首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献，搜索用时 359 毫秒
1.
Accurate identification of vulnerability areas is critical for groundwater resources protection and management. The present study employed the modified DRASTIC model to assess the groundwater vulnerability of Jianghan Plain, a major farming area in central China. DRASTICL model was developed by incorporating the land use factor to the original model. The ratings and weightings of the selected parameters were optimized by analytic hierarchy process (AHP) method and genetic algorithms (GAs) method, respectively. A combined AHP–GAs method was proposed to further develop this methodology. The unity-based normalization process was employed to categorize the vulnerability maps into four types, such as very high (>0.75), high (0.5–0.75), low (0.25–0.5), and very low (<0.25). The accuracy of vulnerability mapping was validated by Pearson’s correlation coefficient between vulnerability index and the nitrate concentration in groundwater and analysis of variance F statistic. The results revealed that the modified DRASTIC model had a large improvement over the conventional model. The correlation coefficient increased significantly from 41.07 to 75.31% after modification. Sensitivity analysis indicated that the depth to groundwater with 39.28% of mean effective weight was the most critical factor affecting the groundwater vulnerability. The developed vulnerability model proposed in this study could provide important objective information for groundwater and environmental management at local level and innovation for international researchers.  相似文献   

2.
A reliable prediction of dispersion coefficient can provide valuable information for environmental scientists and river engineers as well. The main objective of this study is to apply intelligence techniques for predicting longitudinal dispersion coefficient in rivers. In this regard, artificial neural network (ANN) models were developed. Four different metaheuristic algorithms including genetic algorithm (GA), imperialist competitive algorithm (ICA), bee algorithm (BA) and cuckoo search (CS) algorithm were employed to train the ANN models. The results obtained through the optimization algorithms were compared with the Levenberg–Marquardt (LM) algorithm (conventional algorithm for training ANN). Overall, a relatively high correlation between measured and predicted values of dispersion coefficient was observed when the ANN models trained with the optimization algorithms. This study demonstrates that the metaheuristic algorithms can be successfully applied to make an improvement on the performance of the conventional ANN models. Also, the CS, ICA and BA algorithms remarkably outperform the GA and LM algorithms to train the ANN model. The results show superiority of the performance of the proposed model over the previous equations in terms of DR, R 2 and RMSE.  相似文献   

3.
在传统遗传算法和模拟谐振子算法的基础上,结合两者的优点,提出了一种新型快速高效的谐振子遗传算法。通过一个理想的水资源管理模型的算例和一个华北平原典型区地下水资源优化的实际算例,从寻优结果和寻优效率两个方面对谐振子遗传算法、传统遗传算法和模拟谐振子算法进行了对比分析。在两个地下水管理模型中,与传统的遗传算法和模拟谐振子算法相比,新型的谐振子遗传算法搜索效率达到模拟谐振子算法搜索效率的2倍以上,得到的最优解比遗传算法所得到的最优解分别增加供水量1.1×103 m3/d和0.47×108 m3/a,说明谐振子遗传算法具有更强的全局搜索能力和更好的寻优效率。  相似文献   

4.
Groundwater contamination from intensive fertilizer application affects conservation areas in a plain. The DRASTIC model can be applied in the evaluation of groundwater vulnerability to such pollution. The main purpose of using the DRASTIC model is to map groundwater susceptibility to pollution in different areas. However, this method has been used in various areas without modification, thereby disregarding the effects of pollution types and their characteristics. Thus, this technique must be standardized and be approved for applications in aquifers and particular types of pollution. In this study, the potential for the more accurate assessment of vulnerability to pollution is achieved by correcting the rates of the DRASTIC parameters. The new rates were calculated by identifying the relationships among the parameters with respect to the nitrate concentration in groundwater. The methodology was implemented in the Kerman plain in the southeastern region of Iran. The nitrate concentration in water from underground wells was tested and analyzed in 27 different locations. The measured nitrate concentrations were used to associate and correlate the pollution in the aquifer to the DRASTIC index. The Wilcoxon rank-sum nonparametric statistical test was applied to determine the relationship between the index and the measured pollution in Kerman plain. Also, the weights of the DRASTIC parameters were modified through the sensitivity analysis. Subsequently, the rates and weights were computed. The results of the study revealed that the modified DRASTIC model performs more efficiently than the traditional method for nonpoint source pollution, particularly in agricultural areas. The regression coefficients showed that the relationship between the vulnerability index and the nitrate concentration was 82 % after modification and 44 % before modification. This comparison indicated that the results of the modified DRASTIC of this region are better than those of the original method.  相似文献   

