Advertisement

Journal of Soils and Sediments

, Volume 19, Issue 12, pp 3982–3993 | Cite as

Soil matric potential and salt transport in response to different irrigated lands and soil heterogeneity in the North China Plain

  • Bingxia Liu
  • Shiqin WangEmail author
  • Xiaole Kong
  • Xiaojing Liu
Soils, Sec 2 • Global Change, Environ Risk Assess, Sustainable Land Use • Research Article

Abstract

Purpose

In the lowland area of the North China Plain (NCP), increasing utilization of brackish water could promote the transformation of precipitation into available water resources, and alleviate the conflict between increase food production and freshwater scarcity. However, the processes of soil water movement and salt migration might be altered, because utilization of brackish water results in frequent changes in groundwater depth and thickness of vadose zone. Thus, it was necessary to understand soil water movement and salt migration when using brackish water for irrigation.

Materials and methods

In this study, soil matric potential (SMP) and total dissolved solids (TDS) at multiple depths were measured in situ to investigate the mechanisms of soil water movement and salt migration at one grassland (site 1) and at three typical irrigated croplands (sites 2, 3, and 4) with different soil textures and groundwater depths in a lowland area of the NCP.

Results and discussion

The study showed that deep soil water and groundwater were recharged generally following heavy precipitation during rainy season. SMP values increased quickly at site 4 due to relatively homogeneous soils, followed by site 3 > site 2 > site 1 with an obvious hysteresis response of SMP at multiple depths to precipitation. Soil water mainly moved downward in piston flow, and preferential flow also existed in the soil above 100 cm in the percolation process at four sites. Generally, SMP values followed the order of site 4 > site 1 > site 2 > site 3 and exhibited an inverse trend for TDS, which was mainly due to soil heterogeneity and soil texture in vertical profiles. The differences in SMP among the four sites were mainly due to land use and groundwater depth. There were significantly differences in spatiotemporal distribution of water and salts between homogenous and heterogeneous soils. The processes of infiltration and water redistribution ended quickly in relatively homogeneous soils after heavy rains. However, there was obvious hysteresis in SMP with an increase in soil depth in heterogeneous soils.

Conclusions

Homogenous soils favored water infiltration, salt leaching, and groundwater recharge, and the flow of soil water flow was blocked and salt accumulated significantly in layered soils. The soil water movement and the transformation relationship between water and salt in the vadose zone provided a basis for utilization of brackish water irrigation in lowland region of the NCP.

Keywords

Brackish water irrigation North China Plain Salt migration Soil water movement Soil matric potential 

1 Introduction

Increasing freshwater scarcity was a global systemic risk (Mekonnen and Hoekstra 2016). Agricultural irrigation was the largest consumptive sector of global freshwater, and water shortage in agriculture will intensify due to increasing demands for food and biofuels (Siebert et al. 2010; Hu et al. 2010; Wada et al. 2012; Ercin and Hoekstra 2014). Brackish water resources were distributed widely in the North China Plain (NCP), and about 35 billion cubic meters of brackish water and saline water resources can be exploited in the Hebei Plain (Qian et al. 2014). Water scarcity in these regions has forced farmers to explore the use of brackish water for agricultural irrigation. Brackish water can be used successfully for crop irrigation, and it was beneficial for crop production and conservation of fresh water (Malash et al. 2012; Singh and Panda 2012; Chen et al. 2016; Liu et al. 2016). However, irrigation using brackish or saline water that contains large quantities of soluble solutes may affect soil salinity, groundwater quality, soil microbial metabolic activity, and food production profoundly (Russo et al. 2014; Wang et al. 2015b; Chen et al. 2016). In lowland areas of the NCP, freshwater shortage and soil salinization were the major factors that inhibit crop yields and sustainable development of agriculture (Yang et al. 2016). How to utilize and manage brackish water and mitigate or prevent land degradation have become important issues (Li 2016; Wu and Sun 2016).

In lowland areas of NCP, soil water and salt dynamics were the major factors that influence crop growth, and research on the transport of soil water and salt can provide scientific evidence for regulating water and salt. Researchers have focused on soil water dynamics and solute transport to estimate groundwater recharge rates and the potential effects on groundwater quality (Dahan et al. 2014; Turkeltaub et al. 2014; Izbicki et al. 2015). Increasing utilization of brackish water could promote the transformation of precipitation into available water resources, and this could alleviate the serious overexploitation of deep groundwater in the NCP (Zhang et al. 2009; Pang et al. 2010). Brackish water utilization also results in frequent changes in groundwater depth in shallow aquifer and in thickness of vadose zone. The processes of soil water movement and salt migration could be changed with alterations in shallow aquifers and vadose zone, so it was necessary to understand soil water movement and soil salt migration under brackish water irrigation.

