구본운 Gu Bon-wun , 이태구 Lee Tae-gu , 강구 Kang Ku , 홍성구 Hong Seong-gu , 홍승길 Hong Seung-gil , 장태일 Jang Tae-il , 김진호 Kim Jin-ho , 박성직 Park Seong-jik

DOI: JKWST Vol.59(No.3) 1-10, 2017

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The aim of this study is to investigate the chemical properties and heavy metal concentration of soils in conventional and organic paddy. We sampled and analyzed topsoil (0~15 cm) and subsoil (15~30 cm) of conventional and organic paddy fields in Yongin and Anseong, South Korea. The statistical significance between groups was determined by Duncan’s multiple range test and correlation between soil properties was also analyzed. The results show that organic matter (OM) and T-N of conventional paddy soil were higher than those of organic paddy soil. However, higher T-P concentration was observed in organic paddy soil than conventional paddy soil. As, Pb, and Zn concentration in organic paddy soil were statistically lower than those in conventional paddy soil. The couple of water content (WC) & As, OM & T-N, T-P & P₂O₅, T-P & Zn, P₂O₅ & Zn, and Cr & Ni had a good positive correlation but the couple of WC & T-P, WC & Zn, T-P & As, and As & Zn had a strong negative correlation. It can be concluded that organic farming is beneficial to soil environment by reducing the amounts of organic matter, T-N, As, Pb, and Zn concentration in paddy soil when compared to conventional farming.

심현철 Shim Hyun Chul , 최경숙 Choi Kyung Sook

DOI: JKWST Vol.59(No.3) 11-19, 2017

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The decision-making process is the act of finding the best solution among various alternatives through comparison between various criteria based on objectives of the project, evaluation standard, and conditions. However, in practice it is not easy to simply decide the optimum decision, especially for selecting malfunctioning reservoirs because no systematic evaluation criteria or standard assessment process are available. Therefore, this study adopted AHP method, which is a MCDM (multi-criteria decision making technique) to identify the malfunctioning reservoirs for efficient management of reservoirs. Important criteria of the selection of malfunctioning reservoirs and priority weights of each criteria were determined based on results of expert’s survey under a stepwise hierarchical approach. The most important factor for the decision of malfunctioning reservoirs was obtained as Reservoir efficiency among the selected criteria including Reservoir efficiency decrease, Disaster Risk, Reservoir efficiency, Available water storage, Future water demand, Resident Needs. The AHP technique was applied on 11 reservoirs in Andong region to verify its applicability. Scoring method was applied for the comparison with the results of AHP method.

박진기 Park Jin Ki , 박종화 Park Jong Hwa

DOI: JKWST Vol.59(No.3) 21-28, 2017

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The main goal of this paper is to assess application of UAV (Unmanned Aerial Vehicle) remote sensing and GIS based images in detection and measuring of rice field drought area in South Korea. Drought is recurring feature of the climatic events, which often hit South Korea, bringing significant water shortages, local economic losses and adverse social consequences. This paper describes the assesment of the near-realtime drought damage monitoring and reporting system for the agricultural drought region. The system is being developed using drought-related vegetation characteristics, which are derived from UAV remote sensing data. The study area is 3.07 ㎢ of Wonbuk-myeon, Taean-gun, Chungnam in South Korea. UAV images were acquired three times from July 4 to October 29, 2015. Three images of the same test site have been analysed by object-based image classification technique. Drought damaged paddy rices reached 754,362 ㎡, which is 47.1 %. The NongHyeop Agricultural Damage Insurance accepted agricultural land of 4.6 % (34,932 ㎡). For paddy rices by UAV investigation, the drought monitoring and crop productivity was effective in improving drought assessment method.

