Hydrochemical Characteristics and Water Quality Assessment of Groundwater in Northern Foothill of Luoji Mountains
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摘要:
为研究川西大凉山区螺髻山北麓地下水化学特征、演化机制以及评价地下水质现状，笔者系统采集研究区不同地段的15组地下水样品为研究对象。利用Gibbs图解法、离子比例系数法和基于RMSprop算法的BP神经网络评价法，探讨该地区地下水化学特征演化机制，评价地下水质现状，支持服务帮助当地合理开发和安全利用水资源。结果表明研究区水化学类型以Mg2+·Ca2+−HCO3–为主，其水化学离子的形成主要以岩土风化溶滤作用为主，由硅酸盐矿物与碳酸盐矿物共同控制，硅酸盐矿物控制更显著。结合地质背景，认为硅酸盐矿物主要来自火山碎屑岩类、花岗岩类、砂岩类和泥质岩类等岩石。利用BP神经网络对5000组地下水样本学习训练，对研究区样本进行评价，模型训练图像表明BP神经网络能很好拟合地下水样本训练集并且对测试集进行客观准确的判断。研究区地下水评价结果显示：Ⅰ类水质点占13.3%，Ⅱ类水质点占40%，Ⅲ类水质点占46.6%，整体水质较好，建议Ⅲ类水质地区普格县特尔果乡甲甲沟村、普格县特补乡白庙子需要加强地下水污染源调查以及水质保护。
Abstract:To investigate the hydrochemical characteristics, evolution, and assessment of water quality in the northern foot of the Luoyang Mountains in the western Sichuan Daliang Mountains, 15 sets of local groundwater chemistry samples from different sections of the study area were collected as research objects. Analysis and study of hydrochemical characteristics and evolution in this area use Gibbs’ diagram and ion proportion coefficient method. Furthermore, assessing groundwater quality BP neural network classification method with RMSprop algorithm, supporting services to help local communities develop and use water resources wisely and safely. The results show that the water chemistry of the study area is dominated by Mg2+·Ca2+−HCO3−. The hydrochemical evolution of groundwater in this area are mainly derived from rock weathering-dissolution. It is controlled by rocks of silicate and carbonate, with silicate playing a more significant role. Considering the geological background of this area, silicate mainly comes from volcanic, clastic, granitic, sandstone and mud stone. The BP neural network was used to train 5000 groups of groundwater samples, and the samples in the study area were evaluated. The training image of the model showed that the BP neural network could well fit the training set of groundwater samples and accurately judge the test set. The result of groundwater quality in this area indicates that Class I water quality points accounted for 13.3%, Class II water quality points accounted for 40%, Class III water quality points accounted for 46.6%. Its overall water quality is good, and the Class III water quality area needs to strengthen groundwater pollution source investigation as well as water quality protection.
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图 1 研究区水文地质图
γT3. 晚三叠世花岗岩类；Zk. 震旦系开建桥组； Zl. 震旦系列古六组；Zg. 震旦系观音崖组；Zd. 震旦系灯影组；Є1l. 下寒武统龙王庙组；Є2x. 中寒武统西王庙组；Є3e. 上寒武统二道水组；T3bg. 上三叠统白果湾组；J1y. 下侏罗统益门组；J2x. 中侏罗统新村组；J2n. 中侏罗统牛滚凼组；J3g. 晚侏罗统官沟组；K1f. 下白垩统飞天山组；K2x. 中白垩统小坝组；N2Qpx. 中新统—更新统昔格达组；Qapl. 全新统冲洪积物
Figure 1. Hydrogeological map of the study area
