water

Article Effects of Irrigation Water Salinity on Soil Properties, N2O Emission and Yield of Spring Maize under Mulched Drip Irrigation

Chenchen Wei 1, Fahu Li 1, Peiling Yang 1,*, Shumei Ren 1, Shuaijie Wang 1,2, Yu Wang 1, Ziang Xu 1, Yao Xu 1, Rong Wei 1 and Yanxia Zhang 1,3 1 College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083, China 2 Henan Water Conservancy Survey, Ltd., Zhengzhou 450000, China 3 Gongnongqu Electric Pumping Station, Xigu District, Lanzhou 730060, China * Correspondence: [email protected]; Tel./Fax: +86-10-6273-7866



Received: 19 June 2019; Accepted: 24 July 2019; Published: 26 July 2019


Abstract: Brackish water has been widely used to irrigate crops to compensate for insufficient freshwater water supply for agricultural use. The goal of this research was to determine an efficient brackish water use method to increase irrigation efficiency and reduce N2O emission. To this end, we conducted a field experiment with four salinity levels of irrigation water (1.1, 2.0, 3.5, and 5.0 g L 1 with drip irrigation) at Hetao Irrigation District (Inner Mongolia, China) in 2017 and · − 2018. The results show that irrigation with 3.5–5.0 g L 1 water salinity increased the soil salinity · − compared with irrigation using 1.1–2.0 g L 1 water salinity. The soil water content with 5.0 g L 1 · − · − brackish water irrigation was significantly higher than with 1.1–3.5 g L 1 water salinity due to the · − effect of salinity on crop water uptake. The overall soil pH increased with the increase in irrigation water salinity. Saturated soil hydraulic conductivity decreased with the increase in irrigation water salinity. These results indicate that brackish water irrigation aggravates the degree of soil salinization 1 and alkalization. The soil N2O cumulative flux resulting from irrigation with 5.0 g L− water salinity 1 · was 51.18–82.86% higher than that resulting from 1.1–3.5 g L− water salinity in 2017, and was 32.38–44.79% higher than that resulting from 1.1–2.0 g L 1 in 2018. Irrigation with brackish water · − reduced maize yield, and the reduction in yield in 2018 was greater than that in 2017, but irrigation with 2.0 g L 1 brackish water did not significantly reduce maize yield in 2017. These results suggest · − that reducing the salinity of irrigation water may effectively reduce soil N2O emission, alleviate the degree of soil salinization, and increase crop yield.

Keywords: irrigation water salinity; soil salinization and alkalization; soil N2O emission; maize yield; correlation relationship; Hetao Irrigation District

1. Introduction Situated in Inner Mongolia, Hetao Irrigation District (HID) is an important commodity grain-producing area in Northwest China. Due to the region’s arid climate, agricultural production has always depended on local YellowRiver irrigation. Topromote agricultural production, mulched planting technology, due to its heat preservation, water saving, and yield increases, has been widely promoted in HID. However, with the development of the economy, the use of industrial water and domestic water in HID is increasing. Meanwhile, because of policy regulation, the amount of water diverted from the Yellow River will decrease by 20% (from 5 billion m3 to 4 billion m3) in the next 10 years [1]. The problem of insufficient agricultural water use is becoming increasingly serious. Therefore, it is imperative to develop methods for efficient water-saving irrigation. Simultaneously, alternative water sources for irrigation should be found for the sustainable development of agriculture in HID.

Water 2019, 11, 1548; doi:10.3390/w11081548 www.mdpi.com/journal/water Water 2019, 11, 1548 2 of 19

Given the combination of the long-term excessive irrigation use of the Yellow River and the effects of low precipitation and high evaporation, brackish water (salinity concentration ranging from 2 to 5 g L 1) reserves in HID are abundant (up to 8.86 billion m3) and have potential for use [2]. · − However, irrigation with brackish water may lead to the accumulation of salt in the soil tillage layer, resulting in varying degrees of soil salinization and alkalization. These soil conditions cause a decline in the fertility and growth of crops as a result of salinity stress [3,4]. Spring maize, with a growing stage from April to September, is the second largest grain crop in HID (planting area accounts for about 30% of total planting area in HID [5]), after sunflower. Maize growth is sensitive to salt in soil: when the EC of the soil tillage layer exceeds 114 uS cm 1, its yield begins to decline; and when the 1:5 · − EC of the soil tillage layer exceeds 1473 uS cm 1, maize stops growing [5]. Unreasonable irrigation 1:5 · − method with brackish water may lead to a significant decrease in maize yield. In response to this, drip irrigation, which is characterized by delivering a small volume of irrigation water at a high frequency, was reported to be an important method that can effectively use brackish water resources [6]. When using brackish water for drip irrigation, salt only accumulates at the edge of the wetting zone, in which the salt content is relatively low and conducive to crop growth [7]. Therefore, exploring the effective use of brackish water with drip irrigation to guarantee maize yield and improve soil safety should be among HID’s priorities. Irrigation water salinity not only accelerates the process of soil salinization and alkalization but also affects the available soil nitrogen, enzymes, microorganisms, nitrification, and denitrification, all of which can affect soil N2O emission [8,9]. As an important greenhouse gas, N2O is a major contributor to the destruction of the ozone layer through its involvement in photochemical reactions [10]. Its global warming potential is more than 260 times greater than that of CO2 [11]. Most N2O emissions from agricultural soils are products of nitrification and denitrification, accounting for about 59.4% of the global anthropogenic emissions of N2O[12,13]. Therefore, reducing soil N2O emissions from farmland ecosystems is an urgent task. Previous studies on the factors influencing soil N2O emissions from farmland have mostly focused on the amount of fertilizer, fertilizer type, irrigation method, soil amendment, and C/N ratio [14–17]. However, research is lacking and conflicting on the effect of saline irrigation water on N2O emission. Judging from the existing research, salinity has been found to both significantly stimulate [12,18–20] and inhibit soil N2O emissions [21–23], or produced no significant effect [24–26]. For example, Maucieri et al. indicated that irrigation water salinity remarkably promoted N2O emission in their incubation experiment in Australia [20]. Kontopoulou et al. reported that irrigation water salinity did not affect the emissions of N2O in Greek soybean fields [24]. Zou et al. found that irrigation water salinity significantly inhibited soil N2O emissions in a winter wheat and summer maize fields in Beijing, China [21]. However, these research efforts have mostly focused on short-term soil incubation experiments or one-year field experiments, and most did not consider changes in soil conditions caused by brackish water irrigation and climate change, and relevant research has not been conducted in HID. Studies using bare soil, an important part of the mulching system in farmland, have not been reported until now. Exploring N2O emissions from soil at different locations that use film mulching can reflect the actual emission process. Therefore, further studies should be conducted. To address the above issues, we assumed that irrigation water salinity would affect the soil properties, N2O emissions, yield, and irrigation water use efficiency (IWUE). Therefore, our objectives in the present study were to: (1) Investigate the response of soil properties and N2O emissions to different levels of irrigation water salinity, (2) evaluate the effects of irrigation water salinity on the maize yield and IWUE, and (3) propose an efficient brackish water irrigation method that will allow HID to lessen the risk of soil salinization and alkalization, N2O emission, and yield reduction. Water 2019, 11, x FOR PEER REVIEW 3 of 20 Water 2019, 11, 1548 3 of 19 2. Materials and Methods 2. Materials and Methods 2.1. Experimental Site 2.1. Experimental Site We used the Shuguang Experimental Station (40°46′ N, 107°24′ E, and elevation of 1039 m) to conductWe used field the experiments Shuguang with Experimental spring maize Station for (40two◦46 seasons0 N, 107 (2◦240170 E,and and 2018). elevation The location of 1039 m)of the to conductexperimental field experimentssite is illustrated with in spring Figure maize 1. The for region two has seasons a typically (2017 andarid 2018).continental The locationclimate with of the an experimentalaverage annual site precipitation is illustrated inof Figure105 mm,1. Theaverage region annual has a evaporation typically arid of continental 2306.5 mm, climate average with annual an averagetemperature annual of precipitation7.8 °C, and average of 105mm, annual average relative annual humidity evaporation of 48.9% of [2,27]. 2306.5 The mm, soil average properties annual are temperatureshown in Table of 7.8 1.◦ TheC, and daily average meteorological annual relative data of humidity the spring of 48.9%maize [2growth,27]. The stage soil in properties both seasons are shownwere recorded in Table1 .by The the daily standard meteorological farmland data meteorol of the springogical maizestation growth (FY-1000, stage Fortune in both Flyco, seasons Wuhan, were recordedChina) in by the the standardexperimental farmland station meteorological (Figure 2). During station (FY-1000,the growth Fortune stage Flyco, in 2017 Wuhan, and China)2018, the in theprecipitation experimental was station 53.5 and (Figure 202 2mm,). During the average the growth daily stage(day and in 2017 night) and air 2018, temperature the precipitation was 22.0 was and 53.521.4 and °C, 202and mm, the theaverage average soil daily temperature (day and (durin night)g air the temperature sample time) was was 22.0 and22.0 21.4°C and◦C, and23.1 the°C, averagerespectively. soil temperature (during the sample time) was 22.0 ◦C and 23.1 ◦C, respectively.

Water 2019, 11, x FOR PEER REVIEW 4 of 20 FigureFigure 1. 1.Location Location of of the the experimental experimental station. station.

40 80 40 80 (a) 2017 Table 1. Initial properties of the soil tillage layer(b) in 2018 the experimental fields in 2017.

Soil 1:5 Soil Soil Bulk Field Saturated Hydraulic Conductivity Ec − 30 Soil Texture 60 30 NO60 3 Type Density Capacity (10−5·cm·s−1) (uS·cm−1) pH -N

℃ Silt Sand ℃ Clay (%) (g·cm−3) (g·g−1) (mg·kg−1) (%) (%) Silty20 loam 7.694 62.379 29.927 1.5 0.19840 20 5.11 393 8.21 33.3840 Rainfall (mm) Rainfall (mm) Temperature ( ) Temperature ( ) 10 20 10 20

0 0 0 0 05/01 06/01 07/01 08/01 09/01 05/01 06/01 07/01 08/01 09/01

Date (mm/dd) Date (mm/dd) Maximum air temperature Minimum air temperature Soil temperature Rainfall Figure 2. Field meteorological data during the spring maize growth stage in (a)) 20172017 andand ((b)) 2018.2018.

