• Water for future
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• v.28 no.6
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• pp.193-202
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• 1995

The subjective research attempts to apply a rainfall-runoff model capable of considering time-variation of soil water contents which are highly correlated to the river flows on the qpqyungchang river basin and to evaluate its performance for flow forecasting. The model used in this study is a physically-based conceptual time-continuous model, which is composed of the Sacramento soil moisture accounting model and the nonlinear multiple conceptual reservoirs model. The daily precipitation and evaporation data for 7 years and for 3 years were used for the parameter estimation and the model verification, respectively. As a result, the flows including a significant flood event were well simulated, and the cross-correlation coefficient between observed flows and computed flows for the verification periods was 0.87, but in general computed flows were underestimated for the low-flow periods. Also, the effects of precipitation and soil water content to the river flows were analysed for the flood and the drought.

• Advances in environmental research
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• v.7 no.2
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• pp.109-120
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• 2018

In the present study research air quality analyses for $PM_{10}$, were conducted in Shiraz, a city in the south of Iran. The measurements were taken from 2011 through 2012 in two different locations to prepare average data in the city. The averages concentrations were calculated for every 24 hours, each month and each season. Results showed that the highest concentration of $PM_{10}$ occurs generally in the night while the least concentration was found at the afternoon. Monthly concentrations of $PM_{10}$ showed highest value in August, while least value was found in January. The seasonal concentrations showed the least amounts in autumn while the highest amounts in summer. Relations between the air pollutant and some meteorological parameters were calculated statistically using the daily average data. The wind data (velocity, direction), relative humidity, temperature, sunshine periods, evaporation, dew point and rainfall were considered as independent variables. The relationships between concentration of pollutant and meteorological parameters were expressed by multiple linear regression equations for both annual and seasonal conditions SPSS software. RMSE test showed that among different prediction models, stepwise model is the best option.

• Atmosphere
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• v.16 no.3
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• pp.215-223
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• 2006

Among observational, local-environmental, and large-scale factors causing significant changes in climate records, the site relocations and the replacement of the instruments are well-known nonclimatic factors for the analysis of climatic trends, climatic variability, and for the detection of anthropogenic climate change such as heat-island effect and global warming. Using dataset that were contaminated by these nonclimatic factors can affect seriously the assessment of climatic trends and variability, and the detection of the climatic change signal. In this paper, the inhomogeneities, which have been caused by relocation of the observation site, in the climate data of Korea Meteorological Administration (KMA) were examined using two-phase regression model. The observations of pan evaporation and wind speed are more sensitive to site relocations than those of other meteorological elements, such as daily mean, maximum and minimum temperatures, with regardless to region.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.6
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• pp.129-137
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• 2014

This research presents an streamflow modeling approach in a data-scarce estuary reservoir watershed which has been suffered from high salinity irrigation water problem after completion of land reclamation project in South Korea. Since limited hydrology data was available on the Iwon estuary reservoir watershed, water balance relation of the reservoir was used to estimate runoff from upstream of the reservoir. Water balance components in the reservoir consists precipitation, inflow from upstream, discharge through sluice, and evaporation. Estimated daily inflow data, which is stream discharge from upstream, shows a good consistency with the observed water level data in the reservoir in terms of EI (0.93) and $R^2$ (0.94), and were used as observed flow data for the streamflow modeling. HSPF (Hydrological Simulation Program - Fortran) was used to simulate hydrologic response of upstream of the reservoir. The model was calibrated and validated for the periods of 2006 to 2007 and 2008 to 2009, respectively, showing that values of EI and $R^2$ were 0.89 and 0.91 for calibration period, 0.71 and 0.84 for validation period.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.205-205
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• 2021

Surface soil moisture, which governs the partitioning of precipitation into infiltration and runoff, plays an important role in the hydrological cycle. The assimilation of satellite soil moisture retrievals into a land surface model or hydrological model has been shown to improve the predictive skill of hydrological variables. This study aims to improve streamflow prediction with Weather Research and Forecasting model-Hydrological modeling system (WRF-Hydro) by assimilating Soil Moisture Active and Passive (SMAP) data at 3 km and analyze its impacts on hydrological components. We applied Cumulative Distribution Function (CDF) technique to remove the bias of SMAP data and assimilate SMAP data (April to July 2015-2019) into WRF-Hydro by using an Ensemble Kalman Filter (EnKF) with a total 12 ensembles. Daily inflow and soil moisture estimates of major dams (Soyanggang, Chungju, Sumjin dam) of South Korea were evaluated. We investigated how hydrologic variables such as runoff, evaporation and soil moisture were better simulated with the data assimilation than without the data assimilation. The result shows that the correlation coefficient of topsoil moisture can be improved, however a change of dam inflow was not outstanding. It may attribute to the fact that soil moisture memory and the respective memory of runoff play on different time scales. These findings demonstrate that the assimilation of satellite soil moisture retrievals can improve the predictive skill of hydrological variables for a better understanding of the water cycle.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.38 no.3
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• pp.253-263
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• 1993

