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Econ. Environ. Geol. 2021; 54(2): 161-176

Published online April 30, 2021

https://doi.org/10.9719/EEG.2021.54.2.161

© THE KOREAN SOCIETY OF ECONOMIC AND ENVIRONMENTAL GEOLOGY

Groundwater Recharge Evaluation on Yangok-ri Area of Hongseong Using a Distributed Hydrologic Model (VELAS)

Kyoochul Ha1,2, Changhui Park3,*, Sunghyun Kim3, Esther Shin3, Eunhee Lee1

Author Info. +

1Geologic Environment Division, Korea institute of Geoscience and Mineral Resources (KIGAM), Daejeon 34132, Korea
2Department of Mineral & Groundwater Resources, University of Science and Technology (UST)
3GeoGreen21 Co., Ltd., Seoul 08376, Korea

Correspondence to : changhui.park@geogreen21.com

Received: February 3, 2021; Revised: February 19, 2021; Accepted: February 21, 2021

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided original work is properly cited.

Abstract

In this study, one of the distributed hydrologic models, VELAS, was used to analyze the variation of hydrologic elements based on water balance analysis to evaluate the groundwater recharge in more detail than the annual time scale for the past and future. The study area is located in Yanggok-ri, Seobu-myeon, Hongseong-gun, Chungnam-do, which is very vulnerable to drought. To implement the VELAS model, spatial characteristic data such as digital elevation model (DEM), vegetation, and slope were established, and GIS data were constructed through spatial interpolation on the daily air temperature, precipitation, average wind speed, and relative humidity of the Korea Meteorological Stations. The results of the analysis showed that annual precipitation was 799.1-1750.8 mm, average 1210.7 mm, groundwater recharge of 28.8-492.9 mm, and average 196.9 mm over the past 18 years from 2001 to 2018 in the study area. Annual groundwater recharge rate compared to annual precipitation was from 3.6 to 28.2% with a very large variation and average 14.9%. By the climate change RCP 8.5 scenario, the annual precipitation from 2019 to 2100 was 572.8-1996.5 mm (average 1078.4 mm) and groundwater recharge of 26.7–432.5 mm (average precipitation 16.2%). The annual groundwater recharge rates in the future were projected from 2.8% to 45.1%, 18.2% on average. The components that make up the water balance were well correlated with precipitation, especially in the annual data rather than the daily data. However, the amount of evapotranspiration seems to be more affected by other climatic factors such as temperature. Groundwater recharge in more detailed time scale rather than annual scale is expected to provide basic data that can be used for groundwater development and management if precipitation are severely varied by time, such as droughts or floods.

Keywords groundwater, recharge, VELAS, climate change scenario, water budget analysis

분포형 수문모형(VELAS)을 이용한 홍성 양곡리 일대 지하수 함양량 평가

하규철1,2 · 박창희3,* · 김성현3 · 신에스더3 · 이은희1

1한국지질자원연구원 지질환경연구본부 2과학기술연합대학원대학교 광물·지하수자원학과 3㈜지오그린21

요 약

본 연구는 과거와 미래의 연 단위보다 상세한 일단위 지하수 함양량을 평가하기 위해, 분포형 수문모형중의 하나인 VELAS를 이용하여 물수지에 근거한 수문요소별 변동을 분석하고자 하였다. 가뭄에 매우 취약한 충남 홍성군 서부면 양곡리 일대 소유역을 대상으로, VELAS의 입력자료인 수치표고모델, 식생도, 경사도 등의 공간특성자료를 구축하였고, 기후자료는 기상청의 일별 대기온도, 강수, 평균풍속, 상대습도 등의 자료를 공간적으로 보간하였다. 연구지역의 과거 2001년부터 2018년까지 18년 동안 일단위 물수지 분석결과, 연간 강수량은 799.1~1750.8 mm로 평균 1210.7 mm이고, 지하수 함양량은 28.8~492.9 mm로 평균 196.9 mm로 분석되었다. 연 강수량 대비 지하수 함양률은 최소 3.6%에서 최대 28.2%로 변동폭이 매우 크고, 평균 함양률은 14.9%였다. 미래 기후변화 RCP 8.5시나리오에 의한 2019년부터 2100년까지의 일단위 물수지 분석결과, 연간 강수량은 572.8~1996.5 mm(평균 1078.4 mm)이고, 지하수함양량은 26.7~432.5 mm, 평균 174.6 mm(평균 강수량의 16.2%)로서 과거보다 다소 증가하였다. 미래 연간 지하수 함양률은 최소 2.8%, 최대 45.1%, 평균 18.2%로 분석되었다. 물수지를 구성하는 요소들은 강수량과의 상관성이 잘 나타나며, 일단위보다는 연단위로 갈수록 그러한 상관성이 뚜렷했다. 다만, 증발산량은 강수량보다는 기온 등 다른 기후요소에 더 영향을 받는 것으로 보인다. 본 연구를 통해 산정된 연단위 보다 상세 시간 단위에서의 지하수함양량은 가뭄 또는 홍수 등 시기별로 강수량 변동이 심한 경우 지하수개발과 관리에 활용될 수 있는 기초자료를 제공할 수 있을 것으로 기대된다.

