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Nitrogen and phosphorous concentrations in runoff from a purple soil in an agricultural watershed
Agricultural Water Management 97 (2010) 757–762
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Agricultural Water Management journal homepage: www.elsevier.com/locate/agwat
Nitrogen and phosphorous concentrations in runoff from a purple soil in an agricultural watershed J.G. Han a,b,*, Z.B. Li c,d, P. Li c, J.L. Tian d a
School of the Environment, Jiangsu University 72#, Xue Fu Road 301, Zhenjiang 212013, Jiangsu, China Key Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education and Jiangsu Province, Jiangsu University, Zhenjiang 212013, Jiangsu, China c Xi’an University of Technology, Xi’an 710048, Shaanxi, China d Institute of Soil and Water Conservation, CAS & MWR, Yangling 712100, Shaanxi, China b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 1 April 2009 Accepted 12 January 2010 Available online 1 February 2010
Nutrient loss from purple soils has been reported to increase pollution of the Yangtze River. However, few studies have addressed the variations of nutrient concentration in runoff during natural rainstorms in the regions. Nitrogen and phosphorus concentrations in runoff waters from a small agricultural watershed, in the purple soil region of southwest China, were investigated for four natural rainstorms occurred in a conventional double cropping system (wheat–corn) and another six rainstorms in a new triple cropping system (wheat–corn–sweet potato). The NO3 concentrations in runoff for the observed rainstorms generally varied from 1.0 to 3.5 g m3, which were noticeably affected by flow rates. A significant logarithmic correlation between NO3 concentrations and flow rates for each rainstorm was identified. In contrast, the concentrations of NH4+ and dissolved reactive phosphorus (DRP) in runoff fluctuated substantially without a noticeable trend for each rainstorm. Positive linear correlation between the concentrations of DRP and sediment for each rainstorm tested was found under the circumstances of double cropping system. In addition, the ratios of NO3 to NH4+ for the loss amount in 10 rainstorms varied from 1 to 7 for the triple cropping system and 16–29 for the double cropping system. Furthermore, the ratios of the sum of NO3 and NH4+ to DRP for the loss amount in 10 rainstorms ranged from 12 to 79 depending on the cropping systems. Nitrate nitrogen was proved to be the main form of inorganic nitrogen loss in runoff water in the purple soil region. Compared with the conventional double cropping system, the new triple cropping system tends to cause more NH4+ loss. These findings would help develop the effective erosion control strategies and select a suitable cropping system to reduce potential pollution hazards. ß 2010 Elsevier B.V. All rights reserved.
Keywords: NO3 NH4+ Dissolved reactive phosphorus Runoff Purple soil
1. Introduction Purple soil, formed from purple rock series of the Trias– Cretaceous system, or their weathering products, is mainly distributed in the Sichuan Basin, one of the most important agricultural areas of southwest China. Purple rocks are characterized by fast physical weathering, and are broken up by anthropic activities into rock fragments or gravels, in which crops are directly planted (Wei et al., 2006). Unplanned reclamation and land use patterns have accelerated water, soil and nutrient losses. These losses have direct negative effects on land productivity; and additionally, increase pollution and siltation of the Yangtze River, causing problems downstream (Li et al., 2009).
* Corresponding author at: School of the Environment, Jiangsu University 72#, Xue Fu Road 301, Zhenjiang 212013, Jiangsu, China. Tel.: +86 13511690975. E-mail addresses: [email protected], [email protected] (J.G. Han). 0378-3774/$ – see front matter ß 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.agwat.2010.01.007
Nitrogen loss in runoff water is mainly lost as NO3 and NH4+ (Udawatta et al., 2006). In addition, some NH4+ could also be transported with eroded soil material combined with phosphorus (Ramos and Martı´nez, 2004). Zhu et al. (2006) estimated that soil nitrogen was lost at an average rate of 44.34 kg ha1 year1 in the purple soil regions. Surface and subsurface hydrological pathways were considered to contribute to nutrient transport depending on rainfall amount (Liu et al., 2002), topography and flow rate (Cao et al., 2003). Understanding the variations of nutrient concentration in runoff during various rainstorms is very helpful in improving the current erosion model, which would facilitate selecting a management practice that could effectively control the potential pollution hazards in a watershed. However, there is insufficient knowledge of such variations in the purple soil regions, particularly for the circumstances under natural rainstorms. Nutrient loss is heavily influenced by farming practices and cropping system under agricultural land use. Buffer zones and year-round vegetated fields have therefore been introduced as measures to reduce soil erosion and the phosphorus load in runoff
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waters. However, Turtola and Paajanen (1995) and Risto et al. (2000) found these measures tended to increase the loss of dissolved reactive phosphorus (DRP). Udawatta et al. (2006) suggested that the maintenance of a suitable vegetative cover throughout the year could reduce runoff and lower total nitrogen and NO3 losses from agricultural watersheds under a corn– soybean rotation. Jia et al. (2007) found that rainstorms after urea application probably increased NH4+ losses but had little effect on NO3 loss in the surface hydrological pathway. However, there are no detailed data available for the purple soil region, the soil of which is not favorable for erosion control. The objectives of this study were to investigate the concentration variations of NO3, NH4+ and DRP in runoff waters during natural rainstorms, and to compare the impacts of the two cropping systems, a conventional wheat–corn double cropping system and a new wheat–corn–sweet potato triple cropping system, on the nutrient losses in an agricultural watershed. 2. Materials and methods 2.1. Site description The experiment was carried out in a small agricultural watershed, Xujiawan, in Zi-Yang City (30.198N, 104.68E) of the Sichuan Province, China. The region is mainly covered by red or purple rock, from which the purple soils are developed and formed (He, 2003; Wei et al., 2006). The landscape is characterized by hilly mountains with elevations of 395–475 m. The climate is subtropical with an annual mean temperature of 17.3 8C, and an annual mean rainfall of 961 mm, more than 80% of which falls from May to October. The purple soil is classified as Udorthent based on USDA taxonomies (He, 2003). The soil depth is shallow, but the soilforming speed is fast. The clay minerals include hydromica, montmorillonite, and chlorites of 2:1 type. The content of cation exchange capacity ranged from 18.4 to 26.4 cmol+ kg1. The average sand (2–0.05 mm), silt (0.05–0.002 mm), and clay (<0.002 mm) contents are 143.8 29.7, 636.3 28.8, and 219.9 16.3 g kg1, respectively. The watershed is about 10.8 ha, with 7.9 ha of sloping land and 2.9 ha of valley land. Of the sloping land, 2.2 ha is used as farming land, 3.2 ha as woodland, 2.1 ha as wasteland and 0.4 ha as garden plots. The valley land consists of farmland (2.0 ha) and garden plots (0.9 ha). The region is sparsely populated and specific point-source pollution sites are not known. 2.2. Cultivation system and farming practice There are two cultivation systems and the corresponding farming practices investigated in the purple soil region were: a conventional wheat–corn double cropping system and a new wheat–corn–sweet potato triple cropping system. The new triple cropping system is currently being promoted extensively due to the high year production. To compare the impacts of these two
Table 1 The farming practices in 1999–2000. Year
Farming practice
1999
Wheat: sown and base fertilizer applied 16 Oct; seedling fertilizer applied 13 Feb; harvested 11 May. Corn: sown and base fertilizer applied 4 and 14 May, respectively; additional fertilizer applied 10 Jun and 3 Jul; harvested 6 Aug. Sweet potato: planted and base fertilizer applied 12 Aug; additional nitrogen applied 21 Aug; nitrogen and potassium applied 10 Sep; harvested 12 Oct.
