• Journal of Soil and Groundwater Environment
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• v.16 no.5
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• pp.82-89
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• 2011

Understanding snowmelt movement to the watershed is crucial for both climate change and hydrological studies because the snowmelt is a significant component of groundwater and surface runoff in temperature area. In this work, a new energy balance budget algorithm has been developed for melting snow from a snowpack at the Central Sierra Snow Laboratory (CSSL) in California, US. Using two sets of experiments, artificial rain-on-snow experiments and observations of diel variations, carried out in the winter of 2002 and 2003, we investigate how to calculate the amount of snowmelt from the snowpack using radiation energy and air temperature. To address the effect of air temperature, we calculate the integrated daily solar radiation energy input, and the integrated discharge of snowmelt under the snowpack and the energy required to generate such an amount of meltwater. The difference between the two is the excess (or deficit) energy input and we compare this energy to the average daily temperature. The resulting empirical relationship is used to calculate the instantaneous snowmelt rate in the model used by Lee et al. (2008a; 2010), in addition to the net-short radiation. If for a given 10 minute interval, the energy obtained by the melt calculation is negative, then no melt is generated. The input energy from the sun is considered to be used to increase the temperature of the snowpack. Positive energy is used for melting snow for the 10-minute interval. Using this energy budget algorithm, we optimize the intrinsic permeability of the snowpack for the two sets of experiments using one-dimensional water percolation model, which are $52.5{\times}10^{-10}m^2$ and $75{\times}10^{-10}m^2$ for the artificial rain-on-snow experiments and observations of diel variation, respectively.

• The Korean Journal of Quaternary Research
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• v.14 no.1
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• pp.57-63
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• 2000

A simulation model was used to examine the effects of climate variation on the tree-ring structure of Larix leptolepis trees growing at a plantation plot in Worak National Park in central Korea. The model uses mathematical equations to simulate processes affecting cell(tracheid) size variations for individual rings using daily precipitation and temperature measurements. Limiting conditions are estimated from temperature, day length and a calculated water balance. The results indicate that the seasonal growth is mostly limited by the soil moisture content and precipitation income during April and May. The April-May temperature also inversely influences the growth by increasing water losses from soil. The global climate-change scenario which includes regional warming(increasing temperature in spring-summer periods) appears to decrease the duration of optimal growths. Consequently, the model estimated that Larix leptolepis would lose the total production of xylem by 25%.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.3
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• pp.434-442
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• 2008

The objective of this study was to determine the optimum ratio of methionine to methionine plus cystine for growing pigs. A nitrogen balance trial was conducted using a total of 21 barrows (Large WhiteLandrace) over two replicates. The initial body weight was $20.36{\pm}1.22kg$ (mean${\pm}$SD) in the first replicate and $23.54{\pm}1.02kg$ (mean${\pm}$SD) in the second. For each replicate, the 21 pigs were randomly assigned to one of seven dietary treatments with three observations per treatment. The diets included a methionine and cystine-deficient basal diet with all other essential nutrients meeting nutrient requirements and six diets formulated with graded levels of DL-methionine (0.00, 0.03, 0.06, 0.10, 0.13, 0.16%) and $L-Cystine{\cdot}HCl{\cdot}H_2O$ (0.19, 0.15, 0.11, 0.07, 0.04, 0.00%). This resulted in ratios of methionine to methionine plus cystine of 41.3, 29.6, 35.3, 41.2, 46.0, 51.6 and 57.5%. Each experimental period lasted 12 days consisting of a seven-day adaptation period followed by a five-day total collection of urine and feces. During the collection period, pigs were fed 900 g/day for the first replicate and 1,200 g/day for the second replicate. The feed was provided in three equal portions at 0800, 1500, and 2200 h daily. Pigs had ad libitum access to water after feeding. There was a linear (p<0.01) and quadratic (p<0.01) effect on daily gain and feed conversion as the ratio of methionine to methionine plus cystine increased. Pigs receiving the diets providing a methionine to methionine plus cystine ratio of 51.6% had the best daily gain and feed conversion. Plasma urea nitrogen was also lowest for this treatment. Nitrogen retention increased (p<0.01) as the relative proportion of methionine increased up to 51.6% and then a downward trend occurred at 57.5%. The quadratic regression model, as well as one- and two- slope regression line models, were used to determine the optimum ratio of methionine to methionine plus cystine. Eliminating the 35.3% methionine to methionine plus cystine treatment resulted in $R^2$ values in excess of 0.92. The optimal ratio of methionine to methionine plus cystine was estimated to be 54.15% for nitrogen retention and 56.72% for plasma urea nitrogen.

