data which are not available currently should be considered. A plot of frequency distribution of the in-state zones as a function of the revised production and attraction adjustment factors shows the overall " adjustment resulting from the SELINK analysis process. Overall, the revised SELINK adjustments show that the productions for many zones are reduced by, a factor of 0.5 to 0.8 while the productions for ~ relatively few zones are increased by factors from 1.1 to 4 with most of the factors in the 3.0 range. No obvious explanation for the frequency distribution could be found. The revised SELINK adjustments overall appear to be reasonable. The heavy truck VMT analysis is conducted by comparing the 1990 heavy truck VMT that is forecasted by the GM truck forecasting model, 2.975 billions, with the WisDOT computed data. This gives an estimate that is 18.3% less than the WisDOT computation of 3.642 billions of VMT. The WisDOT estimates are based on the sampling the link volumes for USH, 8TH, and CTH. This implies potential error in sampling the average link volume. The WisDOT estimate of heavy truck VMT cannot be tabulated by the three trip types, I-I, I-E ('||'&'||'pound;-I), and E-E. In contrast, the GM forecasting model shows that the proportion ofE-E VMT out of total VMT is 21.24%. In addition, tabulation of heavy truck VMT by route functional class shows that the proportion of truck traffic traversing the freeways and expressways is 76.5%. Only 14.1% of total freeway truck traffic is I-I trips, while 80% of total collector truck traffic is I-I trips. This implies that freeways are traversed mainly by I-E and E-E truck traffic while collectors are used mainly by I-I truck traffic. Other tabulations such as average heavy truck speed by trip type, average travel distance by trip type and the VMT distribution by trip type, route functional class and travel speed are useful information for highway planners to understand the characteristics of statewide heavy truck trip patternS. Heavy truck volumes for the target year 2010 are forecasted by using the GM truck forecasting model. Four scenarios are used. Fo~ better forecasting, ground count- based segment adjustment factors are developed and applied. ISH 90 '||'&'||' 94 and USH 41 are used as example routes. The forecasting results by using the ground count-based segment adjustment factors are satisfactory for long range planning purposes, but additional ground counts would be useful for USH 41. Sensitivity analysis provides estimates of the impacts of the alternative growth rates including information about changes in the trip types using key routes. The network'||'&'||'not;based GMcan easily model scenarios with different rates of growth in rural versus . . urban areas, small versus large cities, and in-state zones versus external stations. cities, and in-state zones versus external stations.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.3
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• pp.49-82
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• 1965

For the stable and high yields of low-land rice in Korea, the characteristics of rice plant for the vegetative and physiological responses, plant type formation, and yield components have been studied in order to obtain the fundamental data for the improvement of cultural practices, especially for the ideal fertilizer application. Furthermore the environmental conditions in Korea including temperatures, light, precipitation, and soil conditions have been compared in the broad sense with those in Japan, and the application of nitrogen, phosphorus, potassium, silicate and other micro-nutrients were described in relation to the characteristics of environmental conditions for the improvement of fertilizer application. 1. The average yield of polished-rice per 10 are in Korea is about 204 kg and this values are much less than those in Japan and Taiwan where they produce 77% to 13% more than in Korea. The rate of yield increase a year in Korea is 4.2 kg, but in Japan and Taiwan the rates of yield increase a year are 81 % and 62%, respectively. It was also found that the coefficient of variation of yield is 7.7% in Korea, 6.7% in Japan and 2.5% in Taiwan. This means that the stability of producing rice in Korea is very low when compared with those in Japan and Taiwan. 2. It was learned from the results obtained from the 'annual yield estimation experiment' that there are big differences in the respect of plant type formations between rice crops grown in Japan and Korea. The important differences found were as follows: (1) The numbers of spikelets per 3.3 square meters are 891 in Korea and 1, 007 in Japan(13% more than in Korea). (2) The numbers of tillers per 3.3 square meters at the stage of maximum tillering are 1, 150 in Korea, but in Japan they showed 19% more than in Korea. (3) The ratio of effective tillers to total tillers is 77.5% in Korea and 74.7% in Japan, which seems to be higher in Korea than in Japan. But the ratio in Korea is very low when considered the numbers of total tillers in both countries. (4) The ratio of grain to straw is 85.4% in Korea and 96.3% in Japan. 