To fulfill applicability of Soil and Water Assessment Tool (SWAT) model, it is important that this model passes through a careful calibration and uncertainty analysis. In recent years, many researchers have come up with various uncertainty analysis techniques for SWAT model. To determine the differences and similarities of typical techniques, we applied three uncertainty analysis procedures to Chungju Dam watershed (6,581.1 $km^2$) of South Korea included in SWAT-Calibration Uncertainty Program (SWAT-CUP): Sequential Uncertainty FItting algorithm ver.2 (SUFI2), Generalized Likelihood Uncertainty Estimation (GLUE), Parameter Solution (ParaSol). As a result, there was no significant difference in the objective function values between SUFI2 and GLUE algorithms. However, ParaSol algorithm shows the worst objective functions, and considerable divergence was also showed in 95PPU bands with each other. The p-factor and r-factor appeared from 0.02 to 0.79 and 0.03 to 0.52 differences in streamflow respectively. In general, the ParaSol algorithm showed the lowest p-factor and r-factor, SUFI2 algorithm was the highest in the p-factor and r-factor. Therefore, in the SWAT model calibration and uncertainty analysis of the automatic methods, we suggest the calibration methods considering p-factor and r-factor. The p-factor means the percentage of observations covered by 95PPU (95 Percent Prediction Uncertainty) band, and r-factor is the average thickness of the 95PPU band.
The impact on hydrologic components considering future potential climate, land use change and vegetation cover information was assessed using SLURP (Semi-distributed Land-Use Runoff Process) continuous hydrologic model. The model was calibrated (1999 - 2000) and validated (2001 - 2002) for the upstream watershed ($260.4\;km^2$) of Gyeongancheon water level gauging station with the coefficient of determination and Nash-Sutcliffe efficiency ranging from 0.77 to 0.60 and 0.79 to 0.60, respectively. Two GCMs (MIROC3.2hires, ECHAM5-OM) future weather data of high (A2), middle (A1B) and low (B1) emission scenarios of the IPCC (Intergovernmental Panel on Climate Change) were adopted and the data was corrected by 20C3M (20th Century Climate Coupled Model) and downscaled by Change Factor (CF) method using 30 years (1977 - 2006, baseline period) weather data. Three periods data of 2010 - 2039 (2020s), 2040 - 2069 (2050s), 2070 - 2099 (2080s) were prepared. To reduce the uncertainty of land surface conditions, future land use and vegetation canopy prediction were tried by CA-Markov technique and NOAA NDVI-Temperature relationship respectively. MIROC3.2 hires and ECHAM5-OM showed increase tendency in annual streamflow up to 21.4 % for 2080 A1B and 8.9 % for 2050 A1B scenario respectively. The portion of future predicted ET about precipitation increased up to 3 % in MIROC3.2 hires and 16 % in ECHAM5-OM respectively. The future soil moisture content slightly increased compared to 2002 soil moisture.
The measured soil data are analyzed to the descriptive statistics and classified into the four models of uncorrelated-normal (UNNO), uncorrelated-nonnormal (VNNN), correlatedonnormal(CONN), and correlated-nonnormal(CONN) . This paper presents the comparisons of reliability index and check points using the advanced first-order second-moment method with respect to the four models as well as BASIC Program. A sin91e-mode Performance function is consisted of the basic design variables of bearing capacity and settlements on shallow foundations and input the above analyzed soil informations. The main conclusions obtained in this study are summarized as follows: 1. In the bearing capacity mode, cohesion and bearing-capacity factors by C-U test are accepted for normal and lognormal distribution, respectively, and negatively low correlated to each other. Since the reliability index of the CONN model is the lowest one of the four model, which could be recommended a reliability.based design, whereas the other model might overestimate the geotechnical conditions. 2. In the case of settlements mode, the virgin compression ratio and preccnsolidation pressure are fitted for normal and lognormal distribution, respectively. Constraining settlements to the lower ones computed by deterministic method, The CONN model is the lowest reliability of the four models.