2000
Wheat: sown and base fertilizer applied 14 Sep; seedling fertilizer applied 20 Feb; harvested 7 May. Corn: sown and base fertilizer applied 16 May; additional fertilizer applied 26 Jun and 30 Jul; harvested 21 Aug.
cultivation systems on nutrient loss, the triple cropping system and the conventional double cropping system were therefore implemented in 1999 and 2000, respectively. The main farming practices are listed in Table 1. The fertilizer rates were determined based on the averaged soil test results. 2.3. Rainstorm characteristics Automatic rain gauges were used to monitor rainfalls in 1999– 2000. The rain gauge has a resolution of 0.199 mm m2. This means that every time 0.199 mm of rain has fallen, the moment this happens will be recorded by the data logger inside the gauge. In 23 rainstorms observed in 1999, six events accounted for 44% of the annual rainfalls. In 11 rainstorms observed in 2000, four events made up 54% of the annual rainfall. These 10 events were selected to investigate the concentration variations of NO3, NH4+ and DRP in runoff water (Table 2). The average rainfall intensity, Iaver (mm h1), was calculated as Ia ¼
P D
(1)
where P (mm) was the rainfall for an event and D (h) was the rainfall duration. 2.4. Water sampling and analysis A flume was devised and constructed at the outlet of the watershed, which provided a means for determining a relationship between water level and the amount of water flow (Fig. 1). The water level was measured at a certain position above the flume by an ultrasonic flow sensor, which was connected to a water sampler (ISCO-6700). Every 2 min the data logger inside the sampler did a water level measurement. The water sampler converted the level measurements to flows. Within the data logger program, a flow value was predefined to trigger a sampling. When the set value was reached, the data logger sent a signal to the sampler. The sampler collected water samples from the flume using a suction tube and a tube pump. The individually collected samples were placed in
Table 2 Rainstorm characteristics. Event
Rainfall (mm)
Durationa (h)
Iaverb (mm h1)
Event
Rainfall (mm)
Duration (h)
Iaver (mm h1)
9 Aug 1999 10 Aug 1999 16 Aug 1999 28 Aug 1999 13 Sep 1999 18 Sep 1999
55 23 30 69 61 64
8.0 1.0 3.0 12.0 9.0 11.0
6.9 23.0 10.0 5.8 6.8 5.8
23 Jun 2000 7 Jul 2000 11 Aug 2000 17 Aug 2000
48 37 48 138
8.0 4.0 6.5 12.0
6.0 9.3 7.4 11.5
a b
The beginning and the end of each rainstorm were determined according to the records of automatic rain gauges. The average rainfall intensity.
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every runoff event the nutrient concentration values were used to construct a nutrient concentration vs. time graph. This graph and the runoff hydrograph were then divided into small segments. For each segment, the nutrient loss was calculated by multiplying segment runoff volume and nutrient concentration. The total nutrient loss during a runoff event was calculated by adding these segment values. 3. Results and discussion
Fig. 1. Flume construction: (a) water sampler; (b) ultrasonic flow meter; (c) sampling tube; (d) flume wall; (e) power supply unit.
separate flasks inside the device, which had a 24-bottle carousel, each bottle with a volume of 1 l. The device could store measurement data of the ultrasonic flow sensor, as well as the time a sample was taken. Each water sample was split into runoff and sediment subsamples by filtration. The runoff sub-samples were put into a plastic bottle, in which 0.5 ml of 98% H2SO4 was added to suppress microbial activity. These samples were kept at 4 8C for subsequent measurements. NO3 and NH4+ concentrations were analyzed colorimetrically using a flow injection analyzer (Lu, 2000). DRP was determined by colorimetric ascorbic acid reduction method (Lu, 2000). The sediment sub-samples were dried at 45 8C for 12 h and then weighed to compute sediment concentration. 2.5. Nutrient losses Each runoff sample and its nutrient concentration represented a particular time and segment of the runoff hydrograph, thus for
Fig. 2. NO3 concentration variations with time during the courses of two runoff events.
In order to ascertain the variations of nutrient concentrations in runoff water in various rainstorms, the nutrient concentrations were plotted against time. The time scale was calculated as a multiple of time to peak runoff rate (Tp). This provided comparisons of nutrient concentration variations between storms in relation to their Tp and it provided a more uniform scale for comparing different rainstorms with extreme variations in runoff durations (Pathak et al., 2004). 3.1. Changes in NO3 concentrations for different runoff events Fig. 2 shows the NO3 concentrations and flow rates with time for two runoff events. There was a similar increasing trend during the period of decreasing flow rates, after the time of 1.0 Tp (time to peak runoff). To clarify how NO3 concentrations varied during the course of a runoff event, NO3 concentrations from 10 runoff events of various sizes were plotted in Fig. 3. The NO3 concentrations gradually increased during periods of decreasing flow rate (generally after 1.0 Tp). This was likely the result of the contributions of subsurface runoff as described by Jia et al. (2007), who investigated the nitrogen losses associated with surface and subsurface runoff under artificial rainfall simulation and confirmed that large amounts of subsurface runoff through macropores could increase the loss of NO3. In contrast, the NO3 concentrations tended to decrease during the period of increasing flow rates (generally before 1.0 Tp). These observations differed from the findings of Li et al. (1998), who reported that inorganic nitrogen ran off at an almost constant concentration under a natural rainstorm in the region. In addition, the NO3 concentrations in runoff water were generally 1.0–3.5 g m3 (Fig. 3). However, there were apparently higher NO3 concentrations observed during the event of 23 June 2000. This observation could be due to the fact that this event was the first erosive rainstorm in 2000. Large amounts of NO3 may have accumulated in the soil surface layers during a prolonged dry period, and subsequently been lost with the initial rainstorm. This was in agreement with the observations of Holloway et al. (2001), who used fresh rock and weathered material to simulate nitrogen release
Fig. 3. Change in NO3 concentrations as a function of the time to peak runoff rates (Tp) for different runoff events.