Characterizing the processes of soil water flow and salt transport in the vadose zone often relies on measurements of soil water content or soil water potential as basic parameters. The soil matric potential (SMP) was probably the most useful way to describe soil water status and movement. The SMP was critical to evaluate soil water flow and solute transport (Hayashi et al. 2009), calculate propagation velocities of the wetting front (Vereecken et al. 2008), and estimate soil water availability to plants (Pan et al. 2013). However, compared with the abundant research on soil water content, less attention has been paid to understanding the dynamics of SMP in the lowland area of NCP. Knowledge of the variability of SMP at different depths can be used to determine the direction of soil water flow and the magnitude of soil water fluxes and to estimate the rate of groundwater recharge (Hubbell et al. 2004; Scanlon et al. 2010). A precise description of SMP could also be used to determine “when” and “how much” to irrigate and to evaluate the impacts of irrigation practices on water movement and salt leaching (Masseroni et al. 2016; Min et al. 2017). Thus, studying the characteristics of SMP dynamics and distribution in the vadose zone was critical for characterizing transport of soil water and salt.

Soil water movement and salt migration were complicated, and they were affected by numerous factors, which include climate conditions; soil properties; such as soil texture, and structure, groundwater depth; and rooting depths of vegetation (Wiesner et al. 2016; Xia et al. 2016; Jia et al. 2017). The main influential factors and their degree of influence on soil water and salt dynamics were quite complex and remain to be analyzed further (Li et al. 2014). Few studies focus on soil water movement and salt migration under brackish water irrigation, where different soil properties and groundwater depths were combined. In this research, SMP and total dissolved solids (TDS) were monitored at four sites with different soil textures, groundwater depths, and different resources of irrigated water. The four field sites included three croplands with different brackish water irrigation regimes and one grassland without irrigation in lowland area of the NCP. The scientific objectives of this study were (1) to illustrate soil water movement and salt transport vertically under different irrigation regimes using brackish water and with different soil textures and groundwater depths, and (2) to reveal the relationship between the factors that influence transport of soil water and salt. The results of the study could be used to provide guidance for water management under agricultural irrigation, such as determining “when” and “how” to irrigate croplands and to avoid soil salinization in lowland areas of the NCP.

2 Material and methods

2.1 Site description

Field experiments were conducted in Nanpi County, which was located in the Low Plain around the Bohai Sea in North China. The climate was semi-humid monsoon, with hot, humid summers, and a rainy season from July to September. During 1990–2016, the average annual precipitation was 562 mm, with about 80% occurring during the rainy season, and the mean annual temperature was 13.2 °C. Water shortage and soil salinization were the major abiotic factors that affect the sustainable development of agriculture in this region. The extensive brackish water resources in Nanpi County in the upper aquifer (shallow groundwater) were stored at a depth of 10–60 m and have TDS of 2–5 g/L (electrical conductivity (EC) of 2.8–8.2 ds/m).

2.2 Experimental design and field observations

Field measurements were conducted in three croplands irrigated with different water resources and one grassland without irrigation. The farmlands all cultivated winter wheat and summer maize in an annual double cropping, agro-system. Generally, winter wheat requires three irrigation applications of 60–80 mm each, and summer maize requires irrigation of about 70 mm (Sun et al. 2010). The different irrigation regimes used shallow groundwater (brackish water, site 2), deep groundwater (freshwater) combined with surface water (salt concentration changed with time) (site 3), and surface water (site 4), and each irrigation event required 60 mm. Geological, hydrogeological, and meteorological characteristic at the four sites were similar. However, there were also some differences in groundwater depths with site 4 > site 1 = site 2 > site 3; site 1 and site 2 were both located in Nanpi Eco-Agricultural Experimental Station, Chinese Academy of Sciences (Table 1).
Table 1

Description of the study sites

 

Site 1

Site 2

Site 3

Site 4

GD range in 2016

300–450 cm

300–450 cm

350–560 cm

180–370 cm

Vegetation

Turfgrass

Winter wheat and Soybean

Winter wheat and summer maize

Winter wheat and summer maize

Irrigation

No

Twice using shallow groundwater (1.90–2.40 g/L) for winter wheat, and no irrigation during soybean growth

Twice using surface water (1.95–2.96 g/L) and once freshwater (about 0.8 g/L) for winter wheat; once freshwater before glowing maize

Three irrigations for winter wheat and once before glowing maize using surface water (1.65–2.85 g/L)

GD is the abbreviation of shallow groundwater depth; the amount of each irrigation is about 60 mm; there are total twice irrigation for site 2, four times irrigation for sites 3 and 4

