Rainfall driven nitrate transport in agricultural karst surface river system: Insight from high resolution hydrochemistry and nitrate isotopes

Agriculture, Ecosystems and Environment 291 (2020) 106787

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Rainfall driven nitrate transport in agricultural karst surface river system: Insight from high resolution hydrochemistry and nitrate isotopes

T

Zhong-Jun Wanga,b, Si-Liang Lic,d,*, Fu-Jun Yuec,d,e,*, Cai-Qing Qinc, Sarah Buckerfieldf, Jie Zengg a

Department of Water Environment, China Institute of Water Resources and Hydropower Research, Beijing 10038, China State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China c Institute of Surface-Earth System Science, Tianjin University, Tianjin 300072, China d Tianjin Key Laboratory of Earth Critical Zone Science and Sustainable Development in Bohai Rim, China e School of Geographical and Earth Sciences, University of Glasgow, Glasgow G12 8QQ, United Kingdom f Biological & Environmental Sciences, Faculty of Natural Sciences, University of Stirling, Stirling FK9 4LA, United Kingdom g Institute of Earth Sciences, China University of Geosciences (Beijing), Beijing 100083, China b

A R T I C LE I N FO

A B S T R A C T

Keywords: High resolution Nitrate isotopes Rainfall event Nutrient Karst Agricultural surface river

High discharge associated with rainfall events causes rapid transport of nutrients to drainage systems in karst terrain. The objective of this study was to understand nitrate dynamics and transport mechanisms during rainfall events in a typical mixed land-use karst catchment in Southwest China. High frequency (hourly) water sampling, discharge and hydrochemistry sensor data at a 15-minute interval were collected from a karst agricultural surface river over four rainfall events, spanning 40 days at the commencement of the wet season. The results showed that high [NH4+–N] (up to 3.12 mg L−1) and [PO43−– P] (up to 1037 μg L−1) were observed in the first rainfall event of the wet season, after a long preceding dry period. Increased [NO3−–N] also occurred during the high discharge associated with early event flows, but the highest [NO3−–N] concentrations (up to 14.9 mg L−1) were observed later in the season during the highest discharge events. All minima for dual nitrate isotopes were found during high discharge conditions and increased through the event time series. This indicates that nitrogen accumulated in the catchment prior to the commencement of the wet season and was flushed by the early rainfall events into the drainage system. Analysis of [NO3−–N], δ15N and δ18O-NO3− values indicate that denitrification, not assimilation, resulted in the high nitrate isotope values before and after rainfall events. According to source apportionment, chemical fertilizer, soil organic nitrogen, and manure and sewage, which varied with discharge, were the main sources of nitrate during rainfall events. The high proportion of nitrate from soil organic nitrogen suggested that soil loss from peak clusters and lowland farmland during heavy rainfall events should be paid more attention in karst area.

1. Introduction As one of the primary nutrients essential for the survival of all organisms, nitrogen plays a vital role in ecosystems. However, the excessive concentrations of active nitrogen (NO3−, NH4+, NO2−, etc.) in ecosystems due to anthropogenic activities has caused severe environmental degradation and ecosystem dysfunction, attracting attention from scientists and policy makers, particularly in agricultural systems (Sigler et al., 2018). High loads of nitrogen on the land surface can leach to groundwater or be transferred via rainfall to surface rivers, which can deteriorate the quality of drinking water and cause eutrophication (Zhang et al., 2015). Globally, nitrogen export by rivers

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from land to the ocean has increased more than 90 % during the last century and resulted in deterioration of water quality in coastal zones, and predictions are for a continued increase of nitrogen concentration in rivers, particularly in agricultural catchments (Beusen et al., 2016). Globally, agricultural practices, e.g. fertilization, contributed large amount of nutrients to surface water, which resulted in nearly half of the earth’s surface water quality was deteriorated by the agricultural non-point source pollution (Wang et al., 2019). This is more serious in karst area where water resources are inherently vulnerable to contamination and support drinking water for one quarter of the world’s population (Ford and Williams, 2007). Karst landscapes hence present a critical area to advance understanding of controls on nutrient

Corresponding authors at: Institute of Surface-Earth System Science, Tianjin University, Tianjin 300072, China. E-mail addresses: [email protected] (S.-L. Li), [email protected] (F.-J. Yue).

https://doi.org/10.1016/j.agee.2019.106787 Received 3 September 2019; Received in revised form 5 December 2019; Accepted 6 December 2019 0167-8809/ © 2019 Elsevier B.V. All rights reserved.

