• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.164-175
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• 2019

The Tor Tong Daeng Irrigation Project with the irrigation area of 61,400 hectares is located in the Ping Basin of the Upper Central Plain of Thailand where farmers depended on both surface water and groundwater. In the drought year, water storage in the Bhumipol Dam is inadequate to allocate water for agriculture, and caused water deficit in many irrigation projects. Farmers need to find extra sources of water such as water from farm pond or groundwater as a supplement. The operation of Bhumipol Dam and irrigation demand estimation are vital for irrigation water allocation to help solve water shortage issue in the irrigation project. The study aims to determine the smart dam operation system to mitigate water shortage in this irrigation project via introduction of machine learning to improve dam operation and irrigation demand estimation via soil moisture estimation from satellite images. Via ANN technique application, the inflows to the dam are generated from the upstream rain gauge stations using past 10 years daily rainfall data. The input vectors for ANN model are identified base on regression and principal component analysis. The structure of ANN (length of training data, the type of activation functions, the number of hidden nodes and training methods) is determined from the statistics performance between measurements and ANN outputs. On the other hands, the irrigation demand will be estimated by using satellite images, LANDSAT. The Enhanced Vegetation Index (EVI) and Temperature Vegetation Dryness Index (TVDI) values are estimated from the plant growth stage and soil moisture. The values are calibrated and verified with the field plant growth stages and soil moisture data in the year 2017-2018. The irrigation demand in the irrigation project is then estimated from the plant growth stage and soil moisture in the area. With the estimated dam inflow and irrigation demand, the dam operation will manage the water release in the better manner compared with the past operational data. The results show how smart system concept was applied and improve dam operation by using inflow estimation from ANN technique combining with irrigation demand estimation from satellite images when compared with the past operation data which is an initial step to develop the smart dam operation system in Thailand.

• Environmental Engineering Research
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• v.18 no.2
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• pp.85-90
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• 2013

This study is an attempt to quantify rainwater utilization and miscellaneous water demand in Tokyo's 23 special wards, the core of the urban area in Tokyo, Japan, in order to elucidate the potential of further rainwater utilization. The rainwater utilization for miscellaneous appropriate water demands, including toilet flushing, air conditioning, and garden irrigation, were calculated for six different types of building: residential house, office, department store, supermarket, restaurant, and accommodation. Miscellaneous water demands in these different types of building were expressed in terms of equivalent rainfall of 767, 1,133, 3,318, 1,887, 16,574, and 2,227 (mm/yr), respectively, compared with 1,528 mm of Tokyo's average annual precipitation. Building types, numbers and its height were considered in this study area using geographic information system data to quantify miscellaneous water demands and the amount of rainwater utilization in each ward. Area precipitation-demand ratio was used to measure rainwater utilization potential for miscellaneous water demands. Office and commercial areas, such as Chiyoda ward, showed rainwater utilization potentials of <0.3, which was relatively low compared to those wards where many residential houses are located. This is attributed to the relatively high miscellaneous water demand. In light of rainwater utilization based on building level, the introduction of rainwater storage mechanisms with a storage depth of 50 mm for six different types of buildings was considered, and calculated as rainfall of 573, 679, 819, 766, 930, and 787 (mm), respectively. Total rainwater utilization using such storage facilities in each building from 23 wards resulted in the retention of 102,760,000 $m^3$ of water for use in miscellaneous applications annually, and this volume corresponded to 26.3% of annual miscellaneous water demand.

• Journal of Soil and Groundwater Environment
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• v.24 no.2
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• pp.23-37
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• 2019

To evaluate the available groundwater supply to the agricultural water demand in the future with the climate change scenarios for 40 sub-regions in Jeju Island, groundwater recharge and the available groundwater supply were estimated using water balance analysis method. Groundwater recharge was calculated by subtracting the actual evapotranspiration and direct runoff from the total amount of water resources and available groundwater supply was set at 43.6% from the ratio of the sustainable groundwater capacity to the groundwater recharge. According to the RCP 4.5 scenario, the available groundwater supply to the agricultural water demand is estimated to be insufficient in 2020 and 2025, especially in the western and eastern regions of the island. However, such a water shortage problem is alleviated in 2030. When applying the RCP 8.5 scenario, available groundwater supply can't meet the water demand over the entire decade.

• Journal of Korean Society of Water and Wastewater
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• v.11 no.3
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• pp.51-58
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• 1997

Determining sizes and the locations of reservoirs in the water distribution system(WDS) with multi-reservoirs is much difficult than that with single reservoir. The extended period simulation(EPS) models provide more comprehensive analysis of water distribution systems than the steady-state models can do. Therefore, EPS models should be applied to the WDS with multi-reservoirs. This study is to investigate the variations of required reservoir sizes and residual nodal pressures according to reservoir locations. In this study, EPS was applied to analyze an artificial and a real WDS under several water demand patterns. As a result, it was found that water demand patterns make no significant differences in the determining of the reservoir size, if they have similar peaking factors. And the variations of the peaking factor should be carefully checked in the design and the analysis of the WDS with multi-reservoirs, because the peaking factor itself will affect the minimum allowable sizes of reservoirs in those systems.

