Analysis of the causes of karst water level recovery in Jinci spring basin

2015 ◽  
pp. 903-907
Author(s):  
Xiaoyan Hao ◽  
Hua Jin
Keyword(s):  
Water Level ◽  
Karst Water

Study on Prediction Model of Karstic Large Spring Water Level Dynamic Coupling Multiple Factors in Jinan

2015 ◽  
Vol 8 (1) ◽  
pp. 309-317 ◽  
Author(s):  
Xing Liting ◽  
Zhou Juan ◽  
Zhang Fengjuan ◽  
Wang Song ◽  
Dou Tongwen ◽  
...  
Keyword(s):  
Prediction Model ◽  
Water Level ◽  
Spring Water ◽  
Anthropogenic Factors ◽  
Karst Water ◽  
Multiple Factors ◽  
Factors Influencing ◽  
Heterogeneous Features ◽  
Dry Seasons ◽  
Natural Decay

In karst regions, due to the heterogeneous features of karst medium, the characteristics of the groundwater flow turn to be of high complexity. Researchers have been seeking proper forecasting methods for karst water dynamic for many years. This paper, taking the spring in Jinan as an example, using regression analysis, analyzed the factors influencing spring water dynamic, and quantitatively evaluated the influencing coefficients of spring water level concerning rainfall, exploitation and recharge as well as the natural decay coefficient of spring water in dry seasons. The prediction model coupling multiple factors was built by investigating natural and anthropogenic factors influencing groundwater level, which could be used for forecasting dynamic of spring water in Jinan. The calculated value of model was highly coincided with the observed value. In consideration of the characteristics of uneven precipitation in Jinan, the suitable zones and volume of artificial recharge were investigated finally, which could help to sustain the spewing of Jinan springs significantly.

scholarly journals Karst hydrogeology of Lamprechtsofen (Leoganger Steinberge, Salzburg)

2019 ◽  
Vol 112 (1) ◽  
pp. 50-61 ◽  
Author(s):  
Katharina Gröbner ◽  
Wolfgang Gadermayr ◽  
Giorgio Höfer-Öllinger ◽  
Harald Huemer ◽  
Christoph Spötl
Keyword(s):  
Electrical Conductivity ◽  
Water Temperature ◽  
Water Level ◽  
Stream Water ◽  
Tracer Tests ◽  
Karst Water ◽  
Stream Flows ◽  
Surface Precipitation ◽  
Mineralized Water ◽  
Show Cave

AbstractThe Leoganger Steinberge are a heavily karstified massif largely composed of Dachstein dolomite and limestone hosting the deepest through-trip cave in the world, Lamprechtsofen, whose frontal parts are developed as a show cave. Many parts of this 60 km-long and 1724 m-deep system are hydrologically active. 1.5 km behind the lower cave entrance Grüntopf stream and Kneippklamm stream merge to form the main cave stream. Another underground stream, Stainerhallen stream, flows through the eponymous hall of the show cave. Since 2007 water temperature, electrical conductivity and water level have been monitored in the Grüntopf and Kneippklamm stream. Water temperature and water level in the Stainerhallen and main cave stream have been measured since 2016.The long-term dataset (2013–2017) shows that the water temperature of the cave streams (Grüntopf stream: 3.7–5.2°C; Kneippklamm stream: 5.1–5.9°C) is largely invariant, but the electrical conductivity varies strongly (Grüntopf stream: 107–210 µS/cm; Kneippklamm stream: 131–248 µS/cm) in response to snowmelt and precipitation events. The event water of the Kneippklamm stream is characterized by a low electrical conductivity and is then followed by slightly warmer and higher mineralized water derived from the phreatic zone. This dual flow pattern also explains the asymmetrical changes of the water level during snowmelt: the fast event water flows directly through vadose pathways to the measurement site, whereas the hydraulic (phreatic) response is delayed. The Grüntopf stream reacts to precipitation and snowmelt events by changes in the karst-water table, which can be explained by a piston flow-model. The Kneippklamm stream reveals evidence of a lifter system.The altitude of the catchments was calculated using δ18O values of water samples from the underground streams and from surface precipitation. The Grüntopf stream shows the highest mean catchment (2280 m a.s.l.), which is in agreement with its daily fluctuations of the water level until August caused by long-lasting snowmelt. The Stainerhallen stream has the lowest catchment (average 1400 m a.s.l.). The catchments of the other two streams are at intermediate elevations (1770–1920 m a.s.l.). The integration of the catchment analyses and observations from tracer tests conducted in the 1970s showed that the latter reflected only one aspect of the karst water regime in this massif. During times of high recharge the water level rises, new flow paths are activated and the karst watershed shifts.