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Fig. 1. Position and land use of Dengzhan river catchment.

Previous work has found approximately up to 96 % of the annual nitrate flux from an agricultural karst catchment occurred during wet season, and that the nitrate flux increased sharply in the first several rainfall events of the early wet season (Yue et al., 2019). A catchmentwide survey conducted in SW China karst region showed that scientific advice is needed to improve the local land and water management (Oliver et al., 2020). To provide scientific advice for water quality management in karst surface rivers, nitrate sources and transformation processes occurring during intensive rainfall events need to be constrained and quantified (Eller and Katz, 2017). Although rainfall events are the main period for nitrogen export, there are only a few studies that focus on nitrate dynamics around rainfall events in karst catchments (Paul et al., 2015). To the author’s knowledge, no study has combined the dual nitrate isotope method and SIAR to trace nitrate sources and transformation processes in karst agricultural catchments during rainfall events in high resolution. In order to investigate nitrate dynamics in agricultural karst surface river during rainfall events, high resolution sampling spanning 40 days during the wet season and including multiple rainfall events of varying magnitude was carried out at Dengzhan (DZ) catchment outlet, SW China. The objectives of this study are: 1) to understand the relationship between nitrate dynamics and discharge in karst surface rivers; 2) to identify nitrate sources and estimate their contribution, and 3) to explore the main processes controlling nitrate dynamics during successive rainfall events.

dynamics, particularly in regions where wet season (more frequency rainfalls) was coincided with growing season with more fertilization practices. The wet season is considered a key period for fluvial solute transport because intensive rainfall increases the catchment hydrological conductivity, which accelerates solute transport (Penna et al., 2015). Moreover, this is of particular relevance to karst areas as the solute from soil can be transported directly to underground aquifers through karst sinkholes, conduits, fractures and fissures. Combined use of hydrological and hydrochemistry information has proven to be a useful method for analyzing nitrogen patterns in rivers (Mueller et al., 2016). However, these datasets do not allow for source apportionment, or elucidation of transformation processes. The nitrate dual isotope (δ15N and δ18O) approach is a powerful method to identify nitrate sources, such as wet deposition (WD), chemical fertilizer (CF), soil organic nitrogen (SON) and manure and sewage (M&S) in aquatic systems based on the characteristic nitrogen and oxygen isotope values of these sources (Liu et al., 2006; Kendall et al., 2007; Hu et al., 2019). Additionally, some abiotic and biotic processes consume or produce nitrate, which influences the isotope values of residual nitrate. For example, nitrate-consuming processes like assimilation and denitrification produce a “coupled” isotope effect, while nitrification, a nitrate-producing process, causes a “decoupled” isotope effect (Kendall et al., 2007). Recently, the nitrate dual isotope method combined with stable isotope mixing model analysis, e.g. Stable Isotope Analysis in R (SIAR), has provided a method to identify nitrate sources and transformations, as well as calculate source contribution (Kim et al., 2015; Jin et al., 2018). Due to its stable physical and chemical characteristics, chloride is a useful tracer of mixing of different water bodies and biological processes occurring in catchment water systems. Differences in chloride concentrations in runoff from different land-use types provides a method for water source apportionment, for example, due to high concentrations in agricultural runoff and sewage, and relatively low concentrations in rainwater and natural landscape runoff (Li et al., 2013; Yue et al., 2017). Trends in chloride coupled with nitrate concentration and isotope values can provide further constraint on nitrate sources. High nitrate levels have been reported in karst rivers in southwestern (SW) China, which is at the center of one of the three major continuous karst areas in the world (Jiang et al., 2009; Li et al., 2009).

