山西柳林泉局部区域溶质运移二维数值模拟

本文建立了用于描述柳林泉域地下水中氯离子运移行为的局部区域二维可混溶溶质运移模型。模型考虑了地下水中溶解盐分浓度变化引起的地下水密度的改变，及其导致的地下水水头的变化。该模型计算值与观测资料基本一致，说明所建模型可以用于实际。据此用所建模型预报了柳林电厂水源地投入使用后对区域地下水位和水质的影响。     

赣州兴国盆地浅层地下水中氟的分布特征研究

本文通过野外现场调查,对赣州兴国盆地及周边303处地下水中氟浓度进行了测试,并对测试数据进行了整理。通过绘制氟浓度等值线图和氟富集模式图对其地下水中的氟分布特征及其成因展开研究,确定了兴国盆地浅层地下水中氟的主要来源是含氟矿物溶解,受水动力条件影响,其含量普遍较低,溶解到地下水中的氟离子随地下水径流进行迁移。研究结果可为当地饮用水合理开发提供氟浓度方面的参考,对居民饮水安全和水环境保护具有一定指导意义。     

新疆祁漫塔格地区地下水化学特征及成因分析

为了解新疆祁漫塔格地区地下水化学特征及主要离子来源,依据地下水采样调查数据,综合利用数理统计分析、Piper三线图、Gibbs图、离子比值和水文地球化学模拟等方法进行分析探讨。结果表明：研究区地下水总体呈弱碱性;地下水化学类型主要为Na-Cl·SO₄型、Na·Mg-Cl·SO₄型和Na·Mg-Cl·SO₄·HCO₃型;蒸发浓缩作用和岩石的风化溶解是影响和控制研究区地下水化学成分的首要因素,其中,岩石的风化溶解以蒸发岩(石膏和盐岩等)和硅酸盐(钾长石、钠长石、钙长石和镁长石等)的溶解为主。     

塔里木沙漠公路沿线浅层地下水化学特征

为研究新疆塔里木沙漠公路沿线浅层地下水水化学特征及其成因,运用数理统计、Piper三线图、Gibbs图、相关性分析和离子比值等方法分析研究区2014年20组浅层地下水水样测试结果,并探讨沙漠公路沿线水化学演化过程的主要控制因素。研究结果表明,浅层地下水中主要阴阳离子为SO42-和Na+;TDS介于543.61～10 249.74mg/L,平均值为4 087.58mg/L;pH值的范围在7.11～9.05,平均值为7.87;总硬度超过450 mg/L的水样占95%;地下水水化学类型以SO4·Cl-Na型、SO4·Cl-Na·Mg型和SO4·Cl-Na·Ca型为主;地下水中SO42-和Na+是TDS的主要来源,且SO42-和Na+主要来源于岩盐或蒸发岩溶解;各主要离子间均有较好的相关性,其来源具有一致性;大气降水作用对研究区地下水化学组分几乎没有影响,地下水主要受蒸发浓缩和岩石风化作用影响;地下水中主要离子来源受硅酸盐岩和蒸发盐岩风化溶解影响较大,同时受到碳酸盐岩的溶解和阳离子交换作用影响。     

荷兰地下水中的砷对饮用水供给的影响

介绍了荷兰饮用水的供给状况,地下水中砷的分布,饮用水中的砷,以及8个典型水文系统中砷的形成过程、水化学特征,分析了荷兰地下水中砷的活动过程,主要包括:吸附和阴离子交换、黄铁矿的氧化反应和氧(氢氧)化铁的还原性溶解以及砷酸盐被还原成亚砷酸盐,并针对不同的情况提出了相应的治理措施。     

柳林泉域岩溶水化学演化及地球化学模拟

为揭示柳林泉域岩溶水化学演化机理,在对柳林泉域水文地质调查的基础上,从岩溶水阴阳离子组成和矿物饱和指数入手,分析了岩溶水化学特征及其演化过程,通过建立逆向地球化学模型,模拟了岩溶含水层中的水岩作用。结果表明:沿地下水流动路径,柳林泉域岩溶水化学类型由补给区的HCO_3-Ca·Mg型演化为径流区的HCO_3·SO_4-Ca·Mg型,在排泄区演化为HCO_3·SO_4-Ca·Na型。柳林泉域岩溶水化学演化的主要地球化学作用为碳酸盐岩和石膏的溶解作用,且沿地下水流动路径,由补给区的方解石和白云石共同溶解作用,逐渐向径流区的白云石和石膏溶解作用为主演化,排泄区还发生了岩盐溶解作用。去白云岩化作用和Na~+-Ca~(2+)离子交换吸附作用在径流区和排泄区影响岩溶水化学类型。     

