• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.4
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• pp.289-297
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• 2010

Common practice of Soil Water Assessment Tool (SWAT) model validation is to use a single variable (i.e., streamlfow) to calibrate SWAT model due to the paucity of actual hydrological measurement data in Korea. This approach, however, often causes errors in the simulated results because of numerous sources of uncertainty and complexity of SWAT model. We employed multi-variables (i.e., streamflow, evapotranspiration, and soil moisture), which were measured at mixed forest in Seolmacheon catchment ($8.54\;km^2$), in order to assess the performance and reduce the uncertainties of SWAT model output. Meteorological and surface topographical data of the catchment were obtained as basic input variables and SWAT model was calibrated using daily data of streamflow (Jan. - Dec.), evapotranspiration (Sep. - Dec.), and soil moisture (Jun. - Dec.) collected in 2007. The model performance was assessed by comparing its results with the observation (i.e., streamflow of 2003 to 2008 and evapotranspiration and soil moisture of 2008). When the multi-variable measurements were used to calibrate the SWAT model, the model results showed better agreement with the measurements compared to those using a single variable measurement by showing increases in coefficient of determination ($R^2$) from 0.72 to 0.76 for streamflow, from 0.49 to 0.59 for soil moisture, and from 0.52 to 0.59 for evapotranspiration. The findings highlight the importance of reliable and accurate collective observation data for improving performance of SWAT model and promote its facilitation for estimating more realistic hydrological cycles at catchment scale.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.14 no.1
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• pp.81-88
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• 1996

Remote sensing technique is a probable means to estimate distribution of actual evapotranspiration over wide area in connection with regional characteristics of vegetation and landuse. Factors controlling evapotranspiration from ground are air temperature, humidity, wind, radiation, soil moisture and so on. Not only the vegetation influences directly the evapotranspiration, but also these factors strongly influnce the vegetation at the area. Therefore we can expect high correlation between the evapotranspiration and the vegetation. To grasp the state of vegetation at any point, NDVI calculated from NOAA/AVHRR data is utilized. It can be considered that evapotranspiration at a forest region is linearly proportional to the NDVI. Here, a model which adopts a direct method to estimate actual evapotranspiration is developed by using the relationship between NDVI and evapotranspiration. This method makes possible to estimate evapotranspiration of Korean Peninsula including North Korea where enough meteorological and hydrological data are unavailable.

• Journal of Climate Change Research
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• v.6 no.3
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• pp.223-231
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• 2015

Although a considerable part of climate change can be explained by temperature change, hydrological change such as precipitation, evapotranspiration, and runoff impact more on society. For the ascertain a hydrological change in agriculture sector, this study estimate evapotranspiration of cropland in the Korean peninsula, and then to assess the drought severity in the past 30 years through the estimated potential evapotranspiration and observed precipitation. The potential evapotranspiration is estimated by EPIC model and Penman-Monteith method and the drought severity in cropland of the Korean peninsula is assessed using Normalized Precipitation Evapotranspiration Index (NPEI) based on the difference in precipitation and potential evapotranspiration. In North Korea, the estimated evapotranspiration tends to increase even though a significant change is not found due to the change of climate. Although a time series change in drought severity in the past 30 years is not pronounced, a deviation by year and difference between South and North Korea is certain. One reason of this is difference in precipitation and evapotranspiration change according to the latitude. The result including expansion of facilities for water management in North Korea can be used for agricultural decision making, as well as base data of climate change adaptation.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1141-1180
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• 2022

The application of satellite imageries has increased in the field of hydrology and water resources in recent years. However, challenges have been encountered on obtaining accurate evapotranspiration and soil moisture. Therefore, present researches have emphasized the necessity to obtain estimations of satellite-based evapotranspiration and soil moisture with related development researches. In this study, we presented the research status in Korea by investigating the current trends and methodologies for evapotranspiration and soil moisture. As a result of examining the detailed methodologies, we have ascertained that, in general, evapotranspiration is estimated using Energy balance models, such as Surface Energy Balance Algorithm for Land (SEBAL) and Mapping Evapotranspiration with Internalized Calibration (METRIC). In addition, Penman-Monteith and Priestley-Taylor equations are also used to estimate evapotranspiration. In the case of soil moisture, in general, active (AMSR-E, AMSR2, MIRAS, and SMAP) and passive (ASCAT and SAR)sensors are used for estimation. In terms of statistics, deep learning, as well as linear regression equations and artificial neural networks, are used for estimating these parameters. There were a number of research cases in which various indices were calculated using satellite-based data and applied to the characterization of drought. In some cases, hydrological cycle factors of evapotranspiration and soil moisture were calculated based on the Land Surface Model (LSM). Through this process, by comparing, reviewing, and presenting major detailed methodologies, we intend to use these references in related research, and lay the foundation for the advancement of researches on the calculation of satellite-based hydrological cycle data in the future.

• Journal of Korea Water Resources Association
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• v.47 no.6
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• pp.547-559
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• 2014

The objective of this study is to evaluate the performance of the complementary relationship-based evapotranspiration models, namely, advection-aridity (AA) model of Brutsaert and Stricker and the CRAE model of Morton for estimating actual evapotranspiration. Both models were applied to the Bokhacheon middle-upper watershed, and their estimates were evaluated against the water balance estimate. The calculation was made on a daily basis and comparison was made on monthly and annual bases. For comparison, the water balance estimates were not obtained from the observed precipitation and streamflow data but were based on the simulated data by using integrated watershed model, SWAT-K which is the revised version of SWAT. The reason not to directly use the observed data for water balance estimate is that the credible record period is not sufficient and the streamflow has been altered due to water use and release. Overall, the results showed that both AA model and CRAE model with their original parameters overestimate annual and monthly evapotranspiration, and the large difference between the complementary relationship-based approach and the water balance approach occurs especially for the dry season from Nov. to Mar. It was found out that the parameters, particularly for the advection related parameter, must be recalibrated to accurately produce monthly and annual regional evapotranspiration for this study area.