• Environmental Engineering Research
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• v.15 no.3
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• pp.135-140
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• 2010

With the various urban characteristics of each city, the existing water demand prediction, which uses average liter per capita day, cannot be used to achieve an accurate prediction as it fails to consider several variables. Thus, this study considered social and industrial factors of 164 local cities, in addition to population and other directly influential factors, and used main substance and cluster analyses to develop a more efficient water demand prediction model that considers unique localities of each city. After clustering, a multiple regression model was developed that proved that the $R^2$ value of the inclusive multiple regression model was 0.59; whereas, those of Clusters A and B were 0.62 and 0.74, respectively. Thus, the multiple regression model was considered more reasonable and valid than the inclusive multiple regression model. In summary, the water demand prediction model using principal component and cluster analyses as the standards to classify localities has a better modification coefficient than that of the inclusive multiple regression model, which does not consider localities.

• Journal of the Korea Convergence Society
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• v.6 no.6
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• pp.221-229
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• 2015

This study aims to identify and analyze the main factors that determine the properties and buying behavior in the premium bottled select and analyze the degree of impact on the relevant variables are premium water demand. When applied to the truncated negative binomial model to derive the study results: The results of estimating the variables that affect the demand for premium mineral water are as follows. Premium bottled water demand of this group my purchases with a choice between buying behavior variables are significantly higher than the relative population. To also do a good ingredient water, it appeared to be on a statistically significant positive effect on the demand for the more groups you purchase a premium bottled water for the purpose of receiving special feeling, just buy purpose is called to drinking water does not significantly affect to be analyzed. Among demographic characteristics it showed that demand for premium bottled water purchases are significantly higher in women than in men, professional / clerical job, such as the military, college graduates were more consumer research as significant in comparison to the relative population. Taste and package design factors of premium bottled mineral water among the select attribute factors are having a significant positive impact on the purchasing demand, local conditions and cost factors have been estimated to be insignificant.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.3
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• pp.1488-1494
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• 2011

In this paper, we propose an algorithm using linear regression model that forecasts the demand of heated water in winter. To supply heated water to apartments, stores and office buildings, Korea District Heating Corp.(KDHC) operates boilers including electric power generators. In order to operate facilities generating heated water economically, it is essential to forecast daily demand of heated water with accuracy. Analysis of history data of Kangnam Branch of KDHC in 2006 and 2007 reveals that heated water supply on previous day as well as temperature are the most important factors to forecast the daily demand of heated water. When calculated by the proposed regression model, mean absolute percentage error for the demand of heated water in winter of the year 2006 through 2009 does not exceed 3.87%.

• Journal of The Korean Society of Agricultural Engineers
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• v.47 no.2
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• pp.3-12
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• 2005

The objective of this study is securement of upland irrigation water using storage level management of small dams. However, it is not new development of water resources but securement of water using storage level management of existing dam. This study has enhanced the water utilization coefficient of dam, after extra available water had been calculated by application of periodical management storage level and this water is used to other water like the upland irrigation water demand. As the result of application, it can secure extra available water except the water requirement. Minimum extra available water except flood is about $20,000,000\;m^3$ and crop irrigation water demand of 10yr frequency is about $2,033,000\;m^3$ in Seongju. The utilization of crop irrigation water can be possible. And extra available water is about $3,102,000\;m^3$ in 2000, $1,959,000\;m^3$ in 2001 except flood period and crop irrigation water demand of 10yr frequency is about $2,272,000\;m^3$ in Donghwa. It is judged that extra available water cannot be used to crop irrigation water during the dry season in Dongwha. Consequently, when management storage level is determined and more efficient use of water is gotten like this study, water utilization coefficient will be enhanced.

• Journal of Korean Society of Water and Wastewater
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• v.22 no.1
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• pp.23-29
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• 2008

Throughout the analysis of field data from water distribution system, valid parameters were determined that can be included in the water service and design plan. This study investigates water consumption patterns to understand the variation of water-demand structures utilizing the pattern analysis of domestic purpose water. Water use data were collected by a public water resources management firm in Korea, Kwater, for 140 houses monitored during three years. Flow meters were installed at the faucet for drinking water, the shower booth, the laundry machine, bathroom sink, toilet, and garden faucet. Data was filtered using multiple physically meaningful criteria to improve analysis credibility. Mann Kendall and Spearman's Rho tests were used to carry out the analysis. Distinct factors of water consumption patterns can be determined for both increasing and decreasing trends of water use. Throughout the data analysis, the characterization of terms was classified and analyzed by the condition of the location of water-demand. Analysis of this data provide a physical basis for the parameter configuration of a reasonable design for a domestic water demand prediction model.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.170-170
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• 2023

Providing safe and readily available water is vital to maintain public health. One of the most prevalent methods to prevent the spread of waterborne diseases is applying chlorine injection to the treated water before distribution. During the water transmission and distribution, the chlorine will experience a reduction, which can imply potential risks for human health if it falls below the minimum threshold. The ability to determine the appropriate initial intensity of chlorine at the source would be significant to prevent such problems. This study proposes two methods that integrate hydraulic and water quality modeling to determine the suitable intensity of chlorine to be injected into the source water to maintain the minimum chlorine concentration (e.g., 0.2 mg/l) at each demand node. The water quality modeling employs the first-order decay to estimate the rate of chlorine reduction in the water. The first method utilizes a backtracking algorithm to trace the path of water from the demand node to the source during each time step, which helps to accurately determine the travel time through each pipe and node and facilitate the computation of time-dependent chlorine decay in the water delivery process. However, as a backtracking algorithm is computationally intensive, this study also explores an alternative approach using a water age. This approach estimates the elapsed time of water delivery from the source to the demand node and calculate the time-dependent reduction of chlorine in the water. Finally, this study compares the outcomes of two approaches and determines the suitable and effective method for calculating the chlorine intensity at the source to maintain the minimum chlorine level at demand nodes.