Long-term prediction of karst water recovery process based on two different approaches in a former mining area, Transdanubian Range, Hungary

2020 ◽  
Author(s):  
Kamilla Modrovits ◽  
András Csepregi ◽  
József Kovács
Keyword(s):  
Time Series ◽  
Water Level ◽  
Trend Analysis ◽  
Recovery Process ◽  
Karst Water ◽  
Deterministic Approach ◽  
Term Prediction ◽  
Transdanubian Range ◽  
Long Term Prediction

<p>The Transdanubian Range is located in the mid-western part of Hungary and contains Mesozoic, mainly Triassic formations with the total thickness of 1.5-2 km. From 1950 to 1990 coal and bauxite mining took place with different centres in this area, therefor large amount of karst water was extracted for preventative purpose. Thus, the water levels decreased from ten to more than a hundred of meters. Since the mining was stopped in the beginning of the 1990s, the natural recharge exceeded the amount of extraction and the recovery of the karst water began. Since then the system is on the way to return to its original – undisturbed – state. Because of the rising water level, economic and technical engineering problems have occurred, which requires the better understanding of the process.</p><p>Water level changes are often predicted with a deterministic approach using different modelling software (e.g. MODFLOW, FEFLOW, etc.). However, stochastic approaches (e.g. trend estimation), which have so far been little used in forecast of groundwater, can also be applied for certain hydrogeological problems. The aims of the research were (i) to find the most accurate trend function describing the recovery process (ii) in order to make a long-term prediction, (iii) and compare the results with the results deterministic modelling. For this purpose, decades of time series from 107 monitoring wells were investigated.</p><p>As a result of the research, it was identified that the karst water time series from the Transdanubian Range can be properly estimated (R<sup>2</sup> > 0.9 in the 82.24% of the cases) by growth and logistic curves, especially by the so-called Richards and “63%” ones. These curves gave the best fit in 57.95% of the cases based on the R<sup>2</sup> value obtained by fitting the 10 examined models. Both the deterministic approach modelling (MODFLOW) and the stochastic approach trend analysis are suitable for estimating and predicting the water level rise in the karst aquifer, but the results are slightly different. Modelling with the MODFLOW software can be affected by the accuracy of input parameters (infiltration, yield of springs, etc.) and the realness of the conceptual model. First and foremost, more and better-quality water level data series are needed for trend analysis, and based on our prior knowledge, it is essential to provide an accurate expected maximum water level (upper limit). The comparison of the two methods unveiled, that growth and logistic curves can also be successfully used in the prediction of groundwater levels. As a conclusion, the number of methods which may be used for such research can be expanded.</p><p>This research is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 810980.</p>

scholarly journals Karst Water Pressure’s Varying Rule and Its Response to Overlying Strata Movement in Coal Mine

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Jian Hao ◽  
Hua Bian ◽  
Anfa Chen ◽  
Jiahui Lin ◽  
Dongjing Xu
Keyword(s):  
Water Level ◽  
Water Column ◽  
Coal Mine ◽  
Simulation Experiment ◽  
Water Pressure ◽  
Water Inrush ◽  
Column Height ◽  
Karst Water ◽  
Working Face ◽  
Water Column Height

Karst water is widespread throughout China and is heavily influenced by complex geological conditions, and floor inrush of karst waters associated with coal seams is the second most common coal mine disaster in China. Due to the limitation of precision and cost of geophysical exploration technology, the volume and pressure of karst water are challenging to measure, especially during the mining process. Therefore, predicting karst pressure’s response to mining is critical for determining the mechanism of water inrush. Here, closed karst water pressure (CKWP) response to mining was studied in an innovative physical simulation experiment. In the simulation experiment, a capsule and a pipe were designed to reflect CKWP and the water level. In the experiment, the vertical stress and karst water level were monitored throughout the process of an advancing coal panel. Monitoring results show that the range of the abutment pressure was about 40 cm, and the peak coefficient value was about 2. When the working face is far away from the water capsule, the stress and water column near the water capsule have no obvious change. With the working face 10 cm from the water capsule, the stress and water column height increased significantly. When the working face was right above the water capsule, the stress and water column rose sharply and reached the maximum value. When the working face advanced beyond the water capsule, the stress and water column height declined. Through establishing a structural mechanics model, the karst water system underneath the working face is assumed to be a hydraulic press. Accordingly, the compressed area was assumed to be a piston. The karst water pressure increases sharply, while the piston is compressed, increasing water inrush risk. This discovery may help determine the water inrush mechanism from a novel point of view.