3. The average temperatures during the growing season at the area of Suwon, Kwangjoo and Taegu are almost same as those in the district of Jookokoo(Fookoo yama) in Japan, i.e., the temperatures during the rice-growing season in Korea are similar to those in the southern-warm regions of Japan. 4. Considering the minimum temperatures at the stage of limiting transplanting, 13$^{\circ}C$, the time of transplanting might be 30 to 40 days earlier than presently practicing transplanting time, which comes around June 10. 5. The temperatures during the vegetative growth in Korea were higher than those temperatures that needed in the protein synthesis which ate the main metabolism during this stage. However, the temperatures at the time of reproductive growth was lower than the temperatures that needed in the sugar assimilation which is main metabolism in this stage. In this point of view, it might be considered that the proper time of growing rice plant in Korea would be rather earlier. 6. The temperatures and the day light conditions at the time of first tillering stage of rice plant, when planted as presenting transplanting practices, are very satisfactory, but the poor day light length, high temperatures and too wet conditions in the time of last-tillering stage(mid or last July) might cause the occurrence of disease such as blast. 7. The heading stage of rice plants at each region through nations when planted as presently practicing method comes when the day light length is short. 8. It was shown that the accumulated average air-temperature at the time of maturing stage was not enough and the heading time was too late, when considered the annual deviations of mean temperatures and low minimum temperatures. 9. The nitrogen content of each plant part at the each growing stage was very high at the stage of vegetative growth when compared with the nitrogen content at the stage of reproductive growth after heading. In this respect it was believed to be important to prevent the nutrient shortages at the reproductive stages, especially after the heading. 10. The area of unsatisfactory irrigation paddy fields and natural rain-fed paddy fields are getting reduced in Korea. The correlation between the rate of reducing unsatisfactory irrigation and natural rain-fed paddy fields and the rate of yield increase were computed. The correlation coefficients(r) between the area of unsatisfactory irrigation paddy fields and yield increase were +0.525, and between the natural rain-fed paddy fields and yield increase, +0.832 and between the unsatisfactory irrigation plus natural rain-fed paddy fields and yield increase, +0.84. And there were. highly significant positive correlations between natural rain-fed paddy fields and yield increases indicating that the less the area of natural rain-fed paddy fields, the greater the yields per unit area. 11. The results obtained from the fertilizer experiments (yield performance trials) conducted in both Korea and Japan showed that the yield of non-fertilized plots per 10 are was 231 kg in Korea and 360 kg in Japan. On the basis of this it might be concluded that the fertility of soil in Korea is lower than that in Japan. Furthermore it was. also found that the yields of non-nitrogen applied plots per 10 are were 236 kg in Korea and 383 kg in Japan. This also indicates that the yields of rice in Korea are largely depending on the nitrogen content in the soil. 12. The followings were obtained when the chemical natures of soils in both Korea and Japan were compared. (1) The content of organic matter, total nitrogen, exchangeable calcium, and magnesium in Korea were no more than the half those in Japan. (2) The content of N/2 chloride and soluble silicate in low-land soil were on the average lower in Korea. (3) The exchange capacity of bases in Korea was no more than half that in Japan. 13. It was also observed by comparing the soil nature of the soil with high yielding capacity with the soil with low yielding capacity that the exchange capacity of bases, exchangeable calcium and magnesium, potassium, phosphorus, manganese, silicate and iron were low in the soil with low yielding capacity. 14. The depth of furrow slice was always deeper in the soil with high yielding capacity, and the depth of furrow slice in Korea was also shallower than that in Japan. 15. Summarizing the various conditions mentioned previously and considering the effects of silicate and trace elements such as manganese and iron besides three elements on the physiological and plant type formation of rice crops, more realistic and more ideal fertilizing practices were proposed. proposed.