# Characterizing the Impact of River Barrage Construction on Stream-Aquifer Interactions, Korea

^{1}

^{2}

_{2}Storage Environmental Management (K-COSEM) Research Center, Department of Earth and Environmental Sciences, Korea University, Seoul 136-701, Korea

^{3}

^{4}

^{*}

## Abstract

**:**

_{d}) and flood amplitudes were reduced to 78% and 59%, respectively. Moreover, the ratio of flood peak time to t

_{d}demonstrated a decreasing tendency after the construction of the CHRB. Hence, it is concluded that the dredging and increase of river-water storage due to CHRB construction enhanced stream–aquifer interactions during the period shortly after the construction of the CHRB.

## 1. Introduction

## 2. Materials and Methods

#### 2.1. Study Area

^{2}), which was located upstream of the CHRB, includes alluvium regions of the Namgang River, Gwangryeo Stream, and Yeongsan Stream within the Nakdong River basin (Figure 1). The Namgang River area (NG_R) is comprised of the downstream portion of the Namgang River (length of ~186.3 km) that flows from south to northeast, and the Gwangryeo Stream area (GR_S) is comprised of the Gwangryeo Stream (length of ~7.5 km), which flows from south to north, and the Iryeong Stream (length of 3 km). The Yeongsan Stream area (YS_S) is comprised of the Yeongsan Stream (length of ~9.8 km), which flows from north to south, the Deokgok Stream (length of 7.3 km), as well as agricultural areas (Figure 1). Sixteen river barrages were constructed on the four major rivers (the Han, Nakdong, Geum, and Yeongsan) in South Korea as a result of the Four Major Rivers Restoration Project (4MRRP) from 2008 until 2012 (Figure 1 and Table 1). The 4MRRP increased the width of the Nakdong River from 330 to 520 m and decreased the elevation of the river bottom from −2.0 to −5.70 m (above mean sea level, AMSL) at the CHRB site [34]. The mean discharge of the river in the dry season (November to February) at the Jindong (JD) gauge station increased from 104.7 m

^{3}/s in 2009–2011 to 178.6 m

^{3}/s in 2012–2013 as a result of the river barrage construction [35].

^{2}) of any river in South Korea. The mean discharge of the river from 2009 to 2013 was 360 m

^{3}/s, and the seasonal variability of the discharge ranged from less than 50 m

^{3}/s in the dry season (December to January) to more than 12,000 m

^{3}/s in the rainy season (June to September) [35]. The study area is composed mostly of agricultural fields with low elevations of 6–10 m AMSL, and these fields are mainly rice fields (>84%). In the study area, groundwater is commonly used for irrigation, and it is influenced by the agricultural cycle of rice cultivation from May to August as well as the cycle of greenhouse agriculture from December to April. The amount of average annual precipitation in Korea is 1357 mm (1981–2010) [36], and the amount of average annual rainfall (2010–2014) in the study area is 1249 mm; in this region, the highest monthly rainfall occurs in August (295 mm) and the lowest monthly rainfall occurs in January (8 mm), based on data from the Georyonggang, Yeongsan, and Jindong rainfall gauging stations. The rainy season (June to September) provides >64% (807 mm) of the annual rainfall, and the rest of the year provides the remaining ~36%.

#### 2.2. Data Collection and Monitoring of Water Levels and Electrical Conductivity

#### 2.3. Governing Equation for Stream-Aquifer Interactions

_{s}(t) is the river stage (L) and$\text{}\alpha $ is the aquifer diffusivity (L

^{2}·T

^{−1}), which is the ratio of transmissivity T (L

^{2}·T

^{−1}) to storativity S(-). The main assumptions of the 1-D analytical equation are that the aquifer parameters such as T and S are constant and that floodwaves through the aquifer are 1-D and perpendicular to flow direction [6,7,10]. The solution of Equation (2) satisfying (2a) and (2b) by the FT method is presented as shown below [23,24]:

^{−1}). Assuming that both river and aquifer are in equilibrium prior to the river stage variation, Equation (4) is solved by a solution analogous to that of heat conduction [21,23]:

#### 2.4. Removal of Noise from Groundwater Level Data with LPF

## 3. Results and Discussion

#### 3.1. Changes in Water Levels and Electrical Conductivity

#### 3.2. Evaluation of Stream–Aquifer Interactions by the Analytical Solution

#### 3.2.1. Theoretical Curves Derived from the Analytical Solution

_{d}= 60, 70, 80, 90, and 100 h), and for a constant R = 1000 m, the h/A values increased with increased flood duration times (t

_{d}) at a fixed $\omega t$ (Figure 4b). This indicates that longer t

_{d}and larger R values induced lower hydraulic gradient change at a certain distance from the stream–aquifer interface, thus causing a longer lag time for the river-water inflow into the aquifer when the floodwave passed through. On the other hand, the sinusoidal stream variations of the study area were applied with less than one half of the wavelength because of the attenuation effect of floodwave propagation as well as the floodwave impact passing through the channel. Therefore, the actual stream stage did not reach to below that of the initial stage (Figure 4). In this study, the flood duration time (t

_{d}) was limited within a ωt of 6.28 and the various time scales were all less than $\pi /\omega $ for each of the flood events.

#### 3.2.2. Selection of Flood Events and Changes in Their Characteristics

_{d}) and induced flood duration time (t

_{g}) with amplitude (A) of floodwaves and groundwater fluctuations. The t

_{d}is the period ranging from the time of the initial river stage to the time that the stage returned to the initial river stage; and the t

_{g}corresponds to WL_G. The average of the t

_{d}and A values from 2011 to 2012 diminished from 181 to 130 h and from 2.05 to 1.01 m, respectively, as a result of the control exerted by the CHRB (Table 3). The highest groundwater fluctuations appeared at the well HAM-056; these values were 2.58 m relative to A = 4.29 m and t

_{d}= 150 h in 2011, and 1.95 m relative to A = 2.17 m and t

_{d}= 144 h in 2012. The average of the median t

_{d}and A values from 2011 to 2012 diminished from 156 to 122 h and from 1.43 to 0.85 m, respectively, which correspond to decreases of 78% and 59%, respectively, compared to the 2011 data. The average of the median t

_{g}and A values from 2011 to 2012 also diminished from 160 to 127 h and from 0.68 to 0.44 m, respectively, which correspond to decreases of 79% and 65%, respectively, compared to the 2011 data (Figure 6).

_{d}and t

_{g}as well as A values, the wells far from the CHRB like HAM-056 displayed a stronger response to the Namgang River (a tributary of the Nakdong River) than the wells near the CHRB like HAM-004 (Table 3 and Figure 6). In contrast, in the rainy season of 2012 (after the construction of the CHRB), the majority of the wells in the study area showed a strong response to the Nakdong River (Table 3 and Figure 6). This change indicates that increased river-water storage due to the construction of the CHRB caused the groundwater level to rise around the river, which then reduced the damping effect on floodwaves passing through the aquifer [15,26,27,30,31].

_{p}) and induced flood peak time (t

_{ip}). The t

_{p}is the time from the initial river stage to the time that the stage reached its peak level, and t

_{ip}corresponds to WL_G. The ratio of t

_{p}to t

_{d}(or t

_{p}/t

_{d}) represents a key feature of the flood hydrograph [10,22]. Specifically, t

_{p}/t

_{d}and t

_{ip}/t

_{g}values smaller than 0.5 indicate steep hydrographs. The t

_{p}values of the floodwave were on average 83 h in 2011 and 57 h in 2012, while t

_{ip}ranged from an average of 91 h (at HAM-056) to 106 h (at HAM-004) in 2011 and ranged from 62 h (at HAM-004) to 72 h (at HAM-041) in 2012 (Table 3). The average time lag between the groundwater response and the flood peak (t

_{lag}) ranged from 8 h (HAM-056) to 23 h (HAM-004) in 2011 and ranged from 5 h (HAM-004) to 13 h (HAM-041) in 2012 (Table 3). The average t

_{ip}/t

_{g}values showed a decreasing tendency with distance from the river in 2011 (Figure 7a,c), but these values showed an increasing trend in 2012 (Figure 7b,c). This change in tendency may reflect the reduction of river flood amplitude caused by the controlled WL_R at the CHRB. In addition, the fluctuations of the WL_Gs and the WL_Rs with the t

_{lag}decreased in 2012 (Table 3), which can be explained by enhanced stream–aquifer interactions at the time of flood events F-1 (in 2011) and F-9 (in 2012) (Figure 8a,b).