2. Materials and methods 2.1. Study site The DZ river is located in Houzhai catchment (26°13′3″-26°15′3″N, 105°41′27″-105°43′28″E), a typical karst catchment and the site of a Karst Critical Zone Observatory in China. The river has a total catchment area of 11.0 km2, comprised of two head water catchments, Chenqi (CHQ) and Changchong (CC) catchments (Fig. 1). The surface elevation decreases from 1514 to 1258 m above mean sea level from northeast to southwest. The landscape is comprised of typical karst cone-depression landforms with conical hills and star-shaped valleys. The higher elevations of the conical hills are typically covered by forest, grass and shrubs, which has increased with the implementation of 2

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(Aqua TROLL 600 Multiparameter Sonde, USA) at a 15-minute interval, and discharge was derived from continuous water level measurements using a Hobo pressure transducer (Zhang et al., 2019). Nutrient concentration ([NO3−-N], [NH4+-N], [SiO32−-Si] and [PO43−-P]) were analyzed by an Auto-Analyzer (SKALAR Sans Plus Systems), and [Cl−] was analyzed with a Dionex ion chromatography (IC) 90 system (Dionex Corp, Sunnyvale, CA, USA). Dual nitrate isotopes (δ15N and δ18O) were derived using the denitrifying bacteria method (McIlvin and Casciotti, 2011). NO3− was converted to N2O and then analyzed with an isotope ratio mass spectrometer (IsoPrime, GV, UK). Four international nitrate standards (USGS-32, USGS-34, USGS-35 and IAEA-NO3) were used for calibration. The standard errors of the denitrifying bacteria method for δ15N-NO3− and δ18O-NO3− were 0.3‰ and 0.5‰, respectively. The δ15N-NO3− and δ18O-NO3− values of samples and nitrate sources were measured in the State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences. Isotope ratios are expressed as δ values and units defined as: δ (‰) = 1000 × [(Rsample/Rstandard)-1] where Rsample and Rstandard represent 15N/14N and 18O/16O ratios of the sample and standard, respectively. The N2 in air and Vienna Standard Mean Ocean Water are references for the 15N/14N and 18 O/16O, respectively. Nutrient flux (F) was calculated as the product of nutrient concentration and instantaneous discharge: F = ∑Ci × Qi Where Ci represents the nutrient concentration of sample collected at time i by auto-sampler and Qi represents discharge at time i.

initiatives to reforest and restore ecological functioning following widespread karst rocky desertification. The valleys are well-developed cultivated land covering nearly half the entire catchment area (48 %), with staple crops being rice, corn, rapeseed, and vegetables, and intensive fertilization occurs in May and early June every year. The most commonly used fertilizers for local farmers are urea, organic fertilizers and compound fertilizers. The DZ river flows through crop lands in the valley bottoms, supplying irrigation water. Recent work has detected high [NO3−-N] (> 10 mg L−1) in both CHQ and CC tributaries, which place DZ river at risk of eutrophication (Yue et al., 2019). The catchment has a subtropical wet monsoon climate with an average annual temperature of 20.1 °C. The highest and lowest temperatures usually occur in July and January, respectively. The annual rainfall in the local area over the past ten years (2008–2017) ranges from 732 to 1770 mm, with a mean value of 1218 mm. The annual rainfall in 2017 was 1172 mm, and the maximum daily rainfall was 100 mm, which occurred during the study period. Most rainfall events occur in the wet season (May to Oct.), which accounts for 85 % of the average annual rainfall. The sampling site is located in the lower reaches of DZ river. Flow in the two feeder tributaries, CHQ surface river and CC surface river, is highly seasonal. Water in these two tributaries flows mainly through underground conduits in the dry season (Nov. to Apr.), and through surface channels in the wet season into DZ river. 2.2. Sample collection Samples were collected by auto-sampler (TC-8000E-II, China) between 14th May and 23th June 2017 under different hydrological conditions with the time interval varying from one hour during the rising and falling limb of events to four hours during base flow. All water samples were stored in a refrigerator until analysis after being filtered through 0.45-μm cellulose-acetate membrane. Four intensive sampling periods (one sample per hour) were conducted over events occurring on the 23th May, 31th May, 5th June and 12th June, and are shown in gray in Fig. 2. There were two periods where data collection was interrupted, 19th - 21th May, and 7th - 12th June, due to water pumping for irrigation causing stream flow to cease.

