Source characteristics and influencing factors of groundwater hydrochemistry in the karst areas of central Guizhou
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摘要: 文章基于区域水文地质、环境地质调查成果,对黔中岩溶区43个地下水点进行了枯水期和丰水期水样采集测试,利用地球化学图解及主成分分析(PCA)法,探讨该区枯水期和丰水期岩溶地下水水化学特征、离子来源及其影响因素。结果表明,该区地下水枯水期和丰水期的水化学特征及影响因素一致,水化学类型均以HCO3(SO4)-Ca(Mg)为主,吉布斯图解分析表明研究区岩溶地下水为岩石风化型,水化学组成主要来源于岩石风化淋滤溶解;[(Ca+Mg)/HCO3] - [ SO4/HCO3]图解分析认为研究区可溶性碳酸盐岩主要受碳酸的风化侵蚀作用控制,局部样品受石膏溶解影响显著;丰水期地下水主成分主要受水岩作用过程(PC1)、人类活动(PC2)及工业生产(PC3)等3类因素影响,这三个影响因素能够解释丰水期地下水水化学组分83.7%的特征;枯水期地下水主要受水岩作用过程(PC1*)和人类活动(PC2*)影响,这二类综合因子能够解释枯水期地下水化学组分85.1%的特征。水岩作用过程是该区地下水水化学组分最主要的影响因素。水岩作用主要影响K+、Na+、Ca2+、Mg2+、HCO−3、TP、F−、SiO2等8项水质指标,人类活动主要影响NH+4、CODMn及Cl−等3项水质指标,而磷矿开采主要影响SO2−4。研究成果深化了对黔中地区岩溶地下水水化学特征的认识,揭示了地下水离子组分来源及影响因素,研究成果对黔中岩溶区地下水资源的合理开发利用与保护具有积极的指导意义。Abstract:
Based on the results of regional hydrogeological and environmental geological surveys, this study conducted comprehensive water sampling and testing at 43 groundwater points across the karst areas of central Guizhou during the dry and wet seasons. The study utilized three widely-used geochemical diagrams—Piper trilinear plots, Gibbs diagrams, and ion ratio diagrams (including relationships like HCO−3-(Mg2+/Ca2+ and [SO2−4/HCO−3]-[Ca2++Mg2+]/HCO−3) to identify the sources and characteristics of hydrochemical indicators of groundwater in the karst areas of central Guizhou. In addition to these geochemical methods, principal component analysis (PCA) was performed separately on the results of water quality tests completed from the dry and wet seasons to further clarify and verify the characteristics of groundwater sources during these two seasons, and to pinpoint specific water quality indicators influenced by various environment and human factors in the karst areas. The research findings reveal that the hydrochemical characteristics and influencing factors of groundwater in the study area are relatively consistent during the dry and wet seasons. Hydrochemical types of groundwater in this area is predominantly characterized by HCO3(SO4)-Ca(Mg). The Gibbs diagrams show that the groundwater chemistry across the study area aligns closely with the rock weathering type, with only minor deviations of a single mine water sample (H6). A comprehensive analysis using Gibbs diagrams confirms that karst groundwater in the study area is primarily of a rock weathering type, with its hydrochemical composition predominantly derived from rock weathering and leaching dissolution processes. Further analysis using the [(Ca+Mg)/HCO3]-[SO4/HCO3] diagrams indicates that the molar ratio of [Ca2++Mg2+]/HCO−3 in groundwater during both the wet and dry seasons is largely below 0.5. This finding is particularly concentrated in the areas dominated by carbonate rocks, with some samples showing a trend towards gypsum dissolution. Particularly, certain samples, such as Spring S214 in Yongjing town of Xifeng county, and Spring C8 in Longyanpo village of Jinzhong town, Kaiyang county, are located either to the right or near the gypsum dissolution line. These positions indicate a significant influence of gypsum dissolution on groundwater chemistry, suggesting gypsum dissolution plays a crucial role in shaping the hydrochemical profile in parts of the areas. A comprehensive analysis of ion ratio correlations suggests that the soluble carbonate rocks in the study area are primarily affected by carbonate weathering and erosion processes. However, significant impacts from gypsum dissolution are also observed in some samples. This suggests that while the majority of the groundwater chemistry is shaped by carbonate dissolution, there are distinct pockets where gypsum dissolution contributes markedly to the groundwater composition. During the wet season, groundwater