# Effect of Plastic Film Residue on Vertical Infiltration Under Different Initial Soil Moisture Contents and Dry Bulk Densities

^{*}

## Abstract

**:**

_{PF}) remains in the soil. The application of a R

_{PF}to a soil will alter soil moisture processes, and thus, affect the soil water distribution and its effectiveness. A quadratic regression orthogonal design was used to study the effects of initial moisture content (I

_{MC}), dry bulk density (D

_{BD}), residual plastic film content (R

_{PFC}), and the burial depth of R

_{PF}on the migration time of wetting front (M

_{F}), moisture content (M

_{C}), and accumulative infiltration (A

_{I}) of a test soil. It was found that I

_{MC}, D

_{BD}, and R

_{PFC}were the main factors affecting M

_{C}, M

_{F}, and A

_{I}, while the burial depth of R

_{PF}had no significant influence. The order of influence for the factors affecting M

_{F}was I

_{MC}> D

_{BD}> R

_{PFC}, while the order of influence for the factors affecting M

_{C}and A

_{I}was D

_{BD}> I

_{MC}> R

_{PFC}. R

_{PFC}was parabolic in relation to M

_{F}, M

_{C}, and A

_{I}, when it was in the range of 50–100 kg/hm

^{2}, while within the same range M

_{C}and A

_{I}reached a maximum and M

_{F}reached a minimum. The analysis of the interactive responses revealed that when the D

_{BD}was greater than 1.29g/cm

^{3}, the M

_{F}initially decreased and then increased with the increase of R

_{PFC}. When the R

_{PFC}was more than 100 kg/hm

^{2}, the M

_{F}initially increased and then decreased with the increase of the D

_{BD}. When the D

_{BD}was larger than 1.31 g/cm

^{3}, the A

_{I}initially increased and then decreased with the increase of R

_{PFC}. It was apparent that the R

_{PF}not only had a blocking effect on the wetting front, but also affected the water flow. When the R

_{PFC}was between 50 and 100 kg/hm

^{2}, the soil M

_{C}was significantly increased. It was suggested that the R

_{PF}pollution area should increase the mechanical recovery of plastic film, standardize the use and recycling of agricultural R

_{PF}, optimize the planting model, and establish a recyclable model for the treatment of R

_{PF}pollution, and it was proposed that the R

_{PFC}remaining after recovery of the R

_{PF}should be less than 50 kg/hm

^{2}.This study can prove the law of soil water movement in the residue film pollution area and provide reference and solution ideas for the comprehensive treatment of residue film pollution in farmland.

## 1. Introduction

_{PF}) affecting soil productivity has been ignored for a long time [13,25]. In addition, to reduce production costs, the thickness of the plastic film applied has decreased in recent years, which has led to an increased incidence of film breakage, while recovery has become more difficult. The accumulation rate of R

_{PF}in agricultural soils is accelerating, and the area of polluted land is expanding [26]. In the long term, the negative outcomes of plastic film pollution will gradually outweigh the economic benefits of the heat and moisture preservation [27,28]. However, the large production costs of degradable membranes make them difficult to promote [29]. Therefore, plastic film cannot currently be replaced by alternative products.

_{PF}on soil infiltration and soil water redistribution, with problems such as soil moisture availability receiving little attention. Previous studies have been conducted to investigate the influence of R

_{PFC}and burial depth of R

_{PF}on soil infiltration [35]. The influence of excessive applications and burial depths of R

_{PF}have been considered as single factors [36] and the relationship between the soil M

_{C}and the migration time of wetting front (M

_{F}), and the burial depth of R

_{PF}, R

_{PFC}, dry bulk density (D

_{BD}), and initial moisture content (I

_{MC}) need to be studied in terms of their interactive effects on the M

_{F}and their influence on soil M

_{C}.

_{PFC}, burial depth of R

_{PF}, D

_{BD}, and I

_{MC}on the M

_{F}and soil M

_{C}; (2) determine the influence of the interactions between two factors on the M

_{F}and soil M

_{C}; (3) establish an optimal R

_{PFC}and soil permeability, where the relationship between the plastic film and land use does not influence the production capacity of the land; and (4) determine a theoretically reasonable irrigation system in areas affected by plastic membrane pollution.

## 2. Materials and Methods

#### 2.1. Experimental Site

#### 2.2. Experimental Materials and Devices

_{MC}was 2.0%. Soil particle size was determined by an MS2000 laser particle size analyzer (Malvern Instruments, Malvern, UK). Clay particles (d < 0.002 mm) comprised 22.1% of the soil, fine particles (0.002 < d < 0.005 mm) accounted for 5.8%, medium sized powder (0.005 < d < 0.02 mm) accounted for 26.4%, powder (0.02 < d < 0.05 mm) accounted for 37.8%, and extremely fine sand (0.05 < d < 0.25 mm) accounted for 7.93%. The saturated hydraulic conductivity and saturated soil moisture were 24.36 cm d

^{−1}and 0.48 cm

^{3}cm

^{−3}, respectively. The soil organic carbon was 6.50 g kg

^{−1}. The dry bulk density of soil was 1.40 gcm

^{−3}. The basic physical and chemical shape of soil was: organic matter 11.20 g kg

^{−1}, total nitrogen 0.93 g kg

^{−1}, nitrate nitrogen 76.27 mg kg

^{−1}, available phosphorus 25.38 mg kg

^{−1}, available potassium 131.97 mg kg

^{−1}, PH value was 8.12.

