Abstract

Oxygen (δ18O) and hydrogen (δD) stable isotopes in the surface waters of the Huai River basin were analyzed in this study. Results indicated the northern waters had higher δ18O and δD than the southern waters, the water δ18O and δD increased along the water flow directions. These variations mostly resulted from the spatial differences of precipitation and evaporation. Comparing with published different continents' river water δ18O data, this study suggests that evaporation effect is a more plausible interpretation than altitude effect as the cause of δ18O increasing from upriver to downriver waters. This region's local surface water line (LSWL, δD = 5.36δ18O − 18.39; r2 = 0.84) represents one of the first presented LSWLs in eastern China. The correlation between d-excess and δ18O demonstrates this region is dominated by the Pacific oceanic moisture masses in summer. Comparing the various LSWLs from eastern China and eastern United States river waters, this study proposes a hypothesis that the water LSWLs slopes of lower latitude regions may be less than those of higher latitude regions within similar topographic areas. This hypothesis may be tested in other geographically comparable coupled areas in the world if corresponding large-scale data can be found.

INTRODUCTION

The analysis of oxygen (δ18O) and hydrogen (δD) stable isotopic composition of water may help improve our understanding of hydrological processes such as precipitation, groundwater recharge, basin water hydrology, and evolution of surface waters undergoing evaporation (Gammons et al. 2006; Ahmad et al. 2012; Katsuyama et al. 2015; Darling & Bowes 2016). This has become an effective method for investigating the hydrologic system on a range of spatial and temporal scales. Basin-wide river waters could provide more convincing information about regional precipitation than that of recent precipitation at a single location in certain areas (Kendall & Coplen 2001). A number of stable isotopic (oxygen and hydrogen) studies have been done in many large river water systems around the world (Simpson & Herczeg 1991; Kendall & Coplen 2001; Dalai et al. 2002; Gammons et al. 2006; Ahmad et al. 2012), and these studies demonstrated that δ18O and δD were useful tracers for regional hydrological studies.

Previous studies have addressed the variation of δ18O and δD in regional surface waters and have suggested they are affected by seasonal precipitation (Dutton et al. 2005; Ahmad et al. 2012; Katsuyama et al. 2015), irrigation or evaporation (Simpson & Herczeg 1991; Ahmad et al. 2012; Darling & Bowes 2016), and latitude or elevation (Dutton et al. 2005; Timsic & Patterson 2014; Katsuyama et al. 2015). However, large-scale (e.g., basin wide) surface water δ18O and δD studies, such as US country-wide rivers (Kendall & Coplen 2001; Dutton et al. 2005), are still limited in the East Asian continent.

The Huai River basin is one of the five largest basins in China and is situated between the Yellow River and the Yangtze River, the two largest rivers in China. The whole Huai River basin (30°55′–36°36′N, and 111°55′–121°25′E) covers five provinces (Hubei, Henan, Anhui, Shandong, and Jiangsu) of China, and has a total drainage area of 270,000 km2 (Figure 1). This basin is an important socio-economic region in China and has been examined in many studies (Wang & Ongley 2004; Ge et al. 2006; Tan et al. 2009; Li et al. 2010a). However, the water δ18O and δD studies in this region are very limited and mostly focused on small areas or few sites. For example, Tan et al. (2009) reported δ18O and δD data for a one-time precipitation event in October 2007 in Wudaogou (nearby to site 7 in this study) of this region, a hydrological experimental catchment (drainage area = 1.36 km2). They indicated that the groundwater of that area mostly recharged from surface water infiltration and less so from deep groundwater. Li et al. (2010a) reported that δ18O values in the main channel of the Huai River (site 2 in our study) were more enriched than that of groundwater from either side of the main channel in both the wet and dry seasons, and revealed that the Huai River main channel recharges its two sides groundwater.

Figure 1

Sampling sites and the water δ18O and δD values at each site in the Huai River basin and the East Line of SNWTP. The upper-left plot shows the location of the Huai River basin in China. The black numbers in the figure present the site number, and the numbers inside the brackets present the δ18O/δD values at each site.

Figure 1

Sampling sites and the water δ18O and δD values at each site in the Huai River basin and the East Line of SNWTP. The upper-left plot shows the location of the Huai River basin in China. The black numbers in the figure present the site number, and the numbers inside the brackets present the δ18O/δD values at each site.

In this study, we analyze the isotopic (δ18O and δD) composition of large-scale surface water samples in the Huai River basin, which includes eight rivers, two large lakes, and one long artificial canal (East Line of the South-North Water Transfer Project (SNWTP)) in the Huai River basin, Eastern China. Our objectives are: (1) to identify the spatial water δ18O and δD characteristics in this region; (2) to discuss the causes that lead to spatial variations in isotope values of this region and, if possible, to identify the most important factor contributing to these variations; (3) to incorporate findings from studies of δ18O and δD values taken from the Yangtze River and Yellow River basin and to explore, at a large scale, surface water δ18O and δD variations over these three river basins in China; (4) to compare local surface water lines (LSWLs) (using δ18O and δD values) of the rivers in eastern China and the eastern United States, to explore at a larger scale (two continents) a view of surface water isotopes.

STUDY AREA AND METHODS

Study area

The terrain of the Huai River basin is generally mountainous to the west and increasingly flat to the east. The landforms of this region consist of 13% mountainous areas, 19% small hills, 52% plains, and 16% swales (lakes) (Ge et al. 2006). In this region, the Hongze Lake (area ∼1,577 km2), Nansi Lake (∼1,097 km2), and Gaoyou Lake (∼675 km2, no samples in this study) are three large open lakes in this region (Figure 1) and their water areas can be large in the rainy season and shrink in the dry season. The average water residence times of the three lakes are 35 days (Hongze Lake), 226 days (Nansi Lake), and 21 days (Gaoyou Lake), respectively. These can be shorter in the rainy season and longer in the dry season (Wang & Dou 1998). The annual mean discharge of water from the Huai River basin is 62 km3 and is similar to the mean discharge of the Yellow River (66 km3/per year). The mean annual precipitation and the evaporation of this region are 920 mm and 1,200 mm, respectively, and vary from site to site. Generally, the annual great precipitation and evaporation in this region happen between June and August (Figure 2).

Figure 2

Monthly evaporation and precipitation differences (ten-year average values for 1996–2005) between northern and southern areas in the Huai River basin (data was obtained from Anhui Province Meteorological Data Sharing Service Database, http://www.ahqh.org.cn). Site Shouxian is very close to site 5 on the Huai River main channel (see Table 1 and Figure 1); Huoshan and Lu'an are very close to site 19 and 20, respectively, on the Pi River.

Figure 2

Monthly evaporation and precipitation differences (ten-year average values for 1996–2005) between northern and southern areas in the Huai River basin (data was obtained from Anhui Province Meteorological Data Sharing Service Database, http://www.ahqh.org.cn). Site Shouxian is very close to site 5 on the Huai River main channel (see Table 1 and Figure 1); Huoshan and Lu'an are very close to site 19 and 20, respectively, on the Pi River.

The East Line of the SNWTP, which is a strategically significant project to supply water to north China, involves the Nansi Lake as its water channel and the waters in Nansi Lake are separated into several sections by sluices (Li et al. 2013). The East Line of the SNWTP (hereafter SNWTP) is constructed at the base of the Jing-Hang Grand Canal. There is about a 650 km part of the SNWTP inside the Huai River basin (from site 43 to site 34), but the SNWTP has no hydraulic connections with Hongze Lake and Gaoyou Lake. There is another man-made canal (Subei Canal) between the Hongze Lake and the Yellow Sea. The Subei Canal is mainly used to irrigate farms and the water is mostly pumped from Hongze Lake. The Subei Canal also discharges the flood waters from Hongze Lake to the Yellow Sea in heavily rainy days. There are several sluices built at the intersection of the SNWTP and the Subei Canal, but no merging of the waters between the SNWTP and the Subei Canal. In the 1970s, the southern section sluices were constructed to pump the Yangtze River water from site 34 to 37 (site 34 is 1 meter more elevated than site 37, Huai'an) for seasonal irrigation purposes. However, the northern section sluices (for the purposes of water transfer to north China) were not started until 2009 (Li et al. 2013). In our sampling period in 2008, the water flow directions in the SNWTP are ‘North to South’ in the northern section (from site 43 to site 38) and ‘South to North’ in the southern section (from site 37 to site 34).