2.2. Experimental Design and Field Management There were four treatments in this field experiment: (1) groundwater drip irrigation with salinity of 1.1 g·L−1 (T1), (2) brackish water drip irrigation with salinity of 2.0 g·L−1 (T2), (3) brackish water drip irrigation with salinity of 3.5 g·L−1 (T3), and (4) brackish water drip irrigation with salinity of 5.0 g·L−1 (T4). The four treatments were laid out in randomized complete blocks with three replicates for a total of 12 plots. There were 1-m buffer channels between adjacent plots to avoid interaction between the treatments. Seeds of the spring maize hybrid Ximeng No.3358, selected as the experimental crop, were sown on 26 April 2017 and 28 April 2018, and harvested on 12 September 2017 and 15 September 2018. The growth stages lasted 140 and 141 days, respectively. The layout of the experimental plot is shown in Figure 3. Two rows of spring maize were planted in each bed. The intra-row spacing was 0.3 m and the inter-row spacing was 0.8 m. The surface of the intra-row soil was covered with plastic mulch. The planting density of the maize was 60,000 plants·ha−1. Drip irrigation belts were arranged in the intra-row center. The thickness of the drip irrigation belts applied in the experiment was 0.4 mm, and the lateral diameter of the drip irrigation belts was 16 mm. The drippers were classified as embedded type. The interval between the drippers was 0.3 m, and the average discharge of each dripper was 2.0 L·h−1. To satisfy the demand for different levels of irrigation water salinity, we used the groundwater of the experimental station and added an equal ratio of NaCl/KCl (Table 2). On the basis of previous publications, the same amounts of irrigation (300 mm) and nitrogen (300 kg·ha−1) were applied for each treatment in the two seasons of the experiment [28,29]. The drip irrigation frequency was designed to be 6 days, and the irrigation amount was 15–25 mm each time [30]. Before they were sown, all plots were fertilized with 375 kg·ha−1 diammonium phosphate and 75 kg·ha−1 urea, and the fertilizers were applied to the soil tillage layer (0–20 cm) by machine [28,29]. The residual nitrogen was used for fertilization in the jointing stage, heading stage, and filling stage at a ratio of 2:2:1 in drip irrigation treatments [31]. The amounts of water and fertilizer were measured using a water meter (DN25, Aimeihui, Zhejiang, China) and a proportional fertilizer pump (Mixrite 2504, Tefen, Kibbutz Nahsholim, Israel) in each plot. The irrigation and fertilization dates for each treatment in 2017 and 2018 are shown in Figure 4.

Water 2019, 11, 1548 4 of 19

Table 1. Initial properties of the soil tillage layer in the experimental fields in 2017.

Saturated Soil Soil Field Hydraulic Ec Soil NO Soil Texture Bulk 1:5 3− Conductivity pH Type Density Capacity (10 5 cm s 1) (uS cm 1) -N − · · − · − Clay Sand Silt (%) (g cm 3) (g g 1) (mg kg 1) (%) (%) · − · − · − Silty loam 7.694 62.379 29.927 1.5 0.198 5.11 393 8.21 33.38

2.2. Experimental Design and Field Management There were four treatments in this field experiment: (1) groundwater drip irrigation with salinity of 1.1 g L 1 (T1), (2) brackish water drip irrigation with salinity of 2.0 g L 1 (T2), (3) brackish water drip · − · − irrigation with salinity of 3.5 g L 1 (T3), and (4) brackish water drip irrigation with salinity of 5.0 g L 1 (T4). · − · − The four treatments were laid out in randomized complete blocks with three replicates for a total of 12 plots. There were 1-m buffer channels between adjacent plots to avoid interaction between the treatments. Seeds of the spring maize hybrid Ximeng No.3358, selected as the experimental crop, were sown on 26 April 2017 and 28 April 2018, and harvested on 12 September 2017 and 15 September 2018. The growth stages lasted 140 and 141 days, respectively. The layout of the experimental plot is shown in Figure3. Two rows of spring maize were planted in each bed. The intra-row spacing was 0.3 m and the inter-row spacing was 0.8 m. The surface of the intra-row soil was covered with plastic mulch. The planting density of the maize was 60,000 plants ha 1. Drip irrigation belts were arranged in the intra-row center. · − The thickness of the drip irrigation belts applied in the experiment was 0.4 mm, and the lateral diameter of the drip irrigation belts was 16 mm. The drippers were classified as embedded type. The interval between the drippers was 0.3 m, and the average discharge of each dripper was 2.0 L h 1. To satisfy the · − demand for different levels of irrigation water salinity, we used the groundwater of the experimental station and added an equal ratio of NaCl/KCl (Table2). On the basis of previous publications, the same amounts of irrigation (300 mm) and nitrogen (300 kg ha 1) were applied for each treatment in the two · − seasons of the experiment [28,29]. The drip irrigation frequency was designed to be 6 days, and the irrigation amount was 15–25 mm each time [30]. Before they were sown, all plots were fertilized with 375 kg ha 1 diammonium phosphate and 75 kg ha 1 urea, and the fertilizers were applied to the soil · − · − tillage layer (0–20 cm) by machine [28,29]. The residual nitrogen was used for fertilization in the jointing stage, heading stage, and filling stage at a ratio of 2:2:1 in drip irrigation treatments [31]. The amounts of water and fertilizer were measured using a water meter (DN25, Aimeihui, Zhejiang, China) and a proportional fertilizer pump (Mixrite 2504, Tefen, Kibbutz Nahsholim, Israel) in each plot. The irrigation and fertilizationWater 2019, 11, datesx FOR PEER for eachREVIEW treatment in 2017 and 2018 are shown in Figure4. 5 of 20

FigureFigure 3. 3.Layout Layout of experimental plot. plot.

Table 2. Iron contents of irrigation water used in the experiment.

Salinity Iron Contents (mg·L−1)

(mg·L−1) Ca2+ Mg2+ Na+ K+ Cl− CO32− SO42− HCO3− 1157 90.2 48.6 152.6 41.2 141.8 0 240.2 442.4 2000 90.2 48.6 355.0 212.8 610.8 0 240.2 442.4 3500 90.2 48.6 715.2 518.4 1445 0 240.2 442.4 5000 90.2 48.6 1075.8 823.8 2279 0 240.2 442.4

350 350 (a)2017 (b)2018 300 300

250 250

200 200

150 150

100 100

50 50

Cumulative irrigation amount (mm) 0 Cumulative irrigation amount (mm) 0

05/01 06/01 07/01 08/01 09/01 05/01 06/01 07/01 08/01 09/01 Date (mm/dd) Date (mm/dd)

Figure 4. Detailed irrigation and fertilization dates for each treatment in (a) 2017 and (b) 2018. Note: Solid arrows represent fertilization events in drip irrigation treatments.

2.3. Measurement Method

2.3.1. Soil N2O Emission

Soil N2O gas samples were collected with a static chamber and analyzed by gas chromatography [32]. The sampling chamber was divided into a top chamber (50 × 50 × 50 cm) and a ground chamber (50 × 50 × 15 cm). The stainless-steel top chamber was covered with a foam board to prevent the temperature from rising too quickly, and two battery-operated fans were equipped to mix the gas. A thermometer slot was employed in the top chamber to measure the temperature during sampling. One week before sampling, the ground chamber was inserted in the center of each plot at a soil depth of 15 cm until the spring maize harvest. To represent the actual N2O emission flux during drip

Water 2019, 11, x FOR PEER REVIEW 5 of 20

Water 2019, 11, 1548 5 of 19 Figure 3. Layout of experimental plot. Table 2. Iron contents of irrigation water used in the experiment. Table 2. Iron contents of irrigation water used in the experiment. 1 Salinity Iron Contents (mg L− ) Salinity Iron Contents (mg·L· −1) 1 2+ 2+ + + 2 2 (mg L ) Ca Mg Na K Cl CO3 SO4 HCO3 · − (mg·L−1) Ca2+ Mg2+ Na+ K+ Cl− CO− 32− SO42− − HCO3− − − 1157 90.21157 48.690.2 48.6 152.6 152.6 41.241.2 141.8 141.8 0 240.2 0 442.4 240.2 442.4 2000 90.22000 48.690.2 48.6 355.0 355.0 212.8212.8 610.8 610.8 0 240.2 0 442.4 240.2 442.4 3500 90.2 48.6 715.2 518.4 1445 0 240.2 442.4 3500 90.2 48.6 715.2 518.4 1445 0 240.2 442.4 5000 90.2 48.6 1075.8 823.8 2279 0 240.2 442.4 5000 90.2 48.6 1075.8 823.8 2279 0 240.2 442.4

350 350 (a)2017 (b)2018 300 300

250 250

200 200

150 150

100 100

50 50

Cumulative irrigation amount (mm) 0 Cumulative irrigation amount (mm) 0

05/01 06/01 07/01 08/01 09/01 05/01 06/01 07/01 08/01 09/01 Date (mm/dd) Date (mm/dd)

Figure 4. Detailed irrigation and fertilization dates for each treatment in (a) 2017 and (b) 2018. Note: SolidFigure arrows 4. Detailed represent irrigation fertilization and fertilization events in drip dates irrigation for each treatments. treatment in (a) 2017 and (b) 2018. Note: Solid arrows represent fertilization events in drip irrigation treatments. 2.3. Measurement Method 2.3. Measurement Method 2.3.1. Soil N2O Emission

2.3.1.Soil Soil NN22OO Emission gas samples were collected with a static chamber and analyzed by gas chromatography [32]. The sampling chamber was divided into a top chamber (50 50 50 cm) and a Soil N2O gas samples were collected with a static chamber and analyzed by gas× chromatography× ground chamber (50 50 15 cm). The stainless-steel top chamber was covered with a foam board to [32]. The sampling chamber× × was divided into a top chamber (50 × 50 × 50 cm) and a ground chamber prevent the temperature from rising too quickly, and two battery-operated fans were equipped to mix (50 × 50 × 15 cm). The stainless-steel top chamber was covered with a foam board to prevent the the gas. A thermometer slot was employed in the top chamber to measure the temperature during temperature from rising too quickly, and two battery-operated fans were equipped to mix the gas. A sampling. One week before sampling, the ground chamber was inserted in the center of each plot thermometer slot was employed in the top chamber to measure the temperature during sampling. at a soil depth of 15 cm until the spring maize harvest. To represent the actual N O emission flux One week before sampling, the ground chamber was inserted in the center of each plot2 at a soil depth during drip irrigation with film mulching, the ground chamber was buried according to the intra- of 15 cm until the spring maize harvest. To represent the actual N2O emission flux during drip and inter-row proportions. In 2018, the ground chambers were also embedded in and between the rows of each plot to explore the relationship between N2O emissions and different locations. During sampling, the convex part of the top chamber was placed into the groove of the bottom chamber and water-sealed with no air exchange. A 100-mL gas sample was extracted from the chamber using a syringe 0, 10, 20, and 30 min after closing the chamber, and the samples were then transferred to sampling bags and tested within a week. The soil N2O samples were collected from 08:30 to 11:30 a.m. every 7–14 days, and there were additional samplings on the first, third, fifth, and seventh days after fertilization [33,34]. The concentration of N2O was measured by gas chromatography (Agilent 7890A, Agilent Technologies, Santa Clara, CA, USA), and its emission flux (F, µg m 2 h 1) was determined by · − · − the following equation [35]: ∆c 273 F = ρ H ( ) ( ) (1) × × ∆t × T Water 2019, 11, 1548 6 of 19 where ρ is the density of N O (kg m 3) in standard temperature and pressure, H is the top chamber 2 · − height (m), ∆c/∆t is the slope of N O concentration variation over time (ppb h 1), and T is the average 2 · − temperature during sampling (K). The N O (kg ha 1) cumulative flux (S) from spring maize soils was calculated by the following 2 · − equation [36]: S = Σn (Fi Di) (2) i × where Fi represents the N O emission flux (kg ha 1 day 1), Di represents days between two sampling 2 · − · − times (days), and n represents the sample number.

