时空克里金评估河套灌区土壤盐分时空格局

doi:10.13866/j.azr.2023.02.03

Abstract

Abstract:

For maintaining crop yield in salt-affected dry agricultural settings, monitoring and analyzing spatio-temporal dynamics of soil salinity over broad areas is crucial yet challenging due to its high variability. The most popular techniques for evaluating spatial distribution patterns and temporal trends are classical statistical analysis and traditional geostatistical analysis, but they are not suitable for accurately capturing spatio-temporal trends of soil salinity due to irregular sampling time and inconsistent spatial position during sampling time. Spatio-temporal Kriging is an extension of spatial geostatistics to space-time geostatistics and may overcome this problem effectively because its model covariance/variance is a function of both space and time. However, its application in spatio-temporal modeling and prediction of regional soil salinity is still unclear. Based on 4582 soil salinity data of 0-1.8 m soil profiles from 68 monitoring locations in the Longsheng study area of Hetao Irrigation District, Inner Mongolia, spatio-temporal variation characteristics of regional soil salinity using a spatio-temporal geostatistical method, and spatio-temporal Kriging interpolation accuracy was compared with traditional spatial Kriging interpolation. Furthermore, the ability of spatio-temporal Kriging to obtain regional soil salinity dynamics was verified using less than half of the original monitoring locations. The results showed that the spatial variation coefficient of soil salt in the study area ranged from 0.43 to 1.14, which was categorized as medium to strong variability. Regional averaged soil salinity dynamics had obvious seasonal variation characteristics, and the root zone (0-0.6 m) soil salinity accumulated in the crop growing season and desalted in the fallow season, while the deep soil salinity (0.6-1.8 m) was the opposite. The sum-metric model can fit the temporal and spatial experience semi-variance of soil salinity well, and the root mean square error (RMSE) between the predicted value and observed value of soil salinity in each layer was less than 0.21 dS·m^-1, which was 0.02-0.09 dS·m^-1 less than that of traditional spatial Kriging. The areas of different soil salinity determined by 32 sparse monitoring locations were in good agreement with those determined by all sampling sites, and the mean relative error between areas of different soil salinity for 0-0.6 m and 0.6-1.2 m were -13.20% and -8.35%, respectively. Similarly, the respective RMSE were 466.67 hm² and 494.43 hm² and the determination coefficient (R²) were 0.79 and 0.72, indicating that spatial distribution of soil salinity obtained by sparse monitoring locations is consistent with the results of all sampling locations. Spatio-temporal Kriging significantly improves the prediction accuracy of soil salinity compared with ordinary Kriging, since it uses more information on soil salinity in time and space. The accurate estimation of spatio-temporal dynamics of soil salinity in the data set of sparse monitoring points was realized, which can greatly improve the monitoring efficiency of the spatio-temporal pattern of soil salinity in the region.

Key words: soil salinity, spatio-temporal Kriging, Hetao Irrigation District, spatio-temporal pattern, sum-metric model

SUN Guanfang, GAO Zhaoliang, ZHU Yan, YANG Jinzhong, QU Zhongyi. Spatio-temporal patterns of soil salinity in Hetao Irrigation District based on spatio-temporal Kriging[J].Arid Zone Research, 2023, 40(2): 182-193.

Figures/Tables 11

Fig. 1

Tab. 1

Statistical characteristics of soil salinity at four sampling times"

