• Journal of Korean Society on Water Environment
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• v.23 no.1
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• pp.64-71
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• 2007

In this study daily flow data is constructed from 8-day intervals flow data which has been measured by Nakdong River Water Environmental Laboratory. TANK model is used to expand 8-day intervals flow data into daily flow data. Using the Sequential quadratic programing, TANK model is auto-calibrated with daily precipitation and 8-day interval flow data. Generated and measured daily surface flow, ground water flow data and ground water recharge are shown to be in a good agreement. From this result, it is thought that this method has the potential to provide daily flow data for calibrating an watershed model such as SWAT.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.2
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• pp.171-183
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• 2005

In order to monitor the global terrestrial carbon cycle, NASA (National Aeronautics and Space Administration) provides 8-day GPP images by use of satellite remote-sensing reflectance data from MODIS (Moderate Resolution Imaging Spectroradiometer) at l-km nadir spatial resolution since December, 1999. MODIS GPP algorithm adopts DAO (Data Assimilation Office) meteorological data to calculate daily GPP. By evaluating reliability of DAO data with respect to surface weather station data, we examined the effect of errors from DAO data on MODIS GPP estimation in the Korean Peninsula from 2001 to 2003. Our analyses showed that DAO data underestimated daily average temperature, daily minimum temperature, and daily vapor pressure deficity (VPD), but overestimated daily shortwave radiation during the study period. Each meteorological variable resulted in different spatial patterns of error distribution across the Korean Peninsula. In MODIS GPP estimation, DAO data resulted in overestimation of GPP by $25\%$ for all biome types but up to $40\%$ for forest biomes, the major biome type in the Korean Peninsula. MODIS GPP was more sensitive to errors in solar radiation and VPD than in temperatures. Our results indicate that more reliable gridded meteorological data than DAO data are necessary for satisfactory estimation of MODIS GPP in the Korean Peninsula.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.3
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• pp.252-261
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• 2018

This study was conducted to develop a method to generate daily maximum and minimum temperatures using monthly data. We analyzed 30-year daily weather data of the 23 meteorological stations in South Korea and elucidated the parameters for predicting annual trend (center value ($\hat{U}$), amplitude (C), deviation (T)) and daily fluctuation (A, B) of daily maximum and minimum temperature. We use national average values for C, T, A and B parameters, but the center value is derived from the annual average data on each stations. First, daily weather data were generated according to the occurrence of rainfall, then calibrated using monthly data, and finally, daily maximum and minimum daily temperatures were generated. With this method, we could generate daily weather data with more than 95% similar distribution to recorded data for all 23 stations. In addition, this method was able to generate Growing Degree Day(GDD) similar to the past data, and it could be applied to areas not subject to survey. This method is useful for generating daily data in case of having monthly data such as climate change scenarios.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.6
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• pp.73-80
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• 2017

The objective of this study is to investigate whether the daily rainfall depth derived from daily data represents the event rainfall depth derived from hourly data. For analysis, the 85th, 90th, and 95th percentile daily rainfall depths were first computed using daily rainfall data (1986~2015) collected at 63 weather stations. In addition, the storm event was separated by the interevent time definition (IETD) of 6, 12, 18, and 24 hr using hourly rainfall data. Based on the separated storm events, the 85th, 90th, and 95th percentile event rainfall depths were calculated and compared with the using hourly rainfall data with the 85th, 90th, and 95th percentile daily rainfall depths. The event rainfall depths computed using the IETD were greater than the daily rainfall depths. The difference between the event rainfall depth and the daily rainfall depth affects the design and size of the facility for controlling the stormwater. Therefore, the designer and policy decision-maker in designing the stormwater best management practices need to take into account the difference generated by the difference of the used rainfall data and the selected IETD.

• Korean Journal of Remote Sensing
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• v.19 no.5
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• pp.341-349
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• 2003

The so-called B-method, a simplified surface energy budget, permits calculation of daily actual evapotranspiration (ET) using remotely sensed data, such as NOAA-AVHRR. Even if the use of satellite data allows estimation of the albedo and surface temperature, this model requires meteorological data measured at ground-level to obtain the other inputs. In addition, a difficulty may be occurred by the difference of temporal scales between the net radiation in daily scale and instantaneous measurement at midday of the surface and air temperatures because the data covered whole day are necessary to obtain accumulated daily net radiation. In order to solve these problems, this study attempted a modification of B-method through an extension of hourly ET value calculated using a complete instantaneous inputs. The estimation of the daily apparent ET from newly proposed system showed a root mean square error of 0.26 mm/day as compared the output obtained from the classical model. It is evident that this may offer more rapid estimation and reduced data volume.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.27-39
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• 2018