2.3.2. Soil Properties When sampling the gas, soil samples were acquired from a depth of 0–0.3 m, and sampling points were located between intra-row maize plants and from the center of inter-row spaces in each plot. Part of the soil was packed in an aluminum box and dried at 105 ◦C for 8–10 h. The remaining soil samples were air-dried, pulverized, and then sifted through a 1 mm sieve. A 10 g subsample was weighed and added to 50 mL of deionized water. After the mixture was shaken, left to stand, and centrifuged, the supernatant EC (µS cm 1) and pH were measured by a multi-parameter tester 1:5 · − (SG23, Mettler Toledo, Shanghai, China). Another 5 g subsample was weighed and added to 50 mL of a KCl solution. After the mixture was shaken, left to stand, and filtered, the NO content (mg kg 1) in 3− · − the supernatant was measured by a continuous flowing analyzer (Alliance FUTURA, AMS, Frépillon, France). After the spring maize harvest in 2018, the saturated hydraulic conductivity (cm s 1) of · − 0–20 cm of soil in the intra-row was measured by the constant-head method.

2.3.3. Spring Maize Yield and IWUE At harvest time, 6 maize plants from each plot were chosen to measure yield. Maize kernel samples were weighed after sun drying and threshing, and the actual yield was converted according to the number of plants. The IWUE was calculated by the following equation:

Y E = (3) Q where E represents the IWUE (kg m 3), Y represents the yield of spring maize (kg ha 1), and Q · − · − represents the cumulative amount of irrigation water (m3 ha 1). · − 2.3.4. Statistical Analysis The ANOVA procedure in SPSS software (IBM, Armonk, NY, USA) was used to statistically analyze the data. A Duncan multiple comparisons test was used to make multiple comparisons of annual average values. Pearson’s correlation analysis procedure in SPSS software (IBM, Armonk, NY, USA) was used to compare the correlations between soil N2O emission, soil properties, and maize yield. The confidence level is 95%.

3. Results

3.1. Soil Water Content Figure5 shows the average intra- and inter-row soil water content of spring maize under di fferent treatments in 2017 and 2018. The soil water content in intra-row soil was higher than that of inter-row soil under T1–T4 treatments (p < 0.05). On the whole, the soil water content in 2018 was higher than in 2017 (p < 0.05), which might be attributed to the large volumes and high frequency of precipitation in 2018 (Figure2). The irrigation water salinity had a significant e ffect on the soil water content (p < 0.05). The intra- and inter-row soil water content under T4 treatment was much higher than that under Water 2019, 11, x FOR PEER REVIEW 7 of 20

USA) was used to compare the correlations between soil N2O emission, soil properties, and maize yield. The confidence level is 95%.

3. Results

3.1. Soil Water Content Figure 5 shows the average intra- and inter-row soil water content of spring maize under different treatments in 2017 and 2018. The soil water content in intra-row soil was higher than that of inter-row soil under T1–T4 treatments (p < 0.05). On the whole, the soil water content in 2018 was Water 2019, 11, 1548 7 of 19 higher than in 2017 (p < 0.05), which might be attributed to the large volumes and high frequency of precipitation in 2018 (Figure 2). The irrigation water salinity had a significant effect on the soil water content (p < 0.05). The intra- and inter-row soil water content under T4 treatment was much higher T1–T3 treatments (p < 0.05), with intra-row increases of 25.55–35.43% and 19.66–29.09% and inter-row than that under T1–T3 treatments (p < 0.05), with intra-row increases of 25.55–35.43% and 19.66– increases of 41.38–57.69% and 23.19–37.10% in 2017 and 2018, respectively. 29.09% and inter-row increases of 41.38–57.69% and 23.19–37.10% in 2017 and 2018, respectively.

0.25 0.25 (a) 2017 (b) 2018 Intra-row Intra-row A Inter-row Inter-row 0.20 0.20 B ) ) -1 A -1 B a g g B . .

b 0.15 B B B 0.15 b b a

0.10 b b b 0.10 Soil water content (g content water Soil Soil waterSoil content(g 0.05 0.05

0.00 0.00 T1 T2 T3 T4 T1 T2 T3 T4 Treatment Treatment Figure 5.FigureAverage 5. Average soil water soil content water duringcontent theduring growth the stagegrowth for stage spring for maize spring under maize di ffundererent different treatments in (a) 2017treatments and (b )in 2018. (a) 2017 Note: and The(b) 2018. data Note: are the The average data are values the average of 15 values measurements of 15 measurements during the during growth stage; thethe error growth line stage; in the the figure error representsline in the figure the stand represents deviation the stand (n = 3); deviation different (n capital= 3); different letters capital between treatmentsletters represent between that treatments the diff representerence in that intra-row the difference is significant in intra-row at the is 0.05 significant level; di atff erentthe 0.05 lowercase level; different lowercase letters between treatments represent that the difference in inter-row is significant letters between treatments represent that the difference in inter-row is significant at the 0.05 level. at the 0.05 level. 3.2. Soil Salinity 3.2. Soil Salinity Figure6 shows the average EC 1:5 in intra- and inter-row soil of spring maize under different Figure 6 shows the average EC1:5 in intra- and inter-row soil of spring maize under different treatments in 2017 and 2018. The EC1:5 in 2018 was lower than that in 2017 in both intra- and inter-row treatments in 2017 and 2018. The EC1:5 in 2018 was lower than that in 2017 in both intra- and inter- soil (p

1000 1000 Intra-row (a) 2017 Intra-row (b) 2018 Inter-row Inter-row 800 a 800 A ) ) a -1 -1 B cm cm . 600 . 600 b A (uS b b (uS b 1:5 C 1:5 B c 400 C 400 c C C Soil EC Soil Soil EC Soil

200 200

0 0 T1 T2 T3 T4 T1 T2 T3 T4 Treatment Treatment

Figure 6.FigureAverage 6. Average soil EC soil1:5 ECduring1:5 during the the growth growth stage stage of of spring spring maize maize under under different di fftreatmentserent treatments in (a) in (a) 2017 and2017 (andb) 2018.(b) 2018. Note: Note: The The data are are the the average average values values of 15 measurements of 15 measurements during the during growth stage; the growth stage; thethe error error line line in in the the figure figure representsrepresents the the stand stand deviation deviation (n = (n 3);= different3); different capital capital letters letters between between treatments represent that the difference in intra-row is significant at the 0.05 level; different lowercase treatments represent that the difference in intra-row is significant at the 0.05 level; different lowercase letters between treatments represent that the difference in inter-row is significant at the 0.05 level. letters between treatments represent that the difference in inter-row is significant at the 0.05 level. 3.3. Soil pH Value Figure 7 shows the average pH value in the intra- and inter-row soil of spring maize under different treatments in 2017 and 2018. The pH value of soil tillage layer under all treatments in 2018 increased to varying degrees compared with that in 2017, and the range increased with the increase in irrigation water salinity (p < 0.05). Irrigation water salinity had a significant effect on pH value in the soil tillage layer (p < 0.05). In 2017, the pH value under T3–T4 treatments increased by 0.48–1.68% compared with that under T1–T2 treatments in intra-row soil (p < 0.05), and the difference between T3 and T4 treatments was significant in intra-row soil (p < 0.05), but there was no significant difference in pH between T1–T4 treatments in inter-row soil (p > 0.05). In 2018, the pH value under T3–T4 treatments increased by 2.13–4.06% compared with that under T1–T2 treatments in intra-row soil (p < 0.05), and the difference between T3 and T4 treatments was significant (p < 0.05). There were significant differences in pH values among T1–T4 treatments in inter-row soil (p < 0.05).

9.00 9.00 (a) 2017 Intra-row Intra-row A(b) 2018 B a Inter-row Inter-row b A C 8.50 B 8.50 C c C C d a a a a

8.00 8.00 Soil pH value pH Soil Soil pH value pH Soil

7.50 7.50

7.00 7.00 T1 T2 T3 T4 T1 T2 T3 T4 Treatment Treatment

Figure 7. Average soil pH value for the growth stage of spring maize under different treatments in (a) 2017 and (b) 2018. Note: The data are the average values of 15 measurements during the growth stage; the error line in the figure represents the stand deviation (n = 3); different capital letters between treatments represent that the difference in intra-row is significant at the 0.05 level; different lowercase letters between treatments represent that the difference in inter-row is significant at the 0.05 level.