composition is mainly influenced by three principal factors: water-rock interactions (PC1), human activities (PC2), and industrial production (PC3). Together, these factors explain 83.7% of the variance in groundwater chemical composition. In contrast, during the dry season, groundwater is primarily influenced by water-rock interactions (PC1*) and human activities (PC2*), jointly accounting for 85.1% of the chemical composition variance. This seasonal variation highlights the dynamic nature of groundwater chemistry in response to both natural and human factors. Water-rock interactions emerge as the predominant factor influencing the hydrochemical composition of groundwater in the study area. These interactions significantly affect the concentrations of major ions such as potassium, sodium, calcium, magnesium, bicarbonate, total phosphorus, fluoride, and silica. Human activities, particularly agricultural and domestic activities, mainly influence the concentrations of ammonium, chemical oxygen demand (CODMn), and chloride. Additionally, the impact of phosphate mining is evident in its contribution to elevated sulfate ion concentrations, particularly in areas near mining operations. The research findings provide valuable insights into the complex hydrochemical dynamics of karst groundwater in central Guizhou. The consistent hydrochemical characteristics observed during the dry and wet seasons, alongside the predominant influence of rock weathering and dissolution processes, underscore the importance of geological factors in shaping groundwater chemistry in karst areas. However, the notable influence of gypsum dissolution in certain samples also highlights the need to consider localized geological variations when groundwater quality and developing management strategies are assessed. Moreover, the identification of human activities and industrial production as significant secondary influences on groundwater quality points to the need for targeted management interventions. These interventions should aim to mitigate the impacts of human activities on groundwater resources, particularly in the areas where agricultural runoff, domestic wastewater discharge, and industrial effluents contribute to the groundwater contamination. Overall, this study enhances our understanding of the hydrochemical characteristics of karst groundwater in central Guizhou, revealing the sources of groundwater ion components and their influencing factors. The findings have significant implications for the rational development and conservation of groundwater resources in karst areas. Effective management strategies should consider both natural geological processes and human influences identified in this study to ensure the sustainable use and protection of groundwater resources in the karst areas in central Guizhou. By integrating hydrogeological surveys with geochemical and statistical analyses, this study provides a comprehensive framework for understanding groundwater systems in karst environment, offering valuable guidance for future research and water resource management. -
0. 引 言
黔中岩溶区是贵州省典型的地下水生态脆弱区[1],岩溶地下水是当地居民生产生活最重要的水源之一。由于岩溶区含水介质的不均一性导致岩溶发育存在差异,区域岩溶水资源分布极不均匀 [2−3]。岩溶区内人类活动及工业生产对岩溶地下水的影响愈发显著,水污染问题已逐渐成为制约区域社会经济发展的重要因素之一[4−6]。
岩溶地下水水化学特征的时空分布规律蕴含着区域地下水的演化历程和影响因素等信息,是水文地球化学研究的重要内容[7−14]。从繁多的水质指标中准确地区分出天然水岩作用过程指标和工农业活动等人为工程活动指标一直是水文地质学、水文地球化学领域研究的热点之一[15−19]。为解决研究对象涉及变量多、主要影响因素难以识别等问题,Jolliffe I.T.[20]和J.Edward Jaekson[21]率先对主成分分析法进行了较为系统的分析和阐述。近年来,主成分分析法(PCA)已广泛应用于水文地球化学研究领域,成为水化学组分特征及其影响因素分析的有效工具[22−31]。
本研究对黔中岩溶地区地下水的枯水期和丰水期进行了系统的水样采集、水质分析,利用变异性分析和主成分分析(PCA),并结合多种地球化学图解,深化了黔中地区岩溶地下水水化学特征的认识,揭示了地下水离子组分来源及影响因素。研究成果对黔中岩溶区地下水资源的合理开发利用与水环境保护具有积极意义。
1. 研究区概况