Methods

Annual precipitation in the Huai River basin is distinct between the south and north areas, and precipitation is more abundant during the summer season. Because many dams and sluices have been constructed in this region, in the rainy season (June to September, Figure 2) most tributaries are in flowing condition, whereas during the other seasons some sections have little flowing water. Thus, we chose the rainy season for our sampling period in this region. Samples were collected from 52 sites of the Huai River basin in July 2008 (Figure 1 and Table 1). All sampling sites (except sites located on the two southern tributaries, Shi River and Pi River) are located on the plains or swales in this region, according to previous reports (Ge et al. 2006). In the Huai River basin, the river leakage recharges groundwater in the rainy season (June to September), whereas the groundwater may only charge the surface water in some mountainous areas (Hu et al. 2009). However, Hongze Lake discharges to ambient groundwater throughout the year due to lake water levels being higher than the surrounding land areas (Wang & Chen 1999). In this study, all the water sampling sites are situated in the plains or lakes, and the water quantities may cover more than 95% of the discharge in this region.

Table 1

Sampling information, δ18O and δD compositions, Cl and SO4 concentrations of the surface waters in the Huai River basin

Water system Type  Sampling site Date Precipitation (mm) T (°C) δ18O (‰) δD (‰) d (‰) Cl (mg/L)L) SO4 (mg/L)L) 
Huai River main channel (HRMC) Main Minggang 12-Jul 5.5 28.9 −7.5 −57.9 2.5 35.5 24.5 
Channel Xixian 12-Jul 5.5 28.6 −7.4 −57.7 1.3 20.1 24.5 
 Huaibin 12-Jul 5.5 28.7 −6.9 −53.8 1.7 10.7 19.6 
 Nanzhao 13-Jul 28.2 −6.5 −53.6 −1.8 10.2 18.6 
 Lutaizi 14-Jul 28.7 −6.2 −50.1 1.6 16.2 21.9 
 Huainan 14-Jul 28.7 −5.9 −45.7 −0.6 15.1 20.3 
 Bengbu 14-Jul 29.8 −5.3 −42.9 −0.4 28.0 35.9 
 Linhuaiguan 17-Jul 2.3 29.6 −5.3 −42.3 −0.3 23.5 29.4 
 Wuhe 17-Jul 2.3 29.6 −5.2 −41.4 −0.2 24.0 29.0 
 10 Xuyu 18-Jul 39.5 30.6 −5.0 −41.0 −1.3 41.9 50.9 
Hongze Lake (HZL) Lake 11 Laozishan 18-Jul 31.3 −4.2 −40.6 −6.9 66.6 62.5 
 12 Lihewa 17-Jul 29.2 −4.8 −45.1 −6.5 46.3 63.0 
 13 Chenzihu 17-Jul 28.9 −4.0 −36.7 −4.6 45.4 48.4 
 14 Erheza 17-Jul 29.3 −3.7 −36.6 −6.8 49.7 68.0 
 15 Sanheza 18-Jul 29.6 −3.5 −36.6 −8.4 29.2 37.6 
 16 Jinhu 18-Jul 31.5 −3.3 −36.2 −9.7 40.9 47.7 
Shi River (SR) South 17 Yeji 12-Jul 29.8 −6.7 −50.7 2.8 6.7 14.6 
Trib 18 Shangshiqiao 12-Jul 30.3 −6.4 −48.0 2.8 7.8 17.5 
Pi River (PR) South 19 Hengpaitou 12-Jul 26.7 −7.8 −56.8 5.5 5.0 14.9 
Trib 20 Matou 13-Jul 30.0 −7.6 −55.7 5.1 6.0 14.2 
 21 Zhengyang 13-Jul 31.5 −7.5 −53.6 6.2 7.9 14.3 
Shaying River (SYR) North 22 Pingdingshan 11-Jul 29.8 −5.2 −43.5 −1.9 19.2 55.9 
Trib 23 Luohe 11-Jul 29.9 −5.1 −46.5 −5.5 205.1 103.5 
 24 Huahang 10-Jul 30.0 −5.1 −47.6 −6.6 72.3 93.3 
 25 Huangqiao 11-Jul 29.8 −5.4 −49.1 −5.6 109.7 129.5 
 26 Zhoukou 11-Jul 29.7 −5.3 −46.5 −4.2 266.8 124.9 
 27 Jieshou 13-Jul 2.5 30.1 −6.9 −59.0 −4.0 131.5 110.3 
 28 Fuyang 13-Jul 2.5 29.9 −6.8 −58.0 −3.8 126.8 128.6 
 29 Yingshang 13-Jul 2.5 30.2 −5.8 −48.0 −1.4 93.0 105.8 
Guo River (GR) North 30 Taikang 11-Jul 0.4 29.9 −5.8 −53.6 −7.0 94.8 177.3 
Trib 31 Bozhou 13-Jul 30.1 −5.7 −53.0 −7.6 184.9 243.6 
 32 Mengcheng 13-Jul 30.2 −5.6 −50.3 −5.9 159.3 169.4 
 33 Huaiyuan 14-Jul 30.6 −4.8 −43.9 −5.3 114.3 160.2 
Southern section of the East Line of SNWTP (SNWTP (S)) South 34 Jiangdu 19-Jul 0.2 31.1 −6.5 −54.4 −2.4 31.4 41.2 
Sec. 35 Gaoyou 19-Jul 0.2 28.5 −4.3 −37.8 −3.5 32.1 41.5 
 36 Baoyin 19-Jul 0.2 29.8 −3.9 −34.9 −3.6 32.8 40.9 
 37 Huai'an 19-Jul 29.5 −3.1 −33.5 −8.5 51.7 52.7 
Northern section of the East Line of SNWTP (SNWTP (N)) North 38 Siyang 17-Jul 29.2 −3.6 −41.0 −12.1 81.7 116.6 
Sec. 39 Suqian 16-Jul 0.4 29.8 −4.4 −41.5 −6.5 82.1 126.9 
 40 Pizhou 14-Jul 29.5 −5.5 −45.7 −1.5 81.7 153.9 
 41 Tai'e'zhuang 18-Jul 28.3 −5.8 −46.7 −0.2 102.8 200.2 
 42 Jining 16-Jul 0.9 28.5 −6.5 −54.7 −2.9 180.4 373.8 
 43 Liangshan 16-Jul 0.9 31.6 −6.8 −56.8 −2.5 47.3 185.0 
Tributaries of Nansi lake (TRI_NSL) Trib 44 Jishu 16-Jul 0.9 29.3 −7.0 −61.7 −5.4 184.2 180.6 
 45 Sunzhuang 16-Jul 0.9 30.6 −6.8 −59.3 −4.8 175.7 259.9 
 46 Liangshanza 16-Jul 0.9 33.4 −6.4 −60.5 −9.6 211.5 302.9 
 47 Yanzhou 17-Jul 0.9 28.5 −6.9 −60.6 −5.0 155.7 178.2 
Nansi Lake (NSL) Lake 48 Weishandao 17-Jul 29.1 −4.0 −43.0 −11.2 120.6 206.4 
 49 Erjibashang 17-Jul 30.3 −3.9 −39.9 −8.9 150.9 220.4 
 50 Erjibaxia 15-Jul 9.8 27.6 −3.7 −39.4 −9.9 147.0 223.1 
 51 Dushandao 15-Jul 9.8 27.7 −3.0 −37.4 −13.6 104.8 132.2 
 52 Nanyanghu 17-Jul 29.2 −2.4 −36.5 −17.2 145.4 241.0 
Water system Type  Sampling site Date Precipitation (mm) T (°C) δ18O (‰) δD (‰) d (‰) Cl (mg/L)L) SO4 (mg/L)L) 
Huai River main channel (HRMC) Main Minggang 12-Jul 5.5 28.9 −7.5 −57.9 2.5 35.5 24.5 
Channel Xixian 12-Jul 5.5 28.6 −7.4 −57.7 1.3 20.1 24.5 
 Huaibin 12-Jul 5.5 28.7 −6.9 −53.8 1.7 10.7 19.6 
 Nanzhao 13-Jul 28.2 −6.5 −53.6 −1.8 10.2 18.6 
 Lutaizi 14-Jul 28.7 −6.2 −50.1 1.6 16.2 21.9 
 Huainan 14-Jul 28.7 −5.9 −45.7 −0.6 15.1 20.3 
 Bengbu 14-Jul 29.8 −5.3 −42.9 −0.4 28.0 35.9 
 Linhuaiguan 17-Jul 2.3 29.6 −5.3 −42.3 −0.3 23.5 29.4 
 Wuhe 17-Jul 2.3 29.6 −5.2 −41.4 −0.2 24.0 29.0 
 10 Xuyu 18-Jul 39.5 30.6 −5.0 −41.0 −1.3 41.9 50.9 
Hongze Lake (HZL) Lake 11 Laozishan 18-Jul 31.3 −4.2 −40.6 −6.9 66.6 62.5 
 12 Lihewa 17-Jul 29.2 −4.8 −45.1 −6.5 46.3 63.0 
 13 Chenzihu 17-Jul 28.9 −4.0 −36.7 −4.6 45.4 48.4 
 14 Erheza 17-Jul 29.3 −3.7 −36.6 −6.8 49.7 68.0 
 15 Sanheza 18-Jul 29.6 −3.5 −36.6 −8.4 29.2 37.6 
 16 Jinhu 18-Jul 31.5 −3.3 −36.2 −9.7 40.9 47.7 
Shi River (SR) South 17 Yeji 12-Jul 29.8 −6.7 −50.7 2.8 6.7 14.6 
Trib 18 Shangshiqiao 12-Jul 30.3 −6.4 −48.0 2.8 7.8 17.5 
Pi River (PR) South 19 Hengpaitou 12-Jul 26.7 −7.8 −56.8 5.5 5.0 14.9 
Trib 20 Matou 13-Jul 30.0 −7.6 −55.7 5.1 6.0 14.2 
 21 Zhengyang 13-Jul 31.5 −7.5 −53.6 6.2 7.9 14.3 
Shaying River (SYR) North 22 Pingdingshan 11-Jul 29.8 −5.2 −43.5 −1.9 19.2 55.9 
Trib 23 Luohe 11-Jul 29.9 −5.1 −46.5 −5.5 205.1 103.5 
 24 Huahang 10-Jul 30.0 −5.1 −47.6 −6.6 72.3 93.3 
 25 Huangqiao 11-Jul 29.8 −5.4 −49.1 −5.6 109.7 129.5 
 26 Zhoukou 11-Jul 29.7 −5.3 −46.5 −4.2 266.8 124.9 
 27 Jieshou 13-Jul 2.5 30.1 −6.9 −59.0 −4.0 131.5 110.3 
 28 Fuyang 13-Jul 2.5 29.9 −6.8 −58.0 −3.8 126.8 128.6 
 29 Yingshang 13-Jul 2.5 30.2 −5.8 −48.0 −1.4 93.0 105.8 
Guo River (GR) North 30 Taikang 11-Jul 0.4 29.9 −5.8 −53.6 −7.0 94.8 177.3 
Trib 31 Bozhou 13-Jul 30.1 −5.7 −53.0 −7.6 184.9 243.6 
 32 Mengcheng 13-Jul 30.2 −5.6 −50.3 −5.9 159.3 169.4 
 33 Huaiyuan 14-Jul 30.6 −4.8 −43.9 −5.3 114.3 160.2 
Southern section of the East Line of SNWTP (SNWTP (S)) South 34 Jiangdu 19-Jul 0.2 31.1 −6.5 −54.4 −2.4 31.4 41.2 
Sec. 35 Gaoyou 19-Jul 0.2 28.5 −4.3 −37.8 −3.5 32.1 41.5 
 36 Baoyin 19-Jul 0.2 29.8 −3.9 −34.9 −3.6 32.8 40.9 
 37 Huai'an 19-Jul 29.5 −3.1 −33.5 −8.5 51.7 52.7 
Northern section of the East Line of SNWTP (SNWTP (N)) North 38 Siyang 17-Jul 29.2 −3.6 −41.0 −12.1 81.7 116.6 
Sec. 39 Suqian 16-Jul 0.4 29.8 −4.4 −41.5 −6.5 82.1 126.9 
 40 Pizhou 14-Jul 29.5 −5.5 −45.7 −1.5 81.7 153.9 
 41 Tai'e'zhuang 18-Jul 28.3 −5.8 −46.7 −0.2 102.8 200.2 
 42 Jining 16-Jul 0.9 28.5 −6.5 −54.7 −2.9 180.4 373.8 
 43 Liangshan 16-Jul 0.9 31.6 −6.8 −56.8 −2.5 47.3 185.0 
Tributaries of Nansi lake (TRI_NSL) Trib 44 Jishu 16-Jul 0.9 29.3 −7.0 −61.7 −5.4 184.2 180.6 
 45 Sunzhuang 16-Jul 0.9 30.6 −6.8 −59.3 −4.8 175.7 259.9 
 46 Liangshanza 16-Jul 0.9 33.4 −6.4 −60.5 −9.6 211.5 302.9 
 47 Yanzhou 17-Jul 0.9 28.5 −6.9 −60.6 −5.0 155.7 178.2 
Nansi Lake (NSL) Lake 48 Weishandao 17-Jul 29.1 −4.0 −43.0 −11.2 120.6 206.4 
 49 Erjibashang 17-Jul 30.3 −3.9 −39.9 −8.9 150.9 220.4 
 50 Erjibaxia 15-Jul 9.8 27.6 −3.7 −39.4 −9.9 147.0 223.1 
 51 Dushandao 15-Jul 9.8 27.7 −3.0 −37.4 −13.6 104.8 132.2 
 52 Nanyanghu 17-Jul 29.2 −2.4 −36.5 −17.2 145.4 241.0 