Water 2019, 11, x FOR PEER REVIEW 8 of 20

1000 1000 Intra-row (a) 2017 Intra-row (b) 2018 Inter-row Inter-row 800 a 800 A ) ) a -1 -1 B cm cm . 600 . 600 b A (uS b b (uS b 1:5 C 1:5 B c 400 C 400 c C C Soil EC Soil Soil EC Soil

200 200

0 0 T1 T2 T3 T4 T1 T2 T3 T4 Treatment Treatment

Water 2019, 11, 1548Figure 6. Average soil EC1:5 during the growth stage of spring maize under different treatments in (a) 8 of 19 2017 and (b) 2018. Note: The data are the average values of 15 measurements during the growth stage; the error line in the figure represents the stand deviation (n = 3); different capital letters between treatments represent that the difference in intra-row is significant at the 0.05 level; different lowercase 3.3. Soil pH Value letters between treatments represent that the difference in inter-row is significant at the 0.05 level. Figure7 shows the average pH value in the intra- and inter-row soil of spring maize under 3.3. Soil pH Value different treatments in 2017 and 2018. The pH value of soil tillage layer under all treatments in 2018 increased to varyingFigure 7 degrees shows the compared average pH with value that in in the 2017, intra- and and the inter-row range increasedsoil of spring with maize the increaseunder in irrigationdifferent water salinity treatments (p < in0.05). 2017 and Irrigation 2018. The water pH value salinity of soil had tillage a significant layer under e allffect treatments on pH valuein 2018 in the increased to varying degrees compared with that in 2017, and the range increased with the increase soil tillagein layer irrigation (p < water0.05). salinity In 2017, (p < 0.05). the pH Irrigation value water under salinity T3–T4 had treatments a significant increased effect on pH by value 0.48–1.68% in comparedthe with soil that tillage under layer T1–T2(p < 0.05). treatments In 2017, the in pH intra-row value under soil T3–T4 (p < 0.05),treatments and increased the difference by 0.48–1.68% between T3 and T4 treatmentscompared waswith significantthat under T1–T2 in intra-row treatments soil in intra-row (p < 0.05), soil but (p < there 0.05), wasand the no difference significant between difference in pH betweenT3 and T4 T1–T4 treatments treatments was significant in inter-row in intra-row soil soil (p >(p <0.05). 0.05), but In there 2018, was the no pH significant value difference under T3–T4 treatmentsin increasedpH between by T1–T4 2.13–4.06% treatments compared in inter-row with soil that (p > under0.05). In T1–T2 2018, the treatments pH value inunder intra-row T3–T4 soil treatments increased by 2.13–4.06% compared with that under T1–T2 treatments in intra-row soil (p (p < 0.05), and the difference between T3 and T4 treatments was significant (p < 0.05). There were < 0.05), and the difference between T3 and T4 treatments was significant (p < 0.05). There were significantsignificant differences differences in pH valuesin pH values among among T1–T4 T1–T4 treatments treatments in in inter-row inter-row soil soil (p ( p< 0.05).< 0.05).

9.00 9.00 (a) 2017 Intra-row Intra-row A(b) 2018 B a Inter-row Inter-row b A C 8.50 B 8.50 C c C C d a a a a

8.00 8.00 Soil pH value pH Soil Soil pH value pH Soil

7.50 7.50

7.00 7.00 T1 T2 T3 T4 T1 T2 T3 T4 Treatment Treatment

Figure 7. Average soil pH value for the growth stage of spring maize under different treatments in (a) 2017 andFigure (b) 2018.7. Average Note: soil The pH datavalue arefor the growth average stage values of spring of 15 maize measurements under different during treatments the growth in (a) 2017 and (b) 2018. Note: The data are the average values of 15 measurements during the growth stage; the error line in the figure represents the stand deviation (n = 3); different capital letters between stage; the error line in the figure represents the stand deviation (n = 3); different capital letters between treatments represent that the difference in intra-row is significant at the 0.05 level; different lowercase treatments represent that the difference in intra-row is significant at the 0.05 level; different lowercase letters betweenletters treatmentsbetween treatments represent represent that thethat ditheff erencedifferenc ine in inter-row inter-row isis significantsignificant at at the the 0.05 0.05 level. level. Water 2019, 11, x FOR PEER REVIEW 9 of 20 3.4. Soil NO3− Content

3.4. Soil NO3− Content – Figure8 shows the average intra- and inter-row soil NO 3 content of spring maize under different Figure 8 shows the average intra- and inter-row soil NO3– content of spring maize under – treatments indifferent 2017 and treatments 2018. Onin 2017 the and whole, 2018. theOn the soil whole, NO3 thecontent soil NO3 in– content inter-row in inter-row soil was soil higher was higher than that of − intra-row soilthan (p 0.05). and inter-row soil (p > 0.05). 3−

60.00 60.00 Intra-row (a) 2017 Intra-row (b) 2018 Inter-row 50.00 Inter-row 50.00 ) ) -1 -1 kg 40.00 kg 40.00 . .

30.00 30.00 -N (mg -N -N (mg -N - - 3 3

20.00 20.00 Soil NO Soil Soil NO Soil

10.00 10.00

0.00 0.00 T1 T2 T3 T4 T1 T2 T3 T4 Treatment Treatment

Figure 8. Average soil NO3− content at the growth stage of spring maize under different treatments in − (a) 2017 andFigure (b) 2018. 8. Average Note: soil The NO data3 content are at the the averagegrowth stage values of spring of15 maize measurements under different duringtreatments the in growth (a) 2017 and (b) 2018. Note: The data are the average values of 15 measurements during the growth stage; the errorstage; line the inerror the line figure in the representsfigure represents the standthe stand deviation deviation ( nn == 3).3).

3.5. Saturated Soil Hydraulic Conductivity

The results of saturated soil hydraulic conductivity (Ksat) at harvest in 2018 are shown in Figure 9. Under all treatments, Ksat decreased to varying degrees compared with that before sowing (Table 1); this decrease was due to the tillage of the surface soil before sowing. Irrigation water salinity significantly affected Ksat (p < 0.05). Ksat decreased with the increase in irrigation water salinity: the value was 54.92–75.93% lower for the T2–T4 treatments than that for the T1 treatment.

3.5 a 3.0

2.5 ) -1 s . 2.0 b cm . -5 1.5 ( 10 sat K 1.0 c c

0.5

0.0 T1 T2 T3 T4 Treatment Figure 9. Effect of irrigation water salinity on saturated soil water conductivity. Note: The error line in the figure indicates the standard deviation (n = 3); different letters between treatments represent a significant difference at the 0.05 level.

Water 2019, 11, x FOR PEER REVIEW 9 of 20

3.4. Soil NO3− Content

Figure 8 shows the average intra- and inter-row soil NO3– content of spring maize under different treatments in 2017 and 2018. On the whole, the soil NO3– content in inter-row soil was higher than that of intra-row soil (p < 0.05). Due to the leaching effect on soil NO3− content by heavy precipitation in 2018 (Figure 2), NO3− content in both intra- and inter-row soil was lower than that in 2017 (p < 0.05). Irrigation water salinity had no significant effect on the average NO3− content in intra- and inter-row soil (p > 0.05).

60.00 60.00 Intra-row (a) 2017 Intra-row (b) 2018 Inter-row 50.00 Inter-row 50.00 ) ) -1 -1 kg 40.00 kg 40.00 . .

30.00 30.00 -N (mg -N -N (mg -N - - 3 3

20.00 20.00 Soil NO Soil Soil NO Soil

10.00 10.00

0.00 0.00 T1 T2 T3 T4 T1 T2 T3 T4 Treatment Treatment

Figure 8. Average soil NO3− content at the growth stage of spring maize under different treatments in Water 2019, 11, 1548 9 of 19 (a) 2017 and (b) 2018. Note: The data are the average values of 15 measurements during the growth stage; the error line in the figure represents the stand deviation (n = 3).

3.5. Saturated3.5. Saturated Soil Hydraulic Soil Hydraulic Conductivity Conductivity

The resultsThe results of saturated of saturated soil hydraulicsoil hydraulic conductivity conductivity (K (Ksatsat)) at at harvest harvest inin 2018 are are shown shown in in Figure Figure 9. Under9. all Under treatments, all treatments, Ksat decreased Ksat decreased to varying to varying degrees degrees compared compared with with that that before before sowingsowing (Table (Table 1); this decrease1); this decrease was due was to due the to tillage the tillage of the of surfacethe surface soil soil before before sowing. sowing. Ir Irrigationrigation water water salinity salinity significantlysignificantly affected affected Ksat K(psat <(p 0.05).< 0.05). KKsatsat decreaseddecreased with with the the increase increase in irrigation in irrigation water watersalinity: salinity: the the valuevalue was was 54.92–75.93% 54.92–75.93% lowerlower for the the T2–T4 T2–T4 trea treatmentstments than than that that for the for T1 the treatment. T1 treatment.

3.5 a 3.0

2.5 ) -1 s . 2.0 b cm . -5 1.5 ( 10 sat K 1.0 c c

0.5

0.0 T1 T2 T3 T4 Treatment FigureFigure 9. Effect 9. Effect of irrigation of irrigation water water salinity salinity on on saturated saturated soil soil waterwater conductivity. Note: Note: The The error error line line in the figurein the figure indicates indicates the standard the standard deviation deviation (n (=n =3); 3); di differentfferent lettersletters between between treatments treatments represent represent a a significantsignificant difference difference at the at 0.05 the 0.05 level. level. Water 2019, 11, x FOR PEER REVIEW 10 of 20 3.6. Soil N2O Emission Flux

3.6. Soil N2O Emission Flux 3.6.1. Seasonal N2O Emission Flux

3.6.1. Seasonal N2O Emission Flux The soil N2O emission flux in 2017 and 2018 had a similar pattern during the growth stage of spring maizeThe (Figure soil N2 O10 emission). The soil flux was in proven2017 and to 2018 be the had emission a similar source pattern of during N2O. the We growth observed stage six of peaks of N2Ospring emission maize flux (Figure in total, 10). The and soil they was appeared proven to one be tothe five emission days aftersource fertilization of N2O. We in observed 2017 and six 2018. Comparedpeaks withof N2O the emission peak value flux in in total, the and one they to five appeared days afterone to fertilization, five days after the fertilization average peakin 2017 values and of 2018. Compared with the peak value in the one to five days after fertilization, the average peak values2 1 N2O emissions in treatments T1, T2, T3, and T4 were 81.57, 89.30, 95.14, and 139.32 µg m− h− in ·−2 −1· 2017, andof N2 thereO emissions was a significantin treatments di ffT1,erence T2, T3, between and T4 thewere T4 81.57, treatment 89.30, 95.14, and T1–T3 and 139.32 treatments µg·m ·h (p < in0.05 ). 2017, and there was a significant difference between the T4 treatment and T1–T3 treatments (p < 0.05). The average peak values of N2O emissions in treatments T1, T2, T3, and T4 were 100.62, 114.30, 154.45, The average peak values of N2O emissions in treatments T1, T2, T3, and T4 were 100.62, 114.30, 154.45, and 184.23 µg m 2 h 1 in 2018, and there was a significant difference between T3–T4 treatments and the and 184.23· −µg·m· −−2·h−1 in 2018, and there was a significant difference between T3–T4 treatments and T1 treatment (p 0.05). Overall, the N O peak emission flux increased with the increase in irrigation the T1 treatment< (p < 0.05). Overall,2 the N2O peak emission flux increased with the increase in waterirrigation salinity. Therewater salinity was no. There peak was N2O no emission peak N2O with emission irrigation with irrigation only. only.

600 600 T1 (a) 2017 (b) 2018 ) ) T1 -1 500 T2 -1 500 T2 h h . T3 .

-2 -2 T3 T4

m m T4 . 400 . 400

300 300

200 200 O emissionO flux (ug emissionO flux (ug 2 2 100 100 Soil N Soil N Soil 0 0

05/01 06/01 07/01 08/01 09/01 05/01 06/01 07/01 08/01 09/01 Date (mm/dd) Date (mm/dd)

Figure 10. Changes in N2O emission flux from soil during the growth stage of spring maize under differentFigure treatments 10. Changes in ( ain) 2017N2O andemission (b) 2018.flux from Note: soil The during error the line growth in the stage figure of indicatesspring maize the under standard deviationdifferent (n = treatments3). in (a) 2017 and (b) 2018. Note: The error line in the figure indicates the standard deviation (n = 3).