• Journal of Soil and Groundwater Environment
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• v.11 no.5
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• pp.9-19
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• 2006

The accurate estimation of groundwater recharge is important for the proper management of groundwater systems. The widely used techniques of groundwater recharge estimation include water table fluctuation method, baseflow separation method, and annual water balance method. However, these methods can not represent the temporal-spatial variability of recharge resulting from climatic condition, land use, soil storage and hydrogeological heterogeneity because the methods are all based on the lumped concept and local scale problems. Therefore, the objective of this paper is to present an effective method for estimating groundwater recharge with spatial-temporal variability using the SWAT model which can represent the heterogeneity of the watershed. The SWAT model can simulate daily surface runoff, evapotranspiration, soil storage, recharge, and groundwater flow within the watershed. The model was applied to the Musimcheon watershed located in the upstream of Mihocheon watershed. Hydrological components were determined during the period from 2001 to 2004, and the validity of the results was tested by comparing the estimated runoff with the observed runoff at the outlet of the catchment. The results of temporal and spatial variations of groundwater recharge were presented here. This study suggests that variations in recharge can be significantly affected by subbasin slope as well as land use.

• Journal of Ecology and Environment
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• v.33 no.2
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• pp.165-173
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• 2010

Soil respiration ($R_S$) is a critical component of the annual carbon balance of forests, but few studies thus far have attempted to evaluate empirical regression models in $R_S$. The principal objectives of this study were to evaluate the relationship between $R_S$ rates and soil temperature (ST) and soil water content (SWC) in soil from a cool-temperate deciduous broad-leaved forest, and to evaluate empirical regression models for the prediction of $R_S$ using ST and SWC. We have been measuring $R_S$, using an open-flow gas-exchange system with an infrared gas analyzer during the snowfree season from 1999 to 2001 at the Takayama Forest, Japan. To evaluate the empirical regression models used for the prediction of $R_S$, we compared a simple exponential regression (flux = $ae^{bt}$Eq. [1]) and two polynomial multiple-regression models (flux = $ae^{bt}{\times}({\theta}{\nu}-c){\times}(d-{\theta}{\nu})^f:$ Eq. [2] and flux = $ae^{bt}{\times}(1-(1-({\theta}{\nu}/c))^2)$: Eq. [3]) that included two variables (ST: t and SWC: ${\theta}{\nu}$) and that utilized hourly data for $R_S$. In general, daily mean $R_S$ rates were positively well-correlated with ST, but no significant correlations were observed with any significant frequency between the ST and $R_S$ rates on periods of a day based on the hourly $R_S$ data. Eq. (2) has many more site-specific parameters than Eq. (3) and resulted in some significant underestimation. The empirical regression, Eq. (3) was best explained by temporal variations, as it provided a more unbiased fit to the data compared to Eq. (2). The Eq. (3) (ST $\times$ SWC function) also increased the predictive ability as compared to Eq. (1) (only ST exponential function), increasing the $R^2$ from 0.71 to 0.78.

• Economic and Environmental Geology
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• v.54 no.2
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• pp.161-176
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• 2021

In this study, one of the distributed hydrologic models, VELAS, was used to analyze the variation of hydrologic elements based on water balance analysis to evaluate the groundwater recharge in more detail than the annual time scale for the past and future. The study area is located in Yanggok-ri, Seobu-myeon, Hongseong-gun, Chungnam-do, which is very vulnerable to drought. To implement the VELAS model, spatial characteristic data such as digital elevation model (DEM), vegetation, and slope were established, and GIS data were constructed through spatial interpolation on the daily air temperature, precipitation, average wind speed, and relative humidity of the Korea Meteorological Stations. The results of the analysis showed that annual precipitation was 799.1-1750.8 mm, average 1210.7 mm, groundwater recharge of 28.8-492.9 mm, and average 196.9 mm over the past 18 years from 2001 to 2018 in the study area. Annual groundwater recharge rate compared to annual precipitation was from 3.6 to 28.2% with a very large variation and average 14.9%. By the climate change RCP 8.5 scenario, the annual precipitation from 2019 to 2100 was 572.8-1996.5 mm (average 1078.4 mm) and groundwater recharge of 26.7-432.5 mm (average precipitation 16.2%). The annual groundwater recharge rates in the future were projected from 2.8% to 45.1%, 18.2% on average. The components that make up the water balance were well correlated with precipitation, especially in the annual data rather than the daily data. However, the amount of evapotranspiration seems to be more affected by other climatic factors such as temperature. Groundwater recharge in more detailed time scale rather than annual scale is expected to provide basic data that can be used for groundwater development and management if precipitation are severely varied by time, such as droughts or floods.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.1
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• pp.156-169
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• 2015