贵州省黔中核心经济区位于黔中岩溶区内,包括息烽县永靖镇、开阳县城关镇、双流镇、金中镇、永温镇两县5个乡镇的部分地区。区内冬无严寒,夏无酷暑,水热同季,春迟夏短,秋早冬长,多云雾,湿度大。年平均气温10.6~15.30 ℃。年均降雨量1 076.2~1 295.4 mm,雨季多始于4 月中旬,每年5 月至8 月降雨量最为充沛,占全年降雨量60%以上,年际降雨总量变化较大,且各月降雨量差异亦较大,枯丰水期特征明显。
研究区地质构造复杂,褶皱及断裂较发育,白垩系及其下伏地层均发生褶皱变形,为多期构造运动形成。区内主要受加东期及燕山期两大构造旋回的影响,后期构造变形改造、破坏叠加于早期形成的褶皱、断裂,由于应力方向不同,局部呈现后期构造受到早期构造制约的现象。北东向构造是本区较为重要的构造形迹,全区均有发育,其次为近南北向和北西向构造。
黔中岩溶区含水岩组包括纯碳酸盐岩含水岩组、碳酸盐岩与碎屑岩互层含水岩组及非碳酸盐岩夹碳酸盐岩含水岩组,区内地下水系统以地下河系统最为发育,仅洋桥至茶园村一带的洋水背斜所在区域为分散排泄系统,且受磷矿地下开采影响,背斜核部周边地下水多以矿井水形式排泄。总体上,研究区地下水主要接受大气降水面状入渗补给,受地形展布及北东向断层、大型“X”节理控制,地下水总体由斜坡向沟谷径流,受沟谷切割及局部隔水层阻隔,以岩溶泉的形式排泄。
2. 样品采集与测试
本研究采集与测试的样品采集于枯、丰水期各43件(图1),总计86件次。采用5 kg聚乙烯取样壶进行采样,采样前先用所采水样清洗3次再进行水样采集,并进行pH、总硬度及溶解性总固体等水质指标的现场测定。所采水样送至贵州黔北建筑实验测试有限公司测定,测试项目包括K+、Na +、Ca2+、Mg2+、 HCO−3、SO2−4、Cl−及部分微量元素离子等共46项水质指标。其中K+、Na+采用AP1402型火焰光度计测定,Ca2+、Mg2+采用GGX-9型原子吸收分光光度计(火焰)测定,NH+4则采用TU-1900型紫外可见分光光度计测定;而HCO−3、SO2−4、Cl−等则按照国标采用50 mL滴定管、XZ-1T型浊度仪进行滴定。各类图解均利用Coreldraw 2018绘制成图,描述统计分析、变异性分析以及主成分分析则利用SPSS 19.0 统计分析软件完成,文本编辑平台为Microsoft 2016。
图 1 黔中岩溶地区水文地质简图及取样点分布位置图1.取样点及编号 2.碳酸盐岩区 3.碎屑岩区 4.第四系区 5.变质岩区 6.县域界线 7.河流水系 8.水库水域 9.工矿企业 10.工业固废堆场(依比例尺) 11.工业固废堆场 12.污水处理厂 13.垃圾堆场 14.县政府驻地 15.乡镇驻地 16.村寨驻地Figure 1. Hydrogeology map and distribution of sampling sites in the karst areas of cental Guizhou1.sampling sites and numbers; 2. carbonate rock zone; 3. clastic rock zone; 4. Quaternary; 5. metamorphic rock zone; 6. the boundary of county; 7. river system; 8. water area of reservoir; 9. industrial and mining enterprises; 10. industrial solid waste dump (on a scale); 11. industrial solid waste dump; 12. sewage treatment plant; 13. dumping site; 14. county government site; 15. township site 16. village site3. 测试结果
3.1 水化学组成
水质化验结果显示(表1),黔中岩溶区地下水阳离子主要包括K+、Na+、Ca2+、Mg2+和NH+4等,在枯水期和丰水期,除NH+4含量变幅较大外,其余阳离子含量变幅小于25%。黔中岩溶区地下水Ca2+丰水期平均含量为56.07 mg·L−1,枯水期平均含量为57.95 mg·L−1,枯、丰水期变幅为3.36%;Mg2+ 丰水期平均含量为27.49 mg·L−1,枯水期平均含量为33.72 mg·L−1,枯、丰水期变幅为22.65%;K+丰水期平均含量为1.74 mg·L−1,枯水期平均含量为1.87 mg·L−1,枯丰水期变幅为7.49%;Na+丰水期平均含量为5.02 mg·L−1,枯水期平均含量为6.10 mg·L−1,枯丰水期变幅为21.54%;NH+4 丰水期平均含量为0.08 mg·L−1,枯水期平均含量为0.04 mg·L−1,枯丰水期变幅为−45.42%。
表 1 黔中岩溶区地下水描述性统计结果Table 1. Descriptive statistical results of groundwater in the karst areas of central Guizhou离子类别 季节 极小值/mg·L−1 极大值/mg·L−1 均值/mg·L−1 变异系数/% 峰度 Ca2+ 丰水期 28.58 239.50 56.07 56.40 28.00 枯水期 20.17 155.50 57.95 38.50 7.65 Mg2+ 丰水期 6.63 288.00 27.49 151.90 38.33 枯水期 8.66 326.20 33.72 139.30 38.05 NH+4 丰水期 0.02 2.00 0.08 368.80 41.45 枯水期 0.02 0.48 0.04 204.30 17.29 K+ 丰水期 0.30 12.70 1.74 130.40 14.04 枯水期 0.40 20.60 1.87 175.30 27.03 Na+ 丰水期 0.50 90.00 5.02 275.30 36.16 枯水期 0.40 115.00 6.10 295.00 33.76 Cl− 丰水期 0.55 27.58 4.44 109.80 11.48 枯水期 1.47 30.89 5.55 91.70 14.39 SO2−4 丰水期 2.00 220.00 33.23 117.80 11.69 枯水期 2.00 883.00 74.60 176.80 35.61 HCO−3 丰水期 55.40 1 138.00 235.50 65.30 29.53 枯水期 34.80 1 295.00 246.50 72.70 29.03 pH 丰水期 6.63 8.37 7.60 4.30 1.76 枯水期 6.96 8.44 7.90 4.70 −0.74 COD 丰水期 0.02 4.77 0.50 149.80 26.34 枯水期 0.02 4.13 0.48 138.20 22.95 TP 丰水期 0.02 7.84 0.35 404.50 22.66 枯水期 0.02 25.50 0.64 603.40 42.97 SiO2 丰水期 0.21 12.90 3.13 53.20 28.81 枯水期 2.14 27.80 4.66 86.90 26.66 F− 丰水期 0.10 0.80 0.17 92.80 7.56 枯水期 0.00 0.84 0.13 92.80 27.00 黔中岩溶区地下水阴离子主要包括HCO−3、SO2−4以及Cl−等,在枯水期丰水期,除SO2−4枯、丰水期含量变幅较大外,其余阴离子枯、丰水期含量变幅小于25%。黔中岩溶区地下水HCO−3丰水期平均含量为235.50 mg·L−1,枯水期平均含量为246.52 mg·L−1,枯丰水期变幅为4.68%;SO2−4丰水期平均含量为33.23 mg·L−1,枯水期平均含量为74.60 mg·L−1,枯丰水期变幅为124.49%;Cl−丰水期平均含量为4.44 mg·L−1,枯水期平均含量为5.55 mg·L−1,枯、丰水期变幅为24.97%。
水质分析结果表明,黔中岩溶区地下水水化学组分含量较为稳定,枯水期和丰水期各离子含量总体变幅低于50%,总磷(TP)、硫酸盐(SO2−4)和铵根离子(NH+4)枯丰水期变幅大于50%。其中SO2−4和TP离子枯丰水期变幅分别为124.49%和85.42%,上述两类离子可能主要受开阳磷矿长期地下开采影响[32];而铵根离子(NH+4)则主要受区内居民生活污染影响[33]。
3.2 变异性分析
变异系数是变量稳定性特征的直接表示,稳定性越强,变异系数就越小,反之亦然。变异系数较大说明地下水化学组分形成及演化的影响因素相对更为复杂。
由表1 可知,黔中岩溶区地下水整体上呈中性,枯水期、丰水期地下水的K+、Na+、Mg2+、NH+4、Cl−和SO2−4的空间变异性较大,丰水期变异系数分别为130.4%、275.3%、151.9%、368.8%、109.8%和117.8%;枯水期变异系数分别为175.3%、295.0%、139.3%、204.3%、91.7%和176.8%。