3.6.2. Seasonal N2O Emission Flux from Different Locations

Figure 11 show that the N2O emission flux from intra- and inter-row soil reached peaks from the first to fifth day after fertilization. The average peak values of N2O emissions in treatments T1, T2, T3, and T4 were 178.09, 207.13, 224.77, and 305.32 µg·m−2·h−1 in intra-row soil, and there was a significant difference between the T4 treatment and T1–T3 treatments (p < 0.05). The average peak values of N2O emissions in treatments T1, T2, T3, and T4 were 57.04, 62.08, 114.89, and 116.11 µg·m−2·h−1 in inter-row soil, and there was a significant difference between T3–T4 treatments and T1– T2 treatments (p < 0.05). Meanwhile, the peak N2O emission flux from intra-row soil was higher than that of inter-row soil under T1–T4 treatments (p < 0.05).

Water 2019, 11, 1548 10 of 19

3.6.2. Seasonal N2O Emission Flux from Different Locations

Figure 11 show that the N2O emission flux from intra- and inter-row soil reached peaks from the first to fifth day after fertilization. The average peak values of N2O emissions in treatments T1, T2, T3, and T4 were 178.09, 207.13, 224.77, and 305.32 µg m 2 h 1 in intra-row soil, and there was a significant · − · − difference between the T4 treatment and T1–T3 treatments (p < 0.05). The average peak values of N2O emissions in treatments T1, T2, T3, and T4 were 57.04, 62.08, 114.89, and 116.11 µg m 2 h 1 in inter-row · − · − soil, and there was a significant difference between T3–T4 treatments and T1–T2 treatments (p < 0.05). Meanwhile, the peak N2O emission flux from intra-row soil was higher than that of inter-row soil underWater 2019 T1–T4, 11, x treatments FOR PEER REVIEW (p < 0.05). 11 of 20

1000 1000 (a) T1 Intra-row (b) T2 Intra-row ) )

-1 -1 Inter-row

h Inter-row h . 800 . 800 -2 -2 m m . .

600 600

400 400 O emissionO flux (ug emissionO flux (ug 2 200 2 200 Soil N Soil N Soil

0 0

05/01 06/01 07/01 08/01 09/01 05/01 06/01 07/01 08/01 09/01 10/01 Date (mm/dd) Date (mm/dd) 1000 1000 (c) T3 Intra-row (d) T4 Intra-row ) ) -1 Inter-row -1 Inter-row h h . 800 . 800 -2 -2 m m . .

600 600

400 400 O emissionO flux (ug emissionO flux (ug 2 200 2 200 Soil N Soil N Soil

0 0

05/01 06/01 07/01 08/01 09/01 05/01 06/01 07/01 08/01 09/01 Date (mm/dd) Date (mm/dd)

Figure 11. Changes in N2O emission flux at different soil locations during the growth stage of spring maizeFigure under 11. Changes different in treatments N2O emission in 2018: flux (a at) T1;different (b) T2; soil (c) T3;locations (d) T4. during Note: Thethe growth error line stage in the of figurespring indicatesmaize under the standard different deviationtreatments (n in= 2018:3). (a) T1; (b) T2; (c) T3; (d) T4. Note: The error line in the figure indicates the standard deviation (n = 3). 3.6.3. N2O Cumulative Flux

3.6.3.The N2O cumulative Cumulative N Flux2O flux under all treatments in 2017 and 2018 is shown in Figure 12a. The cumulative N O flux under T4 treatment increased by 51.18–82.86% in 2017 and 19.83–44.79% in The cumulative2 N2O flux under all treatments in 2017 and 2018 is shown in Figure 12a. The 2018 compared with that under T1–T3 treatments, and the difference between T4 treatment and T1–T2 cumulative N2O flux under T4 treatment increased by 51.18–82.86% in 2017 and 19.83–44.79% in 2018 treatmentscompared inwith the that two yearsunder was T1–T3 significant treatments, (p < 0.05).and the difference between T4 treatment and T1–T2 treatmentsThe cumulative in the two N 2yearsO flux was at di significantfferent locations (p < 0.05). under all treatments in 2018 is shown in Figure 12b. The cumulative N O flux under T4 treatment increased by 22.49–44.76% in intra-row soil and The cumulative2 N2O flux at different locations under all treatments in 2018 is shown in Figure 14.77–46.38% in inter-row soil compared with that under T1–T3 treatments, and the difference between 12b. The cumulative N2O flux under T4 treatment increased by 22.49–44.76% in intra-row soil and T414.77–46.38% treatment and in T1 inter-row treatment soil in intra- compared and inter-row with that soil wasunder significant T1–T3 treatments, (p < 0.05). Also, andthe the cumulative difference between T4 treatment and T1 treatment in intra- and inter-row soil was significant (p < 0.05). Also, the cumulative N2O emission from intra-row soil was significantly higher than that of inter-row soil under T1–T4 treatments (p < 0.05).

Water 2019, 11, 1548 11 of 19

Water 2019, 11, x FOR PEER REVIEW 12 of 20 N2O emission from intra-row soil was significantly higher than that of inter-row soil under T1–T4 treatmentsWater 2019 (, p11<, x0.05). FOR PEER REVIEW 12 of 20 3.0 3.0 2017 (a) Intra-row A (b) 3.0 2018 3.0 Inter-row )

) 2.5

2.5 -1 -1 2017 (a) Intra-row A (b) ha ha .

. 2018 A Inter-row )

) 2.5

2.5 -1 -1 2.0 2.0 AB

ha AB ha .

. a A B B 2.0 AB 2.0 1.5 AB 1.5 B a a B ab B B b ab 1.5 1.5 b B 1.0 b b a 1.0 B ab b ab O cumulative flux (kg O cumulative flux (kg b 2 2 1.0 b b 1.0 N N 0.5 0.5 O cumulative flux (kg O cumulative flux (kg 2 2 N N 0.5 0.5 0.0 0.0 T1 T2 T3 T4 T1 T2 T3 T4 0.0 0.0 Treatment Treatment T1 T2 T3 T4 T1 T2 T3 T4 Figure 12. CumulativeTreatment N2O flux from soil during the growth stage of springTreatment maize under different treatments: (a) cumulative N2O flux in 2017 and 2018; (b) cumulative N2O flux in intra- and inter-row. FigureFigure 12. 12.Cumulative Cumulative N 2NO2O flux flux from from soil soil during during the the growth growth stage stage of of spring spring maize maize under under different different Note: The error line in the figure indicates the standard deviation (n = 3); different capital letters treatments:treatments: (a) ( cumulativea) cumulative N2 ON2 fluxO flux in in 2017 2017 and and 2018; 2018; (b )(b cumulative) cumulative N2 NO2O flux flux in in intra- intra- and and inter-row. inter-row. between treatments represent that the difference in 2017 or intra-row is significant at the 0.05 level; Note:Note: The The error error line inline the in figure the figure indicates indicates the standard the standard deviation deviation (n = 3); different (n = 3);capital different letters capital between letters different lowercase letters between treatments represent that the difference in 2018 or inter-row is treatmentsbetween represent treatments that represent the difference that in the 2017 difference or intra-row in 2017 is significant or intra-row at the 0.05is significant level; different at the lowercase 0.05 level; significant at the 0.05 level. lettersdifferent between lowercase treatments letters represent between that thetreatments difference repr in 2018esent or that inter-row the difference is significant in 2018 at the or 0.05 inter-row level. is significant at the 0.05 level. 3.7.3.7. Spring Spring Maize Maize Yield Yield and and IWUE IWUE 3.7.The SpringThe spring spring Maize maize maize Yield yield andyield andIWUE and IWUE IWUE under under all all treatments treatments in in 2017 2017 and and 2018 2018 is is shown shown in in Figure Figure 13 13.. TheThe increase increaseThe spring in in irrigation irrigation maize wateryield water and salinity salinity IWUE significantly significantlyunder all treatments reduced reduced spring springin 2017 maize maize and yield 2018 yield and is andshown IWUE IWUE in (p Figure <(p 0.05).< 0.05). 13. AfterAfterThe irrigation increase irrigation in with irrigationwith brackish brackish water water water salinity for for onesignificantly one year, year, the the reduced yields yields under spring under T3–T4 maize T3–T4 treatments yield treatments and IWUE significantly significantly (p < 0.05). decreaseddecreasedAfter irrigation by by 11.81–23.93% 11.81–23.93% with brackish compared compared water withfor with one that that year, under under the T1T1yields treatmenttreatment under ((T3–T4pp << 0.05).0.05). treatments After After two twosignificantly years, years, the theyieldsdecreased yields under under by T2–T4 11.81–23.93% T2–T4 treatments treatments compared significantly significantly with decreathat decreased undersed by byT1 13.86–31.47% 13.86–31.47%treatment (p compared compared< 0.05). After with with two that that years, under under theT1 T1treatmentyields treatment under ( p

) A C

-3 AB 10,000 C 4.00 B c

m c . C

10,000 IWUE (kg 4.00 2.00 5000 IWUE (kg Spring maize yield (kg 5000 2.00 Spring maize yield (kg 0 0.00 T1 T2 T3 T4 T1 T2 T3 T4 0.00 0 Treatment Treatment T1 T2 T3 T4 T1 T2 T3 T4 FigureFigure 13. 13.The The yield yield and andTreatment IWUE IWUE of of spring spring maize maize under unde differentr different treatments treatments in 2017Treatmentin 2017 and and 2018: 2018: (a) ( springa) spring maizemaize yield; yield; (b) IWUE.(b) IWUE. Note: Note: The errorThe lineerror in line the figurein the indicates figure indicates the standard the deviationstandard (deviationn = 3); different (n = 3); Figure 13. The yield and IWUE of spring maize under different treatments in 2017 and 2018: (a) spring capitaldifferent letters capital between letters treatments between represent treatments that the represen differencet that in 2017 the isdifference significant in at 2017 the 0.05 is significant level; different at the maize yield; (b) IWUE. Note: The error line in the figure indicates the standard deviation (n = 3); lowercase0.05 level; letters different between lowercase treatments letters represent between that the tr differenceeatments inrepresent 2018 is significant that the atdifference the 0.05 level.in 2018 is different capital letters between treatments represent that the difference in 2017 is significant at the significant at the 0.05 level. 0.05 level; different lowercase letters between treatments represent that the difference in 2018 is significant at the 0.05 level. 3.8. Correlation Analysis among Irrigation Water Salinity, Soil Properties, N2O Emissions and Maize Yield