Korean Journal of Agricultural and Forest Meteorology
/
v.18
no.4
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pp.307-319
/
2016
A Land-Atmosphere Modeling Package (LAMP) for supporting agricultural and forest management was developed at the National Center for AgroMeteorology (NCAM). The package is comprised of two components; one is the Weather Research and Forecasting modeling system (WRF) coupled with Noah-Multiparameterization options (Noah-MP) Land Surface Model (LSM) and the other is an offline one-dimensional LSM. The objective of this paper is to briefly describe the two components of the NCAM-LAMP and to evaluate their initial performance. The coupled WRF/Noah-MP system is configured with a parent domain over East Asia and three nested domains with a finest horizontal grid size of 810 m. The innermost domain covers two Gwangneung deciduous and coniferous KoFlux sites (GDK and GCK). The model is integrated for about 8 days with the initial and boundary conditions taken from the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) data. The verification variables are 2-m air temperature, 10-m wind, 2-m humidity, and surface precipitation for the WRF/Noah-MP coupled system. Skill scores are calculated for each domain and two dynamic vegetation options using the difference between the observed data from the Korea Meteorological Administration (KMA) and the simulated data from the WRF/Noah-MP coupled system. The accuracy of precipitation simulation is examined using a contingency table that is made up of the Probability of Detection (POD) and the Equitable Threat Score (ETS). The standalone LSM simulation is conducted for one year with the original settings and is compared with the KoFlux site observation for net radiation, sensible heat flux, latent heat flux, and soil moisture variables. According to results, the innermost domain (810 m resolution) among all domains showed the minimum root mean square error for 2-m air temperature, 10-m wind, and 2-m humidity. Turning on the dynamic vegetation had a tendency of reducing 10-m wind simulation errors in all domains. The first nested domain (7,290 m resolution) showed the highest precipitation score, but showed little advantage compared with using the dynamic vegetation. On the other hand, the offline one-dimensional Noah-MP LSM simulation captured the site observed pattern and magnitude of radiative fluxes and soil moisture, and it left room for further improvement through supplementing the model input of leaf area index and finding a proper combination of model physics.
Park, Geun-Ae;Ahn, So-Ra;Park, Min-Ji;Kim, Seong-Joon
KSCE Journal of Civil and Environmental Engineering Research
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v.30
no.2B
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pp.121-135
/
2010
This study is to assess the effect of potential future climate change on the inflow of agricultural reservoir and its impact to downstream streamflow by reservoir operation for paddy irrigation water supply using the SLURP. Before the future analysis, the SLURP model was calibrated using the 6 years daily streamflow records (1998-200398 and validated using 3 years streamflow data (2004-200698 for a 366.5 $km^2$ watershed including two agricultural reservoirs (Geumgwang8 and Gosam98located in Anseongcheon watershed. The calibration and validation results showed that the model was able to simulate the daily streamflow well considering the reservoir operation for paddy irrigation and flood discharge, with a coefficient of determination and Nash-Sutcliffe efficiency ranging from s 7 to s 9 and 0.5 to s 8 respectively. Then, the future potential climate change impact was assessed using the future wthe fu data was downscaled by nge impFactor method throuih bias-correction, the future land uses wtre predicted by modified CA-Markov technique, and the future ve potentiacovfu information was predicted and considered by the linear regression bpowten mecthly NDVI from NOAA AVHRR ima ps and mecthly mean temperature. The future (2020s, 2050s and 2e 0s) reservoir inflow, the temporal changes of reservoir storaimpand its impact to downstream streamflow watershed wtre analyzed for the A2 and B2 climate change scenarios based on a base year (2005). At an annual temporal scale, the reservoir inflow and storaimpchange oue, anagricultural reservoir wtre projected to big decrease innautumnnunder all possiblmpcombinations of conditions. The future streamflow, soossmoosture and grounwater recharge decreased slightly, whtre as the evapotransporation was projected to increase largely for all possiblmpcombinations of the conditions. At last, this study was analysed contribution of weather, vegetation and land use change to assess which factor biggest impact on agricultural reservoir and stream watershed. As a result, weather change biggest impact on agricultural reservoir inflow, storage, streamflow, evapotranspiration, soil moisture and groundwater recharge.