2.4. Bayesian isotope mixing models The SIAR based on a Bayesian mixing model was developed by Parnell et al. (2010) to estimate the proportional contribution of nitrate sources. The mixing model can be represented as follows:

Xij =

K

∑k =1 Fk (Sjk + cjk ) + εij

2 Sjk ∼ N (μjk , ωjk )

2.3. Chemical analyses of water samples

2 cjk ∼ N (λjk , τ jk )

Dissolved oxygen concentration (DO), electrical conductivity (EC) and pH were measured in-situ with a hydrological chemistry sensor

εij ∼ N (0, σ 2j) where Xij is the measured isotope value j (j = 1, 2, 3,…, J;) of the mixture i (i = 1, 2, 3,…, N), Sjk is the source value k (k = 1, 2, 3,…, K) of isotope j and is normally distributed with mean μjk and standard deviation ωjk; Fk is the proportion of source k estimated by the SIAR model; cjk is the fractionation factor for isotope j in source k and is normally distributed with mean λjk and standard deviation τjk; and εij is the residual error representing the additional unquantified variation between individual mixtures and is normally distributed with mean 0 and standard deviation σj. Detailed description of the mixing model can be found in other paper (Parnell et al., 2010). 3. Results 3.1. Hydrological and hydrochemistry parameters The discharge at the sampling site during base flow (defined based on the site characteristics as Q < 0.01 m3 s−1) was approximately 0.7 L s−1, during the dry season and the commencement of the wet season. The first rainfall event (E1) occurred on the 22th May with peak discharge of 1 m3 s−1, and rainfall intensity of 24.6 mm h−1, which was relatively higher rainfall intensity than the other two events (E2 and E4 with rainfall intensity 18 mm h−1 and 9.4 mm h−1, respectively). The highest discharge of up to 14.2 m3 s−1 occurred during E3, which

Fig. 2. The time series of (a) [NH4+-N] and [PO43−-P], (b) [SiO32−-Si] and [Cl−], (c) DO and pH, (d) EC and discharge (Q) in DZ river in 2017. The four shaded areas numbered four rainfall events. 3

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Table 1 The isotopic composition of nitrate sources in the study catchment. Potential sources (n)

δ15N-avg. (‰)

δ15N-std. (‰)

δ18O-avg. (‰)

δ18O-std. (‰)

WD (10) SON (16) CF (6) M&S (5)

−7.2 7.3 0 14.5

1.7 1.1 1.4 4.0

60.8 −2.3 −2.3 −2.8

5.3 0.6 0.6 4.5

Fig. 3. The time series of (a) NO3−-N, (b) δ15N-NO3− and (c) δ18O-NO3− in DZ river.

occurred on 12th June, with a total rainfall amount and rainfall intensity of 89 mm and 41.8 mm h−1, respectively. The pH and DO showed regular diurnal variation during the base flow period, with pH values ranging from 7.60 to 8.60, and DO values from approximately 0–20 mg L−1 (Fig. 2c). Low values of pH and DO occurred at dawn, while high values occurred in the early evening. The diurnal variation was interrupted during E1, E3 and E4, and resumed after the events. In contrast to pH and DO, EC fluctuated before E3, then remained relatively stable from E3 to the end of the sampling period (Fig. 2d).

Fig. 4. Flux of NO3−-N, NH4+-N and PO43−-P during the sampling period.

3.4. Nutrient flux during rainfall events There was wide variation in NO3−-N flux between base flow and high discharge periods associated with rainfall events, ranging from 1 mg s-1 to 147 g s−1 (Fig. 4). The lowest NO3−-N fluxes were detected during base flow, while the highest flux (147 g s−1) was detected during E3, when high flux is continuous for three days. The NH4+–N and PO43−– P fluxes showed same fluctuation with NO3−-N flux ranging from 20 μg s−1 to 3.0 g s−1, and PO43−– P from 23 μg s−1 to 1.69 g s−1, respectively.

3.2. Nutrients concentration The [NO3−-N] ranged from 0.5–14.9 mg L−1 (Fig. 3a), with the lowest values being detected during base flow and the peak values during E3. Large fluctuations in [NO3−-N] occurred during E1, E2, E3 and E4. Most samples had very low [NH4+-N], nearly at the detection limit (Fig. 2a). Two peaks in [NH4+-N] occurred during E1 and E2, 2.74 and 3.12 mg L−1 respectively. [NH4+-N] showed a fast response to changes in discharge. The relatively high [NH4+-N] that occurred during E1 and E2 was only sustained for a few hours. [PO43−-P] showed a wide range from 15.6–1037 μg L−1. Low concentrations occurred during the base flow period and two large fluctuations in [PO43−-P] occurred during E1 and E2, with maximum concentrations of 880 μg L−1 and 1037 μg L−1, respectively (Fig. 2a). [SiO32−-Si] showed the same trend as [NO3−-N], with a range from 0.2–3.8 mg L−1. [Cl−] remained at about 20 mg L−1 during base flow, and showed an obvious dilution effect during rainfall events, with the lowest value (7.2 mg L−1) occurring during E4 (Fig. 2b).