Tri, tributary; Sec, section; precipitation is the daily data at the sampling sites (data from China Meteorological Data Sharing Service Database, http://www.cdc.cma.gov.cn); T is the water temperature in sampling; d = deuterium excess, calculated as δD-8δ18O.

The weather conditions were noted every day during the sampling period. All water samples were collected before a precipitation event on the sampling date except for site 18 (Table 1 and Figure 1), where there was a rainfall event occurring at midnight before our sampling date, and the water samples at site 18 had been mixed by new rainfall and upriver waters. Water samples were collected from the top, middle, and bottom at each site, mixed together and filtered (0.45 μm GF/C Millipore nitrocellulose filter) in the field. Filtered 100 mL water samples were placed in high-density polyethylene (HDPE) bottles and stored in an ice box for lab analyses. Water temperature was measured in situ using a handheld meter. Stable isotope and ion (Cl and SO42−) analyses were performed in the laboratory of the Institute of Geographic Sciences and Natural Resources Research (Beijing), Chinese Academy of Sciences. Isotopic analyses were done using a Thermo Finnigan TC/EA with GC-PAL autosampler attached to a Thermo Finnigan MAT-253 continuous flow mass spectrometer via a Conflo III interface. Isotopic values are reported using the standard δ notion relative to the NIST/IAEA reference materials V-SMOW. The analytical precision was ±0.1‰ and ±1.5‰ for δ18O and δD, respectively. Water Cl and SO42− were measured using a Shimadzu Ion Chromatograph (IC) meter (Shimadzu HIC-SP, Japan), and the precision was ±0.1 mg/L. Reagent and procedural blanks were determined in parallel for the sample treatment using identical procedures. Statistical package SPSS (version 11.5, IMB Ltd) and analysis of variance (ANOVA) tests were used in the analysis.

RESULTS

The surface water δ18O and δD compositions from different sampling sites of the Huai River basin are listed in Figure 1 and Table 1. The δ18O value of the whole basin varied from −7.8‰ to −2.4‰ with an average value of −5.4‰. The δD value for the whole basin varied from −61.7‰ to −33.5‰ with an average value of −47.5‰. The δ18O values of the tributaries waters showed clear spatial differences; northern waters were enriched while the southern water systems were depleted (Figure 1). The northern δ18O values ranged from −5.1‰ to −6.9‰ in the Shaying River and −4.8‰ to −5.8‰ in the Guo River. The southern δ18O values ranged from −6.4‰ to −6.7‰ in the Shi River and from −7.5‰ to −7.8‰ in the Pi River. Similar trends were observed for δD values as well.