土层/m	时间	观测数	均值 / (dS·m^-1)	中位数 / (dS·m^-1)	标准差 / (dS·m^-1)	变异系数	峰度	偏度	最小值 / (dS·m^-1)	最大值 / (dS·m^-1)
0~0.2	Y1705	65	0.34	0.23	0.39	1.14	18.52	4.18	0.13	2.34
	Y1709	66	0.35	0.23	0.28	0.78	5.1	2.12	0.1	1.55
	Y1805	67	0.28	0.23	0.13	0.45	3.34	1.69	0.14	0.77
	Y1809	66	0.28	0.2	0.21	0.77	11.34	3.18	0.08	1.29
0.2~0.4	Y1705	65	0.3	0.25	0.18	0.6	3.84	1.87	0.12	0.99
	Y1709	66	0.33	0.24	0.24	0.74	3.39	1.97	0.12	1.19
	Y1805	67	0.29	0.23	0.15	0.52	1.39	1.42	0.13	0.76
	Y1809	66	0.3	0.23	0.21	0.71	9.18	2.87	0.08	1.23
0.4~0.6	Y1705	65	0.31	0.27	0.21	0.66	10.29	2.74	0.11	1.35
	Y1709	66	0.32	0.26	0.2	0.63	1.99	1.57	0.07	0.96
	Y1805	67	0.32	0.24	0.2	0.63	2.58	1.64	0.12	1.02
	Y1809	66	0.32	0.26	0.2	0.63	3.14	1.77	0.1	1.03
0.6~0.8	Y1705	65	0.33	0.26	0.2	0.6	4.3	1.88	0.1	1.18
	Y1709	66	0.29	0.26	0.15	0.53	1.27	1.21	0.07	0.74
	Y1805	67	0.33	0.26	0.2	0.61	2.22	1.62	0.12	1.03
	Y1809	66	0.31	0.24	0.2	0.64	3.73	1.87	0.09	1.06
0.8~1.0	Y1705	65	0.33	0.27	0.19	0.57	5.64	2.06	0.1	1.18
	Y1709	66	0.28	0.27	0.13	0.47	1.94	1.17	0.07	0.73
	Y1805	67	0.33	0.27	0.18	0.54	2.17	1.53	0.12	0.92
	Y1809	66	0.29	0.22	0.17	0.61	3.3	1.8	0.09	0.89
1.0~1.2	Y1705	64	0.31	0.26	0.16	0.52	3.7	1.76	0.06	0.9
	Y1709	66	0.28	0.25	0.13	0.46	0.71	1.1	0.09	0.63
	Y1805	67	0.33	0.27	0.17	0.53	2.26	1.53	0.11	0.9
	Y1809	66	0.28	0.23	0.18	0.62	8.86	2.63	0.09	1.13
1.2~1.4	Y1705	51	0.29	0.24	0.15	0.51	5.79	1.98	0.12	0.92
	Y1709	66	0.26	0.24	0.12	0.44	1.83	1.24	0.09	0.68
	Y1805	65	0.31	0.25	0.15	0.48	0.78	1.26	0.11	0.72
	Y1809	66	0.27	0.23	0.15	0.56	4.2	1.85	0.1	0.91
1.4~1.6	Y1705	45	0.28	0.23	0.15	0.54	4.49	1.82	0.12	0.88
	Y1709	66	0.25	0.24	0.11	0.43	0.89	1.05	0.1	0.55
	Y1805	64	0.29	0.24	0.13	0.46	2.4	1.53	0.14	0.78
	Y1809	66	0.26	0.22	0.13	0.51	6.12	2.17	0.08	0.86
1.6~1.8	Y1705	29	0.32	0.27	0.19	0.61	5.14	2.04	0.12	1.01
	Y1709	66	0.26	0.24	0.12	0.48	5.72	1.76	0.07	0.81
	Y1805	58	0.27	0.22	0.12	0.45	3.16	1.52	0.11	0.77
	Y1809	66	0.25	0.23	0.12	0.47	2.99	1.64	0.08	0.65

Tab. 1

Fig. 2

Tab. 2

Fig. 3

Fig. 4

Fig. 5

Tab. 3

Fig. 6

Fig. 7

Tab. 4

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土层/m	C₀	空间参数		时间参数		联合参数
土层/m	C₀	C_S	a_S	C_T	a_T	C_ST	a_ST	α
0~0.2	0.0063	0.0240	957.00	0.0282	292.70	0.0032	235.01	0.1000
0.2~0.4	0.0081	0.0143	1438.69	0.0201	287.37	0.0092	1217.14	0.6647
0.4~0.6	0.0186	0.0152	1001.61	0.0073	289.24	0.0162	1868.67	0.1000
0.6~0.8	0.0080	0.0249	1615.07	0.0147	227.55	0.0074	1003.57	0.1856
0.8~1.0	0.0055	0.0259	1916.53	0.0188	209.64	0.0009	1003.37	0.4790
1.0~1.2	0.0028	0.0257	1323.09	0.0158	220.30	0.0009	955.91	3.0303
1.2~1.4	0.0069	0.0169	863.06	0.0061	147.70	0.0093	1930.13	0.2737
1.4~1.6	0.0061	0.0187	1127.09	0.0063	175.33	0.0061	1879.02	1.1730
1.6~1.8	0.0042	0.0010	1863.53	0.0132	293.88	0.0241	1827.54	0.0978
0~0.6	0.0089	0.0280	1250.41	0.0046	246.15	0.0017	1861.18	0.0244
0.6~1.2	0.0054	0.0290	1945.91	0.0090	244.73	0.0013	1259.28	0.0391

土层/m	ASML			LSML
土层/m	MRE/%	RMSE/(dS·m^-1)	R²	MRE/%	RMSE/(dS·m^-1)	R²
0~0.6	3.60	0.13	0.64	2.52	0.12	0.73
0.6~1.2	3.11	0.10	0.65	2.54	0.09	0.70

Spatio-temporal patterns of soil salinity in Hetao Irrigation District based on spatio-temporal Kriging

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Figures/Tables 11

References 31

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土层/m	时空克里金			普通克里金
土层/m	MRE/%	RMSE/hm²	R²	MRE/%	RMSE/hm²	R²
0~0.6	-13.20	466.47	0.79	26.14	412.99	0.78
0.6~1.2	-8.35	494.43	0.72	120.09	731.13	0.48

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