3.8. CorrelationThe correlation Analysis between among soil Irriga N2tionO emission Water Salinity, flux and Soil soil Properties, properti Nes2 Ois Emissionsshown in andFigure Maize 14. YieldThere was a significant linear correlation between soil N2O emission flux and soil temperature when the The correlation between soil N2O emission flux and soil properties is shown in Figure 14. There soil temperature ranged from 13.7 °C to 30.1 °C, indicating that the soil temperature was an important was a significant linear correlation between soil N2O emission flux and soil temperature when the

soil temperature ranged from 13.7 °C to 30.1 °C, indicating that the soil temperature was an important

Water 2019, 11, 1548 12 of 19

3.8. Correlation Analysis among Irrigation Water Salinity, Soil Properties, N2O Emissions and Maize Yield

The correlation between soil N2O emission flux and soil properties is shown in Figure 14. There was a significant linear correlation between soil N2O emission flux and soil temperature when the soil temperature ranged from 13.7 ◦C to 30.1 ◦C, indicating that the soil temperature was an important factor causing differences in seasonal N2O emission flux. The soil water content and soil N2O emission fluxes were significantly correlated in 2017 but not in 2018, which is attributed to the heavy precipitation in 2018. N2O emission was significantly correlated with the soil water content in intra-row soil, but not with inter-row soil, indicating that the intra-row soil water content was an important factor driving differences in seasonal N2O emissions. In 2017 and 2018, soil N2O emissions were significantly correlated with soil NO . The concentration of soil NO was 33.07–51.76 mg kg 1 3− 3− · − and 25.50–39.78 mg kg 1 when N O reached its emission peak in 2017 and 2018. Soil N O emission flux · − 2 2 was significantly correlated with soil NO3− in intra-row soil but not in inter-row soil, indicating that – the NO3 in intra-row soil was the main factor causing differences in seasonal N2O emission. The correlation among irrigation water salinity, soil properties, soil N2O emission flux and maize yield is shown in Tables3 and4. The result indicated that high-salinity brackish water irrigation significantly increased the water content of the soil tillage layer by affecting the crop’s absorption of water. High-salinity brackish water also increased the salinity content and pH value, and decreased the saturated hydraulic conductivity of the soil tillage layer, thus accelerating the soil salinization and alkalization process. The combined effect of the above results lead to a decrease in the yield of spring maize.

Table 3. Relationship among irrigation water salinity, soil properties, N2O emission flux, and yield of spring maize in 2017.

Variables IWS SWC EC1:5 pH NO3−–N N2O Yield IWS 1 SWC 0.788 ** 1 EC1:5 0.934 ** 0.933 ** 1 pH 0.706 * 0.638 * 0.720 ** 1 NO –N 0.097 0.315 0.185 0.088 1 3− − − N O 0.753 ** 0.756 ** 0.802 ** 0.672 * 0.030 1 2 − Yield 0.877 ** 0.677 * 0.811 ** 0.571 0.219 0.767 ** 1 − − − − − Note: IWS is irrigation water salinity, SWC is soil water content; ** and * represents a significant correlation at the 0.01 and 0.05 levels, respectively.

Table 4. Relationship among irrigation water salinity, soil properties, N2O emission flux, and yield of spring maize in 2018.

Variables Ksat IWS SWC EC1:5 pH NO3−–N N2O Yield

Ksat 1 IWS 0.826 ** 1 − SWC 0.347 0.783 ** 1 − EC 0.630 * 0.948 ** 0.905 ** 1 1:5 − pH 0.833 ** 0.991 ** 0.743 ** 0.925 ** 1 − NO –N 0.625 * 0.259 0.142 0.040 0.269 1 3− − − − N O 0.619 * 0.837 ** 0.674 * 0.799 ** 0.803 ** 0.133 1 2 − − Yield 0.875 ** 0.885 ** 0.530 0.751 ** 0.898 ** 0.367 0.630 * 1 − − − − − Note: IWS is irrigation water salinity, SWC is soil water content, Ksat is saturated soil hydraulic conductivity; ** and * represents a significant correlation at the 0.01 and 0.05 levels, respectively. Water 2019, 11, x FOR PEER REVIEW 13 of 20 factor causing differences in seasonal N2O emission flux. The soil water content and soil N2O emission fluxes were significantly correlated in 2017 but not in 2018, which is attributed to the heavy precipitation in 2018. N2O emission was significantly correlated with the soil water content in intra- row soil, but not with inter-row soil, indicating that the intra-row soil water content was an important factor driving differences in seasonal N2O emissions. In 2017 and 2018, soil N2O emissions were significantly correlated with soil NO3−. The concentration of soil NO3− was 33.07–51.76 mg·kg−1 and 25.50–39.78 mg·kg−1 when N2O reached its emission peak in 2017 and 2018. Soil N2O emission flux Waterwas 2019significantly, 11, 1548 correlated with soil NO3− in intra-row soil but not in inter-row soil, indicating13of that 19 the NO3– in intra-row soil was the main factor causing differences in seasonal N2O emission.

160 160 2017 (a) Intra-row (b) 140 2018 140 Inter-row ) ) -1 -1

h h y=1.4758x-18.13 . 120 y=6.3068x-106.75 . 120 -2 R=0.562** -2 R=0.306* m m

. n=48 . n=52 100 100 y=1.5737x-20.184 y=1.6353x-21.516 R=0.432** R=0.440** 80 n=52 80 n=52

60 60 O emission (ug O emission (ug 2 2 40 40 Soil N Soil N Soil 20 20

0 0 10 15 20 25 30 35 10 15 20 25 30 35 Soil temperature ()℃ Soil temperature ()℃

160 160 2017 (c) Intra-row (d) 140 2018 140 Inter-row ) ) -1 -1 h h . 120 y=368.19x-14.074 . 120 y=251.51x-29.69 -2 R=0.316* -2 R=0.410** m m

. n=44 . n=52 100 100 y=59.918x+7.6065 y=-62.491x+27.258 R=0.108 R=-0.126 80 n=52 80 n=52

60 60 O emission (ug emission O (ug emission O 2 2 40 40 Soil N Soil N Soil 20 20

0 0 0.05 0.10 0.15 0.20 0.25 0.05 0.10 0.15 0.20 0.25

-1 -1 Soil water content (g.g ) Soil water content (g.g )

400 400 2017 (e) Intra-row (f) 2018 Inter-row ) ) -1 -1 h h

y=4.6339x-114.39 . y=4.3573x-29.338 . 300 300 -2 -2 R=0.504** R=0.596** m m . . n=56 n=56

y=3.8125x-48.658 y=0.2787x+24.125 R=0.529** 200 R=-0.051 200 n=56 n=56 O emission (ug emission O O emission (ug 2 2 100 100 Soil N Soil N

0 0 0 102030405060 0 102030405060 - -1 Soil NO --N (mg.kg-1) Soil NO -N (mg.kg ) 3 3

Figure 14. Relationship between (a) soil N2O emission and soil temperature in different years, (b) soil

N2O emission and soil temperature in different locations, (c) soil N2O emission and soil water content in different years, (d) soil N2O emission and soil water content in different locations, (e) soil N2O – – emission and soil NO3 in different years, and (f) soil N2O emission and soil NO3 in different locations. Note: ** and * represents a significant correlation at the 0.01 and 0.05 levels, respectively. Water 2019, 11, 1548 14 of 19

4. Discussion

4.1. Soil Properties Our results are consistent with previous studies, which indicate that irrigation with brackish water had adverse effects on soil properties (Tables3 and4)[20,37,38]. These results are attributed to irrigation with high-salinity brackish water changing the soil osmotic potential, making it difficult for plants to absorb water and slowing transpiration [3]. High-salinity brackish water is rich in Na+ (Table2). The sodium adsorption ratio of irrigation water increased, leading to an increase in soil pH (Figure7), a decrease in soil hydraulic conductivity, and a decrease in the soil infiltration rate (Figure9)[ 39,40]. As a result, soil compaction hindered the movement of water and salt in soil, resulting in an increase in the water and salinity content of the intra-row soil. There was a gradient of water potential between the intra- and inter-row soil under film mulching conditions (Figure5). As a result of this gradient, salt migrated with water from intra-row soil to inter-row soil. This explains why brackish water irrigation increased the soil water content, salinity, and pH value in inter-row soil.

4.2. Soil N2O Emission Dynamics Nitrification and denitrification, in which soil microorganisms and enzymes participate, are the main pathways for N2O emission in farmland soil [13]. Our result is consistent with the conclusion of Scheer et al. [41], who indicated that soil N2O emissions increased significantly when fertilization and irrigation were simultaneously applied. In our study, the soil N2O emission peaks occurred one to five days after simultaneous irrigation and fertilization; after peaking, N2O emissions gradually returned to normal levels, i.e., the level before fertilization. This may be due the significant linear correlation observed between N2O emission flux and soil NO3− (Figure 14). Sufficient substrates were provided for soil nitrification and denitrification after topdressing urea, which promotes soil N2O emission. Our results also show that the soil N2O emission dynamics were significantly correlated with the soil water content and soil temperature (Figure 14). This finding is consistent with Chen et al.’s conclusion from their greenhouse tomato irrigation experiment, which indicated that the soil water content and soil temperature were the dominant factors driving the soil N2O emission dynamics when fertilizer was not applied [42].

