Soil Sr, Mg, Ca in upstream watersheds of the Guanting and Miyun Reservoirs as climate indicators

doi:10.13745/j.esf.sf.2022.12.70

Abstract

Abstract:

Taking the upstream watersheds of the Guanting and Miyun Reservoirs as examples, this paper explores the soil Sr, Mg, and Ca as indicators of climatic factors, such as temperature, precipitation (P), relative humidity (RH), and sunshine duration under supergene environments. Using regional soil data from agricultural land and regional climate data from the last 20 years, the relationships between soil Sr, Mg, Ca and climatic factors are investigated via multivariate statistical analysis. At 95% confidence level, best-fitting multiple linear regression models between soil element ratio (R_Mg/Ca or R_Sr/Ca) and climatic factors (P and RH) are established. For equation R_Mg/Ca=-1.68+(3.59×P+12.62×RH)×10^-³, the complex correlation coefficient, R², is 0.86 after outlier adjustment; for equation R_Sr/Ca=-3.49×10^-²+(4.95×P+47.11×RH)×10^-⁵, R² is 0.73 after outlier adjustment. A strong positive correlation between Sr, Ca, and Mg in soil is observed under supergene environments, suggesting the three elements may have similar geochemical properties and distribution control mechanisms. The main climatic factors that affect their soil distribution are precipitation and relative humidity, with precipitation having a greater impact. Results show that the Sr, Mg, and Ca contents in soil are inversely correlated with ambient humidity, where higher content usually correlates with drier climates, and vice versa. Compared to soil content, Mg/Ca and Sr/Ca ratios in soil are more effective climate indicators, where areas with low ratios often have relatively dry climates, and vice versa.

Key words: Guanting Reservoir, Miyun Reservoir, supergene environment, soil, climate, Mg/Ca ratio, Sr/Ca ratio, linear regression model

CLC Number:

ZHANG Chenggang, WEI Jing, ZHANG Yutao, WANG Ran, HOU Zhaoshuo, ZHAO Jingxuan, ZHANG Xinran. Soil Sr, Mg, Ca in upstream watersheds of the Guanting and Miyun Reservoirs as climate indicators[J]. Earth Science Frontiers, 2023, 30(6): 485-492.

Figures/Tables 8

Fig.1 Geographical location of the study area

Table 1 Accuracy and precision standards for daily analysis

含量范围	准确度		精密度
含量范围	ΔlgC(GBW)= $l g C i - l g C s$		$λ = ∑ n = 1 i (l g C i - l g C s) 2 4 - 1$
检出限3倍以内	≤0.12	≤0.17
检出限3倍以上	≤0.10	≤0.15
1%~5%	≤0.07	≤0.10
>5%	≤0.05	≤0.08

Table 1 Accuracy and precision standards for daily analysis

含量范围	准确度		精密度
含量范围	ΔlgC(GBW)= $l g C i - l g C s$		$λ = ∑ n = 1 i (l g C i - l g C s) 2 4 - 1$
检出限3倍以内	≤0.12	≤0.17
检出限3倍以上	≤0.10	≤0.15
1%~5%	≤0.07	≤0.10
>5%	≤0.05	≤0.08

Table 2 1995—2017 climate data for each district/county in the study area

行政区		年均气温/℃	年均降水量/mm	年均日照时长/h	年均相对湿度/%
承德市	承德县	9.7	509.9	2 420.2	57.0
	丰宁县	7.3	453.7	2 720.2	54.6
	沽源县	2.7	406.1	2 895.1	60.7
	滦平县	8.0	511.3	2 584.8	58.4
	兴隆县	8.0	683.8	2 435.9	61.2
张家口市	市区	9.3	401.3	2 589.6	45.8
	尚义县	3.9	406.5	2 694.5	57.2
	万全县	8.5	369.8	2 679.4	49.1
	蔚县	8.0	386.4	2 785.2	53.7
	宣化县	8.4	364.8	2 638.3	53.3
	阳原县	8.2	370.4	2 762.8	50.0
	张北县	4.2	374.3	2 686.3	55.4
	涿鹿县	10.3	386.7	2 636.7	49.2
	赤城县	6.9	402.3	2 611.0	52.6
	崇礼县	4.4	464.0	2 574.7	56.4
	怀安县	8.3	383.9	2 567.6	50.2
	怀来县	10.1	374.7	2 790.4	49.5

