Development of Water Supply Plans

Development of Water Supply Plans Using System Dynamics Approach in the Han

River Basin, South Korea

Gunhui Chung1, Myeonho Jeon2, Joong Hoon Kim3, and Tae-Woong Kim4

1 Research Center for Disaster Prevention Science and Technology, Korea University, Seoul, 136-713, Korea; PH (+82-2) 928-1428; FAX (+82-2) 928-1426; e-mail:

gunhui@korea.ac.kr

2 Department of Civil and Environmental Engineering, Hanyang University, Seoul, 133-791, Korea; PH (+82-31) 436-8151; FAX (+82-31) 436-8170; e-mail:

dektol79@hanyang.ac.kr

3 School of Architecture, Civil, and Environmental Engineering, Korea University, Seoul, 136-713, Korea; PH (+82-2) 3290-3316; FAX (+82-2) 928-1426; e-mail:

jaykim@korea.ac.kr

4 Corresponding Author, Department of Civil and Environmental Engineering, Hanyang University, Ansan, 426-791, Korea; PH (+82-31) 400-5184; FAX (+82-31) 436-8170; e-mail: twkim72@hanyang.ac.kr

ABSTRACT

The sustainable development of water resources has been an important issue particularly. Therefore, the long-term water supply plan in a basin scale needs to be evaluated with the consideration of future uncertainties. However, the complexity of the model and future uncertainties cause the difficulty to analyze the water supply model under the various scenarios. System dynamics approach is used to develop a water supply system in the Han River basin, South Korea. The developed model is calibrated by the water supply data and the basin condition is evaluated with respect to the water availability. The future water supply scenarios are developed and the water excess and shortage are evaluated under the various water supply scenarios. The main drag forces to cause this water shortage in the basin are the increasing population in urban areas and future climate change. The system dynamics approach helps the decision maker and stakeholders to understand the model structures, scenarios, and the corresponding results. The developed model is a useful tool to evaluate the long-term water supply plan when the policy maker develops a city development plan including water supply and achieve consensus.

Keywords: Water Supply plan, Reservoir Operation, System Dynamics Approach, Scenario Analysis

INTRODUCTION

As environmental issues becomes important when developing cities, the evaluation of the availability of water supply and sustainability have to be assessed to cope with

future water demand and environmental requirement. Therefore, water supply systems have been developed to calculate water allocation over the entire basin under the future uncertain conditions. A water supply system is a comprehensive system of components that include water sources, users, treatment plants, a transportation network, and reuse facilities (Chung et al, 2008).

The input data to water supply system such as the future precipitation and water demand are involved with uncertainties which make the simulation results inaccurate. Therefore, it is important to take account of the future uncertainties in a long range water supply plan.

The future precipitation is usually predicted by General Circulation Model (GCM) which is a mathematical model to calculate the atmospheric or oceanic circulation based on the Navier-Stokes equations. There are various types of GCM coupling to one or more ice sheet models or chemical transport models. Different models provide the different future prediction results (Figure 1) which is mainly related to the unknown future conditions of population, industry, and technology.

Figure 1. Temperature predictions from some climate models assuming the SRES A2 emissions scenario (https://www.360docs.net/doc/1611189137.html,/wiki/Global_climate_model) To consider the full uncertainties on future climate condition in water supply systems, many research have been conducted in the form of mathematical models (Ocanas and Mays, 1981a and b; Huang and Loucks, 2000; Ejeta et al, 2004) or system dynamics approaches (Simonovic et al, 1997; Palmer et al, 2000; Passell et al, 2002; Stave, 2003, Sumer et al, 2004).

In this study, a water supply system is developed using system dynamics approaches considering the future precipitation uncertainty in the Han River basin, Korea. Two climate change scenarios from KMA_ECHO-G and BCCR_BCM2 model are selected as the future precipitation and water shortage is evaluated.

WATER SUPPLY SYSTEMS

The results from GCM are the spatial average precipitation in a cell which covers the entire Korea peninsula. Therefore, the local precipitation is generated using a downscaling method such as MM5 or K-Nearest Neighbor (KNN) algorithm. The characteristics of the two selected model is listed in Table 1.

The annual average precipitation in the Han River basin is about 1,200 mm, 70% of which is concentrated from June to September. The Han River basin is located in the center of the Korean Peninsula (Figure 2), covers 23% of the territory of South Korea (around 23,000 km2). The population of the basin, 41% of the national total, almost tripled between 1966 and 2005, from about 7 million to almost 20 million. Nevertheless, urban areas account for just 1% of the basin. Forests make up 78%, cultivated areas 16%, and grasslands and water bodies 5% of the basin (https://www.360docs.net/doc/1611189137.html,/index.php/Facing_Water_Challenges_in_the_Han_River_Basin,_K orea:A_WWDR3_Case_Study). The Han River basin is divided into 24 sub-basins named from 1001 to 1024.

Figure 2. Han River basin, Korea

Table 1. Climate change scenarios

Content Scenario 1 Scenario 2

Climate change scenario A1B A2

General Circulation Model (GCM)/Downscaling

Model

KMA_ECHO-G/MM5 BCCR_BCM2/KNN

Predicted data period 2010~2100 2010~2099

Spatial range Korea peninsula

(27㎞)

Seoul station

Figure 3 shows the ten-day precipitations in sub-basins. The sub-basin located in the upstream of the basin (1001) has the largest amount of rainfall during the flood season. The overall rainfall patterns at these sub-basins show almost identical. However, the predicted rainfall patterns in 2050, 2099, and 2100 (Figure 4) are significantly different with respect to location, time, and prediction model (scenario). For example, no peak rainfall is happened during July in the predicted precipitation in 2100 from scenario 1 and rainfall is almost equally distributed over the entire year. The predicted patterns using scenario 2 in 2050 and 2099 have still peak rainfall from June to August, but the sizes are different.