3.3 水化学类型
黔中岩溶区地下水以重碳酸盐型为主,硫酸盐型为辅。由图2可看出,阳离子方面(左下角三角区域),黔中岩溶区枯水期和丰水期地下水有着相似的水化学组成,其投点均明显集中于Ca2+离子端元,且有着向Mg2+离子端元和K++Na+端元过渡的趋势;阴离子方面(右下角三角区域),黔中岩溶区枯水期和丰水期地下水投点均落于HCO−3端元,且显示出逐渐由HCO−3向SO2−4过渡的趋势。水性质方面(中间菱形区域),投点大部分集中于“1”区,指示黔中岩溶区枯水期和丰水期地下水中碱土金属离子含量大于碱金属离子,且碳酸硬度(次生碱度)超过50%,地下水化学性质以碱土金属和弱酸为主。总体上,黔中岩溶区地下水水化学类型以HCO3(SO4)-Ca(Mg)为主。
4. 讨 论
4.1 离子来源
黔中岩溶区枯、丰水期地下水pH介于7.6~7.9之间,属中性水,且枯、丰水期地下水水化学特征总体表现出相似特征。
已有研究表明,岩溶区地下水体可溶性离子组分主要来源于岩石化学风化[34]、大气输入[35](降雨)以及蒸发浓缩效应[36]三个方面。地下水Gibbs 图可用于定性描述地下水各组分的起源及变化趋势[37−38]。将黔中岩溶区枯、丰水期地下水有关离子含量投于Gibbs图(图3),可以看出,黔中岩溶区枯、丰水期地下水集中于岩石风化型区域,表明研究区地下水主要为“岩石风化型”地下水,其离子组分主要来源于可溶性碳酸盐岩的风化溶蚀。
贵州省岩溶区地下水Ca2+、HCO−3及Mg2+离子主要来源于碳酸盐岩的溶蚀作用,而Mg2+ /Ca2+值主要受可溶性碳酸盐岩所含方解石和白云石比例控制[39−41]。黔中岩溶区地下水HCO−3-(Mg2+/Ca2+)关系图(图4)显示,黔中岩溶区枯、丰水期地下水投点均落于白云石和方解石区域之间,其Mg2+/Ca2+值介于0~0.8之间,极个别水样Mg2+/Ca2+比值大于0.8,指示黔中岩溶区枯、丰水期地下水Ca2+、HCO−3及Mg2+均由白云石和方解石矿物溶滤提供。
岩溶地下水水岩作用过程以碳酸溶蚀碳酸盐岩为主,当碳酸盐岩仅被碳酸溶蚀时,地下水中[Ca2++Mg2+]/HCO−3的理论摩尔比为0.5[42],人类生产生活带入的硝酸和硫酸亦可不同程度溶蚀碳酸盐岩[43−48],导致地下水中[Ca2++Mg2+]/HCO−3摩尔比的变化[49]。因此,绘制地下水[SO2−4/HCO−3]-[Ca2++Mg2+]/ HCO−3图5[Ca2++Mg2+]/ HCO−3摩尔比多低于0.5,且投点均集中于图左下角,个别样品存在向石膏溶解线演化的趋势。特别是息烽县永靖镇上洪马村水头上下降泉(S214)和开阳县金中镇岩脚村龙堰坡下降泉(C8)两件水样落于石膏溶解线右侧及其附近,显示其受石膏溶解控制作用显著。
4.2 主成分分析
前述对研究区枯、丰水期地下水组分(K+、Na+、Mg2+、NH+4、Cl−和SO2−4)的空间变异系数较大,表明研究区地下水存在明显的物源信息重叠。因此,需要将数据降维处理,进行PCA分析。
对黔中岩溶区枯、丰水期43 组(86件)水样测试指标采用主成分方法提取特征值,经KMO度量及Bartlett 球型度检验(表2),认为主成分分析法适用,选取特征根大于1公因子进行分析,研究区丰、枯水期地下水分别提取出3个和2个公因子,丰水期提取的3个公因子累计贡献率达到83.7%(表3),枯水期提取的2个公因子累计贡献率达85.1%(表4),认为所提取的公因子均能够反映数据大部分的原始信息。
表 2 KMO 和 Bartlett 检验结果表Table 2. Test results of KMO and Bartlett取样足够度的
Kaiser-Meyer-Olkin 度量丰水期 0.67 枯水期 0.74 Bartlett 的球形度检验
近似卡方丰水期 746.67 枯水期 1 150.82 表 3 丰水期地下水特征值、方差百分数和累计方差百分数Table 3. Eigen values, percentages of variance and cumulative percentages of groundwater in the wet season成分 PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10 PC11 PC12 PC13 特征值 7.269 2.552 1.055 0.661 0.614 0.329 0.17 0.102 0.095 0.076 0.042 0.03 0.004 方差百分数/% 55.918 19.628 8.115 5.088 4.725 2.535 1.306 0.788 0.729 0.588 0.324 0.228 0.029 累计方差百分数/% 55.92 75.55 83.66 88.75 93.48 96.01 97.32 98.10 98.83 99.42 99.74 99.97 100.0 表 4 枯水期地下水特征值、方差百分数和累计方差百分数Table 4. Eigen values, percentages of variance and cumulative percentages of groundwater in the dry season成分 PC1* PC2* PC3* PC4* PC5* PC6* PC7* PC8* PC9* PC10* PC11* PC12* PC13* 特征值 8.971 2.092 0.944 0.407 0.194 0.139 0.080 0.069 0.044 0.035 0.016 0.009 0.000 方差百分数 69.01 16.09 7.263 3.129 1.492 1.067 0.617 0.531 0.339 0.266 0.126 0.068 0.003 累计方差百分数 69.01 85.10 92.36 95.49 96.98 98.05 98.67 99.20 99.54 99.80 99.93 99.99 100.0 地下水主成分图可直观地显示各项综合因子与原变量之间的关系。从图6可看出,黔中岩溶区丰水期地下水(图6左)三个主成分所对应的水化学指标显示出较好的归集特征;枯水期地下水(图6右)主成分提取2项特征因子,为便于进行丰水期和枯水期的对比,特将PC3*引入主成分图。主成分投图显示,枯水期地下水各项水化学指标亦表现出较好的归集特征。
研究区丰水期地下水第一主成分(PC1)的方差百分数为55.9%,由于与水岩作用密切联系的Na+、Mg2+、Ca2+、HCO−3、SiO2、K+、TP以及F−离子等组分的特征值贡献度在第一主成分中相对较大,所以PC1代表以灰岩、白云岩为主可溶性碳酸盐岩含水介质与地下水的水-岩反应,是丰水期地下水中上述离子组分的最主要来源;第二主成分(PC2)的方差百分数为19.6%,由于与人类生产生活排污有密切联系的NH+4、CODMn以及Cl−的特征值贡献度较大,故PC2代表丰水期地下水受人类生产生活影响的综合因子;第三主成分(PC3)的方差百分数为8.12%,由于其SO2−4离子特征值贡献度较大,其次为pH。通过对开阳磷矿开采区巷道涌水的水质化验分析发现,磷矿开采巷道涌水特征水化学指标为SO2−4离子(数据暂未发表),因此PC3代表丰水期地下水受磷矿开采等工业活动的影响。
研究区枯水期地下水第一主成分(PC1*)的方差百分数为69.0%,其与水岩作用密切联系的Na+、K+、Mg2+、SO2−4、TP、HCO−3、F−、SiO2以及Ca2+离子等组分的特征值贡献度在第一主成分中相对较大,所以PC1*代表以方解石和白云石为主的可溶性碳酸盐岩含水介质与地下水发生的水-岩作用,同样是研究区枯水期地下水上述离子的最主要来源;第二主成分(PC2*)的方差百分数为16.1%,由于其与人类生产生活排污有密切联系的CODMn、Cl−以及NH+4的特征值贡献度较大,故PC2*代表枯水期地下水受人类生产生活影响的综合因子。相较于丰水期岩溶地下水,黔中岩溶区枯水期地下水受工业生产活动较小,主要是受枯水期大气降雨入渗量减小控制,而工业生产废物主要是通过大气降水淋滤入渗补给地下水,降雨入渗补给量减小导致入渗的工业污染物减小。故此,黔中岩溶区枯水期地下水受工业生产活动较小。
5. 结 论
(1)黔中岩溶区地下水枯水期和丰水期的水化学特征及其影响因素结果一致,水化学类型以HCO3(SO4)-Ca(Mg)为主,研究区地下水化学组分主要来源于碳酸对可溶性碳酸盐岩的淋滤侵蚀作用,局部受石膏溶解影响显著;
(2)黔中岩溶区地下水水岩作用过程均是其水化学组分最主要的来源途径,水岩作用主要涉及K+、Na+、Ca2+、Mg2+、HCO−3、TP、F−以及SiO2等八项水质指标,人类活动主要涉及NH+4、CODMn及Cl−等三项水质指标,而磷矿开采则主要涉及SO2−4离子;