주요어 지하수, 함양량, VELAS, 기후변화 시나리오, 물수지 분석

Article

Research Paper

Econ. Environ. Geol. 2021; 54(2): 161-176

Published online April 30, 2021 https://doi.org/10.9719/EEG.2021.54.2.161

Copyright © THE KOREAN SOCIETY OF ECONOMIC AND ENVIRONMENTAL GEOLOGY.

Groundwater Recharge Evaluation on Yangok-ri Area of Hongseong Using a Distributed Hydrologic Model (VELAS)

Kyoochul Ha1,2, Changhui Park3,*, Sunghyun Kim3, Esther Shin3, Eunhee Lee1

1Geologic Environment Division, Korea institute of Geoscience and Mineral Resources (KIGAM), Daejeon 34132, Korea
2Department of Mineral & Groundwater Resources, University of Science and Technology (UST)
3GeoGreen21 Co., Ltd., Seoul 08376, Korea

Correspondence to:changhui.park@geogreen21.com

Received: February 3, 2021; Revised: February 19, 2021; Accepted: February 21, 2021

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided original work is properly cited.

Abstract

In this study, one of the distributed hydrologic models, VELAS, was used to analyze the variation of hydrologic elements based on water balance analysis to evaluate the groundwater recharge in more detail than the annual time scale for the past and future. The study area is located in Yanggok-ri, Seobu-myeon, Hongseong-gun, Chungnam-do, which is very vulnerable to drought. To implement the VELAS model, spatial characteristic data such as digital elevation model (DEM), vegetation, and slope were established, and GIS data were constructed through spatial interpolation on the daily air temperature, precipitation, average wind speed, and relative humidity of the Korea Meteorological Stations. The results of the analysis showed that annual precipitation was 799.1-1750.8 mm, average 1210.7 mm, groundwater recharge of 28.8-492.9 mm, and average 196.9 mm over the past 18 years from 2001 to 2018 in the study area. Annual groundwater recharge rate compared to annual precipitation was from 3.6 to 28.2% with a very large variation and average 14.9%. By the climate change RCP 8.5 scenario, the annual precipitation from 2019 to 2100 was 572.8-1996.5 mm (average 1078.4 mm) and groundwater recharge of 26.7–432.5 mm (average precipitation 16.2%). The annual groundwater recharge rates in the future were projected from 2.8% to 45.1%, 18.2% on average. The components that make up the water balance were well correlated with precipitation, especially in the annual data rather than the daily data. However, the amount of evapotranspiration seems to be more affected by other climatic factors such as temperature. Groundwater recharge in more detailed time scale rather than annual scale is expected to provide basic data that can be used for groundwater development and management if precipitation are severely varied by time, such as droughts or floods.

Keywords groundwater, recharge, VELAS, climate change scenario, water budget analysis

분포형 수문모형(VELAS)을 이용한 홍성 양곡리 일대 지하수 함양량 평가

하규철1,2 · 박창희3,* · 김성현3 · 신에스더3 · 이은희1

1한국지질자원연구원 지질환경연구본부 2과학기술연합대학원대학교 광물·지하수자원학과 3㈜지오그린21

Received: February 3, 2021; Revised: February 19, 2021; Accepted: February 21, 2021