장상민 Jang Sangmin , 이진영 Rhee Jinyoung , 윤선권 Yoon Sunkwon , 이태화 Lee Taehwa , 박경원 Park Kyungwon

DOI: JKWST Vol.59(No.3) 29-39, 2017

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In this study, the GPM (Global Precipitation Mission) IMERG (Integrated Multi-satellitE retrievals for GPM) rainfall data was verified and evaluated using ground AWS (Automated Weather Station) and radar in order to investigate the availability of GPM IMERG rainfall data. The SPI (Standardized Precipitation Index) was calculated based on the GPM IMERG data and also compared with the results obtained from the ground observation data for the Hoengseong Dam and Yongdam Dam areas. For the radar data, 1.5 km CAPPI rainfall data with a resolution of 10 km and 30 minutes was generated by applying the Z-R relationship (Z=200R^1.6) and used for accuracy verification. In order to calculate the SPI, PERSIANN_CDR and TRMM 3B42 were used for the period prior to the GPM IMERG data availability range. As a result of latency verification, it was confirmed that the performance is relatively higher than that of the early run mode in the late run mode. The GPM IMERG rainfall data has a high accuracy for 20 mm/h or more rainfall as a result of the comparison with the ground rainfall data. The analysis of the time scale of the SPI based on GPM IMERG and changes in normal annual precipitation adequately showed the effect of short term rainfall cases on local drought relief. In addition, the correlation coefficient and the determination coefficient were 0.83, 0.914, 0.689 and 0.835, respectively, between the SPI based GPM IMERG and the ground observation data. Therefore, it can be used as a predictive factor through the time series prediction model. We confirmed the hydrological utilization and the possibility of real time drought monitoring using SPI based on GPM IMERG rainfall, even though results presented in this study were limited to some rainfall cases.

장선숙 Jang Sun Sook , 김성준 Kim Seong Joon

DOI: JKWST Vol.59(No.3) 41-50, 2017

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The purpose of this study were to evaluate the effect of best management practices (BMPs) of Haean highland agricultural catchment (62.8 ㎢) 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 (R²) 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 °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.

오희상 Oh Heesang , 이한필 Rhee Han-pil

DOI: JKWST Vol.59(No.3) 51-62, 2017

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Since living environment has improved, waterfront space using and clear water demand have increased. Ministry of Environment (ME) designated polluted reservoir (worse than 4th grade) as a priority management reservoir to improve water quality (better than 3rd grade) accordingly. Minstry of Agriculture, Food and Rural Affairs (MAFRA) aims reservoir water quality 4th not 3rd grade. And water quality of agricultural reservoirs was not a great interest. For this reason, there are very few water quality monitoring data. However after designating as a priority management reservoir, reservoir manager should start water quality and flow monitoring of reservoirs and inflow streams. This process makes it possible setting complex model to accurate prediction of reservoir water quality and volume. Mulwang reservoir designated as a priority management reservoir in September 2014. In this study, BASINS/WinHSPF and EFDC-WASP were used to predict effect of water quality improvement countermeasures in Mulwang reservoir. To improve water quality of Mulwang reservoir, Siheung-si and Korea Rural Community Corporation (KRCC) established water quality improvement countermeasures. However result of simulation adapting these countermeasures cannot achieve 3rd grade. So 4 additional scenarios were adapted and the result satisfied 3rd grade. This study could help to establish water quality improvement countermeasure by using complex modeling.

김상민 Kim Sang Min

DOI: JKWST Vol.59(No.3) 63-70, 2017

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The purpose of this study was to calibrate the hydrologic parameters of SWAT model and analyze the daily runoff for the study watershed using SWAT-CUP. The Hardware watershed is located in Virginia, USA. The watershed area is 356.15 ㎢, and the land use accounts for 73.4 % of forest and 23.2 % of pasture. Input data for the SWAT model were obtained from the digital elevation map, landuse map, soil map and others. Water flow data from 1990 to 1994 was used for calibration and from 1997 to 2005 was for validation. The SUFI-2 module of the SWAT-CUP program was used to calibrate the hydrologic parameters. The parameters were calibrated for the highly sensitive parameters presented in previous studies. The P-factor, R-factor, R², Nash-Sutcliffe efficiency (NS), and average flow were used for the goodness-of-fit measures. The applicability of the model was evaluated by sequentially increasing the number of applied parameters from 4 to 11. In this study, 10-parameter set was accepted for calibration in consideration of goodness-of-fit measures. For the calibration period, P-factor was 0.85, R-factor was 1.76, R² was 0.51 and NS was 0.49. The model was validated using the adjusted ranges of selected parameters. For the validation period, P-factor was 0.78, R-factor was 1.60, R² was 0.60 and NS was 0.57.