5.
Groundwater vulnerability modeling is an alternative approach to evaluate groundwater contamination especially in areas affected by intensive anthropogenic activities. However, the DRASTIC model as a well-known method to assess groundwater vulnerability suffers from the inherent uncertainty associated with its seven essential parameters. In this study, three different fuzzy logic (FL) models (Sugeno fuzzy logic, Mamdani fuzzy logic, and Larsen fuzzy logic) are adopted to improve the DRASTIC system to be more realistic. The vulnerability map of groundwater from multiple aquifer systems (i.e., karstic, alluvium, and complex) in Basara basin, Iraq, was created using the FL models. Validation of the FL models results using NO3-N concentration obtained from wells and springs of the study area indicating that all of the three FL models are applicable for improving the DRASTIC model. However, each of the FL models has its own advantages for groundwater vulnerability estimation in different types of aquifer systems in the Basara basin. Therefore, this study proposes the supervised committee fuzzy logic (SCFL) as a multimodel method to combine the advantages of individual FL models. The SCFL method confirms that no water well with high NO3-N levels would be classified as low risk and vice versa. The study suggests that this approach has provided a convenient estimation of pollution risk in the study area and therefore, a more accurate prediction of the intrinsic vulnerability to pollution in the multiple aquifer system can be achieved through SCFL method.  相似文献   

6.
The existing different human activities and planned land uses put the groundwater resources in Jordan at considerable risk. There are evidences suggesting that the quality of groundwater supplies in north Jordan is under threat from a wide variety of point and non-point sources including agricultural, domestic, and industrial. Vulnerability maps are designed to show areas of greatest potential for groundwater contamination on the basis of hydrogeological conditions and human impacts. DRASTIC method incorporates the major geological and hydrogeological factors that affect and control groundwater movement: depth to groundwater (D), net recharge (R), lithology of the aquifer (A), soil texture (S), topography (T), lithology of vadose zone (I), and hydraulic conductivity (C). The main goal of this study is to produce vulnerability maps of groundwater resources in the Yarmouk River basin by applying the DRASTIC method to determine areas where groundwater protection or monitoring is critical. ArcGIS 9.2 was used to create the groundwater vulnerability maps by overlaying the available hydrogeological data. The resulting vulnerability maps were then integrated with lineament and land use maps as additional parameters in the DRASTIC model to assess more accurately the potential risk of groundwater to pollution. The general DRASTIC index indicates that the potential for polluting groundwater is low in the whole basin, whereas the resulting pesticide DRASTIC vulnerability map indicates that about 31% of the basin is classified as having moderate vulnerability, which may be attributed to agricultural activities in the area. Although high nitrate concentrations were found in areas of moderate vulnerability, DRASTIC method did not depict accurately the nitrate distribution in the area.  相似文献   

7.
During the last 25 years, rapid and unplanned land reclamation activity has been carried out in the areas located in both south and east of Wadi El - Natrun Depression of Egypt. Accordingly, negative effects on groundwater levels and vulnerability are frequently caused by localized high levels of abstraction and the return-flow of polluted irrigation water respectively. A groundwater model is a computational method that presents an approximation of an underground water system. In this study the groundwater system is simulated both in quantity and quality by using Mass Balance Transfer Model (NETPATH), Groundwater Modeling System (GMS) and DRASTIC Model to investigate the water - rock interactions, groundwater levels drawdown and vulnerability respectively. Three main geochemical processes namely dedolomitisation, dissolution of halite and silicate weathering were estimated during the flow path. The present over-abstraction of groundwater (105.84 million m3/year) has induced a general head drawdown from 3 to 40 m in years 2015 and 2050 respectively. Best estimate using a 3D GMS hydraulic model was (157000 m3/day) a strategy proposed for the management of groundwater without critical depletion (second scenario). The results document the extent to which a high drawdown can greatly reach 4 m by the end of simulation year 2050. The vulnerability maps of groundwater were constructed using the DRASTIC index method. The results indicated that, the southeastern and central portions of the study area are having high vulnerability rate (> 110). Modified DRASTIC map showed many more dominant high risk areas in the eastern parts of the study area that were low risk, which may be attributed to return flow of polluted irrigation water.  相似文献   