• Journal of Korean Society on Water Environment
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• v.35 no.2
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• pp.131-144
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• 2019

Climate Change affects the hydrological cycle in agricultural watersheds through rising air temperature and changing rainfall patterns. Agricultural watersheds in Korea are characterized by extensive paddy fields and intensive water use, a resource that is under stress from the changing climate. This study analyzed the effects of climate change on river flows for Geum Cheon and Eun-San Choen watershed using STREAM, a semi-distributed watershed model. In order to evaluate the performance and improve the reliability of the model, calibration and validation of the model was done for one flow observation point and three reservoir water storage ratio points. Climate change scenarios were based on RCP data provided by the Korea Meteorological Administration (KMA) and bias corrections were done using the Quantile Mapping method to minimize the uncertainties in the results produced by the climate model to the local scale. Because of water mass-balance, evapotranspiration tended to increase steadily with an increase in air temperature, while the increase in RCP 8.5 scenario resulted in higher RCP 4.5 scenario. The increase in evapotranspiration led to a decrease in the river flow, particularly the decrease in the surface runoff. In the paddy agricultural watershed, irrigation water demand is expected to increase despite an increase in rainfall owing to the high evapotranspiration rates occasioned by climate change.

• Journal of Korea Water Resources Association
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• v.52 no.1
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• pp.61-70
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• 2019

The modified Kling-Gupta efficiency fusion method to merge actual evapotranspiration was proposed and compared with the simple Taylor skill's score method using Global Land Data Assimilation System (GLDAS), Global Land Evaporation Amsterdam Model (GLEAM), MODIS Global Evapotranspiration Project (MOD16), and the flux tower on three different land cover types over the Korean peninsula and China. In the results of the weights estimated from two actual evapotranspiration merging techniques (i.e., STS and KGF), the weights of reanalysis data (i.e, GLDAS and GLEAM) in cropland and grassland showed similar performance, while the results of weights are different according to the merging techniques in forest. Both two merging techniques showed better results than original dataset in grassland and forest. However, there were no improvement in cropland compared to the other land cover types. The results of the KGF method slightly improved compared to those of the STS in grassland and forest.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.2
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• pp.71-81
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• 2007

One of the most important hydrologic components is evapotranspiration. It is a process by which water is evaporated from moist land surfaces and transpired into atmosphere by plants. There are many methods of estimating evapotranspiration rate and its potential such as the methods of soil-moisture sampling, lysimeter measurements, water balance, energy balance, groundwater fluctuations and evapotranspiration. But it is very difficult to estimate evapotranspiration in terms of regional discrete characteristics of topography and/or vegetation. The evapotranspiration is strongly affected by ground covering vegetation, and the degree of vegetation growth. In order to grasp vegetation condition over a vast study area, NDVI (Normalized Difference Vegetation Indices) calculated from the data obtained from NOAA/AVHRR were utilized. Through multi-regression analysis, we developed a model equation to estimate the evapotranspiration using NDVIs and temperature data.

• Journal of Korea Water Resources Association
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• v.53 no.10
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• pp.889-902
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• 2020

This study was performed in Seolmacheon basin to evaluate the adequacy of GLDAS (Global Land Data Assimilation System) and GLEAM (Global Land Evaporation Amsterdam Model) evapotranspiration data. The verification data necessary for the evaluation of adequacy were calculated after processing the latent heat flux data produced in the Seolmacheon basin with the Koflux program. In order to gap-fill the empty period, alternative evapotranspiration was calculated in three ways: FAO-PM (Food and Agriculture Organization-Penman Monteith), MDV (Mean Diurnal Variation) and Kalman Filter. This study selected Kalman Filter method as the data gap-filling method because it showed the best Bias and RMSE among the three methods. The amount of GLDAS spatial evapotranspiration was calculated as Noah (version 2.1) with a time interval of 3 hours and a spatial resolution of 0.25°. The amount of GLEAM spatial evapotranspiration was calculated using GLEAM (version 3.1a). This study evaluated the spatial evapotranspiration of GLDAS and GLEAM as the evapotranspiration based on eddy covariance. As a result of evaluation, GLDAS spatial evapotranspiration showed better results than GLEAM. Accordingly, in this study, the GLDAS method was proposed as a method for calculating the amount of spatial evapotranspiration in the Seolmacheon basin.

• Magazine of the Korean Society of Agricultural Engineers
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• v.35 no.1
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• pp.40-49
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• 1993

The Objectives of this paper were to develop a modified tank model that is capable of simulating daily streamflow from a small watershed using daily watershed evapotranspiration and to test the applicability of the model to different watersheds. Tank model was restructured to consist of three series of tanks, each of which may mathematically reflect watershed runoff mechanisms from different components of surface runoff, interflow, and baseflow. And pan evaporation was correlated to potential evapotranspiration estimated from a combination method, and was multiplied by monthly crop and landuse coefficients, and watershed storage coefficient to estimate the watershed evapotranspiration losses. Ten watersheds were selected to calibrate model parameters that were defined using an optimization scheme, and the results were correlated with watershed parameters. Simulated daily runoff was compared to the observed ones from the tested watersheds. The simulating results were in good agreement with the observed values when optimal and calibrated parameters were used. Ungaged conditions were also applied to compare simulated values to the observed. And the results were in fair conditions for all the tested watersheds which differ considerably in their sizes, landuse types, and physiological features.