water

Article Impacts of the on the Interaction between Surface Water and Groundwater in the Lower Weihe River of Watershed

Dong Zhang 1,2, Dongmei Han 1,2,* and Xianfang Song 1,2 1 Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11 A, Datun Road, Chaoyang , 100101, ; [email protected] (D.Z.); [email protected] (X.S.) 2 College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China * Correspondence: [email protected]; Tel.: +86-10-6488-8866

 Received: 8 May 2020; Accepted: 9 June 2020; Published: 11 June 2020 

Abstract: Sanmenxia Dam, one of the most controversial water conservancy projects in China, has seriously impacted the lower Weihe River of the Yellow River Watershed since its operation. At the Huaxian Station, the dam operation controls the surface water level and leads to the variation of the surface water–groundwater interaction relationship. The river channel switched from a losing reach during the early stage (1959) to a gaining reach in 2010 eventually. The comparison of tracer 18 2 (Cl−, δ O and δ H) characteristics of surface water in successive reaches with that of ambient groundwater shows that the general interaction condition is obviously affected by the dam operation and the impact area can be tracked back to City, around 65 km upstream of the estuary of the Weihe River. The anthropogenic inputs (i.e., agricultural fertilizer application, wastewater discharge, and rural industrial sewage) could be responsible for the deterioration of hydro-environment during the investigation periods of 2015 and 2016, as the population and fertilizer consumption escalated in the last 60 years. The use of contaminated river water for irrigation, along with the dissolved fertilizer inputs, can affect the groundwater quality, in particular resulting in the NO3− concentrations ranging from 139.4 to 374.1 mg/L. The unregulated industrial inputs in some rural areas may increase the Cl− contents in groundwater ranging from 298.4 to 472.9 mg/L. The findings are helpful for the improved comprehensive understanding of impacts of the Sanmenxia Dam on the interaction between surface water and groundwater, and for improving local water resources management.

Keywords: Sanmenxia Dam; surface water–groundwater interaction; lower Weihe River

1. Introduction Surface water (SW) and ambient groundwater (GW) are always interacting in the hydrologic cycle [1]. Understanding the interactions between SW and GW is critical for purposes like water resources utilization and management [2,3], water quality assessment [4,5], and ecohydrology analysis [6,7]. One of the main factors controlling the SW–GW interaction is the hydraulic gradient [8], which is variable since levels of SW and GW are persistently affected by various natural and anthropic conditions. provide many benefits while also disturb the river systems and produce some unexpected hydrologic impacts on discharge, sedimentation, and aquatic vegetation, etc. [9–12]. The SW level can be directly affected by the storing and releasing process of dams, which may change the hydraulic gradients of SW–GW interactions [5,13,14]. SW and GW can also be polluted by many anthropogenic sources, such as agricultural non-point pollutants, domestic sewage, industrial wastewater [15–17]. In different river reaches, water quality may respond differently to the SW–GW interaction changes [18,19].

Water 2020, 12, 1671; doi:10.3390/w12061671 www.mdpi.com/journal/water Water 2020, 12, 1671 2 of 18

In losing river reaches, pollutants from upstream may migrate to ambient GW [20], while, in gaining river reaches, pollutants in GW may also transport to SW [21]. Therefore, understanding the SW–GW interaction variation is important for water resources management. The Sanmenxia Dam is the first large-scale water conservancy project built on the Yellow River. The purposes of the dam were to control flooding, hydroelectric power, agricultural irrigation, and navigation. However, the dam soon suffered from the severe sedimentation problems caused after its operation [22]. The sedimentation problem is not only confined to the but also extended upstream to the Weihe River, which is the largest tributary of the Yellow River. The riverbed elevation in the lower Weihe River has risen sharply due to the serious sedimentation problem, which makes the river water level with the same discharge ascend significantly [23]. This may lead to variations of the SW–GW interaction along the Weihe River, especially in its lower reach. The lower Weihe River Basin has been a major agricultural area in China since the 3rd century B.C. Increasing use of fertilizers in these farmlands during recent decades is likely to affect the SW and GW which support the rural and urban communities with millions of people in this [24]. Other anthropogenic sources like domestic sewage and industrial wastewater may also deteriorate the water quality [25]. It is crucial to improve the understanding of the impact of the Sanmenxia Dam on SW–GW interaction and their potential consequences on the water quality for further water resources management. However, insufficient attention has been paid to these issues in previous studies. Since hydraulic gradients between SW and GW are the major factors controlling their interaction process, analysis of the water level data is helpful for the investigation of SW–GW interaction [26–28]. Statistical methods like Mann–Kendall test are often used to support the analysis [29,30]. Hydrochemical and stable isotopes methods are also widely used to understand the SW–GW interaction in many related studies [31–35]. The general interaction condition can be acquired by separating a river into different segments by the SW sampling sites and comparing the values of these tracers in each segment with the values in the ambient GW samples [34]. This study investigates the impacts of the Sanmenxia Dam on the SW–GW interaction in the lower Weihe River Basin. The objectives of this study are (i) to identify the variations of SW–GW interaction under the impact of the Sanmenxia Dam, (ii) to reveal hydrochemical variations after the dam operation and anthropogenic inputs, and (iii) to obtain a reliable conceptual model of the SW–GW interaction at a typical cross-section.

2. Study Area

2.1. The Lower Weihe River The Weihe River flowing across the southern part of the Plateau is the largest tributary of the Yellow River in terms of the mainstream length (818 km) and the average annual runoff (6.8 billion m3). The Weihe River is also the main sediment source of the Yellow River, which delivers 44.7% of the total sediment load of the Yellow River. The Weihe River Basin with an area of 134,800 km2 is a water-deficient region in the belt of transition between semi-arid and sub-humid zones in China. The average annual temperature of the Weihe River Basin ranges from 6 to 14 ◦C, and the average annual precipitation is about 545 mm. This study focuses on the lower Weihe River Basin, with coordinates between 109◦120 E and 110◦130 E and 34◦220 N to 34◦500 N (Figure1). According to meteorological data from 1950 to 2015 collected from the China Meteorological Data Service Center, the average monthly temperature ranged from 7.0 C in January to 26.4 C in July. The average annual precipitation was 617 mm, and the − ◦ ◦ rainfall from June to September accounted for about 64.4% of the annual precipitation. The average annual potential evapotranspiration was 941 mm. The elevations of the study area range from 243 to 2450 m above sea level and the topography of the south side is obviously higher than the north side. The River, one major tributary of the Weihe River (annual runoff of 0.9 billion m3), flows into the Weihe River in the Huayin County. The general geomorphic types in the research area are Water 2020, 12, 1671 3 of 18

Water 2020, 12, x FOR PEER REVIEW 3 of 18 alluvial plain, diluvium-alluvial plain, and loess platform (Figure1b). The alluvial plain is mainly distributeddistributed along along the the Weihe Weihe River. River. The phreatic The phreatic aquifer aquifer in the alluvial in the plain alluvial is composed plain is of composed Quaternary of unconsolidatedQuaternary unconsolidated sediments with sediments the thickness with the ranging thickness from ranging 10.5 to 63.5from m. 10.5 to 63.5 m.

FigureFigure 1. 1. ((aa)) StudyStudy areaarea andand relevantrelevant samplingsampling sites;sites;( (bb)) locationslocations of of thethe studystudy areaarea andand thethe SanmenxiaSanmenxia Dam;Dam; (c(c)) geomorphic geomorphic types types in in the the study study area. area.

2.2.2.2. SanmenxiaSanmenxia DamDam TheThe Sanmenxia Sanmenxia Dam Dam is located is located on the on middle the middle reach of reach the Yellow of the River Yellow (Figure River1b). (Figure The catchment 1b). The 2 areacatchment above thearea dam above is aboutthe dam 690,000 is about km ,690,000 which accountskm2, which for accounts 92% of the for whole 92% of Yellow the whole River Yellow Basin. TheRiver construction Basin. The andconstruction water impoundment and water impoundment of the dam were of the initiated dam were in 1957 initiated and 1960, in 1957 respectively. and 1960, Therespecti designedvely. normalThe designed water level normal of the water dam level is 350 of m, the and dam due is to 350 the m, estimate and due on to the the influence estimate scope on the of theinfluence dam, over scope 187,000 of the people dam, over in the 187,000 Weinan people City, Dali in the County, Weinan Huayin City, County,Dali County, and Huaxian Huayin CountyCounty, (Figureand Huaxian1a) migrated County from (Figure their 1a) original migrated residences. from their Afteroriginal impoundment residences. After of the impoundment Sanmenxia Dam, of the aSanmenxia severe sedimentation Dam, a severe problem sedimentation became evident, problem especially became evident,in the lower especially Weihe in River. the lower The highest Weihe operationRiver. The water highest level operation on record water is about level 333 on record m and is the about direct 33 backwater3 m and the boundary direct backwater reached upstreamboundary toreached the Huaxian upstream Station. to the In Huaxian order to Stati solveon. the In sedimentation order to solve problem, the sedimentation the operation problem, scheme the of operation the dam hadscheme been of changed the dam twice, had which been alsochanged made twice, the dam which never also meet made the theinitial dam impounding never meet expectation the initial sinceimpounding its operation. expectation The three since operation its operation. modes The were three as operation follows: (i)modes storing were water as follows: mode (Mode (i) storing A), fromwater September mode (Mode 1960 A), to Marchfrom September 1962, the reservoir 1960 to maintainedMarch 1962, a the high reservoir water storage maintained level, (ii)a high detaining water floodstorage water level, and (ii) sluicing detaining sediment flood water mode and (Mode sluicing B), from sediment March mode 1962 (Mode to October B), from 1973, March the reservoir 1962 to keptOctober a low 1973, storage the reservoir level, while kept detaining a low storage floods level, only while during detaining flood seasons floods only (November during flood to June) seasons and sluicing(November sediment to June) with and relatively sluicing large sediment discharges, with andrelatively (iii) storing large cleardischarges, water andand releasing(iii) storing muddy clear waterwater mode and releasing (Mode C), muddy from Novemberwater mode 1973 (Mode to the C), present, from November the reservoir 1973 was to the operated present, at the a high reservoir level towas store operated relatively at a clearhigh leve waterl to in store the relatively non-flood clear seasons water and in atthe a non low-flood level toseasons release and high at a sediment low level concentrationsto release high insediment the flood concentrations seasons. in the flood seasons. TimeTime series series data data of of the the poolpool levellevel ofof thethe SanmenxiaSanmenxia DamDam duringduring thethe floodflood andand non-floodnon-flood seasonsseasons andand thethe wholewhole yearyear presentpresent aa similarsimilar changechange processprocess (Figure(Figure2 ).2). It It shows shows di differentfferent variationvariation charactercharacter corresponding to each operation mode. The pool levels in Mode A increased and reached the highest. The pool levels in Mode B show an obvious downward trend. However, the pool levels in Mode C

