• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.3
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• pp.19-29
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• 2014

This study was to evaluate the potential climate change impact on watershed hydrological components of evapotranspiration, surface runoff, lateral flow, return flow, and streamflow using Soil and Water Assessment Tool (SWAT). For Yongdam dam watershed (930 $km^2$), the SWAT model was calibrated for five years (2002-2006) and validated for three years (2004-2006) using daily streamflow data at three locations and daily soil moisture data at five locations. The Nash-Sutcliffe model efficiency (NSE) and coefficient of determination ($R^2$) were 0.43-0.67 and 0.48-0.70 for streamflow, and 0.16-0.65 and 0.27-0.76 for soil moisture, respectively. For future evaluation, the HadGEM3-RA climate data by Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios were adopted. The biased future data were corrected using 30 years (1982-2011, baseline period) of ground weather data. The HadGEM3-RA 2080s (2060-2099) temperature and precipitation showed increase of $+4.7^{\circ}C$ and +22.5 %, respectively based on the baseline data. The impacts of future climate change on the evapotranspiration, surface runoff, baseflow, and streamflow showed changes of +11.8 %, +36.8 %, +20.5 %, and +29.2 %, respectively. Overall, the future hydrologic results by RCP emission scenarios showed increase patterns due to the overall increase of future temperature and precipitation.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.2
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• pp.47-57
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• 2013

This study is to assess the reduction of non-point source pollution loads for rice straw mulching of upland crop cultivation at a watershed scale. For Byulmi-cheon watershed (1.21 $km^2$) located in the upstream of Gyeongan-cheon, the HSPF (Hydrological Simulation Program-Fortran) and SWAT (Soil and Water Assesment Tool), physically based distributed hydrological models were applied. Before evaluation, the model was calibrated and validated using 9 rainfall events. The Nash-Sutcliffe model efficiency (NSE) for streamflow using the HSPF was 0.62~0.76 and the determination coefficient ($R^2$) for water quality (sediment, total nitrogen T-N, and total phosphorus T-P) were 0.72, 0.62, and 0.63 respectively. The NSE for streamflow using the SWAT were 0.43~0.81 and the $R^2$ for water quality (sediment, T-N, and T-P) were 0.54, 0.87, and 0.64 respectively. From the field experiment of 16 rainfall events, the rice straw cover condition reduced surface runoff average 10.0 % compared to normal surface condition. By handling infiltration capacity (INFILT) in HSPF model, the value of 16.0 mm/hr was found to reduce about 10.0 % reduction of surface runoff. For this condition, the reduction effect of sediment, T-N, and T-P loads were 87.2, 28.5, and 85.1 % respectively. By handling soil hydraulic conductivity (SOL_K) in SWAT model, the value of 111.2 mm/hr was found to reduce about 10.0 point reduction of surface runoff. For this condition, the reduction effect of sediment, T-N, and T-P loads were 80.0, 83.2, and 78.7 % respectively. The rice straw surface covering was effective for removing surface runoff dependent loads such as sediment and T-P.

• Journal of Korean Society on Water Environment
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• v.32 no.1
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• pp.108-114
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• 2016

Sediment-laden water leads to water quality degradation in streams; therefore, best management practices must be implemented in the source area to control nonpoint source pollution. Field monitoring was implemented to measure precipitation, direct runoff, and sediment concentrations at a control plot and straw-applied plot to examine the effect on sediment reduction in this study. A hydrology model, which employs Curve Number (CN) to estimate direct runoff and the Universal Soil Loss Equation to estimate soil loss, was selected. Twenty-five storm events from October 2010 to July 2012 were observed at the control plot, and 14 storm events from April 2011 to July 2011 at the straw-applied plot. CN was calibrated for direct runoff, and the Nash-Sutcliffe efficiency and coefficient of determination were 0.66 and 0.68 at the control plot. Direct runoff at the straw-applied plot was calibrated using the percentage direct runoff reduction. The estimated reduction in sediment load by direct runoff reduction calibration alone was acceptable. Therefore, direct runoff-sediment load behaviors in a hydrology model should be considered to estimate sediment load and the reduction thereof.

