Magazine of the Korean Society of Agricultural Engineers
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v.43
no.2
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pp.78-84
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2001
The daily streamflow in the Yaluhe watershed located in the north-eastern part of China was simulated by DAWAST model and the water balance parameters of the model were calibrated by simplex method. Model verification tests were carried out. The range of root mean square error was 0.34∼1.50mm, that of percent error in volume was -16.9∼-62.0% and that of correlation coefficient was 0.727∼0.920. DAWAST model was revised to consider the phreatic evaporation from the ground water in the frozen soil by adjusting soil moisture content in the unsaturated layer at the end of the melting season. The results of estimation of the daily streamflow by the revised model were statistically improved, that is, the range of root mean square error was 0.31∼1.49mm, that of percent error in volume was -11.7∼-12.1%, and that of correlation coefficient was 0.810∼0.932. The accuracy of DAWAST model was improved and the applicability of DAWAST model was expanded to the frozen region.
Proceedings of the Korea Water Resources Association Conference
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2020.06a
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pp.118-118
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2020
This study investigates the change of flow characteristics over 10 Asian river basins in the past 30 years (1976-2005). The variation is estimated from The Soil and Water Assessment Tool (SWAT) model outputs based on reanalysis data which was bias-corrected for Asian monsoon reagion. The model was firstly calibrated and validated using observed data for daily streamflow. Four statistical criteria were applied to evaluate the model performance, including Coefficient of determination (R2), Nash - Sutcliffe model efficiency coeffi cient (NSE), Root mean square error-observations standard deviation ratio (RSR), and Percentage Bias (PBIAS). Then parameters of the model were applied for the historical period 1976-2005. The estimates show a temporal non-considerable increasing rate of daily streamflow in most of the basins over the past 30 years. The difference of monthly discharge becomes more significant during the months in the wet season (June to September) in all basins. The seasonal runoff shows significant difference in Summer and Autumn, when the rainfall intensity is higher. The line showing averaged runoff/rainfall ratio in all basins is sharp, presenting high variation of seasonal runoff/rainfall ratio from season to season.
Jung, Chung Gil;Moon, Jang Won;Jang, Cheol Hee;Lee, Dong Ryul
Journal of The Korean Society of Agricultural Engineers
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v.55
no.5
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pp.37-48
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2013
The objective of this study is to assess the impact of potential climate change on the hydrological components, especially on the streamflow, evapotranspiration and snowmelt, by using the Soil Water Assessment Tool (SWAT) for 17 Hanriver middle watersheds of South Korea. For future assessment, the SWAT model was calibrated in multiple sites using 4 years (2006-2009) and validated by using 2 years (2010-2011) daily observed data. For the model validation, the Nash-Sutcliffe model efficiency (NSE) for streamflow were 0.30-0.75. By applying the future scenarios predicted five future time periods Baseline (1992-2011), 2040s (2021-2040), 2060s (2041-2060), 2080s (2061-2080) and 2100s (2081-2100) to SWAT model, the 17 middle watersheds hydrological components of evapotranspiration, streamflow and snowmelt were evaluated. For the future precipitation and temperature of RCP 4.5 scenario increased 41.7 mm (2100s), $+3^{\circ}C$ conditions, the future streamflow showed +32.5 % (2040s), +24.8 % (2060s), +50.5 % (2080s) and +55.0 % (2100s). For the precipitation and temperature of RCP 8.5 scenario increased 63.9 mm (2100s), $+5.8^{\circ}C$ conditions, the future streamflow showed +35.5 % (2040s), +68.9 % (2060s), +58.0 % (2080s) and +63.6 % (2100s). To determine the impact on snowmelt for Hanriver middle watersheds, snowmelt parameters of SWAT model were determined through evaluating observed streamflow data during snowmelt periods (November-April). The results showed that average SMR (snowmelt / runoff) of 17 Hanriver middle watersheds was 62.0 % (Baseline). The annual average SMR were 42.0 % (2040s), 39.8 % (2060s), 29.4 % (2080s) and 27.9 % (2100s) by applying RCP 4.5 scenario. Also, the annual average SMR by applying RCP 8.5 scenario were 40.1 % (2040s), 29.4 % (2060s), 18.3 % (2080s) and 12.7 % (2100s).