Figure 3. Ten-day precipitations in year 2003 over sub-basins, the Han River basin, Korea

The water demand in 2003 from Water Plan (2006~2020) is listed in Table 2. The municipal, agricultural, and industrial demands in each sub-basin are considered in the water supply system. Figure 5 shows an example of the developed water supply system

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in sub-basin 1006 using system dynamics approach. Using water balance equation, the water budget is calculated.

Table 2. Average water demand at sub-basins in 2003, the Han River basin, Korea (unit:

x106m3) Sub-basin ID Municipal Demand Agricultural Demand Industrial Demand 1001 18.56 22.40 0.00 1002 12.67 60.94 1.02 1003 43.69 105.41 61.46 1004 47.76 229.79 14.14 1005 4.87 65.73 0.00 1006 66.08 123.89 10.47 1007 85.76 393.79 96.17 1008 0.00 0.00 0.00 1009 0.10 4.79 0.00 1010 16.50 51.48 0.00 1011 7.72 19.07 0.00 1012 16.49 36.30 0.00 1013 51.56 40.90 0.78 1014 12.02 84.19 5.50 1015 17.11 31.63 0.47 1016 56.60 27.85 30.77 1017 0.40 24.72 0.05 1018 1731.14 98.19 284.10 1019 441.66 187.48 245.90 1020 0.00 0.00 0.00 1021 2.25 45.33 0.00 1022 67.46 224.28 10.95 1023 24.29 120.77 4.08 1024 1.29 11.47 0.36

Figure 4. Ten-day precipitations in different years using two downscaling methods in the

Han River basin, Korea

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Figure 5. Water supply systems developed in sub-basin 1006, the Han River basin, Korea

RESULTS AND DISCUSSION

The water supply system is simulated for a year in ten-day time step. The predicted precipitation is used as the inflow to the system. Figure 6 shows the water shortage in sub-basin 1004 where is located in the upstream end of the south part of the Han River basin. Due to the increasing total amount of rainfall and timely distributed rainfall pattern in the future, the water shortage is decreased in the sub-basin. The water shortage is caused because the sub-basin is not supplied from external water sources such as reservoirs or rivers located in outside of the sub-basin. Therefore, the alternative water supply plan is necessary in this area.

However, the future uncertainties are not fully accounted in the system, thus, the more future climate change and water demand scenarios need to be evaluated in the future study. The reservoir operation rules also need to be developed to account the

future data condition.

Figure 6. Water shortage in sub-basin 1006 using different climate change

scenarios in the Han River basin, Korea

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ACKNOWLEDGEMENT

This work was supported by National Research Foundation (NRF) of Korea Grant funded by the Korea government (MEST) (No. 2009-0072476).

REFERENCES

Chung, G., Lansey, K., Blowers, P., Brooks, P., Ela, W., Stewart, S., and Wilson, P.

(2007). “A general water supply planning model: Evaluation of decentralized

treatment.” Environmental Modelling & Software, Vol. 23, No. 7, pp. 893. Ejeta, M.Z., McGuckin, T., and Mays, L.W. (2004). “Market exchange impact on water supply planning with water quality.” Journal of Water Resources Planning

and Management, Vol. 130, No. 6, pp. 439.

Huang, G.H. and Loucks, D.P. (2000). “An inexact two-stage stochastic programming model for water resources model for water resources management under

uncertainty.” Civil Engineering and Environmental Systems, Vol. 17, No. 2,

pp. 95.

Ocanas, G. and Mays, L.W. (1981a). “A model for water reuse planning.” Water Resources Research, Vol. 17, No. 1, pp. 25.

Ocanas, G. and Mays, L.W. (1981b). “Water reuse planning models: extensions and applications.” Water Resources Research, Vol. 17, No. 5, pp. 1311. Palmer, R.N., Mohammadi, A., Hahn, M.A., Kessler, D., Dvorak, J.V., and Parkinson,

D. (2000). “Computer assisted decision support system for high level

infrastructure master planning: case of the city of Portland Supply and

Transmission Model (STM).” Proceedings of the ASCE 2000 Joint

Conference on Water Resources Engineering and Water Resources Planning

and Movement, Minneapolis, MN.

Passell, H., Tidwell, V., and Webb, E. (2002). “Cooperative modeling: a tool for community-based water resource management.” Southwest Hydrology, Vol.

1, No. 4, pp. 26.

Simonovic, S.P., Fahmy, H., and El-shorbagy, A. (1997). “The use of object-oriented modeling for water resources planning in Egypt.” Water Resources

Management, Vol. 11, pp. 243.

Stave, K.A. (2003). “A system dynamics model to facilitate public understanding of water management options in Las Vegas, Nevada.” Journal of Environmental

Management, Vol. 67, No. 4, pp. 303.

Sumer, D.Y., Lansey, K., and Richter, H. (2004). “Evaluation of conservation measures in the Upper San Pedro Basin.” The 2004 World Water and Environmental

Resources Congress, Salt Lake City, UT, ASCE.