This study was to evaluate the RCP climate change impact on hydrological components in the Imha-Dam watershed using SWAT(Soil and Water Assessment Tool) Model. The model was calibrated for six year(2002~2007) and validated for six year(2008~2013) using daily observed streamflow data at three watershed stations. The overall simulation results for the total released volume at this point appear reasonable by showing that coefficient of determination($R^2$) were 0.70~0.85 and Nash-Sutcliffe model efficiency(NSE) were 0.67-0.82 for streamflow, respectively. For future hydrologic evaluation, the HadGEM3-RA climate data by scenarios of Representative Concentration Pathway(RCP) 4.5 and 8.5 of the Korea Meteorological Administration were adopted. The biased future data were corrected using 34 years(1980~2013, baseline period) of weather data. Precipitation and temperature showed increase of 10.8% and 4.9%, respectively based on the baseline data. The impacts of future climate change on the evapotranspiration, soil moisture, surface runoff, lateral flow, return flow and streamflow showed changes of +11.2%, +1.9%, +10.0%, +12.1%, +18.2%, and +11.2%, respectively.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.4
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• pp.21-35
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• 2016

This study is to evaluate the applicability of SWAT (Soil and Water Assessment Tool) model for multi-purpose dams and multi-function weirs operation in Namhan river basin ($12,577km^2$) of South Korea. The SWAT was calibrated (2005 ~ 2009) and validated (2010 ~ 2014) considering of 4 multi-purpose dams and 3 multi-function weirs using daily observed dam inflow and storage, evapotranspiration, soil moisture, and groundwater level data. Firstly, the dam inflow was calibrated by the five steps; (step 1) the physical rate between total runoff and evapotranspiration was controlled by ESCO, (step 2) the peak runoff was calibrated by CN, OV_N, and CH_N, (step 3) the baseflow was calibrated by GW_DELAY, (step 4) the recession curve of baseflow was calibrated by ALPHA_BF, (step 5) the flux between lateral flow and return flow was controlled by SOL_AWC and SOL_K, and (step 6) the flux between reevaporation and return flow was controlled by REVAPMN and GW_REVAP. Secondly, for the storage water level calibration, the SWAT emergency and principle spillway were applied for water level from design flood level to restricted water level for dam and from maximum to management water level for weir respectively. Finally, the parameters for evapotranspiration (ESCO), soil water (SOL_AWC) and groundwater level fluctuation (GWQMN, ALPHA_BF) were repeatedly adjusted by trial error method. For the dam inflow, the determination coefficient $R^2$ was above 0.80. The average Nash-Sutcliffe efficiency (NSE) was from 0.59 to 0.88 and the RMSE was from 3.3 mm/day to 8.6 mm/day respectively. For the water balance performance, the PBIAS was between 9.4 and 21.4 %. For the dam storage volume, the $R^2$ was above 0.63 and the PBIAS was between 6.3 and 13.5 % respectively. The average $R^2$ for evapotranspiration and soil moisture at CM (Cheongmicheon) site was 0.72 and 0.78, and the average $R^2$ for groundwater level was 0.59 and 0.60 at 2 YP (Yangpyeong) sites.

• Journal of Korea Water Resources Association
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• v.49 no.3
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• pp.227-239
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• 2016

This study is to estimate Surface Energy Balance Algorithm for Land (SEBAL) daily spatial evapotranspiration (ET) comparing with eddy covariance flux tower ET in Seolmacheon mixed forest (SMK) and Cheongmicheon rice paddy (CFK). The SEBAL input data of Albedo, Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI) from Terra MODIS products and the meteorological data of wind speed, and solar radiation were prepared for 2 years (2012-2013). For the annual average flux tower ET of 302.8 mm in SMK and 482.0 mm in CFK, the SEBAL ETs were 183.3 mm and 371.5 mm respectively. The determination coefficients ($R^2$) of SEBAL ET versus flux tower ET for total periods were 0.54 in SMK and 0.79 in CFK respectively. The main reason of SEBAL ET underestimation for both sites was from the determination of hot pixel and cold pixel of the day and affected to the overestimation of sensible heat flux.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.3
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• pp.160-174
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• 2014

The purpose of this paper is to develop a meso-scale grid-based continuous hydrological model and apply to assess the future watershed hydrology by climate change. The model divides the watershed into rectangular cells, and the cell profile is divided into three layered flow components: a surface layer, a subsurface unsaturated layer, and a saturated layer. Soil water balance is calculated for each grid cell of the watershed, and updated daily time step. Evapotranspiration(ET) is calculated by Penman-Monteith method and the surface and subsurface flow adopts lag coefficients for multiple days contribution and recession curve slope for stream discharge. The model was calibrated and verified using 9 years(2001-2009) dam inflow data of two watersheds(Chungju Dam and Soyanggang Dam) with 1km spatial resolution. The average Nash-Sutcliffe model efficiency was 0.57 and 0.71, and the average determination coefficient was 0.65 and 0.72 respectively. For the whole Han river basin, the model was applied to assess the future climate change impact on the river bsain. Five IPCC SRES A1B scenarios of CSIRO MK3, GFDL CM2_1, CONS ECHO-G, MRI CGCM2_3_2, UKMO HADGEMI) showed the results of 7.0%~27.1 increase of runoff and the increase of evapotranspiration with both integrated and distributed model outputs.