Water 2020, 12, 1671 4 of 18 corresponding to each operation mode. The pool levels in Mode A increased and reached the highest. TheWater pool 2020, levels 12, x FOR in PEER Mode REVIEW B show an obvious downward trend. However, the pool levels in Mode4 of C18 remain relatively stable after a rise that ends in 1980 (Figure2). Thus, the impacts from the Sanmenxia remain relatively stable after a rise that ends in 1980 (Figure 2). Thus, the impacts from the Sanmenxia Dam that were imposed on the lower Weihe River can be assumed generally unchanged since 1980. Dam that were imposed on the lower Weihe River can be assumed generally unchanged since 1980.

FigureFigure 2.2. PoolPool levellevel (water(water levellevel inin reservoir)reservoir) ofof thethe SanmenxiaSanmenxiaDam Damfrom from 1960 1960 to to 2015. 2015.

3.3. MaterialsMaterials andand MethodsMethods 3.1. Data Collection 3.1. Data Collection The hydrochemical data in 1959 (Table S1 in Supplementary Materials) were collected from the The hydrochemical data in 1959 (Table S1 in Supplementary Materials) were collected from the results of a hydrogeological survey conducted by the Yellow River Conservancy Commission [36]. results of a hydrogeological survey conducted by the Yellow River Conservancy Commission [36]. SW and GW samples form three campaigns in May, August, and November. A total of 19 SW samples SW and GW samples form three campaigns in May, August, and November. A total of 19 SW samples (five sites from the Weihe River and two sites from the Luohe River) and 55 GW samples taken from (five sites from the Weihe River and two sites from the Luohe River) and 55 GW samples taken from phreatic wells (19 sites) which were adjacent to the Weihe and Luohe Rivers were chosen for this phreatic wells (19 sites) which were adjacent to the Weihe and Luohe Rivers were chosen for this study (Figure1a). The gridded meteorological data were from the China Meteorological Data Service study (Figure 1a). The gridded meteorological data were from the China Meteorological Data Service Center. The discharge and water level of the Weihe River were measured daily at the Huaxian Station. Center. The discharge and water level of the Weihe River were measured daily at the Huaxian Station. The ambient GW levels were measured at least every five days at three monitoring wells (B18, B561, The ambient GW levels were measured at least every five days at three monitoring wells (B18, B561, and B562). The population, fertilizer consumption, and groundwater exploitation data were gathered and B562). The population, fertilizer consumption, and groundwater exploitation data were gathered from the China’s economic and social big data research platform (http://data.cnki.net/) which collected from the China’s economic and social big data research platform (http://data.cnki.net/) which statistical yearbooks of the Weinan City. collected statistical yearbooks of the Weinan City. 3.2. Water Sampling 3.2. Water Sampling Three field campaigns were conducted in October 2015, June 2016, and September 2016. A total Three field campaigns were conducted in October 2015, June 2016, and September 2016. A total of 22 SW samples (eight sites from the Weihe River, two sites from the Luohe River) and 41 GW of 22 SW samples (eight sites from the Weihe River, two sites from the Luohe River) and 41 GW samples taken from domestic and agricultural wells (21 sites, phreatic water) adjacent to the Weihe and samples taken from domestic and agricultural wells (21 sites, phreatic water) adjacent to the Weihe Luohe Rivers were collected (Figure1a and Table S1 in Supplementary Materials). The GW samples and Luohe Rivers were collected (Figure 1a and Table S1 in Supplementary Materials). The GW were taken after purging the wells for a few minutes at each site. The polyethylene bottles (50 and samples were taken after purging the wells for a few minutes at each site. The polyethylene bottles 100 mL) used as sample containers were pre-rinsed three times before sample collection and sealed (50 and 100 mL) used as sample containers were pre-rinsed three times before sample collection and with adhesive tape. All the water samples were store in the refrigerator at 4 ◦C after collection. sealed with adhesive tape. All the water samples were store in the refrigerator at 4 °C after collection. 3.3. Analytical Techniques 3.3. Analytical Techniques Major ion compositions for each sample collected in 2015–2016 were measured at the Center for PhysicalMajor and ion Chemical compositions Analysis, for theeach Institute sample of collected Geographic in 2015 Sciences–2016 andwere Natural measured Resources at the Center Research for (IGSNRR),Physical and Chinese Chemical Academy Analysis, of Sciences the (CAS).Institute Major of Geographic cations (Na + Sciences,K+, Ca2 + and, Mg 2 Natural+) were measured Resources + + 2+ 2+ onResearch an inductively (IGSNRR), coupled Chinese plasma Academy optical of emission Sciences spectrometer(CAS). Major (ICP-OES)cations (Na (Perkin-Elmer, K , Ca , Mg Optima) were measured on an inductively coupled plasma optical emission spectrometer (ICP-OES) (Perkin-Elmer Optima 5300DV, Waltham, Massachusetts, USA). Cl−, SO42−, and NO3− were determined by an ion chromatography system (ICS1000). HCO3− was measured by the diluted vitriol-methylic titration method using 0.016 M H2SO4. The normalized inorganic charge balance (NICB) was applied to ensure

Water 2020, 12, 1671 5 of 18

2 5300DV, Waltham, MA, USA). Cl−, SO4 −, and NO3− were determined by an ion chromatography system (ICS1000). HCO3− was measured by the diluted vitriol-methylic titration method using 0.016 M H2SO4. The normalized inorganic charge balance (NICB) was applied to ensure the charge-balance error of the water sample was in a reasonable scope [37,38]. The results of the major ion compositions analysis were accepted when the charge-balance error was within 10%. ± Stable isotopes (δ2H and δ18O) of the water samples were measured at the Key Laboratory of Water Cycle and Related Land Surface Processes of IGSNRR, using a liquid water isotope analyzer (Model DLT-100, LosGatos Research Inc., San Jose, CA, USA) with measurement accuracies of 1% ± and 0.15% for δ2H and δ18O, respectively. All results were normalized to internal laboratory water ± standards (LRG3A, δ2H = 96.4%, δ18O = 13.10%; LRG4A, δ2H = 51.0%, δ18O = 7.69%; LRG5A, − − − − δ2H = 9.5%, δ18O = 2.80%) that were previously calibrated relative to the (VSMOW, 0%). δ2H and − − δ18O values were reported in conventional per thousand deviations referred to the Vienna Standard Mean Ocean Water (V-SMOW, 0%). Table S2 in Supplementary Materials shows the hydrochemical and stable isotopes data.

3.4. Statistical Method The Mann–Kendall test (M-K test) is one of the widely used methods to detect trends of different time series [39]. The statistic S in the Mann–Kendall test is calculated as follow:

 + Xn 1 Xn  1, i f xj > xi −  S = sgn(xj xi) where sgn =  0, i f xj = xi (1) −  i=1 j=i+1  1, i f x < x − j i where x is the variable, n is the length of time series. If n is larger than 8, S will approximately follow a normal distribution [40]. The mean and variance of S can be acquired by Equations (2) and (3) below.

