Groundwater Vulnerability Modeling to Assess Seawater Intrusion: a Methodological Comparison with Geospatial Interpolation

Seawater intrusion has become a growing threat in coastal urban cities due to overexploitation of groundwater. This study examines the accuracy of the commonly used geospatial quality assessment models (GQA) and groundwater vulnerability assessment models (GVA) in determining the extent of seawater intrusion in urban coastal aquifers. For that purpose, interpolation methods (kriging, IDW and co-kriging) and vulnerability assessment models (DRASTIC, EPIK) were compared using groundwater salinity criteria (TDS, Cl^?) collected at three pilot areas along the eastern Mediterranean (Beirut, Tripoli, Jal el Dib). The results showed that while the GIS-based interpolation methods and the vulnerability assessment models captured elements of the groundwater quality deterioration, both had a limited ability to accurately delineate saltwater intrusion. This emphasizes that while interpolation methods and conventional vulnerability models may give general information about groundwater quality, they fail to capture the status of the aquifer at a finer spatial resolution.

     

Artificial Neural Network (ANN) Based Modeling for Karstic Groundwater Level Simulation

A relatively new method of addressing different hydrological problems is the use of artificial neural networks (ANN). In groundwater management ANNs are usually used to predict the hydraulic head at a well location. ANNs can prove to be very useful because, unlike numerical groundwater models, they are very easy to implement in karstic regions without the need of explicit knowledge of the exact flow conduit geometry and they avoid the creation of extremely complex models in the rare cases when all the necessary information is available. With hydrological parameters like rainfall and temperature, as well as with hydrogeological parameters like pumping rates from nearby wells as input, the ANN applies a black box approach and yields the simulated hydraulic head. During the calibration process the network is trained using a set of available field data and its performance is evaluated with a different set. Available measured data from Edward??s aquifer in Texas, USA are used in this work to train and evaluate the proposed ANN. The Edwards Aquifer is a unique groundwater system and one of the most prolific artesian aquifers in the world. The present work focuses on simulation of hydraulic head change at an observation well in the area. The adopted ANN is a classic fully connected multilayer perceptron, with two hidden layers. All input parameters are directly or indirectly connected to the aquatic equilibrium and the ANN is treated as a sophisticated analogue to empirical models of the past. A correlation analysis of the measured data is used to determine the time lag between the current day and the day used for input of the measured rainfall levels. After the calibration process the testing data were used in order to check the ability of the ANN to interpolate or extrapolate in other regions, not used in the training procedure. The results show that there is a need for exact knowledge of pumping from each well in karstic aquifers as it is difficult to simulate the sudden drops and rises, which in this case can be more than 6 ft (approx. 2 m). That aside, the ANN is still a useful way to simulate karstic aquifers that are difficult to be simulated by numerical groundwater models.     

Prediction of scour below submerged pipeline crossing a river using ANN

The process involved in the local scour below pipelines is so complex that it makes it difficult to establish a general empirical model to provide accurate estimation for scour. This paper describes the use of artificial neural networks (ANN) to estimate the pipeline scour depth. The data sets of laboratory measurements were collected from published works and used to train the network or evolve the program. The developed networks were validated by using the observations that were not involved in training. The performance of ANN was found to be more effective when compared with the results of regression equations in predicting the scour depth around pipelines.     

Performance Assessment of Model Averaging Techniques to Reduce Structural Uncertainty of Groundwater Modeling

Water Resources Management - Accurate estimates of groundwater modeling in arid regions have a crucial role in reaching a sustainable management of groundwater sources. However, groundwater...     

Groundwater Quality Zonation Assessment using GIS, EOFs and Hierarchical Clustering

Three methods are utilized in this paper to assist in the groundwater clustering, in an arid region aquifer, into similar zones according to its quality. A multiple regression is first applied in order to assess the importance of the different chemical constituents in the amount of total dissolved salt, which shows the dominance of chlorine and sodium. A multivariate analysis based on empirical orthogonal functions and hierarchical clustering (EOFs) is applied to assist in water quality clustering in the studied aquifer. The clustering has produced five distinguished categories of groundwater quality, which agree well with World Health Organisation criteria and limits for water usage. Based on these categories, spatial distribution maps of groundwater quality are produced by Kriging and GIS software.     