4. Discussion 4.1. Nutrient patterns and transport mechanisms during rainfall events Nutrient concentration changing dramatically during rainfall events has been widely reported across different land use types (Mourad and Perk, 2009; Tondera et al., 2018). In the present study, [NH4+-N] and [PO43−-P] followed very similar trends during the sampling period; both [NH4+-N] and [PO43−-P] increased during events and then declined rapidly. Similar trends have been observed in agricultural surface rivers in other studies (Royer et al., 2006; Yue et al., 2015), but the maximum concentrations observed in this study are the highest reported, indicating very high nutrient loading in the study area. During E1 and E2, both [NH4+-N] and [PO43−-P] showed a significant increase, which may result from these events coinciding with fertilizer application, resulting in high source availability of both N and P in the study area (Buckerfield et al., 2019a; Peng et al., 2011). After E2, [NH4+-N] and [PO43−-P] concentrations remained at low levels through several consecutive rainfall events (E4 and several subsequent events), indicating these solutes were subject to a flushing effect in E1 and E2 and a dilution effect during other events. The high concentration and loading flux of NH4+-N and PO43−-P indicated that their transport was driven by rainfall, and also that karstic aquatic systems are at high risk of pollution with these contaminants. The long period of dry antecedent conditions prior to E1 and E2 would also have facilitated the formation of soil aggregates, which adsorb NH4+-N and PO43−-P, and enhance NH4+-N and PO43−-P accumulation in soil. Timing of rainfall events relative to source availability hence seems to be a critical control on NH4+-N and PO43−-P loading to the drainage

3.3. Dual nitrate isotope values Dual nitrate isotope (δ15N-NO3− and δ18O-NO3−) values ranged between 3.1‰ and 21.2‰, and -2.1‰ and 8.3‰, respectively. The δ15N-NO3− and δ18O-NO3−showed opposite fluctuations to [NO3−-N] during events (Fig. 3). High isotopic values were detected before the rainfall events, i.e. during base flow, when the [NO3−-N] was low, while low isotope values occurred in samples with high [NO3−-N] during the rainfall events. The nitrogen endmember samples were collected in CHQ catchment; M&S had the highest average δ15N (14.5‰), and lowest average δ18O (-2.8‰), while WD had the lowest average δ15N (-7.2‰) and highest average δ18O (60.8‰). The average and standard deviation of all sources are shown in Table 1. 4

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Fig. 5. The relationship between [NO3−-N] and Q during four rainfall events.

nutrients stored on the surface and in the upper soil profile in karst terrain have been shown to migrate via piston flow through the soil matrix, or more rapidly through macro-pores, before reaching the aquifer fractures and eventually conduits of the aquifer, where more rapid transport to springs and the surface water system can occur (Peterson et al., 2002). During heavy rainfall events, nutrients can be flushed directly into surface rivers by overland flow, which could be one of the factors explaining the high nitrate concentrations observed during E3. If the fissure and conduit network become saturated during continuous rainfall, low intensity rainfall events could also produce surface runoff. This process may have occurred during E4, which occurred 7 days after the large volume of rainfall that characterized E3.

