• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.1
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• pp.20-30
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• 2008

This study is to analyse the hydrological behavior of agricultural reservoir using SWAT model. For the upsteam watershed of Gongdo water level gauge station in Anseongcheon watershed, the streamflows at 2 reservoir (Gosam and Geumgwang) locations and Gongdo station were simulated with reservoir inclusion and exclusion. The daily water surface area and storage have been calculated considering the stage-storage curve function of the reservoir. Afterwards, the reservoir operation module in SWAT was modified from original module in SWAT for daily reservoir discharge simulated by water balance equation. Model validation results were Nash-Sutcliffe model efficiency coefficients value of 0.55, root mean square error value of 2.33 mm/day. On the other hand, the simulation results of two reservoir exclusion were Nash-Sutcliffe model efficiency coefficients value of 0.37, root mean square error value of 2.91 mm/day. The difference of Nash-Sutcliffe model efficiency coefficients between the simulation results of two reservoir inclusion and exclusion at Gongdo station was 0.18. This is caused by the storage and release operation of agricultural reservoirs for the runoff occurred at 2 reservoir watersheds.

• Korean Journal of Ecology and Environment
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• v.43 no.3
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• pp.349-355
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• 2010

This study aims at the augmentation of reliability of the long-term rainfall runoff model. To do so agricultural water uses are evaluated by analyzing the effects of small scale irrigational hydraulic structures on long term runoff processes and thereby rainfall-runoff model is modified considering them. As a result the simulation results of the sub-basins having more agricultural reservoirs than the others are disagreed with the observations. The 2nd quarter simulation results show similar trend to it. Especially the farming seasonal results of the drought year as the year of 2008 have many negative discharge values due to the lack of agricultural water uses. This result come from the water uses input data corresponding to not real water uses but water demands. In this study the formulas are derived to estimate the discharges and return ratios and the long term rainfall-runoff model is reformulated based on these. It is confirmed that the errors of the simulation results could be reduced by considering the effects of small scale irrigational hydraulic structures and the reliability of the simulation results improved greatly.

• Parasites, Hosts and Diseases
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• v.53 no.4
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• pp.395-402
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• 2015

Non-human primates (NHPs) are confirmed as reservoirs of Cryptosporidium spp., Giardia intestinalis, and Enterocytozoon bieneusi. In this study, 197 fresh fecal samples from 8 NHP species in Qinling Mountains, northwestern China, were collected and examined using multilocus sequence typing (MLST) method. The results showed that 35 (17.8%) samples were positive for tested parasites, including Cryptosporidium spp. (3.0%), G. intestinalis (2.0%), and E. bieneusi (12.7%). Cryptosporidium spp. were detected in 6 fecal samples of Macaca mulatta, and were identified as C. parvum (n=1) and C. andersoni (n=5). Subtyping analysis showed Cryptosporidium spp. belonged to the C. andersoni MLST subtype (A4, A4, A4, and A1) and C. parvum 60 kDa glycoprotein (gp60) subtype IId A15G2R1. G. intestinalis assemblage E was detected in 3 M. mulatta and 1 Saimiri sciureus. Intra-variations were observed at the triose phosphate isomerase (tpi), beta giardin (bg), and glutamate dehydrogenase (gdh) loci, with 3, 1, and 2 new subtypes found in respective locus. E. bieneusi was found in Cercopithecus neglectus (25.0%), Papio hamadrayas (16.7%), M. mulatta (16.3%), S. sciureus (10%), and Rhinopithecus roxellana (9.5%), with 5 ribosomal internal transcribed spacer (ITS) genotypes: 2 known genotypes (D and BEB6) and 3 novel genotypes (MH, XH, and BSH). These findings indicated the presence of zoonotic potential of Cryptosporidium spp. and E. bieneusi in NHPs in Qinling Mountains. This is the first report of C. andersoni in NHPs. The present study provided basic information for control of cryptosporidiosis, giardiasis, and microsporidiosis in human and animals in this area.

• Korean Journal of Environmental Agriculture
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• v.20 no.3
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• pp.143-149
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• 2001

A contact oxidation canal system with sedimentation basin was installed to study the efficiency of water quality purification. The primary sedimentation basin with 60 min of HRT (Hydraulic Retention Time) included in the system was aimed to sediment pollutants in the water and the deposit being released by the drainage culvert located at the bottom of the system. The oxidation canal aerated by nozzle was to contact the pollutants and oxygen in the surface of plastic filter to purify the water. Discharge, HRT, length of the oxidation canal were $200\;m^3/day$, 90 min, 20 m, respectively. The treatment efficiency of total nitrogen was lower compared with other water quality items such as SS, BOD, TP because the anoxic condition for denitrification was not ensured after the oxidation canal. However, $25%{\sim}89.6%$ of SS, $75.0%{\sim}91.5%$ of BOD, $44.3%{\sim}95.3%$ of TP were removed in this system. Overall, the results indicates that this system appears to have a potential capability for water quality improvement of the reservoirs or the canals in the agricultural watershed.