#### 3.2.3. Removal of Noise Effects in Groundwater Level Data

^{−6}Hz in the range of 1.55 × 10

^{−8}and 2.78 × 10

^{−8}Hz with reference to the flood duration time (t

_{d}). The LPF method effectively corrected irregular changes in groundwater levels, which included effects of barrage operation and agricultural pumping as well as infiltration of rainfall, as shown in the LPF WL_G data at HAM-004 in Figure 9. In this figure, the observed WL_G was well corrected by the LPF as evidenced by the elimination of the effect of the groundwater level decline that occurred on 7 August 2011, due to river-water discharge at the barrage before the beginning of rainfall as well as by the elimination of the effect of rainfall at the flood peak time of 11 August 2011 (Figure 9a). The agricultural pumping effect in early June 2012 and the effect of rainfall at the flood peak time on 10 July 2012, were also removed (Figure 9b).

#### 3.2.4. Application of the Analytical Solution for Evaluating Stream–Aquifer Interactions

^{−2}m

^{2}/h (HAM-056) to 4.67 × 10

^{−1}m

^{2}/h (HAM-041), and the K values ranged from 8.58 × 10

^{−8}m/s (HAM-004) to 5.13 × 10

^{−6}m/s (HAM-041). The hydraulic diffusivity (α) and river resistance (R) were estimated by curve matching to the theoretical curve as shown in Figure 10.

^{2}/h (HAM-040, F-4) to 85,000 m

^{2}/h (HAM-056, F-2) in 2011 and 1640 m

^{2}/h (HAM-040, F-10) to 210,000 m

^{2}/h (HAM-056, F-9) in 2012 (Figure 11). The estimated R values ranged from 110 m (HAM-004, F-1) to 1940 m (HAM-040, F-5) in 2011 and 50 m (HAM-056, F-10) to 400 m (HAM-056, F-11) in 2012 (Figure 11). The 1-D analytical solution was compared with the method of Ferris [44], which solves the sinusoidal water level variation with a simple harmonic motion but can only consider hydraulic conductivity (K) without R [48,49]. The average values of α calculated by the method of Ferris [44] were similar to those obtained by the 1-D analytical solution with consideration of river resistance (Table 3), i.e., the values calculated by the former method were 88.0% in 2011 and 85.2% in 2012 of the values calculated by the latter method.

## 4. Conclusions

_{d}) and the amplitude (A) from 2011 to 2012 diminished from 156 to 122 h and from 1.43 to 0.85 m, respectively. In the same manner, the average values of the median of the induced groundwater fluctuation (t

_{g}) and A from 2011 to 2012 also diminished from 160 to 127 h and from 0.68 to 0.44 m, respectively. The average values of the ratio of the peak time over the duration time (t

_{ip}/t

_{g}) showed an increasing tendency relative to the distance from the river in 2011, but a decreasing tendency was detected in 2012.

^{2}/h and 1250–210,000 m

^{2}/h in the rainy seasons of 2011 and 2012, respectively; overall, there was an increasing trend. Conversely, the river resistance (R) values displayed ranges of 110–1940 m and 50–400 m in 2011 and 2012, respectively; thus, there was a decreasing trend. The results for the R values indicate that stream–aquifer interactions were enhanced by dredging, water storage increases in the CHRB, and increases in the groundwater level adjacent to the river as a result of the effect of the CHRB construction. These findings also indicate that R values can function as useful indicators for estimating hydrogeological environment change as well as changes in stream–aquifer interactions adjacent to rivers influenced by river barrage construction.

