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Volume 41 Issue 4
Aug.  2022
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Article Navigation >  CARSOLOGICA SINICA  > 2022  >  41(4): 542-552
GAO Yu, ZHANG Hua, KANG Xiaoli, ZHOU Junrong, WU Hongmei, LIU Haifeng, YE Xian. Trend analysis of groundwater quality in major basins of Yunnan Province[J]. CARSOLOGICA SINICA, 2022, 41(4): 542-552. doi: 10.11932/karst20220404
Citation: GAO Yu, ZHANG Hua, KANG Xiaoli, ZHOU Junrong, WU Hongmei, LIU Haifeng, YE Xian. Trend analysis of groundwater quality in major basins of Yunnan Province[J]. CARSOLOGICA SINICA, 2022, 41(4): 542-552. doi: 10.11932/karst20220404
shu

Trend analysis of groundwater quality in major basins of Yunnan Province

doi: 10.11932/karst20220404
  • 1.

    Key Laboratory of Geohazard Forecast and Geoecological Restoration in Plateau Mountainous Area Plateau mountains, MNR/Yunnan Institute of Geo-Environment Monitoring, Kunming, Yunnan 650216, China

  • 2.

    Yunnan Key Laboratory of Digital Communications, Yunnan Communications Planning and Design Institute, Kunming, Yunnan 650041, China

  • Received Date: 2022-03-10
    Abstract
  • The plateau intermountain basin in Yunnan Province is an important water source gathering area, a population gathering and economic activity center, as well as an environmental hydrogeological unit with index significance of the impact and change of water environment. This article reviews the general monitoring situation of groundwater quality in the main intermountain basins of Yunnan Province. Among nearly 50 basins with an area of more than 100 square kilometers each, 7 have been laid out groundwater monitoring sites, respectively in Kunming, Yuxi, Dali, Chuxiong, Qujing, Jinghong and Kaiyuan. On the basis of dynamic monitoring data for groundwater quality in these basins from 2016 to 2021, the quality of pore water, fissure water and karst water is evaluated. Besides, the groundwater chemical characteristics are analyzed and the change trend of water quality in Yunnan are predicted with data statistics, Piper trilinear diagrams and time series analyses of wavelet neural network. The simulation results of wavelet neural network show that nitrate ion concentration in Hole 152 of Kunming basin increased in a short term, but then slowed down and leveled off. The concentration of manganese ion in Hole 101 of Chuxiong showed an increasing trend, while the concentration of ammonium ion showed a gradual but continual increase in the recent 1 or 2 years after an initial decrease reached the bottom. The high fitting accuracy of wavelet neural network and the average percentage error (less than 10%) demonstrated a satisfactory prediction, which may provide reference for groundwater treatment, protection and prediction, and the building of an early warning platform.It is found that the chemical types of groundwater are complex and diverse, mainly HCO3-Ca·Mg and HCO3-Ca. The content of ammonia nitrogen, manganese, fluoride and nitrate ion exceeds permitted levels, which may mainly indicate the exceedance of an acceptable level of groundwater quality. Over the past six years, the rates of exceeding permitted levels of pore water quality remained stable at about 70%. The components exceeding permitted levels were mainly pH value, total hardness, iodine ion, nitrate, ammonia nitrogen, etc. As for fissure water quality, its rates of exceeding permitted levels were basically unchanged, but the proportion of Class V water was on the rise, mainly in Kunming, Chuxiong and Yuxi. During 2017 and 2019, the rates of exceeding permitted levels were relatively low, but the fissure water quality was deteriorating. The components exceeding permitted levels were mainly manganese ions, pH values, fluorides, etc. The rates of exceeding permitted levels in terms of karst water quality gradually decreased, and in dry season the rate for Class II and Class III water decreased from 23.91% to 15.22%. Components were mainly manganese ions, arsenic ions, ammonia nitrogen, etc. Different indicators show different pollution causes. Pore water may be polluted with infiltration and recharge brought by atmospheric precipitation in pore aquifer. It may also be polluted when laterally recharged by surface water and by agricultural irrigation. Consequently, the deterioration of pore water is closely connected with the discharge of urban domestic sewage, industrial “three wastes” emissions, the use of chemical fertilizer and pesticide, agricultural irrigation and others. Compared with pore water, fissure water was less affected by pollution. Its pollution was mainly caused by the high background values of red beds and metamorphic rocks. Karst water may pollute karst aquifers through low-lying karst fissures, sinkholes and groundwater drainage. According to the statistical results, the water quality in the main basins of Yunnan Plateau shows a stable trend on the whole, which can provide a scientific basis for local economic and social development, territorial space planning, and rational exploitation and effective protection of groundwater resources.

     

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