基于土壤理化性质估计土壤水分特征曲线Van Genuchten模型参数

doi:10.13249/j.cnki.sgs.2018.07.021

Abstract

Abstract:

The soil water retention curve (SWRC) is the basic parameter of soil hydraulics to study soil water movement and soil water balance, which is closely related to soil physical and chemical properties. But the parameters of model is difficult to estimate. In this study, black soil samples with different erosion intensity were collected in the black soil region of Northeast China, and soil moisture under 7 soil water suction, mechanical composition, organic matter and bulk density were measured. We used Rosetta model to estimate the parameters of Van Genuchten (VG) model and compared the estimated soil moisture with the measured soil moisture. And then the simulation accuracy of different soil physical and chemical indexes and the suitability of the method to the black soil in Northeast China were evaluated. The results showed that there had little effect for the residual water content (θ_r) and saturated water content (θ_s) between 4 or 6 soil properties index, but had large difference for the scale parameter (α) and shape parameter (n). When the 6 indexes were used, shape parameter n decreased with the increased of scale parameter α. The relationship between the shape parameters m and n of the VG model was further modified, which improved the accuracy of model fitting obviously. The results of the 6 indexes were better than the 4 indexes. But the estimated values were different from the measured values and the estimated values were larger than the measured, which means soil moisture estimation need to be corrected according to the estimated value of relatively large degree. The fitting precision of Rosetta model for lightly and moderately erosion black soil was higher, and the precision of severely erosion black soil was lower. The model was suitable for sand content less than 46%, the clay content more than 28% of black soil in Northeast China.

Key words: soil water retention curve, soil physical and chemical properties, black soil, Rosetta model, Van Genuchten model

CLC Number:

S152.7

Shuang Li, Xiangjie Zhao, Yun Xie, Junrui Zhai, Gang Liu, Xiaofei Gao, Jing Li, Yan Gao. Parameter Estimation of Soil Water Retention Curve Based on Soil Physical and Chemical Properties of Van Genuchten Model[J].SCIENTIA GEOGRAPHICA SINICA, 2018, 38(7): 1189-1197.

Figures/Tables 9

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References 20

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侵蚀强度	模型处理	样点编号	黑土层(cm)	砂粒（%）
轻度	拟合	L-1	30	31.93	34.06	34.01
	拟合	L-2	40	31.74	39.50	28.76
	拟合	L-3	40	43.47	24.97	31.56
	验证	L-4	70	32.95	34.60	32.45
	验证	L-5	30	35.27	37.01	27.72
	验证	L-6	55	30.61	36.59	32.80
	验证	L-7	70	26.86	39.22	33.91
中度	拟合	M-1	30	31.30	35.56	33.14
	拟合	M-2	25	32.43	33.48	34.08
	拟合	M-3	20	40.89	25.12	33.99
	验证	M-4	25	33.89	36.72	29.39
	验证	M-5	30	55.81	22.02	22.16
重度	拟合	S-1	0	68.28	13.88	17.84
	拟合	S-2	0	75.31	12.32	12.37
	拟合	S-3	28	53.33	25.50	21.17

侵蚀强度	4指标				6指标
侵蚀强度	θ_r（cm³/cm³）	θ_s（cm³/cm³）	α（1/kPa）	n	θ_r（cm³/cm³）	θ_s（cm³/cm³）	α（1/kPa）	n
轻	0.08^a	0.46^a	0.12^a	1.45^a	0.09^a	0.47^a	0.26^a	1.31^a
中	0.08^a	0.45^a	0.13^a	1.41^a	0.08^a	0.45^a	0.34^a	1.30^a
重	0.06^b	0.39^b	0.25^a	1.52^a	0.06^b	0.39^b	0.31^b	1.37^a

侵蚀强度	指标个数	相对误差（%）			RMSE（cm³/cm³）			1:1线差异性
侵蚀强度	指标个数	前	后		前	后		前	后
轻	4	33.15	13.13		0.11	0.05		显著	显著
轻	6	19.72	5.77		0.06	0.03		显著	显著
中	4	29.69	30.34		0.08	0.08		显著	显著
中	6	18.70	7.76		0.06			0.04	显著	显著
重	4	37.00	37.66	0.10	0.09	显著	显著
重	6	25.42	15.26	0.06		0.05	显著		显著

侵蚀强度	修正后方程⁴	⁴R²	修正后方程⁶	⁶R²	与原关系差异性
轻	m^*=0.39(1.07-1/n)	0.54	m^*=0.53(1.05-1/n)	0.49	显著
中	m^*=0.73(0.89-1/n)	0.76	m^*=0.87(0.96-1/n)	0.75	显著
重	m^*=0.44(1.04-1/n)	0.70	m^*=0.97(0.93-1/n)	0.21	显著

侵蚀强度	样点	相对误差（%）		RMSE（cm³/cm³）		1:1线差异性
侵蚀强度	样点	4	6	4	6	4	6
轻	L-4	6.01	7.02	0.02	0.02	不显著	显著
	L-5	9.35	4.14	0.04	0.02	不显著	不显著
	L-6	8.36	8.10	0.03	0.03	显著	不显著
	L-7	6.78	4.37	0.02	0.02	不显著	显著
中	M-4	11.22	5.91	0.05	0.02	不显著	显著
	M-5	33.11	26.25	0.06	0.05	显著	不显著

Parameter Estimation of Soil Water Retention Curve Based on Soil Physical and Chemical Properties of Van Genuchten Model

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