(3)黔中岩溶区丰水期地下水主要受水岩作用过程(PC1)、人类活动(PC2)及工业生产(PC3)等三类因素的影响,而枯水期地下水则主要受水岩作用过程(PC1*)和人类活动(PC2*)的影响。
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图 1 黔中岩溶地区水文地质简图及取样点分布位置图
1.取样点及编号 2.碳酸盐岩区 3.碎屑岩区 4.第四系区 5.变质岩区 6.县域界线 7.河流水系 8.水库水域 9.工矿企业 10.工业固废堆场(依比例尺) 11.工业固废堆场 12.污水处理厂 13.垃圾堆场 14.县政府驻地 15.乡镇驻地 16.村寨驻地
Figure 1. Hydrogeology map and distribution of sampling sites in the karst areas of cental Guizhou
1.sampling sites and numbers; 2. carbonate rock zone; 3. clastic rock zone; 4. Quaternary; 5. metamorphic rock zone; 6. the boundary of county; 7. river system; 8. water area of reservoir; 9. industrial and mining enterprises; 10. industrial solid waste dump (on a scale); 11. industrial solid waste dump; 12. sewage treatment plant; 13. dumping site; 14. county government site; 15. township site 16. village site
表 1 黔中岩溶区地下水描述性统计结果
Table 1. Descriptive statistical results of groundwater in the karst areas of central Guizhou
离子类别 季节 极小值/mg·L−1 极大值/mg·L−1 均值/mg·L−1 变异系数/% 峰度 Ca2+ 丰水期 28.58 239.50 56.07 56.40 28.00 枯水期 20.17 155.50 57.95 38.50 7.65 Mg2+ 丰水期 6.63 288.00 27.49 151.90 38.33 枯水期 8.66 326.20 33.72 139.30 38.05 NH+4 丰水期 0.02 2.00 0.08 368.80 41.45 枯水期 0.02 0.48 0.04 204.30 17.29 K+ 丰水期 0.30 12.70 1.74 130.40 14.04 枯水期 0.40 20.60 1.87 175.30 27.03 Na+ 丰水期 0.50 90.00 5.02 275.30 36.16 枯水期 0.40 115.00 6.10 295.00 33.76 Cl− 丰水期 0.55 27.58 4.44 109.80 11.48 枯水期 1.47 30.89 5.55 91.70 14.39 SO2−4 丰水期 2.00 220.00 33.23 117.80 11.69 枯水期 2.00 883.00 74.60 176.80 35.61 HCO−3 丰水期 55.40 1 138.00 235.50 65.30 29.53 枯水期 34.80 1 295.00 246.50 72.70 29.03 pH 丰水期 6.63 8.37 7.60 4.30 1.76 枯水期 6.96 8.44 7.90 4.70 −0.74 COD 丰水期 0.02 4.77 0.50 149.80 26.34 枯水期 0.02 4.13 0.48 138.20 22.95 TP 丰水期 0.02 7.84 0.35 404.50 22.66 枯水期 0.02 25.50 0.64 603.40 42.97 SiO2 丰水期 0.21 12.90 3.13 53.20 28.81 枯水期 2.14 27.80 4.66 86.90 26.66 F− 丰水期 0.10 0.80 0.17 92.80 7.56 枯水期 0.00 0.84 0.13 92.80 27.00 表 2 KMO 和 Bartlett 检验结果表
Table 2. Test results of KMO and Bartlett
取样足够度的
Kaiser-Meyer-Olkin 度量丰水期 0.67 枯水期 0.74 Bartlett 的球形度检验
近似卡方丰水期 746.67 枯水期 1 150.82 表 3 丰水期地下水特征值、方差百分数和累计方差百分数
Table 3. Eigen values, percentages of variance and cumulative percentages of groundwater in the wet season
成分 PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10 PC11 PC12 PC13 特征值 7.269 2.552 1.055 0.661 0.614 0.329 0.17 0.102 0.095 0.076 0.042 0.03 0.004 方差百分数/% 55.918 19.628 8.115 5.088 4.725 2.535 1.306 0.788 0.729 0.588 0.324 0.228 0.029 累计方差百分数/% 55.92 75.55 83.66 88.75 93.48 96.01 97.32 98.10 98.83 99.42 99.74 99.97 100.0 表 4 枯水期地下水特征值、方差百分数和累计方差百分数
Table 4. Eigen values, percentages of variance and cumulative percentages of groundwater in the dry season
成分 PC1* PC2* PC3* PC4* PC5* PC6* PC7* PC8* PC9* PC10* PC11* PC12* PC13* 特征值 8.971 2.092 0.944 0.407 0.194 0.139 0.080 0.069 0.044 0.035 0.016 0.009 0.000 方差百分数 69.01 16.09 7.263 3.129 1.492 1.067 0.617 0.531 0.339 0.266 0.126 0.068 0.003 累计方差百分数 69.01 85.10 92.36 95.49 96.98 98.05 98.67 99.20 99.54 99.80 99.93 99.99 100.0 -
[1] 袁道先. 我国西南岩溶石山的环境地质问题[J]. 世界科技研究与发展, 1997, 19(5):41-43.YUAN Daoxian. On the environmental and geologic problems of karst mountains and rocks in the South-west China[J]. World Sci-Tech R & D, 1997, 19(5): 41-43. [2] 杨平恒, 袁道先, 叶许春, 谢世友, 陈雪彬, 刘子琦. 降雨期间岩溶地下水化学组分的来源及运移路径[J]. 科学通报, 2013, 58(18): 1755-1763.YANG Pingheng, YUAN Daoxian, YE Xuchun, XIE Shiyou, CHEN Xuebin, LIU Ziqi. Sources and migration path of chemical compositions in a karst groundwater system during rainfall events[J]. Chinese Science Bulletin, 2013, 58(18): 1755-1763. [3] 张彦林, 李生永, 付东林, 崔旭东. 陇东盆地西部岩溶地下水形成机制研究[J]. 中国地质, 2006, 33(6):1393-1399. doi: 10.3969/j.issn.1000-3657.2006.06.024ZHANG Yanlin, LI Shengyong, FU Donglin, CHUI Xudong. Formation mechanism of karst groundwater in the western Longdong basin, Northwestern China[J]. Geology in China, 2006, 33(6): 1393-1399. doi: 10.3969/j.issn.1000-3657.2006.06.024 [4] 袁道先, 薛禹群, 傅家谟. 