The Cl and SO4 concentrations in northern Shaying River (up to 266.8 and 124.9 mg/L for Cl and SO4, respectively) and Guo River (up to 184.9 and 243.6 mg/L for Cl and SO4), respectively (Table 1), were obviously higher than those from the southern Shi River and Pi River (up to 7.9 and 17.5 mg/L for Cl and SO4). Tables 2 and 3 show the results of isotopic (δ18O and δD) and anionic (Cl and SO4) ANOVAs of the different water systems, respectively. Due to the limited sampling sites (n = 2, not of a Gaussian distribution), the data from Shi River was not included in the one-way ANOVA analysis. It was found that the isotopic (δ18O and δD) and anionic (Cl and SO4) values from the Pi River sites are significantly different (p < 0.01) when compared with northern waters (Shaying River, Guo River, Northern SNWTP, Nansi Lake and its tributaries). In addition, tributary δ18O and δD values also showed an increase in the direction of water flow for all rivers studied here (Figure 1).

Table 2

The one-way ANOVA of the δ18O (lower triangle) and δD (upper triangle) among nine water systems (Shi River is not included, due to only two samples on the river) of the Huai River basin

 HRMC HZL PR SYR GR SNWTP (S) SNWTP (N) TRI_NSL NSL 
HRMC  0.001** 0.073 0.669 0.637 0.013* 0.753 0.000** 0.004** 
HZL 0.000**  0.000** 0.001** 0.002** 0.674 0.007** 0.000** 0.858 
PR 0.009** 0.000**  0.144 0.230 0.001** 0.059 0.171 0.000** 
SYR 0.300 0.000** 0.002**  0.901 0.007** 0.500 0.002** 0.002** 
GR 0.203 0.007** 0.002** 0.665  0.014* 0.495 0.007** 0.005** 
SNWTP (S) 0.002** 0.333 0.000** 0.020* 0.093  0.040* 0.000** 0.808 
SNWTP (N) 0.122 0.003** 0.001** 0.561 0.939 0.078  0.000** 0.015* 
TRI_NSL 0.196 0.000** 0.003** 0.043 0.035* 0.000** 0.018*  0.000** 
NSL 0.000** 0.317 0.000** 0.000** 0.001** 0.070 0.000** 0.000**  
 HRMC HZL PR SYR GR SNWTP (S) SNWTP (N) TRI_NSL NSL 
HRMC  0.001** 0.073 0.669 0.637 0.013* 0.753 0.000** 0.004** 
HZL 0.000**  0.000** 0.001** 0.002** 0.674 0.007** 0.000** 0.858 
PR 0.009** 0.000**  0.144 0.230 0.001** 0.059 0.171 0.000** 
SYR 0.300 0.000** 0.002**  0.901 0.007** 0.500 0.002** 0.002** 
GR 0.203 0.007** 0.002** 0.665  0.014* 0.495 0.007** 0.005** 
SNWTP (S) 0.002** 0.333 0.000** 0.020* 0.093  0.040* 0.000** 0.808 
SNWTP (N) 0.122 0.003** 0.001** 0.561 0.939 0.078  0.000** 0.015* 
TRI_NSL 0.196 0.000** 0.003** 0.043 0.035* 0.000** 0.018*  0.000** 
NSL 0.000** 0.317 0.000** 0.000** 0.001** 0.070 0.000** 0.000**  

For abbreviations of water system see Table 1.

**The difference is significant at the 0.01 level (two-tailed).

*The difference is significant at the 0.05 level (two-tailed).

Table 3

The one-way ANOVA of Cl (lower triangle) and SO4 (upper triangle) among nine different water systems (Shi River is not included) of the Huai River basin

 HRMC HZL PR SYR GR SNWTP (S) SNWTP (N) TRI_NSL NSL 
HRMC  0.216 0.639 0.000** 0.000** 0.505 0.000** 0.000** 0.000** 
HZL 0.244  0.182 0.026* 0.000** 0.700 0.000** 0.000** 0.000** 
PR 0.531 0.154  0.002** 0.000** 0.358 0.000** 0.000** 0.000** 
SYR 0.000** 0.000** 0.000**  0.003** 0.019* 0.000** 0.000** 0.000** 
GR 0.000** 0.001** 0.000** 0.670  0.000** 0.850 0.155 0.547 
SNWTP (S) 0.534 0.712 0.309 0.000** 0.001**  0.000** 0.000** 0.000** 
SNWTP (N) 0.001** 0.033* 0.002** 0.136 0.100 0.024*  0.169 0.640 
TRI_NSL 0.000** 0.000** 0.000** 0.030* 0.123 0.000** 0.001**  0.362 
NSL 0.000** 0.001** 0.000** 0.957 0.731 0.001** 0.167 0.051  
 HRMC HZL PR SYR GR SNWTP (S) SNWTP (N) TRI_NSL NSL 
HRMC  0.216 0.639 0.000** 0.000** 0.505 0.000** 0.000** 0.000** 
HZL 0.244  0.182 0.026* 0.000** 0.700 0.000** 0.000** 0.000** 
PR 0.531 0.154  0.002** 0.000** 0.358 0.000** 0.000** 0.000** 
SYR 0.000** 0.000** 0.000**  0.003** 0.019* 0.000** 0.000** 0.000** 
GR 0.000** 0.001** 0.000** 0.670  0.000** 0.850 0.155 0.547 
SNWTP (S) 0.534 0.712 0.309 0.000** 0.001**  0.000** 0.000** 0.000** 
SNWTP (N) 0.001** 0.033* 0.002** 0.136 0.100 0.024*  0.169 0.640 
TRI_NSL 0.000** 0.000** 0.000** 0.030* 0.123 0.000** 0.001**  0.362 
NSL 0.000** 0.001** 0.000** 0.957 0.731 0.001** 0.167 0.051  

For abbreviations of water system see Table 1.

**The difference is significant at the 0.01 level (two-tailed).

*Difference is significant at the 0.05 level (two-tailed).

The δ18O and δD values for the four southern sites of SNWTP increased from south to north, while isotopic values for the six northern sites increased from north to south (Figure 1). Thus, the δ18O and δD of both sections increase along the direction of the water flow, likely due to higher evaporation rates on hot summer days (Figure 2). Similar results were seen in the Huai River main channel and its four main tributaries excluding the Shaying River that was influenced by a rainfall event on 12 July. Moreover, we saw significant differences between the two sections; the northern SNWTP section Cl and SO4 were obviously higher than those of the southern SNWTP section (Tables 2 and 3).

DISCUSSION

Isotopic variations in waters in the Huai River basin

In a previous study (Tan et al. 2009), the average δ18O for precipitation, surface water, and groundwater at Wudaogou (close to site 7 in this study) were recorded as −9.15‰ (n = 3), −6.76‰ (n = 4), and −8.01‰ (n = 6), respectively; the average δD for precipitation, surface water, and groundwater were −50.38‰, −48.81‰, and −57.32‰, respectively. Li et al. (2010a) also indicated that the main channel of the Huai River could discharge riverine groundwater on two sides in both the rainy and dry seasons. Microcystins can only be produced by river algae but cannot be produced in groundwater; however, Tian et al. (2013) even detected microcystins in the groundwater (maximum microcystin concentration 0.446 μg/L) discharged from the Shaying River main channel (maximum microcystin concentration 1.846 μg/L) in December 2008 and December 2009 (dry season). All the rivers and lakes surrounding levees in our sampling areas are constantly monitored by the government (in rainy season every year) to prevent water flowing out of rivers or lakes (Hongze Lake, Nansi Lake, etc.). Consequently, it can be excluded that the surface waters in our sampling period (July in the rainy season of 2008) and areas were recharged from groundwater.