Habimana, Jean de Dieu;Ha, Doan Thi Thu;Bae, Deg-Hyo
Proceedings of the Korea Water Resources Association Conference
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2020.06a
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pp.117-117
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2020
The main objective of this study was to setup model and evaluate the model performance for streamflow simulation in Burundi using Soil and Water Assessment Tool (SWAT) model. The total area of Burundi is 27,834 ㎢. The elevation of Burundi ranges from 780 m to 2,700m. The West and East are low lands, while the Central part is high land. The topographic data (30 meters Digital Elevation Model) and land use and land cover data of Burundi were obtained respectively from Shuttle Radar Topography Mission (SRTM) and the Regional Centre for Mapping of Resources for Development (RCMRD). The soil data used was obtained from Food and Agriculture Organization (FAO). The local weather data and discharge data were provided by Burundi Hydro meteorological Service (IGEBU). Mean Areal Precipitation (MAP) and Mean Areal Temperature (MAT) were estimated. The streamflow simulation was done for the period 1980-2017. The calibration and validation of river discharge was performed at a daily time step from 2005 through 2011 as the calibration period and 2012 up to 2017 as the validation period. The findings show that streamflow decreases during Jun to September and increases during March to May and October to December.
In this study, Neural Networks models were used to forecast daily streamflow at Jindong station of the Nakdong River basin. Neural Networks models consist of CASE 1(5-5-1) and CASE 2(5-5-5-1). The criteria which separates two models is the number of hidden layers. Each model has Fletcher-Reeves Conjugate Gradient BackPropagation(FR-CGBP) and Scaled Conjugate Gradient BackPropagation(SCGBP) algorithms, which are better than original BackPropagation(BP) in convergence of global error and training tolerance. The data which are available for model training and validation were composed of wet, average, dry, wet+average, wet+dry, average+dry and wet+average+dry year respectively. During model training, the optimal connection weights and biases were determined using each data set and the daily streamflow was calculated at the same time. Except for wet+dry year, the results of training were good conditions by statistical analysis of forecast errors. And, model validation was carried out using the connection weights and biases which were calculated from model training. The results of validation were satisfactory like those of training. Daily streamflow forecasting using Neural Networks models were compared with those forecasted by Multiple Regression Analysis Mode(MRAM). Neural Networks models were displayed slightly better results than MRAM in this study. Thus, Neural Networks models have much advantage to provide a more sysmatic approach, reduce model parameters, and shorten the time spent in the model development.
Mehboob, Muhammad Shafqat;Lee, Jaehyeong;Kim, Yeonjoo
Proceedings of the Korea Water Resources Association Conference
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2021.06a
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pp.137-137
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2021
In this study we aimed to enhance streamflow prediction skill of a land-surface hydrological model, WRF-Hydro, over one of the snow dominated catchments lies in Himalayan mountainous range, Astore. To assess the response of the Himalayan river flows to climate change is complex due to multiple contributors: precipitation, snow, and glacier melt. WRF-Hydro model with default glacier module lacks generating streamflow in summer period but recently developed WRF-Hydro-CROCUS model overcomes this issue by melting snow/ice from the glaciers. We showed that by implementing WRF-Hydro-CROCUS model over Astore the results were significantly improved in comparison to WRF-Hydro with default glacier module. To constraint the model with the observed streamflow we chose 17 sensitive parameters of WRF-Hydro, which include groundwater parameters, surface runoff parameters, channel parameters, soil parameters, vegetation parameters and snowmelt parameters. We used Dynamically Dimensioned Search (DDS) method to calibrate the daily streamflow with the Nash-Sutcliffe efficiency (NSE) being greater than 0.7 both in calibration (2009-2010) and validation (2011-2013) period. Based on the number of iterations per parameter, we found that the parameters related to channel and runoff process are most sensitive to streamflow. The attempts to address the responses of the streamflows to climate change are still very weak and vague especially northwest Himalayan Part of Pakistan and this study is one of a few successful applications of process-based land-surface hydrologic model over this mountainous region of UIB that can be utilized to have an in-depth understanding of hydrological responses of climate change.