_{C}at the end of the test, and rubber plugs were used to seal the holes and prevent leakage during the experiment.

#### 2.3. Design and Methods

#### 2.3.1. Experimental Design

_{MC}, D

_{BD}, R

_{PFC}, and burial depth of R

_{PF}) were selected for testing in the experiment, with each factor selected at five levels. A four-factor and five-level quadratic regression orthogonal experimental design was adopted. Each factor had five levels and a total of 36 combinations. Each combination was repeated three times and the results were averaged. The horizontal coding tables of each factor are shown in Table 1 and the experimental scheme is shown in supplementary materials.

#### 2.3.2. Data Analysis

_{j}

_{ik}represents the data corresponding to row i of Z

_{k}in supplementary materials, Zʹ

_{ik}represents the data corresponding to row i of Zʹ

_{i}in supplementary materials, and y

_{i}represents the data corresponding to row i of y in supplementary materials.

#### Testing of the Regression Equation

#### Testing of the Fitting Degree of the Equation

_{0}is the number of zero level tests.

## 3. Results

#### 3.1. Analysis of the M_{F}

_{PF}on water movement. The R

_{PF}in the field blocks the soil pores and restricts soil water movement, which results in a decrease in the soil water carrying capacity and affects the movement and distribution of the moisture front.

_{F}and I

_{MC}, D

_{BD}, R

_{PFC}, and burial depth of R

_{PF}were obtained. An analysis of variance (ANOVA) of the quadratic regression models was conducted. The results are shown in Table 2. The results showed that the linear terms of I

_{MC}, R

_{PFC}, and D

_{BD}, the quadratic terms of R

_{PFC}and D

_{BD}, and the interaction terms of I

_{MC}and D

_{BD}, D

_{BD}and R

_{PFC}reached significant levels (

**P**< 0.01), while the other terms were not significant. A simplified regression equation (Equation (12) was obtained after eliminating the non-significant items. Because an orthogonal design was adopted and all factors were coded by non-coding, all regression coefficients were independent of each other. Therefore, the remaining factors were fixed at zero, and an equation describing the relationship between the single factor and the M

_{F}was obtained. A diagram showing the relationship between the single factor and the M

_{F}was constructed using Origin. The same procedure was used to determine the relationship between the two-factor interaction effect and the M

_{F}, and a three-dimensional figure was constructed using Matlab.

_{F}followed the order of I

_{MC}> D

_{BD}> R

_{PFC}(133.92 > 85.58 > 49.42). It can be seen from Figure 3 that the M

_{F}decreased linearly with the increase of I

_{MC}and the M

_{F}increased with the increase of D

_{BD}, but the growth rate decreased slowly. The M

_{F}initially decreased and then increased with the increase of R

_{PFC}, reaching a minimum when the R

_{PFC}was 51kg/hm

^{2}(Z

_{3}= −0.98). It can be seen from Figure 4 that when the D

_{BD}was greater than 1.29g/cm

^{3}(Z

_{2}> −1), the M

_{F}initially decreased and then increased with the increase of R

_{PFC}. When the R

_{DD}of soil was less than 1.29 g/cm

^{3}(Z

_{2}< −1), the M

_{F}increased with the increase of R

_{PFC}. When the R

_{PFC}was more than 100 kg/hm

^{2}(Z

_{3}> 0), the M

_{F}initially decreased and then increased with the increase of the D

_{BD}. When the R

_{PFC}was less than 100 kg/hm

^{2}(Z

_{3}< 0), the M

_{F}increased with the increase of D

_{BD}.

_{1}+ 85.58Z

_{2}+49.42Z

_{3}− 21.10Z

_{2}

^{2}+25.15Z

_{3}

^{2}− 42.13Z

_{1}Z

_{2}− 48.38Z

_{2}Z

_{3}

#### 3.2. Analysis of theAccumulative Infiltration (A_{I})

_{PF}. The distribution of soil water indirectly reflected the blocking effect of R

_{PF}on water movement. The R

_{PF}in the field blocks the soil pores, limiting soil water movement. This results in a decrease in the soil water carrying capacity and affects the movement and distribution of the moisture front. According to the analysis method described in data analysis, regression equations were obtained for A

_{I}and I

_{MC}, D

_{BD}, R

_{PFC}, and burial depth of R

_{PF}, and an ANOVA of the regression equation was conducted, with the results shown in Table 3. After eliminating the non-significant items, the simplified regression equation shown in Equation (13) was obtained.