요 약

본 연구는 과거와 미래의 연 단위보다 상세한 일단위 지하수 함양량을 평가하기 위해, 분포형 수문모형중의 하나인 VELAS를 이용하여 물수지에 근거한 수문요소별 변동을 분석하고자 하였다. 가뭄에 매우 취약한 충남 홍성군 서부면 양곡리 일대 소유역을 대상으로, VELAS의 입력자료인 수치표고모델, 식생도, 경사도 등의 공간특성자료를 구축하였고, 기후자료는 기상청의 일별 대기온도, 강수, 평균풍속, 상대습도 등의 자료를 공간적으로 보간하였다. 연구지역의 과거 2001년부터 2018년까지 18년 동안 일단위 물수지 분석결과, 연간 강수량은 799.1~1750.8 mm로 평균 1210.7 mm이고, 지하수 함양량은 28.8~492.9 mm로 평균 196.9 mm로 분석되었다. 연 강수량 대비 지하수 함양률은 최소 3.6%에서 최대 28.2%로 변동폭이 매우 크고, 평균 함양률은 14.9%였다. 미래 기후변화 RCP 8.5시나리오에 의한 2019년부터 2100년까지의 일단위 물수지 분석결과, 연간 강수량은 572.8~1996.5 mm(평균 1078.4 mm)이고, 지하수함양량은 26.7~432.5 mm, 평균 174.6 mm(평균 강수량의 16.2%)로서 과거보다 다소 증가하였다. 미래 연간 지하수 함양률은 최소 2.8%, 최대 45.1%, 평균 18.2%로 분석되었다. 물수지를 구성하는 요소들은 강수량과의 상관성이 잘 나타나며, 일단위보다는 연단위로 갈수록 그러한 상관성이 뚜렷했다. 다만, 증발산량은 강수량보다는 기온 등 다른 기후요소에 더 영향을 받는 것으로 보인다. 본 연구를 통해 산정된 연단위 보다 상세 시간 단위에서의 지하수함양량은 가뭄 또는 홍수 등 시기별로 강수량 변동이 심한 경우 지하수개발과 관리에 활용될 수 있는 기초자료를 제공할 수 있을 것으로 기대된다.

주요어 지하수, 함양량, VELAS, 기후변화 시나리오, 물수지 분석

    Fig 1.

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    Figure 1.Modeling concept and work flow of VELAS model, which are modified from Park et al.(2013).
    Economic and Environmental Geology 2021; 54: 161-176https://doi.org/10.9719/EEG.2021.54.2.161

    Fig 2.

    Download
    Figure 2.Land use (a) and geology (b) with the existing wells of the study area.
    Economic and Environmental Geology 2021; 54: 161-176https://doi.org/10.9719/EEG.2021.54.2.161

    Fig 3.

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    Figure 3.Spatial input data preparation for the VELAS model in the study area, (a) DEM, (b) slope, (c) soil, and (d) vegetation.
    Economic and Environmental Geology 2021; 54: 161-176https://doi.org/10.9719/EEG.2021.54.2.161

    Fig 4.

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    Figure 4.Annual variation of each water budget element in the past (2001~2018).
    Economic and Environmental Geology 2021; 54: 161-176https://doi.org/10.9719/EEG.2021.54.2.161

    Fig 5.

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    Figure 5.Relationships between annual precipitation and recharge, recharge rate in the past (2001~2018).
    Economic and Environmental Geology 2021; 54: 161-176https://doi.org/10.9719/EEG.2021.54.2.161

    Fig 6.

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    Figure 6.Monthly variation for each water budget element in the past (2001~2018).
    Economic and Environmental Geology 2021; 54: 161-176https://doi.org/10.9719/EEG.2021.54.2.161

    Fig 7.

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    Figure 7.Annual variation for each water budget element for the future (2019~2100).
    Economic and Environmental Geology 2021; 54: 161-176https://doi.org/10.9719/EEG.2021.54.2.161

    Fig 8.

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    Figure 8.Monthly variation for each water budget element for the future (2019~2100).
    Economic and Environmental Geology 2021; 54: 161-176https://doi.org/10.9719/EEG.2021.54.2.161

    Fig 9.

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    Figure 9.Monthly variation for each water budget element in the past (2019~2100).
    Economic and Environmental Geology 2021; 54: 161-176https://doi.org/10.9719/EEG.2021.54.2.161

    Table 1 . Comparisons of the distributed hydrological models.