## Acknowledgments

## Author Contributions

## Conflicts of Interest

## References

- Illangasekare, T.; Morel-Seytoux, H.J. Stream-aquifer influence coefficients as tools for simulation and management. Water Resour. Res.
**1982**, 18, 168–176. [Google Scholar] [CrossRef] - Sophocleous, M.; Koussis, A.; Martin, J.L.; Perkins, S.P. Evaluation of simplified stream-aquifer depletion models for water rights administration. Groundwater
**1995**, 33, 579–588. [Google Scholar] [CrossRef] - Ray, C.; Soong, T.W.; Lian, Y.Q.; Roadcap, G.S. Effect of flood-induced chemical load on filtrate quality at bank filtration sites. J. Hydrol.
**2002**, 266, 235–258. [Google Scholar] [CrossRef] - Chen, X.; Chen, X. Stream water infiltration, bank storage, and storage zone changes due to stream-stage fluctuations. J. Hydrol.
**2003**, 280, 246–264. [Google Scholar] [CrossRef] - McCallum, J.L.; Cook, P.G.; Brunner, P.; Berhane, D. Solute dynamics during bank storage flows and implications for chemical base flow separation. Water Resour. Res.
**2010**, 46. [Google Scholar] [CrossRef] - Pinder, G.F.; Bredehoeft, J.D.; Cooper, H.H. Determination of aquifer diffusivity from aquifer response to fluctuations in river stage. Water Resour. Res.
**1969**, 5, 850–855. [Google Scholar] [CrossRef] - Reynolds, R.J. Diffusivity of glacial-outwash aquifer by the floodwave-response technique. Groundwater
**1987**, 25, 290–299. [Google Scholar] [CrossRef] - Barlow, P.M.; DeSimone, L.A.; Moench, A.F. Aquifer response to stream-stage and recharge variations. II. Convolution method and applications. J. Hydrol.
**2000**, 230, 211–229. [Google Scholar] [CrossRef] - Jha, M.K.; Jayalekshmi, K.; Machiwal, D.; Kamii, Y.; Chikamori, K. Determination of hydraulic parameters of an unconfined alluvial aquifer by the floodwave-response technique. Hydrogeol. J.
**2004**, 12, 628–642. [Google Scholar] [CrossRef] - Ha, K.; Koh, D.C.; Yum, B.W.; Lee, K.K. Estimation of layered aquifer diffusivity and river resistance using flood wave response model. J. Hydrol.
**2007**, 337, 284–293. [Google Scholar] [CrossRef] - Jung, M.; Burt, T.P.; Bates, P.D. Toward a conceptual model of floodplain water table response. Water Resour. Res.
**2004**, 40. [Google Scholar] [CrossRef] [Green Version] - Hantush, M.M. Modeling stream–aquifer interactions with linear response functions. J. Hydrol.
**2005**, 311, 59–79. [Google Scholar] [CrossRef] - Welch, C.; Harrington, G.A.; Leblanc, M.; Batlle-Aguilar, J.; Cook, P.G. Relative rates of solute and pressure propagation into heterogeneous alluvial aquifers following river flow events. J. Hydrol.
**2014**, 511, 891–903. [Google Scholar] [CrossRef] - Welch, C.; Cook, P.G.; Harrington, G.A.; Robinson, N.I. Propagation of solutes and pressure into aquifers following river stage rise. Water Resour. Res.
**2013**, 49, 5246–5259. [Google Scholar] [CrossRef] - Lewandowski, J.; Lischeid, G.; Nützmann, G. Drivers of water level fluctuations and hydrological exchange between groundwater and surface water at the lowland River Spree (Germany): Field study and statistical analyses. Hydrol. Process.