_{I}was determined and was found to follow the order of DBD ˃ IMC ˃ R

_{PFC}(759.43 ˃ 287.61 ˃ 233.07). The other factors were fixed to zero to obtain an equation describing the relationship between each single factor and A

_{I}, and a diagram to highlight this was constructed with Origin (Figure 5). From Figure 5, it can be seen that the A

_{I}decreased linearly with the increase of I

_{MC}and D

_{BD}, with the relationship having a negative correlation. The A

_{I}initially increased and then decreased with the increase of R

_{PFC,}displaying a parabolic curve. When the R

_{PFC}reached 53kg/hm

^{2}(Z

_{3}= −0.94), the A

_{I}reached its maximum value. By fixing the I

_{MC}at zero, an equation describing the relationship of A

_{I}, D

_{BD}, and R

_{PFC}was obtained and Matlab was used to construct a three-dimensional diagram (Figure 6). The analysis of the interaction effect showed that when the D

_{BD}was more than 1.31 g/cm

^{3}(Z

_{2}= −0.69), the A

_{I}initially increased and then decreased with the increase of R

_{PFC}. When the D

_{BD}was less than 1.31 g/cm

^{3}(Z

_{2}= −0.69), the A

_{I}decreased linearly with the increase of R

_{PFC}.

_{1}− 759.43Z

_{2}− 233.07Z

_{3}− 125.48Z

_{3}

^{2}+391.13Z

_{2}Z

_{3}

#### 3.3. Analysis of the M_{C}

_{C}refers to the ratio of the weight of water in the soil to the weight of the corresponding solid phase material [40]. According to the analysis method used in data analysis, regression equations were obtained for M

_{C}and I

_{MC}, D

_{BD}, R

_{PFC}, and burial depth of R

_{PF}, and an ANOVA of the regression equation was conducted, with the results shown in Table 4, Table 5, Table 6 and Table 7. According to these tables, regression equations between M

_{C}in each layer and each factor were obtained after eliminating the insignificant items (Equations (14–17)). These four equations were used to describe the relationship between the M

_{C}in each layer and each factor (Figure 7). It can be seen from the figure that the M

_{C}in the four layers declined linearly with the increase in I

_{MC}and D

_{BD}, with the relationships having a negative correlation. With the increase of R

_{PFC}, the M

_{C}initially increased and then decreased. In the 0–10cm layer, when the R

_{PFC}was 74kg/hm

^{2}(Z

_{3}= −0.52), the M

_{C}reached a maximum. In the layer 10–20cm, when the R

_{PFC}was 68kg/hm

^{2}(Z

_{3}= −0.64), the M

_{C}reached a maximum. In the 20–30cm layer, when the R

_{PFC}was 71kg/hm

^{2}(Z

_{3}= −0.58), the M

_{C}reached a maximum. In the 30–40cm layer, when the R

_{PFC}was 59kg/hm

^{2}(Z

_{3}= −0.82), the M

_{C}reached a maximum. There was no significant effect of burial depth of R

_{PF}on soil M

_{C}, and there was no interaction between the two factors.

_{1}− 1.81Z

_{2}− 0.46Z

_{3}− 0.44Z

_{3}

^{2}

_{1}− 2.06Z

_{2}− 0.56Z

_{3}− 0.44Z

_{3}

^{2}

_{1}− 2.04Z

_{2}− 0.58Z

_{3}− 0.50Z

_{3}

^{2}

_{1}− 1.67Z

_{2}− 0.61Z

_{3}− 0.37Z

_{3}

^{2}

## 4. Discussion

#### 4.1. Burial Depth of R_{PF}

_{PF}had little effect on the M

_{F}, A

_{I}, and soil M

_{C}(P < 0.01), and had no significant effect on the results. However, some studies have pointed out that the burial depth of R

_{PF}in the soil had a large influence on the water infiltration wetting front [41], and there was a significant difference between the movement of the wetting front in the 0–10 and 10–20 cm soil layers [42]. This might be due to the fact that the water head is subject to a certain gravity effect under a certain water head (the constant water head was 6 cm in the present study), and the infiltration process occurs under a state of constant soil air pressure. The M

_{F}was rapid, with the slowest time being 720min when the wetting front moved down to 40 cm, with the result that there was no significant effect of the burial depth of R

_{PF}on the M

_{F}. Due to the small range of R

_{PFC}values (0–200 kg/hm

^{2}) and the fast infiltration rate, the burial depth of R

_{PF}did not significantly affect the soil M

_{C}and A

_{I}. Therefore, in the planting area where the infiltration rate of the water is faster, the influence of the buried depth of the residual film on the infiltration can be ignored for the time being.

