11
J. Korea Water Resour. Assoc. Vol. 52, No. 7 (2019), pp. 463-473 pISSN 1226-6280 doi: 10.3741/JKWRA.2019.52.7.463 eISSN 2287-6138 Comparison and discussion of MODSIM and K-WEAP model considering water supply priority Oh, Ji-Hwan a ใ†Kim, Yeon-Su b * ใ†Ryu, Kyong Sik c ใ†Jo, Young Sik d a Researcher, Department of Water Resources Research Center, K-water Institute, Daejeon, Korea b Researcher, Department of Water Resources Research Center, K-water Institute, Daejeon, Korea c Senior Researcher, Department of Water Resources Research Center, K-water Institute, Daejeon, Korea d General Manager of Business Planning Team, Department of Water Resources Management Research & Planning, K-water, Daejeon, Korea Paper number: 19-028 Received: 15 May 2019; Revised: 12 June 2019; Accepted: 12 June 2019 Abstract This study compared the characteristics of the optimization technique and the water supply and demand forecast using K-WEAP (Korea-Water Evaluation and Planning System) model and MODSIM (Modified SIMYLD) model considering wtaer supply priority. Currently, The national water resources plan applied same priority for municipal, industrial and agricultural demand. the K-WEAP model performs the ratio allocation to satisfy the maximum satisfaction rate, whereas the MODSIM model should be applied to the water supply priority of demands. As a result of applying the priority, water shortage decreased by an average of 1,035,000 m 3 than same prioritized results. It is due to the increase of the return flow rate as the distribution of Municipal and industrial water increases. Comparing the analysis results of K-WEAP and MODSIM applying the priorities, the relative error was within 5.3% and the coefficient of determination (R 2 ) was 0.9999. In addition, if both models provide reasonable water balance analysis results, K-WEAP is superior to GUI convenience for model construction and data processing. However, MODSIM is more effective in simulation time efficiency. It is expected that it will be able to carry out analysis according to various scenarios using the model. Keywords: Water supply and demand system, Water supply priority, Water balance analysis, K-WEAP, MODSIM ๊ณต๊ธ‰ ์šฐ์„ ์ˆœ์œ„๋ฅผ ๊ณ ๋ คํ•œ MODSIM ๊ณผ K-WEAP ๋ชจํ˜•์˜ ๋น„๊ต ๋ฐ ๊ณ ์ฐฐ ์˜ค์ง€ํ™˜ a ใ†๊น€์—ฐ์ˆ˜ b * ใ†๋ฅ˜๊ฒฝ์‹ c ใ†์กฐ์˜์‹ d a K-water ์—ฐ๊ตฌ์› ๋ฌผ์ˆœํ™˜์—ฐ๊ตฌ์†Œ ์œ„์ด‰์—ฐ๊ตฌ์›, b K-water ์—ฐ๊ตฌ์› ๋ฌผ์ˆœํ™˜์—ฐ๊ตฌ์†Œ ์œ„์ด‰์—ฐ๊ตฌ์›, c K-water ์—ฐ๊ตฌ์› ๋ฌผ์ˆœํ™˜์—ฐ๊ตฌ์†Œ ์ฑ…์ž„์—ฐ๊ตฌ์›, d ํ•œ๊ตญ์ˆ˜์ž์›๊ณต์‚ฌ ๋ฌผ๊ด€๋ฆฌ๊ธฐํš์ฒ˜ ์‚ฌ์—…๊ธฐํš๋ถ€์žฅ ์š” ์ง€ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๊ณต๊ธ‰ ์šฐ์„ ์ˆœ์œ„์— ๋”ฐ๋ฅธ ๋ฌผ์ˆ˜๊ธ‰ ๋ถ„์„ ๊ฒฐ๊ณผ์˜ ๋น„๊ต๋ฅผ ์œ„ํ•ด ๊ตญ๋‚ด ์ˆ˜์ž์›์žฅ๊ธฐ์ข…ํ•ฉ๊ณ„ํš์—์„œ ํ™œ์šฉํ•œ K-WEAP (Korea-Water Evaluation And Planing System) ๋ชจํ˜•๊ณผ MODSIM (Modified SIMYLD) ๋ชจํ˜•์„ ์ด์šฉํ•˜์—ฌ ๋ถ„์„ํ•˜์˜€๋‹ค. ๊ธฐ์กด์˜ ์ˆ˜์ž์›์žฅ๊ธฐ์ข…ํ•ฉ๊ณ„ํš์€ ์ˆ˜์š”์ฒ˜์˜ ๊ณต๊ธ‰ ์šฐ์„ ์ˆœ ์œ„๋ฅผ ๋ชจ๋‘ ๋™์ผํ•˜๊ฒŒ ๊ณต๊ธ‰ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๊ฐ€์ •ํ•˜์—ฌ ๋ถ„์„ํ•˜์˜€์œผ๋ฉฐ K-WEAP์€ ์ตœ๋Œ€์ถฉ์กฑ๋ฅ ์„ ๋งŒ์กฑ์‹œํ‚ค๊ธฐ ์œ„ํ•œ ๋น„์œจ ๋ฐฐ๋ถ„์„ ์ˆ˜ํ–‰ํ•˜๋Š” ๋ฐ˜๋ฉด MODSIM์€ ๋ฌผ ๊ณต๊ธ‰ ์šฐ์„ ์ˆœ์œ„์˜ ์ ์šฉ์ด ํ•„์ˆ˜์ ์ธ ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ๋จผ์ € ์šฐ์„ ์ˆœ์œ„์— ๋”ฐ๋ฅธ ํ•œ๊ฐ• ์œ ์—ญ์˜ ๋ฌผ์ˆ˜๊ธ‰ ๋ถ„์„ ๊ฒฐ๊ณผ, ํ‰๊ท  1,035 ์ฒœ m 3 ์˜ ๋ฌผ๋ถ€์กฑ์ด ๊ฐ์†Œ ํ•˜์˜€์œผ๋ฉฐ ์ด๋Š” ์ƒยท๊ณต์šฉ์ˆ˜์˜ ๋ฐฐ๋ถ„๋Ÿ‰์ด ์ฆ๊ฐ€ํ•˜๋ฉด์„œ ํšŒ๊ท€์ˆ˜๋Ÿ‰์ด ์ฆ๊ฐ€ํ•˜๊ณ , ์ˆ˜์ž์›์˜ ์žฌ์ด์šฉ์ด ๋งŽ์•„์ง€๊ธฐ ๋•Œ๋ฌธ์ธ ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ์šฐ์„ ์ˆœ์œ„๋ฅผ ์ ์šฉ ํ•œ K-WEAP๊ณผ MODSIM์˜ ๋ถ„์„๊ฒฐ๊ณผ๋ฅผ ๋น„๊ตํ•  ๊ฒฝ์šฐ, ์ƒ๋Œ€์˜ค์ฐจ ์ตœ๋Œ€ 5.3%์ด๋‚ด, ๊ฒฐ์ •๊ณ„์ˆ˜(R 2 )๋Š” 0.9999๋กœ ๋งค์šฐ ์œ ์‚ฌํ•œ ๋ฌผ ๋ถ€์กฑ์ด ๋ฐœ์ƒํ•˜์˜€๋‹ค. ๋˜ ํ•œ ๋‘ ๋ชจํ˜• ๋ชจ๋‘ ํ•ฉ๋ฆฌ์ ์ธ ๋ฌผ ๋ถ€์กฑ ๋ถ„์„ ๊ฒฐ๊ณผ๋ฅผ ์ œ๊ณตํ•œ๋‹ค๋ฉด, ๋ชจํ˜•์˜ ๊ตฌ์ถ•๊ณผ ๋ฐ์ดํ„ฐ ์ฒ˜๋ฆฌ์— ํ•ด๋‹นํ•˜๋Š” GUI ํŽธ์˜์„ฑ์€ K-WEAP์ด ๋” ์šฐ์ˆ˜ํ•œ ๊ฒƒ์œผ๋กœ ๋‚˜ ํƒ€๋‚ฌ์œผ๋‚˜, ๊ตฌ๋™์‹œ๊ฐ„์˜ ํšจ์œจ์„ฑ์€ MODSIM์ด ๋” ์šฐ์ˆ˜ํ•œ ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ํ–ฅํ›„ K-WEAP๋ชจํ˜• ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ MODSIM ๋ชจํ˜•์„ ํ™œ์šฉํ•œ ๋‹ค์–‘ํ•œ ์‹œ๋‚˜ ๋ฆฌ์˜ค์— ๋”ฐ๋ฅธ ๋ถ„์„์„ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค. ํ•ต์‹ฌ์šฉ์–ด: ๋ฌผ์ˆ˜๊ธ‰์ฒด๊ณ„, ๋ฌผ๊ณต๊ธ‰ ์šฐ์„ ์ˆœ์œ„, ๋ฌผ์ˆ˜์ง€ ๋ถ„์„, K-WEAP, MODSIM ยฉ 2019 Korea Water Resources Association. All rights reserved. *Corresponding Author. Tel: +82-42-629-3113 E-mail: [email protected] (Y.-S. Kim)

Comparison and discussion of MODSIM and K-WEAP model

  • Upload
    others

  • View
    4

  • Download
    0

Embed Size (px)

Citation preview

Page 1: Comparison and discussion of MODSIM and K-WEAP model

J. Korea Water Resour. Assoc. Vol. 52, No. 7 (2019), pp. 463-473 pISSN 1226-6280

doi: 10.3741/JKWRA.2019.52.7.463 eISSN 2287-6138

Comparison and discussion of MODSIM and K-WEAP model considering water

supply priority

Oh, Ji-Hwanaใ†Kim, Yeon-Sub*ใ†Ryu, Kyong Sikcใ†Jo, Young Sikd

aResearcher, Department of Water Resources Research Center, K-water Institute, Daejeon, KoreabResearcher, Department of Water Resources Research Center, K-water Institute, Daejeon, KoreacSenior Researcher, Department of Water Resources Research Center, K-water Institute, Daejeon, KoreadGeneral Manager of Business Planning Team, Department of Water Resources Management Research & Planning, K-water, Daejeon, Korea

Paper number: 19-028

Received: 15 May 2019; Revised: 12 June 2019; Accepted: 12 June 2019

Abstract

This study compared the characteristics of the optimization technique and the water supply and demand forecast using K-WEAP

(Korea-Water Evaluation and Planning System) model and MODSIM (Modified SIMYLD) model considering wtaer supply priority.

Currently, The national water resources plan applied same priority for municipal, industrial and agricultural demand. the K-WEAP

model performs the ratio allocation to satisfy the maximum satisfaction rate, whereas the MODSIM model should be applied to the water

supply priority of demands. As a result of applying the priority, water shortage decreased by an average of 1,035,000 m3 than same

prioritized results. It is due to the increase of the return flow rate as the distribution of Municipal and industrial water increases.

Comparing the analysis results of K-WEAP and MODSIM applying the priorities, the relative error was within 5.3% and the coefficient

of determination (R2) was 0.9999. In addition, if both models provide reasonable water balance analysis results, K-WEAP is superior

to GUI convenience for model construction and data processing. However, MODSIM is more effective in simulation time efficiency.

It is expected that it will be able to carry out analysis according to various scenarios using the model.

Keywords: Water supply and demand system, Water supply priority, Water balance analysis, K-WEAP, MODSIM

๊ณต๊ธ‰ ์šฐ์„ ์ˆœ์œ„๋ฅผ ๊ณ ๋ คํ•œ MODSIM๊ณผ K-WEAP ๋ชจํ˜•์˜ ๋น„๊ต ๋ฐ ๊ณ ์ฐฐ

์˜ค์ง€ํ™˜aใ†๊น€์—ฐ์ˆ˜b*ใ†๋ฅ˜๊ฒฝ์‹cใ†์กฐ์˜์‹d

aK-water ์—ฐ๊ตฌ์› ๋ฌผ์ˆœํ™˜์—ฐ๊ตฌ์†Œ ์œ„์ด‰์—ฐ๊ตฌ์›, bK-water ์—ฐ๊ตฌ์› ๋ฌผ์ˆœํ™˜์—ฐ๊ตฌ์†Œ ์œ„์ด‰์—ฐ๊ตฌ์›, cK-water ์—ฐ๊ตฌ์› ๋ฌผ์ˆœํ™˜์—ฐ๊ตฌ์†Œ ์ฑ…์ž„์—ฐ๊ตฌ์›, dํ•œ๊ตญ์ˆ˜์ž์›๊ณต์‚ฌ ๋ฌผ๊ด€๋ฆฌ๊ธฐํš์ฒ˜ ์‚ฌ์—…๊ธฐํš๋ถ€์žฅ

์š” ์ง€

๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๊ณต๊ธ‰ ์šฐ์„ ์ˆœ์œ„์— ๋”ฐ๋ฅธ ๋ฌผ์ˆ˜๊ธ‰ ๋ถ„์„ ๊ฒฐ๊ณผ์˜ ๋น„๊ต๋ฅผ ์œ„ํ•ด ๊ตญ๋‚ด ์ˆ˜์ž์›์žฅ๊ธฐ์ข…ํ•ฉ๊ณ„ํš์—์„œ ํ™œ์šฉํ•œ K-WEAP (Korea-Water Evaluation

And Planing System) ๋ชจํ˜•๊ณผ MODSIM (Modified SIMYLD) ๋ชจํ˜•์„ ์ด์šฉํ•˜์—ฌ ๋ถ„์„ํ•˜์˜€๋‹ค. ๊ธฐ์กด์˜ ์ˆ˜์ž์›์žฅ๊ธฐ์ข…ํ•ฉ๊ณ„ํš์€ ์ˆ˜์š”์ฒ˜์˜ ๊ณต๊ธ‰ ์šฐ์„ ์ˆœ

์œ„๋ฅผ ๋ชจ๋‘ ๋™์ผํ•˜๊ฒŒ ๊ณต๊ธ‰ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๊ฐ€์ •ํ•˜์—ฌ ๋ถ„์„ํ•˜์˜€์œผ๋ฉฐ K-WEAP์€ ์ตœ๋Œ€์ถฉ์กฑ๋ฅ ์„ ๋งŒ์กฑ์‹œํ‚ค๊ธฐ ์œ„ํ•œ ๋น„์œจ ๋ฐฐ๋ถ„์„ ์ˆ˜ํ–‰ํ•˜๋Š” ๋ฐ˜๋ฉด MODSIM์€

๋ฌผ ๊ณต๊ธ‰ ์šฐ์„ ์ˆœ์œ„์˜ ์ ์šฉ์ด ํ•„์ˆ˜์ ์ธ ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ๋จผ์ € ์šฐ์„ ์ˆœ์œ„์— ๋”ฐ๋ฅธ ํ•œ๊ฐ• ์œ ์—ญ์˜ ๋ฌผ์ˆ˜๊ธ‰ ๋ถ„์„ ๊ฒฐ๊ณผ, ํ‰๊ท  1,035 ์ฒœ m3์˜ ๋ฌผ๋ถ€์กฑ์ด ๊ฐ์†Œ

ํ•˜์˜€์œผ๋ฉฐ ์ด๋Š” ์ƒยท๊ณต์šฉ์ˆ˜์˜ ๋ฐฐ๋ถ„๋Ÿ‰์ด ์ฆ๊ฐ€ํ•˜๋ฉด์„œ ํšŒ๊ท€์ˆ˜๋Ÿ‰์ด ์ฆ๊ฐ€ํ•˜๊ณ , ์ˆ˜์ž์›์˜ ์žฌ์ด์šฉ์ด ๋งŽ์•„์ง€๊ธฐ ๋•Œ๋ฌธ์ธ ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ์šฐ์„ ์ˆœ์œ„๋ฅผ ์ ์šฉ

ํ•œ K-WEAP๊ณผ MODSIM์˜ ๋ถ„์„๊ฒฐ๊ณผ๋ฅผ ๋น„๊ตํ•  ๊ฒฝ์šฐ, ์ƒ๋Œ€์˜ค์ฐจ ์ตœ๋Œ€ 5.3%์ด๋‚ด, ๊ฒฐ์ •๊ณ„์ˆ˜(R2)๋Š” 0.9999๋กœ ๋งค์šฐ ์œ ์‚ฌํ•œ ๋ฌผ ๋ถ€์กฑ์ด ๋ฐœ์ƒํ•˜์˜€๋‹ค. ๋˜

ํ•œ ๋‘ ๋ชจํ˜• ๋ชจ๋‘ ํ•ฉ๋ฆฌ์ ์ธ ๋ฌผ ๋ถ€์กฑ ๋ถ„์„ ๊ฒฐ๊ณผ๋ฅผ ์ œ๊ณตํ•œ๋‹ค๋ฉด, ๋ชจํ˜•์˜ ๊ตฌ์ถ•๊ณผ ๋ฐ์ดํ„ฐ ์ฒ˜๋ฆฌ์— ํ•ด๋‹นํ•˜๋Š” GUI ํŽธ์˜์„ฑ์€ K-WEAP์ด ๋” ์šฐ์ˆ˜ํ•œ ๊ฒƒ์œผ๋กœ ๋‚˜

ํƒ€๋‚ฌ์œผ๋‚˜, ๊ตฌ๋™์‹œ๊ฐ„์˜ ํšจ์œจ์„ฑ์€ MODSIM์ด ๋” ์šฐ์ˆ˜ํ•œ ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ํ–ฅํ›„ K-WEAP๋ชจํ˜• ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ MODSIM ๋ชจํ˜•์„ ํ™œ์šฉํ•œ ๋‹ค์–‘ํ•œ ์‹œ๋‚˜

๋ฆฌ์˜ค์— ๋”ฐ๋ฅธ ๋ถ„์„์„ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค.