system. A positive correlation (R2 = 0.82, p < 0.01) between [NO3−-N] and [SiO32−-Si] was detected in water samples, which suggests a shared source for these nutrients. Unlike the fast response of [NH4+-N] and [PO43−-P] during rainfall events, the [NO3−-N] and [SiO32−-Si] had longer response times, lagging behind discharge. The [NO3−-N] and [SiO32−-Si] peaked on the hydrograph recession and then decreased at a slower rate than [NH4+-N] and [PO43−-P] after the event (Figs. 2 and 5). Chemical weathering (silicate weathering, etc.) and biological processes (litter and organic fertilizer decomposition) are the two main sources of Si (Struyf et al., 2010). As the lack of silicate rocks in DZ catchment, the dissolved Si should be derived from the weathering of silicate-containing minerals in soil or biological processes (Wang et al., 2010). This suggests the SiO32−-Si and NO3−-N mainly origin from soil or organic fertilizers in soil. The dynamics of [SiO32−-Si] suggest that rainfall events can significantly elevate [SiO32−-Si] by flushing and promote the transportation (Wang et al., 2010). Compared to the dynamic of [SiO32−-Si], [NO3−-N] was more sensitive to rainfall, with even small rainfall events (E1 and E2) resulting in large fluctuations (Fig. 5). High concentrations (> 10 mg L−1) and small-scale fluctuations in [NO3−-N] were detected in the intensive rainfall event (E3), with a decreasing trend in [NO3−-N] after this heavy rainfall event (Fig. 5c). The highly developed underground conduit system in karst areas results in rapid transport between the surface and groundwater systems. Hydrological studies in karst areas have shown that most rainfall from low intensity events (< 30 mm h−1) moves through subsurface hydrological pathways, generating subsurface lateral flow and underground fissure flow, while surface runoff generally occurs only during heavy storms (rainfall intensity > 30 mm h−1) (Peng and Wang, 2012). Due to the variation in water runoff/infiltration mechanisms with different rainfall intensities, nutrient dynamics between rainfall events are also likely to vary. During successive lower intensity events, the

4.2. Nitrate transformations during the sampling period Although rainfall events drive nutrient transport, biological processes influence nitrogen transformation. Nitrification, denitrification and assimilation are the three main processes controlling nitrogen dynamics directly in eco-systems, but the processes of fixation, mineralization and volatilization are also part of the nitrogen cycle. Fixation usually occurs in the upper layer of water bodies with long retention times, like reservoirs, lakes and oceans, and has little effect on headwaters (Xia et al., 2018). As the present study mainly focused on rainfall events with a short retention time, the influence of fixation on nitrogen concentration and isotope values in the feeder tributaries can be ignored during event flow. The regular diurnal variation of dissolved oxygen and pH values during base flow indicate assimilation was occurring due to large amounts of aquatic plants and phytoplankton growing in the river. In addition, high nitrate and phosphorus concentration in the water leads to eutrophication, which promotes further assimilation (Yang et al., 2008). The large quantities of organic fertilizer and manure applied to crops in the catchment mean mineralization and nitrification are likely 5

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4.3. Sources of nitrate in storm-water runoff

to be the most important processes in the nitrogen cycle. During nitrification, an oxygen atom from oxygen gas and water combines with a nitrogen atom in the ratio 1:2 (Mayer et al., 2001). The δ18O of the water samples collected from CHQ sub-catchment during the sampling period ranged between -10.6 and -5.1‰ (Chen et al., 2018), which suggests the theoretical oxygen isotope values of nitrate derived from nitrification lie between 0.8 and 4.4‰. Most samples had δ18O-NO3− values within this theoretical range of oxygen isotope values (Fig. 7b), indicating nitrification was the primary transformation process occurring. However, many samples had δ18O-NO3− values below or above the theoretical range, which may result from the O exchange during nitrification, or other transformations, such as denitrification and assimilation. Denitrification and assimilation, which are the two primary N-uptake processes, can cause enrichment factors of δ15N and δ18O of 2:1 and 1:1 respectively (Kendall et al., 2007; Granger et al., 2010). Previous studies have found enrichment factors in groundwater from 1.3:1 to 2.1:1, showing evidence for denitrification in sub-surface anaerobic environments (Fukada et al., 2003). The enrichment factor of four samples collected from an underground river outlet along CC tributary (Fig. 1) was 1.5:1 (Fig. 6), and the δ15N and δ18O values of CHQ and CC tributaries before their confluence were nearly equal to the values of rainfall at the sampling site on DZ river. This indicates that denitrification occurring in the underground conduits of DZ catchment is probably the primary reason for the high δ15N and δ18O values found during base flow, and the increasing trend of δ15N and δ18O values after events. Denitrification also occurs in the riparian zone through which water from the catchment passes before reaching rivers. Nitrates altered by denitrification in the riparian zone that are then leached into the river after rainfall events are enriched in 15N (Kellman and Hillaire-Marcel, 2003). Denitrification resulting in elevated nitrate isotope values of river waters has also been found in karst agricultural catchments in France (Paul et al., 2015) and USA (Panno et al., 2001). As a surface river with large amounts of algal growth, assimilation will be occurring in DZ, but there appears to be no significant influence on nitrate concentration and isotope values. In this context, denitrification occurring in the underground system is hence likely to be the primary reason for the high nitrate isotope values in DZ river during base flow. Especially when the surface of the saturated zone (the phreatic zone) rises during prolonged rainfall events in karst, the underground system may provide an anaerobic environment for denitrification, which would explain the decreasing [NO3−-N] and increasing dual nitrate isotope values after the inflection point in all four rainfall events.