#### 4.2. The R_{PFC}

_{PFC}was <51 kg/hm

^{2}, the M

_{F}decreased with the increase in R

_{PFC}, which was conducive to the downward movement of water. When the R

_{PFC}was greater than 51 kg/hm

^{2}, the M

_{F}increased with the increase in R

_{PFC}, which had a blocking effect on the downward movement of the wetting front in the soil [16]. Most previous studies have shown that the R

_{PFC}only had a blocking effect on water transport. In the present study, when the R

_{PFC}was <51 kg/hm

^{2}, the distribution of R

_{PF}in the soil was relatively scattered, and R

_{PF}was present in various forms such as sheets, rods, balls, and cylinders. When water flowed over the R

_{PF}, the smooth surface of the plastic film formed a smooth diversion surface, enabling water to move rapidly downward. When the R

_{PFC}was >51kg/hm

^{2}, there were many molecular chain branches within the R

_{PF}. After encountering water, the adsorption capacity of the adjacent R

_{PF}increased, reducing the number of rapid water transport channels and the cross-sectional area of the soil water. The air pressure of the interface between R

_{PF}and soil particles increased with the increase in the amount of infiltration water [43]. A narrow wet area could then easily form at the front of the R

_{PF}due to the presence of the different large non-uniform flow fields. The soil in the wet area could not achieve a water balance with other areas, in which a water balance is driven by the matrix potential in the short-term. This reduced the driving effect of the matrix potential on the soil water and enhanced the blocking effect of the R

_{PF}on soil water movement. This observation was similar to the results of previous studies obtained by adding other mulches.

_{PFC}and A

_{I}was described by a parabola (a < 0). When the R

_{PFC}was 53 kg/hm

^{2}, A

_{I}reached its maximum value. This was because when the R

_{PFC}was less than 53 kg/hm

^{2}, the water transfer rate was faster with an increase in the R

_{PFC}, which led to a gradual increase in A

_{I}. When the R

_{PFC}was >53 kg/hm

^{2}, the R

_{PF}formed an isolation layer in the soil, which destroyed the uniformity of the soil texture and its configuration, changed the soil water potential at the interface between the R

_{PF}and the soil, reduced the number of macropores in the soil, and reduced the soil water carrying capacity. As a result, the blocking effect of R

_{PF}on the horizontal movement of soil water gradually increased, and then A

_{I}gradually decreased with an increase in R

_{PFC}.

_{PFC}, where α <0, with maximum values of 74, 68, 71, and 59 kg/hm

^{2}, respectively. When the R

_{PFC}was 50–100 kg/hm

^{2}, the water content of each soil layer reached a maximum. There may be some experimental error in this test because when the water content of each layer was at a maximum the maximum R

_{PFC}was not consistent, but all values were within the range of 50–100 kg/hm

^{2}.

#### 4.3. The I_{MC}and D_{BD}

_{MC}, the M

_{F}, A

_{I}, and soil M

_{C}all decreased linearly. This was because the higher the I

_{MC}of the soil, which could degrade the effectiveness of soil infiltration and permeability [12], resulting in less A

_{I}. For the same infiltration time less water was able to infiltrate soils with a higher I

_{MC}, and therefore, the M

_{F}was shorter and the water M

_{C}decreased accordingly.

_{BD}of the soil was positively correlated with the M

_{F}, and negatively correlated with A

_{I}and M

_{C}. This was because the larger the D

_{BD}, the smaller the pores between the soil particles, the greater the blocking effect on soil water migration, and fewer water molecules can be contained in the soil. The D

_{BD}was therefore positively related to the M

_{F}and negatively related to the A

_{I}and M

_{C}. However, with an increase in the D

_{BD}, the porosity of the soil decreased and the influence of D

_{BD}on soil infiltration was reduced. This resulted in a decrease in the advance of the wetting front.

#### 4.4. Interaction Effects Between Two Factors

_{BD}of soil was <1.29 g/cm

^{3}, with an increase in the R

_{PFC}the M

_{F}increased. When the D

_{BD}of soil was >1.29 g/cm

^{3}, with an increase in the R

_{PFC}, the M

_{F}initially decreased and then increased. When the D

_{BD}was >1.31 g/cm

^{3}, the A

_{I}initially increased and then decreased with an increase in the R

_{PFC}. When the D

_{BD}was <1.31 g/cm

^{3}, the A

_{I}decreased linearly with an increase in the R

_{PFC}. This was because the soil D

_{BD}was small and the soil porosity was large, with the shape of the R

_{PF}being more irregular in soil with a small D

_{BD}than in soil with a large D

_{BD}. The R

_{PF}isolation layer destroyed the capillary connectivity of the soil, blocked the continuity of the soil pore connectivity and the water transmission capacity, reduced the vertical infiltration capacity of the soil water, and caused the soil water movement to slow down, which influenced the A

_{I}. When the D

_{BD}was large and the R

_{PFC}was small, the soil porosity was small, and a dense blocking layer formed between the soil particles. A lower R

_{PFC}could form a surface to guide the flow of water, which would promote the infiltration of soil water and reduce the M

_{F}, which would lead to an increase in the A

_{I}. When the R

_{PFC}was <100 kg/hm

^{2}, the M

_{F}increased with the increase of D

_{BD}. When the R

_{PFC}was more than 100 kg/hm

^{2}, the M

_{F}changed to a lesser extent with the increase in R

_{PFC}. This was because when the R

_{PFC}was large, the D

_{BD}of the soil was low and the R

_{PF}had a blocking effect on soil water movement. When the D

_{BD}of the soil increased the adsorption capacity between adjacent pieces of R

_{PF}decreased, but still had a guiding role.