**2009**, 23, 2117–2128. [Google Scholar] [CrossRef] - Burt, T.P.; Bates, P.D.; Stewart, M.D.; Claxton, A.J.; Anderson, M.G.; Price, D.A. Water table fluctuations within the floodplain of the River Severn, England. J. Hydrol.
**2002**, 262, 1–20. [Google Scholar] [CrossRef] - Gillham, R.W. The capillary fringe and its effect on water-table response. J. Hydrol.
**1984**, 67, 307–324. [Google Scholar] [CrossRef] - Kondolf, G.M. Hungry water: effects of dams and gravel mining on river channels. Environ. Manag.
**1997**, 21, 533–551. [Google Scholar] [CrossRef] - Sawyer, A.H.; Cardenas, M.B.; Bomar, A.; Mackey, M. Impact of dam operations on hyporheic exchange in the riparian zone of a regulated river. Hydrol. Process.
**2009**, 23, 2129–2137. [Google Scholar] [CrossRef] - Francis, B.A.; Francis, L.K.; Cardenas, M.B. Water table dynamics and groundwater–surface water interaction during filling and draining of a large fluvial island due to dam-induced river stage fluctuations. Water Resour. Res.
**2010**, 46. [Google Scholar] [CrossRef] - Singh, S.K. Aquifer response to sinusoidal or arbitrary stage of semipervious stream. J. Hydraul. Eng.
**2004**, 130, 1108–1118. [Google Scholar] [CrossRef] - Hall, F.R.; Moench, A.F. Application of the convolution equation to stream-aquifer relationships. Water Resour. Res.
**1972**, 8, 487–493. [Google Scholar] [CrossRef] - Carslaw, H.S.; Jaeger, J.C. Conduction of Heat in Solids, 2nd ed.; Clarendon Press: Oxford, UK, 1959; pp. 50–127. [Google Scholar]
- Bruggeman, G.A. One-dimensional groundwater flow: Orientation table BI. Dev. Water Sci.
**1999**, 46, 77–78. [Google Scholar] - Dong, L.; Cheng, D.; Liu, J.; Zhang, P.; Ding, W. Analytical analysis of groundwater responses to estuarine and oceanic water stage variations using superposition principle. J. Hydraul. Eng.
**2016**, 21, 04015046. [Google Scholar] [CrossRef] - Cloutier, C.A.; Buffin-Bélanger, T.; Larocque, M. Controls of groundwater floodwave propagation in a gravelly floodplain. J. Hydrol.
**2014**, 511, 423–431. [Google Scholar] [CrossRef] - García-Gil, A.; Vázquez-Suñé, E.; Sánchez-Navarro, J.Á.; Lázaro, J.M.; Alcaraz, M. The propagation of complex flood-induced head wavefronts through a heterogeneous alluvial aquifer and its applicability in groundwater flood risk management. J. Hydrol.
**2015**, 527, 402–419. [Google Scholar] [CrossRef] - Zlotnik, V.A.; Huang, H. Effect of shallow penetration and streambed sediments on aquifer response to stream stage fluctuations (analytical model). Groundwater
**1999**, 37, 599–605. [Google Scholar] [CrossRef] - Singh, V.P. Is hydrology kinematic? Hydrol. Process.
**2002**, 16, 667–716. [Google Scholar] [CrossRef] - Vidon, P. Towards a better understanding of riparian zone water table response to precipitation: Surface water infiltration, hillslope contribution or pressure wave processes? Hydrol. Process.
**2012**, 26, 3207–3215. [Google Scholar] [CrossRef] - Vekerdy, Z.; Meijerink, A.M.J. Statistical and analytical study of the propagation of flood-induced groundwater rise in an alluvial aquifer. J. Hydrol.