E(S) = 0 (2)

n(n 1)(2n + 5) Var(S) = − (3) 18 The Z statistics for evaluating the trend is calculated by Equation (4):

 S 1  − i f S > 0  √Var(S)  Z =  0 i f S = 0 (4)   S+1 i f S < 0  √Var(S)

A positive (negative) Z-value indicates an increasing (decreasing) trend. Z-value also can be used to check if the trend is significant at the selected significance level α. The null hypothesis that there is no significant trend will be rejected when |Z| > Z1 α/2. − 4. Results

4.1. Water Level Variations The Huaxian Station is a representative station with relatively continuous data for the study area. Moreover, most of the sediment deposition caused by the Sanmenxia Dam was in the downstream channel of the Huaxian Station [23], which may enhance the variation of SW–GW interaction. The temporal variations of the annual average SW level, ambient GW level, and precipitation can be seen in Figure3a. Water 2020, 12, 1671 6 of 18 Water 2020, 12, x FOR PEER REVIEW 6 of 18

FigureFigure 3. 3.Comparison Comparison of of surface surface water water (SW) (SW) level, level, groundwater groundwater (GW) (GW) level, level, runo runoffff,, and and precipitation: precipitation: (a()a annual) annual average average SW SW level level at at Huaxian Huaxian Station, Station GW, GW level level at at B18, B18, B561, B561, B562, B562, precipitation, precipitation, runo runoffff at at HuaxianHuaxian Station Station from from 1959–2010; 1959–2010; ( b(b––e)e) SW SW level level at at Huaxian Huaxian Station, Station, GW GW level level at at B18, B18, B561, B561, B562 B562 in in 1959,1959, 1981, 1981, 2002, 2002, 2010. 2010.

TheThe trend trend of of the the annual annual average average SW SW level level and and runo runoffff were we analyzedre analyzed by theby the M-K M test.-K test. Statistic StatisticZ of Z theof SWthe levelSW level is 3.99 is indicating3.99 indicating a significant a significant upward upward trend, while trend, statistic while Zstatisticof the runoZ offf theis runoff1.89 showing is −1.89 − ashowing downward a downward trend. When trend. the riverbedWhen the is riverbed stable, the is stable, river water the river level water with level given with discharge given isdischarge almost theis same almost and the the same trends and of river the water trends level of river and runo waterff should level be and consistent. runoff should The inconsistent be consistent. trends The of theinconsistent SW level and trends runo offf theatthe SW Huaxian level and Station runoff indicate at the Huaxian that the riverbedStation indicate has risen that after the the rive operationrbed has ofrisen the Sanmenxiaafter the operation Dam. The ofriverbed the Sanmenxia elevation Dam. at the The Huaxian riverbed Station elevation rose onlyat the 3 Huaxian m during Station 2500 years rose fromonly 5403 m BC during to 1960 2500 AD years [41]. from In 1959 540 (before BC to the1960 dam AD operation), [41]. In 1959 the (before annual the average dam operation), SW level and the runoannualff at average the Huaxian SW level Station and arerunoff 333.4 at mthe and Huaxian 61.9 Station108 m3 ,are respectively. 333.4 m and However, 61.9 × 108 after m3, re 50spectively. years of × theHowever, dam operation after 50 (inyears 2010), of the the dam annual operation average (in SW 2010), level the rose annual 3 m to average 336.4 m SW with level the rose annual 3 m average to 336.4 runom withff of 60.2the annual108 m average3. It indicates runoff that of 60.2 thedam × 10 operation8 m3. It indicates might be that responsible the dam for operation the elevation might of be × theresponsible SW level atfor the the Huaxian elevation Station. of the SW level at the Huaxian Station. TheThe M-K M-K test test was was also also applied applied for for the the annual annual average average GW GW level level series. series. Statistic StatisticZ Zof of the the annual annual averageaverage GW GW at at B18 B18 from from 1959 1959 to to 1985 1985 is is 1.56. 1.56. The The statistic statisticZ Zof of the the annual annual average average GW GW at at B561 B561 and and B561B561 from from 1976 1976 to to 2010 2010 is is −11.82.82 and and −22.20..20. TheThe didifferentfferent trendstrendsof of the the GW GW levels levels in in di differentfferent periods periods − − indicateindicate that that the the controlling controlling factor factor of of the the GW GW level level has has changed changed from from 1959 1959 to 2010. to 2010. In order In order to seek to seek the reasonthe reason why thewhy GW the levels GW levels change, change, the correlation the correlation coefficients coeffi amongcients theamong GW the levels, GW SW levels, level, SW and level the , precipitationand the precipitation were calculated were calculated and shown and in Tableshown1. Thein Table GW 1. levels The atGW B18, levels B561, at and B18, B562 B561, are and highly B562 correlatedare highly with correlated each other. with The each GW other. level The at B18 GW is fromlevel 1959 at B18 to 1985.is from The 1959 GW to levels 1985. at The B561 GW and levels B562 isat fromB561 1976 and toB562 2010. is Thefrom correlation 1976 to 2010. coe ffiThecient correlation of the GW coe levelfficient at B18 of isthe significantly GW level at correlated B18 is significantly to the SW levelcorrelated (0.01 level) to the and SW the level precipitation (0.01 level) (0.05 and level).the precipitation It demonstrates (0.05 thatlevel). the It SW demonstrates level and precipitation that the SW arelevel the and driving precipitation factors of are the the GW driving level from factors 1959 of tothe 1985. GW However,level from the 1959 GW to levels1985. However, at B561 and the B562 GW cannotlevels at present B561 and a significant B562 cannot correlation present a with significant the SW correlation level or the with precipitation. the SW level The or GW the precipitation. exploitation dataThe inGW the exploitation study area increaseddata in the from study 1980 area to 2010increased (Figure from4). The1980 correlation to 2010 (Figure coe ffi cient4). The between correlation the GWcoef levelsficient and between GW exploitation the GW levels are and0.72 GW (B561) exploitation and 0.75 ar (B562),e −0.72 both (B561) negatively and −0.75 correlated (B562), at both a − − significancenegatively levelcorrelated of 0.01, at indicatinga significance that level the driving of 0.01, factor indicating of the that GW the level driving is groundwater factor of the exploitation GW level afteris groundwater the 1980s across exploitation this region. after the 1980s across this region.

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Water 2020, 12, x FOR PEER REVIEW 7 of 18

Table 1. Correlation coefficient of the SW level, GW levels, and precipitation. Table 1. Correlation coefficient of the SW level, GW levels, and precipitation. B18 B561 B562 SW Precipitation B18 B561 B562 SW Precipitation B18B18 1 1 B561 0.99 ** 1 B561 0.99 ** 1 B562 0.97 ** 0.98 ** 1 SWB562 0.85 **0.97 ** 0.980.32 ** 1 0.35 1 − − PrecipitationSW 0.29 *0.85 ** −0.32 0.20 −0.35 0.21 1 0.29 1 Precipitation** significant 0.29 at* 0.010.20 level, * significant0.21 at0.29 0.05 level. 1 ** significant at 0.01 level, * significant at 0.05 level.

Figure 4. Groundwater exploitation from 1980 to 2010.

Figure3 3bb–e–e showsshows thethe relationshiprelationship betweenbetween thethe SWSW andand GWGW levels.levels. BeforeBefore thethe damdam operation,operation, inin 1959,1959, thethe GWGW level level at at B18 B18 is is above above the the river river stage stage at at the the Huaxian Huaxian station station (Figure (Figure3b), 3b), which which means means the reachthe reach around around the Huaxian the Huaxian Station Station is a gaining is a gaining reach. reach. After theAfter dam the operation, dam operation, in 1981, in the 1981, GW levelsthe GW at B18,levels B561, at B18, and B561 B562, and are above B562 are the SWabove level the in SW non-flood level in season non-flood and belowseason the and SW below level the inflood SW level season in (Figureflood season3c). In (Figure 2002 and 3c). 2010, In 2002 the and GW 2010, levels the at GW B561 levels and B562 at B561 are an belowd B562 the are SW below level indicatingthe SW level a losingindicating reach a aroundlosing reach the Huaxian around Stationthe Huaxian (Figure Station3d,e). The(Figure average 3d,e). GW The at average B18 is 335.34 GW at m B18 in 1981 is 335.34 and 335.60m in 1981 m in and 1959, 335.60 while m thein 1959, average while SW the level average at the SW Huaxian level at Station the Huaxian is 335.2 Station m in 1981 is 335.2 and m 333.36 in 1981 m inand 1959, 333.36 as shownm in 1959, in Table as shown2. It is in obvious Table 2. that It is the obvious rising SWthat levelthe rising is the SW main level reason is the for main the changereason for of SW–GWthe change interaction of SW–GW pattern interaction from 1959pattern to 1981from near 1959 the to 1981 Huaxian near Station.the Huaxian The GWStation. levels The at GW B561 levels and B562at B561 have and dropped B562 have from dropped 1981 to from 2010, 1981 while to the 2010, SW while level isthe still SW ascending. level is still Therefore, ascending. the Therefore, rising SW levelthe rising participated SW level in participated the two shifts in the of the two interaction shifts of the pattern, interaction which pattern, makes which the upward makes SW the levelupward the primarySW level cause the primary for the interactioncause for the variations interaction at thevariations Huaxian at Station.the Huaxian Station.

Table 2.2. AnnualAnnual average average water water level level at atthe the Huaxian Huaxian Station Station and and groundwater groundwater level level at B18, at B18,B561 B561,, and andB562 B562 in 1959, in 1959, 1981, 1981, 2002 2002,, and and2010 2010..