Magazine of the Korean Society of Agricultural Engineers
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v.22
no.4
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pp.108-114
/
1980
A deterministic conceptual erosion model which simulates detachment, entrainment, transport and deposition of eroded soil particles by rainfall impact and flowing water is presented. Both upland and channel phases of sediment yield are incorporated into the erosion model. The algorithms for the soil erosion and sedimentation processes including land and crop management effects are taken from the literature and then solved using a digital computer. The erosion model is used in conjunction with the modified Kentucky Watershed Model which simulates the hydrologic characteristics from watershed data. The two models are linked together by using the appropriate computer code. Calibrations for both the watershed and erosion model parameters are made by comparing the simulated results with actual field measurements in the Four Mile Creek watershed near Traer, Iowa using 1976 and 1977 water year data. Two water years, 1970 and 1978 are used as test years for model verification. There is good agreement between the mean daily simulated and recorded streamflow and between the simulated and recorded suspended sediment load except few partial differences. The following conclusions were drawn from the results after testing the watershed and erosion model. 1. The watershed and erosion model is a deterministic lumped parameter model, and is capable of simulating the daily mean streamflow and suspended sediment load within a 20 percent error, when the correct watershed and erosion parameters are supplied. 2. It is found that soil erosion is sensitive to errors in simulation of occurrence and intensity of precipitation and of overland flow. Therefore, representative precipitation data and a watershed model which provides an accurate simulation of soil moisture and resulting overland flow are essential for the accurate simulation of soil erosion and subsequent sediment transport prediction. 3. Erroneous prediction of snowmelt in terms of time and magnitute in conjunction with The frozen ground could be the reason for the poor simulation of streamflow as well as sediment yield in the snowmelt period. More elaborate and accurate snowmelt submodels will greatly improve accuracy. 4. Poor simulation results can be attributed to deficiencies in erosion model and to errors in the observed data such as the recorded daily streamflow and the sediment concentration. 5. Crop management and tillage operations are two major factors that have a great effect on soil erosion simulation. The erosion model attempts to evaluate the impact of crop management and tillage effects on sediment production. These effects on sediment yield appear to be somewhat equivalent to the effect of overland flow. 6. Application and testing of the watershed and erosion model on watersheds in a variety of regions with different soils and meteorological characteristics may be recommended to verify its general applicability and to detact the deficiencies of the model. Futhermore, by further modification and expansion with additional data, the watershed and erosion model developed through this study can be used as a planning tool for watershed management and for solving agricultural non-point pollution problems.
Proceedings of the Korean Society of Agricultural Engineers Conference
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2003.10a
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pp.467-470
/
2003
The size, scale, and number of subwatersheds can affect a watershed modeling process and subsequent results. The objective of this study was to determine the appropriate level of subwatershed division for simulating streamflow. The Soil and Water Assessment Tool(SWAT) model with a GIS interface(BASINS SWAT) was applied to Yongdam Dam watershed. Daily output was analyzed from simulation, which was executed for 10 years using climate data representing the 1987 to 1996 period. The optimal number of subwatersheds and HRUs to adequately predict streamflow was found to be around 15, 174. Increasing the number of subwatersheds and HRUs beyond this level does not significantly affect the computed streamflow. this number of subwatersheds and HRUs can be used to optimize SWAT input data preparation requirements and simplify the interpretation of results without compromising simulation accuracy.
Park, Jong-Yoom;Jung, Hyuk;Jang, Cheol-Hee;Kim, Seong Joon
Journal of The Korean Society of Agricultural Engineers
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v.56
no.3
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pp.19-29
/
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.
Proceedings of the Korea Water Resources Association Conference
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2005.05b
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pp.1219-1223
/
2005
This study was accomplished to confirm the possibility of supplying stream minimum flow from detention storage which was determined to reduce peak flows of flood within developing planned district. The results analyzed was summarized as follows; Firstly, Sin-gil district situated in Ansan city was selected, of which watershed area has $0.56km^2$. And detention storage was determined to $5,370m^3$ from analyzing flood volume by the SCS unit hydrograph method. Secondly, using Visual Basic ver 6.0, a detention storage water balance model was developed, in which simulation was based on conditioning storage inflow and outflow according to streamflow volume or rate state. And streamflow was simulated using the DAWAST model. Thirdly, detention operation scenarios were consisted of the combinations with inflow referencing streamflow of 5mm/day, 10mm/day and outflow referencing streamflow of 1mm/day, 2mm/day. The developed detention storage water balance model was operated to simulate daily water storages of detention sized on flood by scenarios. Stream minimum flows were able to be supplied during 209 days to 237 days per a year, total volume of stream minimum flows supplied for this period was analyzed to reach 27 to $55\% of yearly streamflow volume. If inflow criteria of streamflows to detention was considered to be established on a theoretical condition, it is expected to supply stream minimum flows of 20 to $30\% of yearly streamflow from stream to detention. Also to maximize function of supplying urban stream minimum flow from detention storages, sewage waters within developing planned district have to be treated and entered to detention inflow together with streamflows to enrich function of detention planned to reduce flood volumes.
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