Soils were sampled at depths of 10, 20, 30, 50, 70, 100, 150, 200, 250, 300, 350, and 400 cm at sites 1, 2, and 3, and sampled at depths of 10, 20, 30, 50, 70, 100, 150, 200, 250, and 300 cm at site 4. Soils were brought back to the laboratory to analyze soil texture and initial TDS. Soil textures were defined according to the international soil classification standard. Soils with sandy loam, loam, sandy clay loam, clay loam, and silt clay loam were distributed in an alternating pattern at site 1 and site 2, and soil layers were clay loam and sandy loam at site 3, which indicated the heterogeneous soil structure at those three sites (Fig. 1). Soil profile at site 4 consisted mostly of silt loam, and it exhibited a relatively homogeneous structure (Fig. 1).
Fig. 1

The vertical distribution of soil texture at the four study sites (particle size fractions based on the international soil classification standard) in the North China Plain

2.3 Measurements

SMP and TDS values were measured at different depths corresponding to soils sampled. SMP was recorded using waterflood tensionmeters during 14 July–30 September 2015 and during 1 April–30 September 2016. No monitoring data were collected from October to the end of March, because the temperature was generally low enough that water froze after injecting the tensionmeter, which could not measure SMP after freezing. During this period, winter wheat grew slowly and soil water and salt movement were minimal. TDS values were calculated by measuring the main ions of soil pore water samples by ion chromatography (ICS-600). Soil pore water samples were collected by soil water sampler and extracted by vacuum pump. Sampling of soil pore water occurred every day after irrigation and after a large precipitation event for 7 days, and every 7 days at other times. Water samples were stored in 30-ml polyethylene bottles, transported to the laboratory, and analyzed within 1 week. All samples were sealed with adhesive tape to reduce evaporation. According to historical weather records, 2015 and 2016 were defined as a wet year and a dry year with precipitation of 755.4 mm and 484.2 mm, respectively.

Precipitation and other meteorological parameters were recorded by a standard weather station at Nanpi Eco-Agricultural Experimental Station, located at 38° 06′ N, 116° 40′ E. Data analysis was conducted using SPSS 19.0, SigmaPlot 12.5, and Excel 2013.

3 Results and discussion

3.1 The dynamics of soil matric potential

In general, SMP decreased with time and depth during the dry season in 0-–100-cm layer (Fig. 2), which was probably due to the stronger influence of evapotranspiration (ET) on the surface and near-surface soil and the relatively stable wetness in deeper soil (Takagi and Lin 2011). This study only analyzed SMP within a 200-cm depth, because the SMP values were almost zero and relatively stable below 200 cm. The high values of SMP in the deep layer were attributed mainly to a relatively shallow groundwater table (Table 1). The temporal dynamics of SMP at four sites were all consistent with water (precipitation and irrigation) input (Fig. 2). Small rain events during the dry season had almost no effect on SMP deeper than 20 cm. Following the heavy precipitation events during the rainy season, the rapid increase in SMP was generally recorded in the vadose zone, especially at shallow depths, shortly after, a reduction in SMP always occurred (Fig. 2). The greater the precipitation, the more SMP increased; however, irrigation events produced different effects on the existence of soil water during different seasons. The recharge depth of soil water was deepest when irrigated in early spring, while in late spring and early summer, precipitation was less and water consumption by crops was large, thus SMP mainly varied above 100 cm.
Fig. 2

Daily precipitation and spatiotemporal variations of SMP as monitored in 200-cm profiles 01/04/2016–30/9/2016 at study sites in the North China Plain

Under the direct effects of infiltration and ET, SMP varied remarkably at each monitored depth above 100 cm, 70 cm, 100 cm, and 30 cm, at sites 1, 2, 3, and 4, respectively (Fig. 2, Table 2). The mean of SMP was largest and the variation was smallest at site 4, followed by site 1, but the variation at site 3 was the largest (Table 2). The largest temporal variation in SMP within 20–200 cm occurred at 50 cm at site 1, 20 cm at site 2, and 30 cm at site 3, which was the depth with the smallest mean SMP, largest range, largest standard deviation (SD), and largest standard error of mean (SE) of SMP (Table 2, Fig. 3). Variations in SMP decreased with depth from 10 cm to 200 cm at site 4, which may have been due to upward recharge of soil water by groundwater (Table 2, Fig. 3). Soil water was affected by groundwater depth, and soil was adversely affected by waterlogging at a shallower groundwater depth and by drought stress at a higher groundwater depth (Xia et al. 2016). For the three croplands, mean SMP showed a trend where site 4 > site 2 > site 3, which corresponded to groundwater depths with site 4 < site 2 < site 3 in 2016. Vegetation was one of the primary factors that affected the dynamics of soil moisture, because its type and coverage largely determined the magnitude of ET (Wang et al. 2015a). Soil water at shallow depths was smaller in croplands than in the grassland, which indicated that farming and crop root growth increased SMP variations in shallow layers. These observations all suggested that the differences in SMP at the four sites were mainly due to land use and groundwater depth.
Table 2

Descriptive statistics of soil matric potential in 2016

 

Depth/cm

Range/cm

Mean/cm

SD

SE

 