• Magazine of the Korean Society of Agricultural Engineers
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• v.37 no.3_4
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• pp.34-47
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• 1995

It is experienced fact as a regular annual event that the structure to he designed on unreasonable flood for the agricultural structures including reservoirs have been brought not only loss of lives, but also enormous property damage. For the solution of this problem at issue, this study was conducted to develop an optimal runoff hydrograph model by comparison of the peak flows and time to peak between observed and simulated flows derived by linear time-invariant and linear time-variant models under the condition of having a short duration of heavy rainfall with uniform rainfall intensity at nine small watersheds which are within the range of 55.9 to 140.7 square kilometers in area in Han, Geum, Nagdong and Yeongsan Rivers. The results obtained through this study can be summarized as follows. 1. Storage constants and Gamma function arguments were calculated within the range of 1.2 to 6.42 and of 1.28 to 8.05 respectively by the moment method as the parameters for the analysis of runoff hydrograph based on linear time-invariant model. 2. Parameters for both linear time-invariant and linear time-variant models were calibrated with nine gaged watershed data, using a trial and error method. The resulting parameters including Gamma function argument, N and storage constant, K for linear time-invariant model were related statistically to watershed characteristic variables such as area, slope, length of main stream and the centroid length of the basin. 3. Average relative errors of the simulated peak discharge of calibrated runoff hydrographs by using linear time-variant and linear time-invariant models were shown to be 0.75 and 5.42 percent respectively to the peak of observed runoff hydrographs. Correlation coefficients for the statistical analysis in the same condition were shown to be 0.999 and 0.978 with a high significance respectively. Therefore, it can be concluded that the accuracy of a linear time-variant model is approaching more closely to the observed runoff hydrograph than that of a linear time-invariant model in the applied watersheds. 4. Average relative errors of the time to peak of calibrated runoff hydrographs by using linear time-variant and linear time-invariant models were shown to be 16.44 and 19.89 percent respectively to the time to peak of observed runoff hydrographs. Correlation coefficients in the same condition were also shown to be 0.999 and 0.886 with a high significance respectively. 5. It can be seen that the shape of simulated hydrograph based on a linear time- variant model is getting closer to the observed runoff hydrograph than that of a linear time-invariant model in the applied watersheds. 6. Two different models were verified with different rainfall-runoff events from data for the calibration by relative error and correlation analysis. Consequently, it can be generally concluded that verification results for the peak discharge and time to peak of simulated runoff hydrographs were in good agreement with those of calibrated runoff hydrographs.

• Korean Journal of Agricultural Science
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• v.46 no.3
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• pp.507-517
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• 2019

To follow up on a 2017 survey of tomato virus diseases, samples with virus-like symptoms were collected from the same areas (Buyeo-gun, Chungchungnam-Do and Daejeon, Korea) in 2018. While in 2017 mixed infections of Tomato mosaic virus with either Tomato yellow leaf curl virus (TYLCV) or Tomato chlorosis virus were detected, only TYLCV was detected in symptomatic samples in 2018. TYLCV amplicons of c.777 bp representing the coat protein (CP) coding region were cloned from the TYLCV positive samples, and the sequence data showed a 97.17% to 98.84% nucleotide and 98.45% to 99.22% amino acid identity with the 2017 Buyeo-gun isolate (MG787542), which had the highest amino acid (aa) sequence identity of up to 99.2% with four 2018 Buyeo-gun sequences (MK521830, MK521833, MK521834, and MK521835). The lowest aa sequence identity of 98.45% was found in a 2018 Daejeon isolate (MK521836); the distance between Buyeo-gun and Daejeon is about 45 km. Phylogenetic analysis indicated that the currently reported CP sequences are most closely related to Korean sequences from Masan (HM130912), Goseong (JN680149), Busan (GQ141873), Boseong (GU325634), and the 2017 isolate TYLCV-N (MG787543) in the 'Japan' cluster of TYLCV isolates and distinct from the 'China' cluster isolates from Nonsan (GU325632), Jeonju (HM130913) and Jeju (GU325633, HM130914). Our survey data from 2017 and 2018 suggest that TYLCV has become established in Korea and may be spread by whitefly vectors from weed reservoirs within the farm environment.