YearYear HuaxianHuaxian Station Station (m) (m) B18B18 (m)(m) B561 B561 (m) (m)B562 (m) B562 (m) 19591959 333.36333.36 335.60335.60 - -- - 19811981 335.21335.21 335.34335.34 335.15 335.15 335.01 335.01 20022002 336.61336.61 -- 332.35 332.35 331.10 331.10 2010 336.44 - 334.29 333.88 2010 336.44 - 334.29 333.88

4.2. Hydrochemical Characteristic in Waters 4.2.1. Hydrochemical Characteristics before the Dam Operation 4.2.1. Hydrochemical Characteristics before the Dam Operation In 1959, the TDS values of the SW samples vary from 159.1 (W1 in May) to 363.0 mg/L (W5 in May) In 1959, the TDS values of the SW samples vary from 159.1 (W1 in May) to 363.0 mg/L (W5 in in the Weihe River and from 330.0 (L1 in August) to 674.2 mg/L (L1 in May) in the Luohe River. The TDS May) in the Weihe River and from 330.0 (L1 in August) to 674.2 mg/L (L1 in May) in the Luohe River. The TDS values decrease along the flow direction in the Weihe River and stay almost the same in the Luohe River. The temporal variations of TDS in the Weihe and Luohe Rivers are also different. The

Water 2020, 12, x FOR PEER REVIEW 8 of 18 Water 2020, 12, 1671 8 of 18 former changes a little and the latter shows a sharp difference in three campaigns. The TDS values of the GWvalues samples decrease vary along from the 118.9 flow direction(B47 in May) in the to Weihe 2002.5 River mg/L and (B269 stay almostin November). the same inThe the TDS Luohe values of GWRiver. in the The southeast temporal (including variations of B144, TDS inB47, the B50, Weihe B282, and B41, Luohe and Rivers B245) are are also much different. lower The than former those in the restchanges part aof little the andinvestigated the latter shows area. a sharp difference in three campaigns. The TDS values of the GW samples vary from 118.9 (B47 in May) to 2002.5 mg/L (B269 in November). The TDS values of GW in Na+ and HCO3− are the dominant ions of the SW samples, with concentrations varying from 17.3 the southeast (including B144, B47, B50, B282, B41, and B245) are much lower than those in the rest to 143.0 mg/L and from 118.9 to 251.0 mg/L, respectively. The dominant cation in groundwater is Ca2+ part of the investigated area. + in the southeast+ with concentrations varying from 20.2 to 77.8 mg/L a in the remaining part with Na and HCO3− are the dominant ions of the SW samples, with concentrations varying from − concentrations17.3 to 143.0 ranging mg/L and from from 38.8 118.9 to to 73.9 251.0 mg/L. mg/L, respectively.The dominant The anion dominant in the cation GW in samples groundwater is HCO is 3 , whichCa varies2+ in the from southeast 119.0 to with 1296.7 concentrations mg/L and varyingaccounts from for 20.269.3% to 77.8of the mg anions/L a+ in on the average. remaining part withThe concentrationspiper diagram ranging can be from used 38.8 to todistinguish 73.9 mg/L. Thediffer dominantent water anion types in the of GWthe SW samples and isGW HCO samples3−, in 1959which (Figure varies 5). from The 119.0 SW to has 1296.7 a narrower mg/L and range accounts than for the 69.3% GW, of theplotting anions within on average. Area 1 and Area 5, while theThe GW piper scatters diagram in Area cans be 1, used4, and to 5. distinguish Some GW di samplesfferent water plot typesadjacent of the to SWthe andSW GWon the samples diamond diagram,in 1959 while (Figure other5).s The do SWnot, hasindicating a narrower that range the different than the GW,patterns plotting of SW within–GW Area interaction 1 and Area may 5, exist in thewhile research the GW area. scatters Cl− behaves in Areas 1,relatively 4, and 5. Someconservative GW samplesly and plot is adjacent commonly to the used SW onas thea tracer diamond [42,43]. In 1959,diagram, the rivers while in others the research do not, indicating can be separated that the di intofferent dif patternsferent segments of SW–GW by interaction the SW sampling may exist sites in the research area. Cl behaves relatively conservatively and is commonly used as a tracer [42,43]. shown in Figure 6a,b. The− tributaries of the lower Weihe River in the research area have little impact In 1959, the rivers in the research can be separated into different segments by the SW sampling sites on the tracer values since the discharge of them is quite small. The ambient GW samples are also shown in Figure6a,b. The tributaries of the lower Weihe River in the research area have little impact − listedon in the Figure tracer 6 valuesa,b. There since theare discharge some river of them segments is quite along small. which The ambient the concentrations GW samples are of also Cl listed increase (decrease) with much higher (lower) Cl− values in the ambient GW (e.g., the segments L2-L1 in May, in Figure6a,b. There are some river segments along which the concentrations of Cl − increase (decrease) W2-W1with in much August). higher It(lower) may Cl imply− values that in thethese ambient river GW segments (e.g., the are segments gaining L2-L1 reaches. in May, The W2-W1 remaining in segmentsAugust). that It have may implynot shown that these such river relationships segments aremay gaining indicate reaches. losing The reaches. remaining The segments Huaxian that Station is in havethe river not shown segment such W2 relationships-W1. In May, may the indicate Cl− values losing reaches.decrease The from Huaxian 25.2 (W2) Station to is20.6 in the mg/L river (W1) whilesegment the average W2-W1. Cl In− values May, the in Clth−evalues ambient decrease GW (B41 from 25.2and (W2)B282) to is 20.6 12.5 mg mg/L,/L (W1) which while themeans average that the segmentCl− values is a gaining in the ambient reach. GW It also (B41 andoccurs B282) in is August 12.5 mg / forL, which the river means segment that the segment W2-W1. is The a gaining SW–GW interactionreach. Itcondition also occurs is consistent in August for with the the river results segment obtained W2-W1. from The the SW–GW water interactionlevel data conditionbefore the is dam consistent with the results obtained from the water level data before the dam operation. operation.

FigureFigure 5. 5.PiperPiper plo plott for for the SW andand GW GW samples. samples.

4.2.2. Current Hydrochemical Characteristics

Na+ and HCO3− are the predominant ions of the SW, with concentrations ranging from 17.3 to 143.0 mg/L and 118.9 to 251.0 mg/L, respectively. The dominant cations of the GW are Ca2+ in the southeast with concentrations varying from 20.2 to 77.8 mg/L and Na+ in the remaining part with concentrations ranging from 38.8 to 73.9 mg/L. The dominant anion in GW is HCO3−, which varies from 119.0 to 1296.7 mg/L and account 69.3% of the anions on average.

Water 2020, 12, 1671 9 of 18

Water 2020, 12, x FOR PEER REVIEW 10 of 18

Figure 6. Spatial distribution of the tracers and sketch map of SW–GW interaction patterns along the Figure 6. Spatial distribution of the tracers and sketch map of SW–GW interaction patterns along Weihethe Weihe and Luohe and Luohe Rivers, Rivers, before before the dam: the dam: (a) in (a May) in May 1959, 1959, (b) in (b )August in August 1959; 1959; in current in current status status (c) in June(c) in 2016, June ( 2016,d) in (d September) in September 2016. 2016. The The segments segments of of the the rivers rivers are are separated by by the the surface surface water water samplingsampling sites sites named named with with the the prefix prefix of WPWP oror LP.LP.

4.3. Stable Isotope Characteristic in Water

The values of δ18O and δ2H in the Weihe River range from −8.6‰ to −7.8‰ and −64‰ to −51‰, respectively. The values of the Luohe River vary from −8.2‰ to −6.5‰ for δ18O and from −61‰ to −52‰ for δ2H, respectively. The compositions of groundwater range from −11.3‰ to −7.4 for δ18O and −80‰ to 53‰ for δ2H. The δ18O and δ2H values of SW and GW are plots in Figure 6. The global

Water 2020, 12, 1671 10 of 18

4.2.2. Current Hydrochemical Characteristics

+ Na and HCO3− are the predominant ions of the SW, with concentrations ranging from 17.3 to 143.0 mg/L and 118.9 to 251.0 mg/L, respectively. The dominant cations of the GW are Ca2+ in the southeast with concentrations varying from 20.2 to 77.8 mg/L and Na+ in the remaining part with concentrations ranging from 38.8 to 73.9 mg/L. The dominant anion in GW is HCO3−, which varies from 119.0 to 1296.7 mg/L and account 69.3% of the anions on average. In 2015–2016, the TDS values of the SW samples vary from 479.3 (WP2 in June 2016) to 829.1 mg/L (WP6 in September 2016) in the Weihe River and from 871.3 (LP2 in May 2016) to 1194.1 mg/L (LP2 in September 2016) in the Luohe River. WP6 located in the lower reaches of the Weinan City shows higher TDS values than the remaining sites in the Weihe River, which may result from the untreated anthropogenic pollution. The TDS values of the GW samples vary from 159.3 (S4 in September 2016) to 3152.0 mg/L (S20 in June 2016). The TDS values of some GW samples in the southeast (including S3, S4, S6, S7, S8, S14, S15, and S16) are lower than in the remaining part of the research area. Na+ is the predominant cation in the Weihe and Luohe Rivers, with concentrations ranging from 84.9 to 245.4 mg/L. None of the anions show obvious predominance in the Weihe and Luohe Rivers since HCO3−, SO4−, Cl− accounts for average values of 29.5%, 36.0%, and 29.8% of the total anions, respectively. In general, the southeastern GW samples mentioned above have Ca2+ as the + dominant cation and HCO3− as the dominant anion, while the remaining samples of GW have Na as the dominant cation and HCO3− as the dominant anion. The piper plot can be used to show the variation in hydrochemistry of SW and GW sampled in 2015–2016 (Figure5). The SW samples center in Areas 3 and 5, while the GW samples scatter in Areas 1, 3, and 5 with the exception of S5 and S12 located in Area 2. There are some GW samples plotting adjacent to the surface water, while the rest are not, indicating that different patterns of SW–GW interaction exist in the research area. Generally, the water samples in 2015–2016 move towards the apex of Cl + SO4 + NO3 compared to water samples of 1959 in Figure5, which may suggest increased anthropogenic inputs in this region. Both Cl− and NO3− are related to anthropogenic inputs and can be regarded as two indicator ions for human activity. The average concentration of NO3− in SW samples is 5.1 mg/L before the dam operation and 36.2 mg/L in current status, respectively. The average NO3− concentration in GW samples is 6.7 mg/L before the dam operation and 52.1 mg/L in current status, respectively. The average Cl− concentration of in SW samples is 56.7 mg/L before the dam operation and 140.6 mg/L in current status, respectively. The average Cl− concentration of in GW samples is 78.9 mg/L before the dam operation and 85.6 mg/L in current status, respectively. Furthermore, the extra Cl− resulted from the anthropogenic inputs may disturb the SW–GW interaction deduced from the relationship between Cl− values of SW and GW. Therefore, it might be more reliable to use other tracers like stable isotopes to obtain the SW–GW interaction pattern in 2015–2016.