The International Atomic Energy Agency maintains a database containing oxygen and hydrogen isotopic contents of precipitation from around the world (IAEA/WMO 2010). These contain two GNIP (Global Network of Isotopes in Precipitation) stations, one within the Huai River basin (Zhengzhou, upriver of Shaying River) and one close to the south-eastern border (Nanjing) (Figure 1). In order to present the δ18O and δD relations between precipitation and surface waters of this region, the two GNIP stations' (Zhengzhou and Nanjing) precipitations monthly δ18O and δD variations (from IAEA/WMO 2010) are shown in Figure 3. Although the precipitation isotopic data of Zhengzhou and Nanjing show extremely large seasonal variation throughout the year (Figure 3), the precipitation in the northern Huai River basin (Zhengzhou) during the summer months (June to September) has consistently higher δ18O (1‰ to 2‰) and deuterium (7‰ to 9‰) values than those of the southern basin (Nanjing). Furthermore, δ18O and δD values of Zhengzhou and Nanjing in the summer months are consistently lower than the rest of the year, indicating that the summer precipitation of the Huai River basin (between Zhengzhou and Nanjing) is mostly derived from the moisture masses from the Pacific Ocean (Yamanaka et al. 2004).

Figure 3

Monthly average and SD variations (eight-year average) of δ18O, δD, d-excess, and precipitation of the two IAEA monitoring sites Nanjing and Zhengzhou (see locations in Figure 1). Original data were obtained from the IAEA database (IAEA 2010).

Figure 3

Monthly average and SD variations (eight-year average) of δ18O, δD, d-excess, and precipitation of the two IAEA monitoring sites Nanjing and Zhengzhou (see locations in Figure 1). Original data were obtained from the IAEA database (IAEA 2010).

Our sampling at each site was scheduled to occur before the rainfall event on a certain day, but certain samplings could not avoid the effects of the day-before precipitation events. On the northern tributary of the Shaying River, for example, δ18O and δD values for sites 27 and 28 were more depleted than upriver sites 25 and 26, which were influenced by a rainfall event on 12 July 2008 (Table 1). This is similar to previous isotopic findings on the precipitation and river waters in this region (Tan et al. 2009). However, the rainfall event on 17 July did not decrease the δ18O and δD values of site 10 (sampling time occurred before the rainfall on 18 July at this site) relative to sites 8 and 9 on the Huai River's main channel. This may be the result of the precipitation not being sufficient enough to change the Huai River's main channel waters (only 2.3 mm on 17 July at upriver sites 8 and 9); also, the high air temperatures on 17 and 18 July (29.6°C to 30.6°C, Table 1) might cause the intensive evaporation of river water and decreased the water δ18O and δD values at site 10.

As lakes and reservoirs have more intensive evaporation than their confluent rivers and streams, the δ18O and δD in lake/reservoir waters always have more enriched values than those of their confluent waters (Telmer & Veizer 2000; Gammons et al. 2006). In this study, Hongze Lake and Nansi Lake had distinctly higher isotopic values than the Huai River and Nansi Lake's tributaries, respectively (Table 1), and the differences were significant (Table 2). However, the Cl and SO4 concentrations in these waters did not show significant variance in the comparison (Table 3). These indicate that oxygen and hydrogen isotopes are more sensitive than chemical ions, and thus, it highlights the advantages to using δ18O and δD as tracers in hydrological studies (Schotterer et al. 1993; Kendall & Coplen 2001).

Traditionally, the Huai River main channel serves as a geographic division between southern and northern China in terms of temperature (south-side is subtropic and north-side is warm temperate zone), precipitation (more or less than 750 mm/year), and vegetation (rice and wheat cultivated) distribution. Currently, the northern plain areas in this region have more intensive agricultural and industrial activities than the southern areas, which also produce more pollution in northern areas in this region (Wang & Ongley 2004; Hu et al. 2009; Tian et al. 2013). In the present study, the surface water δ18O and δD variations also exhibit apparently spatial differences between south and north areas. Northern waters were enriched while the southern water systems were depleted (Figure 1). In addition, the northern and southern δ18O and δD differences also exist in the man-made channel of the SNTWP (Figure 1 and Table 1). These surface water isotopes spatial differences, certainly, are affected by the northern and southern differences of temperature, precipitation, evaporation, etc. The Cl and SO4 concentrations in northern tributaries (Shaying River and Guo River) were obviously higher than those in southern tributaries (Shi River and Pi River) (Table 1). Similar north and south variations also exist in the SNWTP water Cl and SO4 (Tables 13). These results might be mostly due to higher pollution in the northern plain (intensive agricultural and industrial activities) of this region (Wang & Ongley 2004; Hu et al. 2009; Tian et al. 2013).

River water isotopic variations along the flow direction

It is expected that upriver waters have lower δ18O and δD values than downriver waters (Simpson & Herczeg 1991; Ramesh & Sarin 1992; Telmer & Veizer 2000; Dalai et al. 2002; Yuan & Miyamoto 2008), but different studies addressed this with various explanations. For instance, Simpson & Herczeg (1991) concluded that the increasing δ18O and δD from upriver to downriver portions of the Murray River (a river in the semi-arid area in Australia) mostly resulted from river water evaporation and heavy isotopic irrigation inflows. Ramesh & Sarin (1992) indicated the increasing δ18O and δD in upper Ganges River (in India) was due to altitude increases (altitude effect), but lowland isotopic increases resulted from evaporation effects. Dalai et al. (2002) demonstrated the altitude effects resulted in the δ18O variations in the Yamuna River (in India) and its tributaries in high mountain areas. The increasing δ18O and δD from upriver to downriver in the Ottawa River (a river in a humid continental climate area in Canada) are addressed mainly by water evapotranspiration (Telmer & Veizer 2000). The δ18O and δD variations in the Pecos River (a river in the southern Rocky Mountains in the United States) were also mainly caused by evaporation-induced isotopic enrichments, and only two creeks were dominated by groundwater which was also affected by the seepage of the surrounding reservoir (Yuan & Miyamoto 2008).

Since irrigation diversions are always associated with water evaporation, the evaporation process can lead to water δ18O and δD increasing (Simpson & Herczeg 1991; Yuan & Miyamoto 2008; Ahmad et al. 2012). Here we discuss only the evaporation and altitude effects on river isotopic variation. In order to compare the evaporation and altitude effects, we compared our data from the Huai River basin with the published data of other large rivers from different countries (Table 4). Altitude effects on δ18O changes varied between 0.7‰ and 37.8‰ per 1,000 m in those rivers, whereas the evaporation effects on δ18O changes only ranged between 0.4‰ and 3.1‰ per 1,000 km (upper section of Table 4). In the Huai River basin waters, the altitude effects ranged between 7.9‰ and 3,200.0‰ per 1,000 m, but evaporation effects varied between 2.6‰ and 20.0% per 1,000 km (lower section of Table 4). Moreover, the studies on the Murray River (Simpson & Herczeg 1991), Ganges River (Ramesh & Sarin 1992), and Yellow River (Su et al. 2004) revealed that the river waters seasonal δ18O and δD changed as well, and that the evaporation effects on δ18O changes were consistently higher in the hot/warm season and lower in the cold/cool season (Table 4). Thus, these studies indicate the high evaporation effects on river δ18O changes in hot/warm seasons and the contrast in cold/cool seasons. Similar findings on evaporation and temperature effects on river δ18O changes were also reported in US national surface waters' samplings (Kendall & Coplen 2001). These δ18O variations in river waters from different continents, along with this study, indicate that evaporation is a more suitable explanation than altitude effect for δ18O increase from upriver to downriver waters.