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Table 3 The relationships between NO3 concentrations and runoff flow rates. Event
Tp rangea
Fitting equation: C NO3 ¼ a ln W þ b
b
9 Aug 1999 10 Aug 1999 16 Aug 1999 28 Aug 1999 13 Sep 1999 18 Sep 1999
0.5–1.5(24) 0.3–3.0(23) 0.4–2.1 (22) 0.8–1.3(15) 0.6–1.0(24) 0.4–1.2(24)
23 Jun 2000 7 Jul 2000 11 Aug 2000 17 Aug 2000
0.7–1.5(21) 0.8–1.5(12) 0.8–1.4(21) 0.8–1.0(12)
a
b
R2
0.67 2.09 16.03 0.90 0.71 2.12
1.02 2.51 4.05 0.08 0.04 2.49
0.735** 0.801** 0.705** 0.708** 0.556** 0.934**
2.38 2.16
1.10 2.53 / 1.81
0.903** 0.502**
0.25
0.901**
NO3
C NO3 : concentration; W: runoff flow rate. a Tp, time to peak runoff rate. Tp range denotes the range of samplings, which was expressed as a multiple of Tp. b Digits in parentheses indicates the number of observations during the range. The symbol ‘‘/’’ means no significant relationship. ** P < 0.01.
from rock and soil under field conditions, and confirmed that geologic nitrogen might be a large and reactive pool that might contribute as a non-point source of NO3 contamination to surface and groundwater. Moreover, the relationships between NO3 concentrations and flow rates were analyzed, and logarithmic correlations for nine events were identified (Table 3). This provided useful information for the prediction of NO3 loss by runoff. 3.2. Changes in NH4+ and DRP concentrations for different runoff events The concentrations of NH4+ and DRP in runoff waters fluctuated substantially and varied differently with time than the NO3 concentrations without a noticeable trend (Fig. 4). This differed from
Fig. 5. Change in NH4+ (top) and dissolved reactive phosphorus (DRP) (bottom) concentrations as a function of the time to peak runoff rates (Tp) for different runoff events.
the results of Li et al. (1998), who reported that both NH4+ and DRP concentrations did not fluctuate widely and high concentrations were observed only in the initial period of runoff. The difference could be due to the fact that the experiments of Li et al. (1998) were conducted on a slope. In addition, neither correlation was found between NH4+ concentration and flow rate, nor there was a correlation between DRP concentration and flow rate. Fig. 5 showed the variations of NH4+ and DRP concentrations during the 10 rainstorms, and the respective concentrations were 0.04–1.70 and 0.03–0.50 g m3. These ranges differed, possibly due to the different natures of NH4+ and DRP ions, which may, to various degrees, be adsorbed on, or released from, the soil particle
Fig. 4. NH4+ (top) and dissolved reactive phosphorus (DRP) (bottom) concentration variations with time during the runoff event of 10 August 1999.
Fig. 6. Change in sediment concentrations as a function of the time to peak runoff rates (Tp) for different runoff events.
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Table 4 The relationships between the concentrations of NH4+, DRP and sediment. Tp rangea
Event
Fitting equation C NHþ 4
C NHþ ¼ aC s þ b
CDRP = aCs + b
4
9 Aug 1999 10 Aug 1999 16 Aug 1999 28 Aug 1999 13 Sep 1999 18 Sep 1999
0.5–1.5(24)b 0.3–3.0(23) 0.4–2.1 (22) 0.8–1.3(15) 0.6–1.0(24) 0.4–1.2(24)
23 Jun 2000 7 Jul 2000 11 Aug 2000 17 Aug 2000
0.7–1.5(21) 0.8–1.5(12) 0.8–1.4(21) 0.8–1.0(12)
a
b
R2
0.04 0.06 0.01
0.48 0.33 0.25 / / /
0.477** 0.683** 0.230*
/ 0.13 / /
0.01
a
R2
b / / / / / /
0.02 0.01 0.01 0.01
0.511**
0.555** 0.903** 0.787** 0.688**
0.01 0.05 0.02 0.04
C NHþ : NH4+ concentration; CDRP: DRP concentration; Cs: sediment concentration. a 4 Tp, time to peak runoff rate. Tp range denotes the range of samplings, which was expressed as a multiple of Tp. b Digits in parentheses indicates the number of observations during the range. The symbol ‘‘/’’ means no significant relationship. * P < 0.05. ** P < 0.01.