ํ•ต์‹ฌ์šฉ์–ด: ๋ฌผ์ˆ˜๊ธ‰์ฒด๊ณ„, ๋ฌผ๊ณต๊ธ‰ ์šฐ์„ ์ˆœ์œ„, ๋ฌผ์ˆ˜์ง€ ๋ถ„์„, K-WEAP, MODSIM

ยฉ 2019 Korea Water Resources Association. All rights reserved.

*Corresponding Author. Tel: +82-42-629-3113

E-mail: [email protected] (Y.-S. Kim)

Page 2: Comparison and discussion of MODSIM and K-WEAP model

J.-H. Oh et al. / Journal of Korea Water Resources Association 52(7) 463-473464

1. ์„œ ๋ก 

์šฐ๋ฆฌ๋‚˜๋ผ๋Š” ์ˆ˜์ž์›์˜ ๊ฐœ๋ฐœ, ์•ˆ์ •์ ์ธ ๊ณต๊ธ‰๊ณผ ํšจ์œจ์ ์ธ ๋ฐฐ

๋ถ„, ํ™์ˆ˜์žฌํ•ด๋ฐฉ์ง€ ๋“ฑ์„ ์œ„ํ•ด ์ˆ˜์ž์›์žฅ๊ธฐ์ข…ํ•ฉ๊ณ„ํš๊ณผ ์œ ์—ญ์ข…

ํ•ฉ์น˜์ˆ˜๊ณ„ํš ๋“ฑ ๊ตญ๊ฐ€ ๊ณ„ํš์„ ์ˆ˜๋ฆฝํ•ด์™”๋‹ค. ๊ธฐ์กด์˜ ์šฉ์ˆ˜๊ณต๊ธ‰๋Šฅ๋ ฅ

ํ‰๊ฐ€์™€ ๊ณ„ํš์€ ์‹œยท๊ตฐ ์ค‘์‹ฌ์˜ ์šฉ์ˆ˜์ˆ˜์š”๋Ÿ‰์„ ๋ฐ”ํƒ•์œผ๋กœ ์ค‘๊ถŒ์—ญ

๋‹จ์œ„๋กœ ํ™•์žฅํ•˜๊ณ , โ€œ์ˆ˜์ž์›์˜ ์ง€์†์  ํ™•๋ณด๊ธฐ์ˆ  ๊ฐœ๋ฐœ์‚ฌ์—…โ€์˜ ์„ฑ

๊ณผ๋กœ ๊ฐœ๋ฐœํ•œ K-WEAP (Korea-Water Evaluation And Planing

System) ๋ชจํ˜•์„ ํ™œ์šฉํ•˜์˜€์œผ๋ฉฐ ์ „๊ตญ 6๊ฐœ ๊ถŒ์—ญ 117๊ฐœ ์ค‘ ์ œ์ฃผ๋„

๋ฅผ ์ œ์™ธํ•œ 113๊ฐœ์˜ ์ค‘๊ถŒ์—ญ์„ ๋Œ€์ƒ์œผ๋กœ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ์ˆ˜์ž์›์žฅ

๊ธฐ์ข…ํ•ฉ๊ณ„ํš(MOLIT, 2016)์˜ ํŠน์ง•์€ ์ค‘๊ถŒ์—ญ ๋‚ด ํ•˜์ฒœ์ˆ˜, ๋Œ

์ˆ˜, ์ง€ํ•˜์ˆ˜๋ฅผ ์—ฐ๊ณ„ํ•˜์—ฌ ๋ชจ๋“  ์ˆ˜๋Ÿ‰์„ ์ด์šฉํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฐ€์ • ํ•˜

์— ์ˆ˜์š”์ฒ˜๋ฅผ ์ƒํ™œ, ๊ณต์—…, ๋†์—…, ํ•˜์ฒœ์œ ์ง€์œ ๋Ÿ‰์œผ๋กœ ๊ตฌ๋ถ„ํ•˜๊ณ ,

์ƒยท๊ณต์šฉ์ˆ˜๋Š” ํšŒ๊ท€์ˆ˜๋Ÿ‰ ์ ์šฉ, ๋†์—…์šฉ์ˆ˜๋Š” ์ˆœ๋ฌผ์†Œ๋ชจ๊ฐœ๋…์„ ์ 

์šฉํ•˜์˜€์œผ๋ฉฐ ์ƒยท๊ณตยท๋†์—…์šฉ์ˆ˜๋ฅผ ๋จผ์ € ๊ณต๊ธ‰ํ•˜๊ธฐ ์œ„ํ•œ 1์ˆœ์œ„๋กœ

์„ค์ •ํ•˜๊ณ , ์ƒยท๊ณตยท๋†์—…์šฉ์ˆ˜๋ฅผ ๊ณต๊ธ‰ ํ›„ ๊ณต๊ธ‰ ์—ฌ๋ ฅ์ด ์žˆ์„ ๊ฒฝ์šฐ

ํ•˜์ฒœ์œ ์ง€์šฉ์ˆ˜๋ฅผ ๊ณต๊ธ‰ํ•˜๋„๋ก 2์ˆœ์œ„๋ฅผ ์ ์šฉํ•˜์˜€๋‹ค. ์ด์™€ ๊ฐ™์€

๊ฐ€์ •๊ณผ ํ˜„์žฌ ๋ฌผ์ˆ˜๊ธ‰ ๋ถ„์„ ์‹œ์Šคํ…œ์€ ์šฉ๋„๋ณ„ ์šฐ์„ ์ˆœ์œ„์— ๋”ฐ๋ผ

ํ•˜๋ฅ˜๋ถ€์˜ ํšŒ๊ท€์ˆ˜ ์žฌ์ด์šฉ๋Ÿ‰์— ๋”ฐ๋ฅธ ๋ฌผ ๋ถ€์กฑ ๊ฒฐ๊ณผ๊ฐ€ ์ƒ์ดํ•˜๊ฒŒ

๋‚˜ํƒ€๋‚  ์ˆ˜ ์žˆ์–ด ์ด์— ๋Œ€ํ•œ ๋น„๊ต ๋ถ„์„๊ณผ ๋ชจํ˜•์˜ ๊ฒ€์ฆ ์ฐจ์›์—์„œ

๋„ ์ •๋Ÿ‰์ ์ธ ๋น„๊ต๊ฐ€ ํ•„์š”ํ•˜๋‹ค. ๋ฌผ ๊ณต๊ธ‰ ์šฐ์„ ์ˆœ์œ„์— ๋”ฐ๋ฅธ ๋ฌผ ๋ถ€

์กฑ๋Ÿ‰์˜ ์ฐจ์ด๋ฅผ ๋ณด๊ณ ์ž ์•„๋ž˜ Fig. 1๊ณผ ๊ฐ™์€ ์˜ˆ์ œ๋ฅผ ์ œ์‹œํ•˜์˜€๋‹ค.

์—ฌ๊ธฐ์„œ, ํŒŒ๋ž€์ƒ‰ ์›์€ ์ค‘๊ถŒ์—ญ์—์„œ ๋ฐœ์ƒํ•˜๋Š” ์œ ์ถœ๋Ÿ‰, ๋…ธ๋ž€์ƒ‰ ์ƒ

์ž๋Š” ์ƒยท๊ณต์šฉ์ˆ˜ ์ˆ˜์š”๋Ÿ‰, ์ดˆ๋ก์ƒ‰ ์ƒ์ž๋Š” ๋†์—…์šฉ์ˆ˜ ์ˆ˜์š”๋Ÿ‰์„ ์˜

๋ฏธํ•œ๋‹ค. ์ƒยท๊ณต์šฉ์ˆ˜์˜ ํšŒ๊ท€์œจ์€ 50%๋ฅผ ์ ์šฉํ•œ ๊ฒฝ์šฐ์ด๋ฉฐ ๊ณต๊ธ‰

๋Ÿ‰์ด ์ˆ˜์š”๋Ÿ‰์„ ๋งŒ์กฑํ•˜์ง€ ๋ชปํ•˜๋Š” ์ƒํƒœ๋กœ ๋ฐฐ๋ถ„์„ ํ•ด์•ผ ํ•˜๋Š” ์กฐ

๊ฑด์ด๋‹ค. Fig. 1(a)๋Š” ์ˆ˜์ž์›์žฅ๊ธฐ์ข…ํ•ฉ๊ณ„ํš๊ณผ ๊ฐ™์ด ๋™์ผ ์šฐ์„ ์ˆœ

์œ„ ์กฐ๊ฑด์œผ๋กœ ์ˆ˜์š”๋Ÿ‰๋น„์— ๋”ฐ๋ผ ๋ถ„๋ฐฐ๋ฅผ ์ ์šฉํ•˜๋ฉด ์ตœํ•˜๋ฅ˜๋ถ€์˜

๋ฌผ ๋ถ€์กฑ์€ ์ƒยท๊ณต์šฉ์ˆ˜ 9.96, ๋†์—…์šฉ์ˆ˜ 6.64๋งŒํผ ๋ถ€์กฑํ•˜์—ฌ ์ด ๋ถ€

์กฑ๋Ÿ‰์€ 16.6์ด ๋ฐœ์ƒํ•œ๋‹ค. ๋‹ค์Œ Fig. 1(b)๋Š” ์ƒยท๊ณต์šฉ์ˆ˜ ๋จผ์ € ๋ถ„

๋ฐฐ๋ฅผ ์ˆ˜ํ–‰ํ•˜๊ณ , ์—ฌ๋ถ„์˜ ๋ฌผ๋Ÿ‰์„ ๋†์—…์šฉ์ˆ˜์— ๋ถ„๋ฐฐํ•˜๋Š” ์šฐ์„ ์ˆœ

์œ„๋ฅผ ์ ์šฉํ•œ ๊ฒฐ๊ณผ์ด๋ฉฐ, ํ•˜๋ฅ˜๋ถ€ ๋ฌผ ๋ถ€์กฑ๋Ÿ‰์€ ์ƒยท๊ณต์šฉ์ˆ˜ 0, ๋†์—…

์šฉ์ˆ˜์˜ โ€“10์ด ๋ฐœ์ƒํ•˜์—ฌ ์ด ๋ฌผ ๋ถ€์กฑ๋Ÿ‰์€ โ€“10์œผ๋กœ ๋ถ„์„๋  ์ˆ˜

์žˆ๋‹ค. ์ฆ‰, ๊ฐ™์€ ๊ณต๊ธ‰๋Ÿ‰๊ณผ ์ˆ˜์š”๋Ÿ‰์ด์ง€๋งŒ ์šฐ์„ ์ˆœ์œ„์— ๋”ฐ๋ผ ํ•˜๋ฅ˜

๋ถ€์—์„œ ๊ฐ€์šฉํ•  ์ˆ˜ ์žˆ๋Š” ์ˆ˜์ž์› ์žฌ์ด์šฉ๋Ÿ‰์˜ ์ฐจ์ด๊ฐ€ ๋ฐœ์ƒํ•˜๊ณ 

์žˆ์œผ๋ฉฐ ์ด๋กœ ์ธํ•ด ๋ฌผ ๋ถ€์กฑ ๊ฒฐ๊ณผ์—๋„ ์ฐจ์ด๋ฅผ ๋ฐœ์ƒ์‹œํ‚ฌ ์ˆ˜ ์žˆ๊ธฐ

์— ๋น„๊ต๊ฐ€ ํ•„์š”ํ•˜๋‹ค.

๋ณธ ์—ฐ๊ตฌ์™€ ๊ด€๋ จ๋œ ์šฐ์„ ์ˆœ์œ„๋ฅผ ๊ณ ๋ คํ•œ ๋ฌผ์ˆ˜๊ธ‰ ๋ถ„์„ ๋ชจํ˜•์˜

์ ์šฉ์— ๊ด€ํ•œ ์—ฐ๊ตฌ๋Š” 2000๋…„๋Œ€ ์ดˆ๋ถ€ํ„ฐ ์ˆ˜ํ–‰๋˜์—ˆ๋‹ค. Yoo et al.

(2000)์€ ์ˆ˜์ž์›๊ณ„ํš์‹œ ์ง€์—ญ ๊ฐ„ ๊ณต๊ธ‰์šฐ์„ ๊ถŒ๊ณผ ์šฉ๋„๋ณ„ ์šฐ์„ ๊ถŒ

์˜ ๋ถ€์—ฌ๋Š” ๋ฌผ ๊ณต๊ธ‰์œ„๊ธฐ์™€ ๋ถ„์Ÿ์„ ํƒ€๊ฐœํ•  ์ˆ˜ ์žˆ๋Š” ๋Œ€์•ˆ์ด ๋  ์ˆ˜

์žˆ๋‹ค๊ณ  ์ œ์–ธํ•˜๊ณ , ํ•œ๊ฐ• ๊ถŒ์—ญ์„ ๋Œ€์ƒ์œผ๋กœ ์ˆ˜์š”์ฒ˜์˜ ๊ณต๊ธ‰์šฐ์„ 

๊ถŒ, ์šฉ๋„๋ณ„ ์šฐ์„ ๊ถŒ์„ ๋ถ€์—ฌํ•˜์—ฌ ๋ฌผ ๋ถ€์กฑ๋Ÿ‰์„ ๋น„๊ต ๋ถ„์„ํ•˜์—ฌ ์ˆ˜

๋ฆฌ๊ถŒ์„ ๋ฐ˜์˜ํ•œ ๋ถ„์„์ด ๊ฐ€๋Šฅํ•จ์„ ํ™•์ธํ•˜์˜€๋‹ค. Yoo (2005)๋Š”

๊ณผ๊ฑฐ์˜ ๋ฌผ์ˆ˜์ง€ ๋ถ„์„์˜ ๋ฌธ์ œ์ ์ธ ์ˆœ๋ฌผ์†Œ๋ชจ๊ฐœ๋…์„ ์ง€์ ํ•˜๊ณ , ์ด

๋ฅผ ๋ณด์™„ํ•˜๊ธฐ ์œ„ํ•œ ๋ฐฉ๋ฒ•์œผ๋กœ MODSIM ๋ชจํ˜•์„ ์ ์šฉํ•˜๊ณ , ํ•œ๊ฐ•

๊ถŒ์—ญ์˜ ์šฉ์ˆ˜ ์ˆ˜์š”์— ๋Œ€ํ•œ ๋Œ ๊ณต๊ธ‰์œจ์„ ์‚ฐ์ •ํ•˜์˜€๋‹ค. Cheong et

al. (2007)์€ ๋ฌผ์ด์šฉ์˜ ํšจ์œจ์„ฑ์„ ๊ทน๋Œ€ํ™”ํ•˜๊ธฐ ์œ„ํ•œ ์˜์‚ฌ๊ฒฐ์ •

์ง€์›์‹œ์Šคํ…œ์˜ ํ•„์š”์„ฑ์„ ์ œ์‹œํ•˜๊ณ , ๊ตญ๋‚ด ์ ์šฉํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์šฐ

๋ฆฌ๋‚˜๋ผ๊ฐ€ ๊ฐ€์ง€๊ณ  ์žˆ๋Š” ๋ฌผ๋ฆฌ์  ์šด์˜์ธก๋ฉด์˜ ํŠน์„ฑ์„ ๋ฐ˜์˜ํ•˜์—ฌ

KModSim์„ ๊ฐœ๋ฐœํ•˜๊ณ , ๊ธˆ๊ฐ• ์œ ์—ญ์— ๋ชจ์˜๋ฅผ ์ˆ˜ํ–‰ํ•˜์—ฌ ์ ์šฉ์„ฑ

์„ ๊ฒ€ํ† ํ•˜์˜€๋‹ค. Ahn et al. (2009)๋Š” ๊ธˆ๊ฐ• ๊ถŒ์—ญ์„ ๋Œ€์ƒ์œผ๋กœ ๋†

์—…๊ฐ€๋ญ„์˜ ๋Œ€์ฑ…์„ ๋งˆ๋ จํ•˜๊ธฐ ์œ„ํ•ด ๋†์—…์šฉ ์ˆ˜๋ฆฌ์‹œ์„ค์„ ๊ณ ๋ คํ•œ

๋ฌผ์ˆ˜์ง€ ๋„คํŠธ์›Œํฌ๋ฅผ MODSIM์„ ํ™œ์šฉํ•˜์—ฌ ๊ตฌ์ถ•ํ•˜๊ณ  TANK

๋ชจํ˜•์— ์˜ํ•œ ์œ ์ถœ๋Ÿ‰๊ณผ ์ˆ˜์š”๋Ÿ‰์ž๋ฃŒ๋ฅผ ํ™œ์šฉํ•˜์—ฌ ๋†์—…์šฉ์ˆ˜ ๊ณต๊ธ‰

์ธก๋ฉด์˜ ๊ณต๊ธ‰๊ฐ€๋Šฅ์œจ๊ณผ ๊ธฐ์—ฌ๋„๋ฅผ ์ •๋Ÿ‰์ ์œผ๋กœ ํ‰๊ฐ€ํ•˜์˜€์œผ๋ฉฐ ๊ณต

๊ฐ„๋ณ„, ์šฉ๋„๋ณ„ ์šฐ์„ ์ˆœ์œ„๋ฅผ ๋ถ€์—ฌํ•˜์—ฌ ๊ฒ€ํ† ํ•˜์˜€๋‹ค. Park et al.

