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Journal of Arid Land
Journal of Arid Land  2022, Vol. 14 Issue (4): 374-389    DOI: 10.1007/s40333-022-0060-6
Research article     
Effects of mixed-based biochar on water infiltration and evaporation in aeolian sand soil
ZOU Yiping1, ZHANG Shuyue1, SHI Ziyue1, ZHOU Huixin1, ZHENG Haowei1, HU Jiahui1, MEI Jing1, BAI Lu2,3, JIA Jianli1,*()
1School of Chemical & Environmental Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
2State Key Laboratory of Water Resource Protection and Utilization in Coal Mining, Beijing 102211, China
3National Institute of Clean-and-Low-Carbon Energy, Beijing 102211, China
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Abstract  

Aeolian sandy soil in mining areas exhibits intense evaporation and poor water retention capacity. This study was designed to find a suitable biochar application method to improve soil water infiltration and minimize soil water evaporation for aeolian sand soil. Using the indoor soil column method, we studied the effects of three application patterns (A (0-20 cm was a mixed sample of mixed-based biochar and soil), B (0-10 cm was a mixed sample of mixed-based biochar and soil and 10-20 cm was soil), and C (0-10 cm was soil and 10-20 cm was a mixed sample of mixed-based biochar and soil)), four application amounts (0% (control, CK), 1%, 2%, and 4% of mixed-based biochar in dry soil), and two particle sizes (0.05-0.25 mm (S1) and <0.05 mm (S2)) of mixed-based biochar on water infiltration and evaporation of aeolian sandy soil. We separately used five infiltration models (the Philip, Kostiakov, Horton, USDA-NRCS (United States Department of Agriculture-Natural Resources Conservation Service), and Kostiakov-Lewis models) to fit cumulative infiltration and time. Compared with CK, the application of mixed-based biochar significantly reduced cumulative soil water infiltration. Under application patterns A, B, and C, the higher the application amount and the finer the particle size were, the lower the migration speed of the wetting front. With the same application amount, cumulative soil water infiltration under application pattern A was the lowest. Taking infiltration for 10 min as an example, the reductions of cumulative soil water infiltration under the treatments of A2%(S2), A4%(S1), A4%(S2), A1%(S1), C2%(S1), and B1%(S1) were higher than 30%, which met the requirements of loess soil hydraulic parameters suitable for plant growth. The five infiltration models well fitted the effects of the treatments of application pattern C and S1 particle size (R2>0.980), but the R2 values of the Horton model exceeded 0.990 for all treatments (except for the treatment B2%(S2)). Compared with CK, all other treatments reduced cumulative soil water infiltration, except for B4%(S2). With the same application amount, cumulative soil water evaporation difference between application patterns A and B was small. Treatments of application pattern C and S1 particle size caused a larger reduction in cumulative soil water evaporation. The reductions in cumulative soil water evaporation under the treatments of C4%(S1), C4%(S2), C2%(S1), and C2%(S2) were over 15.00%. Therefore, applying 2% of mixed-based biochar with S1 particle size to the underlying layer (10-20 cm) could improve soil water infiltration while minimizing soil water evaporation. Moreover, application pattern was the main factor affecting soil water infiltration and evaporation. Further, there were interactions among the three influencing factors in the infiltration process (application amount×particle size with the most important interaction), while there were no interactions among them in the evaporation process. The results of this study could contribute to the rational application of mixed-based biochar in aeolian sandy soil and the resource utilization of urban and agricultural wastes in mining areas.

Key words： biochar      water infiltration      water evaporation      aeolian sand soil      mining areas     
Received: 03 August 2021      Published: 30 April 2022
Corresponding Authors: *JIA Jianli (E-mail: jjl@cumtb.edu.cn)
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ZOU Yiping
ZHANG Shuyue
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ZHOU Huixin
ZHENG Haowei
HU Jiahui
MEI Jing
BAI Lu
JIA Jianli
Cite this article:

ZOU Yiping, ZHANG Shuyue, SHI Ziyue, ZHOU Huixin, ZHENG Haowei, HU Jiahui, MEI Jing, BAI Lu, JIA Jianli. Effects of mixed-based biochar on water infiltration and evaporation in aeolian sand soil. Journal of Arid Land, 2022, 14(4): 374-389.

