Abstract
Gravel mulching is an ancient mulching system with a history of more than 300 years in China. To explore the changes of soil-water content (SWC) and heat transport in watermelon gravel-mulched fields under drip irrigation, we simulated three irrigation quotas (W1, 180 m3/hm2; W2, 270 m3/hm2; and W3, 360 m3/hm2) and three irrigation frequencies (F1, three times; F2, six times; and F3, nine times) based on HYDRUS-2D. The results indicated that peak SWC increased with irrigation quota. The range of fluctuation of SWC decreased as irrigation frequency increased. The temperature of the 0–40 cm soil layer varied with air temperature, but the range of fluctuation decreased with depth. Irrigation affected the distribution of soil water, increased soil heat capacity, and reduced the impact of air temperature on soil temperature, thus delaying the impact of air temperature on soil temperature. High-frequency drip irrigation could therefore effectively improve SWC, reduce water stress during the period of watermelon growth, and effectively delay the effect of air temperature on soil temperature, providing a theoretical basis for developing reasonable irrigation strategies and regulating soil water and heat in gravel-mulched fields.
HIGHLIGHTS
Irrigation affects the distribution of soil moisture and the change of soil temperature.
Under the same irrigation quota, a high-frequency irrigation system is beneficial for increasing the water content of the soil.
High-frequency drip irrigation can effectively reduce the impact of air temperature on the temperature of the soil cultivated layer.
INTRODUCTION
The conditions of soil water and heat are important ecological environmental factors that affect the growth and development of crops and are directly associated with farming methods. Reasonable farming methods (such as mulching and irrigation) can create suitable environments of water and heat for crop growth and development, which are key measures for sustained high crop yields (Dong et al. 2014; Yang et al. 2018). Gravel-mulching is an ancient mulching system with a history of more than 300 years in China. Sand and gravel mulches on the soil surface can increase the rate of use of precipitation, inhibit soil evaporation, prevent secondary salinization, improve soil physical and chemical properties, and substantially increase the storage of water in the soil. Gravel mulching can also conserve soil heat and ultimately increase crop yield (Wang et al. 2017; Zhao et al. 2017, 2019, 2020). Gravel mulching is used in rain-fed agriculture, but rainfall often cannot meet the water demand during crop growth, thereby decreasing yields. Supplementary irrigation is therefore particularly necessary for gravel-mulched fields. Xie et al. (2006) proposed that drip irrigation should replace the previously used extensive flood irrigation. Drip irrigation can increase crop yields in gravel-mulched fields and can stabilize and increase output without aggravating the degradation of gravel-mulched fields.
As a local water-saving method of irrigation applied near the root zones of crops, drip irrigation can be used for managing water and fertilizer use at any time based on the conditions of crop growth. It is widely used in practices of agricultural production and has substantial advantages for conserving water and increasing yields. Different volumes and frequencies of irrigation, however, will inevitably have different effects on crop growth and the distribution and migration of soil water and heat (Sui et al. 2008). Irrigation frequency with the same amount of water is one of the most important factors affecting the conditions of soil water and heat, the use efficiencies of water and fertilizer, and crop yield (Jha et al. 2017; Liu et al. 2019). Chastain et al. (2015) reported that repeated irrigation can greatly increase the yield of ryegrass seed compared with a single irrigation. Cao et al. (2003) found that irrigation frequency could affect the spatial distribution of soil water and the capacity of soil to store water and that an appropriate irrigation frequency in indoor homogeneous soil-column experiments could increase the total volume of water stored in the soil. Wang et al. (2008) found that the average soil-water content (SWC) with high-frequency drip irrigation fluctuated within a relatively stable small range and that drip irrigation could substantially delay the impact of air temperature on ground temperature.