防止我国西南岩溶地区地下河变成“下水道”的对策与建议[R]. 中国科学院院士建议, 2007, 4: 1-14. [5] 管清花, 李福林, 王爱芹, 冯平, 田婵娟, 陈学群, 刘丹. 济南市岩溶泉域地下水化学特征与水环境演化[J]. 中国岩溶, 2019, 38(5):653-662. doi: 10.11932/karst20190501GUAN Qinghua, LI Fulin, WANG Aiqin, FENG Ping, TIAN Chanjuan, CHEN Xuequn, LIU Dan. Hydrochemistry characteristics and evolution of karst spring groundwater system in Jinan[J]. Carsologica Sinica, 2019, 38(5): 653-662. doi: 10.11932/karst20190501 [6] 鲁孟胜, 韩宝平, 武凡, 孙德全, 张兆民. 鲁西南地区高氟地下水特征及成因探讨[J]. 中国地质, 2014, 41(1):294-302. doi: 10.3969/j.issn.1000-3657.2014.01.024LU Mengsheng, HAN Baoping, WU Fan, SUN Dequan, ZHANG Zhaomin. Characteristics and genesis of high-fluorine groundwater in southwestern Shandong Province[J]. Geology in China, 2014, 41(1): 294-302. doi: 10.3969/j.issn.1000-3657.2014.01.024 [7] 朱琳, 苏小四. 吉林西部地区第四系潜水水质影响因素的R型因子分析[J]. 地球科学与环境学报, 2006, 28(1):51-56. doi: 10.3969/j.issn.1672-6561.2006.01.011ZHU Lin, SU Xiaosi. Application of R-mode analysis in determining influencing factors of Quaternary unconfined groundwater quality in west area of Jilin Province[J]. Journal of Earth Sciences and Environment, 2006, 28(1): 51-56. doi: 10.3969/j.issn.1672-6561.2006.01.011 [8] 董维红, 苏小四, 侯光才, 林学钰, 柳富田. 鄂尔多斯白垩系地下水盆地地下水水化学类型的分布规律[J]. 吉林大学学报(地球科学版), 2007, 37(2): 288-292.DONG Weihong, SU Xiaosi, HOU Guangcai, LIN Xueyu, LIU Futian. Distribution law of groundwater hydrochemical type in the Ordos Cretaceous Artesian Basin[J]. Journal of Jilin University (Earth Science Edition), 2006, 36(3): 391 398. [9] 任坤, 师阳, 李晓春, 蓝家程, 徐尚全. 典型岩溶槽谷区地下水化学特征及地球化学敏感性分析[J]. 中国岩溶, 2014, 33(1):15-21. doi: 10.3969/j.issn.1001-4810.2014.01.003REN Kun, SHI Yang, LI Xiaochun, LAN Jiacheng, XU Shangquan. Study of the chemical features and geochemical susceptibility of the groundwater system in a typical karst trough valley[J]. Carsologica Sinica, 2014, 33(1): 15-21. doi: 10.3969/j.issn.1001-4810.2014.01.003 [10] 冯亚伟, 陈洪年, 卜华, 贾德旺. 羊庄岩溶水系统水化学成因及同位素特征[J]. 中国岩溶, 2019, 38(3):394-403. doi: 10.11932/karst20190309FENG Yawei, CHEN Hongnian, BU Hua, JIA Dewang. Hydro-chemical genesis and isotope characteristics of Yangzhuang karst water system[J]. Carsologica Sinica, 2019, 38(3): 394-403. doi: 10.11932/karst20190309 [11] 樊连杰, 裴建国, 邹胜章, 杜毓超, 卢丽. 重庆市南川区南部岩溶地下水水文地球化学特征[J]. 中国岩溶, 2017, 36(5):697-703.FAN Lianjie, PEI Jianguo, ZOU Shengzhang, DU Yuchao, LU Li. Hydrogeochemical characteristics of karst groundwater in southern Nanchuan district of Chongqing[J]. Carsologica Sinica, 2017, 36(5): 697-703. [12] 杨秀丽, 罗维, 裴建国, 犹俊. 贵阳市岩溶地下水水质变化特征浅析[J]. 中国岩溶, 2017, 36(5):713-720.YANG Xiuli, LUO Wei, PEI Jianguo, YOU Jun. Analysis of variation characteristics of karst groundwater quality in Guiyang City[J]. Carsologica Sinica, 2017, 36(5): 713-720. [13] 杨桂花, 潘晓东, 袁建飞, 邓国仕, 唐业旗. 黔西北裸露岩溶地区水文地球化学特征对土地利用方式的响应研究[J]. 中国岩溶, 2018, 37(4):535-544. doi: 10.11932/karst20180407YANG Guihua, PAN Xiaodong, YUAN Jianfei, DENG Guoshi, TANG Yeqi. Response of hydrogeochemical characteristics to land-use modes in exposed karst areas of northwestern Guizhou Province[J]. Carsologica Sinica, 2018, 37(4): 535-544. doi: 10.11932/karst20180407 [14] 张海月, 杨平恒, 王建力, 蓝家程, 詹兆君, 任娟, 张宇. 城市化对岩溶水系统化学组分演化的影响:以重庆市南山老龙洞地下河为例[J]. 中国岩溶, 2017, 36(4):541-549. doi: 10.11932/karst20170416ZHANG Haiyue, YANG Pingheng, WANG Jianli, LAN Jiacheng, ZHAN Zhaojun, REN Juan, ZHANG Yu. Effect of urbanization on the hydrogeochemical evolution of karst groundwater system: A case of the Laolongdong watershed, Chongqing, China[J]. Carsologica Sinica, 2017, 36(4): 541-549. doi: 10.11932/karst20170416 [15] Chen K P, Jiao J J, Huang J M, Huang R Q. Multivariate statistical evaluation of trace elements in groundwater in a coastal area in Shenzhen, China[J]. Environmental Pollution, 2007, 147(3): 771-780. doi: 10.1016/j.envpol.2006.09.002 [16] Cloutier V, Lefebvre R, Therrien R, Savard M M. Multivariate statistical analysis of geochemical data as indicative of the hydrogeochemical evolution of groundwater in a sedimentary rock aquifer system[J]. Journal of Hydrology, 2008, 353(3): 294-313. [17] 黄科云, 刘德深, 马祖陆, 许丹丹, 欧梦梦, 杨苗清. 