_{F}, A

_{I}, and M

_{C}. These three factors were all fixed to zero for analysis, while the I

_{MC}was 11%, the D

_{BD}of the soil was 1.35 g/cm

^{3}, and the R

_{PFC}was 100kg/hm

^{2}. Through an analysis of the interaction effect between two factors, it was found that changes in the D

_{BD}and R

_{PFC}had a certain influence on the result when the magnitude of the factors was fixed to zero. Through the above analysis, it was determined that the R

_{PF}not only had a blocking effect on water movement, but also had a diversion effect. The influence of the R

_{PFC}on soil water movement was determined through the simulation of 1 × 2 cm rectangular pieces of R

_{PF}; hence, ignoring the actual differences in the shape and size of R

_{PF}. In future studies, the influence of the size and shape of R

_{PF}on soil hydrodynamic properties should be considered.

## 5. Conclusions

_{PF}used as a mulch in farmland is increasing annually. The amount of R

_{PF}in the soil is also increasing annually. The R

_{PF}retained in the soil causes “white pollution” and damages the environment. In this experiment, the surface soil of Yangling was used to determine the effect of residual film on one-dimensional soil infiltration. Found that when the R

_{PFC}was 50–100 kg hm

^{2}, the M

_{F}can reach a minimum value, and the soil M

_{C}and A

_{I}can reach a maximum value. There may be a certain error in the test, resulting in R

_{PFC}in the range of 50–100 kg hm

^{−2}. Therefore, it is proposed that the R

_{PFC}should be controlled to be below 50 kg/hm

^{2}when the R

_{PF}is recovered after agricultural operations. This study can provide a reference for reasonable irrigation in residual film area.

_{PFC}on infiltration. The relationship between various physiological indexes of crops and R

_{PFC}should also be studied to establish a model of R

_{PF}and crops yield to provide advice for the cultivation of residual film area.

## Supplementary Materials

## Author Contributions

## Funding

## Conflicts of Interest

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**Figure 3.**The relationships among M

_{F}and various factors. Z

_{1}, Z

_{2}, and Z

_{3}represents mean initial moisture content, dry bulk density and residual plastic film content, respectively.

**Figure 4.**Surface interaction effects between D

_{BD}and R

_{PFC}. Z

_{2}and Z

_{3}represents mean dry bulk density and residual plastic film content respectively.

**Figure 5.**The relationships among A

_{I}and various factors. Z

_{1}, Z

_{2}, and Z

_{3}represents mean initial moisture content, dry bulk density, and residual plastic film content, respectively.

**Figure 6.**Surface interaction effects between D

_{BD}and R

_{PFC}. Z

_{2}and Z

_{3}represents mean dry bulk density and residual plastic film content respectively.

**Figure 7.**The relationships among M

_{C}and various factors. Z

_{1}, Z

_{2}, and Z

_{3}represents mean initial moisture content, dry bulk density, and residual plastic film content, respectively; (

**a**) The relationships among 0–10cm MC and various factors,(

**b**) The relationships among 10–20cm MC and various factors, (

**c**) The relationships among 20–30cm MC and various factors, (

**d**) The relationships among 30–40cm MC and various factors.

Z_{j} | I_{MC}Z _{1}/% | D_{BD}Z _{2}/(g/cm³) | R_{PFC}Z _{3}/(kg/hm²) | Burial Depth of R_{PF}Z_{4}/cm |
---|---|---|---|---|

r (2) | 16 | 1.45 | 200 | 30~40 |

1 | 14 | 1.41 | 150 | 20~30 |

0 | 11 | 1.35 | 100 | 10~20 |

−1 | 8 | 1.29 | 50 | 0~10 |

r (−2) | 6 | 1.25 | 0 | 0 |

_{MC}

_{,}D

_{BD}

_{,}R

_{PFC}and R

_{PF}represents mean initial moisture content, dry bulk density, residual plastic film content and residual plastic film, respectively.