Hydrogeology of the Sterkfontein Cave System, Cradle of Humankind, South Africa

2017 ◽  
Vol 120 (3) ◽  
pp. 403-420
Author(s):  
P. Hobbs ◽  
N. de Meillon
Keyword(s):  
Water Resources ◽  
Water Level ◽  
Mine Water ◽  
World Heritage Site ◽  
Karst Water ◽  
Water Drainage ◽  
Cave System ◽  
Fossil Site ◽  
Cradle Of Humankind ◽  
The Impact

Abstract A water level rise of almost 3 m in the space of two years in the Sterkfontein Cave system since late-2009 necessitated the re-routing of the tourist path through the cave to successively higher elevations on three occasions. It also raised concern for a possible association with copious acidic and sulphate-rich mine water drainage from the West Rand Goldfield (a.k.a. Western Basin) starting in early-2010, and the related threat to the UNESCO-inscribed fossil site. Although these circumstances have had little impact on the tourist value of the site, a prognosis of the impact on cave water level and quality is indicated by virtue of its karst setting and palaeontological significance. Historical and recent potentiometric data, together with ancillary hydrogeological and hydrochemical information acquired in the course of a water resources monitoring programme for the broader Cradle of Humankind World Heritage Site, provides new insight into the hydrogeology of the cave system. An improved understanding of the hydrophysical and hydrochemical response of the cave water system sheds light on the location of this system within the water resources environment. It is proposed that the present-day maximum cave water level is constrained to an elevation of ~1440 m above mean sea level. The recent electrical conductivity of 78 mS/m for cave water is 32% greater than the 59 mS/m recorded in mid-2010 and earlier. Similarly, the recent sulphate concentration of 161 mg/L is 178% greater than the 58 mg/L recorded before 2010. Compared to coeval values for ambient karst groundwater represented by the normative Zwartkrans Spring water, the magnitude of the increases in the springwater are similar, viz. 48% (from 84 to 124 mS/m) in salinity and 166% (from 154 to 409 mg/L) in sulphate. Although a distinct mine water impact is evident in both instances, the values indicate a muted impact on the cave water chemistry compared to the springwater. These and other documented observations better inform the threat from various poorer quality water sources to the fossil site in particular, and to the broader karst water resource in general. This contextualises concern for the hydroenvironmental future of Sterkfontein Cave and other nearby fossil sites such as Swartkrans, Rising Star and Bolt’s Farm. The dynamic response of the water resources environment to a variety of hydrological and hydrogeological drivers reinforces the need for monitoring vigilance across a range of disciplines.

scholarly journals Identification and Estimation of Solute Storage and Release in Karst Water Systems, South China

2020 ◽  
Vol 17 (19) ◽  
pp. 7219
Author(s):  
Liang Zhang ◽  
Mingming Luo ◽  
Zhihua Chen
Keyword(s):  
Solute Transport ◽  
Water Level ◽  
Groundwater Remediation ◽  
Tracer Tests ◽  
Water Systems ◽  
Breakthrough Curves ◽  
Karst Water ◽  
Transport Pathways ◽  
Advection Dispersion ◽  
Storage Rate

Solute storage and release in groundwater are key processes in solute transport for groundwater remediation and protection. In karst areas where concentrated recharge conditions exist, pollution incidents can easily occur in springs that are hydraulically connected to densely inhabited karst depressions. The intrinsic heterogeneity common in karst media makes modeling solute transport very difficult with great uncertainty. Meanwhile, it is noteworthy that solute storage and release within subsurface conduits and fissures exhibit strong controlling function on pollutant attenuation during underground floods. Consequently, in this paper, we identified and estimated the solute storage and release processes in karst water systems under concentrated recharge conditions. The methodology uses the advection–dispersion method and field tracer tests to characterize solute transport in different flow paths. Two solute transport pathways were established (i.e., linear pathway (direct transport through karst conduits) and dynamic pathway (flow through fissures)). Advection–dispersion equations were used to fit the breakthrough curves in conduit flow, while the volume of solute storage in fissures were calculated by segmenting the best fitting curves from the total breakthrough curves. The results show that, greater recharge flow or stronger dynamic conditions leads to lower solute storage rate, with the storage rate values less than 10% at high water level conditions. In addition, longer residence time was recorded for solute exchange between conduits and fissures at the low water level condition, thereby contributing to a higher solute storage rate of 26% in the dynamic pathway.

