• Water Engineering Research
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• v.5 no.2
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• pp.55-68
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• 2004

The GLEAMS (Groundwater Loading Effects of Agricultural Management System, version 3.0) water quality model was used to predict hydrology and water quality and to evaluate the effects of soil types from a cattle-grazed pasture field of Bermuda-Rye grass rotation with poultry litter application as a fertilizer in North Alabama. The model was applied and evaluated by using four years (1999-2002) of field-measured data to compare the simulated results for the 2.71- ha Summerford watershed. $R^2$ values between observed and simulated runoff, sediment yields, TN, and TP were 0.91, 0.86, 0.95, and 0.69, respectively. EI (Efficiency Index) of these parameters were 0.86, 0.67, 0.70, and 0.48, respectively. The statistical parameters indicated that GLEAMS provided a reasonable estimation of the runoff, sediment yield, and nutrient losses at the studied watershed. The soil infiltration rates were compared with the rainfall events. Only high intensity rainfall events generated runoff from the watershed. The measured and predicted infiltration rates were higher during dry soil conditions than wet soil conditions. The ratio of runoff to precipitation was ranging from 2.2% to 8.8% with average of 4.3%. This shows that the project site had high infiltration and evapotranspiration which generated the low runoff. The ratio of runoff to precipitation according to soil types by the GLEAMS model appeared that Sa (Sequatchie fine sandy loam) soil type was higher and Wc (Waynesboro fine sandy loam, severely eroded rolling phase) soil type relatively lower than the weighted average of the soil types in the watershed. The model under-predicted runoff, sediment yields, TN, and TP in Wb (Waynesboro fine sandy loam, eroded undulating phase) and Wc soil types. General tendency of the predicted data was similar for all soil types. The model predicted the highest runoff in Sa soil type by 105% of the weighted average and the lowest runoff in Wc soil type by 87% of the weighted average

• Journal of Korea Water Resources Association
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• v.38 no.7 s.156
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• pp.575-584
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• 2005

The judgement model to warn of possible pollution accident is constructed by multi-perceptron, multi layer neural network, neuro-fuzzy and it is trained stability, notice, and warming situation due to developed standard axis. The water quality forecasting model is linked to the runoff forecasting model, and joined with the judgement model to warn of possible pollution accident, which completes the artificial intelligence warning system. And GUI (Graphic User Interface) has been designed for that system. GUI screens, in order of process, are main page, data edit, discharge forecasting, water quality forecasting, warming system. The application capability of the system was estimated by the pollution accident scenario. Estimation results verify that the artificial intelligence warning system can be a reasonable judgement of the noized water pollution data.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.52-59
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• 2005

The goal of this project is to estimate the instream flow of the Han River Basin to ensure the adequate supply of suitable quality water for preservation and enhancement of aquatic ecosystems. A applied model is Physical Habitant Simulation System(PHABSIM) of Instream Flow Incremental Methodology(IFIM). The parameters which are needed to simulation by PHABSIM such as flow depth, velocity distribution and channel cover with cross section data are obtained by field survey. The Habitat Suitability Criteria with the application of univariate curve on Zacco platypus as a target species was able to be established by conducting the field investigation. The estimated results of ecological recommended instream flow by this study has important meanings that the future river management have to seriously take into account for the natural environment and functions of river system.

• Korean Journal of Remote Sensing
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• v.22 no.3
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• pp.183-197
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• 2006

Combinations of visible and near-infrared (NIR) bands in an image are widely used for estimating vegetation vigor and productivity. Using this approach to understand within-field grain crop variability could allow pre-harvest estimates of yield, and might enable mapping of yield variations without use of a combine yield monitor. The objective of this study was to estimate within-field variations in crop yield using vegetation indices derived from hyperspectral images. Hyperspectral images were acquired using an aerial sensor on multiple dates during the 2003 and 2004 cropping seasons for corn and soybean fields in central Missouri. Vegetation indices, including intensity normalized red (NR), intensity normalized green (NG), normalized difference vegetation index (NDVI), green NDVI (gNDVI), and soil-adjusted vegetation index (SAVI), were derived from the images using wavelengths from 440 nm to 850 nm, with bands selected using an iterative procedure. Accuracy of yield estimation models based on these vegetation indices was assessed by comparison with combine yield monitor data. In 2003, late-season NG provided the best estimation of both corn $(r^2\;=\;0.632)$ and soybean $(r^2\;=\;0.467)$ yields. Stepwise multiple linear regression using multiple hyperspectral bands was also used to estimate yield, and explained similar amounts of yield variation. Corn yield variability was better modeled than was soybean yield variability. Remote sensing was better able to estimate yields in the 2003 season when crop growth was limited by water availability, especially on drought-prone portions of the fields. In 2004, when timely rains during the growing season provided adequate moisture across entire fields and yield variability was less, remote sensing estimates of yield were much poorer $(r^2<0.3)$.