8.
When used in a comprehensive risk assessment framework, aquifer vulnerability maps are a tool to identify the relative susceptibility of the groundwater from sources of contamination at the land surface. The DRASTIC method was designed for use over large areas with a wide variety of geological and hydrogeologic settings as a screening tool in groundwater protection and management. In this study, a series of vulnerability maps were made for the Greater Oliver area, in south central Okanagan, British Columbia, Canada, to test the sensitivity of the methodology to changes in input data type, interpretation, and mapping approaches. The study also illustrates how DRASTIC can be modified for use in areas of limited geological variability, where it may be important for smaller-scale changes in vulnerability to be recognized. Maps were produced using the original DRASTIC rating tables, a set of expanded tables using the original properties but modified ranges to accommodate the variability of data in the valley bottom region, and alternate tables, with modified properties and ranges. Differences in vulnerability rating for the maps using selected combinations and data interpretations are compared to the map using original DRASTIC rating tables using visual and statistical methods. One map was generated using expert hydrological knowledge. The modified tables allowed a greater amount of variability to be expressed in the valley bottom area compared to using the original tables and methods, and could provide a reasonable approach for assessing local scale variability for source water protection planning.  相似文献   

9.
Three vulnerability index models were applied to assess the pollution potential of Nabeul-Hammamet shallow aquifer, Tunisia: DRASTIC, Pesticide DRASTIC and the Susceptibility Index (SI). An output map layer of each one was obtained using a geographic information system (GIS). The SI layer was overlain with DRASTIC and Pesticide DRASTIC and the percentage areas of agreement and divergence in vulnerability categories were extracted. DRASTIC results suggest the aquifer has mostly low vulnerability. Pesticide DRASTIC and SI identify three vulnerability categories (low, moderate, high) in the aquifer. Published data on current chemical groundwater composition indicate that parts of the aquifer are highly contaminated, revealing that DRASTIC underestimates the risk of pollution; Pesticide DRASTIC and SI reflect this risk better. Agreement in vulnerability categories between the two last models is found for 64 % of the aquifer area. To help manage land-use allocation and prevent Nabeul-Hammamet-aquifer contamination, DRASTIC is not recommended. Pesticide DRASTIC and SI are recommended but for slightly different applications. SI helps in the monitoring of current vulnerable areas and, thus, in contamination prevention. Pesticide DRASTIC could better intervene as a criterion in a multi-criteria analysis to select the best sites for specific on-the-ground practice or future land use.  相似文献   

10.
两种智能算法在求解地下水管理模型中的对比   总被引：5，自引：0，他引：5  
分别将禁忌搜索和遗传算法与地下水流模型MODFLOW和地下水溶质运移模型MT3DMS相耦合,并将其应用于求解地下水资源优化管理模型。在概述两种智能算法基本原理和地下水管理模型组成的基础上,结合两个理想的应用实例,从优化结果和计算效率两个方面对禁忌搜索和遗传算法进行了对比分析。在两个实例中,禁忌搜索分别以高于遗传算法10倍和27倍的计算效率得到了减少抽水流量约160 m3/d和节约治理成本约47万元的治理方案。结果表明,禁忌搜索在求解地下水管理模型中具有较好的应用前景。  相似文献   