4.3. Stable Isotope Characteristic in Water The values of δ18O and δ2H in the Weihe River range from 8.6% to 7.8% and 64% to 51%, − − − − respectively. The values of the Luohe River vary from 8.2% to 6.5% for δ18O and from 61% − − − to 52% for δ2H, respectively. The compositions of groundwater range from 11.3% to 7.4 for − − − δ18O and 80% to 53% for δ2H. The δ18O and δ2H values of SW and GW are plots in Figure6. − The global meteoric water line (GMWL, δ2H = 8δ18O + 10) [30], and the local meteoric water line (LMWL, δ2H = 7.49δ18O + 6.13, precipitation in the Xi’an Station, IAEA) are also shown in Figure7. The water samples are scattered along the GWML and the LWML, indicating that both the SW and GW most likely come from modern precipitation. Water 2020, 12, x FOR PEER REVIEW 11 of 18 meteoric water line (GMWL, δ2H = 8δ18O + 10) [30], and the local meteoric water line (LMWL, δ2H = 7.49δ18O + 6.13, precipitation in the Xi’an Station, IAEA) are also shown in Figure 7. The water samples are scatteredWater 2020 along, 12, 1671 the GWML and the LWML, indicating that both the SW and GW most11 oflikely 18 come from modern precipitation.

FigureFigure 7. Relation 7. Relation betwee betweenn δ18δ18OO and and δ22H ofof the the SW SW and and GW GW in 2015–2016. in 2015–2016.

The SW samples show a narrow range in Figure7. The Luohe River water samples are more Theenriched SW samples in heavier show isotopes a narrow than the range Weihe in River, Figure probably 7. The resulting Luohe from River the di waterfferent evaporationsamples are more enrichedrate in heavier of these two isotopes rivers. Thethan GW the samples Weihe show River, a broader probably range resulting of stable isotopes from the than different SW. Some evaporation GW rate of thesesamples two are rivers. adjacent The to theGW SW, samples possibly indicatingshow a broader the close range interaction of stable of the SW isotopes and GW. than The averageSW. Some GW samples deuteriumare adjacent excess to of the the WeiheSW, possibly River (5.6% indicating) is close to the the interceptclose interaction of the local of meteoric the SW water and line GW. The (6.13%), so it can be assumed that the evaporation is not obvious. The average deuterium excess of average deuterium excess of the Weihe River (5.6‰) is close to the intercept of the local meteoric the is only 0.1%, which may imply that the evaporation in the Luohe River is significant. water lineAs (6.13 Figure‰6c,d), so shows, it can in be 2016, assumed there are that also the some evaporation river segments is not along obvious which δ. 18TheO or averageδ2H enrich deuterium excess of(deplete) the Luo with River much is higher only (lower)0.1‰, tracerwhich values may in imply the ambient that GW.the Itevaporation suggests these in river the segments Luohe River is significant.are gainingAs Figure reach, 6c e.g.,,d show the segmentss, in 201 LP2-LP16, there inare June, also WP4-WP3 some river in August. segments The remaining along which segments δ18O or δ2H enrich (deplete)that have notwith shown much such higher relationships (lower) may tracer indicate values losing in reaches. the ambient In June, the GW. Huaxian It suggests Station is these in river the river segment WP5-WP3. δ18O enriches from 8.6% (WP5) to 7.8% (WP3) while the average segments are gaining reach, e.g., the segments LP2−-LP1 in June, WP4− -WP3 in August. The remaining δ18O value of the ambient GW (B41 and B282) is 7.8%, indicating the segment is not a gaining reach. − segmentsIn that September, have thenot Huaxian shown Station such isrelationships in the river segment may WP6-WP4.indicate losingδ18O enriches reaches. from In 8.5%June, (WP6) the Huaxian − Station isto in8.1% the river(WP4) segment while the WP5 average-WP3.δ18O δ value18O enriches of the ambient from GW −8.6 (B41‰ and(WP5) B282) to is −78.8%.8‰ ,(WP3) showing while the − − average that δ18O the value segment of is the not ambient a gaining GW reach. (B41 The SW–GWand B282) interaction is −7.8‰, is also indicating consistent with the the segment results is not a gaining deducedreach. In from September, the water level the dataHuaxian in current Station status. is in the river segment WP6-WP4. δ18O enriches 18 from −8.55.‰ Discussion (WP6) to −8.1‰ (WP4) while the average δ O value of the ambient GW (B41 and B282) is −8.8‰, showing that the segment is not a gaining reach. The SW–GW interaction is also consistent with the5.1. results Surface deduced Water and from Groundwater the water Interaction level Variationsdata in current status. The Cl− concentrations of the SW and GW alongside the rivers from two campaigns in May 1959 5. Discussionand August 1959 were selected to obtain the condition of the SW–GW interaction before the dam operation (Figure6a,b). δ18O and δ2H values of surface water and groundwater alongside the rivers from two campaigns in June 2016 and September 2016 were selected to obtain the condition of the 5.1. Surface Water and Groundwater Interaction Variations SW–GW interaction in the current status, as shown in Figure6c,d. The variations of the SW–GW Theinteraction Cl− concentrations along the Weihe of the and SW Luohe and Rivers GW canalongside be seen fromthe rivers Figure 6from. two campaigns in May 1959 and August By1959 comparing were selected the interaction to obtain conditions the before condition the dam of operation the SW and–GW in current interaction status (comparing before the dam May 1959 with June 2016; August 1959 with September 2016), several variations of the SW–GW 18 2 operationinteraction (Figure can6a,b be). found.δ O and Before δ H the values dam operation, of surface the water channels and upstream groundwater W3 are losingalongside reaches, the rivers from twowhereas campaigns the channels in June downstream 2016 and W3 areSeptember gaining reaches. 2016 Inwere current selected status, some to obtain channels the downstream condition of the SW–GWW3 interaction are losing reaches,in the whichcurrent may status, result fromas shown the rising in SWFigure level. 6 Asc,d. indicated The variations by the relationship of the SW–GW interactionbetween along SW the level Weihe and ambient and Luohe GW level Rivers at the can Huaxian be seen Station, from an Figure assumption 6. can be made that the By comparing the interaction conditions before the dam operation and in current status (comparing May 1959 with June 2016; August 1959 with September 2016), several variations of the SW–GW interaction can be found. Before the dam operation, the channels upstream W3 are losing reaches, whereas the channels downstream W3 are gaining reaches. In current status, some channels downstream W3 are losing reaches, which may result from the rising SW level. As indicated by the relationship between SW level and ambient GW level at the Huaxian Station, an assumption can be