• Journal of Korean Society of Environmental Engineers
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• v.31 no.9
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• pp.765-774
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• 2009

Fiber Dyeing and Finishing facility has been recognized as an important pollution source due to its consumption of large volumes of water and chemicals. Unit mass discharge for the conventional water quality parameters such as flowrate, SS, $BOD_5,\;COD_{Mn},\;COD_{Cr}$, TN, TP were estimated. To represent the respective industries, three companies were carefully selected based on its manufacturing goods, flowrate and location at various unit operations and processes. More than 90% of decrease in unit mass estimation between influent and effluent of BOD was observed. But the values themselves were similar to those of Fiber Manufacturing facility due to the high loadings of organic matter. Biodegradability of influent was almost three times higher than that of effluent. Unit mass discharge estimations of unit process (estimated in this study) based on space, products and raw material were similar to those of composite process (estimated by National Institute of Environmental Research), while big difference was observed in the other factors. Unit mass discharge factors calculated in this study can be used as the reference for the estimation of water pollution loading costs in Nakdong river basin. For the effective water pollution control and management, it is essential to characterize the various types of water quality parameters from the effluents of individual industrial wastewater treatment plants.

• Korean Journal of Environmental Agriculture
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• v.18 no.1
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• pp.18-23
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• 1999

A numerical model of flow velocity in the standing water system is presented. This model(RMA-2), based on the 2-dimensional unsteady momentum and continuity equations, uses finite element techniques to simulate the distribution of velocity over a spatial location of lakes. The present model represents an improvement over existing numerical water quality models in that it can model the unsteady state and can, therefore, cope with time with a spatial location of standing waters such as lakes and large reservoirs. The model thus allows the engineer to do more accurate estimation of water flows and thus water qualities in standing waters where directions and velocities of the flow become more important for the simulation of the water quality than in running waters. Tests for the data collected in the lake "Paldang" indicates that the model works well under limited circumstances. However, to be more accurate estimation of velocity with the present model, accumulation of data for the measurement of velocities and renovation of geometrical conditions of the lake would be needed.

• Coupled systems mechanics
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• v.11 no.1
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• pp.79-91
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• 2022

Models for water treatment processes include simulation, i.e., modelling of water quality, flow hydraulics, process controls and design. Water treatment processes are inherently dynamic because of the large variations in the influent water flow rate, concentration and composition. Moreover, these variations are to a large extent not possible to control. Mathematical models and computer simulations are essential to describe, predict and control the complicated interactions of the water treatment processes. An accurate description of such systems can therefore result in highly complex models, which may not be very useful from a practical, operational point of view. The main objective is to combine knowledge of the process dynamics with mathematical methods for processes estimation and identification. Good modelling practice is way to obtain this objective and to improve water treatment processes(its understanding, design, control and performance- efficiency). By synthesize of existing knowledge and experience on good modelling practices and principles the aim is to help address the critical strategic gaps and weaknessesin water treatment models application.

• Korean Journal of Soil Science and Fertilizer
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• v.48 no.5
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• pp.499-504
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• 2015

Decision making by farmers regarding irrigation is critical for crop production. Therefore, the precision irrigation technique is very important to improve crop quality and yield. Recently, much attention has been given to remote sensing of crop canopy temperature as a crop water-stress indicator, because it is a scientifically based and easily applicable method even at field scales. This study monitored a series of time-variant canopy temperature of cucumber under three different irrigation treatments: under-irrigation (control), optimal-irrigation, and over-irrigation. The difference between canopy temperature ($T_c$) and air temperature ($T_a$), $T_c-T_a$, was calculated as an indicator of cucumber water stress. Vapor pressure deficit (VPD) was evaluated to define water stress on the basis of the temperature difference between leaf and air. The values of $T_c-T_a$ was negatively related to VPD; further, cucumber growth in the under- and over-irrigated fields showed water stress, in contrast to that grown in the optimally irrigated field. Thus, thermal infrared measurements could be useful for evaluating crop water status and play an important role in irrigation scheduling of agricultural crops.

• Journal of the Korean Society of Marine Environment & Safety
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• v.13 no.1 s.28
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• pp.93-102
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• 2007

Particle materials sink in bottom and dissolved inorganic substances release from sediment and many kinds of materials continuously exchange in sediment and water column as well as transfer and transformation in sediment. The study of sediment quality means the state of sediment pollution relation of the water quality, sediment biota, materials fluxes between sediment and water column, transformation of materials in sediment is being important in recent. The state of sediment quality imply that the history of water pollution for long time, because the sediment quality does not change temporally. The sediment quality of bottom water can be used as a good indicator of pollution at present and in future. The major index of sediment qualities are the content of nutrients and hazard materials such as metals, Ignition Loss (IL), Total Sulfur (TS), Oxidation Reduction Potential (ORP), sediment COD, color, odor and the release of nutrients from sediment. However, there are some arguments between researchers about compare to estimation of sediment quality and sampling and analysis of sediment. In this study, I will introduce the method of sediment sampling, analyzing and estimating of the sediment pollution.

• Journal of Environmental Policy
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• v.6 no.1
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• pp.83-109
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• 2007

This study evaluates citizen's willingness-to-pay for the benefits from improved water quality of the Taehwa river in Ulsan, Korea, using a contingent valuation method with double-bounded dichotomous choice. The estimation results of the bivariate probit model shows the amounts of willingness-to-pay are monthly 3,458.5 Korean Won per household and yearly 14,760 million Korean Won for total households in Ulsan, Korea. These estimates are equivalent to the social values of improved water quality of the Taehwa river. This study also tests the inter-dependence between two answers, which may occur in the responses of the questions for the double-bounded dichotomous choice, and all the null hypotheses on the inter-dependence are rejected in this study.