**1998**, 205, 112–125. [Google Scholar] [CrossRef] - Barlow, J.R.; Coupe, R.H. Use of heat to estimate streambed fluxes during extreme hydrologic events. Water Resour. Res.
**2009**, 45, 1–10. [Google Scholar] [CrossRef] - Sophocleous, M.A. Stream-floodwave propagation through the Great Bend alluvial aquifer, Kansas: Field measurements and numerical simulations. J. Hydrol.
**1991**, 124, 207–228. [Google Scholar] [CrossRef] - Ministry of Land, Transportation, and Maritime Affairs (MLTM). The Detail Design of Development of Residential Sites for Nakdong River 18 District; MLTM: Seoul, Korea, 2009.
- Ministry of Land, Infrastructure, and Transport (MOLIT). Korea Annual Hydrological Report 2013; MOLIT: Seoul, Korea, 2013.
- National Climate Data Service System (NCDSS). Available online: http://sts.kma.go.kr/eng/jsp/home/contents/main/main.do (accessed on 29 September 2015).
- Choi, S.H.; Lyeo, S.C. National Geological Survey of Korea; Geological map of Namji Sheet (1:50000); National Geological Survey of Korea: Seoul, Korea, 1972; Sheet-6820-II. [Google Scholar]
- Kim, G.-B.; Cha, E.-J.; Jeong, H.-G.; Shin, K.-H. Comparison of time series of alluvial groundwater levels before and after barrage construction on the lower Nakdong River. J. Eng. Geol.
**2013**, 23, 105–115. (In Korean) [Google Scholar] [CrossRef] - Hydronet Limited (Hydronet). The Report for the Installation of the Groundwater Observation Equipment; Hydronet Limited: Seoul, Korea, 2012; pp. 1–311. [Google Scholar]
- Spanoudaki, K.; Nanou-Giannarou, A.; Paschalinos, Y.; Memos, C.D.; Atamou, A.I. Analytical solutions to the stream-aquifer interaction problem: A critical review. Global NEST J.
**2010**, 12, 126–139. [Google Scholar] - Hantush, M.S. Wells near streams with semipervious beds. J. Geophys. Res.
**1965**, 70, 2829–2838. [Google Scholar] [CrossRef] - Cooper, H.H.; Rorabaugh, M.I. Ground-water Movements and Bank Storage Due to Flood Stages in Surface Streams; U.S. Government Printing Office: Washington, DC, USA, 1963; pp. 343–366.
- Hantush, M.S. Discussion of paper by P.P. Rowe, An equation for estimating transmissibility and coefficient of storage from river-level fluctuations. J. Geophys. Res.
**1961**, 66, 1310–1311. [Google Scholar] [CrossRef] - Ferris, J.G. Cyclic fluctuations of water level as a basis for determining aquifer transmissibility. Assemblee Generale Bruxelles Ass. Int. Hydrol. Sci.
**1951**, 2, 148–155. [Google Scholar] - Bentall, R. Methods of Determining Permeability, Transmissibility and Drawdown; USGS Water Supply Paper 1536-I; United States Government Printing Office: Washington, DC, USA, 1964; p. 99.
- Spongberg, M.E. Spectral analysis of base flow separation with digital filters. Water Resour. Res.
**2000**, 36, 745–752. [Google Scholar] [CrossRef] - Walker, J.S. Fast Fourier Transforms, 2nd ed.; CRC Press: Boca Raton, FL, USA, 1996; pp. 58–76. [Google Scholar]
- Jacob, C.E. Flow of Groundwater in Engineering Hydraulics; Rouse, H., Ed.; John Wiley: New York, NY, USA, 1950; pp. 321–386. [Google Scholar]
- Carr, P.A.; Van Der Kamp, G.S. Determining aquifer characteristics by the tidal method. Water Resour. Res.
**1969**, 5, 1023–1031. [Google Scholar] [CrossRef]