Fig.2 Statistical distribution of Sr, Mg, and Ca contents in soil before (a, c, e) and after (b, d, f) outlier adjustment

Table 3 Summary of Sr, Mg, and Ca contents (w%) and elemental ratios in soil by district/county

行政区		样本数/个	元素含量			元素比值
行政区		样本数/个	w(Sr)/ (mg·kg^-1)	w(Mg)/ %	w(Ca)/ %	Mg/Ca	Sr/Ca
承德市	承德县	8	119.13	0.78	0.88	0.93	0.014 3
	丰宁县	1 768	204.74	0.89	1.58	0.63	0.014 6
	沽源县	351	173.83	0.71	1.06	0.67	0.017 5
	滦平县	415	238.21	1.06	1.23	0.93	0.020 9
	兴隆县	142	181.27	1.19	1.30	1.00	0.015 7
张家口市	市区	848	278.11	1.16	3.72	0.33	0.008 0
	尚义县	283	293.73	1.04	3.34	0.35	0.010 1
	万全县	1 547	281.01	1.04	3.07	0.36	0.009 9
	蔚县	2 811	247.14	1.28	4.87	0.28	0.005 6
	宣化县	1 828	283.15	1.29	4.17	0.32	0.007 1
	阳原县	1 693	304.47	1.40	4.91	0.30	0.006 4
	张北县	33	239.83	1.03	1.64	0.68	0.016 1
	涿鹿县	1 990	255.16	1.32	4.49	0.30	0.006 0
	赤城县	3 188	211.08	1.02	2.31	0.51	0.010 8
	崇礼县	1 109	228.17	1.02	2.08	0.58	0.012 4
	怀安县	1 767	275.85	1.37	4.49	0.31	0.006 4
	怀来县	2 011	278.79	1.19	4.03	0.31	0.007 8

Table 4 Pearson correlation coefficients between soil elements and climatic factors

气候要素	各气候要素间相关系数
气候要素	Sr含量	Mg含量	Ca含量	年均气温	年降水量	年相对湿度	年日照时长
Sr含量	1
Mg含量	0.79^*	1
Ca含量	0.79^*	0.92^*	1
年均气温	0.17	0.49	0.40	1
年降水量	-0.68^*	-0.60^*	-0.80^*	-0.12	1
年相对湿度	-0.60^*	-0.66^*	-0.70^*	-0.69^*	0.61^*	1
年日照时长	0.28	0.04	0.24	-0.36	-0.54	0.06	1

Fig.3 Linear regression models between Mg/Ca ratio in soil and annual precipitation (left) and relative humidity (right)

Fig.4 Linear regression models between Sr/Ca ratio in soil and annual precipitation (left) and relative humidity (right)

[1]	张甘霖, 史舟, 朱阿兴, 等. 土壤时空变化研究的进展与未来[J]. 土壤学报, 2020, 57(5): 1060-1070.
[2]	李徐生, 韩志勇, 杨守业, 等. 镇江下蜀土剖面的化学风化强度与元素迁移特征[J]. 地理学报, 2007, 62(11): 1174-1184.
[3]	陈骏, 安芷生, 汪永进, 等. 最近800 ka洛川黄土剖面中Rb/Sr分布和古季风变迁[J]. 中国科学D辑: 地球科学, 1998, 28(6): 498-504.
[4]	陈骏, 汪永进, 陈旸, 等. 中国黄土地层Rb和Sr地球化学特征及其古季风气候意义[J]. 地质学报, 2001, 75(2): 259-266.
[5]	刘安娜, 庞奖励, 黄春长, 等. 甘肃庄浪全新世