• Journal of Environmental Science International
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• v.11 no.12
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• pp.1275-1279
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• 2002

This study was performed to improve water demand estimation and analize correlation between generation of domestic sewage and domestic water use. To improve the prediction of water demand estimation, new water demand equation was developed. The results is as follows. $InQ_t = {\beta}_0+{\beta}_1InP_t+{\beta}_2InY_t+{\beta}_3InH_t+{varepsilon}_t$By using the statistical analysis of the "generation of domestic sewage" and "domestic water use", the regression equation between them is formed. The result is as follows. Generation of domestic sewage : 0.8487 $\times$ Domestic water use + 684.57 ($R^2$= 0.972)>$R^2$= 0.972)

• Journal of Korean Society of Water and Wastewater
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• v.21 no.1
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• pp.75-82
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• 2007

When one forecasts urban water demand in a long-term, multivariate model can give more benefits than per capita requirement model. However, the former has shortcomings in that statistically high explanatory power cannot be obtained well, and change in customer behavior cannot be considered. If the past water consumption effects the future water demand, dynamic model may describe real water consumption data better than static model, i.e. the existing multivariate model. On these grounds, this study built dynamic model using system dynamics. From a case study in Seoul and Busan city, dynamic model was expected to forecast water demand more descriptively and reliably.

• Journal of Digital Convergence
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• v.16 no.7
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• pp.1-8
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• 2018

In Korea, water supply capacity and facility investments had been emphasized around the 1980s. The water pricing have gained focuses in water policy since the 1990s. This study analyzes a water demand and estimates the relation of water demand and other socio-economic variable, using econometric models on the city of Busan. Water price and income are two key elements to explain water demand. Modeling approach using translog function provides better results, and water demand responds positively to population and income. Energy and water prices are negative factors in deciding water demand. It is requested that water pricing needs to reflect more production costs. Alternative approaches such as water saving facilities by household and use of digital water information should be emphasized for efficient water management in a local community.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.185-185
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• 2023

Agricultural water demand is considered as the major sector of water withdrawal due to irrigation. The majority part of the global agricultural field depends on various irrigation techniques. Therefore, a timely and sufficient supply of water is the most important requirement for agriculture. Irrigation is implemented in different ways in various land surface models, it can be modeled empirically based on observed irrigation rates or by calculating water supply and demand. Certain models can also calculate the irrigation demand as per the soil water deficit. In these implementations, irrigation is typically applied uniformly over the irrigated land regardless of crop types or irrigation techniques. Whereas, the latest version of Community Land Model (CLM) in the Community Terrestrial Systems Model (CTSM) uses a global distribution map of irrigation with 64 crop functional types (CFTs) to simulate the irrigation water demand. It can estimate irrigation water withdrawal from different sources and the amount or the areas irrigated with different irrigation techniques. Hence, we set up the model for the simulation period of 16 years from 2000 to 2015 to analyze the global irrigation demand at a spatial resolution of 1.9° × 2.5°. The simulated irrigation water demand is evaluated with the available observation data from FAO AQUASTAT database at the country scale. With the evaluated model, this study aims to suggest new sustainable scenarios for the ratios of irrigation water withdrawal, high depending on the withdrawal sources e.g. surface water and groundwater. With such scenarios, the CFT maps are considered as the determining factor for selecting the areas where the crop pattern can be altered for a sustainable irrigation water management depending on the available withdrawal sources. Overall, our study demonstrate that the scenarios for the future sustainable water resources management in terms of irrigation water withdrawal from the both the surface water and groundwater sources may overcome the excessive stress on exploiting the groundwater in major river basins globally.

• Journal of Soil and Groundwater Environment
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• v.23 no.1
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• pp.92-105
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• 2018

In this study, the projected land use area in 2030 for major crop production was estimated in Jeju Island using land cover map, and corresponding agricultural water demand for 40 sub-regions was quantitatively assessed using the future climate change scenario (RCP 4.5). Estimated basic unit of water demand in 2030 was the highest in the western region, and the lowest in the eastern region. Monthly maximum agricultural water demand analysis revealed that water demand in August of 2030 substantially increased, suggesting the climate of Jeju Island is changing to a subtropical climate in 2030. Agricultural water demand for sub-region in 2030 was calculated by multiplying the target area of the water supply excluding the area not in use in winter season by the basic unit of water demand, and the maximum and minimum values were estimated to be $306,626m^3/day$ at Seogwipo downtown region and $77,967m^3/day$ at Hallim region, respectively. Consequently, total agricultural water demand in Jeju Island in 2030 was estimated to be $1,848,010m^3/day$.

