An attribute recognition model based on entropy weight for evaluating the quality of groundwater sources

In our study, entropy weight coefficients, based on Shannon entropy, were determined for an attribute recognition model to model the quality of groundwater sources. The model follows the theory previously proposed by Chen Q S. In the model, firstly, the author establishes the attribute space matrix and determines the weight based on Shannon entropy theory; secondly, calculates attribute measure; thirdly, evaluates that with confidence criterion and score criterion; finally, an application example is given. The results show that the water quality of the groundwater sources for the city comes up to the grade II or III standard. There is no pollution that obviously exceeds the standard and the water can meet people’s needs .The results from an evaluation of this model are in basic agreement with the observed situation and with a set pair analysis (SPA) model.

Variation characteristics of aquifer parameters induced by groundwater source heat pump operation under variable flow

The variation characteristics of aquifer parameters,induced by groundwater source heat pump(GWSHP) operation under variable flow,were theoretically analyzed through a case study,in which the characteristics of building air conditioning load were considered.The results,compared with the constant flow operation,indicate that the influence on the variations of porosity,hydraulic conductivity and confined water head is decreased by 48%,51% and 71%,respectively,under variable flow operation.The security of variable flow operation is superior to that of constant flow.It is also concluded that the climate region and function of the buildings are primary factors which affect the suitability of variable flow operation in GWSHP.

Assessment of Groundwater Source of Piedmont Plain Area of China Northwest Arid Region Based On Numerical Modeling

After the middle of 1960s,along with the appearance and extensive utilization of computer featured in large capacity and rapid speed,numerical method(mainly include finite difference method and finite element

Dynamic assessment of pollution risk of groundwater source area in Northern China

Based on the dynamic analysis and research of pollution risk of groundwater sources, this paper creates the dynamic assessment method of pollution risk of groundwater source area under the theory of "source-pathway-receptor", and applies this method to one typical fissure karst groundwater source area in northern China. Following the 30-year petroleum pollutant migration simulation and pollution risk assessment of groundwater source area, this study finds that the very high risk zone is mainly located in Q Petrochemical Company and the surrounding area and the area adjacent to River Z. Within this period of thirty years, the pollution risk of groundwater source area has showed a dynamic trend that features an inverted "V" shape. The ratio of very high risk zone to the total area will be 18.1%, 17.47% and 16.62% during the tenth year, the twentieth year and the thirtieth year separately, and will reach the highest level of 19.45% during the fifteenth year. Meanwhile, the vertical migration distance of pollutant centre concentration changed from the surface soil at the outset to the deepest point of about 250 meters underground during the tenth year. The results of this risk assessment indicate the dynamic feature of pollution risk. The dilution, degradation and migration of petroleum pollutants in groundwater system contribute to an ultimate decline in pollution risk.

Water Quality Evaluation and Analysis on the Causes of Pollution for Groundwater Sources in Yantai, China

Based on the investigation for the 14 groundwater sources, the water quality of the groundwater sources had been analyzed, using the evaluation method of the combination of inorganic and organic index instead of the traditional method which was only based on inorganic index. The results showed that the quality of 12 groundwater sources satisfied class III standard of groundwater quality and other two exceeded class III standard. There were one groundwater source, whose water quality reached class 1 standard, and five groundwater sources, whose water quality reached class II standard. There were seven groundwater sources, in which the fluorine, an organic pollutant, was detected. The results showed that the groundwater resources in Yantai City were less polluted and the main pollutant in groundwater was nitrate. According to the analytical data and the environmental conditions of groundwater sources, the conclusion was drawn that the agriculture and rural non-point pollution were the main reasons of groundwater pollution.