Integrating Remote Sensing and GIS Techniques with Groundwater Flow Modeling for Assessment of Waterlogged Areas

False Colour Composites (FCC's) of IRS-1A LISS-II sensor pertaining to the dates 9th April 1989 and 7th December 1989 are used to delineate the pre-monsoon and post-monsoon surface waterlogged areas in a region around Habibpur sub-distributary bounded by Vaishali branch canal and Gandak river in North Bihar, India for the year 1989 using visual interpretation technique. Also, digital data of IRS-1C LISS-III sensor pertaining to the dates 7th December 1998 and 6th April 1999 are analyzed in a digital image processing software – ERDAS Imagine 8.3.1, to delineate the pre-monsoon and post-monsoon surface waterlogged areas for the year 1998–1999. Further, for the study area, the waterlogging conditions are delineated for the year 1991–1992 using the groundwater flow modeling software package, MODFLOW. The results obtained using satellite remote sensing data and groundwater flow modeling are integrated in a GIS environment in ERDAS Imagine for assessment of the waterlogging areas.     

应用DRASTIC模型评价湛江市浅层地下水脆弱性

地下水脆弱性研究是目前国际水文地质工作的热点,而脆弱性评价是确定地下水资源保护措施是否可行的关键。该文根据湛江市的具体情况,选取地下水埋深等7个参数作为评价因子,在GIS平台上建立其基础和专题数据库,应用DRASTIC模型对湛江市浅层地下水脆弱性进行评价,编制脆弱性分区图。应用实测地下水硝酸盐浓度分布状况对评价结果进行验证,结果表明DRASTIC模型能够较好地反映湛江市浅层地下水脆弱性。     

基于神经网络的水沙运动预报模型与回归模型比较及应用

河道水沙运动过程中是一个复杂的非线性动力学过程，鉴于神经网络具有很强的处理大规模复杂非线性动力学系统的能力，本文将神经网络理论应用于河道水沙运动规律的模拟与预报，以期识别水流泥沙运动变化过程与其影响因素因子之间的复杂非线性关系，为河道水沙模拟和预报提供一条新的方法和途径。在此基础上将神经网络模型与传统回归模拟进行了对比分析并用于螺山站流量大于5000m^3/s的水沙规律模拟，两模型模拟结果与实际水沙规律一带，神经网络模型在水沙因素选择方面回归模型简单，有较成熟的数学理论基础，而回归模型数学表达直观，易于理解。     

Operational Prediction of Groundwater Fluctuation in South Florida using Sequence Based Markovian Stochastic Model

The ecosystem of South Florida is characterized by a vast wetland system, karst surficial hydrogeology, and extended coastal boundary. The ecosystem is poised under risks of: ecological failure due to increased fragmentation by urbanization; groundwater flow disruption because of sinkhole formation; and intrusion of oceanic water with decreasing water table head because of drought or over pumping. It was found important to synthesize the spatiotemporal state of the groundwater hydrology and also develop a forecasting model to support the intensive management and monitoring in place. In this study, an objective was set to develop a stochastic sequence model capable of forecasting groundwater levels on a monthly span at a daily time scale. The groundwater level simulation was conceptualized as a sequence of daily fluctuating states of magnitudes and patterns that has a defined probability of occurrence. The model setup involved representation of daily fluctuation magnitudes in ten states and pattern changes in three states. The sequential occurrence of states of magnitudes and patterns at each time step was used for estimation of the transitional probabilities and employed in a hidden Markov model frame work for ensemble generation and estimation of posterior probabilities. A realization was chosen based on the highest maximum likelihood ratio of 90% and smallest root mean square error of 0.05–0.12 m against the historical data. A monthly forecasting at daily time step was done dynamically incorporating observed data at each time step and revising prior and posterior probability estimation in the hidden Markov model formulation. A case study was conducted at three well sites, which are situated at three different hydrogeologic settings. The model not only reproduced annual groundwater fluctuation patterns but also forecasted preceding monthly fluctuations at maximum likelihood ratio above 90% and root mean square error below 0.15 m. A further study was recommended first to analyze break point parametric estimation for seasonal analysis, and secondly to integrate the approach in other hydrological models for the purpose of synthetic groundwater fluctuation generation.     