云南鹤庆西山岩溶地下水主要离子雨季和旱季对比及来源分析[J]. 地球与环境, 2015, 43(2):183-189.HUANG Keyun, LIU Deshen, MA Zhulu, XU Dandan, OU Mengmeng, YANG Miaoqing. Major ion chemistry and their source of karst groundwater from the Heqing west mountain, China during flood and dry seasons[J]. Earth and Environment, 2015, 43(2): 183-189. [18] 蒲俊兵, 袁道先, 蒋勇军, 苟鹏飞, 殷建军. 重庆岩溶地下河水文地球化学特征及环境意义[J]. 水科学进展, 2010, 21(5):628-636.PU Junbing, YUAN Daoxian, JIANG Yongjun, GOU Pengfei, YIN Jianjun. Hydrogeochemistry and environmental meaning of Chongqing subterranean karst streams in China[J]. Advances in Water Science, 2010, 21(5): 628-636. [19] 陈静生, 王飞越, 何大伟. 黄河水质地球化学[J]. 地学前缘, 2006, 13(1): 58-73.CHEN Jingsheng, WANG Feiyue, HE Dawei. Geochemistry of water quality of the Yellow River basin[J]. Earth Science Frontiers, 2006, 13(1): 58-73. [20] Jolliffe I. Principal component analysis[M]. New York, USA: Springer, 1986. [21] J Edward Jackson. A user's guide to principal components[M]. New York, USA: A Wiley-Interscience Publication, 1992. [22] Sun Jianguo. A note on principal component analysis for multi-dimensional data[J]. Statistics & Probability Letter, 2000, 46(1): 69-73. [23] 王松, 夏绍玮. 一种鲁棒主成分分析(PCA)算法[J]. 系统工程理论与实践, 1998, 18(l):9-13. doi: 10.3321/j.issn:1000-6788.1998.01.002WANG Song, XIA Shaowei. A robust principal component analysis (PCA) algorithm[J]. Systems Engineering-Theory & Practice, 1998, 18(l): 9-13. doi: 10.3321/j.issn:1000-6788.1998.01.002 [24] Irie B, Miyake S. Capabilities of three-layered Perceptrons[C]//Proceedings of the IEEE Inter Coof on Neural Networks, 1988(1): 641-648. [25] Hanson S. Knowledge representation in connectionist networks. Bell communications Research Technical Report[R]. 1987. [26] John I Marden. Some robust estimates of principal components[J]. Statistics & Probability Letter, 1999, 43: 349-359. [27] Mohamed N Nounou, Bhavik R Bakshi, Prem K Goel, Shen X T. Improving principal component analysis Bayesian estimation[R]. Proceedings of the American Control Conference Arlington, 2001: 25-27. [28] 孟生旺. 用主成份分析法进行多指标综合评价应注意的问题[J]. 统计研究, 1992(4):86-87. [29] 陈述云, 张崇莆. 对多指标综合评价的主成分分析方法的改进[J]. 统计研究, 1995(1):35-39. [30] 阎慈琳. 关于用主成分分析做综合评价的若干问题[J]. 数理统计与管理, 1998, 17(2):22-25.YAN Cilin. On composite evaluation by principal component analysis[J]. Journal of Applied Statistics and Management, 1998, 17(2): 22-25. [31] 姜旭平, 马宁辉. PCA方法及其在多准则评估模型中的应用[J]. 系统理论与实践, 1997, 17(4): 110-115.JIANG Xuping, MA Ninghui. Research on PCA and it's application in multicriteria evaluation[J]. Systems Engineering-Theory & Practice, 1997, 17(4): 110-115. [32] 冯慕华, 潘继征, 柯凡, 李文朝. 云南抚仙湖流域废弃磷矿区水污染现状[J]. 湖泊科学, 2008, 20(6):766-772. doi: 10.3321/j.issn:1003-5427.2008.06.011FENG Muhua, PAN Jizheng, KE Fan, LI Wenchao. Water pollution of post-mined lands in Lake Fuxian watershed in Yunnan Province[J]. Journal of Lake Sciences, 2008, 20(6): 766-772. doi: 10.3321/j.issn:1003-5427.2008.06.011 [33] 朱丹尼, 邹胜章, 周长松, 李录娟, 谢浩. 不同城镇功能区岩溶地下水化学敏感因子识别[J]. 