**Figure 2.**Schematic cross-section of A-Aʹ (modified from [36]).

**Figure 3.**Temporal variation of the (

**a**) water level and (

**b**) electrical conductivity in the study area. NG_R, YS_S, and GR_S represent the Namgang River area, Yeongsan Stream area, and Gwangryeo Stream area, respectively.

**Figure 4.**Dimensionless groundwater head (h/A) for dimensionless time ($\omega t$) and distance from the river−aquifer interface according to (

**a**) river resistance (R) and (

**b**) flood duration time (t

_{d}).

**Figure 6.**Flood duration time (t

_{d}) in JD and duration time of induced groundwater fluctuation (t

_{g}) in observation wells (HAM-004, 040, 019, 056) along with amplitude (A) values for floodwave and groundwater fluctuations during flood events F-1 to F-6 in 2011 and F-7 to F-12 in 2012; (

**a**) t

_{d}versus t

_{g}, and (

**b**) A, respectively.

**Figure 7.**Flood duration time of groundwater levels (WL_Gs) for the flood events in 2011 and 2012; (

**a**) t

_{p}/t

_{d}(in JD) and t

_{ip}/t

_{g}(in observation wells) in 2011; (

**b**) t

_{p}/t

_{d}and t

_{ip}/t

_{g}in 2012; and (

**c**) average of t

_{ip}/t

_{g}versus distance from the river in 2011 and 2012.

**Figure 8.**Water level versus t

_{d}and t

_{g}for (

**a**) the F-1 event in 2011 and (

**b**) the F-9 event in 2012.

**Figure 9.**Example of observed (OBS) and low-pass filtered (LPF) groundwater level data at HAM-004 during the rainy season of (

**a**) 2011 and (

**b**) 2012.

**Figure 10.**Example of normalized filtered groundwater level (WL_G) data (i.e., low-pass filtered (LPF) data) versus normalized t

_{g}by the Fourier transform (FT) solution and Ferris (1951) [44] solution for flood events of F-4 (2011) and F-9 (2012); (

**a**) HAM-004 in 2011; (

**b**) HAM-004 in 2012; (

**c**) HAM-019 in 2011; (

**d**) HAM-019 in 2012; (

**e**) HAM-040 in 2011; (

**f**) HAM-040 in 2012; (

**g**) HAM-056 in 2011; (

**h**) HAM-056 in 2012; and (

**i**) HAM-041 in 2012.

**Figure 11.**Changes in hydraulic diffusivity (α) and river resistance (R) derived through use of the Fourier transform method. The numbers along the x-axis indicate the flood events, which are shown in order. (

**a**) HAM-004; (

**b**) HAM-040; (

**c**) HAM-019; (

**d**) HAM-056; and (

**e**) HAM-041.

Data | Unit | Location | Observation Period |
---|---|---|---|

Rainfall | mm | Yeongsan (in YS_S), Jindong (in GR_S), and Georyonggang (in NG_R) rainfall gauge stations | June 2011–February 2013 |

WL_R | m (AMSL) | Deongnam (in YS_S), Jingdong (in GR_S), and Georyonggang (in NG_R) gauge stations | |

Electrical conductivity of river water (EC_R) | µS/cm | Chilseo purification plant (with the Jingdong gauge station) | July 2012–February 2013 |

Groundwater level (WL_G) and Electrical conductivity (EC_G) | m (AMSL) and µS/cm | HAM-004, 005, 007, 008, 010, 013, 019, 022 (in YS_S), 038, 040, 042, 043, 046 (in GR_S), 056, 057, 059 (in NG_R) | June 2011–February 2013 |

HAM-014, 015, 021, 023, 035 (in YS_S), 045, 047, 048 (in GR_S), 060, 061, 062, 063, 064, 065 (in NG_R) | June 2012–February 2013 |

Year/Season | Before the River Barrage | After the River Barrage | ||
---|---|---|---|---|

2011 | 2012 | |||

Rainy (June–September) | Dry (November–Februaty) | Rainy (June–September) | Dry (November–February) | |

Rainfall (mm) | 1018 | 125 | 862 | 175 |

WL_R (m, AMSL) | 2.58 | 3.29 | 5.15 | 4.46 |

Fluctuation of WL_R (max–min. m) | 9.50 | 2.29 | 7.12 | 1.48 |

WL_G (m, AMSL) | 4.64 | 5.03 | 5.40 | 4.88 |

Average differences of WL_R (m) | 1.87 | |||

Fluctuation of WL_G (m) (max–min, m) | 12.30 | 8.15 | 13.75 | 9.74 |

Average differences of WL_R fluctuation (m) | 1.60 | |||

EC_R (µS/cm) | - | - | 370 | 262 |

Fluctuation of EC_R (max–min, µS/cm) | - | - | 549 | 322 |

EC_G (µS/cm) | 675 | 670 | 680 | 650 |

Fluctuation of EC_G (max–min, µS/cm) | 1404 | 2351 | 1709 | 1544 |

**Table 3.**Average values of estimated hydraulic parameters (FT: 1-D analytical solution derived by the Fourier transform).