Since the global positioning system (GPS) has been included in mobile devices (e.g., for car navigation, in smartphones, and in smart watches), the impact of personal GPS log data on daily life has been unprecedented. For example, such log data have been used to solve public problems, such as mass transit traffic patterns, finding optimum travelers' routes, and determining prospective business zones. However, a real-time analysis technique for GPS log data has been unattainable due to theoretical limitations. We introduced a machine learning model in order to resolve the limitation. In this paper presents a new, three-stage real-time prediction model for a person's daily route activity. In the first stage, a machine learning-based clustering algorithm is adopted for place detection. The training data set was a personal GPS tracking history. In the second stage, prediction of a new person's transient mode is studied. In the third stage, to represent the person's activity on those daily routes, inference rules are applied.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2012.11a
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• pp.279-280
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• 2012

The Construction Standard Production Unit(CSPU) has been used for the standard cost estimate in public and private construction projects. However, It is questionable if the reliability and/or authenticity of the system is acceptable due to the lack of consistent enactment and/or revision procedures. This study identifies informational conditions and issues relative to using daily work report as a data collection method for enacting and/or revising CSPU system, and establishes the measures for improving the daily work report. This study aims on the information constitution of daily job-site report, daily manpower report, wages register for specialty contractors. According to the research results, most of necessary data were included in a daily job-site report. In conclusion, it is investigated that data of daily manpower report and wage register need to be included in a daily job-site report for understanding the current state of worker in the future.

• Atmosphere
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• v.17 no.1
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• pp.17-26
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• 2007

The station relocations, the replacement of instruments, and the change of a procedure for calculating derived climatic quantities from observations are well-known nonclimatic factors that seriously contaminate the worthwhile results in climate study. Prior to embarking on the climatological analysis, therefore, the quality and homogeneity of the utilized data sets should be properly evaluated with metadata. According to the metadata of the Korea Meteorological Administration (KMA), there have been plenty of changes in the procedure computing the daily mean values of temperature, humidity, etc, since 1904. For routine climatological work, it is customary to compute approximate daily mean values for individual days from values observed at fixed hours. In the KMA, fixed hours were totally 5 times changed: at four-hourly, four-hourly interval with additional 12 hour, eight-hourly, six-hourly, three-hourly intervals. In this paper, the homogeneity in the daily mean temperature dataset of the KMA was assessed with the consistency and efficiency of point estimators. We used the daily mean calculated from the 24 hourly readings as a potential true value. Approximate daily means computed from temperatures observed at different fixed hours have statistically different properties. So this inhomogeneity in KMA climate data should be kept in mind if you want to analysis secular aspects of Korea climate using this data set.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.6
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• pp.111-119
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• 2012

Applicability of 8 day interval flow data for the calibration of hydrologic model was evaluated using Hydrological Simulation Program-Fortran (HSPF) at Kyungan watershed. The 8 day interval flow monitored by Ministry of Environment located at upstream was calibrated and periodically validated during 2004-2008. And continuous daily flow monitored by Ministry of Construction & Transportation (MOCT) and located at the mouth was compared with daily simulated data during 2004-2007 as spatial validation. Automatic calibration tool which is Model-Independent Parameter Estimation & Uncertainty Analysis (PEST) was applied for HSPF calibration procedure. The model efficiencies for calibration and periodic validation were 0.63 and 0.88, and model performances were fair and very good, respectively, based on criteria of calibration tolerances. Continuous daily stream flow at the mouth of Kyungan watershed were good agreement with observed continuous daily stream flow with showing 0.63 NS value. The PEST program is very useful tool for HSPF hydrologic calibration using non-continuous daily stream flow as well as continuous daily stream flow. The 8 day interval flow data monitored by MOE could be used to calibrate hydrologic model if the continuous daily stream flow is unavailable.

• Magazine of the Korean Society of Agricultural Engineers
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• v.30 no.1
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• pp.50-62
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• 1988

This study refers to the development of a hydrologic model simulating daily inflow and release rates for irrigation reservoirs. A daily - based model is needed for adequate operation of an irrigation reservoir sufficing the water demand for paddy fields which is closely related to meteorological conditions. Inflow rates to a reservoir need to be accurately described, which may be simulated using a hydrologic model from daily rainfall data. And the objective of this paper is to develop, test, and apply a hydrologic model for daily runoff simmulation. A well - known tank model was selected and modified to simulate daily inflow rates. The model parameters were calibrated using observed runoff data from twelve watersheds, Relationships between the parameters and the watershed characteristics were derived by a multiple regression analysis. The simulation results were in agreement with the data. The inflow model was found to simulate low flow conditions more accurately than high flow conditions, which may be adequate for water resources utilization.