Table 4

Comparison between the upriver and downriver δ18O values of surface waters in the Huai River basin and other rivers from different continents

River Country River flow direction Total length (km) δ18O (‰)
 
In research
 
δ18O changes
 
Sampling period Data source 
Upriver Downriver Length (km) Drops (m) Evaporation effects (‰/103 km) Elevation effects (‰/km) 
Murray River Australia E to W 2,370 −7.94 −1.84 2,215 180 2.8 33.9 Jan 1989 Simpson & Herczeg (1991)  
    −7.84 −1.03 2,215 180 3.1 37.8 Apr 1989 Simpson & Herczeg (1991)  
    −8.30 −5.32 2,215 180 1.3 16.6 Jun 1989 Simpson & Herczeg (1991)  
Ottawa River Canada W to E 1,160 −11.10 −10.10 900 360 0.9 2.8 Sep 1991 Telmer & Veizer (2000)  
   1,160 −12.70 −11.40 900 360 1.2 3.6 May 1992 Telmer & Veizer (2000)  
Yangtze River China W to E 6,380 −13.80 −8.30 4,090 1,470 1.3 3.7 Aug 2006 Li et al. (2010b
Yellow River China W to E 5,460 −13.10 −7.00 3,910 3,290 1.6 1.4 Aug–Sep 2000 Su et al. (2004)  
    −11.80 −8.80 3,910 3,290 0.8 0.7 Mar–Apr 2001 Su et al. (2004)  
Danube River Europe W to E 2,857 −10.83 −9.65 2,204 300 0.5 3.9 Aug–Sep 2007 Rank et al. (2009)  
Ganges River India W to E 2,700 −9.20 −3.80 2,100 213 1.2 25.4 Mar 1982 Ramesh & Sarin (1992)  
    −11.50 −10.60 2,100 213 2.6 4.2 Sep 1982 Ramesh & Sarin (1992)  
Yamuna River India N to S 1,376 −9.40 −7.80 1,376 1,450 0.4 1.1 Jun 1999 Dalai et al. (2002)  
Indus River Pakistan NE to SW 2,900 −12.8 −7.5 2,000 2,430 2.7 2.2 Jan–Jun 2003 Ahmad et al. (2012)  
Missouir River United States NW to ES 3,690 −17.60 −10.90 3,246 950 2.1 7.1 1984–1987 Winston & Criss (2003)  
Pecos River United States N to S 1,400 −6.00 −3.90 1,400 1,800 1.5 1.2 Mar 2005 Yuan & Miyamoto (2008)  
    −4.80 −3.10 1,400 1,800 1.2 0.9 May 2005 Yuan & Miyamoto (2008)  
Huai River China W to E 1,000 −7.5 −5.0 600 52 4.2 48.1 Jul 2008 This study 
Shayin River China N to S 620 −6.9 −5.0 150 15 12.7 126.7 Jul 2008 This study 
Guo River China N to S 420 −5.8 −4.8 300 31 3.3 32.3 Jul 2008 This study 
Shi River China S to N 220 −6.7 −6.4 90 3.3 50.0 Jul 2008 This study 
Pi River China S to N 260 −7.8 −7.5 130 38 2.6 7.9 Jul 2008 This study 
North part of SNWTP China N to S 390 −6.5 −3.1 390 23 8.7 147.8 Jul 2008 This study 
South part of SNWTP China S to N 160 −6.8 −3.6 160 20.0 3,200.0 Jul 2008 This study 
River Country River flow direction Total length (km) δ18O (‰)
 
In research
 
δ18O changes
 
Sampling period Data source 
Upriver Downriver Length (km) Drops (m) Evaporation effects (‰/103 km) Elevation effects (‰/km) 
Murray River Australia E to W 2,370 −7.94 −1.84 2,215 180 2.8 33.9 Jan 1989 Simpson & Herczeg (1991)  
    −7.84 −1.03 2,215 180 3.1 37.8 Apr 1989 Simpson & Herczeg (1991)  
    −8.30 −5.32 2,215 180 1.3 16.6 Jun 1989 Simpson & Herczeg (1991)  
Ottawa River Canada W to E 1,160 −11.10 −10.10 900 360 0.9 2.8 Sep 1991 Telmer & Veizer (2000)  
   1,160 −12.70 −11.40 900 360 1.2 3.6 May 1992 Telmer & Veizer (2000)  
Yangtze River China W to E 6,380 −13.80 −8.30 4,090 1,470 1.3 3.7 Aug 2006 Li et al. (2010b
Yellow River China W to E 5,460 −13.10 −7.00 3,910 3,290 1.6 1.4 Aug–Sep 2000 Su et al. (2004)  
    −11.80 −8.80 3,910 3,290 0.8 0.7 Mar–Apr 2001 Su et al. (2004)  
Danube River Europe W to E 2,857 −10.83 −9.65 2,204 300 0.5 3.9 Aug–Sep 2007 Rank et al. (2009)  
Ganges River India W to E 2,700 −9.20 −3.80 2,100 213 1.2 25.4 Mar 1982 Ramesh & Sarin (1992)  
    −11.50 −10.60 2,100 213 2.6 4.2 Sep 1982 Ramesh & Sarin (1992)  
Yamuna River India N to S 1,376 −9.40 −7.80 1,376 1,450 0.4 1.1 Jun 1999 Dalai et al. (2002)  
Indus River Pakistan NE to SW 2,900 −12.8 −7.5 2,000 2,430 2.7 2.2 Jan–Jun 2003 Ahmad et al. (2012)  
Missouir River United States NW to ES 3,690 −17.60 −10.90 3,246 950 2.1 7.1 1984–1987 Winston & Criss (2003)  
Pecos River United States N to S 1,400 −6.00 −3.90 1,400 1,800 1.5 1.2 Mar 2005 Yuan & Miyamoto (2008)  
    −4.80 −3.10 1,400 1,800 1.2 0.9 May 2005 Yuan & Miyamoto (2008)  
Huai River China W to E 1,000 −7.5 −5.0 600 52 4.2 48.1 Jul 2008 This study 
Shayin River China N to S 620 −6.9 −5.0 150 15 12.7 126.7 Jul 2008 This study 
Guo River China N to S 420 −5.8 −4.8 300 31 3.3 32.3 Jul 2008 This study 
Shi River China S to N 220 −6.7 −6.4 90 3.3 50.0 Jul 2008 This study 
Pi River China S to N 260 −7.8 −7.5 130 38 2.6 7.9 Jul 2008 This study 
North part of SNWTP China N to S 390 −6.5 −3.1 390 23 8.7 147.8 Jul 2008 This study 
South part of SNWTP China S to N 160 −6.8 −3.6 160 20.0 3,200.0 Jul 2008 This study 

LSWL upon δ18O and δD

The δ18O and δD composition of meteoric water and surface waters have been known to vary in a systematic manner (Craig 1961; Ramesh & Sarin 1992; Kendall & Coplen 2001; Dutton et al. 2005). However, the exact relationship between δ18O and δD of precipitation and surface water varies from geographical region to region (Kendall & Coplen 2001; Dalai et al. 2002; Yuan & Miyamoto 2008). Our δ18O and δD data (Figure 4(a) and 4(b)) show a clear linear trend (δD = 5.36δ18O − 18.39; r2 = 0.84, p < 0.01) that represents the LSWL for the Huai River basin, eastern China. The slope (5.36) and intercept (−18.39) of the Huai River basin LSWL are both between that of the summer Yellow River LSWL (δD = 4.71δ18O − 22.64; r2 = 0.92, p < 0.01; derived from Su et al. 2004) and the summer Yangtze River LSWL (δD = 7.68δ18O + 1.59; r2 = 0.98, p < 0.01; derived from Li et al. 2010b). Most points of these three rivers fall below the global meteoric water line (GMWL, δD = 8δ18O + 10; Craig 1961), representing the strong summer evaporation effects on δ18O and δD surface waters, which are similar to other river basins that have intensive evaporation in the hot season (Gammons et al. 2006; Yuan & Miyamoto 2008; Ahmad et al. 2012).

Figure 4

Local surface water line (LSWL) for the Huai River basin. (a) GMWL (Craig 1961) and LSWLs of the Yellow River basin and Yangtze River basin (data from Su et al. (2004) and Li et al. (2010a, 2010b)) are shown for reference. (b) Comparison of different waters around the Huai River basin LSWL (δD = 5.36δ18O − 18.39; r2 = 0.84), and GMWL and LMWLs of Zhengzhou and Nanjing (data from IAEA (2010)) are shown for reference.

Figure 4

Local surface water line (LSWL) for the Huai River basin. (a) GMWL (Craig 1961) and LSWLs of the Yellow River basin and Yangtze River basin (data from Su et al. (2004) and Li et al. (2010a, 2010b)) are shown for reference. (b) Comparison of different waters around the Huai River basin LSWL (δD = 5.36δ18O − 18.39; r2 = 0.84), and GMWL and LMWLs of Zhengzhou and Nanjing (data from IAEA (2010)) are shown for reference.