白城市地下水质量现状评价

根据吉林省白城市境内选取的9个测点地下水指标的实测数据,对白城市地下水质量现状进行评价。选取的评价指标分别为氨氮、铁、氟化物、铅、砷、高锰酸钾、矿化度、硬度。评价方法分别采用加附注评分法与人工神经网络法,其中人工神经网络法选用BP神经网络、T-S模糊神经网络2种方法。评价结果显示:2种人工神经网络法评价的水质类别均在Ⅰ～Ⅲ类之间,水质较好;加附注评分法评价出的水质类别中只有穆家店屯水质属于Ⅱ类,其他测点均为Ⅳ类。对比3种方法评价的结果可知,BP神经网络与模糊神经网络评价的水质类型之间的差异较小,加附注评分法比其他2种方法评价得出的水质类别大。     

Uncertainty Analysis in Sediment Load Modeling Using ANN and SWAT Model

Sediment load estimation is essential in many water resources projects. In this study, the capability of two different types of model including SWAT as a process-based model and ANNs as a data-driven model in simulating sediment load were evaluated. The issue of uncertainty in the simulated outputs of the two models which stems from different sources was also investigated. Calibration and uncertainty analysis of SWAT were performed using monthly observed discharge and sediment load values and through the application of SUFI-2 procedure. The issue of uncertainty in the ANN model was also accounted for by training a network several times with different initial weights and bias values as well as randomly-selected training and validation sets, each time a network trained. Trying different input variables to find the best and most efficient network structure, it was found that in the forested watershed of Kasilian, adding average daily rainfall or previous values of discharge dose not change the performance of the ANN model significantly. Comparing the results of SWAT and ANN, it was found that SWAT model has a superior performance in estimating high values of sediment load, whereas ANN model estimated low and medium values more accurately. Moreover, prediction interval for the results of ANN was narrower than that of SWAT which suggests that ANN outputs are with less uncertainty.     

泾源县地下水演化及其地球化学模拟

以揭示泾源县地下水水化学场的形成机理为主要研究目的,在了解泾源县水文地质条件的基础上,分析了地下水水化学演化特征,选择3条模拟路径,应用PHREEQC软件对其进行了水-岩作用的地球化学模拟,定量分析研究了该区地下水的演化过程、形成机理.结果表明:各种矿物在3条模拟路径上具有相同的溶解沉淀趋势.TDS沿模拟路径的变化主要是由SO42-含量的变化引起的.在模拟路径1和3上,钠长石、岩盐、钠蒙脱石、钾长石和CO2发生了溶解作用,白云石、方解石和石膏发生了沉淀作用,同时还发生了Na+、Ca2+之间的阳离子交换作用,在路径2上,发生的是钠长石、岩盐、钠蒙脱石、石膏和钾长石的溶解以及Na+、Ca2+之间的阳离子交换,白云石和方解石发生了沉淀作用.在这些溶解沉淀作用综合作用下,地下水水化学成分发生了变化.     

An Empirical Assessment of On-Farm Water Productivity using Groundwater in a Semi-Arid Indian Watershed

Realistic estimation of irrigation volume applied to any crop at farm level generally requires information on event based discharge rates and corresponding periods of irrigation application. Use of mean seasonal discharge rates leads to erroneous estimation of volume due to unaccounted seasonal fluctuations in the water table, upon which the discharge rate of tube well is dependent. In the absence of such information, an alternative approach of estimating farm level water application based upon water table fluctuation data has been adopted in this study. The total actual water extracted during each irrigation event from the watershed was distributed among the farms irrigating crops in proportion to the product of irrigation time and the pump capacity (h_p). Volume of water withdrawal concurrent to an irrigation event was computed based on the water level fluctuations in the wells in conjunction with potential recharge contribution from the surface storage structures to the groundwater aquifer. A production function approach was used to estimate the marginal productivity of water for selected crops at various stages of plant growth. Water, as an input in the production function, encompassed either in-situ soil moisture storage from rainfall or irrigation from groundwater or both. The inter-season as well as intra-season groundwater use, and the consequent groundwater withdrawals were analyzed based on the marginal value and output elasticity of water at different crop growth stages during the season. The cotton crop realized marginal value product of water, ranging from Rs. 1.03/m³ to Rs. 10.43/m³ at different crop growth stages in cotton. Castor crop had the marginal value product ranging from Rs. 2.89/m³ to Rs. 6.81/m³. The availability and use of water, including soil moisture, in the two seasons, coupled with the local harvest prices received, yielded the differential marginal values of water.     

邯郸市地下水水质变化趋势预测分析

根据邯郸市浅层地下水水质状况,选择了分布在污染严重地区、饮水型地方病地区的具有代表性的监测井,采用线性趋势检验法进行分析.对选取的氯化物、硫酸盐、总硬度、溶解性总固体、氟化物、铁、锰、铅、铵氮、高锰酸盐指数等9项参数分别进行统计分析.根据分析结果,对未来几年邯郸市地下水水质进行了初步预测.     