Water 2020, 12, x FOR PEER REVIEW 12 of 18 made that the interaction pattern of SW–GW under the predominant impacts of the dam may shift fromWater gain2020ing, 12 reaches, 1671 before the dam operation to losing condition after the dam operation.12 of 18 The shifting direction consistent with the assumption can be found along the reach from near WP5 to WP3interaction and the reach pattern from of SW–GW near WP6 under to theWP5, predominant indicating impacts that the of impact the dam of may Sanm shiftenxia from Dam gaining on the interactionreaches beforeof SW the–GW dam can operation affect toas losing far as condition to WP6. after The the interaction dam operation. pattern The shifting shifting direction from losing conditionconsistent to gaining with the condition assumption along can the be foundreach from along WP8 the reach to WP6 from in near August WP5– toSeptember WP3 and and the reachthe reach fromfrom LP2 nearto LP1 WP6 in toMay WP5,–June indicating may result that the from impact the obvious of Sanmenxia decline Dam of onrunoff the interaction in the Weihe of SW–GW and Luohe Riverscan with affect the as farminor as to influence WP6. The interactionof the Sanmenxia pattern shifting Dam. fromIn the losing current condition status, to gainingthe reach condition WP2-WP1 nearestalong the the Sanmenxia reach from Dam WP8 is to a WP6 losing in August–Septemberreach in two campaigns, and the indicating reach from LP2the reach to LP1 is in under May–June stronger influencemay result of the from dam the than obvious other decline river ofsegments. runoff in the Weihe and Luohe Rivers with the minor influence of the Sanmenxia Dam. In the current status, the reach WP2-WP1 nearest the Sanmenxia Dam is a 5.2. Anthropogeniclosing reach in twoSources campaigns, and Impacts indicating on Surface the reach Water is under and Groundwater stronger influence of the dam than other river segments. Human activity is one important factor influencing water quality. The general increase of the Cl− 5.2. Anthropogenic Sources and Impacts on Surface Water and Groundwater and NO3− ions may result from the rapid growth of the population and the fertilizer consumption in this area Humanfrom 1959 activity to 2020 is one [44,45] important. The factorpopulation influencing and the water fertilizer quality. consumption The general increase increase of the from Cl− 158.4 to 325.9and NOmillion3− ions tons may and result from from 0.1 the to rapid 12.4 growthmillion of tons, the population respectively and (shown the fertilizer in Figure consumption 8). There in are servalthis kinds area from of anthropogenic 1959 to 2020 [44 ,45 inputs]. The including population agricultural and the fertilizer activities, consumption domestic increase wastewater, from 158.4 and untreatedto 325.9 industrial million tons or and urban from sewage 0.1 to 12.4 that million may tons, affect respectively the SW and (shown GW. in FigureThe threshold8). There arevalues serval of Cl− kinds of anthropogenic inputs including agricultural activities, domestic wastewater, and untreated and NO3− that can be used to distinguish whether water samples are potentially affected by industrial or urban sewage that may affect the SW and GW. The threshold values of Cl and NO that anthropogenic inputs can be estimated by cumulative probability plots [46,47] (Figure− 9). By3− referring can be used to distinguish whether water samples are potentially affected by anthropogenic inputs can − − − − to thebe national estimated standard by cumulative of Cl probability (250 mg/L) plots and [46 NO,473] (Figure(10 mg/L),9). By the referring background to the national levels standardof Cl and of NO3 (shown in Figure 10) are determined as 203.6 and 24.5 mg/L, respectively. Based on the background Cl− (250 mg/L) and NO3− (10 mg/L), the background levels of Cl− and NO3− (shown in Figure 10) are levels,determined four water as 203.6types and are 24.5 identified mg/L, respectively. among the Based water on samples the background taken from levels, sampling four water sites types shown are in Figureidentified 1a for amongthe research the water area. samples A detai takenled from water sampling type sitesclassification shown in Figure is provided1a for the as research Figure area. 10a, the spatialA detailed distribution water of type the classification dominant isanthropogenic provided as Figure input 10 a,types the spatialfor each distribution sampling of site the dominantare shown in Figureanthropogenic 10b,c. The percentages input types for of eacheach sampling water type site in are different shown in water Figure bodies 10b,c. Theand percentages periods are of estim each ated and watershown type in Table in diff erent3. water bodies and periods are estimated and shown in Table3.

FigureFigure 8. Variations 8. Variations of ofpopulation population and and fertilizer fertilizer consumption in in the the study study area area from from 1959 1959 to 2016. to 2016.

Water 2020, 12, x FOR PEER REVIEW 13 of 18

Water 2020, 12, 1671 13 of 18 Water 2020, 12, x FOR PEER REVIEW 13 of 18

Figure 9. Plots of cumulative probability to determining the threshold values of (a) NO3− and (b) Cl−.

Table 3. Results of water type classification.

Percentage of Different Water Types Type Relative Abundance Period SW GW

A Low Cl−–low NO3− Pre 1 100.0% 78.2% B Low Cl−–High NO3− Pre 0.0% 12.7% C High Cl−–low NO3− Pre 0.0% 7.3% D High Cl−–High NO3− Pre 0.0% 1.8%

A Low Cl−–low NO3− Post 2 13.6% 43.9% B Low Cl−–high NO3− Post 72.7% 34.1% − − C High Cl –low NO3 Post 0.0% 19.5% D High Cl−–high NO3− Post 13.6% 2.4% FigureFigure 9. Plots 9. Plots of cumulative of cumulative probability probability to determining the the threshold threshold values values of (a of) NO (a) NOand3− (andb) Cl (b.) Cl−. 1 Pre means before operation, 2 Post means current status. 3− −

Table 3. Results of water type classification.

Percentage of Different Water Types Type Relative Abundance Period SW GW

A Low Cl−–low NO3− Pre 1 100.0% 78.2% B Low Cl−–High NO3− Pre 0.0% 12.7% C High Cl−–low NO3− Pre 0.0% 7.3% D High Cl−–High NO3− Pre 0.0% 1.8%

A Low Cl−–low NO3− Post 2 13.6% 43.9% B Low Cl−–high NO3− Post 72.7% 34.1% C High Cl−–low NO3− Post 0.0% 19.5% − − D High Cl –high NO3 Post 13.6% 2.4% 1 Pre means before operation, 2 Post means current status. Figure 10. (a) Bivariate plot of Cl− vs. NO3− for distinguishing water types (points below 1 mg/L are Figure 10. (a) Bivariate plot of Cl− vs. NO3− for distinguishing water types (points below 1 mg/L are not notshown); shown); dominant dominant water water types types in each in each sampling sampling site: (site:b) before (b) before the dam the operation,dam operation, (c) present (c) present status. status. Table 3. Results of water type classification.

All the SW samples in 1959 are below the threshold values of Cl− and NO3− (Type A area) that Percentage of Different Water Types can be identifiedType as noRelative obvious Abundance anthropogenic Period input. 72.7% of the SW samples in 2015–2016 are in Type B area. Since there is little application of chemical fertilizerSW in 1959, while GWchemical nitrogen 1 fertilizer has Abeen excessively Low Cl−–low used NO in 3China− nowadays.Pre Moreover,100.0% the SW samples 78.2% in September 2016 B Low Cl –High NO Pre 0.0% 12.7% have higher concentrations− of NO3− than3− the samples in June 2016, showing the precipitation or C High Cl−–low NO3− Pre 0.0% 7.3% irrigation during June to September has a positive influence on the concentrations of NO3− (e.g., the D High Cl−–High NO3− Pre 0.0% 1.8% NO3− of WP2 is 28.2 mg/L in June and 40.8 mg/L in2 September). Therefore, the increased NO3− in SW A Low Cl−–low NO3− Post 13.6% 43.9% B Low Cl−–high NO3− Post 72.7% 34.1% C High Cl−–low NO3− Post 0.0% 19.5% D High Cl−–high NO3− Post 13.6% 2.4% 1 Pre means before operation, 2 Post means current status.

All the SW samples in 1959 are below the threshold values of Cl− and NO3− (Type A area) that can be identified as no obvious anthropogenic input. 72.7% of the SW samples in 2015–2016 are in Type B Figure 10. (a) Bivariate plot of Cl− vs. NO3− for distinguishing water types (points below 1 mg/L are area. Since there is little application of chemical fertilizer in 1959, while chemical nitrogen fertilizer has not shown); dominant water types in each sampling site: (b) before the dam operation, (c) present been excessively used in China nowadays. Moreover, the SW samples in September 2016 have higher status. concentrations of NO3− than the samples in June 2016, showing the precipitation or irrigation during June to September has a positive influence on the concentrations of NO3− (e.g., the NO3− of WP2 is All the SW samples in 1959 are below the threshold values of Cl− and NO3− (Type A area) that can be identified as no obvious anthropogenic input. 72.7% of the SW samples in 2015–2016 are in Type B area. Since there is little application of chemical fertilizer in 1959, while chemical nitrogen fertilizer has been excessively used in China nowadays. Moreover, the SW samples in September 2016 have higher concentrations of NO3− than the samples in June 2016, showing the precipitation or irrigation during June to September has a positive influence on the concentrations of NO3− (e.g., the NO3− of WP2 is 28.2 mg/L in June and 40.8 mg/L in September). Therefore, the increased NO3− in SW

Water 2020, 12, 1671 14 of 18

28.2 mg/L in June and 40.8 mg/L in September). Therefore, the increased NO3− in SW may result from the polluted surface runoff flow through the agricultural areas [19]. A total of 12.7% of GW samples in 1959 are in Type B area. These GW samples are only distributed along the Luohe River and have not shown higher NO3− in August 1959 than that in May 1959, indicating that they are more likely affected by domestic sewage, which could have a minor relationship with precipitation or irrigation. A total of 34.1% of groundwater samples in 2015–2016 are in Type B area. The water samples BP5 and BP12 (Figure 10c), classified as Type B, have much greater NO3− (average value 224.5 mg/L) than that in the rest of the groundwater samples in Type B area (average value 49.9 mg/L). Since most of the cropland is in the northern Weihe River area, the agricultural activities may be responsible for the higher NO3− in BP5 and BP12. A well-established canal irrigation system is located in the northern Weihe River area and the main irrigation source is the river water already characterized as high NO3−. The irrigation water with high NO3− and the return flow carrying nitrate from agricultural fertilizer together make S5 and BP12 heavily concentrate NO3−. Most of the population gathers in the southern Weihe river area, so that BP9 and BP10 are more likely affected by domestic sewage. The GW samples of BP2, BP11, and BP17 are in Type C (Figure 10c) characterized as high Cl− and low NO3−. Anthropogenic sources of Cl− such as fertilizers, wastewater, sewage, and manure can lead to higher NO3− values in GW. Since BP2, BP11, BP17 have little spatial connection and other samples near these sites are in Type B or Type A both having relatively low Cl− concentrations, it is improbable that BP2, BP11, BP17 are obviously under the impact of saline water. These sites are in rural and relatively far from cities and counties. Therefore, there may be unregulated industrial waste discharge in BP2, BP11, and BP17 which is not rare in the rural areas of China [48]. There are no SW samples in Type C area, indicating no untreated industrial sewage directly draining into the Weihe and Luohe Rivers. The different anthropogenic inputs into one part of the SW and GW may impact the other part through the SW–GW interaction. The industrial input in BP17 increases Cl− in the Weihe River from WP6 to WP5 by the SW–GW interaction of GW recharging surface water in June 2016. The agricultural input from upstream area in WP1 may increase NO3− in BP2 by the SW–GW interaction of surface water recharging groundwater since the NO3− in BP2 has an upward trend in three campaigns from 2015 to 2016.