(2013)์€ ์‚ฝ๊ต์ฒœ ์œ ์—ญ์„ ๋Œ€์ƒ์œผ๋กœ ํ•˜์ฒœ์ˆ˜ ์‚ฌ์šฉ ํ—ˆ๊ฐ€์™€ ํ—ˆ๊ฐ€

์ด์™ธ ์ˆ˜๋ฆฌ๊ถŒ ์ „์ˆ˜์กฐ์‚ฌ ๊ฒฐ๊ณผ๋ฅผ ํ™œ์šฉํ•˜์—ฌ ์šฉ์ˆ˜์‚ฌ์šฉ๋Ÿ‰์„ ์ถ”์ •ํ•˜

๊ณ , MODSIM ๋ชจํ˜•์„ ์ ์šฉํ•œ ๋ฌผ์ˆ˜์ง€ ๋ถ„์„์„ ์ˆ˜ํ–‰ํ•˜์˜€์œผ๋ฉฐ ๋†

์—…์šฉ์ˆ˜ ๋“ฑ์˜ ํ—ˆ๊ฐ€ ์ด์™ธ ์ˆ˜๋ฆฌ๊ถŒ์˜ ๋น„์œจ์ด ์ƒ๋Œ€์ ์œผ๋กœ ๋†’๊ธฐ ๋•Œ

๋ฌธ์— ํฌํ•จ ์œ ๋ฌด์— ๋”ฐ๋ผ ๋ฌผ ๋ถ€์กฑ ๊ฒฐ๊ณผ๊ฐ€ ์ƒ์ดํ•˜๊ฒŒ ๋‚˜ํƒ€๋‚˜ ํ—ˆ๊ฐ€

์ด์™ธ ์ˆ˜๋ฆฌ๊ถŒ๊ด€๋ฆฌ์— ๋Œ€ํ•œ ์‹œ๊ธ‰ํ•จ๊ณผ ํ†ต๊ณ„์ž๋ฃŒ์˜ ์ถ•์ ์ด ํ•„์š”

ํ•˜๋‹ค๊ณ  ์ง€์ ํ•˜์˜€๋‹ค. ๋˜ํ•œ Lim et al. (2017)์€ SAMS 2007๊ณผ

KModSim ๋ชจํ˜•์„ ํ™œ์šฉํ•˜์—ฌ ์ค‘๊ถŒ์—ญ์˜ ์‹ ๊ทœ๋Œ์ธ ์˜์ฃผ๋Œ์„ ๋Œ€

์ƒ์œผ๋กœ ๊ธฐ์ค€์ €์ˆ˜๋Ÿ‰์„ ์‚ฐ์ •ํ•˜๊ณ , ๋‚ด์„ฑ์ฒœ ์œ ์—ญ์˜ ๋ฌผ ๋ถ€์กฑ ์ •๋„

๋ฅผ ํŒŒ์•…ํ•˜์—ฌ ์˜์ฃผ๋Œ์ด ํ•˜์ฒœ์œ ์ง€์œ ๋Ÿ‰ ํ™•๋ณด์— ๊ธฐ์—ฌํ•˜๋Š” ์ •๋„๋ฅผ

ํ‰๊ฐ€ํ•˜์˜€์œผ๋ฉฐ ๋ณธ ๋…ผ๋ฌธ์—์„œ๋„ ์ƒํ™œ, ๊ณต์—…, ๋†์—…์šฉ์ˆ˜ ์ˆœ์œผ๋กœ ์šฐ

(a) Distribution of demand ratio (b) Application of demand priority

Fig. 1. Results of water shortage considering priority

Page 3: Comparison and discussion of MODSIM and K-WEAP model

J.-H. Oh et al. / Journal of Korea Water Resources Association 52(7) 463-473 465

์„ ์ˆœ์œ„๋ฅผ ์ ์šฉํ•˜์—ฌ ๋ถ„์„ํ•˜์˜€๋‹ค. ๊ฐ€์žฅ ์ตœ๊ทผ์— Choi et al. (2018)

์€ ๊ตญ๋‚ด ์ˆ˜ํ–‰๋˜๊ณ  ์žˆ๋Š” ๋ฌผ์ˆ˜์ง€ ๋ถ„์„ ๋ฐฉ๋ฒ•์— ๋Œ€ํ•œ ๊ฐ€์ •๊ณผ ๋ฌธ์ œ

์ ์œผ๋กœ ๋ฏธ๋ž˜์˜ ๋‹ค์–‘ํ•œ ์‹œ๋‚˜๋ฆฌ์˜ค ๋ถ„์„, ์ˆ˜์š”๋Ÿ‰ ์ฆ๊ฐ€์— ๋งž์ถฐ ๊ณต

๊ธ‰์‹œ์„ค์ด ์ฆ๊ฐ€ํ•œ๋‹ค๋Š” ๊ฐ€์ •, ์ง€์—ญ๊ณต๊ธ‰์›์— ๋Œ€ํ•œ ๊ฐ€์ •, ์ผ์ • ํšŒ

๊ท€์œจ ๊ฐ€์ • ๋“ฑ์„ ์ œ์‹œํ•˜์˜€์œผ๋ฉฐ, ์ด์— ๊ธˆ๊ฐ• ์œ ์—ญ์„ ๋Œ€์ƒ์œผ๋กœ ๊ฐœ

์„ ๋ฐฉ์•ˆ ๋ณ„ ๋ฌผ์ˆ˜๊ธ‰ ๋ถ„์„ ๊ฒฐ๊ณผ๋ฅผ ๋„์ถœํ•˜์—ฌ ์žฌํ˜„์„ฑ๊ณผ ํ˜„์‹ค์ ์ธ

๋ถ„์„๊ฒฐ๊ณผ๋ฅผ ์ œ๊ณตํ•  ์ˆ˜ ์žˆ๋‹ค๊ณ  ์ œ์‹œํ•˜์˜€๋‹ค. MODSIM์„ ํ™œ์šฉ

ํ•œ ์—ฐ๊ตฌ๋ฅผ ์ •๋ฆฌํ•ด๋ณด๋ฉด ์ˆ˜์ž์›๊ณ„ํš์˜ ํ™œ์šฉ, ๊ตญ๋‚ด ์ˆ˜์ž์›์‹œ์„ค

๋ฌผ์˜ ์šด์˜ ํ‰๊ฐ€ ๋ฐ ๊ฐœ์„ ๋ฐฉ์•ˆ, ๊ฐ€๋ญ„ ๋Œ€์ฑ… ๋งˆ๋ จ ๋“ฑ ๋ฌผ์ˆ˜๊ธ‰ ๊ณ„ํš

๋ฐ ์šด์˜ ๋ถ„์•ผ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๊ฐ€ ์žˆ์—ˆ์œผ๋ฉฐ ์ฃผ์š” ํ‚ค์›Œ๋“œ๋กœ ์ˆ˜์š”์ฒ˜

์˜ โ€œ๊ณต๊ธ‰์šฐ์„ ๊ถŒโ€๊ณผ โ€œ์ˆ˜๋ฆฌ๊ถŒ๊ด€๋ฆฌโ€ ๋“ฑ์œผ๋กœ ์ด๋Š” 2์žฅ ๋ฌผ์ˆ˜๊ธ‰ ๋ถ„

์„ ๋ชจํ˜•์˜ ์ตœ์ ํ™” ๋ฐฉ๋ฒ• ๋น„๊ต์—์„œ ๋ชจํ˜•์˜ ํŠน์„ฑ์„ ์ œ์‹œํ•˜๊ณ ์ž

ํ•œ๋‹ค. ์ด์ฒ˜๋Ÿผ MODSIM ๋ชจํ˜•์„ ์ด์šฉํ•œ ๋ฌผ์ˆ˜๊ธ‰ ๋ถ„์„์„ ์ˆ˜ํ–‰ํ•œ

์—ฐ๊ตฌ๋Š” ๋งŽ์•˜์ง€๋งŒ ์šฐ์„ ์ˆœ์œ„์— ๋”ฐ๋ฅธ ๋ฌผ๋ถ€์กฑ๋Ÿ‰์˜ ๋น„๊ต์™€ ๋ชจํ˜•์˜

๊ฒ€์ฆ ์ธก๋ฉด์—์„œ K-WEAP๋ชจํ˜•๊ณผ MODSIM๋ชจํ˜•์— ๋Œ€ํ•œ ๋น„๊ต

๋ถ„์„์„ ์ˆ˜ํ–‰ํ•œ ์—ฐ๊ตฌ๋Š” ์—†์—ˆ๊ธฐ ๋•Œ๋ฌธ์— ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋‘ ๋ชจํ˜•

์˜ ํŠน์„ฑ์„ ๊ณ ์ฐฐํ•˜๊ณ  ๋ฌผ์ˆ˜๊ธ‰ ๋ถ„์„๊ฒฐ๊ณผ๋ฅผ ๋น„๊ตํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค.

2. ๋ฌผ ์ˆ˜๊ธ‰ ๋ถ„์„ ์‹œ์Šคํ…œ ๋ฐ ๋ชจํ˜•์˜ ์ตœ์ ํ™” ๋ฐฉ๋ฒ• ๋น„๊ต

๋ฐ ํŠน์„ฑ

2.1 ๋ชจํ˜•์˜ ๊ฐœ์š”

๋ณธ ์—ฐ๊ตฌ์—์„œ ์ ์šฉํ•œ ๋ชจํ˜•์€ K-WEAPdss ๋ชจํ˜•์œผ๋กœ 21์„ธ๊ธฐ

ํ”„๋ก ํ‹ฐ์–ด์—ฐ๊ตฌ๊ฐœ๋ฐœ์‚ฌ์—…์˜ โ€œ์ˆ˜์ž์›์˜ ์ง€์†์ ํ™•๋ณด๊ธฐ์ˆ ๊ฐœ๋ฐœ ์‚ฌ

์—…๋‹จโ€์˜ ์ง€์› ํ•˜์— ๊ฐœ๋ฐœํ•œ ํ•œ๊ตญํ˜• ํ†ตํ•ฉ์ˆ˜์ž์›ํ‰๊ฐ€๊ณ„ํš๋ชจํ˜•์ด

๋ฉฐ SEI-B (Stockholm Environment Institute-Boston Center)

์™€ ํ•œ๊ตญ๊ฑด์„ค๊ธฐ์ˆ ์—ฐ๊ตฌ์›์ด ๊ณต๋™ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค(Lee and Choi,

2011). ๋ชจํ˜•์€ ์ง€์†์ ์ธ ๋ฐœ์ „์„ ํ†ตํ•ด ํ˜„์žฌ๋Š” ์ˆ˜๋Ÿ‰-์ˆ˜์งˆ์˜ ํ†ต

ํ•ฉ, ๊ฒฝ์ œ์„ฑ ๋ถ„์„ ๋“ฑ ๋ณตํ•ฉ์ ์ธ ํ‰๊ฐ€์™€ ๊ณ„ํš์ด ๊ฐ€๋Šฅํ•˜๋‹ค. ๋ชจํ˜•์˜

ํŠน์ง•์€ ์„ ํ˜•๊ณ„ํš๋ฒ•(linear programming)์„ ํ•ด์„ํ•˜๊ธฐ ์œ„ํ•œ

simplex method๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ๋ชจ๋“  ์ œ์•ฝ์กฐ๊ฑด๊ณผ ์šฐ์„ ์ˆœ์œ„๋ฅผ ๋งŒ

์กฑ์‹œํ‚ค๋ฉด์„œ ์ˆ˜์š”์ฒ˜์˜ ๊ณต๊ธ‰์„ ์ตœ๋Œ€ํ™”ํ•˜๋ฉฐ, ์ˆ˜์š”์ฒ˜๋Š” ์šฐ์„ ์ˆœ

์œ„์™€ ์ˆ˜์›์„ ํ˜ธ๋„์— ์˜ํ•ด ๊ณต๊ธ‰ํ•œ๋‹ค(Choi et al., 2010).

MODSIM์€ ๋ฏธ๊ตญ ํ…์‚ฌ์Šค์˜ ์ˆ˜์ž์›๊ฐœ๋ฐœ๋ถ€(Texas Water

Development Board, 1972)๊ฐ€ ๊ฐœ๋ฐœํ•œ SIMYLD ๋„คํŠธ์›Œํฌ

๋ชจํ˜•์„ ๋ฏธ ์ฝœ๋กœ๋ผ๋„ ์ฃผ๋ฆฝ๋Œ€ํ•™์˜ Labadie ๊ต์ˆ˜๊ฐ€ ์ˆ˜์ •ํ•˜์—ฌ

MODSIM (MODified SIMYLD)์œผ๋กœ ๋ชจํ˜•์ด ๊ฐœ๋ช…๋˜์—ˆ์œผ๋ฉฐ

Version 8.5.0๊นŒ์ง€ ๊ฐœ๋ฐœ๋˜์—ˆ๋‹ค. MODSIM์€ ํ•˜์ฒœ์œ ์—ญ ๋„คํŠธ

์›๋ชจํ˜•(river basin network model)์œผ๋กœ ํ•˜์ฒœ์œ ์—ญ ๊ด€๋ฆฌ์— ์žˆ

์–ด์„œ ๋ฌผ๋ฆฌ์ , ์ˆ˜๋ฌธํ•™์ , ์ œ๋„์ ์ธ ์ธก๋ฉด์—์„œ ๋ฌผ์ด ๋ฐฐ๋ถ„๋  ์ˆ˜

์žˆ๊ณ (Yoo, 2005), ์œ ์—ญ ์ˆ˜์ž์›๊ด€๋ฆฌ ์‹œ์„ค์˜ ์ „์ฒด์ ์ธ ๋ฐฐ์น˜ ๋ฐ

์šด์˜์กฐ๊ฑด์„ ๋‹ค์–‘ํ•˜๊ฒŒ ๋ฐ˜์˜ํ•  ์ˆ˜ ์žˆ๋„๋ก ๊ตฌ์ถ•๋˜์–ด ์žˆ๋Š” ํ•˜์ฒœ

์œ ์—ญ ๊ด€๋ฆฌ ์˜์‚ฌ ๊ฒฐ์ • ์ง€์›์‹œ์Šคํ…œ์ด๋‹ค(Labadie and Larson,

2007). MODSIM์€ K-WEAP๋ชจํ˜•๊ณผ ๊ฐ™์€ ์ตœ์ ํ™” ๋ฐฉ๋ฒ• ์ค‘ ์„ 

ํ˜•๊ณ„ํš๋ฒ•์„ ํ†ตํ•ด ์ˆ˜์ž์› ๋ถ„๋ฐฐ๋ฅผ ์ˆ˜ํ–‰ํ•˜๋ฉฐ ์ด๋ฅผ ํšจ์œจ์ ์œผ๋กœ

ํ•ด์„ํ•˜๊ธฐ ์œ„ํ•œ ์ •์ˆ˜ ๊ธฐ๋ฐ˜์˜ Lagrangian relaxation algorithm

RELAX-IV๋ฅผ ์ ์šฉํ•˜์—ฌ ํ•ด์„ํ•œ๋‹ค. RELAX-IV์•Œ๊ณ ๋ฆฌ์ฆ˜์€

simplex method์— ๋Œ€๋น„ ํ•ด์„ ์ˆ˜ํ–‰์‹œ๊ฐ„์ด ์ตœ์†Œ 5๋ฐฐ ์ด์ƒ ๋น ๋ฅด

๋‹ค๊ณ  ์•Œ๋ ค์ ธ ์žˆ๋‹ค(K-Water, 2008).