Figure 4(b) shows the comparison of internal Huai River basin LSWL with local meteoric water lines (LMWL) of two IAEA stations (Zhengzhou and Nanjing). Theoretically, the LMWL of the Huai River basin should be found between Zhengzhou LMWL and Nanjing LMWL, because Zhengzhou and Nanjing are located near the northern and southern borders of the Huai River basin, respectively (Figure 1). In our study, however, all surface water isotopic data points fall below both Zhengzhou and Nanjing LMWLs. In addition, most northern sites (Shaying River, Guo River, Nansi Lake and its tributaries) fall even below the Huai River basin LSWL. All of this once again highlights the evaporation effects in the Huai River basin with higher evaporation effects seen in the northern waters relative to southern. The high evaporation of northern waters in the Huai River Basin may be due to natural landforms of plains which are cultured as farms (Shao et al. 1989; Ge et al. 2006). Also, it could be due to less forest cover percentages in the northern plains than the southern mountainous areas in this region (Wang & Ongley 2004).

The Huai River basin LSWL (slope and intercept) falls between the southern Yangtze basin LSWL and the northern Yellow River basin LSWL, and there are obvious isotopic differences that exist between south and north waters inside this region (Figures 1 and 4). These may be an indication that the Huai River main channel is the δ18O and δD ‘boundary’ between southern and northern China, and the three LSWLs show a progression of increasing slope and intercept, moving from southern to northern China. Based on these results, along with those of our report on the spatial differences in ionic chemistry of this region (Zhang et al. 2011), we suggest that the main channel of the Huai River is likely the geographic division line of surface water isotopic and ionic chemistry for eastern China in addition to its already acknowledged role as a geographic division line for temperature, precipitation, and vegetation distribution (Wang & Ongley 2004).

Characteristics of deuterium excess

Deuterium excess (d-excess) was defined by Dansgaard (1964) as d = δD − 8δ18O, and the d value is typically close to +10‰ for precipitation samples in temperate climates (i.e., the δD intercept of the GMWL). Sites dominated by continental vapor (e.g., Mongolia) have decreasing d-excess with decreasing δ18O, whereas d-excess decreases with increasing δ18O in sites dominated by oceanic moisture masses (Schotterer et al. 1993; Araguás-Araguás et al. 1998). In the present study, the surface waters' δ18O show a significantly negative correlation to d-excess (r = 0.76, p < 0.01; Figure 5), which indicates that this region is dominated by the Pacific oceanic moisture masses in the summer (Araguás-Araguás et al. 1998; Yamanaka et al. 2004).

Figure 5

Relationship between the d-excess and δ18O in the surface waters of the Huai River basin.

Figure 5

Relationship between the d-excess and δ18O in the surface waters of the Huai River basin.

Surface water d-excess values can vary significantly from geographical region to region because the surface water in a given place can be influenced by various issues. For example, the river waters from arid western US areas have much lower d-excess values (below −2) compared to the humid eastern US river waters (above 10) (Kendall & Coplen 2001). The d-excess values of the Kachura site on the Indus River were obviously lower than other sampling sites, exhibiting the evaporation effects of Kachura Lake (Ahmad et al. 2012). Eastern Canadian surface water d-excess values were higher in coastal areas (Newfoundland and Nova Scotia) but lower in the waters from western inland areas (Labrador and Quebec), because the two areas are controlled by recycled moisture and land evaporation, respectively (Timsic & Patterson 2014). In this study, only five sites from two southern rivers (Shi River and Pi River) and four sites from the upriver Huai River main channel had positive d-excess values (1.3 to 6.2). All 43 of the remaining sites had negative d-excess values and much lower d-excess values in Hongze Lake (−9.7 to −4.6) and Nansi Lake (−17.2 to −8.9) compared with their water source rivers (Table 1). These low d-excess values in this region and much lower values found in lake samples demonstrate the intensive evaporation of this region in the summer season. Our current regional study can be comparable to previous large-scale surface water isotopic research (Kendall & Coplen 2001; Ahmad et al. 2012). However, the water d-excess values of the southern section of the SNWTP (sites 34 to 37) were lower than the values from the two southern rivers (Shi and Pi, sites 17 to 21). These findings are the converse to previous studies in eastern Canadian waters, in which d-excess values were higher in coastal water but lower in inland areas waters (Timsic & Patterson 2014). It suggests that oceanic moisture effects above the SNWTP south section (sites 34 to 37) may not be as strong as the moisture effects above the Shi River and Pi River (sites 17 to 21), or the evaporation effects in former areas are greater than the latter area.

Latitude effects on the slopes of LSWLs

Based on more than 4,800 river water samples across 50 states of the United States, Kendall & Coplen (2001) published the slopes and intercepts of the local river water lines (LSWL, δD = (slope) δ18O + intercept. Note: although Kendall & Coplen (2001) used the term ‘LWML’, they clearly indicated that regressions were calculated from river water isotopic data, which is the same as LSWL in our study). Rivers in the eastern United States, which are derived from the Appalachian Mountains and flow into the Atlantic Ocean, are largely controlled by the North American monsoon (Kendall & Coplen 2001) and can be compared with eastern Chinese rivers that are derived from the western mountains and controlled by the East Asian monsoon. Here, we compare the LSWLs of rivers in eastern China and the eastern United States and present the results in Figure 6. Given the preceding discussion of spatial differences between northern and southern waters in the Huai River basin, we separated the northern waters (Shaying River, Guo River, northern six sites of the East Line of the SNWTP, Nansi Lake and its tributaries) and the southern waters (Huai River, Shi River, Pi River, Hongze Lake and four southern sites of the East Line of the SNWTP) of the Huai River basin. This national scale comparison shows that river elevation slopes of LSWLs of both eastern China and the eastern United States increased northward (Figure 6). This is independent of the comparison between separate Chinese rivers or larger-scale areas in China (northern and southern halves of the basin) or the United States (state by state). Kendall & Coplen (2001) speculated that the extent of evaporative fractionation of rainwater could impart a distinctive LSWL within a certain area/region, and although they indicated the ‘latitude effects’ on large-scale (e.g., national) river water δ18O variations, they did not point out that the slopes of LSWLs in the eastern USA (east of the Appalachian Mountains) increased northward.

Figure 6

Spatial changes in the slopes of LSWLs of eastern China and eastern United States surface waters: lower table shows the comparison in the slopes of LSWLs from north to south in the two countries. Superscript letters a, b, c in the lower table stand for Su et al. (2004), Li et al. (2010a, 2010b), and Kendall & Coplen (2001), respectively.

Figure 6

Spatial changes in the slopes of LSWLs of eastern China and eastern United States surface waters: lower table shows the comparison in the slopes of LSWLs from north to south in the two countries. Superscript letters a, b, c in the lower table stand for Su et al. (2004), Li et al. (2010a, 2010b), and Kendall & Coplen (2001), respectively.

Comparing the slopes of LSWLs of rivers from both eastern China and the eastern United States, our study proposes a new hypothesis of latitude effects on the river water line slopes on a large scale (using δ18O and δD values). The slopes of regional LSWLs increase with increasing latitude when regions have similar surrounding landforms. It is rare to be able to couple regions from across the globe; however, due to the similarity in landforms, latitudes, and coastlines, the plains of eastern China and the eastern United States can be coupled together as monsoon-influenced areas. This novel hydrological theory may be tested in other comparable areas, such as eastern Africa and eastern South America if corresponding large-scale data can be found.

CONCLUSIONS

The results of this study show the stable isotope composition of surface waters from the Huai River basin in China. The isotopic and anionic data indicate the difference between northern and southern waters in this region. Northern waters (Shaying River, Guo River, the six northern sites of the East Line of SNWTP and Nansi Lake and its tributaries) having higher δ18O, δD, Cl, and SO4 values than southern waters (Shi River and Pi River). The differences are mostly derived from southern and northern precipitation variation, intensive evaporation and irrigation, with little influence from groundwater recharge. The two big lakes in this region, Hongze Lake and Nansi Lake, also exhibited higher δ18O and δD composition values than their confluent waters, which also indicate their sensitivity to evaporation relative to that of rivers.

