Analysis on environmental hydrogeology in spring area
Zhang Guojian
(Henan Institute of Hydrogeology and Engineering Geology, Xinxiang, 4532)
Based on the analysis of a large number of predecessors' relevant data, this paper basically finds out the hydrogeological conditions of the spring area, determines the boundary and nature of the spring area through 1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[ ∶ 5, comprehensive hydrogeological survey, groundwater dynamic field survey, geophysical exploration, pumping test and water quality test.
key words: groundwater exploitation in Hongqiqu, a spring flow precipitation in Xiaonanhai spring area
Anyang City is located in the middle and upper part of Huan River alluvial fan in northern Henan Province, and is an important industrial city in northern Henan Province. At present, it has formed an industrial system with complete categories such as metallurgy, electric power, electronics, light industry, textiles and medicine. With the development of economy, the demand for water resources is increasing. Xiaonanhai Spring, as one of the main water supply sources in Anyang City, is supplied to Anyang Steel, power plant, fertilizer plant and other enterprises as well as Wanjin Irrigation District after being regulated by Zhangwu Reservoir. It is also the main planned water source for urban domestic water. Due to the serious phenomena of drilling wells, coal mining and mining in the spring area, the hydrogeological conditions have changed greatly, the vegetation has been destroyed, the ecological environment has deteriorated, and the spring water output has decreased year by year. In the 1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[97s, it was 8.3 m3/year. It was 5.62 m3/s in 1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[98s and 4.48 m3/s in 1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[99s. Before July 2, the weather continued to be dry, and the flow of Nanhai Spring was only 1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[.95m3/s, which caused serious water shortage in Anyang City and posed a serious threat to industrial and agricultural production in Anyang City.
1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[ Overview of regional hydrogeological conditions
Xiaonanhai Spring is located in the transition zone between Taihang Mountain uplift belt and North China Plain subsidence belt, starting from the Xishan fault in Linzhou in the west and the Tangxi fault in the east. The block sandwiched in the middle is a structural fault block that descends step by step from west to east. From west to east, it can be roughly divided into three relatively independent hydrogeological units; Taking the Xishan fault in Linzhou as the boundary, the west of the fault is a hydrogeological unit in the bedrock area composed of Archean metamorphic rocks and Sinian quartzite sandstone. On the east side of the hydrogeological unit in bedrock area is a karst hydrogeological unit composed of Cambrian and Ordovician carbonate rocks. This unit is partially exposed with intrusive diorite and covered with Cenozoic sediments in Linzhou basin and depression zone. With the contact between Ordovician and Carboniferous and Permian strata extending in the near north-south direction as the boundary, it is divided into clastic sedimentary hydrogeological units composed of conglomerate, sandstone, limestone, mudstone and shale in Carboniferous, Permian and Tertiary strata.
regional deep faults not only control the distribution of hydrogeological units, but also control the boundary of karst groundwater spring system, and divide karst groundwater system into several systems. For example, the Xishan fault in Linzhou is the junction of Cambrian and Ordovician in the east and Archaean in the west, which forms the water-resisting boundary of karst water and separates this karst water system from the karst water system in Xin 'an Spring Area in Changzhi, Shanxi. The fault bundle in the east of this work area is the joint of Ordovician in the west panel and Carboniferous and Permian in the east panel, which forms the water-blocking boundary in the east of karst water. The karst water from the west is blocked by sandstone and mudstone, and it is concentrated in the low-lying areas of the valley to discharge the strata to form karst springs. From south to north, the working area can be divided into four karst water subsystems, namely, Shimensi spring domain, Xujiagou spring domain and Pearl spring domain, and most springs are separated by groundwater watershed boundary, surface water watershed boundary and stratum water blocking boundary.
The investigation has determined that the area of Xiaonanhai spring area is 934.6km2, with intrusive rock water-resisting boundary in the north, stratum water-resisting boundary in the east, groundwater ridge boundary in the south and surface watershed (fault water-resisting boundary) in the west.