地下水地理信息系统设计与实现

针对GIS在地下水资源管理中缺乏专业模型支持的缺陷，研究开发了地下水地理信息系统(Groundwater Geographical Information System，简称GGIS)。利用Delphi、MapObjects和OpenGL技术，实现了地下水模型与GIS组件的完全集成。GGIS具有集数据管理、可视化、建模、绘制钻孔柱状和水位剖面图、生成有限元网格等功能。开发的系统在建模、模型输入输出等方面变得更方便。实践证明，将GIS与地下水模型完全集成，极大地提高了地下水建模效率。     

江汉平原西缘地下水水文地球化学过程研究

鄂西丘陵山区地下水向江汉平原运移是较复杂的水文地球化学过程,通过数理统计、水化学分析、Gibbs图以及水文地球化学模拟等方法对江汉平原西缘不同类型地下水运动及其化学组分变化规律进行了研究。结果表明:裂隙岩溶水主要化学类型为HCO_3-Ca和HCO_3-Ca+Mg型,碎屑岩类裂隙水为HCO_3-Ca和HCO_3-Ca+Na型,孔隙水以HCO_3-Ca型为主。方解石和白云石的溶解是丘陵山区主要的水文地球化学过程,孔隙水和裂隙水以岩盐和石膏的溶解为主,裂隙水中还存在阳离子交换吸附作用,少量孔隙水受蒸发-沉淀作用的影响。地下水由丘陵山区向平原区径流过程中发生了石膏以及少量岩盐和钾长石的溶解,同时伴随着阳离子交换吸附和硝化反应,方解石和少量的钠长石因为过饱和而发生沉淀。     

潮白河地下水调蓄区水岩作用过程模拟

南水北调中线工程通水后,将有部分结余水量用于补给潮白河地下水调蓄区。由于南方地表水(以下简称南水)与北京当地地下水的水质存在一定差异,回灌过程中很有可能发生水岩相互作用。研究以潮白河地下水回灌区为例,通过静态摇瓶实验和水文地球化学模拟等研究方法,对南水补给北京深层地下水过程中产生的水岩作用过程和水质影响程度进行分析评价。研究结果表明:南水回灌过程中,地下水的主要离子成分会受到硝化作用、阳离子交换作用及包气带矿物质溶解等作用的综合影响。两种水混合过程中,土壤矿物相中的方解石和白云石不断溶解,Ca2+、Mg2+浓度逐渐升高,反应过程中还伴随强烈的阳离子交换作用,主要为Na+与Ca2+、Mg2+的交换。南水比例越大,溶解氧促进硝化作用越明显;在硝化作用和碳酸平衡的共同影响下,地下水的pH值呈现先降低后升高的趋势。     

西北富水地区盐渍土地层内温湿度变化规律研究

温湿度对盐渍土地区公路的季节性冻胀和沉陷有着明显的影响，为研究富水地区盐渍土地基的温湿度变化规律，以柳园至敦煌公路某区段为例，通过多层土壤参数监测仪对公路两侧的温湿度进行了为期1年的监测，并采用公式拟合的方式建立了不同深度地层的温度曲线表达式，在拟合出的温度曲线表达式的基础上确定了受地表温度变化影响的临界地层深度，最后通过湿度监测结果研究了不同深度地层的湿度变化规律和地层冻结深度。研究结果表明:研究区段地层年温度近似呈正弦曲线式变化，不同深度的地层温度曲线间存在着温度滞后现象，滞后时间与地层深度呈正比；研究区段地层在冬季出现结冰现象，冻土层深度在25ｃｍ～45ｃｍ之间；地层温度受地表温度影响的临界深度为400ｃｍ～500ｃｍ；地层湿度受地下水的影响表现出夏季湿度大、冬季湿度小的特点。     

Model uncertainty--parameter uncertainty versus conceptual models.

Uncertainties in model structures have been recognised often to be the main source of uncertainty in predictive model simulations. Despite this knowledge, uncertainty studies are traditionally limited to a single deterministic model and the uncertainty addressed by a parameter uncertainty study. The extent to which a parameter uncertainty study may encompass model structure errors in a groundwater model is studied in a case study. Three groundwater models were constructed on the basis of three different hydrogeological interpretations. Each of the models was calibrated inversely against groundwater heads and streamflows. A parameter uncertainty analysis was carried out for each of the three conceptual models by Monte Carlo simulations. A comparison of the predictive uncertainties for the three conceptual models showed large differences between the uncertainty intervals. Most discrepancies were observed for data types not used in the model calibration. Thus uncertainties in the conceptual models become of increasing importance when predictive simulations consider data types that are extrapolates from the data types used for calibration.     