Depth/cm

Range/cm

Mean/cm

SD

SE

Site 1

10

244.70

− 130.57

50.60

3.90

Site 3

10

363.20

− 183.93

88.28

6.81

20

189.70

− 110.58

40.63

3.13

20

270.10

− 186.67

65.80

5.08

30

226.10

− 146.59

49.16

3.79

30

335.60

− 207.40

80.34

6.25

50

246.40

− 162.52

56.56

4.36

50

321.20

− 158.16

77.41

5.97

70

227.70

− 141.31

52.16

4.02

70

294.60

− 134.46

71.49

5.52

100

165.30

− 110.03

39.87

3.08

100

160.50

− 85.12

38.16

2.94

150

124.80

− 38.79

17.14

1.32

150

127.70

− 57.53

36.84

2.84

200

67.50

− 31.10

20.15

1.56

200

60.30

− 24.21

19.94

1.54

Site 2

10

281.30

− 180.27

69.78

5.38

Site 4

10

257.50

− 139.27

57.54

5.19

20

302.20

− 198.03

76.45

5.90

20

187.90

− 117.17

39.22

3.44

30

227.80

− 134.30

53.41

4.12

30

141.30

− 87.80

34.10

2.99

50

190.30

− 119.34

40.34

3.11

50

103.80

− 64.04

28.65

2.51

70

185.20

− 121.82

41.12

3.17

70

125.50

− 52.93

27.93

2.45

100

157.90

− 74.99

27.88

2.15

100

102.30

− 49.71

24.29

2.13

150

81.20

− 45.63

19.59

1.51

150

91.20

− 40.92

22.22

1.95

200

52.90

− 23.46

12.42

0.96

200

35.80

− 16.50

9.03

0.79

SE is the abbreviation of standard error of mean; SD is the abbreviation of standard deviation

Fig. 3

The box plots of SMP in 200-cm profiles 1/04/2016–30/9/2016 at study sites in the North China Plain

3.2 Soil water movement after heavy precipitation

As known from the above analysis, small precipitation events contributed little to any increase in SMP. Infiltration and redistribution of soil water generally occurred with heavy precipitation events during the rainy season. One extreme precipitation event occurred on 2 August 2015 with 120.8 mm of rainfall within 24 h. SMP within a 50-cm depth increased rapidly and reached a peak on 2 August, but the response of SMP below these depths was obviously slower at site 1 and site 2 (Fig. 4). Infiltration and water redistribution were completed on 5 August at site 1 and on 6 August at site 2. The relatively longer time lags at deeper depths suggested that hysteresis of SMP to precipitation with depth existed at site 1 and site 2. The response of SMP was much faster at site 3 and site 4, and the infiltration processes were finished on 4 August and 3 August 2015, respectively. These different features were likely caused by the differences in soil texture at the four sites. Textural contrast in soils created a discontinuity in soil hydraulic properties in natural and reclaimed soils, which potentially limited downward water flow and chemical transport (Si et al. 2011).
Fig. 4

The distribution of soil matric potential after extreme rain event with 120.8-mm rainfall

The effects of two heavy precipitation events in 2016 on infiltration and distribution of soil water were analyzed (Fig. 5). The first heavy rainfall event (53.7 mm) occurred on 30 June 2016 before the rainy season. SMP increased at shallow depths and infiltration reached to depths of 100 cm, 100 cm, 150 cm, and 100 cm at site 1, site 2, site 3, and site 4, respectively (Fig. 5a). Redistribution of the percolating water from the upper layer at the four sites was not followed by observable changes in SMP monitored at the deeper layers, which indicated that no deep leakage occurred with the first heavy precipitation. Figure 5 b clearly demonstrates how SMP increased and how water flowed across the vadose zone following the second heavy rainfall event (80.8 mm on 20 July 2016). The values of SMP increased rapidly above 70 cm, 150 cm, 100 cm, and 200 cm at 21 July 2016 at site 1, site 2, site 3, and site 4, respectively. The saturated zone of soil water gradually moved upward at the four sites, except for site 3, during the processes of infiltration and water redistribution. This was due to thick clay loam layers at 30–170 cm that blocked water movement. The saturated depths reached 150 cm, 200 cm, 300 cm, and 150 cm at site 1, site 2, site 3, and site 4, respectively. The response in SMP at different depths was faster at site 4 than at site 1 and site 2.
Fig. 5

The vertical variations of soil matric potential after the (a) first and (b) second heavy precipitation event in 2016