Source identification using dual nitrate isotopes and chloride signatures (Fig. 7a) suggests that multiple sources contributed nitrate to DZ river during rainfall events. M&S usually contains a high concentration of nitrate and chloride and relatively high isotope values (6 to 25‰), while CF usually contains more nitrogen than chloride and has low nitrate isotope values (-4 to 4‰) (Kendall et al., 2007). The dual nitrate isotopic signatures (Fig. 7b) indicate that CF, SON and M&S are the major nitrate sources to DZ river during the sampling period. Previous work has found transformation usually has little effect on nitrate concentration and isotope values during high discharge associated with large rainfall events (Sebestyen et al., 2008). Hence the isotopic fractionation caused by biological processes such as denitrification will be non-significant during high discharge periods. Consequently, samples, in particular event samples, can reflect nitrate source information more directly. Thus, nitrate source contribution can be estimated using SIAR for the four rainfall events. The results suggested that the contributions from CF, SON and M&S accounted for at least 93 % of nitrate to DZ river during the rainfall events (Fig. 8). Previous study has concluded WD is the main nitrate source during rainfall events (Buda and DeWalle, 2009), but the results of this study suggest WD constituted a low contribution (less than 10 %) during rainfall events. This is also supported by the relatively low nitrogen concentration in WD within Houzhai catchment (Zeng et al., 2019). The nitrate concentration in the present study samples is several times (5–30) higher than rainwater samples indicating a high flux of nitrate from other sources, which is consistent with the SIAR estimation of a low contribution from WD. The time series of δ15N-NO3− show that the high [NO3−-N] during rainfall events corresponded with low δ15NNO3− values, ranging from 2 to 8‰, which further supports SON or a mixture of CF and M&S being the main nitrate sources. The SIAR results suggested that SON was the predominant and persistent nitrate source in this karst agricultural catchment. This is more significant during E1 and E2. Furthermore, the high yield of sediment discharge from karst peak cluster and lowland area during the highly intensive rainfall events was potential reason of high contribution from SON (Peng and Wang, 2012; Li et al., 2017). Recently studies found that karst fissures can store water and nutrient sources and gradually release them (Yue et al., 2019; Zhang et al., 2019), which may increase the SON contribution during later rainfalls. Additionally, compare to subterraneous stream, the sediment discharge by soil loss during heavy rainfall events was more concentrated in surface stream. The high areal proportion of paddy field and slope farmland would significantly increase the nutrient flux of catchment by surface stream during rainfall events as rich nitrogen in farmland soil (Wang et al., 2014).

Fig. 6. The relationship between (a) δ15N-NO3− and δ18O-NO3−, (b) ln [NO3−-N] and δ15N & δ18O of four samples along CC tributary (solid triangle), the solid circle represented the samples collected from DZ river on the same day. 6

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Fig. 7. The relationship between (a) δ15N-NO3− and NO3−/Cl−, (b) δ15N-NO3− and δ18O-NO3−. The gray shade area represents theoretical δ18O ranges produced by nitrification.

Fig. 8. Nitrate sources contribution calculated by SIAR during four rainfall events monitored in this study. Three color box plots from deep to shallow representing 25 %, 75 % and 95 % credibility interval, respectively.

contribution of M&S in E4.