4.3. Effect of Irrigation Water Salinity on N2O Emissions

Our study shows that irrigation water salinity had no effect on soil NO3− content (Figure8), indicating that soil nitrification might not be affected by irrigation water salinity. We also found that the soil N2O emission increased with the increase in irrigation water salinity. Although there was no correlation between the seasonal N2O emission flux and seasonal soil EC1:5, the average N2O emission flux had a significant positive correlation with the average soil EC1:5 (Tables3 and4), which is contrary to the correlation between N2O emission and soil NO3− content. This indicates that the effect of salinity on N2O emission was durative rather than explosive. Although opposing results have been reported in some other papers, the discrepancy might be due to a threshold soil salinity level that directed the influence on nitrification and denitrification rates (EC = 1130 µS cm 1)[43]. When the soil salinity was lower than the threshold, the increased 1:5 · − nitrification and denitrification rates were attributed to the increase in soil salinity, whereas the nitrification and denitrification rates decreased when the soil salinity was higher than the threshold [43]. However, this value was higher than the soil EC1:5 measurements in our experiment (Figure6), indicating that salinity might increase the nitrification and denitrification rate. The increase in soil salinity might also result in reduced N2O reductase activity, resulting in the promotion of N2O accumulation in the denitrification process [44]. Because Na+,K+, and higher pH values have stronger salting-out potential, the solubility of N2O in soil solution is expected to decrease after irrigation with high-salinity brackish water [45]. These processes could be a pathway by which salinity promotes N2O emissions. Water 2019, 11, 1548 15 of 19

Because crop water uptake was restricted by irrigation water salinity, the water content in the soil tillage layer was significantly improved by using high-salinity brackish water irrigation compared with other treatments in the actual irrigation process (Figure5). There was a positive correlation between soil N2O emission flux and soil water content (Tables3 and4, and Figure 14). This agrees with the findings of previous studies [12,18,34,36,46], which reported that soil N2O emission flux increased as the soil’s saturated water content increased from 30% to 90%. This occurs because increased water content reduces the oxygen concentration and thereby induces soil nitrification and denitrification and thus the production of N2O. This may be another pathway through which salinity promotes N2O emission. In conclusion, 2.0 g L 1 brackish water irrigation has the potential to significantly reduce · − soil N2O emission while saving freshwater resources. Wang et al. observed the effect of alternating brackish water and freshwater irrigation on soil N2O emission under the same experimental conditions as ours (Table5)[ 26]. Their results indicated that irrigation water salinity and the alternating irrigation method had no significant effect on soil N2O emission. Although this is contrary to our result, the reason may be that alternating irrigation reduces the effect of salinity on soil physical properties. Comparing this with our results, alternating brackish water and freshwater irrigation can potentially reduce soil N2O emission.

Table 5. Effect of different brackish water irrigation methods on soil N2O emission in 2017.

Current Research Wang’s Research [26] N O Flux N O Flux N O Flux Treatment 2 Treatment 2 Treatment 2 (ug m 2 h 1) (ug m 2 h 1) (ug m 2 h 1) · − · − · − · − · − · − 2.0 g L 1 52.30 2.0 g L 1 1:1 47.96 2.0 g L 1 1:2 44.86 · − · − · − 3.5 g L 1 51.10 3.5 g L 1 1:1 46.95 3.5 g L 1 1:2 41.73 · − · − · − 5.0 g L 1 78.17 5.0 g L 1 1:1 44.52 5.0 g L 1 1:2 40.66 · − · − · − Note: 1:1 means to irrigate with freshwater once after one instance of brackish water irrigation; 1:2 means to irrigate with freshwater once after two instances of brackish water irrigation.

4.4. Effect of Different Location on N2O Emissions The proportion of uncovered area in the farmland system cannot be neglected under film mulching conditions. Until now, research was lacking on N2O emissions at different locations under film mulching conditions. Our results demonstrate a positive correlation between soil N2O emission and soil NO3− content in intra-row soil, but there was no correlation with soil NO3− content in inter-row soil (Figure 14). After simultaneous irrigation and fertilization, the N2O emission flux in intra- and inter-row soil of each treatment was improved to different extents, and this may have been caused by the horizontal diffusion of N2O[47]. The average N2O emission flux in intra- and inter-row soil increased as the irrigation water salinity increased, which might also be the result of the interaction between soil water and salinity (Tables3 and4). The result also indicates that soil N 2O emission in intra-row soil was larger than that in inter-row soil. This phenomenon may be ascribed to the fertilization position. In drip irrigation treatments, fertilizers and water can be applied to the root zone directly through drippers, causing intra-row soil to have better water and fertilizer conditions than inter-row soil.

4.5. Effect of Irrigation Water Salinity on Spring Maize Yield Various studies have been conducted on the impact of irrigation water salinity on crop yield [37,38, 48,49]. Zhu et al. and Feng et al. reported that the maize yield decreased with the increase in irrigation water salinity [37,49]. Our results show the same phenomenon. Compared with T1 treatment, the yield under T2–T4 treatments decreased by 7.60–23.93% and 13.86–31.47% in 2017 and 2018, respectively. This may be caused by the relatively poor resistance of maize to Na+ during the rapid growth stage [48]. The increasing irrigation water salinity caused an increase in Na+ in the soil, and irrigation with high-salinity water was found to likely lead to ion toxicity due to Na+ osmotic stress, resulting in a reduction in maize yield [50]. However, there was no significant difference between T1 and T2 Water 2019, 11, 1548 16 of 19 treatments in 2017, indicating that it is feasible to use 2.0 g L 1 brackish water for irrigation in the short · − term when freshwater resources are in short supply. Wang et al. also observed the effect of alternating irrigation with brackish water and freshwater on spring maize yield under the same experimental conditions as ours (Table6)[ 26]. Comparing their results with ours, we surmise that the yield of spring maize could improve by alternating irrigation using brackish water and freshwater compared with the yield when using brackish water irrigation alone. Alternating irrigation can reduce the accumulation of soil salinity and ion toxicity, thus increasing the yield. This means that alternating irrigation with brackish water and freshwater is another way to use brackish water resources in areas with scarce freshwater resources.

Table 6. Effect of different brackish water irrigation methods on spring maize yield in 2017.

Current Research Wang’s Research [26] Treatment Yield (kg ha 1) Treatment Yield (kg ha 1) Treatment Yield (kg ha 1) · − · − · − 2.0 g L 1 13,434 2.0 g L 1 1:1 14,651 2.0 g L 1 1:2 13,914 · − · − · − 3.5 g L 1 12,822 3.5 g L 1 1:1 13,208 3.5 g L 1 1:2 13,636 · − · − · − 5.0 g L 1 11,060 5.0 g L 1 1:1 12,957 5.0 g L 1 1:2 12,449 · − · − · − Note: 1:1 means to irrigate with freshwater once after one instance of brackish water irrigation; 1:2 means to irrigate with freshwater once after two instances of brackish water irrigation.

5. Conclusions Irrigation with 3.5–5.0 g L 1 brackish water promoted the accumulation of soil salt, increased the · − soil pH value, and reduced the soil water conductivity. By affecting the water absorption of crops, the soil water content increased after irrigation with 5.0 g L 1 brackish water. Irrigation with high-salinity · − brackish water accelerated the degree of soil salinization and alkalization. On this basis, due to the interaction between soil water and soil salinity, soil N2O emissions significantly increased by irrigation with 5.0 g L 1 brackish water. Irrigation with 3.5–5.0 g L 1 brackish water significantly reduced the · − · − yield of spring maize. Compared with continuous irrigation with 3.5–5.0 g L 1 brackish water, continuous irrigation · − with 2.0 g L 1 brackish water or alternating irrigation with brackish water and freshwater could slow · − the degree of soil salinization and alkalization, reduce soil N2O emissions, and increase maize yield. Thus, these are potential measures to solving the current agricultural water crisis in Hetao Irrigation District. These results can also provide references for areas considering the use of brackish water.

Author Contributions: F.L., P.Y., and C.W. designed the experiments; C.W., S.W., Y.W., and Z.X. conducted the experiments; S.R. contributed materials; C.W. analyzed the data and wrote the paper; P.Y., Y.Z., Y.X., and R.W. revised the paper. Funding: This research was funded by the National Natural Science Foundation of China, grant numbers 51679239. Acknowledgments: The authors thank Yiqiang Zhang, Yuhong Xia, and Xiangzhu Zhang for their valuable assistance with the experimental work. Conflicts of Interest: The authors declare no conflict of interest.

References

1. Zhang, H.M.; Xiong, Y.W.; Huang, G.H.; Xu, X.; Huang, Q.Z. Effects of water stress on processing tomatoes yield, quality and water use efficiency with plastic mulched drip irrigation in sandy soil of the Hetao Irrigation District. Agric. Water Manag. 2017, 179, 205–214. [CrossRef] 2. He, X.; Yang, P.L.; Ren, S.M.; Li, Y.K.; Jiang, G.Y.; Li, L.H. Quantitative response of oil sunflower yield to evapotranspiration and soil salinity with saline water irrigation. Int. J. Agric. Biol. Eng. 2016, 9, 63–73. [CrossRef] 3. Cucci, G.; Rubino, P.; Caliandro, A. Effects of irrigation water with different salt concentrations and SAR values on soil salinisation and sodification. Ital. J. Agron. 2003, 7, 41–48. Water 2019, 11, 1548 17 of 19

4. Wang, S.J.; Huang, G.H.; Yang, J.G.; Wang, J.; Tai, R.K.; Meng, L.G. Effect of irrigation with saline water on water-salt dynamic and spring wheat yield. Trans. Chin. Soc. Agric. Eng. 2010, 26, 27–33. 5. Tong, W.J.; Chen, Z.D.; Chen, F.; Liu, Q.; Li, Z.H.; Wen, X.Y.; Gao, H.Y.; Chen, A.P.Analysis of maize salt tolerance in Hetao irrigation district and its ecological adaptable region. Trans. Chin. Soc. Agric. Eng. 2012, 28, 131–137. 6. Wang, Q.J.; Shan, Y.Y. Review of research development on water and soil regulation with brackish water irrigation. Trans. Chin. Soc. Agric. Mach. 2015, 46, 117–126. [CrossRef] 7. Yaron, B.; Shalhevet, J.; Shimshi, D. Patterns of salt distribution under trickle Irrigation. In Physical Aspects of Soil Water and Salts in Ecosystems; Springer: Berlin, Germany, 1973; pp. 389–394. 8. Tam, N.F.Y. Effects of wastewater discharge on microbial populations and enzyme activities in mangrove soils. Environ. Pollut. 1998, 102, 233–242. [CrossRef] 9. Irshad, M.; Honna, T.; Yamamoto, S.; Eneji, A.E.; Yamasaki, N. Nitrogen mineralization under saline conditions. Commun. Soil Sci. Plant Anal. 2005, 36, 1681–1689. [CrossRef]

10. Ravishankara, A.R.; Daniel, J.S.; Portmann, R.W. Nitrous oxide (N2O): The dominant ozone-depleting substance emitted in the 21st century. Science 2009, 326, 123–125. [CrossRef] 11. Pachauri, R.K.; Allen, M.R.; Barros, V.R.; Broome, J.; Cramer, W.; Christ, R.; Church, J.A.; Clarke, L.; Dahe, Q.; Dasgupta, P.; et al. Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change; IPCC: Geneva, Switzerland, 2014. 12. Wei, Q.; Xu, J.Z.; Liao, L.X.; Li, Y.W.; Wang, H.Y.; Rahim, S.F. Water salinity should be reduced for irrigation to

minimize its risk of increased soil N2O emissions. Int. J. Environ. Res. Public Health 2018, 15, 2114. [CrossRef] 13. Malla, G.; Bhatia, A.; Pathak, H.; Prasad, S.; Jain, N.; Singh, J. Mitigating nitrous oxide and methane emissions from soil in rice–wheat system of the Indo-Gangetic plain with nitrification and urease inhibitors. Chemosphere 2005, 58, 141–147. [CrossRef][PubMed] 14. Ozlu, E.; Kumar, S. Response of surface GHG fluxes to long-term manure and inorganic fertilizer application in corn and soybean rotation. Sci. Total Environ. 2018, 626, 817–825. [CrossRef][PubMed] 15. Mechler, M.A.A.; Jiang, R.W.; Silverthorn, T.K.; Oelbermann, M. Impact of biochar on soil characteristics and temporal greenhouse gas emissions: A field study from southern Canada. Biomass Bioenerg 2018, 118, 154–162. [CrossRef] 16. Maris, S.C.; Teira-Esmatges, M.R.; Català, M.M. Influence of irrigation frequency on greenhouse gases emission from a paddy soil. Paddy Water Environ. 2016, 14, 199–210. [CrossRef] 17. Pitombo, L.M.; Cantarella, H.; Packer, A.P.C.; Ramos, N.P.; Do Carmo, J.B. Straw preservation reduced total