• Journal of Korea Water Resources Association
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• v.46 no.9
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• pp.885-896
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• 2013

SEMMA (Soil Erosion Model for Mountain Areas) should be revised to apply on mountain watershed of large scale. In this study, the basic structure of original SEMMA and methods to calculate main parameters are reviewed and the revised parameters are presented to expand a range of application. SEMMA-Ic is new model revised by a rate of vegetation cover which is substituted for index of vegetation structure to use specially NDVI for large scale areas. The correlation coefficient and the Nash-Sutcliffe simulation efficiency for the revised model decreased rather than those of original model. However the evaluation of the revised model on watershed showed the approximate simulation with measured sediment yield and the underestimated simulation when sediment yield is large. The additional research for channel erosion is needed so that soil erosion model for hillslopes is used to estimate sediment yield from a watershed.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.3
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• pp.41-50
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• 2017

The purpose of this study were to evaluate the effect of best management practices (BMPs) of Haean highland agricultural catchment ($62.8km^2$) under future climate change using SWAT (Soil and Water Assessment Tool). Before future evaluation, the SWAT was setup using 3 years (2009~2011) of observed daily streamflow, suspended solid (SS), total nitrogen (T-N), and total phosphorus (T-P) data at three locations of the catchment. The SWAT was calibrated with average 0.74 Nash and Sutcliffe model efficiency for streamflow, and 0.78, 0.63, and 0.79 determination coefficient ($R^2$) for SS, T-N, and T-P respectively. Under the HadGEM-RA RCP (Representative Concentration Pathway) 4.5 and 8.5 scenarios, the future precipitation and maximum temperature showed maximum increases of 8.3 % and $4.2^{\circ}C$ respectively based on the baseline (1981~2005). The future 2040s and 2080s hydrological components of evapotranspiration, soil moisture, and streamflow showed changes of +3.2~+17.2 %, -0.1~-0.7 %, and -9.1~+8.1 % respectively. The future stream water quality of suspended solid (SS), total nitrogen (T-N), and total phosphorus (T-P) showed changes of -5.8~+29.0 %, -4.5~+2.3 %, and +3.7~+17.4 % respectively. The future SS showed wide range according to streamflow from minus to plus range. We can infer that this was from the increase of long-term rainfall variability in 2040s less rainfalls and 2080s much rainfalls. However, the results showed that the T-P was the future target to manage stream water quality even in 2040s period.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.6
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• pp.19-30
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• 2013

This study is to evaluate the use of dual-polarization radar data for storm runoff modeling in Namgang dam (2,293 $km^2$) watershed using KIMSTORM (Grid-based KIneMatic wave STOrm Runoff Model). The Bisl dual-polarization radar data for 3 typhoons (Khanun, Bolaven, Sanba) and 1 heavy rain event in 2012 were obtained from Han River Flood Control Office. Even the radar data were overall less than the ground data in areal average, the spatio-temporal pattern between the two data was good showing the coefficient of determination ($R^2$) and bias with 0.97 and 0.84 respectively. For the case of heavy rain, the radar data caught the rain passing through the ground stations. The KIMSTORM was set to $500{\times}500$ m resolution and a total of 21,372 cells (156 rows${\times}$137 columns) for the watershed. Using 28 ground rainfall data, the model was calibrated using discharge data at 5 stations with $R^2$, Nash and Sutcliffe Model Efficiency (ME) and Volume Conservation Index (VCI) with 0.85, 0.78 and 1.09 respectively. The calibration results by radar rainfall showed $R^2$, ME and VCI were 0.85, 0.79, and 1.04 respectively. The VCI by radar data was enhanced by 5 %.

• Journal of Environmental Science International
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• v.24 no.4
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• pp.437-447
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• 2015

Estimation of runoff peak is needed to assess water availability, in order to support the multifaceted water uses and functions, hence to underscore the modalities for efficient water utilization. The magnitude of storm rainfall acts as a primary input for basin level runoff computation. The rainfall-runoff linkage plays a pivotal role in water resource system management and feasibility level planning for resource distribution. Considering this importance, a case study has been carried out in the Hancheon basin of Jeju Island where distinctive hydrological characteristics are investigated for continuous storm rainfall and high permeable geological features. The study aims to estimate unit hydrograph parameters, peak runoff and peak time of storm rainfalls based on Clark unit hydrograph method. For analyzing observed runoff, five storm rainfall events were selected randomly from recent years' rainfall and HEC-hydrologic modeling system (HMS) model was used for rainfall-runoff data processing. The simulation results showed that the peak runoff varies from 164 to 548 m3/sec and peak time (onset) varies from 8 to 27 hours. A comprehensive relationship between Clark unit hydrograph parameters (time of concentration and storage coefficient) has also been derived in this study. The optimized values of the two parameters were verified by the analysis of variance (ANOVA) and runoff comparison performance were analyzed by root mean square error (RMSE) and Nash-Sutcliffe efficiency (NSE) estimation. After statistical analysis of the Clark parameters significance level was found in 5% and runoff performances were found as 3.97 RMSE and 0.99 NSE, respectively. The calibration and validation results indicated strong coherence of unit hydrograph model responses to the actual situation of historical storm runoff events.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.1
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• pp.37-45
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• 2011