The results showed that there was deep leakage at site 1, site 2, and site 4 after the second heavy precipitation, and it was much more significant in pushing the wetting front to the bottom of the vadose zone. This indicated that shallow groundwater could be recharged at the four sites after the second heavy precipitation, except at site 3 with thick and heavy soil texture layer. In relatively homogeneous soils, the response time of changes in SMP from precipitation was short due to silt loam soils with a faster infiltration rate (site 4). However, hysteresis existed in heterogeneous soils (especially at site 1 and site 2), and soil texture with clay loam and silt clay loam blocked water from moving to deeper depths that resulted in more water stored above 70 cm at site 3. The differences in water infiltration and redistribution were mainly attributed to different soil textures. In a layered soil, water dynamics was affected not only by the interlayer properties and the thickness of the layers, but also by their spatial configuration. Soils with textural layering in profile impeded vertical water movement because of the discontinuity in hydraulic properties (Zornberg et al. 2010; Zettl et al. 2011). Soil profiles with vertical heterogeneity in soil texture hindered vertical water movement, reduced percolation, and stored more water than homogeneous soils with a similar vertical texture (Zornberg et al. 2010; Huang et al. 2011).

3.3 Mechanism of soil water movement

In natural soil profiles, layered soils with vertical texture or structure were ubiquitous and soil profiles with uniform texture were scarce. Thus, water flow in the vadose zone was very complex, and the major mechanisms of soil water movement were uniform flow and preferential flow. In general, the relatively steady and consistent variations in total water potential were observed after a rainstorm at the four sites (Fig. 6). The consistent variations in potential soil profiles and the similar distributions in depths > 100 cm at the four sites indicated there was a uniform infiltration process and that the dominated flow mechanism were matric flow in the percolation process. Rimon et al. (2011) concluded that the water percolation mechanism was governed by matric flow through relatively consistent propagation of the wetting fronts.
Fig. 6

The total soil water potential dynamics after a heavy rain event with 80.8 mm during 19–26 July 2016

Nevertheless, this did not preclude temporal occurrence of preferential flow, especially in shallow layers. Preferential flow was faster than average water movement that moved along a fraction of the pore space, thereby bypassing most of the matrix (Baram et al. 2012). Preferential flow was expected to have been eliminated by the wetting-front propagation process, which wetted the entire domain, even if it did develop on the wetting front (Rimon et al. 2011). There are some differences in variation in total water potential in the upper 100 cm at the four sites, which suggested that other processes resulted in differences in residence time, mixing effect or preferential flow. Total water potential increased rapidly after a heavy rain on 20 July within 30 cm, 70 cm, 50 cm, and 50 cm at site 1, site 2, site 3, and site 4, respectively, which corresponded to the interface of textural layers. The observed pattern of abrupt changes and rapid increases in the total water potential profiles cannot be explained by the slow matrix flow rate (Baram et al. 2012). These patterns were mainly caused by vertical heterogeneous structures, vegetation root channels, worm holes, and other disturbances that likely created macrospores in the soil to allow water to exhibit of preferential flow (Šimůnek et al. 2003; Li et al. 2013).

3.4 The dominant factors of soil salinity dynamics

Soil salt at shallow depths migrated into deeper depths after extreme precipitation, and TDS values of soil water were mainly diluted above 50-cm depths at the four sites (Fig. 7). Precipitation was a critical determinant of salt migration, and heavy precipitation (> 100 mm) caused significant leaching of soluble salts in shallow layers (0–200 cm) (He et al. 2017). Extreme precipitation has a relatively short-term effect on salt leaching in deep soils where the TDS values decreased slightly, but TDS values increased rapidly several days after the rainfall. Furthermore, salt eluted to deeper soil layers when the capillary barrier vanished during the rainy season (Tejedor et al. 2003; Guo et al. 2006). The influencing depths of extreme precipitation on soil salt leaching were consistent with the depth at which soil water was recharged, and the dilution depth was largest at site 4. The finding confirmed that the migration of water and salts was interrelated. This is because most soil salt is related to soil water movement, and the transport of soil water determined the changes and movement of soluble solutes in soil (Zhao et al. 2013; Li et al. 2016; Zhang et al. 2017). The decrease in TDS suggested that there was no accumulation of salts within 50 cm after extreme precipitation due to the leaching effects from infiltration. The TDS values were lowest near the soil surface and accumulated at deep depths at the four sites, but the vertical distribution was different after extreme precipitation. The accumulated depths were related to the uppermost, major layer of clay loam or silt clay loam. The layered soil caused the dynamics of water and salts in layered soils to be very different from that in homogenous soils (Kanzari et al. 2012).
Fig. 7

The distribution of soil salinity dynamics after extreme precipitation with 120.8-mm rainfall on 2 August 2015