Optimization model analysis of centralized groundwater source heat pump system in heating season

The ground-water heat-pump system （GWHP） provides a high efficient way for heating and cooling while consuming a little electrical energy. Due to the lack of scientific guidance for operating control strategy, the coefficient of performance （COP） of the system and units are still very low. In this paper, the running strategy of GWHP was studied. First, the groundwater thermal transfer calculation under slow heat transfixion and transient heat transfixion was established by calculating the heat transfer simulation software Flow Heat and using correction factor. Next, heating parameters were calculated based on the building heat load and the terminal equipment characteristic equation. Then, the energy consumption calculation model for units and pumps were established, based on which the optimization method and constraints were established. Finally, a field test on a GWHP system in Beijing was conducted and the model was applied. The new system operation optimization idea for taking every part of the GWHP into account that put forward in this paper has an important guiding significance to the actual operation of underground water source heat pump.

Integrated Sequential Groundwater Contaminant Source Characterization and Pareto-Optimal Monitoring Network Design Application for a Contaminated Aquifer Site

Accurate and reliable groundwater contaminant source characterization with limited contaminant concentration monitoring measurement data remains a challenging problem. This study presents an illustrative application of developed methodologies to a real-life contaminated aquifer. The source characterization and optimal monitoring network design methodologies are used sequentially for a contaminated aquifer site located in New South Wales, Australia. Performance of the integrated optimal source characterization methodology combining linked simulation-optimization, fractal singularity mapping technique (FSMT) and Pareto optimal solutions is evaluated. This study presents an integrated application of optimal source characterization with spatiotemporal concentration measurement data obtained from sequentially designed monitoring networks. The proposed sequential source characterization and monitoring network design methodology shows efficiency in identifying the unknown source characteristics. The designed monitoring network achieves comparable efficiency and accuracy utilizing much smaller number of monitoring locations as compared to a more ideal scenario where concentration measurements from a very large number of widespread monitoring wells are available. The proposed methodology is potentially useful for efficient characterization of unknown contaminant sources in a complex contaminated aquifer site, where very little initial concentration measurement data are available. The illustrative application of the methodology to a real-life contaminated aquifer site demonstrates the capability and efficiency of the proposed methodology.

Identification of Unknown Groundwater Pollution Sources and Determination of Optimal Well Locations Using ANN-GA Based Simulation-Optimization Model

The linked simulation-optimization model can be used for solving a complex groundwater pollution source identification problem. Advanced simulators have been developed and successfully linked with numerous optimization algorithms for identification of groundwater pollution sources. However, the identification of pollution sources in a groundwater aquifer using linked simulation-optimization model has proven to be computationally expensive. To overcome this computational burden, an approximate simulator, the artificial neural network (ANN) model can be used as a surrogate model to replace the complex time-consuming numerical simulation model. However, for large-scale aquifer system, the performance of the ANN-based surrogate model is not satisfactory when a single ANN model is used to predict the concentration at different observation locations. In such a situation, the model efficiency can be enhanced by developing separate ANN model for each of the observation locations. The number of ANN models is equal to the number of observation wells in the aquifer. As a result, the complexity of the ANN-based simulation-optimization model will be related to the number of observation wells. Thus, this study used a modified formulation to find out the optimal numbers of observation wells which will eventually reduce the computational time of the model. The performance of the ANN-based simulation-optimization model is evaluated by identifying the groundwater pollutant sources of a hypothetical study area. The limited evaluation shows that the model has the potential for field application.

The Source of Groundwater Recharge Based on Entropy Theory in the Arid Areas of North China

Objective Any natural system is constantly exchanging material, energy and information with the environment, and all tkese processes follow the basic law of thermodynamics, with no exception of groundwater recharge and discharge process. On the basis of the principle of the first law of thermodynamics, the reverse geochemical simulation method is widely used in the study of groundwater recharge, runoff and drainage process. However, some studies only consider the material conservation in theprocess, but ignore the probability of the transformation.