中国岩溶, 2018, 37(4):484-492. doi: 10.11932/karst20180402ZHU Danni, ZOU Shengzhang, ZHOU Changsong, LI Lujuan, XIE Hao. Identification of hydrochemical sensitive factors of karst groundwater in different functional urban areas[J]. Carsologica Sinica, 2018, 37(4): 484-492. doi: 10.11932/karst20180402 [34] Lasaga A C, Soler J M, Ganor J, Burch T E, Nagy K L. Chemical weathering rate laws and global geochemical cycles[J]. Geochimica et Cosmochimica Acta, 1994, 58(10): 2361-2386. doi: 10.1016/0016-7037(94)90016-7 [35] Gibbs R J. Mechanisms controlling world water chemistry[J]. Science, 1970, 170(3962): 1088-1090. doi: 10.1126/science.170.3962.1088 [36] Feth J H, Gibbs R J. Mechanisms controlling world water chemistry: Evaporation-crystallization process[J]. Science, 1971, 172(3985): 870-872. doi: 10.1126/science.172.3985.870 [37] Kilham P. Mechanisms controlling the chemical composition of lakes and rivers: Data from Africa[J]. Limnology and Oceanography, 1990, 35(1): 80-83. doi: 10.4319/lo.1990.35.1.0080 [38] Négrel P. Geochemical study of a granitic area—the Margeride Mountains, France: Chemical element behavior and 87Sr/86Sr constraints[J]. Aquatic Geochemistry, 1999, 5(2): 125-165. doi: 10.1023/A:1009625412015 [39] 江峰, 李强, 吉勤克补子, 周亚男. 贵州省岩溶地区饮用天然矿泉水化学特征及其宏量组分来源分析[J]. 贵州地质, 2019, 36(2):173-179. doi: 10.3969/j.issn.1000-5943.2019.02.010JIANG Feng, LI Qiang, JI Qinkebuzi, ZHOU Ya'nan. The chemical characteristics of the potable natural mineral water and its major components source analysis of the karst area in Guizhou Province[J]. Guizhou Geology, 2019, 36(2): 173-179. doi: 10.3969/j.issn.1000-5943.2019.02.010 [40] White W B. Geomorphology and hydrology of karst terrains[M]. New York: Oxford University Press, 1988: 103-1481. [41] 黄奇波, 覃小群, 刘朋雨, 蓝芙宁, 张连凯, 苏春田. 乌江中上游段河水主要离子化学特征及控制因素[J]. 环境科学, 2016, 37(5):1779-1787.HUANG Qibo, QIN Xiaoqun, LIU Pengyu, LAN Funing, ZHANG Liankai, SU Chuntian. Major ionic features and their controlling factors in the upper-middle reaches of Wujiang river[J]. Environmental Science, 2016, 37(5): 1779-1787. [42] 李军, 刘丛强, 李龙波, 李思亮, 王宝利, B Chetelat. 硫酸侵蚀碳酸盐岩对长江河水DIC循环的影响[J]. 地球化学, 2010, 39(4):305-313.LI Jun, LIU Congqiang, LI Longbo, LI Siliang, WANG Baoli, B Chetelat. The impacts of chemical weathering of carbonate rock by sulfuric acid on the cycling of dissolved inorganic carbon in Changjiang River water[J]. Geochimica, 2010, 39(4): 305-313. [43] Barnes R T, Raymond P A. The contribution of agricultural and urban activities to inorganic carbon fluxes within temperate watersheds[J]. Chemical Geology, 2009, 266(3): 327-336. [44] Jiang Y. The contribution of human activities to dissolved inorganic carbon fluxes in a karst underground river system: Evidence from major elements and δ13CDIC in Nandong, Southwest China[J]. Journal of Contaminant Hydrology, 2013, 152(4): 1-11. [45] Perrin A S, Probst A, Probst J L. Impact of nitrogenous fertilizers on carbonate dissolution in small agricultural catchements: Implications for weathering CO2 uptake at regional and global scales[J]. Geochimica et Cosmochimica Acta, 2008, 72(13): 3105-3123. doi: 10.1016/j.gca.2008.04.011 [46] Semhi K, Suchet P A, Clauer N, Probst J L. Impact of nitrogen fertilizers on the natural weathering-erosion processes and fluvial transport in the Garonne basin[J]. Applied Geochemistry, 2000, 15(6): 865-878. doi: 10.1016/S0883-2927(99)00076-1 [47] Cartwright I. The origins and behaviour of carbon in a major semiarid river, the Murray River, Australia, as constrained by carbon isotopes and hydrochemistry[J]. Applied Geochemistry, 2010, 25(11): 1734-1745. doi: 10.1016/j.apgeochem.2010.08.020 [48] Li S L, Calmels D, Han G, Gaillardet J R, Liu C Q. Sulfuric acid as an agent of carbonate weathering constrained by δ13CDIC: Examples from Southwest China[J]. Earth and Planetary Science Letters, 2008, 270(3): 189-199. [49] 刘丛强, 蒋颖魁, 陶发祥, 郎赟超, 李思亮. 西南喀斯特流域碳酸盐岩的硫酸侵蚀与碳循环[J]. 地球化学, 2008, 37(4): 404-414.LIU Congqiang, JIANG Yingkui, TAO Faxiang, LANG Yunchao, LI Siliang. Chemical weathering of carbonate rocks by sulfuric acid and the carbon cycling in Southwest China[J]. Geochimica, 2008, 37(4): 404-414. 期刊类型引用(0)
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