Table 5 The average nutrient concentrations in runoff and the loss amounts for each rainstorm observed in 1999–2000. Event
Tpa (min)
Tp rangeb
Aver. sd (g m3) 9 Aug 1999 10 Aug 1999 16 Aug 1999 28 Aug 1999 13 Sep 1999 18 Sep 1999 23 Jun 2000 7 Jul 2000 11 Aug 2000 17 Aug 2000
64 30 46 90 222 186 124 86 146 112
0.5–1.5(24)e 0.5–1.5(8) 0.5–1.5(14) 0.8–1.3(15) 0.6–1.0(24) 0.5–1.2(21) 0.7–1.5(21) 0.8–1.5(12) 0.8–1.4(21) 0.8–1.0(12)
DRPc
NH4+
NO3 d
2.11 0.34 1.92 0.20 1.89 0.37 1.91 0.54 1.59 0.43 1.85 0.28 4.10 0.88 2.58 0.67 2.14 0.20 1.44 0.12
Loss amount ratios
Loss amount (kg)
Aver. sd (g m3)
Loss amount (kg)
Aver. sd (g m3)
Loss amount (kg)
NO3/ NH4+
(NO3 + NH4+)/ DRP
1.42 0.43 0.66 0.63 1.08 1.94 2.28 0.80 1.30 0.51
0.71 0.21 0.46 0.10 0.29 0.07 0.49 0.34 0.85 0.48 0.28 0.07 0.13 0.04 0.17 0.05 0.09 0.03 0.07 0.02
0.48 0.11 0.10 0.20 0.80 0.30 0.08 0.05 0.05 0.02
0.23 0.10 0.12 0.06 0.12 0.05 0.16 0.06 0.18 0.07 0.03 0.02 0.05 0.03 0.09 0.05 0.04 0.02 0.06 0.01
0.16 0.03 0.05 0.06 0.15 0.04 0.03 0.03 0.02 0.02
3 4 7 3 1 6 29 16 26 26
12 18 15 14 13 56 79 28 68 27
a
Tp, time to peak runoff rate. Tp range denotes the range of samplings, which was shown as a multiple of Tp. The average values and loss amounts were calculated from the observations occurred in the range of 0.5–1.5 Tp to provide a more standardized scale for comparing different rainstorm. These ranges were yet not uniform due to a high variation during field monitoring. c Dissolved reactive phosphorus. d Standard deviation. e Digits in parentheses indicates the number of observations during the Tp range. b
surfaces of suspended and deposited sediments, thus affecting the concentrations in the runoff waters. Sediment concentrations from the 10 runoff events are shown in Fig. 6. The sediment concentrations gradually decreased with time. The peak sediment concentrations for most storms occurred during the early period of increasing flow rates. Sediment concentrations for the runoff events observed in 2000 were much higher than in 1999, which could be due to the difference in cropping systems during the 2 years. The relationships between the concentrations of NH4+, DRP and sediments were presented in Table 4. Positive linear correlations between NH4+ and sediment concentrations for four runoff events were found during the 2 years. In contrast, there were positive linear correlations between the concentrations of DRP and sediment for all the events observed in 2000 (under the conventional double cropping system).
application on 10 September 1999 (Table 1). Nutrient losses were heavily affected by farming practice. In addition, the higher amounts of NO3 lost during the runoff event of 23 June 2000 could be due to the fact that this event was the first erosive rainstorm in 2000. This indicated that a rainstorm following a prolonged dry period tends to cause a large loss of NO3. The ratios of NO3 to NH4+ for the loss amount in 10 rainstorms ranged from 1 to 7 for the triple cropping system in 1999 and 16– 29 for the double cropping system in 2000. Both variations showed that NO3 was the main form of inorganic nitrogen loss in runoff water. Moreover, the ratios of the sum of NO3 and NH4+ to DRP for the loss amount in 10 rainstorms varied from 12 to 56 and 27 to 79 for the triple and double cropping system, respectively.
3.3. Effects of two cropping systems on nutrient losses
The variations of NO3 concentration in runoff water were noticeably affected by flow rates. A significant logarithmic correlation between NO3 concentrations and flow rates for each rainstorm were identified. This provided useful information for the prediction of NO3 loss by runoff. Further investigations of the contribution of subsurface runoff to NO3 loss should be mainly carried out due to the fact that NO3 concentrations gradually increased during the period of decreasing flow rates for a runoff event. In addition, NO3
Table 5 shows the average nutrient concentrations and the loss amounts for each rainstorm observed in 1999–2000. A high nutrient concentration level during the runoff event of 9 August 1999 could result from the harvesting activities on 6 August 1999 (Table 1). The losses of NO3 and NH4+ during the runoff events of 13 and 18 September 1999 could be increased by the nitrogen
4. Conclusions
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J.G. Han et al. / Agricultural Water Management 97 (2010) 757–762
was proved to be the main form of inorganic nitrogen loss, therefore, fertilizer application level of NO3 should be reduced in the purple soil region. When it is unavoidable, small quantities of repeated and timely applications are recommended. In contrast, the concentrations of NH4+ and DRP in runoff waters fluctuated substantially without a noticeable trend for each rainstorm. Positive linear correlations between the concentrations of DRP and sediment for each rainstorm were identified under the circumstances of wheat–corn double cropping system, which indicated that cropping system would notably affect the losses of DRP and soil. The application of the new wheat–corn–sweet potato triple cropping system in the region merits serious consideration because the system tends to increase NH4+ loss but it can enhance crop yield. Acknowledgements The authors appreciate Dr. Z.H. Cao and Dr. X.Z. Shi of the Institute of Soil Science, CAS for the smooth operation and providing staff for sampling and measurements. This research was funded by the National Natural Science Foundation of China (40905070, 40771124), China Postdoctoral Science Foundation funded project (20070420970), Jiangsu Planned Projects for Postdoctoral Research Funds (0702010B) and EROCHiNut project (ERBIC18CT980372). References Cao, W., Hong, H., Yue, S., Ding, Y., Zhang, Y., 2003. Nutrient loss from an agricultural catchment and landscape modeling in southeast China. Bulletin of Environmental Contamination and Toxicology 71, 761–767.