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http://jal.xjegi.com/10.1007/s40333-022-0060-6     OR     http://jal.xjegi.com/Y2022/V14/I4/374

pH EC
(μS/cm)		 CEC
(cmol/kg)		 TC
(g/kg)		 SOC
(g/kg)		 TN
(g/kg)		 AN
(mg/kg)		 TP
(g/kg)		 AP
(mg/kg)		 Number of
microorganisms (×104/g)
7.77 309.91 5.00 18.70 10.67 0.65 52.68 0.51 32.84 151.99
Table 1 Physical and chemical properties of tested aeolian sandy soil
pH CEC
(cmol/kg)		 BET
(m2/g)		 C
(%)		 H
(%)		 N
(%)		 O
(%)		 P
(g/kg)		 K
(g/kg)		 Zn
(mg/kg)		 Cu
(mg/kg)		 Cr
(mg/kg)		 Average pore size (nm) Pore volume
(cm3/g)
8.02 19.12 72.03 61.02 3.51 0.66 8.93 4.81 9.50 183.99 8.31 1.79 9.77 0.18
Table 2 Physical and chemical properties of mixed-based biochar
Fig. 1 Schematic diagram showing the application patterns of mixed-based biochar. CK, control. Application patterns for mixed-based biochar were as follows: (1) 0-20 cm was a mixed sample of mixed-based biochar and soil (A); (2) 0-10 cm was a mixed sample of mixed-based biochar and soil and 10-20 cm was soil (B); and (3) 0-10 cm was soil and 10-20 cm was a mixed sample of mixed-based biochar and soil (C).
Treatment Application pattern Application amount Particle size
CK
A1%(S1) A 1% S1
A1%(S2) S2
A2%(S1) 2% S1
A2%(S2) S2
A4%(S1) 4% S1
A4%(S2) S2
B1%(S1) B 1% S1
B1%(S2) S2
B2%(S1) 2% S1
B2%(S2) S2
B4%(S1) 4% S1
B4%(S2) S2
C1%(S1) C 1% S1
C1%(S2) S2
C2%(S1) 2% S1
C2%(S2) S2
C4%(S1) 4% S1
C4%(S2) S2
Table 3 Full-factorial design experiment used in this study
Fig. 2 Demonstration of the device used in determinations of soil water infiltration and evaporation
Fig. 3 Dynamic changes in wetting fronts under different application patterns, amounts, and particle sizes of biochar. Application patterns of mixed-based biochar were as follows: (1) 0-20 cm was a mixed sample of mixed-based biochar and soil (A); (2) 0-10 cm was a mixed sample of mixed-based biochar and soil and 10-20 cm was soil (B); and (3) 0-10 cm was soil and 10-20 cm was a mixed sample of mixed-based biochar and soil (C). S1, 0.05-0.25 mm; S2, <0.05 mm. The four application amounts of mixed-based biochar in dry soil were 0% (control, CK), 1%, 2%, and 4%.
Treatment Application pattern A Application pattern B Application pattern C
p v R2 p v R2 p v R2
CK 3.867 0.685 0.998 3.867 0.685 0.998 3.867 0.685 0.998
1%(S1) 2.240 0.746 0.994 2.582 0.759 0.991 2.013 1.079 0.951
1%(S2) 2.949 0.602 0.997 2.200 0.683 0.985 2.542 0.928 0.967
2%(S1) 2.108 0.723 0.991 2.878 0.608 0.974 2.023 0.930 0.951
2%(S2) 2.048 0.616 0.999 2.349 0.563 0.988 2.649 0.782 0.938
4%(S1) 2.406 0.594 0.990 2.604 0.565 0.985 3.412 0.685 0.947
4%(S2) 1.851 0.539 0.952 1.442 0.614 0.943 3.553 0.599 0.911
Table 4 Fitting results for the wetting front and infiltration time under different application patterns, application amounts, and particle sizes of mixed-based biochar
Fig. 4 Effects of application patterns, application amounts, and particle sizes of mixed-based biochar on cumulative soil water infiltration. (a), application pattern A; (b), application pattern B; (c), application pattern C.
Model name Equation Model parameter
Theory-based model Green and Ampt (1911) $I={{K}_{s}}[1+({{\theta }_{s}}-{{\theta }_{i}}){{S}_{f}}/I]$ I is the cumulative soil water infiltration (cm); Ks is the saturated hydraulic conductivity (cm/s); θi and θs are the presumed initial and saturated water contents (g/g), respectively; and Sf is the average potential suction of the wetting front (cm).