N2O emissions from a sugarcane field. Soil Use Manag. 2017, 33, 583–594. [CrossRef] 18. Zhang, W.; Zhou, G.W.; Li, Q.; Liao, N.; Guo, H.J.; Min, W.; Ma, L.J.; Ye, J.; Hou, Z.A. Saline water irrigation stimulate

N2O emission from a drip-irrigated cotton field. Acta Agric. Scand. Sect. B-Soil Plant Sci. 2016, 66, 141–152. [CrossRef] 19. Ghosh, U.; Thapa, R.; Desutter, T.; Yangbo, H.; Chatterjee, A. Saline–sodic soils: Potential sources of nitrous oxide and carbon dioxide emissions? Pedosphere 2017, 27, 65–75. [CrossRef] 20. Maucieri, C.; Zhang, Y.; McDaniel, M.D.; Borin, M.; Adams, M.A. Short-term effects of biochar and salinity on soil greenhouse gas emissions from a semi-arid Australian soil after re-wetting. Geoderma 2017, 307, 267–276. [CrossRef] 21. Zou, Q.H.; Ren, S.M.; Yang, P.L.; Niu, Y.T.; Zou, T. Effects of reclaimed water irrigation and brackish water irrigation on soil greenhouse gas emissions. J. Irrig. Drain. 2014, 33, 80–82. [CrossRef] 22. Zhang, L.H.; Song, L.P.; Wang, B.C.; Shao, H.B.; Zhang, L.W.; Qin, X.C. Co-effects of salinity and moisture on

CO2 and N2O emissions of laboratory-incubated salt-affected soils from different vegetation types. Geoderma 2018, 332, 109–120. [CrossRef] 23. Azam, F.; Müller, C. Effect of sodium chloride on denitrification in glucose amended soil treated with ammonium and nitrate nitrogen. J. Plant Nutr. Soil Sci. 2003, 166, 594–600. [CrossRef] 24. Kontopoulou, C.K.; Bilalis, D.; Pappa, V.A.; Rees, R.M.; Savvas, D. Effects of organic farming practices and salinity on yield and greenhouse gas emissions from a common bean crop. Sci. Hortic. 2015, 183, 48–57. [CrossRef]

25. Inubushi, K.; Barahona, M.A.; Yamakawa, K. Effects of salts and moisture content on N2O emission and nitrogen dynamics in Yellow soil and Andosol in model experiments. Biol. Fertil. Soils 1999, 29, 401–407. [CrossRef] Water 2019, 11, 1548 18 of 19

26. Wang, S.J.; Yang, P.L.; Su, Y.P.; Shang, F.Z.; Wei, C.C.; Ren, S.M. Effects of alternative irrigation between

brackish water and fresh water on CO2 and N2O emission from spring maize soil. J. China Agric. Univ. 2018, 23, 41–48. [CrossRef] 27. Wang, X.M.; Liu, H.J.; Zhang, L.W.; Zhang, R.H. Climate change trend and its effects on reference evapotranspiration at Linhe Station, Hetao Irrigation District. Water Sci. Eng. 2014, 7, 250–266. [CrossRef] 28. Zhou, L.F.; He, J.Q.; Qi, Z.J.; Dyck, M.; Zou, Y.F.; Zhang, T.B.; Feng, H. Effects of lateral spacing for drip irrigation and mulching on the distributions of soil water and nitrate, maize yield, and water use efficiency. Agric. Water Manag. 2018, 199, 190–200. [CrossRef] 29. Li, J.G.; Qu, Z.Y.; Chen, J.; Wang, F.; Jin, Q. Effect of different thresholds of drip irrigation using saline water on soil salt transportation and maize yield. Water 2018, 10, 1855. [CrossRef] 30. Ren, Z.S.; Qu, Z.Y.; Li, Z.; Liu, A.Q. Interactive effects of nitrogen fertilization and irrigation on grain yield, water use efficiency and nitrogen use efficiency of mulched drip-irrigated maize in Hetao Irrigation District, China. J. Soil Water Conserv. 2016, 30, 149–155. [CrossRef] 31. Qi, Y.L.; Shi, H.B.; Li, R.P.; Zhao, J.D.; Feng, Y.Y. The effects of water and nitrogen coupling on photosynthetic characteristics under mulched drip irrigation. Water Sav. Irrig. 2017, 42, 50–52. 32. Ma, Z.W.; Gao, X.P.; Tenuta, M.; Kuang, W.N.; Gui, D.W.; Zeng, F.J. Urea fertigation sources affect nitrous oxide emission from a drip-fertigated cotton field in northwestern China. Agric. Ecosyst. Environ. 2018, 265, 22–30. [CrossRef] 33. Han, B.; Ye, X.H.; Li, W.; Zhang, X.C.; Zhang, Y.L.; Lin, X.G.; Zou, H.T. The effects of different irrigation regimes on nitrous oxide emissions and influencing factors in greenhouse tomato fields. J. Soils Sediments 2017, 17, 2457–2468. [CrossRef]

34. Wang, G.S.; Liang, Y.P.; Zhang, Q.; Jha, S.K.; Gao, Y.; Shen, X.J.; Sun, J.S.; Duan, A.W. Mitigated CH4 and N2O emissions and improved irrigation water use efficiency in winter wheat field with surface drip irrigation in the North China Plain. Agric. Water Manag. 2016, 163, 403–407. [CrossRef]

35. Ding, J.J.; Fang, F.L.; Lin, W.; Qiang, X.J.; Xu, C.Y.; Mao, L.L.; Li, Q.Z.; Zhang, X.M.; Li, Y.Z. N2O emissions and source partitioning using stable isotopes under furrow and drip irrigation in vegetable field of North China. Sci. Total Environ. 2019, 665, 709–717. [CrossRef]

36. Yin, G.F.; Wang, X.F.; Du, H.Y.; Shen, S.Z.; Liu, C.R.; Zhang, K.Q.; Li, W.C. N2O and CO2 emissions, nitrogen use efficiency under biogas slurry irrigation: A field study of two consecutive wheat-maize rotation cycles in the North China Plain. Agric. Water Manag. 2019, 212, 232–240. [CrossRef] 37. Feng, G.X.; Zhang, Z.Y.; Wan, C.Y.; Lu, P.R.; Bakour, A. Effects of saline water irrigation on soil salinity and yield of summer maize(zea mays L.) in subsurface drainage system. Agric. Water Manag. 2017, 193, 205–213. [CrossRef] 38. Karlberg, L.; Rockström, J.; Annandale, J.G.; Steyn, J.M. Low-cost drip irrigation—A suitable technology for southern Africa? An example with tomatoes using saline irrigation water. Agric. Water Manag. 2007, 89, 59–70. [CrossRef] 39. McNeal, B.L.; Coleman, N.T. Effect of solution composition on soil hydraulic conductivity. Soil Sci. Soc. Am. J. 1966, 30, 308–312. [CrossRef] 40. Oster, J.D.; Schroer, F.W. Infiltration as Influenced by irrigation water quality. Soil Sci. Soc. Am. J. 1979, 43, 444–447. [CrossRef] 41. Scheer, C.; Wassmann, R.; Kienzler, K.; Ibragimov, N.; Eschanov, R. Nitrous oxide emissions from fertilized, irrigated cotton (Gossypium hirsutum L.) in the Aral Sea Basin, Uzbekistan: Influence of nitrogen applications and irrigation practices. Soil Biol. Biochem. 2008, 40, 290–301. [CrossRef] 42. Chen, H.; Hou, H.J.; Wang, X.Y.; Zhu, Y.; Qaisar, S.; Wang, Y.F.; Cai, H.J. The effects of aeration and irrigation regimes

on soil CO2 and N2O emissions in a greenhouse tomato production system. J. Integr. Agric. 2018, 17, 449–460. [CrossRef] 43. Zeng, W.Z.; Xu, C.; Wu, J.W.; Huang, J.S.; Ma, T. Effect of salinity on soil respiration and nitrogen dynamics. Ecol. Chem. Eng. Sci. 2013, 20, 519–530. [CrossRef] 44. Menyailo, O.V.; Stepanov, A.L.; Umarov, M.M. The transformation of nitrous oxide by denitrifying bacteria in Solonchaks. Eurasian Soil Sci. 1997, 30, 178–180.

45. Heincke, M.; Kaupenijohann, M. Effects of soil solution on the dynamics of N2O emissions: A review. Nutr. Cycl. Agroecosystems 1999, 55, 133–157. [CrossRef]

46. Chen, H.; Hou, H.J.; Cai, H.J.; Zhu, Y. Soil N2O emission characteristics of greenhouse tomato fields under aerated irrigation. Trans. Chin. Soc. Agric. Eng. 2016, 32, 111–117. [CrossRef] Water 2019, 11, 1548 19 of 19

47. Nishimura, S.; Komada, M.; Takebe, M.; Yonemura, S.; Kato, N. Nitrous oxide evolved from soil covered with plastic mulch film in horticultural field. Biol. Fertil. Soils 2012, 48, 787–795. [CrossRef] 48. Zhu, C.L.; Lv, W.; Huang, M.Y.; Zhai, Y.M.; Qiang, C. Effects of biochar on coastal reclaimed soil salinity distribution and maize growth with cycle fresh and saline water irrigation. Trans. Chin. Soc. Agric. Mach. 2019, 50, 227–234. [CrossRef] 49. Zhu, C.L.; Qiang, C.; Huang, M.Y.; Zhai, Y.M.; Lv, W. Effect of alternate irrigation with fresh and slight saline water on physiological growth of summer maize in coastal reclamation area. Trans. Chin. Soc. Agric. Mach. 2018, 49, 253–261. [CrossRef] 50. Munns, R. Physiological processes limiting plant growth in saline soils: Some dogmas and hypotheses. Plant Cell Environ. 2010, 16, 15–24. [CrossRef]

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