Climatological informations have not been fully utilized by agricultural research and extension workers in Korea due mainly to inaccessbilty to the archived climate data. This study was initiated to improve access to historical climate data gathered from 72 weather stations of Korea Meteorological Administration for agricultural applications by using a microcomputer-based methodology. The climatological elements include daily values of average, maximum and minimum temperature, relative humidity, average and maximum wind speed, wind direction, evaporation, precipitation, sunshine duration and cloud amount. The menu-driven, user-friendly data retrieval system(CLIDAS) provides quick summaries of the data values on a daily, weekly and monthly basis and selective retrieval of weather records meeting certain user specified critical conditions. Growing degree days and potential evapotranspiration data are derived from the daily climatic data, too. Data reports can be output to the computer screen, a printer or ASCII data files. CLIDAS can be run on any IBM compatible machines with Video Graphics Array card. To run the system with the whole database, more than 50 Mb hard disk space should be available. The system can be easily upgraded for further expansion of functions due to the module-structured design.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.6
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• pp.43-54
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• 2018

The accurate estimation of reference crop evapotranspiration ($ET_o$) is essential in irrigation water management to assess the time-dependent status of crop water use and irrigation scheduling. The importance of $ET_o$ has resulted in many direct and indirect methods to approximate its value and include pan evaporation, meteorological-based estimations, lysimetry, soil moisture depletion, and soil water balance equations. Artificial neural networks (ANNs) have been intensively implemented for process-based hydrologic modeling due to their superior performance using nonlinear modeling, pattern recognition, and classification. This study adapted two well-known ANN algorithms, Backpropagation neural network (BPNN) and Generalized regression neural network (GRNN), to evaluate their capability to accurately predict $ET_o$ using daily meteorological data. All data were obtained from two automated weather stations (Chupungryeong and Jangsu) located in the Yeongdong-gun (2002-2017) and Jangsu-gun (1988-2017), respectively. Daily $ET_o$ was calculated using the Penman-Monteith equation as the benchmark method. These calculated values of $ET_o$ and corresponding meteorological data were separated into training, validation and test datasets. The performance of each ANN algorithm was evaluated against $ET_o$ calculated from the benchmark method and multiple linear regression (MLR) model. The overall results showed that the BPNN algorithm performed best followed by the MLR and GRNN in a statistical sense and this could contribute to provide valuable information to farmers, water managers and policy makers for effective agricultural water governance.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.4
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• pp.1-13
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• 2005

In the process of a hydrology circulation, evapotranspiration is considered a very important factor to build a plan for the development of water resources and to operate water resources system. This study purposes to estimate daily potential evapotranspiration quantity in consideration of energy factors of the surface by using spatial information such as Landsat TM (ETM+) data, DEM and Landcover. Kyounan-cheon, Han River is selected as a target area, and landcover is divided by vegetation and non-vegetation covered area. Penman-Monteith equation which considers leaf-area index is used to estimate potential evapotranspiration quantity of vegetation covered area. The combination method (energy burget and aerodynamic method) is used in non-vegetation covered area. Among the input data for estimating potential evapotranspiration, NDVI, SR and Albedo is formed by Landsat, TM and ETM+ from 1986 through 2002. ground heat flux is estimated by using NDVI distribution map, LAI distribution map is drawn by using SR distribution map. The result of estimation shows that the average potential evapotranspiration in the whole basin is about 1.8-3.2mm/day per each cell. THe results of estimating potential evapotranspiration quantity by each landcover are as follows; water surface 3.6-4.9mm/day, city 1.4-3.1mm/day, bareland 1.4-3.5mm/day, grassland 1.7-3.7mm/day, forest 1.7-3.0mm/day and farmland 1.8-3.6mm/day. The potential evapotranspiration quantity is underestimated in comparison with observed evaporation data by evaporation pan, but it is considered that it has physical propriety.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.1B
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• pp.29-36
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• 2011