水利工程地下水环境影响评价

拟建的四川某水库位于丘陵峡谷之中,工程区内分布侏罗系、白垩系河湖相红色砂、泥岩沉积,属于红层地区。项目建设是否会对区域地下水环境产生影响,进而导致与地下水有关的水土流失及生态破坏等环境问题值得特别关注。通过对该新建水利工程的地下水环境现状调查评价与监测,了解区域地下水环境现状,预测本工程在施工期和运营期对周围地下水环境影响的范围和程度,从环境保护角度出发论证工程建设的合理性、可行性。     

柴达木盆地地下水功能评价

在详细调查柴达木盆地水文地质条件的基础上,建立了地下水功能评价指标体系,采用层次分析法对地下水功能进行综合评价。结果表明:盆地内地下水可持续利用性强的区域为那棱格勒河、格尔木河及塔塔棱河三大流域的补给径流区,地下水系统处于良好可利用状况,地下水的生态功能或地质环境功能没有问题;其余各流域的山前补给径流区地下水可持续利用性为一般—较强,地下水的生态功能或地质环境功能已经发生一些问题或较严重问题;地下水可持续利用性较弱区分布于各流域排泄区绿洲带内;盆地中心区排泄区和各流域咸卤水分布区,地下水可持续利用性弱,地下水的生态功能或地质环境功能已经发生很严重的问题。     

哈头才当水源地地下水位模拟与预测

采用MODFLOW软件对哈头才当水源地地下位进行数值模拟,经数值模型识别与验证,所取参数基本合理,水位拟合情况良好,模型能够真实地反映水源地地下水位的变化特征。在模型识别与验证的基础上,给出预测模型的初始条件、边界条件及其源汇项,对2009年10月—2029年10月地下水位进行了预测。结果表明:水源地按照设计开采方案开采,地下水位不会持续下降,计算区内大部分区域水位降深小于6 m,总体降深较小,不会对生态造成明显的影响。     

地下水资源动态评价的机制与技术框架

充分考虑地下水资源动态变化特征,以国民经济的实际需求为依据,提出以信息技术为支撑的地下水资源动态评价的机制和技术框架。在具体工作的实施上,结合我国地下水资源数据特征、工作现状和新技术应用状况,建立以独立地下水系统为单元的数据获取、数据管理、资源评价、数据共享与服务的动态评价平台实体;以网络环境为基础、以WEB服务为机制,实现独立的地下水动态评价平台实体之间的互联互通和协同工作,建立统一的门户网站面向社会提供数据与信息的共享和服务。     

Simulation-Optimization Modeling of Conjunctive Use of Surface Water and Groundwater

Water resources management in semiarid regions with low precipitation and high potential of evapotranspiration is a great challenge for managers and decision makers. In those regions, both sources of water should be managed conjunctively so as to minimize shortages of water in dry seasons. In conjunctive use, the difficulty increases as one must represent the response of both systems interactions, and develop management strategies that simultaneously address surface water and aquifer regulation. This paper focuses on the simulation-optimization for conjunctive use of surface water and groundwater on a basin-wide scale, the Najafabad plain in west-central Iran. A trained artificial neural network model is developed as a simulator of surface water and groundwater interaction while a genetic algorithm is developed as the optimization model. The main goal of the simulation-optimization model is to minimize shortages in meeting irrigation demands for three irrigation systems subject to constraints on the control of cumulative drawdown of the underlying water table and maximum capacity of surface irrigation systems. To achieve the main goal, three scenarios are presented. Results of the proposed model demonstrate the importance of the conjunctive use approach for planning the management of water resources in semiarid regions.     

北方浅层地下水超采区地下水预测模型

针对北方地区地下水动态特征,选定河北省大清河地下水系统的大沙河-磁河冲洪积扇孔隙地下水系统小区作为研究区。研究区地下水动态主要受降水影响,年内变化较大,根据这一特点,利用神经网络等工具建立了研究区浅层地下水分月地下水预测模型。模型采用1991年-2000年数据进行参数率定,采用2001年-2005年数据对模型进行了验证。通过该模型的建立,解决了北方地下水预测中预测精度差、模型不稳定的难题,为水资源管理提供了科学依据,为其他类似地区地下水动态预测奠定了坚实的基础。