11.
The assessment of groundwater vulnerability to pollution has proved to be an effective tool for the delineation of protection zones in areas affected by groundwater contamination due to intensive fertilizer applications. By modifying and optimizing the well known and widely used DRASTIC model it was possible to predict the intrinsic vulnerability to pollution as well as the groundwater pollution risk more accurately. This method incorporated the use of simple statistical and geostatistical techniques for the revision of the factor ratings and weightings of all the DRASTIC parameters under a GIS environment. The criterion for these modifications was the correlation coefficient of each parameter with the nitrates concentration in groundwater. On the basis of their statistical significance, some parameters were subtracted from the DRASTIC equation, while land use was considered as an additional DRASTIC parameter. Following the above-mentioned modifications, the correlation coefficient between groundwater pollution risk and nitrates concentration was considerably improved and rose to 33% higher than the original method. The model was applied to a part of Trifilia province, Greece, which is considered to be a typical Mediterranean region with readily available hydrogeological and hydrochemical data.
Resumen La evaluación de vulnerabilidad del agua subterránea a la contaminación ha demostrado ser una herramienta efectiva para la delimitación de zonas de protección en áreas afectadas por contaminación de aguas subterráneas debido a aplicaciones intensivas de fertilizantes. Mediante la modificación y optimización del bien conocido y ampliamente utilizado modelo DRASTIC fue posible predecir la vulnerabilidad intrínseca a la contaminación así como el riesgo a la contaminación del agua subterránea con mayor precisión. Este método incorporó el uso de técnicas estadísticas y geoestadísticas simples para la revisión del pesaje y establecimiento de rangos de factores de todos los parámetros DRASTIC bajo un ambiente SIG. El criterio para estas modificaciones fue el coeficiente de correlación de cada parámetro con las concentraciones de nitraros en agua subterránea. En base al grado significativo estadístico algunos parámetros fueros sustraídos de la ecuación DRASTIC, mientras que se consideró el uso de la tierra como un parámetro adicional de DRASTIC. Siguiendo las modificaciones antes mencionadas se mejoró considerablemente el coeficiente de correlación entre el riesgo a la contaminación del agua subterránea y las concentraciones de nitratos incrementando en 33% su valor en relación al método original. El modelo se aplicó en una parte de la provincia Trifilia, Grecia, la cual se considera ser una región Mediterránea típica con datos hidroquímicos e hidrogeológicos fácilmente disponibles.
Résumé L’évaluation de la vulnérabilité des eaux souterraines à la pollution a montré qu’elle est un outil efficace pour délimiter les zones de protection dans les zones affectées par la contamination des eaux souterraines due à l’utilisation intensive de fertilisants. En modifiant et optimisant le modèle DRASTIC, bien connu et souvent utilisé, il a été possible de prédire la vulnérabilité intrinsèque à la pollution, et de définir plus précisément le risque de pollution. Cette méthode incorpore l’utilisation de simples techniques statistiques et géostatistiques, pour la révision des facteurs d’estimation et de pondération de tous les paramètres de DRASTIC sous S.I.G. Le critère de ces modifications était le coefficient de corrélation de chaque paramètre avec la concentration en nitrates dans les eaux souterraines. Sur la base de leur signification statistique, certains paramètres ont été soustraits de l’équation DRASTIC. Suivant les modifications mentionnées ci-dessus, le coefficient de corrélation entre les concentrations en nitrate et le risque de pollution des eaux souterraines a été considérablement amélioré de 33% par rapport à la méthode originale. Le modèle a été appliqué sur une partie de la province de Trifilia en Grèce, qui est considérée comme une région typiquement méditerranéenne avec des données hydrogéologiques et hydrochimiques aisément accessibles.
  相似文献   

12.
Groundwater, the most vital water resource being used for irrigation, domestic and industrial purposes is nowadays under severe threat of contamination. Groundwater contamination risk assessment is an effective tool for groundwater management. In the study, a DRASTIC model which is based on the seven hydrogeological parameters viz: depth of water, net-recharge, aquifer media, soil media, topography, impact of vadose zone and hydraulic conductivity was used to evaluate the groundwater pollution potentiality of upper Betwa watershed. ArcGIS was used to create the ground water vulnerability map by overlaying the seven layers. Based on groundwater vulnerability map, the watershed has been divided in three vulnerable zones viz; low vulnerability zone with 42.83 km2 of area, moderate with 369.21 km2 area and high having 270.96 km2 of area. Furthermore, the DRASTIC model has been validated by nitrate concentration over the area. Results of validation have shown that in low vulnerable zone, no nitrate contamination has been recorded. While in the moderate zone nitrate has been found in the range of 1.6-10ppm. However, in high vulnerable zone 11-40ppm of nitrate concentration in groundwater has been recorded, which proves that the DRASTIC model is applicable for the prediction of groundwater vulnerability in the watershed and in similar areas too.  相似文献   