Stochastic and Robust Multi-Objective Optimal Management of Pumping from Coastal Aquifers Under Parameter Uncertainty

Combined simulation-optimization approaches have been used as tools to derive optimal groundwater management strategies to maintain or improve water quality in contaminated or other aquifers. Surrogate models based on neural networks, regression models, support vector machies etc., are used as substitutes for the numerical simulation model in order to reduce the computational burden on the simulation-optimization approach. However, the groundwater flow and transport system itself being characterized by uncertain parameters, using a deterministic surrogate model to substitute it is a gross and unrealistic approximation of the system. Till date, few studies have considered stochastic surrogate modeling to develop groundwater management methodologies. In this study, we utilize genetic programming (GP) based ensemble surrogate models to characterize coastal aquifer water quality responses to pumping, under parameter uncertainty. These surrogates are then coupled with multiple realization optimization for the stochastic and robust optimization of groundwater management in coastal aquifers. The key novelty in the proposed approach is the capability to capture the uncertainty in the physical system, to a certain extent, in the ensemble of surrogate models and using it to constrain the optimization search to derive robust optimal solutions. Uncertainties in hydraulic conductivity and the annual aquifer recharge are incorporated in this study. The results obtained indicate that the methodology is capable of developing reliable and robust strategies for groundwater management.     

Assessment and Prediction of Groundwater using Geospatial and ANN Modeling

In semi-arid regions, the deterioration in groundwater quality and drop in water level upshots the importance of water resource management for drinking and irrigation. Therefore geospatial techniques could be integrated with mathematical models for accurate spatiotemporal mapping of groundwater risk areas at the village level. In the present study, changes in water level, quality patterns, and future trends were analyzed using eight years (2012–2019) groundwater data for 171 villages of the Phagi tehsil, Jaipur district. Kriging interpolation method was used to draw spatial maps for the pre-monsoon season. These datasets were integrated with three different time series forecasting models (Simple Exponential Smoothing, Holt's Trend Method, ARIMA) and Artificial Neural Network models for accurate prediction of groundwater level and quality parameters. Results reveal that the ANN model can describe groundwater level and quality parameters more accurately than the time series forecasting models. The change in groundwater level was observed with more than 4.0 m rise in 81 villages during 2012–2013, whereas ANN predicted results of 2023–2024 predict no rise in water level?>?4.0 m. However, based on predicted results of 2024, the water level will drop by more than 6.0 m in 16 villages of Phagi. Assessment of water quality index reveals unfit groundwater in 74% villages for human consumption in 2024. This time series and projected groundwater level and quality at the micro-level can assist decision-makers in sustainable groundwater management.

     

Modeling of Ground Water Salinity on the Caspian Southern Coasts

Water salinity is one of the main restrictive factors in water exploiting. Also, unsuitable management and exploitation of water resources has led to an increase of surface and groundwater salinity. Thus, in view of human needs to water resources, it is necessary to study and define water salinity factors in order to weaken these factors. This research has been conducted to investigate the factors of groundwater salinity and also, to provide a model for estimating groundwater salinity on the Caspian southern coasts. Data included in the model are: water qualitative examinations in the area, annual precipitation and evaporation, water table depth, surface water salinity, aquifer formation (Transmissivity) and distance from Caspian Sea. Surface and groundwater salinity was estimated by sampling in different sites on the Caspian southern coasts. Then, Multivariate Regression method was used by using SPSS software. In this stage, groundwater EC has been used as a variable for water salinity or dependent variable and groundwater salinity factors have been used as independent variables. A linear model and a non-linear model were presented. The models efficiency was evaluated by applying them in the sites that their data were not used for presenting the models. Finally, groundwater EC average map was provided by using the presented non-linear model and Geographic Information System in the Eastern part of Mazandaran province. In view of salinity hazard increases in the coastal terrains and agricultural areas, the places with high hazard salinity must be defined and managed to decrease water resources salinity.     

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.

     

京津冀平原浅层地下水漏斗演变规律与影响因素

为研究华北地区河湖生态补水对地下水漏斗演变的影响,以京津冀平原浅层地下水漏斗2003年至2022年的相对变化作为识别目标,从气象因素、地形因素、人为因素和含水层水力学特性4个方面进行考虑,选取8个具体指标构建特征变量数据集,使用逻辑回归（logistic regression, LR）、支持向量机（support vector machine, SVM）和随机森林（random forest, RF）方法建立漏斗演变识别模型,并利用敏感度、特异度和决定系数R2 对拟合效果进行对比评价,结果显示随机森林为最优模型。进而利用模型分析研究区地下水漏斗演变规律,阐明具体因素对漏斗演变的影响作用。研究表明：京津冀平原区浅层地下水漏斗在2010年之前整体呈扩张趋势,之后在部分地区呈现缩减和消失的态势。河湖补水前,地下水漏斗发展主要受开采影响,其重要度约50%;2018年后河湖补水对抑制漏斗扩张发挥了较为明显的作用,重要度达16%。从发展过程来看,地下水开采依然是控制京津冀平原浅层地下水漏斗变化最重要的因素。对比宁柏隆和高蠡清两个典型浅层地下水漏斗的发展变化可知,河道生态补水对宁柏隆漏斗变化的贡献率接近10%,而对高蠡清漏斗变化影响的重要度仅为1%,因此持续的河流生态补水对宁柏隆漏斗水位恢复会产生积极影响,而对于高蠡清漏斗则需要以水源置换压减农业灌溉地下水量为关键手段实现水位恢复。     