2.2 ๋ชจํ˜•์˜ ์ตœ์ ํ™” ๋ฐฉ๋ฒ• ๋น„๊ต ๋ฐ ํŠน์„ฑ ๊ณ ์ฐฐ

K-WEAP๊ณผ MODSIM ๋ชจํ˜•์€ ์ตœ์ ํ™” ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ํ†ตํ•ด

์ˆ˜์š”๋Ÿ‰์— ๋Œ€ํ•œ ๋ฌผ ๊ณต๊ธ‰์„ ๋ฐฐ๋ถ„ํ•˜๋ฉฐ ๋ชฉ์ ํ•จ์ˆ˜ ๋ฐ ์ œ์•ฝ์กฐ๊ฑด์„

๋น„๊ตํ•œ ํ‘œ๋Š” ์•„๋ž˜ Table 1๊ณผ ๊ฐ™๋‹ค. ๋จผ์ € ๋ชฉ์ ํ•จ์ˆ˜๋ฅผ ๋น„๊ตํ•ด๋ณด

๋ฉด, K-WEAP ๋ชจํ˜•์€ ์ˆ˜์š”์ฒ˜๋ฅผ ๊ธฐ์ค€์œผ๋กœ ๊ฐ ์ˆ˜์š”์ฒ˜์˜ ์ตœ์ข…์ถฉ

์กฑ๋ฅ (water demand satisfaction ratio)์ด ์ตœ๋Œ€ํ™”(maximize)

๋  ์ˆ˜ ์žˆ๋„๋ก ์ˆ˜์ž์› ๋ฐฐ๋ถ„์ด ์ด๋ฃจ์–ด์ง€๊ฒŒ ๋˜๋ฏ€๋กœ ์ตœ์†Œ๋น„์šฉ์ด๋‚˜

์ตœ๋Œ€ ์ด์œค์„ ๋ชฉ์ ์œผ๋กœ ํ•˜๋Š” ์ตœ์ ํ™”์™€๋Š” ์„ฑ๊ฒฉ์ด ๋‹ค๋ฅด๊ณ , ๋‹จ์ง€

์ฃผ์–ด์ง„ ๋ฐฐ๋ถ„์šฐ์„ ์ˆœ์œ„์— ๋”ฐ๋ผ ๋ฐฐ๋ถ„ํ•œ๋‹ค(Park et al., 2003). ๋ฐ˜

๋ฉด์˜ MODSIM์€ ๊ณต๊ธ‰์ฒ˜๋ฅผ ๊ธฐ์ค€์œผ๋กœ ๋„คํŠธ์›Œํฌ ํ๋ฆ„์˜ ์งˆ๋Ÿ‰

๋ณด์ „์„ ์œ ์ง€ํ•˜๋Š” ๋ฒ”์œ„์—์„œ ๊ณ„์‚ฐ ๊ธฐ๊ฐ„์— ๊ฑธ์ณ ํ๋ฆ„๊ณผ ๋น„์šฉ

(cost)์ด ์ตœ์†Œ๊ฐ€ ๋˜์–ด ์ƒ๋Œ€์  ์ด๋“์ด ๋งŽ์ด ๋ฐœ์ƒํ•˜๋Š” ์ˆ˜์š”์ฒ˜์—

๋ฌผ ๋ฐฐ๋ถ„์„ ์ˆ˜ํ–‰ํ•œ๋‹ค. ์ œ์•ฝ์กฐ๊ฑด์„ ๊ฒ€ํ† ํ•ด๋ณด๋ฉด K-WEAP๋ชจํ˜•

์€ ์ˆ˜์š”๋Ÿ‰์— ๋น„ํ•ด ๊ณต๊ธ‰๊ฐ€๋Šฅ๋Ÿ‰์ด ๋งŽ์œผ๋ฉด ์ถฉ์กฑ๋ฅ ์„ 100% ๋ชจ๋‘

๋งŒ์กฑํ•˜๊ฒ ์ง€๋งŒ, ์ˆ˜์š”๋Ÿ‰์„ ๋งŒ์กฑ์‹œํ‚ค๋Š” ์–‘์˜ ๋ฌผ์ด ์—†๋Š” ๊ฒฝ์šฐ ์ˆ˜

์š” ์š”๊ตฌ๋Ÿ‰์— ๋Œ€ํ•œ ๋น„์œจ๋งŒํผ ๋งŒ์กฑ์‹œํ‚ค๊ฒŒ ๋œ๋‹ค. ์—ฌ๊ธฐ์„œ, qk๋Š” ๋…ธ

๋“œ๋‚ด์˜ ์œ ์ž…๋Ÿ‰, qj๋Š” ์œ ์ถœ๋Ÿ‰, S๋Š” ์ €๋ฅ˜๋ณ€ํ™”๋Ÿ‰, C๋Š” ์ˆœ์†Œ๋ชจ๋Ÿ‰,

Table 1. Comparison of optimization method for K-WEAP and MODSIM models

Classification K-WEAP MODSIM

Objective function Max (Water demand satisfaction ratio) Minโˆˆ

Straint condition

0 โ‰ค Water demand satisfaction ratio โ‰ค 1 ยท

โˆˆ

โˆˆ

ยฑ , โˆˆ โˆˆ

โˆˆ

โˆˆ

โ‰ฆ โ‰ฆ โˆˆ

Page 4: Comparison and discussion of MODSIM and K-WEAP model

J.-H. Oh et al. / Journal of Korea Water Resources Association 52(7) 463-473466

Li๋Š” ๋งํฌ๋‚ด์˜ ์œ ์ž…๋Ÿ‰, Lo๋Š” ์œ ์ถœ๋Ÿ‰, Lloss๋Š” ์†์‹ค๋Ÿ‰์œผ๋กœ ์งˆ๋Ÿ‰๋ณด

์กด(mass balance)์ƒํƒœ๋ฅผ ์˜๋ฏธํ•œ๋‹ค. MODSIM ๋ชจํ˜•์˜ ์ œ์•ฝ์กฐ

๊ฑด์˜ OPRPi๋Š” ์šฐ์„ ์ˆœ์œ„๋ฅผ ์˜๋ฏธํ•˜์—ฌ ๋ชฉ์ ํ•จ์ˆ˜์˜ Ck๋ฅผ ๊ฒฐ์ •ํ•˜

๋Š” ๋ณ€์ˆ˜๋กœ์„œ ์ˆ˜์š”์ฒ˜๊ฐ„ ์ƒ๋Œ€์ ์ธ ๋น„์šฉ์„ ๊ณ„์‚ฐ์„ ์ˆ˜ํ–‰ํ•œ๋‹ค. ์—ฌ

๊ธฐ์„œ, Oi๋Š” ๋…ธ๋“œ i์—์„œ ์‹œ์ž‘ํ•˜๋Š” ๋ชจ๋“  ์œ ์ถœ ๋งํฌ, Ii๋Š” ๋…ธ๋“œ i์—์„œ

๋๋‚˜๋Š” ๋ชจ๋“  ์œ ์ž… ๋งํฌ์ด๋ฉฐ, bit๋Š” ์‹œ๊ฐ„ t์ผ ๋•Œ ๋…ธ๋“œ i์—์„œ์˜ ์œ 

์ž… ํ˜น์€ ์ˆ˜์š”, t๋Š” ๋„คํŠธ์›Œํฌ์˜ ๋ชจ๋“  ๋…ธ๋“œ ์ˆ˜์ด๋ฉฐ, lkt๋Š” ์‹œ๊ฐ„ t์ผ

๋–„ ๋งํฌ k์—์„œ์˜ ํ•˜ํ•œ์น˜, ukt๋Š” ์‹œ๊ฐ„ t์ผ ๋•Œ ๋งํฌ k์—์„œ์˜ ์ƒํ•œ์น˜

๋ฅผ ๋‚˜ํƒ€๋‚ธ๋‹ค. ๋…ธ๋“œ ์ œ์•ฝ์กฐ๊ฑด(node constraints)์€ ์–ด๋–ค ๋…ธ๋“œ์—

์„œ ์œ ์ž…๋˜๋Š” ์–‘๊ณผ ์œ ์ถœ๋˜๋Š” ์–‘์˜ ํ•ฉ์€ ๊ฐ™์Œ์„ ์˜๋ฏธํ•˜๋ฉฐ, ์•„ํฌ

์ œ์•ฝ์กฐ๊ฑด(arc constraints)์€ ๋ชจ๋“  ์•„ํฌ๋‚˜ ๋งํฌ์— ๋Œ€ํ•œ ๋ฒ”์œ„์˜

์ƒํ•œ ๊ฐ’๊ณผ ํ•˜ํ•œ ๊ฐ’์„ ๊ฐ–๋Š”๋‹ค.

๋‘ ๋ชจํ˜•์˜ ๋ชฉ์ ํ•จ์ˆ˜์— ๋”ฐ๋ผ ์ˆ˜์ž์› ๋ฐฐ๋ถ„๋Ÿ‰์˜ ๋น„๊ต๋ฅผ ์œ„ํ•ด

์œ„์˜ Fig. 2์™€ ๊ฐ™์€ ์˜ˆ์ œ๋ฅผ ํ†ตํ•ด ํ•ด์„ํ•˜์˜€๋‹ค. Fig. 2(a)๋Š” ๋„คํŠธ

์›Œํฌ์˜ ๋ชจ์‹๋„๋ฅผ ์˜๋ฏธํ•˜๊ณ , ๋‘ ๊ฐœ์˜ ์ˆ˜์š”์ฒ˜ A์™€ B๋Š” ์œ„์น˜์ •๋ณด

์™€ ๊ด€๊ณ„์—†์ด ๋™์ผํ•œ ์šฐ์„ ์ˆœ์œ„๋ฅผ ๊ฐ€์ง€๋ฉฐ, ์ˆ˜์š”๋Ÿ‰์€ ๊ฐ๊ฐ 100,

50์„ ์š”๊ตฌํ•˜๊ณ  ์žˆ๋Š” ์ƒํ™ฉ์œผ๋กœ ์ด ์ˆ˜์š”๋Ÿ‰์€ 150, ํ•˜์ฒœ์˜ ํ๋ฅด

๋Š” ๊ณต๊ธ‰๋Ÿ‰์€ 60์œผ๋กœ์„œ ์ถฉ์กฑ๋ฅ ์„ 100% ๋งŒ์กฑํ•  ์ˆ˜ ์—†๋Š” ๊ฒฝ์šฐ์ด

๋‹ค. Figs. 2(b) and 2(c)๋Š” K-WEAP๋ชจํ˜•๊ณผ MODSIM ๋ชจํ˜•์„

ํ™œ์šฉํ•˜์—ฌ ๋„คํŠธ์›Œํฌ ๋ชจ์‹๋„๋ฅผ ์‹ค์ œ ๋ฐ˜์˜ํ•œ ๋ชจํ˜• ๊ตฌ์ถ•๋„์ด๋‹ค.

์•ž์„œ ์ œ์‹œํ•œ ๋ชจํ˜•์˜ ํŠน์„ฑ์œผ๋กœ ์ธํ•ด K-WEAP์€ ์ตœ์ข… ์ˆ˜์š”์ถฉ

์กฑ๋ฅ ์„ ๋งŒ์กฑํ•˜๊ธฐ ์œ„ํ•ด ์ˆ˜์š”๋Ÿ‰์˜ ๋น„์œจ ๋ถ„๋ฐฐ๋ฅผ ์ˆ˜ํ–‰ํ•˜์—ฌ ์ˆ˜์š”

์ฒ˜ A์˜ ๋ฌผ ๋ถ€์กฑ์€ 60, ์ˆ˜์š”์ฒ˜ B์˜ ๋ฌผ ๋ถ€์กฑ์€ 30์œผ๋กœ ๋ถ„์„๋œ๋‹ค.

ํ•œํŽธ, MODSIM๋ชจํ˜•์—์„œ๋Š” ์ˆ˜์š”์ฒ˜ A์˜ ๋ฌผ ๋ถ€์กฑ๋Ÿ‰์€ 40 ๋˜๋Š”

90, ์ˆ˜์š”์ฒ˜ B์˜ ๋ฌผ ๋ถ€์กฑ๋Ÿ‰์€ 0 ๋˜๋Š” 50์œผ๋กœ ๋ถ„์„๋˜๋Š”๋ฐ, ์ด๊ฒƒ

์€ ์šฐ์„ ์ˆœ์œ„๊ฐ€ ๋™์ผํ•œ ์ˆ˜์š”์ฒ˜๊ฐ€ 2๊ฐœ ์ด์ƒ ๋  ๊ฒฝ์šฐ ๋ชฉ์ ํ•จ์ˆ˜

์— ๋”ฐ๋ผ ๋ฐœ์ƒํ•˜๋Š” ๋น„์šฉ์ด ๊ฐ™๊ธฐ ๋•Œ๋ฌธ์— ๋‹ค์ˆ˜์˜ ์ตœ์ ํ•ด๊ฐ€ ๋ฐœ์ƒ

ํ•˜๋Š” ์กฐ๊ฑด์œผ๋กœ ๊ฒฐ๊ณผ์ ์œผ๋กœ๋Š” ๋…ธ๋“œ ์ƒ์„ฑ ์ˆœ์œ„๋ฅผ ๊ณ ๋ คํ•˜์—ฌ ๋ฌผ

๋ถ„๋ฐฐ๋ฅผ ์ˆ˜ํ–‰ํ•œ๋‹ค. ์ด์— MODSIM์€ ๋ชจํ˜•์˜ ํŠน์„ฑ์ƒ ์ตœ์†Œ๋น„

์šฉ์„ ๊ณ„์‚ฐํ•˜๊ธฐ ์œ„ํ•œ ์šฐ์„ ์ˆœ์œ„์˜ ์ ์šฉ์ด ํ•„์ˆ˜์ ์ธ ๊ฒƒ์„ ์•Œ ์ˆ˜

์žˆ๋‹ค.