The depth of salt accumulation was most thick at site 1, and TDS was largest at site 3. The accumulation layers of soil salt were 50–350 cm at site 1, 70–350 cm at site 2, 50–220 cm at site 3, and 30–170 cm at site 4. TDS decreased first and then increased in the accumulation layers, although TDS values below the accumulation layers showed the inverse tendency at the four sites. Soil layering diluted salt concentrations because of the increase of water content in layered soils (Sadegh-Zadeh et al. 2009). Overall, the TDS was lowest at site 4, followed by site 2 and site 1, and it was largest at site 3. Soil salt leaching was largest at site 4, and least at site 3. This was due to the relatively homogeneous soil texture that resulted in a greater infiltration rate of water and a greater leaching rate of salt at site 4. This was quite different from that in homogeneous soils, because of the discontinuity in hydraulic properties, and both the soil texture and the layering of differently textured soils affected salt migration (Li et al. 2013). Consequently, salt accumulation in the root zone was also tightly linked to the configuration of differently textured soil layers, especially at site 3 with thick loam layers that blocked water and salt transport. Thus, soil texture and layered soil were the dominant factors that influenced the concentration and migration of salt at our sites. Homogeneous soils were more suitable for irrigation with brackish water, and irrigating with brackish water under soils with thick layers of clay loam or silt clay loam should be avoided, especially at shallow depths.

4 Conclusions

This study investigated mechanisms of soil water movement and salt migration by monitoring SMP and TDS under different soil textures, groundwater depths, and land use in a lowland area of the NCP. The results showed that soil water movement generally occurred with heavy precipitation events during the rainy season. Following heavy precipitation during the rainy season, a rapid increase in SMP was recorded, especially at shallow depths. The differences in SMP among the four sites were mainly due to land use and groundwater depth.

The dominant flow mechanism of soil water that moved downward was piston flow during the percolation process at four sites. However, water movement at the four sites was more complex in the upper depths (0–100 cm) than at deeper depths.

Soil texture and its vertical heterogeneity caused the spatiotemporal distribution of water and salts in the layered soil profile to be very different from that in homogenous soils. The processes of infiltration and water redistribution were completed rapidly in relatively homogeneous soils after heavy rains. However, there was obvious hysteresis of SMP with an increase in soil depth in heterogeneous soils. Homogenous soils favored water infiltration, salt leaching, and groundwater recharge. Although the flow of soil water was blocked and salt accumulated significantly in heterogeneous soils, the blocking effects of clay loam on water and salt transport were more significant. The results provide guidance for irrigating with brackish water under different soil textures and soil layers with vertical spatial heterogeneity.

Notes

Acknowledgements

The authors gratefully appreciate the Nanpi Agro-ecology Research Station of Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences.

Funding

The authors received funding from the Science and Technology Service Network (STS) Program of Chinese Academy of Sciences (KFJ-STS-ZDTP-053), the National Natural Science Foundation of China (No. 41601216 and No. 41530859), the Key Support Program of Key Laboratory of Agricultural Water Resources, Chinese Academy of Sciences (ZZKT201603), the 100-Talent Project of Chinese Academy of Sciences, and the Natural Science Foundation of Hebei province (D2017503021).