2 Analysis and determination of spring flow
Xiaonanhai spring water all flows into Zhangwu Reservoir for industrial production and agricultural irrigation of Anyang steel mills and power plants. According to the analysis and arrangement of existing data, the spring flow has a significant decreasing trend. These data are found according to the outflow of Nanhai Reservoir, the inflow of Zhangwu Reservoir and the relationship curve between reservoir water level and discharge, and the inflow is reduced and calculated according to the principle of water balance. Because it is difficult to accurately calculate the leakage in the reservoir area, When analyzing and sorting out the original data, it is also found that when the outflow of Zhangwu Reservoir is large, the calculation deviation of inflow is greater. Considering the above factors, the least square method is adopted to discard the abnormal values in the utilization of data, and the outflow and precipitation of the two reservoirs are compared daily. The inflow of Zhangwu Reservoir in the period when the outflow of the two reservoirs is relatively stable or there is no water discharge or rainfall is selected as the daily flow of spring water, and the average inflow value of Zhangwu Reservoir is taken as the monthly flow. Because there are many factors affecting the numerical value of flow, it is inevitable that there are differences between the calculated spring flow value and the actual value, but the overall change trend is consistent with the actual situation.
3 Analysis of factors affecting the spring flow
Through the comprehensive analysis of this survey and previous data, the main control factors affecting the spring flow are as follows.
3.1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[ Natural factors
3.1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[.1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[ Precipitation
The influence of precipitation on spring flow is mainly manifested in two aspects: one is to recharge the groundwater in the spring area by infiltration, and then collect it in Xiaonanhai spring group by underground runoff; Second, it is collected to Huan River through surface runoff, and replenished groundwater in spring area through leakage of flow.
because of the different interannual and internal changes of precipitation, the influence on the spring flow is also different. The interannual changes of precipitation, due to the regulation and storage of groundwater in the spring area, mainly affect the annual average change of Xiaonanhai Spring, and the changes of precipitation in the year lead to the differences of spring flow in the year.
3.1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[.2 Huan River
The length of Huan River passing through this area is about 5km, and the water leakage from Shuimoshi to Xiejiaping is serious. The water leakage from Huan River is the main recharge source of groundwater in Nanhai Spring. There are two sources of Huan river: one is descending water flow; The second is to receive the backwater from Hongqi Canal and continuously replenish the groundwater in the spring area. According to predecessors and the measured data of this survey, it is speculated that the leakage of Huan River is also the main factor of the flow of Nanhai Spring.
3.2 human factors
3.2.1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[ groundwater exploitation
with the development of social economy in the spring area, the amount of artificially exploited groundwater has increased year by year, especially after the 1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[99s, when the amount of artificially exploited groundwater has surged, it is bound to seize part of the spring flow. The South China Sea spring discharge presents three steps, and correspondingly, the artificial exploitation of groundwater also presents three steps. See Table 1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[ for specific data.
Table 1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[ Corresponding Table of Spring Flow and Artificial Groundwater Exploitation
Therefore, the current groundwater exploitation is the main controlling factor of spring flow, and the influence of groundwater exploitation on spring flow will be more and more serious from the development trend.
3.2.2 Red Flag Canal Water Diversion
Red Flag Canal draws turbid Zhangjiang River into Linzhou. On the one hand, it directly replenishes the groundwater in the spring area through canal leakage and canal irrigation infiltration; on the other hand, it retreats to Huan River, and indirectly replenishes the groundwater through river leakage. As can be seen from Table 2, among the three platforms of spring flow, the change trend of red flag canal water diversion is also obvious.
3.2.3 quarrying in the overflow area of the spring group will also have a certain impact on the overflow of the spring
4. Weight analysis of factors affecting the spring flow
4.1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[ Selection of factors affecting the spring flow
From the above analysis, it is not difficult to see that there are four main factors affecting the spring flow: precipitation, groundwater exploitation, water diversion of Hongqi Canal and leakage of Huan River. Among them, the leakage of Huan River is mainly caused by the runoff (flood) and the backwater of Hongqi Canal, and it is closely related to them. Relatively speaking, Huan River leakage is only an indirect influence factor, so precipitation, groundwater exploitation and water diversion of Hongqi Canal can be taken as the control factors affecting the spring flow.