• Journal of Korean Society of Water and Wastewater
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• v.37 no.6
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• pp.363-373
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• 2023

Numerous studies have established a correlation between sociodemographic characteristics and water usage, identifying population as a primary independent variable in mid- to long-term demand forecasting. Recent dramatic sociodemographic changes, including urban concentration-rural depopulation, low birth rates-aging population, and the rise in single-person households, are expected to impact water demand and supply patterns. This underscores the necessity for operational and managerial changes in existing water supply systems. While sociodemographic characteristics are regularly surveyed, the conducted surveys use aggregate units that do not align with the actual system. Consequently, many water demand forecasts have been conducted at the administrative district level without adequately considering the water supply system. This study presents an upward water demand forecasting model that accurately reflects real water facilities and consumers. The model comprises three key steps. Firstly, Statistics Korea's SGIS (Statistical Geological Information System) data was reorganized at the DMA level. Secondly, DMAs were classified using the SOM (Self-Organizing Map) algorithm to consider differences in water facilities and consumer characteristics. Lastly, water demand forecasting employed the PCR (Principal Component Regression) method to address multicollinearity and overfitting issues. The performance evaluation of this model was conducted for DMAs classified as rural areas due to the insufficient number of DMAs. The estimation results indicate that the correlation coefficients exceeded 0.9, and the MAPE remained within approximately 10% for the test dataset. This method is expected to be useful for reorganization plans, such as the expansion and contraction of existing facilities.

• Journal of Environmental Science International
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• v.22 no.5
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• pp.639-649
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• 2013

Over 96.2% of the agricultural water in Jeju Island is obtained from groundwater and there are quite distinct characteristics of agricultural water demand/supply spatially because of regional and seasonal differences in cropping system and rainfall amount. Land use for cultivating crops is expected to decrease 7.4% (4,215 ha) in 2020 compared to 2010, while market garden including various vegetable crop types having high water demand is increasing over the Island, especially western area having lower rainfall amount compared to southern area. On the other hand, land use for fruit including citrus and mandarin having low water demand is widely distributed over southern and northern part having higher rainfall amount. The agricultural water demand of $1,214{\times}10^3\;m^3/day$ in 2020 is estimated about 1.39 times compared to groundwater supply capacity of $874{\times}10^3\;m^3/day$ in 2010 with 42.4% of eastern, 103.1% of western, 61.9% of southern, and 77.0% of northern region. Moreover, net secured amount of agricultural groundwater would be expected to be much smaller due to regional disparity of water demand/supply, the lack of linkage system between the agricultural water supply facilities, and high percentage of private wells. Therefore, it is necessary to ensure the total net secured amount of agricultural groundwater to overcome the expected regional discrepancy of water demand and supply by establishing policy alternative of regional water supply plan over the Island, including linkage system between wells, water tank enlargement, private wells maintenance and public wells development, and continuous enlargement of rainwater utilization facilities.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.26 no.6
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• pp.757-764
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• 2002

Chlorination dosage in water treatment plant of field is determined by chlorination demand experiment through two or three hours after raw water was sampled in inflow. It is impossible to continuously control for real time because the sampled water is adapted chlorination dosage after water treatment process had been proceeded. Therefore in this study, we will design informal chlorination demand system, this designed system will be experimented as to water quality and accuracy of control in various conditions. Throughout these experimental results, we will revise the system and the revised system is enable to optimal control of chlorination dosage. Finally, we have developed chlorination demand system, which can automatically determination of chlorination dosage to be determined according to variety of raw water quality inflow in water treatment plant.

• Proceedings of the KSME Conference
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• 2000.04b
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• pp.807-812
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• 2000

Chlorination dosage in water treatment plant of field is determined by chlorination demand experiment through two or three hours after raw water was sampled in inflow. It is impossible to continuously control fer real time because sampled water is adapted chlorination dosage after water treatment process had been proceeded. Therefore in this study, we will design informal chlorination demand system this designed system will be experimented as to water quality and accuracy of control in various conditions. Throughout these. experimental results, we will revise the system and revised system is enable to optimal control of chlorination dosage. Finally, We have developed chlorination demand system, which can automatically determination of chlorination dosage to be determined according to variety of raw water quality inflow in water treatment plant.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.156-156
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• 2022

Explicitly spatially distributed and reliable data on industrial water demand is very much important for both policy makers and researchers in order to carry a region-specific analysis of water resources management. However, such type of data remains scarce particularly in underdeveloped and developing countries. Current research is limited in using different spatially available socio-economic, climate data and geographical data from different sources in accordance to predict industrial water demand at finer resolution. This study proposes a random forest regression (RFR) model to predict the industrial water demand at 0.50× 0.50 spatial resolution by combining various features extracted from multiple data sources. The dataset used here include National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer Suite (VIIRS) night-time light (NTL), Global Power Plant database, AQUASTAT country-wise industrial water use data, Elevation data, Gross Domestic Product (GDP), Road density, Crop land, Population, Precipitation, Temperature, and Aridity. Compared with traditional regression algorithms, RF shows the advantages of high prediction accuracy, not requiring assumptions of a prior probability distribution, and the capacity to analyses variable importance. The final RF model was fitted using the parameter settings of ntree = 300 and mtry = 2. As a result, determinate coefficients value of 0.547 is achieved. The variable importance of the independent variables e.g. night light data, elevation data, GDP and population data used in the training purpose of RF model plays the major role in predicting the industrial water demand.