References

  1. Baram S, Kurtzman D, Dahan O (2012) Water percolation through a clayey vadose zone. J Hydrol 424:165–171Google Scholar
  2. Chen LJ, Feng Q, Wei YP, Li CS, Zhao Y, Li HY, Zhang BG (2016) Effects of saline water irrigation and fertilization regimes on soil microbial metabolic activity. J Soils Sediments 17(2):1–8Google Scholar
  3. Dahan O, Babad A, Lazarovitch N, Russak EE, Kurtzman D (2014) Nitrate leaching from intensive organic farms to groundwater. Hydrol Earth Syst Sci 18:333–341Google Scholar
  4. Ercin AE, Hoekstra AY (2014) Water footprint scenarios for 2050: a global analysis. Environ Int 64:71–82Google Scholar
  5. Guo G, Araya K, Jia H, Zhang Z, Ohomiya K, Matsuda J (2006) Improvement of solute-affected soils: 1. Interception of capillarity. Biosyst Eng 94(1):139–150Google Scholar
  6. Hayashi Y, Kosugi K, Mizuyama T (2009) Soil water retention curves characterization of a natural forested hillslope using a scaling technique based on a lognormal pore-size distribution. Soil Sci Soc Am J 73:55–64Google Scholar
  7. He KK, Yang YH, Yang YM, Chen SY, Hu QL, Liu XJ, Gao F (2017) HYDRUS simulation of sustainable brackish water irrigation in a winter wheat-summer maize rotation system in the North China Plain. Water 9(7):536Google Scholar
  8. Hu YK, Moiwo JP, Yang YH, Han SM, Yang YM (2010) Agricultural water-saving and sustainable groundwater management in Shijiazhuang Irrigation District North China plain. J Hydrol 393:219–232Google Scholar
  9. Huang MB, Barbour SL, Elshorbagy A, Zettl JD, Si BC (2011) Infiltration and drainage processes in multi-layered coarse soils. Can J Soil Sci 91(2):169–183Google Scholar
  10. Hubbell JM, Nicholl MJ, Sisson JB, McElroy DL (2004) Application of a Darcian approach to estimate liquid flux in a deep vadose zone. Vadose Zone J 3(2):560–569Google Scholar
  11. Izbicki JA, Flint AL, O’Leary DR, Nishikawa T, Martin P, Johnson RD, Clark DA (2015) Storage and mobilization of natural and septic nitrate in thick unsaturated zones, California. J Hydrol 524:147–165Google Scholar
  12. Jia XX, Shao MA, Zhu YJ, Luo Y (2017) Soil moisture decline due to afforestation across the Loess Plateau, China. J Hydrol 546:113–122Google Scholar
  13. Kanzari S, Hachicha M, Bouhlila R, Battle-Sales J (2012) Characterization and modeling of water movement and solutes transfer in a semi-arid region of Tunisia (Bou Hajla, Kairouan) -salinization risk of soils and aquifers. Comput Electron Agric 86:34–42Google Scholar
  14. Li P (2016) Groundwater quality in western China: challenges and paths forward for groundwater quality research in western China. Expos Health 8(3):305–310Google Scholar
  15. Li XP, Chang SX, Salifu KF (2013) Soil texture and layering effects on water and solute dynamics in the presence of a water table: a review. Environ Rev 22:41–50Google Scholar
  16. Li JG, Pu LJ, Han MF, Zhu M, Zhang RS, Xiang YZ (2014) Soil salinization research in China: advances and prospects. J Geogr Sci 24(5):943–960Google Scholar
  17. Li P, Wu J, Qian H, Zhang Y, Yang N, Jing L, Yu P (2016) Hydrogeochemical characterization of groundwater in and around a wastewater irrigated forest in the south eastern edge of the Tengger desert, Northwest China. Expo Health 8(3):331–348Google Scholar
  18. Liu XW, Til FK, Chen SY (2016) Effects of saline irrigation on soil salt accumulation and grain yield in the winter wheat-summer maize double cropping system in the low plain of North China. J Integr Agric 15:2886–2898Google Scholar
  19. Malash N, Ali F, Fatahalla M, Hatem M, Tawfic S (2012) Response of tomato to irrigation with saline water applied by different irrigation methods and water management strategies. Int J Plant Prod 2:101–116Google Scholar
  20. Masseroni D, Facchi A, Gandolfi C (2016) Is soil water potential a reliable variable for irrigation scheduling in the case of peach orchards? Soil Sci 181(6):232–240Google Scholar
  21. Mekonnen MM, Hoekstra AY (2016) Four billion people facing severe water scarcity. Sci Adv 2(2):e1500323Google Scholar
  22. Min LL, Shen YJ, Pei HW, Jing BD (2017) Characterizing deep vadose zone water movement and solute transport under typical irrigated cropland in the North China Plain. Hydrol Process 31(7):1–12Google Scholar
  23. Pan L, Adamchuk VI, Martin DL, Schroeder MA, Ferguson RB (2013) Analysis of soil water availability by integrating spatial and temporal sensor-based data. Precis Agric 14:414–433Google Scholar
  24. Pang HC, Li YY, Yang JS, Liang YS (2010) Effect of brackish water irrigation and straw mulching on soil salinity and crop yields under monsoonal climatic conditions. Agric Water Manag 97:1971–1977Google Scholar
  25. Qian Y, Zhang ZJ, Fei YH (2014) Sustainable exploitable potential of shallow groundwater in the North China Plain. Chin J Eco-Agric 22:890–897 in Chinese with English abstract Google Scholar
  26. Rimon Y, Nativ R, Dahan O (2011) Physical and chemical evidence for pore-scale dual-domain flow in the vadose zone. Vadose Zone J 10(1):322–331Google Scholar
  27. Russo D, Laufer A, Gerstl Z, Ronen D, Weisbrod N, Zentner E (2014) On the mechanism of field-scale solute transport: insights from numerical simulations and field observations. Water Resour Res 50:7484–7504Google Scholar