scholarly journals Evaluating the Impaction of Coal Mining on Ordovician Karst Water through Statistical Methods

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1409 ◽  
Author(s):  
Dan Huang ◽  
Zaibin Liu ◽  
Wenke Wang
Keyword(s):  
Water Level ◽  
Coal Mining ◽  
Groundwater Level ◽  
Mine Drainage ◽  
Underground Water ◽  
Wavelet Coherence ◽  
Karst Water ◽  
Factors Affecting ◽  
Spring Flow ◽  
Underground Water Level

This study aims to reveal karst water trend change and the variation of affecting factors in the Heilongdong spring area due to long-term coal mining. In this study, five yearly recoded data over more than 40 years were collected, including underground water level dynamics, water flow, groundwater withdrawal for industrial and agricultural production and domestic production (groundwater withdrawal), mine drainage and rainfall. On that basis, we conducted linear regression, innovative trend analysis (ITA) and the Mann–Kendall method to quantitative analyze the trend and mutation sequence of the time series of environmental hydrological parameters in the study area. To determine the correlation of different affecting parameters under coal mining, as well as the trend of the correlation, we conducted multivariate linear regression analysis and exploited wavelet coherence. The results suggest: (1) under human influence, the annual value of underground water level in the Heilongdong spring area shows an insignificant decrease of 0.42 m/a; precipitation shows a significant downward trend of 2.34 mm/a, primarily the decrease of rainstorm; the spring flow shows a significant decrease of 9.41 × 106 m3/a, and springs with different flow show a significant decrease. (2) The abrupt changes of various factors affecting spring flow in the study area were successively delayed by rainfall, mine drainage rate, industrial and agricultural water consumption and underground water level. (3) Since the year of the start of dramatic changes, under the impact of increased manual mining and mine drainage, the amount of spring overflow has decreased, the groundwater level has decreased, and the groundwater dynamics have varied from meteorological type to meteorology-artificial type. Moreover, the factors affecting the dynamic changes of groundwater have been changed to rainfall and artificial mining and drainage. (4) As the results of Wavelet coherence analysis suggest, the spring flow resonates significantly with rainfall from the period of 3a to 15a. The correlation between the original spring flow and groundwater level is more obvious than that between the original spring flow and rainfall. The correlation between residual flow and groundwater level is less obvious than that between residual flow and rainfall. The above results provide a basis for comprehensively exploiting water resources in coal mining areas and regional groundwater resources protection measures.

scholarly journals Comparison of Various Growth Curve Models in Characterizing and Predicting Water Table Change after Intensive Mine Dewatering Is Discontinued in an East Central European Karstic Area

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1047
Author(s):  
Kamilla Modrovits ◽  
András Csepregi ◽  
Ilona Kovácsné Székely ◽  
István Gábor Hatvani ◽  
József Kovács
Keyword(s):  
Water Level ◽  
Water Table ◽  
Growth Curve ◽  
Water Resource Management ◽  
Water Levels ◽  
Water Level Fluctuations ◽  
Karst Water ◽  
East Central ◽  
Growth Curve Models ◽  
Deterministic Modelling

The modeling of karst water level fluctuations is a crucial task in the water resource management of vulnerable karstic areas. In the Transdanubian Range (East Central Europe, Hungary), from 1950 to 1990, coal and bauxite mining were carried out, with large amounts of karst water being extracted, thus lowering the water table by amounts ranging between 10 and 100 m. Since the cessation of mining activities in the early 1990s, the volume of natural recharge has exceeded the amount of dewatering, and the system has begun to return to its original undisturbed state. This apparently welcome development does, however, bring economic and technical engineering problems. The estimation and prediction of such water level changes is often tackled via the use of deterministic approaches, however, in the present case, it is also addressed with an alternative approach using trend estimation to monthly water level data from 107 karst water wells over the period 1990–2017. To approximate the change in karst water levels, (i) growth curve models were fitted to the monthly data, allowing the estimation of karst water levels, at least as far as 2030. Similarly, this was also done with (ii) deterministic modelling in order to describe the recovery process up to 2030. Specifically, measured and predicted values for karst water level were used to derive interpolated (kriged) maps to compare the forecasting power of the two approaches. Comparing the results of the trend analysis with those of the traditional deterministic modelling results, it is apparent that the two approaches predict similar spatial distribution of water levels, but slightly different future water level values.

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