Evapotranspiration (ET) from the various surfaces needs to be understood because it is a crucial hydrological factor to grasp interaction between the land surface and the atmosphere. A traditional way of estimating it, which is calculating it empirically using lysimeter and pan evaporation observations, has a limitation that the measurements represent only point values. However, these measurements cannot describe ET because it is easily affected by outer circumstances. Thus, remote sensing technology was applied to estimate spatial distribution of ET. In this study, we estimated major components of energy balance method (i.e. net radiation flux, soil heat flux, sensible heat flux, and latent heat flux) and ET as a map using Mapping Evapo-Transpiration with Internalized Calibration (METRIC) satellite-based image processing model. This model was run using Landsat imagery of Gyeongan watershed in Korea on Feb 1, 2003 and Sep 13, 2006. Basic statistical analyses were also conducted. The estimated mean daily ETs had respectively 22% and 11% of errors with pan evaporation data acquired from the Suwon Weather Station. This result represented similar distribution compared with previous studies and confirmed that the METRIC algorithm had high reliability in the watershed. In addition, ET distribution of each land use type was separately examined. As a result, it was identified that vegetation density had dominant impacts on distribution of ET. Seasonally, ET in a growing season represented significantly higher than in a dormant season due to more active transpiration. The ET maps will be useful to analyze how ET behaves along with the circumstantial conditions; land cover classification, vegetation density, elevation, topography.

• Magazine of the Korean Society of Agricultural Engineers
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• v.31 no.1
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• pp.31-44
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• 1989

In the vinyl house cultivation, the water consumption, evapotnanspirafion ratio, growth condifion by the growing stages and yields of tomato and cucumber were investigated when they cultivated by nutriculture, rice hull charcoal culture and NFF culture. The results obtained are summarized as follows: 1. The mean air temperature in the vinyl house during the experimental perica j was 1.9$^{\circ}$C higher than the outdoor air temperature, the rrnocirnum and minimum air temperature in the vinyl house was 4.6C and 1.7$^{\circ}$C higher than the outdoor temperature, respectively, and the mean daily evaporation in the vinyl house during the experimental period was 4.3rnm that is 02rnrn more than the outdoor evaporation 2. In the tomato cultivation, the growth of rice hull charcoal culture was the best among the three methods, and the growth of NFT culture and nutriculture were worse than the soil cultivation which is standard, and among the nutriculture, the growth of EC 1.3m.mho plot was the best. 3. In the cucumber cultivation, the growth of rice hull charcoal culture was the best, and while the growth condition of NFT culture was worse than the standard soil cultivation, the growth of nutriculture was better than the standard soil cultivation, and the growth of EC 1.3m.mho plot was the highest among the different treatments in the nutriculture. 4. In the tomato cultivation, the total water consumption of rice hull charcoal culture plot was 1107.5rnm which is the highest amount among the three methods, and in the nutriculture, the total water consumption of EC 1.3m.mho plot was 22lAmm which is the highest among the three different treatments. 5. In the cucumber cultivation, the total water consumption of rice hull charcoal culture was 11762rnm which is the highest, and the total water consumption of EC 1.3m.mho plot was 284.9rnm which is more than the 278.9mm of EC 1.Smmho plot and 262.9mm of EC 1.7rnmho plot. 6. The crop coefficient(Kc) of tomato was 0.82 in NFT culture, 4.67 in rice hull charcoar culture and 0.86~0.91 in nutriculture. 7. The crop coefficient(Kc) of cucumber was higher than tomato as 1.13 in NFT culture, 520 in rice hull charcoal culture and 1.08~1.19 in nutriculture. 8. The evapotranspiration ratio in the mid and late season were higher than the beginning and elongation stage, and the average evaportranspiration ratio of tomato and cucumber was 3.81 and 424, respectively, in the rice hull charcoal culture plot. 9. In the tomato cultivation, the total yield per plant of rice bull charcoal culture was 1443.Og which is the highest, and in the nutriculture, their yields were worse because of the damage of downy nidew disease. 10. In the cucumber cultivation, the total yield per plant of rice hull charcoal culture was 1965.7g which is the highest, and while the yield of NFT culture was ahout 25% lower than the stadard soil cultivation, the yield of nutriculture was higher than the standard soil cultivation, and among the treatments in the nutriculture, the yield of EC 1.3m.mho plot was the highest.