13.
Sustainable development requires the management and preservation of water resources indispensable for all human activities. When groundwater constitutes the main water resource, vulnerability maps therefore are an important tool for identifying zones of high pollution risk and taking preventive measures in potential pollution sites. The vulnerability assessment for the Eocene aquifer in the Moroccan basin of Oum Er-Rabia is based on the DRASTIC method that uses seven parameters summarizing climatic, geological, and hydrogeological conditions controlling the seepage of pollutant substances to groundwater. Vulnerability maps were produced by using GIS techniques and applying the “generic” and “agricultural” models according to the DRASTIC charter. Resulting maps revealed that the aquifer is highly vulnerable in the western part of the basin and areas being under high contamination risk are more extensive when the “agricultural” model was applied.  相似文献   

14.
DRASTIC indexing and integrated electrical conductivity (IEC) modeling are approaches for assessing aquifer vulnerability to surface pollution. DRASTIC indexing is more common, but IEC modeling is faster and more cost-effective because it requires less data and fewer processing steps. This study aimed to compare DRASTIC indexing with IEC modeling to determine whether the latter is sufficient on its own. Both approaches are utilized to determine zones vulnerable to groundwater pollution in the Nile Delta. Hence, assessing the nature and degree of risk are important for realizing effective measures toward damage minimization. For DRASTIC indexing, hydrogeological factors such as depth to aquifer, recharge rate, aquifer media, soil permeability, topography, impact of the vadose zone, and hydraulic conductivity were combined in a geographical information system environment for assessing the aquifer vulnerability. For IEC modeling, DC resistivity data were collected from 36 surface sounding points to cover the entire area and used to estimate the IEC index. Additionally, the vulnerable zones identified by both approaches were tested using a local-scale resistivity survey in the form of 1D and 2D resistivity imaging to determine the permeable pathways in the vadose zone. A correlation of 0.82 was obtained between the DRASTIC indexing and IEC modeling results. For additional benefit, the obtained DRASTIC and IEC models were used together to develop a vulnerability map. This map showed a very high vulnerability zone, a high-vulnerability zone, and moderate- and low-vulnerability zones constituting 19.89, 41, 27, and 12%, respectively, of the study area. Identifying where groundwater is more vulnerable to pollution enables more effective protection and management of groundwater resources in vulnerable areas.  相似文献   

15.
Blasting operations usually produce significant environmental problems which may cause severe damage to the nearby areas. Air-overpressure (AOp) is one of the most important environmental impacts of blasting operations which needs to be predicted and subsequently controlled to minimize the potential risk of damage. In order to solve AOp problem in Hulu Langat granite quarry site, Malaysia, three non-linear methods namely empirical, artificial neural network (ANN) and a hybrid model of genetic algorithm (GA)–ANN were developed in this study. To do this, 76 blasting operations were investigated and relevant blasting parameters were measured in the site. The most influential parameters on AOp namely maximum charge per delay and the distance from the blast-face were considered as model inputs or predictors. Using the five randomly selected datasets and considering the modeling procedure of each method, 15 models were constructed for all predictive techniques. Several performance indices including coefficient of determination (R 2), root mean square error and variance account for were utilized to check the performance capacity of the predictive methods. Considering these performance indices and using simple ranking method, the best models for AOp prediction were selected. It was found that the GA–ANN technique can provide higher performance capacity in predicting AOp compared to other predictive methods. This is due to the fact that the GA–ANN model can optimize the weights and biases of the network connection for training by ANN. In this study, GA–ANN is introduced as superior model for solving AOp problem in Hulu Langat site.  相似文献   

16.
基于DRASTIC模型的城市地下水脆弱性评价综述   总被引：2，自引：0，他引：2  
地下水脆弱性评价是环境规划和决策的有用手段,国内外已有很多研究,也提出了各种计算防污性能的模型。文章针对城市地下水污染问题介绍了评价地下水防污性能的DRASTIC模型。对DRASTIC模型的指标体系和评价方法进行了介绍,列举了DRASTIC模型的局限性;综述了目前国内外基于DRASTIC模型的城市地下水脆弱性分析的改进的模型及其应用实例,并对其应用前景进行了展望。  相似文献   