    ModelFeaturesDeveloperReferences
    SWAT (Soil and Water Assessment Tool)Calculation based on each HRU(Hydrological Response Unit) of land use and soil and topographyAgricultural Research Service, US Department of Agriculture (USDA ARS)Neitsch et al.(2002), Arnold et al.(1999)
    SWAT-KImprovement of SWAT model for Korean characteristicsKorea Institute of Construction and Transportation (KICT)KICT(2007), Kim et al.(2008), Kim et al.(2009)
    MIKE-SHE(System Hydrologique European)A physically-based distributed tracking model that simulates all hydrological components of water cycleAbbott et al.(1986), DHI(1999)Abbott et al.(1986), Kim et al.(2007), Kim et al.(2020)
    VfloTMPhysically-based distributed model used mainly for flood estimationOklahoma UniversityVieux(2004), Park and Kang(2006)
    VELAS(Vegetation, land cover, and soil water dynamics)A simple hydrologic feedback model to simulate daily responses of hydrologic processes under various conditions of vegetation, land cover, and soil in a fully-distributed mannerUniversity of Missouri-Kansas City, Kongju National University, Korea Institute of Geoscience and Mineral Resources (KIGAM)Park et al.(2013)

    Table 2 . Annual water budget analysis results in the past (2001~2018).

    YearPrecipitation (mm/yr)Interception (mm/yr)Runoff (mm/yr)Evapotranspiration (mm/yr)Groundwater recharge (mm/yr)Recharge rate (%)
    20011037.6118.6234.7584.0103.710.0
    20021071.5130.9217.8616.378.07.3
    20031459.8173.0364.6644.5281.019.3
    20041213.2153.4242.3631.5181.014.9
    20051307.2131.7356.6598.9226.017.3
    2006890.7113.1197.9574.2103.711.6
    20071405.3173.8317.4566.8266.519.0
    20081069.0172.4167.1590.9155.914.6
    20091262.1174.3270.7622.3169.913.5
    20101654.6196.2459.2604.2431.326.1
    20111750.8186.1501.9569.8492.928.2
    20121496.4156.9414.0543.1347.423.2
    20131111.3144.1230.0616.7133.812.0
    20141054.2157.1177.9583.6133.012.6
    2015799.1130.783.9577.328.83.6
    2016869.8109.1147.9591.133.43.8
    20171014.4150.6180.1537.7151.715.0
    20181325.9139.3348.3594.8225.317.0
    Minimum799.1109.183.9537.728.83.6
    Maximum1750.8196.2501.9644.5492.928.2
    Average1210.7150.6272.9591.6196.914.9
    Median1162.2152.0238.5591.0162.914.8

    Table 3 . Basic statistics of the annual water budget analysis results during each period of the future (2019-2100).

    Hydrologic elememtPeriod
    Total
    (2019-2100)    		1st
    (2019-2040)    		2nd
    (2041-2060)    		3rd
    (2061-2080)    		4th
    (2081-2100)
    Precipitation(mm/yr)Minimum572.8630.1722.3773.1572.8
    Maximum1996.51544.11577.21996.51646.5
    Average1078.41048.21024.11159.21085.1
    Median1022.01001.2972.21108.11085.1
    Interception
    (mm/yr)    		Minimum81.585.791.3101.781.5
    Maximum168.4166.3162.1168.4158.4
    Average123.7125.1117.7127.2124.7
    Median121.0125.1118.3128.1123.0
    Runoff
    (mm/yr)    		Minimum78.6110.278.6137.888.0
    Maximum877.4490.1500.6877.4577.9
    Average264.4251.5237.8295.8261.7
    Median226.8209.7204.9256.0253.3
    Evapotranspiration
    (mm/yr)    		Minimum387.0387.0459.5432.0418.6
    Maximum632.6564.5568.9605.7632.6
    Average521.6493.7516.5539.1540.0
    Median524.6503.4510.4544.9545.3
    Recharge
    (mm/yr)    		Minimum26.747.426.745.128.6
    Maximum432.5410.8432.5384.5354.3
    Average174.6180.4157.0194.5166.0
    Median167.1153.0135.2182.2177.2
    Recharge rate
    (%)    		Minimum2.84.94.94.73.0
    Maximum45.142.842.840.137.0
    Average18.218.818.820.317.3
    Median17.416.014.119.018.5

    KSEEG
    Oct 29, 2024 Vol.57 No.5, pp. 473~664
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