This study was conducted to predict and analyze water quality changes due to climate change using the SWAT (Soil and Water Assessment Tool) model for the main stream and major tributaries of the Yeongsan River Basin. To enhance the reliability of the model, input data was constructed using weather and flow data provided by the government from 2007 to 2021, and the model was calibrated. The mid-emission scenario (SSP2-4.5) and extreme emission scenario (SSP5-8.5), derived using the WRF climate change model from the 6th IPCC report, were applied to SWAT to predict flow and nutrient loads. The water quality changes under future climate change scenarios were analyzed by categorizing them into short-term (2021-2040), mid-term (2041-2060), and long-term (2081-2100) periods. Water quality assessments were conducted based on the Living Environment Standards and the Real-Time Water Quality Index (RTWQI). As a result, in most areas of the Yeongsan River Basin, the concentration of TN was found to be at or above the "Poor" level, with the "Very Poor" level being predominant, especially in the main stream and downstream areas. While the concentration of TP showed some variation depending on the scenario, it exhibited a trend of improvement over the long term. The RTWQI assessment generally showed higher water quality levels compared to the evaluation based on living environment standards, with a trend of water quality improvement over time. This suggests that the concentration of TN can act as a major problem as agricultural regions are the main areas in water quality management in the Yeongsan River basin. Therefore, in order to improve water quality according to future climate change, it is expected that it is necessary to further reduce point and non-point sources such as agricultural non-point source reduction management such as fertilizer management and conservation agriculture, and improvement of roof greening and sewage treatment plants in urban areas.
Characterizing the risk posed by a mixture of chemicals is a challenging task due to the chemical interactions of individual components that may affect their physical behavior and hence alter their exposure to receptors. In this study, cell tests that represent subsurface environment were carried out using benz[a]anthracene (BaA) and p-xylene focusing on phasetransforming interaction to verify increased mobility and risk of highly sorbed pollutants in the presence of less sorbed, mobile liquid pollutants. A transport model was also developed to interpret results and to simulate the same process on a field scale. The experimental results showed that BaA had far greater mobility in the presence of p-xylene than in the absence of that. The main transport mechanisms in the vadose zone were by dissolution to p-xylene or water. The transport model utilizing Defined Time Steps (DTS) was developed and tested with the experimental results. The predicted and observed values showed similar tendency, but the more work is needed in the future study for more precise modeling. The field-scale simulation results showed that transport of BaA to groundwater table was significantly faster in the presence of NAPL, and the oral carcinogenic risk of BaA calculated with the concentration in groundwater was 15${\sim}$87 times larger when mixed with NAPL than when solely contaminated. Since transport rate of PAHs is very slow in the subsurface without NAPL and no degradation of PAHs was considered in this simulation during the transport, the increase of risk in the presence of NAPL is expected to be greater for the actual contaminated site.