Understanding soil water and temperature is important for the management of drip irrigation, farming, and fertilization. Most studies have investigated the transport of soil water and heat under conditions of plastic-mulching and irrigation using numerical simulations (He et al. 2018; Zhao et al. 2018b; Grecco et al. 2019). Zhang et al. (2018) reported that the HYDRUS model could well simulate SWC and heat transfer for potato farmland under drip irrigation with film mulching. Many studies of gravel-mulched fields have mainly focused on changes in SWC (Wang et al. 2018; Zhao et al. 2020), salt transport (Tan et al. 2018; Hu et al. 2020), the impact of irrigation systems on crop yields (Ma & Tian 2016), and the effect of evaporation on gravel-mulched fields (Yuan et al. 2009; Ma & Li 2011). The impacts of different drip-irrigation systems on SWC and heat transfer in gravel-mulched fields, however, have not yet been studied. We therefore used HYDRUS-2D to simulate changes in SWC and heat in gravel-mulched soil under different irrigation quotas and frequencies, determine the influence of the drip-irrigation systems on the distribution of soil water and heat in a gravel-mulched field, and identify the mechanisms of changes to SWC and heat in a gravel-mulched field under drip irrigation. This study provides theoretical guidance for the design of a reasonable irrigation system for watermelon gravel-mulched fields and for the rational regulation of soil water and heat in these fields.
NUMERICAL MODEL
HYDRUS-2D is a popular software that can simulate water, heat and nutrient dynamics in variably saturated porous media (Šimůnek et al. 2016). HYDRUS-2D uses the Galerkin finite-element method to solve the Richards equations of saturated and unsaturated water flows and the convection–dispersion equations of heat and solute transport. Our study used watermelon on gravel-mulch as the research object, with three drip-irrigation quotas (W1, 180 m3/hm2; W2, 270 m3/hm2; and W3, 360 m3/hm2) and three irrigation frequencies (F1, three times; F2, six times; and F3, nine times), for a total of nine treatments (Table 1). The simulated period was from 31 May to 11 August 2019, for a total of 72 d. The optimal irrigation volume was determined based on the upper and lower limits of SWC. The upper SWC limit was the water-holding capacity of the field (24% SWC by weight) (Ma & Tian 2016), and the lower SWC limit was the most suitable amount of water for each stage of watermelon growth: 40% water-holding capacity at the seedling stage, 50% water-holding capacity at the vining stage, 40% water-holding capacity at the flowering and fruiting stages, 60% water-holding capacity at the swelling stage, and 50% water-holding capacity at the maturation stage.
Irrigation treatments of watermelon in growth period in gravel-mulched field
Treatment . | Irrigation quota (m3/hm2) . | Irrigation frequency . | Irrigation amount at each data (m3/hm2) . | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
06–01 . | 06–08 . | 06–15 . | 06–25 . | 07–01 . | 07–10 . | 07–17 . | 07–25 . | 08–05 . | |||
W1F1 | 180 | 3 | 60 | 0 | 0 | 60 | 0 | 0 | 0 | 60 | 0 |
W1F2 | 180 | 6 | 30 | 0 | 30 | 30 | 0 | 30 | 0 | 30 | 30 |
W1F3 | 180 | 9 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 |
W2F1 | 270 | 3 | 90 | 0 | 0 | 90 | 0 | 0 | 0 | 90 | 0 |
W2F2 | 270 | 6 | 45 | 0 | 45 | 45 | 0 | 45 | 0 | 45 | 45 |
W2F3 | 270 | 9 | 30 | 30 | 30 | 30 | 30 | 30 | 30 | 30 | 30 |
W3F1 | 360 | 3 | 120 | 0 | 0 | 120 | 0 | 0 | 0 | 120 | 0 |
W3F2 | 360 | 6 | 60 | 0 | 60 | 60 | 0 | 60 | 0 | 60 | 60 |
W3F3 | 360 | 9 | 40 | 40 | 40 | 40 | 40 | 40 | 40 | 40 | 40 |
Treatment . | Irrigation quota (m3/hm2) . | Irrigation frequency . | Irrigation amount at each data (m3/hm2) . | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
06–01 . | 06–08 . | 06–15 . | 06–25 . | 07–01 . | 07–10 . | 07–17 . | 07–25 . | 08–05 . | |||