He, Y.R., 2003. Purple Soils in China. Chinese Science Press, Beijing. Holloway, J.M., Dahlgren, R.A., Casey, W.H., 2001. Nitrogen release from rock and soil under simulated field conditions. Chemical Geology 174 (4), 403– 414. Jia, H.Y., Lei, A.L., Lei, J.S., Ye, M., Zhao, J.Z., 2007. Effects of hydrological processes on nitrogen loss in purple soil. Agricultural Water Management 89, 89–97. Li, D.Q., Wang, J.Z., Wan, H.F., Deng, N.R., Liu, P., 1998. Law of non-point source pollutants losses in a typical small watershed of Dongjiang drainage basin of Guangdong Province. Journal of Soil Water Conservation 4, 12–18. Li, Z.B., Li, P., Han, J.G., Li, M., 2009. Sediment flow behavior in agro-watersheds of the purple soil region in China under different storm types and spatial scales. Soil and Tillage Research 2, 285–291. Liu, G.C., Lin, S.Y., Liu, S.Z., 2002. Characteristics of runoff generation and its numerical simulation of surface flow in hilly area with purple soil under conventional tillage systems. Journal of Hydraulic Engineering 12, 101–108. Lu, R.K., 2000. Soil and Agro-chemical Analysis. China Agricultural Scientech Press, Beijing. Pathak, P., Wani, S.P., Singh, P., Sudi, R., 2004. Sediment flow behavior from small agricultural watersheds. Agricultural Water Management 67, 105–117. Ramos, M.C., Martı´nez, J.A., 2004. Nutrient losses from a vineyard soil in Northeastern Spain caused by an extraordinary rainfall event. Catena 55, 79–90. Risto, U., Markku, Y., Ella, T., 2000. Suspended soil as a source of potential bioavailable phosphorus in surface runoff waters from clay soils. Water Research 34, 2477–2482. Turtola, E., Paajanen, A., 1995. Influence of improved subsurface drainage on phosphorus losses and nitrogen leaching from a heavy clay soil. Agricultural Water Management 28, 295–310. Udawatta, R.P., Motavalli, P.P., Garrett, H.E., Krstansky, J.J., 2006. Nitrogen losses in runoff from three adjacent agricultural watersheds with claypan soils. Agricultural Ecosystem Environment 117, 39–48. Wei, C.F., Ni, J.P., Gao, M., Xie, D.T., Hasegawa, S.H., 2006. Anthropic pedogenesis of purple rock fragments in Sichuan Basin, China. Catena 68, 51–58. Zhu, B., Peng, K., Xie, H.M., 2006. Nitrogen balance of agro-ecosystem in a typical watershed in the hilly area of central Sichuan Basin. Chinese Journal of EcoAgriculture 14, 109–112.
Contents lists available at ScienceDirect
Agricultural Water Management journal homepage: www.elsevier.com/locate/agwat
Nitrogen and phosphorous concentrations in runoff from a purple soil in an agricultural watershed J.G. Han a,b,*, Z.B. Li c,d, P. Li c, J.L. Tian d a
School of the Environment, Jiangsu University 72#, Xue Fu Road 301, Zhenjiang 212013, Jiangsu, China Key Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education and Jiangsu Province, Jiangsu University, Zhenjiang 212013, Jiangsu, China c Xi’an University of Technology, Xi’an 710048, Shaanxi, China d Institute of Soil and Water Conservation, CAS & MWR, Yangling 712100, Shaanxi, China b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 1 April 2009 Accepted 12 January 2010 Available online 1 February 2010
Nutrient loss from purple soils has been reported to increase pollution of the Yangtze River. However, few studies have addressed the variations of nutrient concentration in runoff during natural rainstorms in the regions. Nitrogen and phosphorus concentrations in runoff waters from a small agricultural watershed, in the purple soil region of southwest China, were investigated for four natural rainstorms occurred in a conventional double cropping system (wheat–corn) and another six rainstorms in a new triple cropping system (wheat–corn–sweet potato). The NO3 concentrations in runoff for the observed rainstorms generally varied from 1.0 to 3.5 g m3, which were noticeably affected by flow rates. A significant logarithmic correlation between NO3 concentrations and flow rates for each rainstorm was identified. In contrast, the concentrations of NH4+ and dissolved reactive phosphorus (DRP) in runoff fluctuated substantially without a noticeable trend for each rainstorm. Positive linear correlation between the concentrations of DRP and sediment for each rainstorm tested was found under the circumstances of double cropping system. In addition, the ratios of NO3 to NH4+ for the loss amount in 10 rainstorms varied from 1 to 7 for the triple cropping system and 16–29 for the double cropping system. Furthermore, the ratios of the sum of NO3 and NH4+ to DRP for the loss amount in 10 rainstorms ranged from 12 to 79 depending on the cropping systems. Nitrate nitrogen was proved to be the main form of inorganic nitrogen loss in runoff water in the purple soil region. Compared with the conventional double cropping system, the new triple cropping system tends to cause more NH4+ loss. These findings would help develop the effective erosion control strategies and select a suitable cropping system to reduce potential pollution hazards. ß 2010 Elsevier B.V. All rights reserved.
Keywords: NO3 NH4+ Dissolved reactive phosphorus Runoff Purple soil
1. Introduction Purple soil, formed from purple rock series of the Trias– Cretaceous system, or their weathering products, is mainly distributed in the Sichuan Basin, one of the most important agricultural areas of southwest China. Purple rocks are characterized by fast physical weathering, and are broken up by anthropic activities into rock fragments or gravels, in which crops are directly planted (Wei et al., 2006). Unplanned reclamation and land use patterns have accelerated water, soil and nutrient losses. These losses have direct negative effects on land productivity; and additionally, increase pollution and siltation of the Yangtze River, causing problems downstream (Li et al., 2009).