Journal of the Korean Institute of Landscape Architecture
/
v.48
no.3
/
pp.34-44
/
2020
In order to suggest performance analysis directions of ecological components based on a vegetation-based LID system model, this study seeks to analyze the statistical significance between monitoring results by using SWMM computer simulation and rainfall and run-off simulation devices and provide basic data required for a preliminary system design. Also, the study aims to comprehensively review a vegetation-based LID system's soil, a vegetation model, and analysis plans, which were less addressed in previous studies, and suggest a performance quantification direction that could act as a substitute device-type LID system. After monitoring artificial rainfall for 40 minutes, the test group zone and the control group zone recorded maximum rainfall intensity of 142.91mm/hr. (n=3, sd=0.34) and 142.24mm/hr. (n=3, sd=0.90), respectively. Compared to a hyetograph, low rainfall intensity was re-produced in 10-minute and 50-minute sections, and high rainfall intensity was confirmed in 20-minute, 30-minute, and 40-minute sections. As for rainwater run-off delay effects, run-off intensity in the test group zone was reduced by 79.8% as it recorded 0.46mm/min at the 50-minute point when the run-off intensity was highest in the control group zone. In the case of computer simulation, run-off intensity in the test group zone was reduced by 99.1% as it recorded 0.05mm/min at the 50-minute point when the run-off intensity was highest. The maximum rainfall run-off intensity in the test group zone (Dv=30.35, NSE=0.36) recorded 0.77mm/min and 1.06mm/min in artificial rainfall monitoring and SWMM computer simulation, respectively, at the 70-minute point in both cases. Likewise, the control group zone (Dv=17.27, NSE=0.78) recorded 2.26mm/min and 2.38mm/min, respectively, at the 50-minutes point. Through statistical assessing the significance between the rainfall & run-off simulating systems and the SWMM computer simulations, this study was able to suggest a preliminary design direction for the rainwater run-off reduction performance of the LID system applied with single vegetation. Also, by comprehensively examining the LID system's soil and vegetation models, and analysis methods, this study was able to compile parameter quantification plans for vegetation and soil sectors that can be aligned with a preliminary design. However, physical variables were caused by the use of a single vegetation-based LID system, and follow-up studies are required on algorithms for calibrating the statistical significance between monitoring and computer simulation results.
Kim, Yeon-Deok;Hwang, Beoung-Hyeon;Cho, Sung-Woo;Kim, Sang-Hwan
Journal of Korean Tunnelling and Underground Space Association
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v.23
no.4
/
pp.233-252
/
2021
This paper is a study to improve the efficiency of mixing technology in the shield TBM chamber. Currently, the number of construction cases using the TBM method is increasing in Korea. According to the increasing use of TBM method, research on TBM method such as Disc Cutter, Cutter bit, and Segment also shows an increasing trend. However, there is little research on the mixing efficiency in chamber and chamber. In order to improve the smooth soil treatment and the behavior of the excavated soil, a study was conducted on the change of the mixing efficiency according to the effective mixing bar arrangement in the chamber. In the scale model experiment, the ground was composed using plastic materials of different colors for ease of identification. In addition, the mixing bar arrangement was different and classified into 4 cases, and the particle size distribution was classified into single particle size and multiple particle size, and the experiment was conducted with a total of 8 cases. The rotation speed of the cutter head of all cases was the same as 5 RPM, and the experiment time was also carried out in the same condition, 1 minute and 30 seconds. In order to check the mixing efficiency, samples at the upper, middle (left or right), and lower positions of each case were collected and analyzed. As a result of the scaled-down model experiment, the mixing efficiency of Case 4 and Case 4-1 increased compared to Case 1 and Case 1-1, which are actually used. Accordingly, it is expected that the mixing efficiency can be increased by changing the arrangement of the mixing bar in the chamber, and it is considered to be effective in saving air as the mixing efficiency increases. Therefore, this study is considered to be an important indicator for the use of shield TBM in Korea.
As the environmental pollution caused by excessive uses of chemical fertilizers and pesticides is aggravated, organic farming using pasture and livestock manure is gaining an increased necessity. The application rate of the organic farming materials to the field is determined as a function of crops and soil types, weather and cultivation surroundings. When livestock manure is used for organic farming materials, the volatilization of ammonia from field-spread animal manure is a major source of atmospheric pollution and leads to a significant reduction in the fertilizer value of the manure. Therefore, an ammonia emission model should be presented to reduce the ammonia emission and to know appropriate application rate of manure. In this study, the ammonia emission rate from field-applied pig manure is predicted using an artificial neural network (ANN) method, where the Michaelis-Menten equation is employed for the ammonia emission rate model. Two model parameters (total loss of ammonia emission rate and time to reach the half of the total emission rate) of the model are predicted using a feedforward-backpropagation ANN on the basis of the ALFAM (Ammonia Loss from Field-applied Animal Manure) database in Europe. The relative importance among 15 input variables influencing ammonia loss is identified using the weight partitioning method. As a result, the ammonia emission is influenced mush by the weather and the manure state.
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