Variance Source | Sum of Squares | Degree of Freedom | Mean Square | Partial Correlation | F-Ratio | P |
---|---|---|---|---|---|---|

Z_{1} | 430,408.2 | 1 | 430,408.2 | −0.9648 | 282.3304 | 0.0001 |

Z_{2} | 175,788.2 | 1 | 175,788.2 | 0.9197 | 115.3099 | 0.0001 |

Z_{3} | 58,608.17 | 1 | 58,608.17 | 0.8042 | 38.4446 | 0.0001 |

Z_{4} | 80.6667 | 1 | 80.6667 | −0.0501 | 0.0529 | 0.8203 |

Z_{1}^{2} | 62.3472 | 1 | 62.3472 | 0.0441 | 0.0409 | 0.8417 |

Z_{2}^{2} | 14,252.35 | 1 | 14,252.35 | −0.555 | 9.349 | 0.006 |

Z_{3}^{2} | 20,234.01 | 1 | 20,234.01 | 0.6223 | 13.2727 | 0.0015 |

Z_{4}^{2} | 5390.681 | 1 | 5390.681 | −0.3796 | 3.5361 | 0.074 |

Z_{1}Z_{2} | 28,392.25 | 1 | 28,392.25 | −0.6856 | 18.6242 | 0.0003 |

Z_{1}Z_{3} | 12.25 | 1 | 12.25 | 0.0196 | 0.008 | 0.9294 |

Z_{1}Z_{4} | 72.25 | 1 | 72.25 | 0.0475 | 0.0474 | 0.8298 |

Z_{2}Z_{3} | 37,442.25 | 1 | 37,442.25 | −0.7342 | 24.5606 | 0.0001 |

Z_{2}Z_{4} | 2652.25 | 1 | 2652.25 | 0.2766 | 1.7398 | 0.2014 |

Z_{3}Z_{4} | 702.25 | 1 | 702.25 | −0.1465 | 0.4606 | 0.5047 |

Regression | 774,098.1 | 14 | 55,292.72 | F2 = 36.26979 | 0.0001 | |

Residual | 32,014.17 | 21 | 1524.484 | |||

Lack of fit | 22,307.92 | 10 | 2230.792 | F1 = 2.52813 | 0.0001 | |

Error | 9706.25 | 11 | 882.3864 | |||

Sum | 806,112.2 | 35 |

Factors | Sum of Squares | Degree of Freedom | Mean Square | Partial Correlation | F-Ratio | P |
---|---|---|---|---|---|---|

Z_{1} | 1,985,291 | 1 | 1,985,291 | −0.7791 | 32.4444 | 0.0001 |

Z_{2} | 13,841,432 | 1 | 13,841,432 | −0.9566 | 226.2023 | 0.0001 |

Z_{3} | 1,303,728 | 1 | 1,303,728 | −0.7097 | 21.3061 | 0.0001 |

Z_{4} | 9680.97 | 1 | 9680.97 | −0.0865 | 0.1582 | 0.6948 |

Z_{1}^{2} | 129,160.7 | 1 | 129,160.7 | −0.3022 | 2.1108 | 0.161 |

Z_{2}^{2} | 484,006.6 | 1 | 484,006.6 | 0.5231 | 7.9098 | 0.0104 |

Z_{3}^{2} | 503,850.7 | 1 | 503,850.7 | −0.5307 | 8.2341 | 0.0092 |

Z_{4}^{2} | 87,288.17 | 1 | 87,288.17 | −0.2522 | 1.4265 | 0.2457 |

Z_{1}Z_{2} | 58,888.73 | 1 | 58,888.73 | −0.2093 | 0.9624 | 0.3378 |

Z_{1}Z_{3} | 104,022.4 | 1 | 104,022.4 | 0.2737 | 1.7 | 0.2064 |

Z_{1}Z_{4} | 26,511.98 | 1 | 26,511.98 | 0.1422 | 0.4333 | 0.5175 |

Z_{2}Z_{3} | 2,447,723 | 1 | 2,447,723 | 0.8098 | 40.0017 | 0.0001 |

Z_{2}Z_{4} | 20,067.56 | 1 | 20,067.56 | 0.124 | 0.328 | 0.5729 |

Z_{3}Z_{4} | 14,174.09 | 1 | 14,174.09 | 0.1045 | 0.2316 | 0.6353 |

Regression | 21,015,826 | 14 | 1,501,130 | F2 = 24.53208 | 0.0001 | |

Residual | 1,285,001 | 21 | 61,190.51 | |||

Lack of fit | 1,244,848 | 10 | 124,484.8 | F1 = 34.10330 | 0.0001 | |

Error | 40,152.51 | 11 | 3650.228 | |||

Sum | 22,300,827 | 35 |

Factors | Sum of Squares | Degree of Freedom | Mean Square | Partial Correlation | F-Ratio | P |
---|---|---|---|---|---|---|