  28. Sadegh-Zadeh F, Seh-Bardan BJ, Samsuri AW, Mohammadi A, Chorom M, Yazdani GA (2009) Saline soil reclamation by means of layered mulch. Arid Land Res Manag 23(2):127–136Google Scholar
  29. Scanlon BR, Reedy RC, Gates JB (2010) Effects of irrigated agro ecosystems: 1. Quantity of soil water and groundwater in the southern High Plains, Texas. Water Resour Res 46:W09537Google Scholar
  30. Si BC, Dyck M, Parkin GW (2011) Flow and transport in layered soils: preface. Can J Soil Sci 91(2):127–132Google Scholar
  31. Siebert S, Burke J, Faures JM, Frenken K, Hoogeveen J, Doll P, Portmann FT (2010) Groundwater use for irrigation- a global inventory. Hydrol Earth Syst Sci 14:1863–1880Google Scholar
  32. Šimůnek J, Jarvis NJ, van Genuchten MT, ärdenäs aA (2003) Review and comparison of models for describing non-equilibrium and preferential flow and transport in the vadose zone. J Hydrol 272:4–35Google Scholar
  33. Singh A, Panda SN (2012) Effect of saline irrigation water on mustard (Brassica juncea) crop yield and soil salinity in a semi-arid area of North India. Exp Agric 48:99–110Google Scholar
  34. Sun HY, Shen YJ, Yu Q, Flerchinger GN, Zhang YQ, Liu CM, Zhang XY (2010) Effect of precipitation change on water balance and WUE of the winter wheat–summer maize rotation in the North China Plain. Agric Water Manag 97(8):1139–1145Google Scholar
  35. Takagi K, Lin HS (2011) Temporal dynamics of soil moisture spatial variability in the Shale Hills Critical Zone Observatory. Vadose Zone J 10(3):832–842Google Scholar
  36. Tejedor M, Jimenez CC, Diaz F (2003) Use of volcanic mulch to rehabilitate saline-sodic soils. Soil Sci Soc Am J 67(6):1856–1861Google Scholar
  37. Turkeltaub T, Dahan O, Kurtzman D (2014) Investigation of groundwater recharge under agricultural fields using transient deep vadose zone data. Vadose Zone J 13(4).  https://doi.org/10.2136/vzj2013.10.0176 Google Scholar
  38. Vereecken H, Huisman JA, Bogena H, Vanderborght J, Vrugt JA, Hopmans JW (2008) On the value of soil moisture measurements in vadose zone hydrology: a review. Water Resour Res 44:W00D06Google Scholar
  39. Wada Y, van Beek LPH, Bierkens MFP (2012) Non-sustainable groundwater sustaining irrigation: a global assessment. Water Resour Res 48:335–344Google Scholar
  40. Wang T, Wedin DA, FranzTE HJ (2015a) Effect of vegetation on the temporal stability of soil moisture in grass-stabilized semi-arid sand dunes. J Hydrol 521:447–459Google Scholar
  41. Wang XP, Yang JS, Liu GM, Yao RQ, Yu SP (2015b) Impact of irrigation volume and water salinity on winter wheat productivity and soil salinity distribution. Agric Water Manag 149:44–54Google Scholar
  42. Wiesner S, Gröngröft A, Ament F, Eschenbach A (2016) Spatial and temporal variability of urban soil water dynamics observed by a soil monitoring network. J Soils Sediments 16(11):2523–2537Google Scholar
  43. Wu J, Sun Z (2016) Evaluation of shallow groundwater contamination and associated human health risk in an alluvial plain impacted by agricultural and industrial activities, mid-west China. Expos Health 8(3):311–329Google Scholar
  44. Xia JB, Zhang SY, Zhao XM, Liu JH, Chen YP (2016) Effects of different groundwater depths on the distribution characteristics of soil-Tamarix water contents and salinity under saline mineralization conditions. Catena 142:166–176Google Scholar
  45. Yang LL, Ding XQ, Liu XJ, Li PM (2016) Impacts of long-term jujube tree/winter wheat-summer maize intercropping on soil fertility and economic efficiency-A case study in the lower North China Plain. Eur J Agron 75:105–117Google Scholar
  46. Zettl JD, Barbour SL, Huang M, Si BC, Leskiw LA (2011) Influence of textural layering on field capacity of coarse soils. Can J Soil Sci 91(2):133–147Google Scholar
  47. Zhang ZJ, Luo GZ, Wang Z, Liu CH, Li YS, Jiang XQ (2009) Study on sustainable utilization of groundwater in North China plain. Resour Sci 31(3):355–360 in Chinese with English abstract Google Scholar
  48. Zhang X, Li P, Li ZB, Yu GQ (2017) Soil water-salt dynamics state and associated sensitivity factors in an irrigation district of the loess area: a case study in the luohui canal irrigation district, China. Environ Earth Sci 76(20):715Google Scholar
  49. Zhao XF, Xu HL, Zhang P, Fu JY, Bai Y (2013) Soil water, salt, and groundwater characteristics in shelterbelts with no irrigation for several years in an extremely arid area. Environ Monit Assess 185:10091–10100Google Scholar
  50. Zornberg JG, Bouazza A, McCartney JS (2010) Geosynthetic capillary barriers: current state of knowledge. Geosynth Int 17(5):273–300Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Bingxia Liu
    • 1
  • Shiqin Wang
    • 1
    Email author
  • Xiaole Kong
    • 1
    • 2
  • Xiaojing Liu
    • 1
  1. 1.Key Laboratory of Agricultural Water Resources, Hebei Laboratory of Agricultural Water-Saving, Center for Agricultural Resources Research, Institute of Genetics and Developmental BiologyChinese Academy of SciencesShijiazhuangChina
  2. 2.University of Chinese Academy of SciencesBeijingChina

Personalised recommendations