CF contributed less nitrate during E1 and E2 (13 % and 11 %) but more during E3 (39 %) and E4 (27 %), suggesting that high rainfall increases CF leaching and transport to the drainage network from farmland areas. Nitrate derived from CF can be quickly flushed from farmland into rivers during high rainfall events when overland runoff occurs, as has been observed in many agricultural contexts (Wang and Zhu, 2011). Although manure is not the main nitrogen fertilizer in this area, the slow rate of nitrogen transformations such as mineralization and nitrification cause long retention times in agricultural soils, which is reflected in fecal contamination detected in drainage networks a long time after fertilization (Buckerfield et al., 2019b). For example, the SIAR model calculation suggests M&S contributed about one fifth of the nitrate to DZ river during the first three rainfall events. The continuous leaching of nitrate from M&S probably resulted in a diminishing contribution with successive events, which would explain the lower

4.4. Implications for nitrogen control in karst river catchments High [NO3−-N] above the drinking water limit (10 mg L−1) set by the Chinese Surface Water Environmental Quality Standards (GB38382002) was detected during rainfall events, particularly the heavy rainfall event where overland flow occurred (E3). The strong positive correlation between NO3−-N flux and discharge (R2 = 0.98, p < 0.01) indicates that rainfall events were the key periods for NO3−-N export in this study. Large amounts of NO3−-N export to surface rivers also leads to elevated [NO3−-N] in groundwater from farmland, due to rapid exchange between the surface and groundwater systems in the karst critical zone. This results in deterioration of both surface and groundwater quality. 7

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References

The sources contribution calculation implied that soil erosion in peak cluster and lowland farmland should be pay more attention on runoff and overland flow during rainfall events. In addition, fertilization of farmland should also be concerned as it may responsible for the rapid increase in [NO3−-N] during rainfall events. China used one third of global fertilizers (Ju et al., 2009; Wang et al., 2020), the low efficiency of fertilizer would deteriorate the water quality, particularly in karst area with more exchange between surface and underground (Tan et al., 2015). Thus, rough fertilization methods should avoid, and scientific fertilization method must consider the climate factor and the special hydrogeological structure in the present karst area. The careful timing of fertilization during the wet season may be useful in decreasing [NO3−-N] and improving the water quality during rainfall events. Changes in land management have been shown to produce significant reduction of stream nitrate concentration in some agricultural settings (Casal et al., 2019). In this karst setting, measures such as distributing farmland with high fertilization rates at a maximum possible distance from sinkholes could reduce the direct transport of fertilizer via overland flow into sinkholes and subsequently groundwater aquifers. In addition, increasing the amount of organic and slow-release fertilizer, with a longer fertilization effect, and spreading sufficient amounts of mulch are also practices that can reduce [NO3−-N] in surface waters. Reducing the areal proportion would improve soil and nutrient loss during rainfall events. In addition, knowledge exchange among farmers, scientists and policy maker also can useful for the karst environment management and improvement of agroecosystems (Oliver et al., 2020).

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5. Conclusion In this study, continuous sampling of a surface river in a karst agricultural catchment over the first 40 days of the wet season was used to explore the dynamics of nutrient transport within karstic surface rivers during rainfall events. Dual nitrate isotope analysis showed denitrification was the main reason for high nitrate isotope values during base flow periods and increasing nitrate isotope values after rainfall events. The diurnal variation of pH and DO indicates assimilation occurs in the surface river, but due to the input of nitrate from tributaries, [NO3−-N] at the sampling site didn’t show significant evidence of an assimilation effect. Source apportionment results indicated SON, CF and M&S are the main nitrate sources in the study catchment. Bayesian mixing model results indicated that SON contributed most nitrate during rainfall events, except for one heavy storm where overland flow occurred. Fertilizer is usually applied directly to croplands, meaning applied fertilizer will be flushed directly into surface rivers when overland flow is generated. Strategic fertilization regimes, both in terms of timing, method, and quantity of application, and planning of the spatial layout of farmland taking into account the karstic hydrology is advised to control nitrate leaching and reduce the occurrence of high nitrate concentrations in karst rivers.

Declaration of Interest Statement The authors declare no competing financial interest. Acknowledgements We thank editor and two reviewers for their constructive comments. This work was supported by the National Natural Science Foundation of China [grant numbers 41571130072, 41861144026]; the National Key R&D Program of China [grant number 2016YFA0601002]; the Independent Innovative Foundation of Tianjin University [grant number 2019XZS-0016] and UK Natural Environment Research Council [grant number NE/N007425/1]. 8

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