5.3. Conceptual Model and Environmental Implications Previous studies have not paid much attention to the SW–GW interaction under the impact of the Sanmenxia Dam. However, the SW–GW interaction has changed since the Sanmenxia Dam operation. A conceptual model of the SW–GW interaction at a representative section (the Huaxian Station) is presented as Figure 11. In order to give some environmental implications, several components like unregulated rural industrial input and domestic input that are not found around the Huaxian Station at current status but appear in the whole research area are also integrated into this model. Thus, this model helps to draw a more comprehensive picture of the SW–GW interaction and the potential aquatic environment problems. The uplifted riverbed caused by the Sanmenxia Dam makes the river water level higher in the current status and eventually induces the variation of SW–GW interaction. Anthropogenic sources like industrial wastewater, domestic sewage, irrigation return flow, and surface runoff both affected by agricultural activities are also influencing the water quality. The SW and GW are not two isolated parts but an interconnected system. The pollutants discharging into SW may migrate to GW, of which the inverse process can also happen in the lower Weihe River Basin, through the SW–GW interactions. Since the dam has an obvious impact on the interaction, it is essential to take the dam operation into account when coping with the serious water environment in this area. Water 2020, 12, 1671 15 of 18 Water 2020, 12, x FOR PEER REVIEW 15 of 18

Figure 11. Conceptual diagram of the SW–GWSW–GW interaction integrated with potential anthropogenic inputs: ( (a)) before before the dam operation, ( b) at current status.

6. Conclusions The Sanmenxia Dam has dramatically increased the water level in the lower Weihe River since 1959. The The SW SW level level rise rise has has inevitably inevitably affected affected the SW the– SW–GWGW interaction interaction that plays that playsa vital arole vital in hydro role in- environment.hydro-environment. Meanwhile, Meanwhile, the lower the lower Weihe Weihe River River area area is is being being faced faced with with hydrohydro-environment-environment pressures. Therefore, it is crucial to assess the impact of the dam on the SW SW–GW–GW interaction. The main conclusions of the study are as follows: (1) AtAt the the Huaxian Huaxian Station, Station, the the dam ope operationration plays a key role in raising the SWSW level.level. After the 1980s,1980s, the the GW GW level level decreased decreased because because of of the the increased increased groundwater groundwater exploitation. The variations ofof SW SW and and GW levels induced the shift of SW–GWSW–GW interaction. Three different different patterns of the SWSW–GW–GW int interactioneraction can can be be identified identified in the past 60 years including (i) gaining reach during the earlyearly stage stage (i.e. (i.e.,, in in 1959), 1959), ( (ii)ii) gaining gaining reach reach in in non non-flood-flood season and losing reach in flood flood season (i.e.(i.e.,, in in 1981), 1981), and and ( (iii)iii) losing losing reach reach in 2002 and 2010. (2) DetailedDetailed SW SW–GW–GW interaction interaction patterns patterns along along the the lower lower Weihe Weihe River are first first examined from the 18 2 multimulti-environmental-environmental tracers (Cl−−,, δδ18O,O, and and δδ2HH)) of of the the water water samples. samples. Before Before the the dam dam operation, operation, thethe channels channels upstream upstream W3 W3 are are losing losing reaches, while downstream W3 are gaining reaches. In the currentcurrent status, status, the the distribution distribution of of SW SW–GW–GW interaction interaction along along the the Weihe Weihe River River is is more more complex. complex. SomeSome channels channels downstream downstream W3 W3 are are losing losing reaches, reaches, which which may may result result from the rising SW level inducedinduced by by the the ddamam operation. Gaining Gaining reaches reaches also also appeared upstream W3, indicating the impactimpact of of the the dam dam lessens lessens as the distance increase. The The impact impact of of the the dam dam on on the the SW SW–GW–GW interactioninteraction can can reach reach to to W3 W3 (65 (65 km km from from the the estuary estuary of the the Weihe River). − − (3) InIn general, general, the hydro-environmenthydro-environment deteriorates in in 2015–2016 2015–2016 especially especially for for the the NO NO3−3 andand Cl Cl− concentrationsconcentrations as as the the population population and and fertilizer fertilizer consumption consumption escalated escalated during during the the last last 60 60 years. years. FourFour water water types types can can be be distinguished distinguished in in the the lower Weihe River Basin. No SW samples showed oobviousbvious anthropogenic anthropogenic input input i inn 1959, 1959, but, but, in in 2015 2015–2016,–2016, 72.7 72.7%% of SW samples (mean nitrate concentration of 34.7 mg/L) were affected by agricultural input. A total of 78.2% of the GW samples in 1959 show no obvious anthropogenic input, while 34.1% of GW samples (mean

Water 2020, 12, 1671 16 of 18

concentration of 34.7 mg/L) were affected by agricultural input. A total of 78.2% of the GW samples in 1959 show no obvious anthropogenic input, while 34.1% of GW samples (mean nitrate concentration of 124.7 mg/L) in 2015–2016 are affected by agricultural or domestic inputs. GW sampling sites of BP2, BP11, and BP17 (mean Cl− concentration of 372.2 mg/L) might be affected by industrial input in the rural area. (4) Evidence has also shown that different SW–GW interaction patterns may produce different influences on the water system. The impacts of the dam which change the SW–GW interaction patterns and make the water system more variable present a challenge to water resource management in this area. Further research may focus on how the different SW–GW interaction patterns affect the pollutant migration and make a suitable operation mode of the dam to improve the local water resources management.

Supplementary Materials: The following are available online at http://www.mdpi.com/2073-4441/12/6/1671/s1, Table S1: Major ions and stable isotope concentrations in surface water and groundwater in 1959, Table S2: Major ions and stable isotope concentrations in surface water and groundwater in 2015–2016. Author Contributions: Data curation, D.Z.; Formal analysis, D.Z.; Methodology, D.Z.; Supervision, D.H. and X.S.; Visualization, D.Z.; Writing—original draft, D.Z.; Writing—review and editing, D.H. and X.S. All authors have read and agreed to the published version of the manuscript. Funding: This work is funded by Chinese Academy of Sciences (KJZD-EW-TZ-G10). Conflicts of Interest: The authors declare no conflict of interest.

References

1. Sophocleous, M. Interactions between groundwater and surface water: The state of the science. Hydrogeol. J. 2002, 10, 52–67. [CrossRef] 2. Winter, T.C. Ground Water and Surface Water: A Single Resource; DIANE Publishing Inc.: Darby, PA, USA, 1998; Volume 1139. 3. Essaid, H.I.; Caldwell, R.R. Evaluating the impact of irrigation on surface water—Groundwater interaction and stream temperature in an agricultural watershed. Sci. Total Environ. 2017, 599–600, 581–596. [CrossRef] 4. Fernald, A.G.; Guldan, S.J. Surface Water–Groundwater Interactions Between Irrigation Ditches, Alluvial Aquifers, and Streams. Rev. Fish. Sci. 2007, 14, 79–89. [CrossRef] 5. Dun, Y.; Tang, C.; Shen, Y. Identifying interactions between river water and groundwater in the Plain using multiple tracers. Environ. Earth Sci. 2013, 72, 99–110. [CrossRef] 6. Jolly, I.D.; McEwan, K.L.; Holland, K.L. A review of groundwater-surface water interactions in arid/semi-arid wetlands and the consequences of salinity for wetland ecology. Ecohydrology 2008, 1, 43–58. [CrossRef] 7. Woessner, W.W. Stream and fluvial plain ground water interactions: Rescaling hydrogeologic thought. Groundwater 2000, 38, 423–429. [CrossRef] 8. Epting, J.; Huggenberger, P.; Radny, D.; Hammes, F.; Hollender, J.; Page, R.M.; Weber, S.; Banninger, D.; Auckenthaler, A. Spatiotemporal scales of river-groundwater interaction—The role of local interaction processes and regional groundwater regimes. Sci. Total Environ. 2018, 618, 1224–1243. [CrossRef] 9. Graf, W.L. Dam nation: A geographic census of American dams and their large-scale hydrologic impacts. Water Resour. Res. 1999, 35, 1305–1311. [CrossRef] 10. Lu, X.X.; Siew, R.Y. Water discharge and sediment flux changes over the past decades in the Lower River: Possible impacts of the Chinese dams. Hydrol. Earth Syst. Sci. 2006, 10, 181–195. [CrossRef] 11. Kondolf, G.M.; Rubin, Z.K.; Minear, J.T. Dams on the Mekong: Cumulative sediment starvation. Water Resour. Res. 2014, 50, 5158–5169. [CrossRef] 12. New, T.; Xie, Z.J.B. Impacts of large dams on riparian vegetation: Applying global experience to the case of China’s Three Gorges Dam. Biodivers Conserv 2008, 17, 3149–3163. [CrossRef] 13. 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.[CrossRef] 14. Arntzen, E.V.; Geist, D.R.; Dresel, P.E. Effects of fluctuating river flow on groundwater/surface water mixing in the hyporheic zone of a regulated, large cobble bed river. River Rese. Appl. 2006, 22, 937–946. [CrossRef] Water 2020, 12, 1671 17 of 18