W1F1 | 180 | 3 | 60 | 0 | 0 | 60 | 0 | 0 | 0 | 60 | 0 |
W1F2 | 180 | 6 | 30 | 0 | 30 | 30 | 0 | 30 | 0 | 30 | 30 |
W1F3 | 180 | 9 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 |
W2F1 | 270 | 3 | 90 | 0 | 0 | 90 | 0 | 0 | 0 | 90 | 0 |
W2F2 | 270 | 6 | 45 | 0 | 45 | 45 | 0 | 45 | 0 | 45 | 45 |
W2F3 | 270 | 9 | 30 | 30 | 30 | 30 | 30 | 30 | 30 | 30 | 30 |
W3F1 | 360 | 3 | 120 | 0 | 0 | 120 | 0 | 0 | 0 | 120 | 0 |
W3F2 | 360 | 6 | 60 | 0 | 60 | 60 | 0 | 60 | 0 | 60 | 60 |
W3F3 | 360 | 9 | 40 | 40 | 40 | 40 | 40 | 40 | 40 | 40 | 40 |
Numerical modeling theory for soil water flow
Numerical modeling theory for heat transport
Root water absorption
Initial conditions
Boundary conditions
The simulated area was a rectangle with a length (vertical) of 100 cm and a width (horizontal) of 50 cm. The soil texture in the simulated area was assumed to be uniform and isotropic. The upper boundary of the saturated area for calculation was the flux boundary that varied over time during drip irrigation, which was the third type of boundary condition, and the temperature boundary condition was the third type of boundary condition (Cauchy boundary). Without irrigation, the upper boundary was the atmospheric boundary. The temperature boundary condition was the first type of boundary condition (Dirichlet boundary). The left and right boundaries of the simulated area for calculation were assumed to be impervious, i.e. were zero-flux boundaries, and the temperature boundary condition was the second type of boundary condition (Neumann boundary). The lower boundary of the simulated area for calculation was assumed to be a free-drainage boundary condition due to the depth of the groundwater. The flow boundary condition was then the first type of boundary condition, and the temperature boundary condition was the second type of boundary condition (Neumann boundary).
Model parameters
The thickness of the gravel layer in the simulated area was 10 cm, the soil depth was 100 cm, and the parameters of soil-water transport were predicted using neural networks and the Rosetta module in HYDRUS, based on the composition of the soil particles (part of the American agricultural system). The soil hydraulic parameters are presented in Table 2, and the parameters for the transfer of heat in the soil are presented in Table 3.
Soil hydraulic parameters
Type . | Depth/cm . | θr/cm3.cm−3 . | θs/cm3.cm−3 . | α/cm−1 . | n . | Ks/cm.d−1 . |
---|---|---|---|---|---|---|
Sand | 0–10 | 0.0544 | 0.384 | 0.0302 | 4.705 | 1,567.1 |
Sandy Loam | 10–110 | 0.0352 | 0.382 | 0.0052 | 1.587 | 112.4 |
Type . | Depth/cm . | θr/cm3.cm−3 . | θs/cm3.cm−3 . | α/cm−1 . | n . | Ks/cm.d−1 . |
---|---|---|---|---|---|---|
Sand | 0–10 | 0.0544 | 0.384 | 0.0302 | 4.705 | 1,567.1 |
Sandy Loam | 10–110 | 0.0352 | 0.382 | 0.0052 | 1.587 | 112.4 |
Soil thermal transfer parameters
Type . | Solid . | Org . | DL . | DT . | b1 . | b2 . | b3 . | Cn . | Co . | Cw . |
---|---|---|---|---|---|---|---|---|---|---|
Sand | 0.57 | 0 | 5 | 1 | 4.92 × 106 | −5.20 × 107 | 10.6 × 108 | 6.91 × 107 | 9.04 × 107 | 1.50 × 108 |
Sandy Loam | 0.59 | 0 | 5 | 1 | 5.25 × 106 | 8.49 × 106 | 3.31 × 107 | 6.91 × 107 | 9.04 × 107 | 1.50 × 108 |
Type . | Solid . | Org . | DL . | DT . | b1 . | b2 . | b3 . | Cn . | Co . | Cw . |
---|---|---|---|---|---|---|---|---|---|---|
Sand | 0.57 | 0 | 5 | 1 | 4.92 × 106 | −5.20 × 107 | 10.6 × 108 | 6.91 × 107 | 9.04 × 107 | 1.50 × 108 |
Sandy Loam | 0.59 | 0 | 5 | 1 | 5.25 × 106 | 8.49 × 106 | 3.31 × 107 | 6.91 × 107 | 9.04 × 107 | 1.50 × 108 |
Note: Solid is the ratio of soil solid to total volume; Org is the ratio of organic matter to total volume; DL is the longitudinal thermal diffusivity (cm2·s−1); DT is the transverse thermal diffusivity (cm2·s−1); b1, b2 and b3 are the coefficients in the thermal conductivity function; Cn, Co and Cw are the heat capacity of soil solid phase, soil organic matter and soil liquid phase (J·g−1·°C−1).