박관용 Park Gwanyong , 권경석 Kwon Kyeong-seok , 이인복 Lee In-bok , 하태환 Ha Taehwan , 김락우 Kim Rack-woo , 이민형 Lee Minhyung

DOI: JKWST Vol.59(No.3) 71-81, 2017

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Organic dust generated inside livestock facilities includes toxic organic matters such as bacteria and endotoxin. Dust can cause respiratory disease for worker and livestock, and consequently, degradation of welfare and productivity. Influence of dust on livestock workers has been studied since the 1970s. However, exposure limit for cattle farmer has not been established, unlike exposure limit for pig and poultry farmer. Furthermore, study on air quality inside livestock facility, especially inside dairy farm has been rarely conducted in Korea. In this study, dust concentration of TSP, PM10, inhalable and respirable dust has been monitored in the commercial dairy house according to location and working activities. Bedding material inside the stall was one of the major sources of dust. The amount of dust was related to water content level of the bedding material. Dust concentration was relatively high in leeward location, and the highest concentration was measured during TMR mixing process. The maximum value of inhalable dust concentration was 29.1 times higher than the reference value as fine particles drop to the TMR mixer. Dust generated by TMR mixing was presumed to decrease by adjusting moisture and drop height of feed.

성충현 Seong Chounghyun , 황세운 Hwang Syewoon , 오찬성 Oh Chansung , 조재필 Cho Jaepil

DOI: JKWST Vol.59(No.3) 83-96, 2017

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This study presented a surface water quality modeling framework considering the spatial resolution of pollutant load estimation to better represent stream water quality characteristics in the Saemangeum watershed which has been focused on keeping its water resources sustainable after the Saemangeum embankment construction. The watershed delineated into 804 sub-watersheds in total based on the administrative districts, which were units for pollutant load estimation and counted as 739 in the watershed, Digital Elevation Model (DEM), and agricultural structures such as drainage canal. The established model consists of 7 Mangyung (MG) sub-models, 7 Dongjin (DJ) sub-models, and 3 Reclaimed sub-models, and the sub-models were simulated in a sequence of upstream to downstream based on its connectivity. The hydrologic calibration and validation of the model were conducted from 14 flow stations for the period of 2009 and 2013 using an automatic calibration scheme. The model performance to the hydrologic stations for calibration and validation showed that the Nash-Sutcliffe coefficient (NSE) ranged from 0.66 to 0.97, PBIAS were -31.0~16.5 %, and R² were from 0.75 to 0.98, respectively in a monthly time step and therefore, the model showed its hydrological applicability to the watershed. The water quality calibration and validation were conducted based on the 29 stations with the water quality constituents of DO, BOD, TN, and TP during the same period with the flow. The water quality model were manually calibrated, and generally showed an applicability by resulting reasonable variability and seasonality, although some exceptional simulation results were identified in some upstream stations under low-flow conditions. The spatial subdivision in the model framework were compared with previous studies to assess the consideration of administrative boundaries for watershed delineation, and this study outperformed in flow, but showed a similar level of model performance in water quality. The framework presented here can be applicable in a regional scale watershed as well as in a need of fine-resolution simulation.

서영민 Seo Youngmin , 최은혁 Choi Eunhyuk , 여운기 Yeo Woonki

DOI: JKWST Vol.59(No.3) 97-110, 2017

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This study investigates the efficiencies of machine learning models, including artificial neural network (ANN), generalized regression neural network (GRNN), adaptive neuro-fuzzy inference system (ANFIS) and random forest (RF), for reservoir water level forecasting in the Chungju Dam, South Korea. The models’ efficiencies are assessed based on model efficiency indices and graphical comparison. The forecasting results of the models are dependent on lead times and the combination of input variables. For lead time t = 1 day, ANFIS1 and ANN6 models yield superior forecasting results to RF6 and GRNN6 models. For lead time t = 5 days, ANN1 and RF6 models produce better forecasting results than ANFIS1 and GRNN3 models. For lead time t = 10 days, ANN3 and RF1 models perform better than ANFIS3 and GRNN3 models. It is found that ANN model yields the best performance for all lead times, in terms of model efficiency and graphical comparison. These results indicate that the optimal combination of input variables and forecasting models depending on lead times should be applied in reservoir water level forecasting, instead of the single combination of input variables and forecasting models for all lead times.