Z_{1} | 40.3782 | 1 | 40.3782 | −0.89 | 79.9942 | 0.0001 |

Z_{2} | 78.9525 | 1 | 78.9525 | −0.939 | 156.4148 | 0.0001 |

Z_{3} | 5.0508 | 1 | 5.0508 | −0.5681 | 10.0063 | 0.0047 |

Z_{4} | 0.0002 | 1 | 0.0002 | −0.0044 | 0.0004 | 0.9841 |

Z_{1}^{2} | 0.0458 | 1 | 0.0458 | 0.0656 | 0.0906 | 0.7663 |

Z_{2}^{2} | 3.8157 | 1 | 3.8157 | 0.5145 | 7.5594 | 0.012 |

Z_{3}^{2} | 6.1864 | 1 | 6.1864 | −0.6071 | 12.256 | 0.0021 |

Z_{4}^{2} | 2.2103 | 1 | 2.2103 | 0.4154 | 4.3788 | 0.0487 |

Z_{1}Z_{2} | 0.8236 | 1 | 0.8236 | 0.2685 | 1.6316 | 0.2154 |

Z_{1}Z_{3} | 0.6765 | 1 | 0.6765 | −0.2449 | 1.3402 | 0.26 |

Z_{1}Z_{4} | 2.4571 | 1 | 2.4571 | −0.4338 | 4.8677 | 0.0386 |

Z_{2}Z_{3} | 1.8701 | 1 | 1.8701 | 0.3873 | 3.7048 | 0.0679 |

Z_{2}Z_{4} | 0.2377 | 1 | 0.2377 | −0.1481 | 0.4708 | 0.5001 |

Z_{3}Z_{4} | 1.2939 | 1 | 1.2939 | −0.3298 | 2.5634 | 0.1243 |

Regression | 143.9986 | 14 | 10.2856 | F2 = 20.37708 | 0.0001 | |

Residual | 10.6 | 21 | 0.5048 | |||

Lack of fit | 10.3697 | 10 | 1.037 | F1 = 49.52981 | 0.0001 | |

Error | 0.2303 | 11 | 0.0209 | |||

Sum | 154.5987 | 35 |

Factors | Sum of Squares | Degree of Freedom | Mean Square | Partial Correlation | F-Ratio | P |
---|---|---|---|---|---|---|

Z_{1} | 41.554 | 1 | 41.554 | −0.851 | 55.1587 | 0.0001 |

Z_{2} | 102.0113 | 1 | 102.0113 | −0.9304 | 135.4094 | 0.0001 |

Z_{3} | 7.5264 | 1 | 7.5264 | −0.5678 | 9.9905 | 0.0047 |

Z4 | 0.1442 | 1 | 0.1442 | −0.095 | 0.1913 | 0.6663 |

Z_{1}^{2} | 1.4706 | 1 | 1.4706 | 0.2916 | 1.9521 | 0.177 |

Z_{2}^{2} | 0.5778 | 1 | 0.5778 | 0.1877 | 0.767 | 0.3911 |

Z_{3}^{2} | 6.2481 | 1 | 6.2481 | −0.5321 | 8.2937 | 0.009 |

Z_{4}^{2} | 0.3828 | 1 | 0.3828 | 0.1537 | 0.5081 | 0.4838 |

Z_{1}Z_{2} | 0.6241 | 1 | 0.6241 | 0.1948 | 0.8284 | 0.3731 |

Z_{1}Z_{3} | 1.092 | 1 | 1.092 | −0.2541 | 1.4496 | 0.242 |

Z_{1}Z_{4} | 1.199 | 1 | 1.199 | −0.2654 | 1.5916 | 0.2209 |

Z_{2}Z_{3} | 1.3924 | 1 | 1.3924 | 0.2844 | 1.8483 | 0.1884 |

Z_{2}Z_{4} | 0.0625 | 1 | 0.0625 | −0.0627 | 0.083 | 0.7761 |

Z_{3}Z_{4} | 0.7656 | 1 | 0.7656 | −0.2149 | 1.0163 | 0.3249 |

Regression | 165.0509 | 14 | 11.7893 | F2 = 15.64914 | 0.0001 | |

Residual | 15.8204 | 21 | 0.7534 | |||

Lack of fit | 14.5316 | 10 | 1.4532 | F1 = 12.40190 | 0.0001 | |

Error | 1.2889 | 11 | 0.1172 | |||

Sum | 180.8713 | 35 |

Factors | Sum of Squares | Degree of Freedom | Mean Square | Partial Correlation | F-Ratio | P |
---|---|---|---|---|---|---|