Philip (1957) $I=S{{t}^{0.5}}+At$ S is the sorptivity (cm/s0.5); A is the stable permeability (cm/s); and t is the infiltration time (s).
Empirical model Kostiakov (1932) $I=K{{t}^{n}}$ K (K>0) and n (0<n<1) are the dimensionless empirical constants.
Horton (1941) $I=at+1/c(b-a)(1-{{\text{e}}^{-ct}})$ a and b are the presumed initial and final soil water infiltration rates (cm/s), respectively; c is an empirical constant; and e is the natural logarithm (approximately 2.71828).
USDA-NRCS (1974) $I=a''{{t}^{b''}}+0.6985$ a'' and b'' are the dimensionless empirical constants.
Kostiakov-Lewis
(Mezencev, 1948)		 \[I=K'{{t}^{b'}}+A't\] K' (K'>0) and b' (0<b'<1) are the dimensionless empirical constants, and A' (A'>0) is the final soil water infiltration rate at the steady state condition.
Table 5 Models used to determine the effects of mixed-based biochar on soil water infiltration (Wang et al., 2017)
Treatment Philip Kostiakov Horton USDA-NRCS Kostiakov-Lewis (Mezencey)
S A R2 K n R2 a b c R2 a'' b'' R2 K' A' b' R2
CK 2.972 0.163 0.919 1.837 0.862 0.868 0.045 2.935 0.280 0.993 2.672 0.562 0.936 3.629 0.010 0.453 0.940
A1%(S1) 1.481 0.145 0.976 1.145 0.730 0.984 0.110 1.075 0.129 0.999 1.052 0.711 0.975 1.455 0.005 0.625 0.986
A1%(S2) 1.684 0.149 0.969 1.164 0.760 0.973 0.081 1.112 0.103 0.997 1.236 0.693 0.971 1.507 0.003 0.650 0.980
A2%(S1) 1.621 0.042 0.957 1.072 0.700 0.971 0.082 0.968 0.125 0.995 1.096 0.639 0.956 1.449 0.010 0.574 0.969
A2%(S2) 2.148 0.010 0.928 1.683 0.600 0.934 0.078 1.465 0.151 0.994 2.187 0.476 0.933 2.527 0.001 0.453 0.942
A4%(S1) 1.836 0.043 0.964 1.084 0.720 0.968 0.053 0.966 0.090 0.999 1.301 0.621 0.964 1.682 0.003 0.564 0.974
A4%(S2) 1.532 0.010 0.866 1.607 0.510 0.910 0.046 1.123 0.135 1.000 2.081 0.399 0.935 3.101 0.002 0.310 0.932
B1%(S1) 1.092 0.343 0.989 1.089 0.810 0.994 0.110 1.039 0.093 0.992 0.895 0.839 0.985 1.091 0.150 0.706 0.992
B1%(S2) 1.400 0.292 0.986 1.131 0.810 0.992 0.150 1.056 0.078 0.999 1.115 0.776 0.987 1.446 0.020 0.701 0.992
B2%(S1) 1.429 0.430 0.967 1.168 0.870 0.992 0.287 1.121 0.061 0.996 1.280 0.805 0.972 1.254 0.051 0.814 0.992
B2%(S2) 2.267 0.010 0.915 1.357 0.700 0.939 0.010 1.459 0.111 0.981 2.126 0.519 0.908 2.200 0.001 0.528 0.913
B4%(S1) 1.925 0.267 0.974 1.290 0.810 0.988 0.032 1.167 0.054 0.998 1.532 0.721 0.979 1.731 0.003 0.710 0.978
B4%(S2) 2.392 0.010 0.483 3.185 0.450 0.736 0.029 2.775 0.185 0.996 5.660 0.266 0.829 8.513 0.010 0.158 0.960
C1%(S1) 0.735 0.551 0.996 1.066 0.879 0.997 0.051 1.062 0.067 1.000 0.790 0.955 0.987 1.173 0.001 0.828 0.998
C1%(S2) 0.448 0.728 1.000 1.145 0.875 1.000 0.820 1.410 1.044 1.000 0.703 1.061 0.991 0.445 0.768 0.386 1.000
C2%(S1) 1.070 0.327 0.994 1.075 0.803 0.992 0.310 1.088 0.167 1.000 0.857 0.841 0.988 1.271 0.102 0.652 0.997
C2%(S2) 0.909 0.609 0.984 0.989 0.958 0.992 0.066 1.144 0.042 0.996 1.044 0.900 0.984 1.298 0.021 0.838 0.989
C4%(S1) 1.100 0.396 0.992 1.127 0.827 0.996 0.089 1.069 0.074 1.000 0.959 0.847 0.989 1.323 0.012 0.752 0.996
C4%(S2) 1.530 0.228 0.984 1.237 0.760 0.990 0.092 1.115 0.093 1.000 1.169 0.739 0.984 1.533 0.001 0.668 0.991
Table 6 Parameters in the five infiltration models
Fig. 5 Effects of different application patterns, application amounts, and particle sizes of mixed-based biochar on cumulative soil water evaporation
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