15. Gu, B.; Ge, Y.; Chang, S.X.; Luo, W.; Chang, J. Nitrate in groundwater of China: Sources and driving forces. Glob. Environ. Chang. 2013, 23, 1112–1121. [CrossRef] 16. Yadav, R.K.; Goyal, B.; Sharma, R.K.; Dubey, S.K.; Minhas, P.S. Post-irrigation impact of domestic sewage effluent on composition of , crops and ground water—A case study. Environ. Int. 2002, 28, 481–486. [CrossRef] 17. Sun, B.; Zhang, L.; Yang, L.; Zhang, F.; Norse, D.; Zhu, Z. Agricultural Non-Point Source Pollution in China: Causes and Mitigation Measures. AMBIO 2012, 41, 370–379. [CrossRef][PubMed] 18. Leschik, S.; Musolff, A.; Krieg, R.; Martienssen, M.; Bayer-Raich, M.; Reinstorf, F.; Strauch, G.; Schirmer, M. Application of integral pumping tests to investigate the influence of a losing stream on groundwater quality. Hydrol. Earth Syst. Sci. 2009, 13, 1765–1774. [CrossRef] 19. Teng, Y.; Hu, B.; Zheng, J.; Wang, J.; Zhai, Y.; Zhu, C. Water quality responses to the interaction between surface water and groundwater along the , NE China. Hydrogeol. J. 2018, 26, 1591–1607. [CrossRef] 20. Weng, H.; Chen, X. Impact of polluted canal water on adjacent and groundwater systems. Environ. Geol. 2000, 39, 945–950. [CrossRef] 21. Squillace, P.J.; Thurman, E.M.; Furlong, E.T. Groundwater as a nonpoint source of atrazine and deethylatrazine in a river during base flow conditions. Water Resour. Res. 1993, 29, 1719–1729. [CrossRef] 22. Wang, G.; , B.; Wang, Z.-Y. Sedimentation problems and management strategies of Sanmenxia Reservoir, Yellow River, China. Water Resour. Res. 2005, 41.[CrossRef] 23. Wang, Z.Y.; Wu, B.; Wang, G. Fluvial processes and morphological response in the Yellow and Weihe Rivers to closure and operation of Sanmenxia Dam. Geomorphology 2007, 91, 65–79. [CrossRef] 24. Li, J.; Li, H.; Shen, B.; Li, Y. Effect of non-point source pollution on water quality of the Weihe River. Int. J. Sediment Res. 2011, 26, 50–61. [CrossRef] 25. Zhang, Z.M.; Wang, X.Y.; Zhang, Y.; Nan, Z.; Shen, B.G. The Over Polluted Water Quality Assessment of Weihe River Based on Kernel Density Estimation. Proced. Environ. Sci. 2012, 13, 1271–1282. [CrossRef] 26. Oh, Y.-Y.; Hamm, S.-Y.; Yoon, H.; Kim, G.-B. Analytical and statistical approach for evaluating the effects of a river barrage on river-aquifer interactions. Hydrol. Process. 2016, 30, 3932–3948. [CrossRef] 27. Kalbus, E.; Reinstorf, F.; Schirmer, M. Measuring methods for groundwater? surface water interactions: A review. Hydrol. Earth Syst. Sci. Discuss. 2006, 10, 873–887. [CrossRef] 28. 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. [CrossRef] 29. de Brito Neto, R.T.; Santos, C.A.G.; Mulligan, K.; Barbato, L. Spatial and temporal water-level variations in the Texas portion of the Ogallala Aquifer. Nat. Hazards 2016, 80, 351–365. [CrossRef] 30. Han, Q.; Zhang, S.; Huang, G.; Zhang, R. Analysis of Long-Term Water Level Variation in Dongting Lake, China. Water 2016, 8, 306. [CrossRef] 31. Oyarzún, R.; Jofré, E.; Morales, P.; Maturana, H.; Oyarzún, J.; Kretschmer, N.; Aguirre, E.; Gallardo, P.; Toro, L.E.; Muñoz, J.F.; et al. A hydrogeochemistry and isotopic approach for the assessment of surface water–groundwater dynamics in an arid basin: The Limarí watershed, North-Central Chile. Environ. Earth Sci. 2014, 73, 39–55. [CrossRef] 32. Yang, L.; Song, X.; Zhang, Y.; Han, D.; Zhang, B.; Long, D. Characterizing interactions between surface water and groundwater in the Jialu River basin using major ion chemistry and stable isotopes. Hydrol. Earth Syst. Sci. 2012, 16, 4265–4277. [CrossRef] 33. Menció, A.; Mas-Pla, J. Assessment by multivariate analysis of groundwater–surface water interactions in urbanized Mediterranean streams. J. Hydrol. 2008, 352, 355–366. [CrossRef] 34. Négrel, P.; Petelet-Giraud, E.; Barbier, J.; Gautier, E. Surface water–groundwater interactions in an alluvial plain: Chemical and isotopic systematics. J. Hydrol. 2003, 277, 248–267. [CrossRef] 35. Zhu, M.; Wang, S.; Kong, X.; Zheng, W.; Feng, W.; Zhang, X.; Yuan, R.; Song, X.; Sprenger, M. Interaction of Surface Water and Groundwater Influenced by Groundwater Over-Extraction, Waste Water Discharge and Water Transfer in Xiong’an New Area, China. Water 2019, 11, 539. [CrossRef] 36. National Earth System Science Data Center, National Science & Technology Infrastructure of China. Available online: http://www.geodata.cn (accessed on 8 February 2020). Water 2020, 12, 1671 18 of 18

37. Huh, Y.; Tsoi, M.-Y.; Zaitsev, A.; Edmond, J.M. The fluvial geochemistry of the rivers of Eastern : I. tributaries of the River draining the sedimentary platform of the Siberian Craton. Geochim. Cosmochim. Acta 1998, 62, 1657–1676. [CrossRef] 38. Edmond, J.M.; Palmer, M.R.; Measures, C.I.; Grant, B.; Stallard, R.F. The fluvial geochemistry and denudation rate of the Guayana Shield in Venezuela, Colombia, and Brazil. Geochim. Cosmochim. Acta 1995, 59, 3301–3325. [CrossRef] 39. Mann, H.B. Nonparametric test against trend. Econometrica 1945, 13, 245–259. [CrossRef] 40. Zhang, Q.; Li, J.; David Chen, Y.; Chen, X. Observed changes of temperature extremes during 1960–2005 in China: Natural or human-induced variations? Theor. Appl. Climatol. 2011, 106, 417–431. [CrossRef] 41. Zhang, G. Mechanism of Riverbed Aggradation at Tongguan Reach and Channel Shrinkage at Lower Weihe River. Master’s Dissertation, Xi’an University of Technology, Xi’an, China, 2002. 42. Han, D.; Song, X.; Currell, M.J.; Cao, G.; Zhang, Y.; Kang, Y. A survey of groundwater levels and hydrogeochemistry in irrigated fields in the Karamay Agricultural Development Area, : Implications for soil and groundwater salinity resulting from surface water transfer for irrigation. J. Hydrol. 2011, 405, 217–234. [CrossRef] 43. Solomon, D.K.; Cook, P.G. Environmental Tracers in Subsurface Hydrology; Springer: New York, NY, USA, 2000. 44. Scanlon, B.R.; Jolly, I.; Sophocleous, M.; Zhang, L. Global impacts of conversions from natural to agricultural ecosystems on water resources: Quantity versus quality. Water Resour. Res. 2007, 43.[CrossRef] 45. Ramakrishnaiah, C.R.; Sadashivaiah, C.; Ranganna, G. Assessment of Water Quality Index for the Groundwater in Tumkur Taluk, Karnataka State, India. E-J. Chem. 2009, 6, 757424. [CrossRef] 46. Kumar, P.S. Evolution of groundwater chemistry in and around Vaniyambadi industrial area: Differentiating the natural and anthropogenic sources of contamination. Chem. Erde-Geochem. 2014, 74, 641–651. [CrossRef] 47. Park, S.-C.; Yun, S.-T.; Chae, G.-T.; Yoo, I.-S.; Shin, K.-S.; Heo, C.-H.; Lee, S.-K.J.J.O.H. Regional hydrochemical study on salinization of coastal aquifers, western coastal area of South Korea. J. Hydrol. 2005, 313, 182–194. [CrossRef] 48. Wang, M.; Webber, M.; Finlayson, B.; Barnett, J. Rural industries and water pollution in China. J. Environ. Manag. 2008, 86, 648–659. [CrossRef][PubMed]

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