3. ๋Œ€์ƒ ์œ ์—ญ ๋ฐ ๋ชจํ˜• ๊ตฌ์ถ•์„ ์œ„ํ•œ ์ž…๋ ฅ ์ž๋ฃŒ ์ •๋ฆฌ

3.1 ๋Œ€์ƒ ์œ ์—ญ

๋ณธ ์—ฐ๊ตฌ์˜ ์ ์šฉ ๋Œ€์ƒ ์œ ์—ญ์€ ํ•œ๊ฐ•์œผ๋กœ์„œ 4๊ฐœ์˜ ๋Œ€๊ถŒ์—ญ์œผ๋กœ

๊ตฌ์„ฑ๋˜์–ด ์žˆ๊ณ , ํ•œ๊ฐ• 34,428.1 km2, ์•ˆ์„ฑ์ฒœ 1,658.66 km2, ํ•œ๊ฐ•

์„œํ•ด 1,970.81 km2, ํ•œ๊ฐ•๋™ํ•ด 3,889.68 km2๋กœ ์ด 41,947.25 km2

๋กœ ๊ตญ๋‚ด 5๋Œ€๊ฐ• ๊ถŒ์—ญ ์ค‘ ๊ฐ€์žฅ ํฐ ๋ฉด์ ์„ ์ฐจ์ง€ํ•˜๊ณ  ์žˆ๋‹ค. ํ•œ๊ฐ• ์œ 

์—ญ์€ ์ง€์—ญ์  ํŠน์ˆ˜์„ฑ์œผ๋กœ ์ธํ•ด ๋‹ค๋ฅธ ์œ ์—ญ๊ณผ ๋‹ค๋ฅด๊ฒŒ ๋ณธ๋ฅ˜ ๋‚ด ํ•˜

๊ตฟ๋‘‘์ด ์กด์žฌํ•˜์ง€ ์•Š๊ณ , ์ƒ๋ฅ˜๋ถ€๋Š” ๊ณต์œ ํ•˜์ฒœ์ธ ๋ถํ•œ๊ฐ•๊ณผ ์ž„์ง„

๊ฐ•์„ ํฌํ•จํ•˜๊ณ  ์žˆ์–ด ๋‹ค๋ฅธ ์œ ์—ญ์— ๋น„ํ•ด ์ˆ˜์ž์› ๊ด€๋ฆฌ์™€ ํŠน์„ฑ์ด

ํŠน๋ณ„ํ•œ ์œ ์—ญ์ด๋‹ค. ์ˆ˜์ž์›์žฅ๊ธฐ์ข…ํ•ฉ๊ณ„ํš(MOLIT, 2016)์—์„œ

๋Š” ํ•œ๊ฐ• ๊ถŒ์—ญ์„ ํ•œ๊ฐ• 24๊ฐœ ์œ ์—ญ, ์•ˆ์„ฑ์ฒœ 1๊ฐœ, ํ•œ๊ฐ•์„œํ•ด 2๊ฐœ, ํ•œ

๊ฐ•๋™ํ•ด 3๊ฐœ ๋“ฑ ์ด 30๊ฐœ์˜ ์ค‘๊ถŒ์—ญ์œผ๋กœ ๊ตฌ๋ถ„ํ•˜์—ฌ ๋„คํŠธ์›Œํฌ๋ฅผ ๊ตฌ

์ถ•ํ•˜์˜€๊ณ , ์ฃผ์š” ์ˆ˜์ž์›์‹œ์„ค๋ฌผ์€ 4๊ฐœ์˜ ๋‹ค๋ชฉ์ ๋Œ, 2๊ฐœ ์šฉ์ˆ˜์ „

์šฉ๋Œ, 1๊ฐœ ๋ฐœ์ „์ „์šฉ๋Œ, 2๊ฐœ ํ•˜๊ตฟ๋‘‘ ๋ฐ ๋‹ด์ˆ˜ํ˜ธ, 3๊ฐœ ๋‹ค๊ธฐ๋Šฅ๋ณด ๋“ฑ

์ด 12๊ฐœ๋ฅผ ์ ์šฉํ•˜์˜€๋‹ค. ์•„๋ž˜์˜ Fig. 3๊ณผ Table 2๋Š” MODSIM

๋ชจํ˜• ๊ตฌ์ถ•์„ ์œ„ํ•œ ํ•œ๊ฐ• ์œ ์—ญ์˜ ๋Œ€๊ถŒ์—ญ ๋ฐ ์ค‘๊ถŒ์—ญ, ์œ ์—ญ ๋‚ด ์ˆ˜์ž

์›์‹œ์„ค๋ฌผ์˜ ์ •๋ณด๋ฅผ ๋ณด์—ฌ์ฃผ๊ณ  ์žˆ๋‹ค.

(a) Network diagram (b) K-WEAP (c) MODSIM

Fig. 2. Example to compare water shortage results

Fig. 3. Study area for construction of MODSIM

Page 5: Comparison and discussion of MODSIM and K-WEAP model

J.-H. Oh et al. / Journal of Korea Water Resources Association 52(7) 463-473 467

3.2 ์ž…๋ ฅ์ž๋ฃŒ ์ •๋ฆฌ ๋ฐ ๋ชจํ˜•์˜ ๊ตฌ์ถ•

๋ฌผ ๋ถ€์กฑ ์ „๋ง๊ณผ ํ‰๊ฐ€๋ฅผ ์œ„ํ•ด์„œ๋Š” ์ž์—ฐ์œ ์ถœ๋Ÿ‰, ๊ด‘์—ญ๋„์ˆ˜๋Ÿ‰,

์šฉ์ˆ˜์ˆ˜์š”๋Ÿ‰, ํšŒ๊ท€์œจ, ํ•˜์ฒœ์œ ์ง€์œ ๋Ÿ‰, ์šฐ์„ ์ˆœ์œ„ ๋“ฑ์ด ํ•„์š”ํ•˜

๋‹ค. ์ˆ˜์ž์›์žฅ๊ธฐ์ข…ํ•ฉ๊ณ„ํš(MOLIT, 2016)์—์„œ๋Š” 2020๋…„์˜

๋ชฉํ‘œ์—ฐ๋„๋ฅผ ๊ธฐ์ค€์œผ๋กœ ๊ณ ์ˆ˜์š”, ๊ธฐ์ค€์ˆ˜์š”, ์ €์ˆ˜์š” ๋“ฑ 3๊ฐœ์˜ ์‹œ

๋‚˜๋ฆฌ์˜ค๋กœ ๊ตฌ๋ถ„ํ•˜์—ฌ 1966๋…„โˆผ2015๋…„(49๊ฐœ๋…„)์˜ ํ•˜์ฒœ์œ ๋Ÿ‰

์ด ์žฅ๋ž˜์— ๋ฐ˜๋ณต๋œ๋‹ค๋Š” ๊ฐ€์ •์„ ํ†ตํ•ด ๋ฌผ ๋ถ€์กฑ์„ ์‚ฐ์ •ํ•˜์˜€์œผ๋ฉฐ

๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋ชฉํ‘œ์—ฐ๋„ 2020๋…„์˜ ๊ธฐ์ค€์ˆ˜์š”์ž๋ฃŒ๋ฅผ ์ด์šฉํ•˜

์—ฌ ๋ชจํ˜•์— ์ ์šฉํ•˜์˜€๋‹ค. ๋ถ„์„ ๊ฒฐ๊ณผ์˜ ๋น„๊ต๋ฅผ ์œ„ํ•ด ์ž์—ฐ์œ ์ถœ๋Ÿ‰

์€ 4๋‹จ ํƒฑํฌ๋ชจํ˜•์„ ์ด์šฉํ•œ ๋งค๊ฐœ๋ณ€์ˆ˜ ๊ฒ€์ฆ๊ณผ ์ง€์—ญํ™”๊ฐ€ ์ˆ˜ํ–‰๋œ

๊ฒฐ๊ณผ๋ฅผ ์ ์šฉํ•˜์˜€์œผ๋ฉฐ ์ž๋ฃŒ์˜ ๊ธฐ๊ฐ„์€ 1966๋…„โˆผ2015๋…„(49

๋…„)์˜ ๋ฐ˜์ˆœ ๋‹จ์œ„(5์ผ) ์ž๋ฃŒ๋ฅผ ์ค‘๊ถŒ์—ญ ๋‹จ์œ„๋กœ ๊ตฌ์„ฑํ•˜์˜€๋‹ค. ์ˆ˜

์ž์›์‹œ์„ค๋ฌผ์€ ์ €์ˆ˜์ง€์™€ ๋‹ค๊ธฐ๋Šฅ๋ณด 12๊ฐœ, ๊ด‘์—ญ์œผ๋กœ ๋„์ˆ˜๋˜๋Š”

์–‘๊ณผ ํ•˜์ฒœ์œ ์ง€์œ ๋Ÿ‰ 24๊ฐœ ์ง€์  ๋“ฑ ์ผ๊ด€์„ฑ ์œ ์ง€๋ฅผ ์œ„ํ•ด ์ €์ˆ˜์šฉ

๋Ÿ‰๊ณผ ์šด์˜๋ฐฉ๋ฒ• ๋“ฑ์„ ๊ทธ๋Œ€๋กœ ์ ์šฉํ•˜์˜€๋‹ค. ์šฉ์ˆ˜์ˆ˜์š”๋Ÿ‰์€ ์ƒํ™œ,

๊ณต์—…, ๋†์—…, ํ•˜์ฒœ์œ ์ง€์œ ๋Ÿ‰์œผ๋กœ ์‹œยท๊ตฐ ๋‹จ์œ„๋กœ ์ƒ์„ฑ๋œ ์ˆ˜์š”๋Ÿ‰

์„ ํ† ๋Œ€๋กœ ์ค‘๊ถŒ์—ญ ๋‹จ์œ„๋กœ ๋ณ€ํ™˜ํ•œ ์ˆ˜์š”๋Ÿ‰์„ ์ ์šฉํ•˜์˜€์œผ๋ฉฐ ๋ณธ

์—ฐ๊ตฌ์—์„œ๋„ ์ผ๊ด€์„ฑ์„ ์œ ์ง€ํ•˜์˜€๋‹ค. ์ˆ˜์š” ํŒจํ„ด์€ ์ƒยท๊ณต์šฉ์ˆ˜์˜

๊ฒฝ์šฐ ์—ฐ์ค‘ ์ผ์ •ํ•œ ์ด์šฉ ํŒจํ„ด์„ ๊ฐ–๋Š” ๊ฒƒ์œผ๋กœ ๊ฐ€์ •ํ•˜์˜€๊ณ , ๋†์—…

์šฉ์ˆ˜๋Š” ๋…ผ, ๋ฐญ, ์ถ•์‚ฐ์œผ๋กœ ๊ตฌ๋ถ„ํ•˜์˜€์œผ๋ฉฐ ๊ฐ ํ•ญ๋ชฉ๋ณ„ ์‹œ๊ฐ„์— ๋”ฐ๋ฅธ

์ด์šฉ ํŒจํ„ด์„ ์ฐธ์กฐํ•˜์—ฌ ์ ์šฉํ•˜์˜€๋‹ค(MLTM, 2011). ๋‹ค์Œ

Table 3์€ ์ˆ˜์ž์›์žฅ๊ธฐ์ข…ํ•ฉ๊ณ„ํš์—์„œ ํ™œ์šฉํ•œ ์šฉ์ˆ˜์ˆ˜์š”๋Ÿ‰์„

๋ณด์—ฌ์ฃผ๊ณ  ์žˆ์œผ๋ฉฐ, Fig. 4๋Š” ํ•œ๊ฐ•์œ ์—ญ์— ์ ์šฉํ•œ ๋†์—…์šฉ์ˆ˜ ํ•ญ๋ชฉ

๋ณ„ ์ˆ˜์š” ํŒจํ„ด์„ ๋ณด์—ฌ์ฃผ๊ณ  ์žˆ๋‹ค.

MODSIM ๋ชจํ˜• ๋„คํŠธ์›Œํฌ ๊ตฌ์„ฑ์„ ์œ„ํ•œ ์ฃผ์š” ๋…ธ๋“œ๋Š” ๋น„์ €๋ฅ˜

๋…ธ๋“œ(nonstorage), ๋งํฌ(link) ๋˜๋Š” ์•„ํฌ(arcs), ์ˆ˜์š”์ฒ˜(consumptive

demand), ์ €์ˆ˜์ง€(reservoir), ํ†ต๊ณผ์ˆ˜์š”(flowthru demand), ์ถœ

๊ตฌ(network sink) ๋“ฑ์ด๋‹ค. ๋น„์ €๋ฅ˜๋…ธ๋“œ๋Š” ํ•˜์ฒœ, ํšŒ๊ท€์ง€์ , ์ง€๋ฅ˜

์œ ์ž… ๋“ฑ ์‹œ๊ณ„์—ด๋ฐ์ดํ„ฐ(time series data)๋ฅผ ์ž…๋ ฅํ•˜๊ณ , ์ €์ˆ˜์ง€๋…ธ

๋“œ๋Š” ์šฐ์„ ์ˆœ์œ„, ์ €์ˆ˜์ง€์˜ ์ œ์›์ •๋ณด ๋ฐ ์šด์˜์„ ์ž…๋ ฅํ•  ์ˆ˜ ์žˆ๋‹ค.

๋˜ํ•œ ๋งํฌ๋Š” ๋…ธ๋“œ์™€ ๋…ธ๋“œ๊ฐ„ ๋ฌผ ์ด๋™๊ณผ ํ•˜๋„ ์†์‹ค(losses)์™€ ๋น„

์šฉ(cost)์„ ์ ์šฉํ•  ์ˆ˜ ์žˆ๋‹ค. ์ˆ˜์š”์ฒ˜๋Š” ์šฐ์„ ์ˆœ์œ„(priority)์™€ ์‹œ

๊ณ„์—ด๋กœ ๊ตฌ์„ฑ๋œ ์ˆ˜์š”๋Ÿ‰, ํšŒ๊ท€์ง€์  ๋“ฑ์„ ์ž…๋ ฅํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ, ํ†ต๊ณผ

์ˆ˜์š”๋…ธ๋“œ๋Š” ์†Œ๋ชจ๋˜์ง€ ์•Š๋Š” ์ˆ˜์š”๋Ÿ‰(nonconsumptive demand)

์œผ๋กœ ๊ด‘์—ญ์˜ ์ด๋™์ด๋‚˜ ํ•˜์ฒœ์œ ์ง€์œ ๋Ÿ‰ ์ ์šฉ์— ํ™œ์šฉํ•  ์ˆ˜ ์žˆ๋‹ค.

์ถœ๊ตฌ๋…ธ๋“œ๋Š” ์‹œ์Šคํ…œ์˜ ์งˆ๋Ÿ‰๋ณด์ „์„ ์œ ์ง€ํ•˜๋Š” ์ฐจ์›์—์„œ ๋ชจ๋“  ๋„ค

ํŠธ์›Œํฌ ๊ตฌ์„ฑ ์™„๋ฃŒ์‹œ ์œ ์—ญ ์ถœ๊ตฌ๋ถ€์— ํ•ญ์‹œ ์ ์šฉํ•ด์•ผ ํ•œ๋‹ค. ์ •๋ฆฌ

๋œ ์ž…๋ ฅ ์ž๋ฃŒ๋ฅผ MODSIM์—์„œ ์š”๊ตฌํ•˜๋Š” ๋…ธ๋“œ์— ๋งž์ถฐ ์ ์šฉํ•˜

์˜€์œผ๋ฉฐ, ๊ตฌ์„ฑํ•œ ๋ชจํ˜•์€ Fig. 5์™€ ๊ฐ™๋‹ค.

Table 2. Water resource facility in the Han-river basin

Basin code Name Major purposeStorage Capacity (million m3)

Total Effective Inactive

1001 Gwangdong Water supply dam 13.1 9.5 2.3

1003 Chungju Multi-function dam 2619.6 2251.7 23.7

1006 Hoengseong Multi-function dam 86.9 86.9 2.6

1007 Ippo Multi-function weir 16.6 14.3 2.8

1007 Yeoju Multi-function weir 13.4 11.3 6.4

1007 Gangcheon Multi-function weir 11.0 8.7 2.4

1010 Hwacheon Hydropower 1018.4 1018.4 360.4

1012 Soyanggang Multi-function dam 2764.8 2478.9 307.2

1021 Hwanggang Multi-function dam 430.0 380.0 30.0

1101 Anseongcheon Barrage Barrage and reservoir 142.0 142.0 59.1

1202 Namyang Barrage Barrage and reservoir 31.0 31.0 19.6

1302 Dalbang Water supply dam 8.7 7.6 0.1

Fig. 4. Water demand pattern of agricultural water by type

Page 6: Comparison and discussion of MODSIM and K-WEAP model

J.-H. Oh et al. / Journal of Korea Water Resources Association 52(7) 463-473468

Table 3. Water demand for national water resources plan unit : m3/year

Basin code

Agricultural

Municipal Industrial Note Paddy field FieldLivestock

Irrigation Non-irrigation Irrigation

1001 5,694 88 14,340 371 17,245,537 27,893,614 ใ€€

1002 21,982 1,671 20,710 1,100 12,795,939 1,117,333 ใ€€

1003 35,315 3,770 14,750 1,655 42,122,814 18,839,260 ใ€€

1004 108,644 4,365 19,400 5,184 56,469,782 13,838,990 ใ€€

1005 40,711 2,362 8,253 1,230 5,634,615 3,339,934 ใ€€

1006 65,766 9,057 4,741 4,408 81,812,607 7,182,898 ใ€€

1007 179,880 74,912 22,977 16,388 129,155,977 83,819,282 ใ€€

1008 0 0 0 0 0 0 North Korea

1009 2,349 369 421 58 42,851 50,009 ใ€€

1010 21,865 4,416 4,576 906 12,015,748 1,608,204 ใ€€

1011 9,011 2,659 3,592 109 6,185,845 278,769 ใ€€

1012 10,432 1,916 6,260 594 13,466,273 39,437,830 ใ€€

1013 16,909 426 4,067 1,024 50,197,399 16,902,565 ใ€€

1014 37,968 4,276 3,321 2,145 15,833,681 4,983,631 ใ€€

1015 10,643 1,139 2,905 1,209 27,687,995 683,643 ใ€€

1016 12,159 2,209 5,224 678 87,248,137 2,603,186 ใ€€

1017 6,258 3,156 1,379 650 354,607 61,508 ใ€€

1018 17,320 6,466 28,375 1,810 1,624,948,247 79,901,787 ใ€€

1019 110,418 7,797 20,261 2,601 536,918,484 22,260,231 ใ€€

1020 0 0 0 0 0 0 ใ€€

1021 29,457 5,986 341 788 1,552,775 352,060 ใ€€

1022 130,829 31,546 9,965 11,889 103,945,562 50,400,604 ใ€€

1023 73,777 11,993 2,053 4,036 28,189,707 86,827,267 ใ€€

1024 11,220 261 139 359 783,573 188,910 ใ€€

1101 322,493 32,956 20,072 12,197 390,612,384 135,723,432 ใ€€

1201 109,646 28,511 4,666 1,988 269,303,985 25,241,473 ใ€€

1202 204,263 31,148 38,503 5,473 171,121,444 171,424,091 ใ€€

1301 53,646 7,733 2,182 925 26,543,945 1,731,414 ใ€€

1302 51,156 2,651 5,854 868 50,685,341 15,553,855 ใ€€

1303 8,736 479 4,482 283 24,731,234 722,884 ใ€€

2001 ใ€€ ใ€€ ใ€€ ใ€€ 11,400,000 ใ€€

Outside basin

(Diversion)