Z_{1} | 24.8067 | 1 | 24.8067 | −0.7409 | 25.5609 | 0.0001 |

Z_{2} | 99.5523 | 1 | 99.5523 | −0.9111 | 102.5792 | 0.0001 |

Z_{3} | 7.958 | 1 | 7.958 | −0.5299 | 8.2 | 0.0093 |

Z4 | 0.028 | 1 | 0.028 | −0.0371 | 0.0289 | 0.8667 |

Z_{1}^{2} | 0.091 | 1 | 0.091 | 0.0667 | 0.0938 | 0.7624 |

Z_{2}^{2} | 0.9614 | 1 | 0.9614 | 0.2122 | 0.9907 | 0.3309 |

Z_{3}^{2} | 7.854 | 1 | 7.854 | −0.5274 | 8.0928 | 0.0097 |

Z_{4}^{2} | 0.2568 | 1 | 0.2568 | 0.1116 | 0.2646 | 0.6123 |

Z_{1}Z_{2} | 0.6006 | 1 | 0.6006 | 0.1692 | 0.6189 | 0.4402 |

Z_{1}Z_{3} | 0.0042 | 1 | 0.0042 | 0.0144 | 0.0044 | 0.948 |

Z_{1}Z_{4} | 0.5256 | 1 | 0.5256 | −0.1586 | 0.5416 | 0.4699 |

Z_{2}Z_{3} | 1.113 | 1 | 1.113 | 0.2276 | 1.1469 | 0.2964 |

Z_{2}Z_{4} | 3.441 | 1 | 3.441 | −0.3801 | 3.5457 | 0.0736 |

Z_{3}Z_{4} | 0.3906 | 1 | 0.3906 | −0.1371 | 0.4025 | 0.5327 |

Regression | 147.5834 | 14 | 10.5417 | F2 = 10.86219 | 0.0001 | |

Residual | 20.3803 | 21 | 0.9705 | |||

Lack of fit | 19.9954 | 10 | 1.9995 | F1 = 57.14589 | 0.0001 | |

Error | 0.3849 | 11 | 0.035 | |||

Sum | 167.9637 | 35 |

Factors | Sum of Squares | Degree of Freedom | Mean Square | Partial Correlation | F-Ratio | P |
---|---|---|---|---|---|---|

Z_{1} | 24.9492 | 1 | 24.9492 | −0.8376 | 49.3765 | 0.0001 |

Z_{2} | 67.0338 | 1 | 67.0338 | −0.9292 | 132.6653 | 0.0001 |

Z_{3} | 8.9426 | 1 | 8.9426 | −0.6763 | 17.6981 | 0.0004 |

Z4 | 0.0925 | 1 | 0.0925 | −0.093 | 0.1831 | 0.6731 |

Z_{1}^{2} | 1.2813 | 1 | 1.2813 | 0.3282 | 2.5359 | 0.1262 |

Z_{2}^{2} | 3.3822 | 1 | 3.3822 | 0.4916 | 6.6936 | 0.0172 |

Z_{3}^{2} | 4.4377 | 1 | 4.4377 | −0.543 | 8.7826 | 0.0074 |

Z_{4}^{2} | 2.858 | 1 | 2.858 | 0.4606 | 5.6563 | 0.027 |

Z_{1}Z_{2} | 0.5006 | 1 | 0.5006 | 0.2122 | 0.9906 | 0.3309 |

Z_{1}Z_{3} | 0.6521 | 1 | 0.6521 | −0.2406 | 1.2905 | 0.2688 |

Z_{1}Z_{4} | 1.9113 | 1 | 1.9113 | −0.3907 | 3.7826 | 0.0653 |

Z_{2}Z_{3} | 0.015 | 1 | 0.015 | 0.0376 | 0.0297 | 0.8648 |

Z_{2}Z_{4} | 3.3948 | 1 | 3.3948 | −0.4923 | 6.7186 | 0.017 |

Z_{3}Z_{4} | 0.1351 | 1 | 0.1351 | −0.1121 | 0.2673 | 0.6106 |

Regression | 119.5862 | 14 | 8.5419 | F2 = 16.90505 | 0.0001 | |

Residual | 10.611 | 21 | 0.5053 | |||

Lack of fit | 10.5042 | 10 | 1.0504 | F1 = 108.22336 | 0.0001 | |

Error | 0.1068 | 11 | 0.0097 | |||

Sum | 130.1972 | 35 |

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Cao, J.; Chen, P.; Li, Y.; Fang, H.; Gu, X.; Li, Y.
Effect of Plastic Film Residue on Vertical Infiltration Under Different Initial Soil Moisture Contents and Dry Bulk Densities. *Water* **2020**, *12*, 1346.
https://doi.org/10.3390/w12051346

**AMA Style**

Cao J, Chen P, Li Y, Fang H, Gu X, Li Y.
Effect of Plastic Film Residue on Vertical Infiltration Under Different Initial Soil Moisture Contents and Dry Bulk Densities. *Water*. 2020; 12(5):1346.
https://doi.org/10.3390/w12051346

**Chicago/Turabian Style**

Cao, Junhao, Pengpeng Chen, Yupeng Li, Heng Fang, Xiaobo Gu, and Yuannong Li.
2020. "Effect of Plastic Film Residue on Vertical Infiltration Under Different Initial Soil Moisture Contents and Dry Bulk Densities" *Water* 12, no. 5: 1346.
https://doi.org/10.3390/w12051346