4.2 selection of spring flow period
as can be clearly seen from table 1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[, the spring flow presents three steps, corresponding to three periods respectively, that is, before 1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[976, 1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[977-1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[989 and after 1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[99. In order to facilitate the following calculation, the data periods are selected as 1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[971,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[-1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[976, 1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[977-1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[989 and 1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[99. See Table 2 for the data of spring flow, precipitation, artificial exploitation of groundwater and water diversion of Hongqi Canal in each period.
table 2 data list of each time period
4.3 weight analysis of spring discharge influencing factors
the weight analysis of spring discharge influencing factors adopts grey system theory to carry out multivariate correlation analysis, which is a common problem in hydrogeological analysis, and its purpose is to find out the advantages and disadvantages of their correlation with factors from multiple factors. When studying the correlation between things, the grey system theory takes the past and present behavior effects of things (factors) as the basis of analysis, and excavates the regularity from it. In order to judge the main factors, the variable value of "correlation degree" is put forward to determine the weight of the influence of different times and different factors on the spring flow.
4.3.1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[ Method principle of correlation degree analysis
There are m sub-factors (X1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[,X2, ..., Xm) which have a certain correlation with the parent factor (X), and they all have at least n dynamic observation values in the same period, and their values are abbreviated as sequences.
mother sequence: {x (I)} I = 1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[,2, ..., n
subsequence: {xk (I)} k = 1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[,2, ..., m
i=1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[,2, ..., n
For comparison, they are standardized. If these polylines have a common * * * intersection (called reference point), the distance δ k (L) between the kth sub-line L and the bus at the same moment = {| x (L)-xk (L) |} is the basic basis for measuring their relevance at that moment. Obviously, the smaller δ k (L) is, the better the correlation between the sub-line and the bus at time L. The correlation of the sequence from time t=l to time t=n is expressed by the correlation coefficient:
Essays on Geological Environment and Economy. Series 2
ξk(i)—— the k-th sub-line and bus X. The correlation coefficient at time I satisfies ≤ξk≤1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[, and the closer ξk is to 1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[, the better their correlation is.
Δmin, Δmax—— the application data of the m-th sub-line in the interval
4.3.2
According to the existing data, there are three factors: the first factor is the water diversion of Hongqi Canal, the second factor is the groundwater exploitation in the spring area, and the third factor is the rainfall in the spring area.
let's set the matrix [xij]i=1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[,2,3,4
j=1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[,2, …, 1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[3
[xij]-the parent factor, the spring flow over the years;
[xki]-sub-factor, k=2 is the annual water intake of Hongqi Canal
k=3 is the annual groundwater exploitation in the spring area
k=4 is the annual rainfall in the spring area.
4.3.3 Calculation results
See Table 3 for the calculation results.
table 3 correlation coefficient table of each time period
note: X2—— water diversion quantity of hongqi canal, X3—— groundwater exploitation quantity, X4—— precipitation.
5 comprehensive analysis of the reasons for the decrease of spring discharge
From the weight analysis results of the above-mentioned spring discharge influencing factors, it can be seen that in the first and second periods, the size of spring discharge is closely related to its positive correlation factors, precipitation and water diversion of Hongqi Canal, and the negative correlation factor, artificial exploitation, only occupies a secondary position. Combined with Table 2, the reasons for the change of spring discharge in the second period are mainly the increase of artificial exploitation and the decrease of water diversion.
compared with the second period, the precipitation in the third period (1,n]的距离Δk（i）的最小值和最大值。
显然若参考点选在某时刻（1），则有Δmin=，其中令Δk（min）=min{|X（i）—Xk（i）|）
Δk（max）=max{|X（i）—Xk（i）|）
Δmin=min｛Δk（min）｝
Δmax=max｛Δk（max）｝
ξ——正实数，取经验数，其值大小影响各时刻[1,n]关联系数的序。本文取ξ＝.5，于是第k条子线与母线在[l,n]关联度记为Gk且 ∈[99 ~ 23) is not much different, but with the increase of artificial exploitation, the water diversion of Hongqi Canal has decreased significantly, but both of them have become the main influencing factors of spring flow during this period, so the decrease of spring flow is an inevitable consequence. In the mining amount, the influence of mine drainage on the reduction of spring water inflow is more obvious.
6 Conclusion
Based on the above analysis results, at present, the main reasons for the decrease of spring flow are the increase of artificial groundwater exploitation and the decrease of water diversion in Hongqi Canal. Recently, with the increase of artificial exploitation of underground water, it has become the main factor affecting the size of spring flow.