3011 ใ€€ ใ€€ ใ€€ ใ€€ 46,460,000 ใ€€

3101 ใ€€ ใ€€ ใ€€ ใ€€ 18,270,000 ใ€€

3201 ใ€€ ใ€€ ใ€€ ใ€€ 38,390,000 ใ€€

3202 ใ€€ ใ€€ ใ€€ ใ€€ 52,960,000 ใ€€

Fig. 5. Construction of MODSIM model in the Han-river basin

Page 7: Comparison and discussion of MODSIM and K-WEAP model

J.-H. Oh et al. / Journal of Korea Water Resources Association 52(7) 463-473 469

3.3 ์šฐ์„ ์ˆœ์œ„ ์ ์šฉ

์ˆ˜์š”์ฒ˜ ๊ณต๊ธ‰ ์šฐ์„ ์ˆœ์œ„๋Š” ์„ ํ–‰์—ฐ๊ตฌ๋ฅผ ์ฐธ์กฐํ•˜์—ฌ ์ ์šฉํ•˜์˜€

๋‹ค. Yoo (2005)๋Š” ์ˆ˜๋ฆฌ๊ถŒ์„ ๋ฐ˜์˜ํ• ๋งŒํผ ์ˆ˜๋ฆฌ๊ถŒ์ด ์ฒด๊ณ„ํ™”๋˜

์–ด ์žˆ์ง€ ์•Š์•„ ์ƒ๋ฅ˜ ๋ฐ ์ง€๋ฅ˜์— ์šฐ์„  ๊ณต๊ธ‰ํ•˜๋Š” ์›์น™์„ ๋‘๊ณ , ์šฉ๋„

๋ณ„๋กœ๋Š” ์ƒํ™œ, ๊ณต์—…, ๋†์—…, ํ•˜์ฒœ์œ ์ง€์šฉ์ˆ˜ ์ˆœ์œผ๋กœ ์ ์šฉํ•˜์˜€์œผ

๋ฉฐ, Ahn et al. (2009) ๊ฐ™์€ ๋ฐฉ๋ฒ•์„ ์ ์šฉํ•œ ๋ฐ” ์žˆ๋‹ค. ์ด์— ๋ณธ ์—ฐ๊ตฌ

์—์„œ๋„ ์„ ํ–‰์—ฐ๊ตฌ๋ฅผ ์ฐธ์กฐํ•˜์—ฌ Table 4์™€ ๊ฐ™์ด ๊ด‘์—ญ๋„์ˆ˜(Div)

๋ฅผ ํฌํ•จํ•œ ์ƒ๋ฅ˜ ์ˆ˜์š”์ฒ˜๊ฐ€ ํ•˜๋ฅ˜ ์ˆ˜์š”์ฒ˜๋ณด๋‹ค ์šฐ์„ , ์ง€๋ฅ˜ ์ˆ˜์š”์ฒ˜

๊ฐ€ ๋ณธ๋ฅ˜ ์ˆ˜์š”์ฒ˜๋ณด๋‹ค ์šฐ์„  ๊ณต๊ธ‰ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ์ ์šฉํ•˜์˜€์œผ๋ฉฐ, ์šฉ

๋„๋ณ„๋กœ๋Š” ์ƒยท๊ณต์šฉ์ˆ˜, ๋†์—…์šฉ์ˆ˜, ํ•˜์ฒœ์œ ์ง€์œ ๋Ÿ‰ ์ˆœ์œผ๋กœ ์šฐ์„ ์ˆœ

์œ„๋ฅผ ์ ์šฉํ•˜์˜€๋‹ค.

4. ๋ฌผ ์ˆ˜๊ธ‰ ๋ถ„์„ ๊ฒฐ๊ณผ์˜ ๋น„๊ต ๋ฐ ๊ณ ์ฐฐ

4.1 ์šฐ์„ ์ˆœ์œ„ ์ ์šฉ ์—ฌ๋ถ€์— ๋”ฐ๋ฅธ K-WEAP๋ชจํ˜•์˜ ๋ฌผ ๋ถ€

์กฑ๋Ÿ‰ ๋น„๊ต ๋ถ„์„

๋ณธ ์ ˆ์—์„œ๋Š” K-WEAP๋ชจํ˜•๊ณผ MODSIM ๋ชจํ˜•์˜ ๋ฌผ์ˆ˜๊ธ‰ ๋ถ„

์„ ๊ฒฐ๊ณผ์— ์•ž์„œ ์šฐ์„ ์ˆœ์œ„์˜ ์ ์šฉ ์—ฌ๋ถ€์— ๋”ฐ๋ฅธ ๋ฌผ ๋ถ€์กฑ ๋ถ„์„๊ฒฐ

๊ณผ์˜ ์ฐจ์ด๋ฅผ ๋ณด๊ณ ์ž K-WEAP๋ชจํ˜•์„ ์ด์šฉํ•˜์—ฌ ๋น„๊ต๋ฅผ ์ˆ˜ํ–‰

ํ•˜์˜€๋‹ค. ์ด์— ์ „์ฒด 30๊ฐœ ์ค‘๊ถŒ์—ญ ์ค‘ ํ•˜์ฒœ์˜ ์ตœ์ƒ๋ฅ˜๋ถ€ ์œ ์—ญ์ด๊ฑฐ

๋‚˜ ๋‹จ๋…์œผ๋กœ ๊ตฌ์„ฑ๋˜์–ด ํšŒ๊ท€์˜ ์˜ํ–ฅ๊ณผ ๋ฌด๊ด€ํ•œ ์œ ์—ญ์€ ์ œ์™ธํ•˜

๊ณ , ํšŒ๊ท€์˜ ์˜ํ–ฅ์„ ๋ฐ›์„ ์ˆ˜ ์žˆ๋Š” ์œ ์—ญ์ธ 13๊ฐœ ์œ ์—ญ(1003, 1005,

1007, 1009, 1010, 1012, 1013, 1015, 1017, 1018, 1019, 1023,

1024)์— ๋Œ€ํ•œ 49๊ฐœ๋…„๊ฐ„ ๋ฌผ ๋ถ€์กฑ๋Ÿ‰์„ ์‚ฐ์ •ํ•œ ๊ฒฐ๊ณผ๋Š” Fig. 6๊ณผ

๊ฐ™๋‹ค. ์—ฌ๊ธฐ์„œ, ๊ฒ€์ •์ƒ‰ ๋ง‰๋Œ€๋Š” ์ˆ˜์ž์›์žฅ๊ธฐ์ข…ํ•ฉ๊ณ„ํš๊ณผ ๋™์ผํ•œ

์ˆ˜์š”๋Ÿ‰๋น„ ๋ฐฐ๋ถ„์„ ์˜๋ฏธํ•˜๊ณ , ํšŒ์ƒ‰ ๋ง‰๋Œ€๋Š” ์šฐ์„ ์ˆœ์œ„๋ฅผ ์ ์šฉํ•œ ๊ฒฐ

๊ณผ๋ฅผ ๋‚˜ํƒ€๋‚ด๊ณ  ์žˆ์œผ๋ฉฐ ๋ฌผ ๋ถ€์กฑ๋Ÿ‰์˜ ์ฐจ์ด๋ฅผ ๊ฐ™์ด ๋„์‹œํ•˜์˜€๋‹ค.

๋ฌผ ๋ถ€์กฑ๋Ÿ‰ ์ฐจ์ด๋Š” ํ‰๊ท  1,035 ์ฒœm3์ด ๋ฐœ์ƒํ•˜์˜€๊ณ , ์ตœ๋Œ€ ๋ฌผ๋ถ€์กฑ

์˜ ์ฐจ์ด๋Š” 1993๋…„ 2,918.22 ์ฒœm3์˜ ์ฐจ์ด๊ฐ€ ๋ฐœ์ƒํ•˜์˜€์œผ๋ฉฐ, 49

๊ฐœ๋…„์˜ ๋ˆ„์ ์น˜๋กœ ๋ณด๋ฉด ์•ฝ 146,792.97 ์ฒœm3์— ํ•ด๋‹นํ•˜๋Š” ์–‘์œผ๋กœ

์šฐ์„ ์ˆœ์œ„๋ฅผ ์ ์šฉํ•œ ๋ชจํ˜•์—์„œ ๋ฌผ ๋ถ€์กฑ๋Ÿ‰์ด ๊ฐ์†Œ๋จ์„ ๋ณด์˜€๋‹ค.

๋˜ํ•œ Fig. 7์€ ํ•œ๊ฐ•์œ ์—ญ์—์„œ ๋ฌผ ๋ถ€์กฑ์ด ๋‹ค์†Œ ํฌ๊ฒŒ ๋ฐœ์ƒํ•œ

1991๋…„โˆผ1995๋…„์— ๋Œ€ํ•œ ์ฃผ์š” ๋‹ค๋ชฉ์ ๋Œ์ธ ์†Œ์–‘๊ฐ•๋Œ๊ณผ ์ถฉ์ฃผ

๋Œ์˜ ์ €์ˆ˜๋Ÿ‰์˜ ํŒจํ„ด์„ ๋„์‹œํ•˜์˜€๋‹ค. ํ‰๊ท ์ €์ˆ˜๋Ÿ‰์„ ๊ธฐ์ค€์œผ๋กœ

์†Œ์–‘๊ฐ•๋Œ์€ ๋™์ผ ์šฐ์„ ์ˆœ์œ„์‹œ 2,139.43๋ฐฑ๋งŒm3, ์šฐ์„ ์ˆœ์œ„๋ฅผ

์ ์šฉํ•œ ๊ฒฝ์šฐ ํ‰๊ท  2,334.84๋ฐฑ๋งŒm3์„ ๋ณด์˜€๊ณ , ์ถฉ์ฃผ๋Œ์€ ๋™์ผ

์šฐ์„ ์ˆœ์œ„์‹œ 1,840.84๋ฐฑ๋งŒm3, ์šฐ์„ ์ˆœ์œ„ ์ ์šฉ์‹œ 2029.69๋ฐฑ๋งŒ

m3์œผ๋กœ ์ฆ๊ฐ€ํ•œ ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ์ด๋Š” ์•ž์—์„œ ์„ค๋ช…ํ•œ ๋ฌผ์ˆ˜

๊ธ‰ ๋ถ„์„ ์ฒด๊ณ„์˜ ํŠน์„ฑ๊ณผ ๊ฐ™์ด ๋™์ผํ•œ ๊ณต๊ธ‰๋Ÿ‰๊ณผ ์ˆ˜์š”๋Ÿ‰์ด์ง€๋งŒ

์šฐ์„ ์ˆœ์œ„์— ๋”ฐ๋ผ ์ƒยท๊ณต์šฉ์ˆ˜์˜ ์ˆ˜์š”๋Ÿ‰์ด ๋” ๋จผ์ € ๋ฐฐ๋ถ„๋˜์–ด ํšŒ

๊ท€์ˆ˜๋Ÿ‰์ด ์ƒ๋Œ€์ ์œผ๋กœ ์ฆ๊ฐ€ํ•˜๋ฉด์„œ ๋Œ์—์„œ ๋ฐฉ๋ฅ˜๋ฅผ ํ•˜์ง€ ์•Š๋”๋ผ

๋„ ์šฉ์ˆ˜ ๊ณต๊ธ‰์„ ๋” ๋งŒ์กฑํ•  ์ˆ˜ ์žˆ๊ธฐ ๋•Œ๋ฌธ์ธ ๊ฒƒ์œผ๋กœ ํŒ๋‹จ๋œ๋‹ค.

Table 4. Application of priority considering space and demand type

Basin

Code

Consumptive DemandDiversion

(FlowThru)NoteMunicipal

&IndustrialAgricultural

1001 2 3 1 (Div_Gwangdong)

Sink :

4,999

Dam :

4,000

1002 1 2 ใ€€

1003 4 5 6 (Div_Chungju)

1004 1 2 ใ€€

1005 7 8 ใ€€

1006 2 3 1 (Div_Hoengsung)

1007

9 10 1007-1 (Gangcheon weir)

11 12 1007-2 (Yeoju weir)

13 14 1007-3 (Ippo weir)

15 16 1007-4

1008 1 2 ใ€€

1009 3 4 ใ€€

1010 5 6 ใ€€

1011 1 2 ใ€€

1012 3 4 ใ€€

1013 7 8 ใ€€

1014 1 2 ใ€€

1015 9 10 ใ€€

1016 1 2 ใ€€

1017 17 18 ใ€€

1018

- - 19 (Div_Paldangdam1)

- - 20 (Div_Paldangdam2)

- - 21 (Div_Hanriverweir)

22 23

1019 25 27 ใ€€

1020 1 2 ใ€€

1021 4 5 3 (Div_Hwanggangdam)

1022 1 2 ใ€€

1023 6 7 ใ€€

1024 28 29 ใ€€

1101 1 2 3 (Div_Asanho)

1201 1 2 ใ€€

1202 1 3 ใ€€

1301 1 2 ใ€€

1302 2 3 1 (Div_Dalbang)

1303 1 2 ใ€€

2001 1 - ใ€€

3011 1 - ใ€€

3101 1 - ใ€€

3201 1 - ใ€€

3202 1 - ใ€€

Page 8: Comparison and discussion of MODSIM and K-WEAP model

J.-H. Oh et al. / Journal of Korea Water Resources Association 52(7) 463-473470

4.2 ์šฐ์„ ์ˆœ์œ„๋ฅผ ๊ณ ๋ คํ•œ ๋ชจํ˜• ๊ฐ„ ๋ฌผ ๋ถ€์กฑ๋Ÿ‰ ๋น„๊ต ๋ถ„์„

๋ณธ ์ ˆ์—์„œ๋Š” ์•ž์„œ ๋ถ„์„ํ•œ ์šฐ์„ ์ˆœ์œ„๋ฅผ ์ ์šฉํ•œ K-WEAP๊ณผ

MODSIM์— ๋Œ€ํ•œ ๋ถ„์„ ๊ฒฐ๊ณผ๋ฅผ ๋น„๊ตํ•˜์˜€์œผ๋ฉฐ ์—ฐ๋ณ„ ๋ฌผ ๋ถ€์กฑ ์ด

๋Ÿ‰์„ ๋น„๊ตํ•œ ๊ฒฐ๊ณผ๋Š” Table 5์™€ Fig. 8๊ณผ ๊ฐ™๋‹ค. ์ตœ๋Œ€ ๋ฌผ ๋ถ€์กฑ์ด

๋ฐœ์ƒํ•œ ๋…„๋„๋Š” 2015๋…„์œผ๋กœ ๊ธฐ์กด์˜ ์ˆ˜์ž์›์žฅ๊ธฐ์ข…ํ•ฉ๊ณ„ํš์˜

๋ถ„์„๊ฒฐ๊ณผ์™€ ๋™์ผํ•œ ๊ฒฐ๊ณผ๊ฐ€ ๋‚˜ํƒ€๋‚ฌ๊ณ , ๋ชจํ˜• ๊ฐ„ ๋ฌผ ๋ถ€์กฑ๋Ÿ‰์˜ ์ฐจ

์ด๋Š” ์—ฐ ํ‰๊ท  892 ์ฒœm3, ์—ฐ๋ณ„๋กœ๋Š” โ€“88โˆผ2,697 ์ฒœm3์œผ๋กœ ๋ถ„์„

๋˜์–ด ์ƒ๋Œ€์˜ค์ฐจ ์ตœ๋Œ€ 5.3% ์ด๋‚ด์˜ ๊ฒฐ๊ณผ๋ฅผ ๋ณด์˜€๋‹ค. 5.3% ์ด๋‚ด์˜

๋ฌผ๋ถ€์กฑ๋Ÿ‰ ๋ฐœ์ƒ ์ฐจ์ด๋Š” ์ž…๋ ฅ์ž๋ฃŒ ๊ตฌ์„ฑ์‹œ ์†Œ์ˆซ์  ์ฒ˜๋ฆฌ๊ฒฐ๊ณผ์—

๋”ฐ๋ฅธ ์ฐจ์ด์™€ ์ƒ์ดํ•œ ์ตœ์ ํ™” ์•Œ๊ณ ๋ฆฌ์ฆ˜ ๋ฐ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋ฐ˜๋ณตํšŸ์ˆ˜

์ฐจ์ด๋กœ ํŒ๋‹จ๋œ๋‹ค. Fig. 9๋Š” ๋‘ ๋ชจํ˜•์˜ ๋ถ„์„ ๊ฒฐ๊ณผ์— ๋Œ€ํ•œ ์ƒ๊ด€์„ฑ

์„ ๋ถ„์„ํ•˜์˜€์œผ๋ฉฐ, ๊ฒฐ์ •๊ณ„์ˆ˜(R2)๋Š” 0.9999๋กœ ๋งค์šฐ ์œ ์‚ฌํ•จ์„ ๋‚˜

ํƒ€๋‚ด ์šฐ์„ ์ˆœ์œ„๋ฅผ ๊ณ ๋ คํ•œ ๋‘ ๊ฐœ ๋ชจํ˜•์— ๋Œ€ํ•œ ๋น„๊ต์™€ ๊ฒ€์ฆ ์ธก๋ฉด

์—์„œ ์ ์ ˆํžˆ ๋ถ„์„๋œ ๊ฒƒ์œผ๋กœ ํŒ๋‹จ๋œ๋‹ค.