RESULTS AND DISCUSSION
Dynamic changes in SWC
SWC of each layer in the nine irrigation treatments tended to increase during irrigation and then gradually decreased as the water evaporated (Figure 1). Under the same irrigation volume, due to the large single irrigation volume, the peak SWC of low-frequency irrigation is larger than that of medium-frequency and high-frequency. For example, the maximum peak SWC of the 10–40 cm layer treated by W1F1 is 2.09%–7.62% and 2.28%–12.08% higher than those of W1F2 and W1F3, respectively. But with the increase of irrigation frequency, the fluctuation range of SWC decreases. High-frequency irrigation has the characteristics of ‘less irrigation for many times’, which makes the SWC of the wet layer higher than other treatments, which is consistent with the research conclusion of Sui et al. (2008).
Dynamic change in soil-water content in the 0–40 cm layer under the irrigation treatments.
Dynamic change in soil-water content in the 0–40 cm layer under the irrigation treatments.
SWC was within the upper limit for all three irrigation quotas, but SWC for F1 was lower than the water content required at the later stages of watermelon growth (Figure 1). The lower limit is when the watermelon will be under some amount of water stress. High-frequency irrigation can effectively reduce the duration of water stress during growth and ensure enough water for growth. Cao et al. (2003) found that increasing irrigation frequency, if appropriate, for the same total irrigation volume could play a role in increasing the amount of soil water stored. Zhang et al. (2020) also found that volumetric SWC was higher under high-frequency irrigation than conventional frequency. The amplitude of fluctuation of SWC was smaller for F3 than the other treatments, indicating that high-frequency irrigation could maintain SWC within a relatively stable range, consistent with the conclusions of Wang et al. (2008).
Distribution of water in the soil profile
An appropriate irrigation volume has a large impact on improving the efficiency of use of soil water. At the same irrigation volume, the higher the frequency, the smaller the volume of a single irrigation and the shallower the depth of water infiltration. Taking the W1 irrigation quotas as an example, the water distribution of the soil profile after irrigation with different treatments is analyzed. The depth of water infiltration at the end of irrigation was >50, 45, and 40 cm for W1F1, W1F2, and W1F3, respectively (Figure 2). The depth of water infiltration was in the order W1F1 > W1F2 > W1F3, and the moist range reached a reasonable water-absorbing root system area of the watermelon. The volumetric SWC of the soil surrounding the drippers gradually decreased 1–2 d after irrigation, and the body of wet soil continued to move downward. The migration distance of the wet soil body was in the order W1F1 > W1F2 > W1F3. Excessive irrigation could thus easily cause the deep infiltration of water that cannot be effectively used by the root system. Increasing the frequency of irrigation to reduce the volume of single irrigations could therefore increase SWC in the main root zone and increase the water-use efficiency of the plant.
Distribution of water in the soil profile after irrigation of W1F1 (a–c), W1F2 (d–f) and W1F3 (g–i).