• Journal of Soil and Groundwater Environment
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• v.26 no.4
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• pp.27-43
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• 2021

Since climate factors, such as precipitation, temperature, etc., show repeated patterns every year, it can be said that future changes can be predicted by analyzing past climate data. As with groundwater, seasonal variations predominate. Therefore, when a drought occurs, the groundwater level is also lowered. Thus, a change in the groundwater level can represent a drought. Like precipitation, groundwater level changes also have a high correlation with drought, so many researchers use Standard Groundwater Level Index (SGI) to which the Standard Precipitation Index (SPI) method is applied to evaluate the severity of droughts and predict drought trends. However, due to the strong interferences caused by the recent increase in groundwater use, it is difficult to represent the droughts of regions or entire watersheds by only using groundwater level change data using the SPI or SGI methods, which analyze data from one representative observation station. Therefore, if the long-term groundwater level changes of all the provinces of a watershed are analyzed, the overall trend can be shown even if there is use interference. Thus, future groundwater level changes and droughts can be more accurately predicted. Therefore, in this study, it was confirmed that the groundwater level changes in the last 5 years compared with the monthly average groundwater level changes of the monitoring wells installed before 2015 appeared similar to the drought occurrence pattern. As a result of analyzing the correlation with the water storage yields of 3,423 agricultural reservoirs that do not immediately open their sluice gates in the cases of droughts or floods, it was confirmed that the correlation was higher than 56% in the natural state. Therefore, it was concluded that it is possible to re-evaluate agricultural droughts through long-term groundwater level change analyses.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.107-120
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• 2010

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 was assessed using the SLURP (semi-distributed land use-based runoff process), a physically based hydrological model. The fundamental input data (elevation, meteorological data, land use, soil, vegetation) was collected to calibrate and validate of the SLURP model for a 366.5 $km^2$ watershed including two agricultural reservoirs (Geumgwang and Gosam) located in Anseongcheon watershed. Then, the CCCma CGCM2 data by SRES (special report on emissions scenarios) A2 and B2 scenarios of the IPCC (intergovernmental panel on climate change) was used to assess the future potential climate change. The future weather data for the year, m ms, m5ms and 2amms was downscaled by Change Factor method through bias-correction using 3m years (1977-2006) weather data of 3 meteorological stations of the watershed. In addition, the future land uses were predicted by modified CA (cellular automata)-Markov technique using the time series land use data fromFactosat images. Also the future vegetation cover information was predicted and considered by the linear regression between monthly NDVI (normalized difference vegetation index) from NOAA AVHRR images and monthly mean temperature using eight years (1998-2006) data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.404-411
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• 2019

In this study, the HEC-HMS was applied to determine rainfall-runoff processes for the Gokgyuchun basin. Several sub-basins have large-scale reservoirs for agricultural needs and they store large amounts of initial runoff. Three infiltration methods were implemented to reflect the effect of initial loss by reservoirs: 'SCS-CN'(Scheme I), 'SCS-CN' with simple surface method(Scheme II), and 'Initial and Constant rate'(Scheme III). Modeling processes include incorporating three different methods for loss due to infiltration, Clark's UH model for transformation, exponential recession model for baseflow, and Muskingum model for channel routing. The parameters were calibrated using an optimization technique with trial and error method. Performance measures, such as NSE, RAR, and PBIAS, were adopted to aid in the calibration processes. The model performance for those methods was evaluated at Gangcheong station, which is the outlet of study site. Good accuracy in predicting runoff volume and peak flow, and peak time was obtained using the Scheme II and III, considering the initial loss, whereas Scheme I showed low reliability for storms. Scheme III did not show good matches between observed and simulated values for storms with multi peaks. Conclusively, Scheme II provided better results for both single and multi-peak storms. The results of this study can provide a useful tool for decision makers to determine master plans for regional flood control management.

• The Transactions of the Korea Information Processing Society
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• v.13 no.4
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• pp.199-207
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• 2024

Local reservoirs are crucial sources for agricultural water supply, necessitating stable water level management to prepare for extreme climate conditions such as droughts. Water level prediction is significantly influenced by local climate characteristics, such as localized rainfall, as well as seasonal factors including cropping times, making it essential to understand the correlation between input and output data as much as selecting an appropriate prediction model. In this study, extensive multivariate data from over 400 reservoirs in Jeollabuk-do from 1991 to 2022 was utilized to train and validate a water level prediction model that comprehensively reflects the complex hydrological and climatological environmental factors of each reservoir, and to analyze the impact of each input feature on the prediction performance of water levels. Instead of focusing on improvements in water level performance through neural network structures, the study adopts a basic Feedforward Neural Network composed of fully connected layers, batch normalization, dropout, and activation functions, focusing on the correlation between multivariate input data and prediction performance. Additionally, most existing studies only present short-term prediction performance on a daily basis, which is not suitable for practical environments that require medium to long-term predictions, such as 10 days or a month. Therefore, this study measured the water level prediction performance up to one month ahead through a recursive method that uses daily prediction values as the next input. The experiment identified performance changes according to the prediction period and analyzed the impact of each input feature on the overall performance based on an Ablation study.