Estimation of Groundwater Recharge from the Rainfall and Irrigation in an Arid Environment Using Inverse Modeling Approach and RS

Quantifying recharge from agricultural areas is important to sustain long-term groundwater use, make intelligent groundwater allocation decisions, and develop on-farm water management strategies. The scarcity of data in many arid regions, especially in the Middle East, has necessitated the use of combined mathematical models and field observations to estimate groundwater recharge. This study was designed to assess the recharge contribution to groundwater from rainfall and irrigation return flow in the Mosian plain, west of Iran. The Inverse modeling approach and remote sensing technology (RS) were used to quantify the groundwater recharge. The recharge for steady–state conditions was estimated using the Recharge Package of MODFLOW. The land-use map for the research area was produced using remote sensing and satellite images technology. According to results, groundwater recharge from the rainfall and irrigation return flow was at the rate of 0.15 mm/day. The recharge to the groundwater from rainfall was about 0.08 mm/day (10.8 % of total rainfall). The average of groundwater recharge contribution in the study area was about 0.39 mm/day that include 15.2 % of the total water used in the irrigated fields. We can conclude that irrigation water is the most important resource of groundwater recharge in this area, consequently, it should be integrated into relevant hydrological models as the main source of groundwater recharge.     

地下水数值模型在中国的应用现状及发展趋势

地下水数值模型在地下水资源定量评价及相关领域研究中得到了广泛的应用。本文介绍了几种流行的数值模拟模型,阐述了模型特点及其在我国的应用现状。指出模型对客观实体概化存在误差,模拟精度有待于提高;裂隙介质、岩溶介质中的地下水运移模拟技术未解决,限制了模型应用范围;强调了模型数据前后处理能力的不足;指出了模拟技术在地下水源汇项概化、地下水运动机理方面的发展前景,提出多种模型耦合以及与GIS紧密结合的重要性,并指出由于使用对象的转变给地下水模型发展带来的新机遇。     

Developing a Multi-Objective Conflict-Resolution Model for Optimal Groundwater Management Based on Fallback Bargaining Models and Social Choice Rules: a Case Study

Conflict-resolution models can be used as practical approaches to consider the contradictions and trade-offs between the involved stakeholders in integrated water resource management. These models are utilized to reach an optimal solution considering agents interactions. In this paper, a new methodology is developed based on multi-objective optimization model (NSGA-II), groundwater simulation model, M5P model tree, fallback bargaining procedures and social choice rules to determine the optimal groundwater management policies with an emphasis on resolving conflicts between stakeholders. By incorporating the multi-objective simulation-optimization model and bargaining methods, the optimal groundwater allocation policies are determined and the preferences of the stakeholders as well as social criteria such as justice are also considered. The obtained data set, based on Monte Carlo analysis of calibrated MODFLOW model, is used for training and validating the M5P meta-models. The validated M5P meta-models are linked with NSGA-II to determine the trade-off curve (Pareto front) for the objectives. Social choice rule and fallback bargaining methods, as conflict-resolution models, are applied to determine the best socio-optimal solution among stakeholders, and their results are compared. The effectiveness of the proposed methodology is verified in a case study of Darian aquifer, Fars province, Iran. Results indicated that the solutions obtained by the proposed conflict-resolution approaches have an appropriate applicability. Total groundwater withdrawal, after applying the optimal groundwater allocations, reduced to 20.85 MCM, resulting in a 4.62 m increase in the mean groundwater level throughout the aquifer.     

Application of Several Data-Driven Techniques for Predicting Groundwater Level

In this study, several data-driven techniques including system identification, time series, and adaptive neuro-fuzzy inference system (ANFIS) models were applied to predict groundwater level for different forecasting period. The results showed that ANFIS models out-perform both time series and system identification models. ANFIS model in which preprocessed data using fuzzy interface system is used as input for artificial neural network (ANN) can cope with non-linear nature of time series so it can perform better than others. It was also demonstrated that all above mentioned approaches could model groundwater level for 1 and 2 months ahead appropriately but for 3 months ahead the performance of the models was not satisfactory.