scholarly journals The influence of hydrogeological and anthropogenic variables on phthalate contamination in eogenetic karst groundwater systems

2018 ◽  
Vol 237 ◽  
pp. 298-307 ◽  
Author(s):  
Norma I. Torres ◽  
Xue Yu ◽  
Ingrid Y. Padilla ◽  
Raul E. Macchiavelli ◽  
Reza Ghasemizadeh ◽  
...  
Keyword(s):  
Karst Groundwater ◽  
Groundwater Systems

scholarly journals Method for Identifying and Estimating Karst Groundwater Runoff Components Based on the Frequency Distributions of Conductivity and Discharge

Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2494 ◽  
Author(s):  
Zejun Wang ◽  
Qianlong Chen ◽  
Ziqi Yan ◽  
Mingming Luo ◽  
Hong Zhou ◽  
...  
Keyword(s):  
Water Resources ◽  
Gaussian Mixture ◽  
Water Volume ◽  
Karst Water ◽  
Karst Groundwater ◽  
Frequency Distributions ◽  
Groundwater Runoff ◽  
Karst Water Resources ◽  
Groundwater Systems ◽  
Fast Flow

Identification and estimation of groundwater runoff components in karst groundwater systems to improve understanding of karst water circulation and water-rock interactions is essential for water resources assessment and development. A Gaussian mixture model is presented for identifying and estimating karst groundwater runoff components based on the frequency distributions of conductivity and discharge. Successful application of this method in the Heilongquan karst spring in South China showed that groundwater runoff components can be divided into 6–8 grades, corresponding to the grades of groundwater in karst fissures. The conductivity and discharge thresholds dividing fast and slow flow were determined to be approximately 300 μS cm−1 and 0.3 m3 s−1, respectively, with fast flow exhibiting lower conductivity and larger discharge. On an annual basis, fast flow occurred 9% of the time and accounted for 35% of total water volume. The results of the method compared favorably to that of hydrograph recession analysis. Estimation of groundwater runoff components based on frequency distributions of conductivity and discharge provides a novel alternative method for the quantitative evaluation of karst water resources.

Prediction of Karst Groundwater Level Based on R-Language - Taking Jinci Spring Basin as an Example

2015 ◽  
Vol 730 ◽  
pp. 230-234 ◽  
Author(s):  
Hui Jun Shi ◽  
Xin Qi ◽  
Hua Jin
Keyword(s):  
Groundwater Level ◽  
Multiple Linear Regression Model ◽  
Karst Groundwater ◽  
Groundwater Levels ◽  
R Language ◽  
Study Results ◽  
Groundwater Systems ◽  
Annual Time ◽  
Groundwater Level Prediction

Considering the complexity and randomness of the karst groundwater systems, a multiple linear regression model was developed for groundwater-level prediction based on the R language. The Jinci Spring basin was taken as a case study. Results show that the established model can predict the dynamics of the karst groundwater levels with high accuracy at an annual time scale, which can be served for macroscopic groundwater management.

scholarly journals Microplastic Contamination in Karst Groundwater Systems

Ground Water ◽  
2019 ◽  
Vol 57 (2) ◽  
pp. 189-196 ◽  
Author(s):  
Samuel V. Panno ◽  
Walton R. Kelly ◽  
John Scott ◽  
Wei Zheng ◽  
Rachel E. McNeish ◽  
...  
Keyword(s):  
Karst Groundwater ◽  
Groundwater Systems

scholarly journals Temporal Variations of Water Chemistry in the Wet Season in a Typical Urban Karst Groundwater System in Southwest China

2020 ◽  
Vol 17 (7) ◽  
pp. 2520 ◽  
Author(s):  
Min Xiao ◽  
Zenglei Han ◽  
Sen Xu ◽  
Zhongliang Wang
Keyword(s):  
Water Quality ◽  
Water Chemistry ◽  
Dissolved Inorganic Carbon ◽  
Major Ions ◽  
Temporal Variations ◽  
Karst Groundwater ◽  
Soil Co2 ◽  
Rainfall Events ◽  
Anthropogenic Inputs ◽  
Groundwater Systems

It is important to investigate temporal variations of water chemistry for the purpose of improving water quality in karst groundwater systems. Groundwater samples were collected daily under various land uses of Guiyang. Major ions and stable carbon isotope composition of dissolved inorganic carbon (δ13CDIC) were analyzed to understand the biogeochemical processes. The water chemistry was dominated by Ca2+, Mg2+, HCO3-, and SO42-, which mainly derived from the dissolution of carbonate rocks (limestone and dolomite) and oxidation of sulfide. The groundwater was defined as of the HCO3-Ca Mg and HCO3·SO4-Ca·Mg type, according to its hydrochemical characteristics. Results suggested that hydrochemical concentrations changed quickly, in response to rainfall events. The fast response revealed that karst groundwater was easily impacted by rainfall and anthropogenic inputs according to temporal variation of water chemistry. The distribution of DIC (dissolved inorganic carbon) and δ13CDIC showed that DIC is mainly sourced from soil CO2(g) influx and carbonate dissolution. δ13CDIC and major ions ratios suggested that carbonate minerals were dissolved by H2SO4 at groundwater in wooded area, contributing an important source for DIC due to the slight enrichment of heavy δ13CDIC. More negative δ13CDIC values were observed after rainfall reflected the fact that soil CO2(g) and organic carbon oxidation influxes accounted for a large share during DIC formation. Various δ13CDIC and hydrochemical patterns were observed under various land use and human activity conditions. Meanwhile, relative high nitrate loads were found in groundwater after rainfall, suggesting high anthropogenic inputs following rainwater as having side effects on water quality. This study suggests that water chemistry and isotopic proof provide a better understanding of water quality and carbon dynamics responding to rainfall events in the karst groundwater systems.

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