17.
A modified DRASTIC model for groundwater vulnerability assessment (abbreviated as DRARCH model by combining the first letters of its six assessment indices) was proposed. It is essentially the specific application of DRASTIC model rather than a new model. Both natural hydrogeological conditions that prevent groundwater from contamination and important intrinsic hydrogeochemical properties of sediments in vadose zone that are related to the retardation of contaminants were considered as vulnerability indices. The DRARCH model consists of six indices: (1) Depth to the water table, (2) net Recharge, (3) Aquifer thickness, (4) Ratio of cumulative thickness of clay layers to total thickness of vadose zone, (5) Contaminant adsorption coefficient of sediment in vadose zone, and (6) Hydraulic conductivity of aquifer. The rating values and the weights of these vulnerability indices were obtained by contaminant transport simulation and factor analysis method respectively. Furthermore, the DRARCH model was applied to evaluate the groundwater vulnerability to arsenic contamination in Taiyuan basin, northern China, where groundwaters with high arsenic concentration occur in some localities. GIS-based mapping of groundwater vulnerability using this model indicates that the distribution of very high and high-vulnerability areas corresponds well to that of high-arsenic groundwaters. The DRARCH model is therefore reliable and useful for guiding groundwater environment management.  相似文献   

18.
Accurate and reliable prediction of shallow groundwater level is a critical component in water resources management. Two nonlinear models, WA–ANN method based on discrete wavelet transform (WA) and artificial neural network (ANN) and integrated time series (ITS) model, were developed to predict groundwater level fluctuations of a shallow coastal aquifer (Fujian Province, China). The two models were testified with the monitored groundwater level from 2000 to 2011. Two representative wells are selected with different locations within the study area. The error criteria were estimated using the coefficient of determination (R 2), Nash–Sutcliffe model efficiency coefficient (E), and root-mean-square error (RMSE). The best model was determined based on the RMSE of prediction using independent test data set. The WA–ANN models were found to provide more accurate monthly average groundwater level forecasts compared to the ITS models. The results of the study indicate the potential of WA–ANN models in forecasting groundwater levels. It is recommended that additional studies explore this proposed method, which can be used in turn to facilitate the development and implementation of more effective and sustainable groundwater management strategies.  相似文献   

19.
Groundwater plays a key role in arid regions as the majority of water is supplied by it. Groundwater pollution is a major issue, because it is susceptible to contamination from land use and other anthropogenic impacts. A study was carried out to build a vulnerability map for the Ordos Plateau using the DRASTIC model in a GIS environment. The map was designed to show the areas of the highest potential for groundwater pollution based on hydrogeological conditions. Seven environmental parameters, such as depth to water table, net recharge, aquifer media, soil media, topography, impact of the vadose zone media, and hydraulic conductivity of the aquifer, were incorporated into the DRASTIC model and GIS was used to create a groundwater vulnerability map by overlaying the available data. The results of this study show that 24.8 % of the study area has high pollution potential, 24.2 % has moderate pollution potential, 19.7 % has low pollution potential, and the remaining 31.3 % of the area has no risk of groundwater pollution. The regional distribution of nitrate is well correlated with the DRASTIC vulnerability index. In contrast to this, although the DRASTIC model indicated that the western part had no risk, nitrate concentrations were higher in some of these areas. In particular, higher nitrate concentrations were recorded along river valleys and around lakes, such as the Mulin River valley. This is mainly caused by the intensive agricultural development and favorable conditions for recharge along river valleys.  相似文献   

20.
油田区地下水系统特殊防污性能评价   总被引：1，自引：1，他引：0       下载免费PDF全文
针对中国典型油田区的水文地质条件、主要石油类污染物性质,对地下水防污性能评价模型DRASTIC进行了改进,建立了油田区地下水系统特殊防污性能评价模型——DORKI。在该模型中选取DRASTIC模型中的地下水埋深、净补给量、包气带介质3个评价因子,增加了土壤有机质含量和有机碳-水分配系数Koc2个评价因子。根据相关资料确定了新增评价因子的评分并通过层次分析法中的九标度法确定了5个评价因子的权重。最后结合某油田区的情况,对DORKI进行实例应用和分析,结果表明,DORKI模型能够较为准确地用于原油组分对油田区地下水的污染风险评价。  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号