* Corresponding author at: School of the Environment, Jiangsu University 72#, Xue Fu Road 301, Zhenjiang 212013, Jiangsu, China. Tel.: +86 13511690975. E-mail addresses: [email protected], [email protected] (J.G. Han). 0378-3774/$ – see front matter ß 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.agwat.2010.01.007
Nitrogen loss in runoff water is mainly lost as NO3 and NH4+ (Udawatta et al., 2006). In addition, some NH4+ could also be transported with eroded soil material combined with phosphorus (Ramos and Martı´nez, 2004). Zhu et al. (2006) estimated that soil nitrogen was lost at an average rate of 44.34 kg ha1 year1 in the purple soil regions. Surface and subsurface hydrological pathways were considered to contribute to nutrient transport depending on rainfall amount (Liu et al., 2002), topography and flow rate (Cao et al., 2003). Understanding the variations of nutrient concentration in runoff during various rainstorms is very helpful in improving the current erosion model, which would facilitate selecting a management practice that could effectively control the potential pollution hazards in a watershed. However, there is insufficient knowledge of such variations in the purple soil regions, particularly for the circumstances under natural rainstorms. Nutrient loss is heavily influenced by farming practices and cropping system under agricultural land use. Buffer zones and year-round vegetated fields have therefore been introduced as measures to reduce soil erosion and the phosphorus load in runoff
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waters. However, Turtola and Paajanen (1995) and Risto et al. (2000) found these measures tended to increase the loss of dissolved reactive phosphorus (DRP). Udawatta et al. (2006) suggested that the maintenance of a suitable vegetative cover throughout the year could reduce runoff and lower total nitrogen and NO3 losses from agricultural watersheds under a corn– soybean rotation. Jia et al. (2007) found that rainstorms after urea application probably increased NH4+ losses but had little effect on NO3 loss in the surface hydrological pathway. However, there are no detailed data available for the purple soil region, the soil of which is not favorable for erosion control. The objectives of this study were to investigate the concentration variations of NO3, NH4+ and DRP in runoff waters during natural rainstorms, and to compare the impacts of the two cropping systems, a conventional wheat–corn double cropping system and a new wheat–corn–sweet potato triple cropping system, on the nutrient losses in an agricultural watershed. 2. Materials and methods 2.1. Site description The experiment was carried out in a small agricultural watershed, Xujiawan, in Zi-Yang City (30.198N, 104.68E) of the Sichuan Province, China. The region is mainly covered by red or purple rock, from which the purple soils are developed and formed (He, 2003; Wei et al., 2006). The landscape is characterized by hilly mountains with elevations of 395–475 m. The climate is subtropical with an annual mean temperature of 17.3 8C, and an annual mean rainfall of 961 mm, more than 80% of which falls from May to October. The purple soil is classified as Udorthent based on USDA taxonomies (He, 2003). The soil depth is shallow, but the soilforming speed is fast. The clay minerals include hydromica, montmorillonite, and chlorites of 2:1 type. The content of cation exchange capacity ranged from 18.4 to 26.4 cmol+ kg1. The average sand (2–0.05 mm), silt (0.05–0.002 mm), and clay (<0.002 mm) contents are 143.8 29.7, 636.3 28.8, and 219.9 16.3 g kg1, respectively. The watershed is about 10.8 ha, with 7.9 ha of sloping land and 2.9 ha of valley land. Of the sloping land, 2.2 ha is used as farming land, 3.2 ha as woodland, 2.1 ha as wasteland and 0.4 ha as garden plots. The valley land consists of farmland (2.0 ha) and garden plots (0.9 ha). The region is sparsely populated and specific point-source pollution sites are not known. 2.2. Cultivation system and farming practice There are two cultivation systems and the corresponding farming practices investigated in the purple soil region were: a conventional wheat–corn double cropping system and a new wheat–corn–sweet potato triple cropping system. The new triple cropping system is currently being promoted extensively due to the high year production. To compare the impacts of these two
Table 1 The farming practices in 1999–2000. Year
Farming practice
1999
Wheat: sown and base fertilizer applied 16 Oct; seedling fertilizer applied 13 Feb; harvested 11 May. Corn: sown and base fertilizer applied 4 and 14 May, respectively; additional fertilizer applied 10 Jun and 3 Jul; harvested 6 Aug. Sweet potato: planted and base fertilizer applied 12 Aug; additional nitrogen applied 21 Aug; nitrogen and potassium applied 10 Sep; harvested 12 Oct.
2000
Wheat: sown and base fertilizer applied 14 Sep; seedling fertilizer applied 20 Feb; harvested 7 May. Corn: sown and base fertilizer applied 16 May; additional fertilizer applied 26 Jun and 30 Jul; harvested 21 Aug.
cultivation systems on nutrient loss, the triple cropping system and the conventional double cropping system were therefore implemented in 1999 and 2000, respectively. The main farming practices are listed in Table 1. The fertilizer rates were determined based on the averaged soil test results. 2.3. Rainstorm characteristics Automatic rain gauges were used to monitor rainfalls in 1999– 2000. The rain gauge has a resolution of 0.199 mm m2. This means that every time 0.199 mm of rain has fallen, the moment this happens will be recorded by the data logger inside the gauge. In 23 rainstorms observed in 1999, six events accounted for 44% of the annual rainfalls. In 11 rainstorms observed in 2000, four events made up 54% of the annual rainfall. These 10 events were selected to investigate the concentration variations of NO3, NH4+ and DRP in runoff water (Table 2). The average rainfall intensity, Iaver (mm h1), was calculated as Ia ¼
P D
(1)
where P (mm) was the rainfall for an event and D (h) was the rainfall duration. 2.4. Water sampling and analysis A flume was devised and constructed at the outlet of the watershed, which provided a means for determining a relationship between water level and the amount of water flow (Fig. 1). The water level was measured at a certain position above the flume by an ultrasonic flow sensor, which was connected to a water sampler (ISCO-6700). Every 2 min the data logger inside the sampler did a water level measurement. The water sampler converted the level measurements to flows. Within the data logger program, a flow value was predefined to trigger a sampling. When the set value was reached, the data logger sent a signal to the sampler. The sampler collected water samples from the flume using a suction tube and a tube pump. The individually collected samples were placed in
Table 2 Rainstorm characteristics. Event
Rainfall (mm)
Durationa (h)
Iaverb (mm h1)
Event
Rainfall (mm)
Duration (h)
Iaver (mm h1)
9 Aug 1999 10 Aug 1999 16 Aug 1999 28 Aug 1999 13 Sep 1999 18 Sep 1999
55 23 30 69 61 64
8.0 1.0 3.0 12.0 9.0 11.0
6.9 23.0 10.0 5.8 6.8 5.8
23 Jun 2000 7 Jul 2000 11 Aug 2000 17 Aug 2000
48 37 48 138
8.0 4.0 6.5 12.0
6.0 9.3 7.4 11.5
a b
The beginning and the end of each rainstorm were determined according to the records of automatic rain gauges. The average rainfall intensity.
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every runoff event the nutrient concentration values were used to construct a nutrient concentration vs. time graph. This graph and the runoff hydrograph were then divided into small segments. For each segment, the nutrient loss was calculated by multiplying segment runoff volume and nutrient concentration. The total nutrient loss during a runoff event was calculated by adding these segment values. 3. Results and discussion
Fig. 1. Flume construction: (a) water sampler; (b) ultrasonic flow meter; (c) sampling tube; (d) flume wall; (e) power supply unit.
separate flasks inside the device, which had a 24-bottle carousel, each bottle with a volume of 1 l. The device could store measurement data of the ultrasonic flow sensor, as well as the time a sample was taken. Each water sample was split into runoff and sediment subsamples by filtration. The runoff sub-samples were put into a plastic bottle, in which 0.5 ml of 98% H2SO4 was added to suppress microbial activity. These samples were kept at 4 8C for subsequent measurements. NO3 and NH4+ concentrations were analyzed colorimetrically using a flow injection analyzer (Lu, 2000). DRP was determined by colorimetric ascorbic acid reduction method (Lu, 2000). The sediment sub-samples were dried at 45 8C for 12 h and then weighed to compute sediment concentration. 2.5. Nutrient losses Each runoff sample and its nutrient concentration represented a particular time and segment of the runoff hydrograph, thus for
Fig. 2. NO3 concentration variations with time during the courses of two runoff events.