Fig. 10์€ ์ค‘๊ถŒ์—ญ ์ค‘ ๋„์ˆ˜์˜ ์˜ํ–ฅ์ด ์—†์–ด ์ˆ˜๊ณ„์‚ฐ๊ณผ ๋น„๊ต ๊ฐ€

๋Šฅํ•œ ํ™์ฒœ๊ฐ• ์œ ์—ญ(1014)์˜ ์‹œ๊ณ„์—ด ๊ฒฐ๊ณผ๋ฅผ ์˜ˆ์‹œ๋กœ ๋‚˜ํƒ€๋ƒˆ์œผ

๋ฉฐ, ๊ฐ€๋กœ์ถ•์€ 1967๋…„โˆผ2015๋…„(49๊ฐœ๋…„)์˜ 5์ผ๋‹จ์œ„ ๊ฒฝ๊ณผ์ผ์ˆ˜

๋กœ ํ‘œํ˜„ํ•˜์˜€๋‹ค. ๋ชจํ˜•๊ฐ„์˜ ์‹œ๊ณ„์—ด ๋น„๊ต์‹œ ๋งค์šฐ ์œ ์‚ฌํ•œ ๋ฌผ ๋ถ€์กฑ

๋Ÿ‰๊ณผ ๋ฌผ๋ถ€์กฑ ์‹œ์ ์„ ๋™์ผํ•˜๊ฒŒ ์ œ๊ณตํ•˜๊ณ  ์žˆ์–ด ๋ถ„์„๊ฒฐ๊ณผ์˜ ์ผ๊ด€

์„ฑ์„ ํ™•์ธํ•˜์—ฌ ๋ชจํ˜•์˜ ๊ฒ€์ฆ์„ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค.

Fig. 6. Water shortage results due to priority by K-WEAP model

(a) Soyanggang dam (b) Chungju dam

Fig. 7. Storage capacity patterns due to priority in the major dam

Fig. 8. Comparison of water shortage results between K-WEAP and MODSIM

Page 9: Comparison and discussion of MODSIM and K-WEAP model

J.-H. Oh et al. / Journal of Korea Water Resources Association 52(7) 463-473 471

Fig. 11์€ ํ•œ๊ฐ• ์œ ์—ญ ๋‚ด ์ฃผ์š”๋Œ์ธ ์†Œ์–‘๊ฐ•๋Œ๊ณผ ์ถฉ์ฃผ๋Œ์˜ ์ €

์ˆ˜๋Ÿ‰์„ ๋น„๊ตํ•˜์˜€๋‹ค. ์†Œ์–‘๊ฐ•๋Œ์€ ์ƒ๋ฅ˜๋ถ€์— ์กด์žฌํ•˜์—ฌ ์ €์ˆ˜๋Ÿ‰

์˜ ๋ณ€ํ™”์™€ ๊ฒฝํ–ฅ์ด ์ผ๊ด€๋œ ํŒจํ„ด์„ ๋ณด์ด๋‚˜, ์ถฉ์ฃผ๋Œ์€ ํ•œ๊ฐ• ํ•˜๊ตฌ

๊นŒ์ง€ ์˜ํ–ฅ์„ ๋ฏธ์น˜๊ธฐ ๋•Œ๋ฌธ์— ์ €์ˆ˜๋Ÿ‰์˜ ์ผ๋ถ€ ์ฐจ์ด๊ฐ€ ๋ฐœ์ƒํ•˜์˜€

๋‹ค. ์ด๊ฒƒ์€ ์•ž์„œ ์ œ์‹œํ•œ ์ƒ๋Œ€์˜ค์ฐจ๊ฐ€ ๋ฐœ์ƒํ•œ ์›์ธ๊ณผ ๋งˆ์ฐฌ๊ฐ€์ง€

๋กœ ์ž…๋ ฅ์ž๋ฃŒ ๊ตฌ์„ฑ์‹œ ์†Œ์ˆซ์  ์ฒ˜๋ฆฌ๊ฒฐ๊ณผ์— ๋”ฐ๋ฅธ ์ฐจ์ด์™€ ์ƒ์ดํ•œ

์ตœ์ ํ™” ์•Œ๊ณ ๋ฆฌ์ฆ˜ ๋ฐ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋ฐ˜๋ณตํšŸ์ˆ˜ ์ฐจ์ด๋กœ ํŒ๋‹จ๋œ๋‹ค.

4.3 ๋ชจํ˜•์˜ ์žฅยท๋‹จ์  ๋ฐ ๊ตฌ๋™์‹œ๊ฐ„ ๊ฒ€ํ† 

4.3.1 ๋ชจํ˜•์˜ ์žฅยท๋‹จ์ (GUI ํŽธ์˜์„ฑ)

๋ฌผ์ˆ˜๊ธ‰ ๋ชจ๋ธ ๊ตฌ์ถ•์‹œ ๋ฌผ ์ด๋™ ์ •๋ณด์˜ ์ž…๋ ฅ์€ ํ•„์ˆ˜์ ์ด๋ฉฐ ์ 

์ ˆํžˆ ๊ตฌ๋ถ„ํ•˜๊ณ  ๋„คํŠธ์›Œํฌ๋ฅผ ์ƒ์„ฑํ•˜๊ธฐ ์œ„ํ•ด GIS๊ธฐ๋ฐ˜์˜ ๋ ˆ์ด์–ด

(layer)๋ฅผ ๋ชจํ˜• ๋‚ด๋ถ€์—์„œ ํ™œ์šฉํ•˜๋Š” ๊ฒƒ์€ ๋งค์šฐ ํšจ์œจ์ ์ผ ์ˆ˜ ์žˆ

๋‹ค. K-WEAP๋ชจํ˜•์€ GIS๋„๊ตฌ๋ฅผ ํ†ตํ•ด ํŽธ์ง‘ํ•œ shp ํ˜•ํƒœ์˜ ํŒŒ์ผ

์„ ๋ถˆ๋Ÿฌ๋“ค์—ฌ ์ž‘์—…์ด ๊ฐ€๋Šฅํ•˜์ง€๋งŒ, MODSIM ๋ชจํ˜•์€ ์ด๋ฏธ์ง€ํ˜•

ํƒœ๋กœ ๋ณ€ํ™˜ ์‚ฌ์šฉํ•˜์—ฌ์•ผ ํ•˜๋ฉฐ ์‚ฌ์ด์ฆˆ์™€ ์šฉ๋Ÿ‰์— ๋”ฐ๋ผ ์ผ๋ถ€ ์ œ์•ฝ

์ด ์กด์žฌํ•œ๋‹ค. K-WEAP ๋ชจํ˜•์€ ๋…ธ๋“œ๋ณ„ ์ •๋ณด๋ฅผ ๊ฐ๊ฐ ์ž…๋ ฅ๊ฐ€๋Šฅ

ํ•˜๊ณ , ๋ชจ์‹๋„์ƒ ๋‹ค๋ฅธ ์ƒ‰์œผ๋กœ ํ‘œํ˜„ํ•  ์ˆ˜ ์žˆ์–ด ๋‹จ์ˆœ ๋„คํŠธ์›Œํฌ์˜

๊ฒฝ์šฐ ๋ฌผ ์ด๋™ ๊ฒฝ๋กœ ํŒŒ์•…์ด ์›ํ™œํ•œ ํŠน์ง•์ด ์žˆ๋‹ค. MODSIM ๋ชจํ˜•

์€ ๋น„์„ ํ˜•์ ์ธ ํ•˜๋„ ์†์‹ค์ด๋‚˜ ํ•˜๋„์ถ”์ ์„ ์œ„ํ•œ ๊ธฐ๋Šฅ์„ ๊ณ„์‚ฐ์ƒ

ํฌํ•จํ•˜์ง€ ์•Š๋Š”๋‹ค๋ฉด ํ•˜์ฒœ, ์ทจ์ž…์ˆ˜๋กœ ๋“ฑ link์— ๋Œ€ํ•œ ๊ตฌ๋ถ„์ด ๋ณ„

๋„๋กœ ์กด์žฌํ•˜์ง€ ์•Š๊ณ , ๊ด‘์—ญ๊ณผ ํ•˜์ฒœ์œ ์ง€์œ ๋Ÿ‰, ํšŒ๊ท€์ˆ˜ ๋“ฑ์˜ ์ •๋ณด

Table 5. Comparison of water shortage results between K-WEAP

and MODSIM

YearWater shortage (1,000 m3) Difference

(1,000 m3)

Relative error

(%)MODSIM K-WEAP

1967 148,882 148,470 412 0.3%

1968 188,824 187,488 1,336 0.7%

1969 70,839 70,379 460 0.7%

1970 145,520 145,055 465 0.3%

1971 124,062 123,440 622 0.5%

1972 132,574 131,574 1,000 0.8%

1973 148,926 147,775 1,151 0.8%

1974 19,623 19,474 149 0.8%

1975 153,504 152,717 787 0.5%

1976 189,617 187,905 1,712 0.9%

1977 106,015 103,318 2,697 2.6%

1978 170,700 169,182 1,518 0.9%

1979 28,746 28,689 57 0.2%

1980 111,191 111,279 -88 -0.1%

1981 151,515 150,794 721 0.5%

1982 187,242 186,686 556 0.3%

1983 181,635 181,004 631 0.3%

1984 168,016 166,955 1,061 0.6%

1985 150,015 149,519 496 0.3%

1986 164,093 162,972 1,121 0.7%

1987 41,270 40,787 483 1.2%

1988 176,693 176,063 630 0.4%

1989 124,809 123,354 1,455 1.2%

1990 57,725 56,848 877 1.5%

1991 98,496 98,160 336 0.3%

1992 86,278 84,969 1,309 1.5%

1993 16,930 16,081 849 5.3%

1994 151,604 150,155 1,449 1.0%

1995 185,718 184,274 1,444 0.8%

1996 144,451 143,338 1,113 0.8%

1997 47,016 46,465 551 1.2%

1998 106,297 105,297 1,000 0.9%

1999 127,448 126,948 500 0.4%

2000 208,043 206,661 1,382 0.7%

2001 193,194 192,194 1,000 0.5%

2002 175,689 174,456 1,233 0.7%

2003 111,647 110,683 964 0.9%

2004 86,899 86,646 253 0.3%

2005 169,556 168,281 1,275 0.8%

2006 74,164 74,020 144 0.2%

2007 121,794 121,461 333 0.3%

2008 91,971 90,701 1,270 1.4%

2009 97,543 97,252 291 0.3%

2010 107,051 106,731 320 0.3%

2011 110,812 109,803 1,009 0.9%

2012 185,823 184,605 1,218 0.7%

2013 111,876 111,572 304 0.3%

2014 170,060 168,484 1,576 0.9%

2015 250,840 248,559 2,281 0.9%

Fig. 9. Coefficient of determination result between K-WEAP and

MODSIM

Fig. 10. Time series results in the Hongcheonriver basin (1014)

Page 10: Comparison and discussion of MODSIM and K-WEAP model

J.-H. Oh et al. / Journal of Korea Water Resources Association 52(7) 463-473472

๋Š” ๋„คํŠธ์›Œํฌ์—์„œ ๋ณ„๋„๋กœ ํ‘œํ˜„๋˜์ง€ ์•Š๊ธฐ ๋•Œ๋ฌธ์— ๋ชจ์‹๋„์ƒ ๊ฒฝ๋กœ

ํŒŒ์•…์ด ์–ด๋ ค์šด ๋‹จ์ ์ด ์žˆ์œผ๋‚˜ ๋„คํŠธ์›Œํฌ๊ฐ€ ๋ณต์žกํ•ด์ง€๋”๋ผ๋„ ๋ถ€

ํ•˜๊ฐ€ ๊ฑธ๋ฆฌ์ง€ ์•Š๊ณ , ๋…ธ๋“œ์™€ ๋…ธ๋“œ ๊ฐ„ ๊ฐ๊ฐ ๋งํฌ๋กœ ์—ฐ๊ฒฐํ•˜๊ธฐ ๋•Œ๋ฌธ

์— ์ˆ˜์ •๊ณผ ์ž๋ฃŒ๋ณด์™„์ด ํŽธ๋ฆฌํ•œ ์žฅ์ ์ด ์žˆ๋‹ค. ์ž๋ฃŒ์˜ ์ž…์ถœ๋ ฅ ๋ถ€

๋ถ„์—์„œ๋Š” K-WEAP ๋ชจํ˜•์€ ๋„คํŠธ์›Œํฌ๋ฅผ ๊ตฌ์ถ•ํ•œ ๊ฐ๊ฐ์˜ ๋…ธ๋“œ

์ •๋ณด์— ๋Œ€ํ•˜์—ฌ ์—‘์…€๋กœ ๊ฐ€์ ธ์˜ค๊ธฐ/๋‚ด๋ณด๋‚ด๊ธฐ ๊ธฐ๋Šฅ์„ ํ†ตํ•ด ์‹œ๊ณ„

์—ด์ž๋ฃŒ์™€ ์ž…๋ ฅํ•˜๋Š” ๋ชจ๋“  ๋งค๊ฐœ๋ณ€์ˆ˜๋ฅผ ์ผ๊ด„์ ์œผ๋กœ ์ž…ยท์ถœ๋ ฅ์ด

๊ฐ€๋Šฅํ•˜๋‹ค. MODSIM์€ Import time series ๊ธฐ๋Šฅ์„ ํ†ตํ•ด ์™ธ๋ถ€

์˜ ์‹œ๊ณ„์—ด ๋ฐ์ดํ„ฐ๋ฅผ ๋ชจํ˜• ๋‚ด๋ถ€์— ์ž…๋ ฅํ•˜๊ณ , ์ˆ˜์ • ์ ์šฉํ•  ์ˆ˜ ์žˆ

์ง€๋งŒ ์‹œ๊ณ„์—ด์„ ์ œ์™ธํ•œ ์ €์ˆ˜์ง€๋…ธ๋“œ์˜ ์‹œ์„ค๋ฌผ ์ œ์›, ์ˆ˜์š”์ฒ˜๋ณ„

์šฐ์„ ์ˆœ์œ„, ํšŒ๊ท€์œจ, ํšŒ๊ท€์ง€์  ๋“ฑ์€ ์ง์ ‘ ์ž…๋ ฅํ•˜๋„๋ก ๊ตฌ์„ฑ๋˜์–ด

์žˆ์–ด ์ƒ๋Œ€์ ์œผ๋กœ GUI ํŽธ์˜์„ฑ์ด ๋‹ค์†Œ ๋‚ฎ๋‹ค.