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图 3 研究区地下水水化学Piper图
Figure 3. Piper diagram of hydrochemical of groundwater in the study area
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图 6 研究区水化学离子与矿物风化作用关系图
Figure 6. Correlation of hydrochemical ions and mineral weathering
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图 7 BP神经网络结构图
Inputs. 输入层；Hidden1. 第一隐层；Hidden2. 第二隐层；Outputs：输出层；x1-18. 输入18个水质指标；Sigmoid. 激活函数；w1-3. 不同层的权重；b1-3. 不同层的偏置；Ⅰ-Ⅴ. 5种水质输出；Loss. 损失函数；Targets. 标签；Forward propagation. 正向传播；Backforward propagation. 反向传播
Figure 7. Neural network structure diagram
表 1 水样品概况统计表
Table 1 General situation of water samples
点号 类型 水体状况 位置 采集时间（日 时） 01-SY 井水 淡水 西昌市黄水乡新塘沟村大庆沟 8.24 9:38 02-SY 井水 淡水 西昌市黄水乡新塘沟村大庆沟 8.24 10:39 03-SY 井水 淡水 西昌市黄水乡洼垴村七组 8.24 11:35 04-SY 井水 淡水 德昌县阿月乡光辉村罗家坪子 8.24 12:33 05-SY 井水 淡水 德昌县阿月乡光辉村西番箐 8.24 13:15 06-SY 井水 淡水 西昌市黄水乡观音岩 8.24 14:45 07-SY 井水 淡水 西昌市黄水乡书夫村二组 8.24 15:15 08-SY 井水 淡水 西昌市中坝乡小浸沟 8.25 9:20 09-SY 井水 淡水 西昌市黄联关镇哈土村四组 8.25 10:25 10-SY 井水 淡水 西昌市西溪乡长板桥村 8.25 12:00 11-SY 井水 淡水 西昌市安哈镇摆摆顶村 8.25 13:21 12-SY 井水 淡水 西昌市安哈镇摆摆顶村 8.25 13:44 13-SY 井水 淡水 普格县五道菁乡黄草坪村五组 8.25 14:41 14-SY 井水 淡水 普格县特尔果乡甲甲沟村 8.25 15:24 15-SY 井水 淡水 普格县特补乡白庙子 8.25 16:35 
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表 2 地下水化学指标统计表（N=15）
Table 2 Index of groundwater chemistry
指标 最大值（μg/L） 最小值（μg/L） 平均值（μg/L） 标准差 指标 最大值（μg/L） 最小值（μg/L） 平均值（μg/L） 标准差 pH值 8.08 6.65 7.68 0.35 TDS 230.40 6.70 85.91 67.35 $ {\text{Na}}^{\text{+}} $ 6.57 0.25 3.96 1.98 As 2.58 1.77 2.13 0.27 $ {\text{NH}}_{\text{4}}^{\text{+}} $ 0.24 0.05 0.10 0.06 Sb 0.27 0.10 0.11 0.04 $ {\text{Al}}^{\text{3+}} $ 0.19 0.01 0.07 0.06 Hg 0.19 0.03 0.06 0.04 $ {\text{Fe}}^{\text{3+}} $ 0.10 0.03 0.04 0.02 Cr 5.85 0.10 1.92 1.91 $ {\text{F}}^{{-}} $ 0.30 0.01 0.10 0.10 Co 0.74 0.02 0.24 0.22 $ {\text{Cl}}^{{-}} $ 4.26 0.86 1.52 0.90 Cu 0.59 0.07 0.19 0.19 $ {\text{SO}}_{\text{4}}^{\text{2-}} $ 17.20 0.67 7.36 5.24 Pb 10.26 0.08 0.76 2.63 $ {\text{NO}}_{\text{3}}^{{-}} $ 10.19 0.02 2.39 3.15 Zn 1.84 0.43 0.85 0.34 $ {\text{K}}^{\text{+}} $ 1.30 0.66 0.92 0.17 Mn 6.33 0.11 1.91 1.95 $ {\text{Ca}}^{\text{2+}} $ 64.53 0.59 19.31 19.14 Ni 9.54 0.05 2.66 3.02 $ {\text{Mg}}^{\text{2+}} $ 26.55 0.12 6.57 6.77 Mo 3.25 0.05 0.73 1.02 $ {\text{HCO}}_{\text{3}}^{{-}} $ 268.40 12.00 92.92 81.41 总硬度 221.00 1.90 75.27 71.14
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表 3 研究区水质综合排名表
Table 3 Comprehensive ranking of water quality in the study area
排名 点号 类型 1 5-SY Ⅰ类 2 12-SY Ⅰ类 3 2-SY Ⅱ类 4 4-SY Ⅱ类 5 6-SY Ⅱ类 6 10-SY Ⅱ类 7 11-SY Ⅱ类 8 13-SY Ⅱ类 9 1-SY Ⅲ类 10 3-SY Ⅲ类 11 7-SY Ⅲ类 12 8-SY Ⅲ类 13 9-SY Ⅲ类 14 14-SY Ⅲ类 15 15-SY Ⅲ类
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