In order to ascertain the variations of nutrient concentrations in runoff water in various rainstorms, the nutrient concentrations were plotted against time. The time scale was calculated as a multiple of time to peak runoff rate (Tp). This provided comparisons of nutrient concentration variations between storms in relation to their Tp and it provided a more uniform scale for comparing different rainstorms with extreme variations in runoff durations (Pathak et al., 2004). 3.1. Changes in NO3 concentrations for different runoff events Fig. 2 shows the NO3 concentrations and flow rates with time for two runoff events. There was a similar increasing trend during the period of decreasing flow rates, after the time of 1.0 Tp (time to peak runoff). To clarify how NO3 concentrations varied during the course of a runoff event, NO3 concentrations from 10 runoff events of various sizes were plotted in Fig. 3. The NO3 concentrations gradually increased during periods of decreasing flow rate (generally after 1.0 Tp). This was likely the result of the contributions of subsurface runoff as described by Jia et al. (2007), who investigated the nitrogen losses associated with surface and subsurface runoff under artificial rainfall simulation and confirmed that large amounts of subsurface runoff through macropores could increase the loss of NO3. In contrast, the NO3 concentrations tended to decrease during the period of increasing flow rates (generally before 1.0 Tp). These observations differed from the findings of Li et al. (1998), who reported that inorganic nitrogen ran off at an almost constant concentration under a natural rainstorm in the region. In addition, the NO3 concentrations in runoff water were generally 1.0–3.5 g m3 (Fig. 3). However, there were apparently higher NO3 concentrations observed during the event of 23 June 2000. This observation could be due to the fact that this event was the first erosive rainstorm in 2000. Large amounts of NO3 may have accumulated in the soil surface layers during a prolonged dry period, and subsequently been lost with the initial rainstorm. This was in agreement with the observations of Holloway et al. (2001), who used fresh rock and weathered material to simulate nitrogen release
Fig. 3. Change in NO3 concentrations as a function of the time to peak runoff rates (Tp) for different runoff events.
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Table 3 The relationships between NO3 concentrations and runoff flow rates. Event
Tp rangea
Fitting equation: C NO3 ¼ a ln W þ b
b
9 Aug 1999 10 Aug 1999 16 Aug 1999 28 Aug 1999 13 Sep 1999 18 Sep 1999
0.5–1.5(24) 0.3–3.0(23) 0.4–2.1 (22) 0.8–1.3(15) 0.6–1.0(24) 0.4–1.2(24)
23 Jun 2000 7 Jul 2000 11 Aug 2000 17 Aug 2000
0.7–1.5(21) 0.8–1.5(12) 0.8–1.4(21) 0.8–1.0(12)
a
b
R2
0.67 2.09 16.03 0.90 0.71 2.12
1.02 2.51 4.05 0.08 0.04 2.49
0.735** 0.801** 0.705** 0.708** 0.556** 0.934**
2.38 2.16
1.10 2.53 / 1.81
0.903** 0.502**
0.25
0.901**
NO3
C NO3 : concentration; W: runoff flow rate. a Tp, time to peak runoff rate. Tp range denotes the range of samplings, which was expressed as a multiple of Tp. b Digits in parentheses indicates the number of observations during the range. The symbol ‘‘/’’ means no significant relationship. ** P < 0.01.
from rock and soil under field conditions, and confirmed that geologic nitrogen might be a large and reactive pool that might contribute as a non-point source of NO3 contamination to surface and groundwater. Moreover, the relationships between NO3 concentrations and flow rates were analyzed, and logarithmic correlations for nine events were identified (Table 3). This provided useful information for the prediction of NO3 loss by runoff. 3.2. Changes in NH4+ and DRP concentrations for different runoff events The concentrations of NH4+ and DRP in runoff waters fluctuated substantially and varied differently with time than the NO3 concentrations without a noticeable trend (Fig. 4). This differed from
Fig. 5. Change in NH4+ (top) and dissolved reactive phosphorus (DRP) (bottom) concentrations as a function of the time to peak runoff rates (Tp) for different runoff events.
the results of Li et al. (1998), who reported that both NH4+ and DRP concentrations did not fluctuate widely and high concentrations were observed only in the initial period of runoff. The difference could be due to the fact that the experiments of Li et al. (1998) were conducted on a slope. In addition, neither correlation was found between NH4+ concentration and flow rate, nor there was a correlation between DRP concentration and flow rate. Fig. 5 showed the variations of NH4+ and DRP concentrations during the 10 rainstorms, and the respective concentrations were 0.04–1.70 and 0.03–0.50 g m3. These ranges differed, possibly due to the different natures of NH4+ and DRP ions, which may, to various degrees, be adsorbed on, or released from, the soil particle
Fig. 4. NH4+ (top) and dissolved reactive phosphorus (DRP) (bottom) concentration variations with time during the runoff event of 10 August 1999.
Fig. 6. Change in sediment concentrations as a function of the time to peak runoff rates (Tp) for different runoff events.
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Table 4 The relationships between the concentrations of NH4+, DRP and sediment. Tp rangea
Event
Fitting equation C NHþ 4
C NHþ ¼ aC s þ b
CDRP = aCs + b
4
9 Aug 1999 10 Aug 1999 16 Aug 1999 28 Aug 1999 13 Sep 1999 18 Sep 1999
0.5–1.5(24)b 0.3–3.0(23) 0.4–2.1 (22) 0.8–1.3(15) 0.6–1.0(24) 0.4–1.2(24)
23 Jun 2000 7 Jul 2000 11 Aug 2000 17 Aug 2000
0.7–1.5(21) 0.8–1.5(12) 0.8–1.4(21) 0.8–1.0(12)
a
b
R2
0.04 0.06 0.01
0.48 0.33 0.25 / / /
0.477** 0.683** 0.230*
/ 0.13 / /
0.01
a
R2
b / / / / / /
0.02 0.01 0.01 0.01
0.511**
0.555** 0.903** 0.787** 0.688**
0.01 0.05 0.02 0.04
C NHþ : NH4+ concentration; CDRP: DRP concentration; Cs: sediment concentration. a 4 Tp, time to peak runoff rate. Tp range denotes the range of samplings, which was expressed as a multiple of Tp. b Digits in parentheses indicates the number of observations during the range. The symbol ‘‘/’’ means no significant relationship. * P < 0.05. ** P < 0.01.