Distribution of water in the soil profile after irrigation of W1F1 (a–c), W1F2 (d–f) and W1F3 (g–i).
Dynamics of soil temperature
Solar radiation is the main source of heat for soil. Heat is continuously exchanged between the soil and the atmosphere everywhere. The amount of heat in the soil will also vary due to changes in SWC, thereby affecting the distribution of soil temperature. The trend of change of soil temperature was similar among the irrigation treatments in our study (Figure 3). The temperature of each layer varied with the air temperature. The temperature of the surface layer (0–10 cm) was strongly affected by the air temperature, and the temperature fluctuated greatly with the changes in air temperature. The fluctuations in soil temperature were mainly correlated with air temperature, irrigation, and rainfall. The deeper the soil layer, the smaller the influence of air temperature, irrigation, and rainfall, and the smaller the range of fluctuation. The range of fluctuation of the soil temperature decreased with depth, consistent with the results reported by Zhao et al. (2018a).
Dynamic changes in soil temperature in the 0–40 cm layer under the irrigation.
Differences in SWC are a key factor that determines how fast the soil temperature fluctuates due to changes in air temperature. The soil temperature in our study tended to decrease after irrigation, and the increase in temperature decreased, because SWC increased after irrigation and the specific heat capacity of the soil increased with SWC. Irrigation generally delayed the impact of air temperature on soil temperature, because irrigation affected the distribution of water and increased the specific heat capacity of the soil.
Distribution of temperature in the soil profile
The change of soil temperature is closely related to the law of soil water movement. It can be seen from Figure 4 that after irrigation, the soil temperature distribution of the W1F1–W1F3 treatments showed a trend of change from high to low in the vertical direction. The temperature of the soil surface 0–30 cm of the three treatments is 0.5–2.0 °C lower than that of one day after irrigation. This is because after irrigation, the soil temperature decreases with the increase of soil moisture content, indicating that irrigation has a cooling effect on the soil. The surface soil temperature has the largest variation range, while the deep soil is less affected by irrigation, indicating that the influence of irrigation on the surface soil temperature is greater than that of the deep soil. With the influence of soil water consumption and air temperature, the soil temperature increases. This is because the soil temperature drops after irrigation. After the irrigation is completed, the soil temperature slowly rises as the soil moisture is consumed. This is consistent with the results of Qi et al. (2019).
Temperature distribution of soil profile after irrigation of W1F1 (a–c), W1F2 (d–f) and W1F3 (g–i).
Temperature distribution of soil profile after irrigation of W1F1 (a–c), W1F2 (d–f) and W1F3 (g–i).
CONCLUSIONS
Irrigation quotas and frequency strongly affected the distribution of soil water. Irrigation quotas affected SWC by increasing peak SWC as irrigation volume increased. Irrigation frequency affected SWC by decreasing the range of fluctuation of SWC as irrigation frequency increased. The range of fluctuation of SWC was smaller for F3 than for F1 and F2, which is conducive to maintaining SWC within a relatively stable range and effectively reducing the duration of water stress during the period of watermelon growth. The changes in soil temperature tended to be similar in all irrigation treatments. The temperature of each soil layer varied with the changes in air temperature. The temperature of the surface soil layer (0–10 cm) was greatly affected by the air temperature, with large fluctuations with changes in air temperature. The range of fluctuation of soil temperature decreased with depth. Our comprehensive analysis of the effects of different drip-irrigation systems on the distribution of soil water and heat in compacted gravel-mulched soil indicated that high-frequency drip irrigation at the same irrigation volume was conducive to maintaining SWC within a relatively stable range, increasing SWC of the cultivated layer, and effectively regulating changes in soil temperature.
ACKNOWLEDGEMENTS
This research was supported by National Natural Science Foundation of China (51869010), Guidance Program for Industrial Support of Colleges and Universities in Gansu Province (2019C-13), Longyuan Youth Innovation and Entrepreneurship Project and the Lanzhou University of Technology Hongliu first-class discipline funding and Water Conservancy Science Experimental Research and Technology Extension Project of Gansu Province.
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.