Observation Point | Factors of Observation Points | Flood Events (F-1 to F-12) in June–September | |||
---|---|---|---|---|---|

F-1 to F-6 in 2011 | F-7 to F-12 in 2012 | ||||

FT | Ferris (1951) [44] | FT | Ferris (1951) [44] | ||

Jindong (JD) | t_{d} (h) | 181 | 130 | ||

t_{p} (h) | 83 | 57 | |||

A (m) | 2.05 | 0.54 | |||

HAM-004 | t_{g} (h) | 186 | 133 | ||

t_{ip} (h)/t_{lag} (h) | 106/23 | 62/5 | |||

A (m) | 1.05 | 0.63 | |||

x (m) | 300 | ||||

T (m^{2}/h)/K (m/s) | 1.22 × 10^{−2}/8.68 × 10^{−8} | ||||

α (m^{2}/h) | 5400 | 3980 | 21,850 | 16,850 | |

R (m) | 335 | - | 88 | - | |

HAM-019 | t_{g} (h) | 190 | 133 | ||

t_{ip} (h)/t_{lag} (h) | 101/18 | 65/9 | |||

A (m) | 0.84 | 0.48 | |||

x (m) | 600 | ||||

T (m^{2}/h)/K (m/s) | 3.73 × 10^{−1}/3.91 × 10^{−6} | ||||

α (m^{2}/h) | 11,250 | 9300 | 22,717 | 19,850 | |

R (m) | 420 | - | 125 | - | |

HAM-040 | t_{g} (hr) | 185 | 135 | ||

t_{ip} (h)/t_{lag} (h) | 97/14 | 63/6 | |||

A (m) | 0.89 | 0.54 | |||

x (m) | 250 | ||||

T (m^{2}/h)/K (m/s) | 4.52 × 10^{−2}/4.18 × 10^{−7} | ||||

α (m^{2}/h) | 3333 | 2045 | 6983 | 5357 | |

R (m) | 975 | - | 108 | - | |

HAM-041 | t_{g} (h) | - | 128 | ||

t_{ip} (h)/t_{lag} (h) | - | 70/13 | |||

A (m) | - | 0.52 | |||

x (m) | 800 | ||||

T (m^{2}/h)/K (m/s) | 4.67 × 10^{−1}/5.13 × 10^{−6} | ||||

α (m^{2}/h) | - | - | 52,533 | 46,350 | |

R (m) | - | - | 138 | - | |

HAM-056 | t_{g} (h) | 191 | 122 | ||

t_{ip} (h)/t_{lag} (h) | 91/8 | 63/7 | |||

A (m) | 1.30 | 0.57 | |||

x (m) | 850 | ||||

T (m^{2}/h)/K (m/s) | 1.84 × 10^{−2}/1.50 × 10^{−7} | ||||

α (m^{2}/h) | 74,167 | 67,566 | 132,667 | 114,917 | |

R (m) | 363 | - | 163 | - |

© 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Oh, Y.-Y.; Hamm, S.-Y.; Ha, K.; Yoon, H.; Chung, I.-M.
Characterizing the Impact of River Barrage Construction on Stream-Aquifer Interactions, Korea. *Water* **2016**, *8*, 137.
https://doi.org/10.3390/w8040137

**AMA Style**

Oh Y-Y, Hamm S-Y, Ha K, Yoon H, Chung I-M.
Characterizing the Impact of River Barrage Construction on Stream-Aquifer Interactions, Korea. *Water*. 2016; 8(4):137.
https://doi.org/10.3390/w8040137

**Chicago/Turabian Style**

Oh, Yun-Yeong, Se-Yeong Hamm, Kyoochul Ha, Heesung Yoon, and Il-Moon Chung.
2016. "Characterizing the Impact of River Barrage Construction on Stream-Aquifer Interactions, Korea" *Water* 8, no. 4: 137.
https://doi.org/10.3390/w8040137