Refining aquifer heterogeneity and understanding groundwater recharge sources in an intensively exploited agrarian dominated region of the Ganga Plain

Densely populated region of Ganga Plain is facing aquifer vulnerability through waterborne pollutants and groundwater stress due to indiscriminate abstraction,causing environmental and socio-economic instabilities.To address long-term groundwater resilience,it is crucial to understand aquifer heterogeneity and connectivity,groundwater recharge sources,effects of groundwater abstraction etc.In this con-text,present study aims to understand factors responsible for vertical and spatial variability of groundwater chemistry and to identify groundwater recharge sources in an intensively exploited agrarian region of the Ganga Plain.Interpretation of chemometric,statistical,and isotopic analysis categorises the alluvial aquifer into zone 1(G1;ground surface to 100 m)and zone 2(G2;>100 m-210 m).The group G1 samples are characterized by a wide variation in hydrochemical species,noted with pockets of F-and NO3-rich groundwater,and fresh to more evolved water types,while group G2 groundwater is characterized by a sharp increase in freshwater types and limited variation in their isotopic and hydrochemical species.The G1 groundwater chemistry is governed by soil mineralogy,local anthropogenic inputs(SO42-,Cl-,and NO3-),and manifested by multiple recharge sources(local precipitation,river,canal water,pond).The G2 group is dominated by geogenic processes and mainly recharged by the local precipitation.Geospatial signatures confirm more evolved water type for group G1 in northwestern region,while fresh-water type covers the rest of the study area.Fluoride rich groundwater is attributed to sodic water under alkaline conditions and enrichedδ18O values emphasizing role of evaporation in F-mobilization from micas and amphiboles abundant in the soil.The findings provide insight into potential groundwater vulnerability towards inorganic contaminants,and ground water recharge sources.The outcome of this study will help to develop aquifer resilience towards indiscriminate groundwater extraction for agricultural practices and aim towards sustainable management strategies in a similar hydrogeological setting.

Groundwater contaminant source identification considering unknown boundary condition based on an automated machine learning surrogate

Groundwater contamination source identification(GCSI)is a prerequisite for contamination risk evaluation and efficient groundwater contamination remediation programs.The boundary condition generally is set as known variables in previous GCSI studies.However,in many practical cases,the boundary condition is complicated and cannot be estimated accurately in advance.Setting the boundary condition as known variables may seriously deviate from the actual situation and lead to distorted identification results.And the results of GCSI are affected by multiple factors,including contaminant source information,model parameters,boundary condition,etc.Therefore,if the boundary condition is not estimated accurately,other factors will also be estimated inaccurately.This study focuses on the unknown boundary condition and proposed to identify three types of unknown variables(contaminant source information,model parameters and boundary condition)innovatively.When simulation-optimization(S-O)method is applied to GCSI,the huge computational load is usually reduced by building surrogate models.However,when building surrogate models,the researchers need to select the models and optimize the hyperparameters to make the model powerful,which can be a lengthy process.The automated machine learning(AutoML)method was used to build surrogate model,which automates the model selection and hyperparameter optimization in machine learning engineering,largely reducing human operations and saving time.The accuracy of AutoML surrogate model is compared with the surrogate model used in eXtreme Gradient Boosting method(XGBoost),random forest method(RF),extra trees regressor method(ETR)and elasticnet method(EN)respectively,which are automatically selected in AutoML engineering.The results show that the surrogate model constructed by AutoML method has the best accuracy compared with the other four methods.This study provides reliable and strong support for GCSI.

Petroleum Pollution of Groundwater in Zibo and Its Prevention Measures

The source of ground water supply in Dawu is an extremely huge one in Shandong province. Now it is faced with serious pollution of petroleum in Hougao area. Aiming at this problem, the petroleum pollution in aeration zone and in groundwater was analyzed. The result shows that the contaminant of groundwater comes from the leaching of petroleum in the soil horizon of aeration zone through precipitation, and the quick flow of groundwater makes the convection dominate themigration of contaminant. So movement of groundwater controls the distribution of petroleum contaminant, which is consistent with the direction of ground flow. Building a groundwater closure zone in Hougao is an effective method to stop the contaminated groundwater flowing toward the water supply source of Dawu. The petroleum contaminant can be effectively reduced through using the aeration, biological and oxidation technologies.