4.3.2 ๊ตฌ๋™์‹œ๊ฐ„ ๊ฒ€ํ† 

๋ณธ ์—ฐ๊ตฌ์—์„œ ํ™œ์šฉํ•œ ๊ฐ ๋ชจํ˜•์— ๋Œ€ํ•œ ๊ตฌ๋™์‹œ๊ฐ„์„ ๊ฒ€ํ† ํ•œ ๊ฒฐ

๊ณผ ๊ณ„์‚ฐ ํšจ์œจ ์ธก๋ฉด์—์„œ ์†๋„๋Š” MODSIM์ด K-WEAP๋ณด๋‹ค ์šฐ

์ˆ˜ํ•œ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ด๋Š” ์ตœ์ ํ™” ๋ฐฉ๋ฒ•์„ ํ•ด์„ํ•˜๋Š” ๋ฐฉ์‹์—

์„œ Lagrangian relaxation algorithm RELAX-IV๊ฐ€ Simplex

Method๋ณด๋‹ค ์†๋„์ธก๋ฉด์—์„œ ํšจ์œจ์ ์ž„์„ ๋ณด์—ฌ์ฃผ๋Š” ๊ฒฐ๊ณผ๋กœ ํŒ๋‹จ

๋œ๋‹ค. ์•„๋ž˜ Table 6์€ ๋ณธ ์—ฐ๊ตฌ์˜ ๋ชจ์˜ ๊ฒฐ๊ณผ ๋„์ถœ์„ ์œ„ํ•ด ์‹œํ–‰์ฐฉ

์˜ค๋ฅผ ํ†ตํ•ด ๊ตฌ๋™์‹œ๊ฐ„์„ ๊ฒ€ํ† ํ•˜์˜€๋‹ค. 3ํšŒ ํ‰๊ท  K-WEAP์€ 63

๋ถ„, MODSIM์€ 1.57๋ถ„์œผ๋กœ ์•ฝ 61.43๋ถ„์˜ ์ฐจ์ด๊ฐ€ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ,

๋ชจํ˜• ๊ตฌ์ถ•๊ณผ ๊ฒฐ๊ณผ๋ฅผ ํ•ด์„ํ•˜๋Š” ์‹œ๊ฐ„์ด ๋Œ€ํญ ๊ฐ์†Œ๋จ์„ ๋ณด์˜€๋‹ค.

5. ๊ฒฐ ๋ก 

๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๊ณต๊ธ‰ ์šฐ์„ ์ˆœ์œ„์— ๋”ฐ๋ฅธ ๋ฌผ์ˆ˜๊ธ‰ ๋ถ„์„ ๊ฒฐ๊ณผ์˜

๋น„๊ต๋ฅผ ์œ„ํ•ด ๊ตญ๋‚ด ์ˆ˜์ž์›์žฅ๊ธฐ์ข…ํ•ฉ๊ณ„ํš์—์„œ ํ™œ์šฉํ•œ K-WEAP

๋ชจํ˜•๊ณผ MODSIM ๋ชจํ˜•์„ ์ด์šฉํ•˜์—ฌ ๋น„๊ต๋ถ„์„ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ

์˜ ์ฃผ์š” ๊ฒฐ๊ณผ๋ฅผ ์š”์•ฝํ•˜๋ฉด ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค.

1) ๊ธฐ์กด์˜ ์ˆ˜์ž์›์žฅ๊ธฐ์ข…ํ•ฉ๊ณ„ํš์€ ์šฉ๋„๋ณ„ ์ˆ˜์š”์ฒ˜์˜ ๊ณต๊ธ‰ ์šฐ

์„ ์ˆœ์œ„๋ฅผ ๋ชจ๋‘ ๋™์ผํ•˜๊ฒŒ ๊ณต๊ธ‰ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๊ฐ€์ •ํ•˜์˜€์œผ๋ฉฐ

์ตœ์ ํ™”๋ฅผ ์ˆ˜ํ–‰ํ•˜๋Š” ๋ชฉ์ ํ•จ์ˆ˜์˜ ์ฐจ์ด์— ๋”ฐ๋ผ K-WEAP์€

์ตœ๋Œ€์ถฉ์กฑ๋ฅ ์„ ๋งŒ์กฑ์‹œํ‚ค๊ธฐ ์œ„ํ•œ ๋น„์œจ ๋ฐฐ๋ถ„์„ ์ˆ˜ํ–‰ํ•˜๋Š” ๋ฐ˜

๋ฉด MODSIM์€ ๋ฌผ ๊ณต๊ธ‰ ์šฐ์„ ์ˆœ์œ„์˜ ์ ์šฉ์ด ํ•„์ˆ˜์ ์ธ ๊ฒƒ์œผ

๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค.

2) ์ด์— ๋™์ผ ์šฐ์„ ์ˆœ์œ„์™€ ๊ณต๊ธ‰ ์šฐ์„ ์ˆœ์œ„๋ฅผ ์ ์šฉํ•œ ๊ฒฐ๊ณผ, ๋ฌผ

๋ถ€์กฑ๋Ÿ‰์˜ ์ฐจ์ด๋Š” ํ‰๊ท  1,035 ์ฒœm3์ด ๋ฐœ์ƒํ•˜์˜€๊ณ , ์ตœ๋Œ€ ๋ฌผ

๋ถ€์กฑ์˜ ์ฐจ์ด๋Š” 1993๋…„ 2,918.22 ์ฒœm3์˜ ์ฐจ์ด๊ฐ€ ๋ฐœ์ƒํ•˜์˜€

์œผ๋ฉฐ, 49๊ฐœ๋…„์˜ ๋ˆ„์ ์น˜๋กœ ๋ณด๋ฉด ์•ฝ 146,792.97 ์ฒœm3์ด ๋ฐœ์ƒ

ํ•˜์˜€๋‹ค. ๋˜ํ•œ ๋Œ ์ €์ˆ˜๋Ÿ‰์˜ ๊ฒฝํ–ฅ ๋น„๊ต ์‹œ ์ €์ˆ˜๋Ÿ‰์ด ๋” ์ฆ๊ฐ€ํ•˜

๋Š” ๊ฒฝํ–ฅ์„ ๋ณด์˜€๋‹ค. ์ด๋Š” ๊ณต๊ธ‰ ์šฐ์„ ์ˆœ์œ„์— ๋”ฐ๋ผ ์ƒยท๊ณต์šฉ์ˆ˜

์˜ ์ˆ˜์š”๋Ÿ‰์ด ๋” ๋จผ์ € ๋ฐฐ๋ถ„๋˜๊ธฐ ๋•Œ๋ฌธ์ด๋ฉฐ ํšŒ๊ท€๋Ÿ‰์ด ์ƒ๋Œ€์ 

์œผ๋กœ ์ฆ๊ฐ€ํ•˜๋ฉด์„œ ์˜ํ–ฅ์„ ๋ฐ›์„ ์ˆ˜ ์žˆ๋Š” ์œ ์—ญ์—์„œ ์ˆ˜์ž์› ์žฌ

์ด์šฉ์ด ์ƒ๋Œ€์ ์œผ๋กœ ๋งŽ์•„์ง€๊ธฐ ๋•Œ๋ฌธ์ธ ๊ฒƒ์œผ๋กœ ํŒ๋‹จ๋œ๋‹ค.

3) ์šฐ์„ ์ˆœ์œ„๋ฅผ ์ ์šฉํ•œ K-WEAP๊ณผ MODSIM์„ ๋น„๊ตํ•  ๊ฒฝ

์šฐ ์ตœ๋Œ€ ๋ฌผ ๋ถ€์กฑ์ด ๋ฐœ์ƒํ•œ ๋…„๋„๋Š” 2015์œผ๋กœ ๋™์ผํ•œ ๊ฒฐ๊ณผ

๋ฅผ ๋‚˜ํƒ€๋ƒˆ์œผ๋ฉฐ, ์ƒ๋Œ€์˜ค์ฐจ ์ตœ๋Œ€ 5.3%์ด๋‚ด, ๊ฒฐ์ •๊ณ„์ˆ˜(R2)๋Š”

0.9999๋กœ ๋งค์šฐ ์œ ์‚ฌํ•œ ๋ถ€์กฑ๋Ÿ‰๊ณผ ์‹œ์ ์„ ๋‚˜ํƒ€๋ƒˆ๋‹ค. ์ผ๋ถ€ ๋ชจ

ํ˜• ๊ฐ„์˜ ๋ฌผ ๋ถ€์กฑ๋Ÿ‰์˜ ์ฐจ์ด๋Š” ์—ฐ ํ‰๊ท  0.89 ๋ฐฑ๋งŒํ†ค, ์—ฐ๋ณ„๋กœ๋Š”

โ€“0.08โˆผ2.69 ๋ฐฑ๋งŒํ†ค์ด ๋ฐœ์ƒํ•˜์˜€๋Š”๋ฐ, ์ด ๊ฒฐ๊ณผ๋Š” ์ž…๋ ฅ์ž

๋ฃŒ ๊ตฌ์„ฑ์‹œ ์†Œ์ˆซ์  ์ฒ˜๋ฆฌ๊ฒฐ๊ณผ์— ๋”ฐ๋ฅธ ์ฐจ์ด์™€ ์ƒ์ดํ•œ ์ตœ์ ํ™”

์•Œ๊ณ ๋ฆฌ์ฆ˜ ๋ฐ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋ฐ˜๋ณตํšŸ์ˆ˜ ์ฐจ์ด๋กœ ํŒ๋‹จ๋œ๋‹ค.

4) ๋‘ ๋ชจํ˜• ๋ชจ๋‘ ํ•ฉ๋ฆฌ์ ์ธ ๋ฌผ ๋ถ€์กฑ ๋ถ„์„ ๊ฒฐ๊ณผ๋ฅผ ์ œ๊ณตํ•œ๋‹ค๊ณ 

๊ฐ€์ •ํ•  ๊ฒฝ์šฐ, ๋ชจํ˜•์˜ ๊ตฌ์ถ•๊ณผ ๋ฐ์ดํ„ฐ ์ฒ˜๋ฆฌ์— ํ•ด๋‹นํ•˜๋Š” GUI

Table 6. Comparison of performance speed between K-WEAP and

MODSIM

Performance speed K-WEAP MODSIM

1 59 min 1.55 min

2 66 min 1.58 min

3 64 min 1.58 min

Average 63 min 1.57 min

Desktop SpecificationIntel (R) Core (TM) i7-6700 CPU

@3.40 GHz, RAM : 4.00 GB

(a) Soyanggang dam (b) Chungju dam

Fig. 11. Time series results in the Hongcheonriver basin (1014)

Page 11: Comparison and discussion of MODSIM and K-WEAP model

J.-H. Oh et al. / Journal of Korea Water Resources Association 52(7) 463-473 473

ํŽธ์˜์„ฑ์€ K-WEAP์ด ๋” ์šฐ์ˆ˜ํ•œ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋‚˜, ๊ตฌ๋™

์‹œ๊ฐ„์˜ ํšจ์œจ์„ฑ ์„ ๊ณ ๋ คํ•  ๊ฒฝ์šฐ๋Š” MODSIM์ด ๋” ์šฐ์ˆ˜ํ•œ

๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค.

ํ˜„์žฌ๋Š” ์ค‘๊ถŒ์—ญ ๋‹จ์œ„์˜ ํ•˜์ฒœ์ˆ˜, ๋Œ์ˆ˜, ์ง€ํ•˜์ˆ˜๋ฅผ ์—ฐ๊ณ„ํ•˜์—ฌ ๋ชจ

๋“  ์ˆ˜๋Ÿ‰์„ ์ด์šฉํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฐ€์ • ํ•˜์— ์ˆ˜์š”์ฒ˜๋ณ„ ์šฐ์„ ์ˆœ์œ„๋ฅผ

๋™์ผํ•˜๊ฒŒ ์ ์šฉํ•˜์˜€์ง€๋งŒ, ์ง€๊ธˆ๊ณผ ๊ฐ™์€ ์‹œ์Šคํ…œ์—์„œ๋Š” ๊ฐ™์€ ๊ณต

๊ธ‰๋Ÿ‰๊ณผ ์ˆ˜์š”๋Ÿ‰์ž„์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ๊ณต๊ธ‰ ์šฐ์„ ์ˆœ์œ„๋ฅผ ๊ณ ๋ คํ•จ์— ๋”ฐ

๋ผ ๋ฌผ ๋ถ€์กฑ๋Ÿ‰์˜ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ์ด์— ๋”ฐ๋ผ

์šฐ์„ ์ˆœ์œ„๋ฅผ ์ ์šฉํ•œ K-WEAP๊ณผ MODSIM ๋ชจํ˜•์˜ ๊ฒฐ๊ณผ์— ๋Œ€

ํ•œ ๊ฒ€์ฆ์„ ์ˆ˜ํ–‰ํ•˜์˜€์œผ๋ฉฐ ํ–ฅํ›„ ๊ตญ๊ฐ€์ฐจ์›์˜ ๋ฌผ์ˆ˜๊ธ‰ ์ „๋ง์„ ์ˆ˜ํ–‰

ํ•  ๊ฒฝ์šฐ, ์‹ค์ œ ๊ณต๊ธ‰ ์šฐ์„ ์ˆœ์œ„์˜ ๋ฐ˜์˜๊ณผ ๋”๋ถˆ์–ด K-WEAP๋ชจํ˜•

๋ฟ๋งŒ ์•„๋‹ˆ๋ผ MODSIM ๋ชจํ˜•์„ ํ™œ์šฉํ•œ ๋‹ค์–‘ํ•œ ์‹œ๋‚˜๋ฆฌ์˜ค์— ๋”ฐ

๋ฅธ ๋ถ„์„์„ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค.

References

Ahn, S. R., Park, G. A., Shin, Y. H., and Kim, S. J. (2009). โ€œAssessment

of the potential water supply rate of agricultural irrigation

facilities using MODSIM - For Geum River Basin -.โ€ Journal

of Korea Water Resources Association, Vol. 42, No. 10, pp. 825-843.

Cheong, T. S., Kang, S. U., Ko, I. H., and Hwang, M. H. (2007).

โ€œDevelopment and validation of KModSim for the decision

support system in Geum River Basin.โ€ Journal of the Korean

Society of Civil Engineers, Vol. 27, No. 3B, pp. 319-329.

Choi, S. J., Kang, S. K., Lee, D. R., and Kim, J. H. (2018). โ€œA study

on water supply and demand prospects for water resources

planning.โ€ Journal of the Korean Society of Hazard Mitigation,

Vol. 18, No. 7, pp. 589-593.

Choi, S. J., Lee, D. R., Moon, J. W., and Kang, S. K. (2010).

โ€œApplication of K-WEAPโ€, Journal of Korea Water Resources

Association, Vol. 43, No. 7, pp. 625-633.

K-Water (2008). A study on the basic plan for water management.

11-B500001-000091-01, p. 246.

Labadie, J. W., and Larson, R. (2007). MODSIM 8.1:River Basin

Management Decision Support System User Manual and

Documentation. p. 4-24.

Lee, D. R., and Choi, S. J. (2011). โ€œintroduction of integrated water

resources assessment planning Model-K-WEAP (Korea-water

evaluation and planning system).โ€ Water for future, Vol. 44,

No. 9, pp. 117-123.

Lim, J. S., Kang, S. U., Kim, H. N., and Lee, E. L. (2017). โ€œEvaluation

of potential securing instream flow according to estimating

operation rule in naeseongcheon watershed.โ€ Journal of the

Korean Society of Hazard Mitigation, Vol. 17, No. 1, pp. 265-277.

Ministry of Land, Transport and Maritime Affairs (MLTM) (2011).

Research report for National water resources plan (2011~2020).

Ministry of Land, Infrastructure and Transport (MOLIT) (2016).

National water resources plan (2011~2020)(3rd rev.)

Park, H. A., Lee, D. R., Moon, J. W., and Kang, S. U. (2003).

โ€œEvaluation of applicability of K-WEAP in the Gum-River Basin.โ€

Proceedings of Korean Society of Civil Engineers, pp. 1966-1971.

Park, J. E., Kim, Y. S., Kim, J. K., and Koh, D. K. (2013). โ€œEvaluation

of spatio-temporal water shortage in sapgyo catchment employing

total water right survey and water balance analysis.โ€ Journal of

Korea Water Resources Association, Vol. 46, No. 10, pp. 1005-1016.

Yoo, J. H. (2005). โ€œSuggestion of the water budget analysis method

by MODSIM for the assessment of the water supply reliability.โ€

Journal of the Korean Society of Civil Engineers, Vol. 25,

No. 1B, pp. 9-17.

Yoo, J. H., Lee, Yoon, S. Y., and Kim, S. (2000). โ€œWater budget

analysis in consideration of supply priorities.โ€ Proceedings of

Korean Society of Civil Engineers, pp. 449-452.