Table 5 The average nutrient concentrations in runoff and the loss amounts for each rainstorm observed in 1999–2000. Event
Tpa (min)
Tp rangeb
Aver. sd (g m3) 9 Aug 1999 10 Aug 1999 16 Aug 1999 28 Aug 1999 13 Sep 1999 18 Sep 1999 23 Jun 2000 7 Jul 2000 11 Aug 2000 17 Aug 2000
64 30 46 90 222 186 124 86 146 112
0.5–1.5(24)e 0.5–1.5(8) 0.5–1.5(14) 0.8–1.3(15) 0.6–1.0(24) 0.5–1.2(21) 0.7–1.5(21) 0.8–1.5(12) 0.8–1.4(21) 0.8–1.0(12)
DRPc
NH4+
NO3 d
2.11 0.34 1.92 0.20 1.89 0.37 1.91 0.54 1.59 0.43 1.85 0.28 4.10 0.88 2.58 0.67 2.14 0.20 1.44 0.12
Loss amount ratios
Loss amount (kg)
Aver. sd (g m3)
Loss amount (kg)
Aver. sd (g m3)
Loss amount (kg)
NO3/ NH4+
(NO3 + NH4+)/ DRP
1.42 0.43 0.66 0.63 1.08 1.94 2.28 0.80 1.30 0.51
0.71 0.21 0.46 0.10 0.29 0.07 0.49 0.34 0.85 0.48 0.28 0.07 0.13 0.04 0.17 0.05 0.09 0.03 0.07 0.02
0.48 0.11 0.10 0.20 0.80 0.30 0.08 0.05 0.05 0.02
0.23 0.10 0.12 0.06 0.12 0.05 0.16 0.06 0.18 0.07 0.03 0.02 0.05 0.03 0.09 0.05 0.04 0.02 0.06 0.01
0.16 0.03 0.05 0.06 0.15 0.04 0.03 0.03 0.02 0.02
3 4 7 3 1 6 29 16 26 26
12 18 15 14 13 56 79 28 68 27
a
Tp, time to peak runoff rate. Tp range denotes the range of samplings, which was shown as a multiple of Tp. The average values and loss amounts were calculated from the observations occurred in the range of 0.5–1.5 Tp to provide a more standardized scale for comparing different rainstorm. These ranges were yet not uniform due to a high variation during field monitoring. c Dissolved reactive phosphorus. d Standard deviation. e Digits in parentheses indicates the number of observations during the Tp range. b
surfaces of suspended and deposited sediments, thus affecting the concentrations in the runoff waters. Sediment concentrations from the 10 runoff events are shown in Fig. 6. The sediment concentrations gradually decreased with time. The peak sediment concentrations for most storms occurred during the early period of increasing flow rates. Sediment concentrations for the runoff events observed in 2000 were much higher than in 1999, which could be due to the difference in cropping systems during the 2 years. The relationships between the concentrations of NH4+, DRP and sediments were presented in Table 4. Positive linear correlations between NH4+ and sediment concentrations for four runoff events were found during the 2 years. In contrast, there were positive linear correlations between the concentrations of DRP and sediment for all the events observed in 2000 (under the conventional double cropping system).
application on 10 September 1999 (Table 1). Nutrient losses were heavily affected by farming practice. In addition, the higher amounts of NO3 lost during the runoff event of 23 June 2000 could be due to the fact that this event was the first erosive rainstorm in 2000. This indicated that a rainstorm following a prolonged dry period tends to cause a large loss of NO3. The ratios of NO3 to NH4+ for the loss amount in 10 rainstorms ranged from 1 to 7 for the triple cropping system in 1999 and 16– 29 for the double cropping system in 2000. Both variations showed that NO3 was the main form of inorganic nitrogen loss in runoff water. Moreover, the ratios of the sum of NO3 and NH4+ to DRP for the loss amount in 10 rainstorms varied from 12 to 56 and 27 to 79 for the triple and double cropping system, respectively.
3.3. Effects of two cropping systems on nutrient losses
The variations of NO3 concentration in runoff water were noticeably affected by flow rates. A significant logarithmic correlation between NO3 concentrations and flow rates for each rainstorm were identified. This provided useful information for the prediction of NO3 loss by runoff. Further investigations of the contribution of subsurface runoff to NO3 loss should be mainly carried out due to the fact that NO3 concentrations gradually increased during the period of decreasing flow rates for a runoff event. In addition, NO3
Table 5 shows the average nutrient concentrations and the loss amounts for each rainstorm observed in 1999–2000. A high nutrient concentration level during the runoff event of 9 August 1999 could result from the harvesting activities on 6 August 1999 (Table 1). The losses of NO3 and NH4+ during the runoff events of 13 and 18 September 1999 could be increased by the nitrogen
4. Conclusions
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was proved to be the main form of inorganic nitrogen loss, therefore, fertilizer application level of NO3 should be reduced in the purple soil region. When it is unavoidable, small quantities of repeated and timely applications are recommended. In contrast, the concentrations of NH4+ and DRP in runoff waters fluctuated substantially without a noticeable trend for each rainstorm. Positive linear correlations between the concentrations of DRP and sediment for each rainstorm were identified under the circumstances of wheat–corn double cropping system, which indicated that cropping system would notably affect the losses of DRP and soil. The application of the new wheat–corn–sweet potato triple cropping system in the region merits serious consideration because the system tends to increase NH4+ loss but it can enhance crop yield. Acknowledgements The authors appreciate Dr. Z.H. Cao and Dr. X.Z. Shi of the Institute of Soil Science, CAS for the smooth operation and providing staff for sampling and measurements. This research was funded by the National Natural Science Foundation of China (40905070, 40771124), China Postdoctoral Science Foundation funded project (20070420970), Jiangsu Planned Projects for Postdoctoral Research Funds (0702010B) and EROCHiNut project (ERBIC18CT980372). References Cao, W., Hong, H., Yue, S., Ding, Y., Zhang, Y., 2003. Nutrient loss from an agricultural catchment and landscape modeling in southeast China. Bulletin of Environmental Contamination and Toxicology 71, 761–767.
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