The δ18O variations of eight rivers from different continents and those of the Huai River basin indicate that evaporation is a more plausible interpretation than latitude effect for the seen δ18O increases from upriver to downriver waters. Latitude affects the rough tendency of δ18O values for a number of rivers in a large area, but not for any given river in isolation. The d-excess variations in the surface water also point towards the high evaporative enrichments in the Huai River basin in the summer and highlights that lakes are more sensitive to evaporation than rivers. The significant negative correlation between d-excess and δ18O also attests that the Huai River basin is dominated by the Pacific oceanic moisture masses in the summer.

Our δ18O and δD composition data define the LSWL for the Huai River basin, which is one of the first presented LSWL for surface waters in eastern China. Compared with published data from the Yellow River and Yangtze River, the Huai River basin LSWL slope and intercept hold the middle positions from all three rivers/basins, suggesting that the Huai River could be the geographic division between southern and northern China. Furthermore, the comparison between the LSWLs of eastern China and the eastern United States raises a hypothesis that slopes of LSWLs increase as a result of increasing latitude. This novel hydrological theory may be tested in other coupled comparable areas in the world if corresponding large-scale data can be found.

ACKNOWLEDGEMENTS

This study was supported by the Key Program National Natural Sciences Foundation of China (Grant No. 40830636, 40721140020), the China Postdoctoral Science Foundation (Grant No. 20090450564), and the project of The Ministry of Science and Technology of China (Grant No. 2008ZX07010-006-1). The authors thank the colleagues from the Huai River Water Resources Commission for help in the field and the authors appreciate Silviya Ivanova and Lyndon Barr for the help on English proofs.

REFERENCES

REFERENCES
Ahmad
M.
,
Latif
Z.
,
Tariq
J. A.
,
Rafique
M.
,
Akram
W.
,
Aggarwal
P.
&
Vitvar
T.
2012
Isotope Investigations of Major Rivers of Indus Basin, Pakistan. Monitoring Isotopes in Rivers, Creation of the Global Network of Isotopes in Rivers (GNIR), Results of a Coordinated Research Project 2002–2006
.
IAEA
,
Vienna
, pp.
167
186
.
Araguás-Araguás
K.
,
Froehlich
L. K.
&
Rozanski
K.
1998
Stable isotope composition of precipitation over South East Asia
.
J. Geophys. Res.
103
,
28721
28742
.
Dansgaard
W.
1964
Stable isotopes in precipitation
.
Tellus
16
,
436
468
.
Dutton
A.
,
Wilkinson
B. H.
,
Welker
J. M.
,
Bowen
G. J.
&
Lohmann
K. C.
2005
Spatial distribution and seasonal variation in 18O/16O of modern precipitation and river water across the conterminous USA
.
Hydrol. Process.
19
,
4121
4146
.
Gammons
C. H.
,
Poulson
S. R.
,
Pellicori
D. A.
,
Reed
P. J.
,
Roesler
A. J.
&
Petrescu
E. M.
2006
The hydrogen and oxygen isotopic composition of precipitation, evaporated mine water, and river water in Montana, USA
.
J. Hydrol.
328
,
319
330
.
Ge
W.
,
Ye
N.
,
Gong
J.
,
Yu
J.
,
Zuo
Z.
,
Yang
Z.
&
Huang
J.
2006
The Quaternary aquifer division and character analysis of plain in the Huai River basin
.
Resour. Survery Environ.
27
,
268
276
(in Chinese with English abstract)
.
Hu
W.
,
Wang
S.
,
Wang
G.
&
Deng
W.
2009
Study on the groundwater dynamic of the Huaibei Alluvial Plain in Anhui Province
.
J. Nat. Resour.
24
,
1893
1901
(in Chinese with English abstract)
.
IAEA/WMO
2010
Global Network of Isotopes in Precipitation
.
The GNIP Database
. .
Katsuyama
M.
,
Yoshioka
T.
&
Konohira
E.
2015
Spatial distribution of oxygen-18 and deuterium in stream waters across the Japanese archipelago
.
Hydrol. Earth Syst. Sci.
19
,
1577
1588
.
Li
M.
,
Gao
S.
&
Li
K.
2010a
Features of hydrogen and oxygen isotopes of Quaternary groundwater in Henan plain and the recharge analysis
.
China Geotechnical Investigation & Surveying
11
,
42
47
(in Chinese with English abstract)
.
Li
S.
,
Liu
C.
,
Li
J.
,
Liu
X.
,
Chetelat
B.
,
Wang
B.
&
Wang
F.
2010b
Assessment of the sources of nitrate in the Changjiang River, China using a nitrogen and oxygen isotopic approach
.
Environ. Sci. Technol.
44
,
1573
1578
.
Li
S.
,
Yu
Z.
,
Miu
Y.
&
Xu
J.
2013
The projection of Siyang Station
.
Jiangsu Water Resour.
3
,
52
53
(in Chinese)
.
Ramesh
R.
&
Sarin
M. M.
1992
Stable isotope study of the Ganga (Ganges) river system
.
J. Hydrol.
139
,
49
62
.
Rank
D.
,
Papesch
W.
,
Heiss
G.
&
Tesch
R.
2009
Isotopic composition of river water in the Danube Basin – results from the Joint Danube Survey
.
Austrian J. Earth Sci.
102
,
170
180
.
Schotterer
U.
,
Fröhlich
K.
&
Stichler
W.
1993
Temporal variation of 18O and deuterium excess in precipitation, river and spring water in alpine regions of Switzerland
. In:
Isotope Techniques in the Study of Past and Current Environmental Changes in the Hydrosphere and the Atmosphere, Proceedings of Symposium
.
International Atomic Energy Agency
,
Vienna
,
Austria
, pp.
19
23
.
Shao
S.
,
Guo
S.
&
Han
S.
1989
Geomorphic structures and evolution of Huang-Huai-Hai plain in China
.
Acta Geograph. Sin.
44
,
314
322
(in Chinese with English abstract)
.
Simpson
H. J.
&
Herczeg
A. L.
1991
Stable isotopes as an indicator of evaporation in the River Murray, Australia
.
Water Resour. Res.
27
,
1925
1935
.
Su
X.
,
Lin
X.
,
Liao
Z.
&
Wang
J.
2004
The main factors affecting isotopes of Yellow River water in China
.
Water Int.
29
,
475
482
.
Tan
Z.
,
Lu
B.
,
Wang
J.
&
Sun
Y.
2009
Characteristics of stable hydrogen and oxygen isotopes of precipitation and runoff in wudaogou hydrological experimental catchment
.
J. Hohai Univ.
37
,
650
654
(in Chinese with English abstract)
.
Tian
D.
,
Zheng
W.
,
Wei
X.
,
Sun
X.
,
Liu
L.
,
Chen
X.
,
Zhang
H.
,
Zhou
Y.
,
Chen
H.
,
Wang
X.
,
Zhang
R.
,
Jiang
S.
,
Zheng
Y.
&
Qu
W.
2013
Dissolved microcystins in surface and ground waters in regions with high cancer incidence in the Huai River Basin of China
.
Chemosphere
91
,
1064
1071
.
Wang
Q.
&
Chen
J.
1999
Formation and evolution of Hongze lake and the Huaihe River mouth along the lake
.
J. Lake Sci.
11
,
237
244
(in Chinese with English abstract)
.
Wang
S.
&
Dou
H.
1998
China Lakes Record
.
Science Press
,
Beijing
, pp.
268
270
.
Winston
W. E.
&
Criss
R. E.
2003
Oxygen isotope and geochemical variations in the Missouri River
.
Environ. Geol.
43
,
546
556
.
Yamanaka
T.
,
Shimada
J.
,
Hamada
Y.
,
Tanaka
T.
,
Yang
Y.
,
Zhang
W.
&
Hu
C.
2004
Hydrogen and oxygen isotopes in precipitation in the northern part of the North China Plain: climatology and inter-storm variability
.
Hydrol. Process.
18
,
2211
2222
.
Zhang
L.
,
Song
X.
,
Xia
J.
,
Yuan
R.
,
Zhang
Y.
,
Liu
X.
&
Han
D.
2011
Major element chemistry of the Huai River basin, China
.
Appl. Geochem.
26
,
293
300
.