• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.160-160
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• 2019

Water is a limited source that needs to be properly managed and distributed to the ever-growing population of the world. Rapid urbanization and development have increased the overall water demand of the world drastically. However, there is loss of billions of liters of water every year due to leakages in water distribution systems. Such water loss means significant financial loss for the utilities as well. World bank estimates a loss of $14 billion annually from wasted water. To address these issues and for the development of efficient and reliable leakage management techniques, high efforts have been made by the researchers and engineers. Over the past decade, various techniques and technologies have been developed for leakage management and leak detection. These include ideas such as pressure management in water distribution networks, use of Advanced Metering Infrastructure, use of machine learning algorithms, etc. For leakage detection, techniques such as acoustic technique, and in recent yeats transient test-based techniques have become popular. Smart Water Grid uses two-way real time network monitoring by utilizing sensors and devices in the water distribution system. Hence, valuable real time data of the water distribution network can be collected. Best results and outcomes may be produced by proper utilization of the collected data in unison with advanced detection and management techniques. Long term reduction in Non Revenue Water can be achieved by detecting, localizing and repairing leakages as quickly and as efficiently as possible. However, there are still numerous challenges to be met and future research works to be conducted in this field.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.578-578
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• 2016

In the past decade, many countries developed varies promising theories, methodologies and technologies for water resources management, such as Smart Water in Korea, eWater in Australia, Intelligent Water in Untied States, and Internet of Water in China. It is no exaggeration to say that Smart Water Management(SWM) will have a major role to play in addressing the global water challenges in the background of climate change, population growth and rapid urbanization. As a result, we can see major shifts taking place in the structure of the water industry, with a need for new approaches, skills, and water management policies. All these point towards a brighter future for the smart water sector and a new water paradigm, with applications and potential throughout the water cycle. However, each countries have their technology and industry standard system which may swift similar innovation and technology into different channels. In that sense, developing a common performance index and standard docking adapter for assessing Smart Water Management Initiatives(SWMI) is crucial for drawing a linkage of SWMI and SWMs to a way to implement advanced technology across Asia and Pacific. The performance index and standard docking adapter will facilitate quantitative and qualitative effects of utilized SWM techniques.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.149-149
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• 2022

Accurate quantitative evaluation of baseflow contribution to streamflow is imperative to address seasonal drought vulnerability, flood occurrence and groundwater management concerns for efficient and sustainable water resources management in watersheds. Several baseflow separation algorithms using recursive filters, graphical method and tracer or chemical balance have been developed but resulting baseflow outputs always show wide variations, thereby making it hard to determine best separation technique. Therefore, the current global shift towards implementation of artificial intelligence (AI) in water resources is employed to compare the performance of deep learning models with conventional hydrograph separation techniques to quantify baseflow contribution to streamflow of Piney River watershed, Tennessee from 2001-2021. Streamflow values are obtained from the USGS station 03602500 and modeled to generate values of Baseflow Index (BI) using Web-based Hydrograph Analysis (WHAT) model. Annual and seasonal baseflow outputs from the traditional separation techniques are compared with results of Long Short Term Memory (LSTM) and simple Gated Recurrent Unit (GRU) models. The GRU model gave optimal BFI values during the four seasons with average NSE = 0.98, KGE = 0.97, r = 0.89 and future baseflow volumes are predicted. AI offers easier and more accurate approach to groundwater management and surface runoff modeling to create effective water policy frameworks for disaster management.

• Journal of Environmental Science International
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• v.24 no.10
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• pp.1239-1251
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• 2015

Impervious areas have been expanded by urbanization and the natural structure of water circulation has been destroyed. The limits of centralized management for controlling storm water runoff in urban areas have been suggested. Low impact development (LID) technologies have been promoted as a crucial alternative, establishing a connection with city development plans to build green infrastructures in environmentally friendly cities. Thus, the improvement of water circulation and the control of nonpoint source were simulated through XP-SWMM (storm water and wastewater management model for experts) in this study. The application of multiple LID combination practices with permeable pavements, bioretention cells, and gutter filters were observed as reducing the highest runoff volume by up to 70%. The results from four different LID installation scenarios indicated that permeable paving is the most effective method for reducing storm water runoff. The rate of storm water runoff volume reduced as the rainfall duration extended. Based on the simulation results, each LID facility was designed and constructed in the target area. The LID practices in an urban area enable future studies of the analysis of the criteria, suitable capacity, and cost-efficiency, and proper management methods of various LID techniques.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.2
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• pp.121-132
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• 2018

Along with climate change, it is reported that the extreme climate events such as severe drought could cause difficulties of agricultural water supply. To minimize such damages, it is necessary to secure the agricultural water resources by using or saving the amount of irrigation water efficiently. The objectives of this study were to develop paddy water management scenarios and to evaluate their effectiveness on water saving. Three water management scenarios (a) deep irrigation with ponding depth of 20~80 mm (control, CT), (b) no/intermittent irrigation until paddy cracks (water management A, WM-A), and (c) intermittent irrigation with ponding depth under 20 mm (water management B, WM-B) were developed. Water saving effects were analyzed using monitored data from experimental paddy fields, and agricultural water supply was analyzed on a reservoir-scale using MASA model. The observed irrigation amounts were reduced by 21 % and 17 % for WM-A and WM-B compared to CT, respectively, and mainly occurred by the increase of effective rainfall. The simulation results showed that water management scenarios could reduce irrigation by 21~51 % and total inflow by 10~24 % compared to CT. The long-term simulated water level change of agricultural reservoir resulted in the decrease of dead level occurrence for WM-A and WM-B. The study results showed that WT-A and WT-B have more benefit than CT in the aspect of agricultural reservoir water supply.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1989.10a
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• pp.52-52
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• 1989

• 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.

• Water for future
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• v.16 no.4
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• pp.199-203
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• 1983

• Journal of Korean Society on Water Environment
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• v.38 no.4
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• pp.177-189
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• 2022

Nature-based Solutions (NbS) are defined as practical and technical approaches to restoring functioning ecosystems and biodiversity as a means to address socio-environmental challenges and provide human-nature co-benefits. This study reviews NbS-related literature to identify its key characteristics, techniques, and challenges for its application in climate-adaptive water management. The review finds that NbS has been commonly used as an umbrella term incorporating a wide range of existing ecosystem-based approaches such as low-impact development (LID), best management practices (BMP), forest landscape restoration (FLR), and blue-green infrastructure (BGI), rather than being a uniquely-situated practice. Its technical form and operation can vary significantly depending on the spatial scale (small versus large), objective (mitigation, adaptation, naturalization), and problem (water supply, quality, flooding). Commonly cited techniques include green spaces, permeable surfaces, wetlands, infiltration ponds, and riparian buffers in urban sites, while afforestation, floodplain restoration, and reed beds appear common in non- and less-urban settings. There is a greater lack of operational clarity for large-scale NbS than for small-scale NbS in urban areas. NbS can be a powerful tool that enables an integrated and coordinated action embracing not only water management, but also microclimate moderation, ecosystem conservation, and emissions reduction. This study points out the importance of developing decision-making guidelines that can inform practitioners of the selection, operation, and evaluation of NbS for specific sites. The absence of this framework is one of the obstacles to mainstreaming NbS for water management. More case studies are needed for empirical assessment of NbS.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09b
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• pp.1279-1280
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• 2005