Mandae watershed in Gangwon province has been known as one of soil erosion hot spot watersheds within Hanggang basin. Thus numerous efforts have been made to reduce soil erosion and pollutant loads into receiving watershed. However, proper best management practices have not been suggested because no monitoring flow and water quality data were available. Thus, modeling technique could not be utilized to evaluate water quality issue properly at Mandae watershed to develop and implement the best management practices. In this study, the SWAT model was applied to the Mandae watershed, Gangwon province to evaluate the SWAT prediction ability and water quality improvement with vegetated filter strip (VFS) in this study. The Nash-Sutcliffe model efficiency (NSE) and Coefficient of determination ($R^2$) values for flow simulation were 0.715 and 0.802, respectively, and the NSE and $R^2$ values were 0.903 and 0.920 for T-P simulation indicating the SWAT can be used to simulate flow and T-P with acceptable accuracies. The SWAT model, calibrated for flow and T-P, was used to evaluate water quality improvement with the VFS in agricultural fields. It was found that approximately 56.19 % of T-P could be reduced with vegetated filter strip of 5 m at the edge of agricultural fields within the watershed (34.86 % reduction with VFS of 1m, 48.29 % with VFS of 3 m). As shown in this study, the T-P, which plays key roles in eutrophication in the waterbodies, can be reduced with proper installation of the VFS.

• Korean Journal of Remote Sensing
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• v.24 no.1
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• pp.45-55
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• 2008

The impact on streamflow and groundwater recharge considering future potential climate and land use change was assessed using SLURP (Semi-distributed Land-Use Runoff Process) continuous hydrologic model. The model was calibrated and verified using 4 years (1999-2002) daily observed streamflow data for a $260.4km^2$ which has been continuously urbanized during the past couple of decades. The model was calibrated and validated with the coefficient of determination and Nash-Sutcliffe efficiency ranging from 0.8 to 0.7 and 0.7 to 0.5, respectively. The CCCma CGCM2 data by two SRES (Special Report on Emissions Scenarios) climate change scenarios (A2 and B2) of the IPCC (Intergovemmental Panel on Climate Change) were adopted and the future weather data was downscaled by Delta Change Method using 30 years (1977 - 2006, baseline period) weather data. The future land uses were predicted by CA (Cellular Automata)-Markov technique using the time series land use data of Landsat images. The future land uses showed that the forest and paddy area decreased 10.8 % and 6.2 % respectively while the urban area increased 14.2 %. For the future vegetation cover information, a linear regression between monthly NDVI (Normalized Difference Vegetation Index) from NOAA/AVHRR images and monthly mean temperature using five years (1998 - 2002) data was derived for each land use class. The future highest NDVI value was 0.61 while the current highest NDVI value was 0.52. The model results showed that the future predicted runoff ratio ranged from 46 % to 48 % while the present runoff ratio was 59 %. On the other hand, the impact on runoff ratio by land use change showed about 3 % increase comparing with the present land use condition. The streamflow and groundwater recharge was big decrease in the future.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.123-132
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• 2019

This study is to estimate the spatial soil moisture using Terra MODIS (Moderate Resolution Imaging Spectroradiometer) satellite data and machine learning technique. Using the 3 years (2015~2017) data of MODIS 16 days composite NDVI (Normalized Difference Vegetation Index) and daily Land Surface Temperature (LST), ground measured precipitation and sunshine hour of KMA (Korea Meteorological Administration), the RDA (Rural Development Administration) 10 cm~30 cm average TDR (Time Domain Reflectometry) measured soil moisture at 78 locations was tested. For daily analysis, the missing values of MODIS LST by clouds were interpolated by conditional merging method using KMA surface temperature observation data, and the 16 days NDVI was linearly interpolated to 1 day interval. By applying the RNN-LSTM (Recurrent Neural Network-Long Short Term Memory) artificial neural network model, 70% of the total period was trained and the rest 30% period was verified. The results showed that the coefficient of determination ($R^2$), Root Mean Square Error (RMSE), and Nash-Sutcliffe Efficiency were 0.78, 2.76%, and 0.75 respectively. In average, the clay soil moisture was estimated well comparing with the other soil types of silt, loam, and sand. This is because the clay has the intrinsic physical property for having narrow range of soil moisture variation between field capacity and wilting point.