Genetic Algorithms for Optimal Operation of Soil Aquifer Treatment Systems

The genetic algorithm (GA) is a nonconventional search technique which is patterned after the biological processes of natural selection and evolution. It has the ability to search large and complex decision spaces and handle nonconvexities. In this paper, the genetic algorithm is investigated and applied to solve the optimal operation problem of soil aquifer treatment (SAT) systems. This problem involves finding optimal water application time and drying time which maximize infiltration for a predetermined starting influent rate of waste water and subject to various physical and operational constraints. A new scaling method is developed and some improvements on the evolution procedure are presented. A comprehensive GA–SAT computer model was developed and applied to an example SAT problem. The results are encouraging, when compared with using the successive approximation linear quadratic regulator algorithm. It was found that genetic algorithms are easy to program and interface with large complicated simulators.     

Locating Optimal Position of Pumping Wells in Aquifer Using Meta-Heuristic Algorithms and Finite Element Method

Water Resources Management - An optimal pumping policy ensures the sustainability of groundwater resources when groundwater is extracted. In this paper, several simulation models (genetic...     

Monitoring and Predicting Saltwater Intrusion via Temporal Aquifer Vulnerability Maps and Surrogate Models

This article proposes a methodology to accurately monitor seawater intrusion (SWI) using time-varied GALDIT vulnerability maps. The properly produced samples are then used as input–output patterns for the approximate SWI simulation. As a novelty, the specific area of high susceptibility to SWI is proposed as the dynamic saltwater wedge position to suitably select the monitoring locations (MLs) from a narrowed area. It is observed that varied initial conditions over time periods have more influence than variable pumping rates on salinity at MLs far from the production wells. Support Vector Regression (SVR), Artificial Neural Network (ANN) and Gaussian Process Regression (GPR) models have been substituted for the numerical model of SWI. Input training patterns of the surrogate models are initial salinity concentrations at selected MLs plus transient pumping values via Latin hypercube sampling. The final salinity at MLs constitutes the output patterns. The paper applies this new methodology to a small study area subject to the SWI problem. The generalization ability of surrogate models for predicting new initial conditions-pumping datasets was evaluated using performance criteria considering the ML locations. All surrogates offered good results for predicting SWI at specified MLs. The SVR model had poor performance compared to ANN and GPR models in MLs near the pumping wells, due to their salinity fluctuations over time.

     

西北地区未来降水量变化预测

利用MAGGIC/SCENGEN5.3软件中的14个大气环流模型预测了西北地区降水量的变化情况,采用AR4中A1B-AIM、A2ASF和A1FI情景来模拟未来CO2排放情景。结果表明:12050年A2ASF情景下多模型预测西北五省各季节降水量绝对值变化的中位数为-0.2~0.6 mm/d,但预测的极端值范围变化很大;2根据最佳模型预测,最有可能出现干旱的地区及相应季节为陕西的夏季和冬季、甘肃的夏季及新疆的春季、夏季、冬季。建议使用14个大气环流模型模拟和最佳模型预测的中位数区间作为置信区间以应对西北地区因气候变化出现的极端气候状况;314个大气环流模型模拟与最佳模型预测降水量中位数在大部分西北地区可能略有增大,但在气温相应升高情况下,可能出现干旱情况。     

Evaluation of Groundwater Resources in Lower Cretaceous Aquifer System in Sinai

The Sinai Peninsula has an area of 61000 km² and its populationis about 325000. It is located in an arid area. Extensivedevelopment in the socio-economic, industrial and agriculturalis in process. Although Lower Cretaceous aquifer is the mostprospective aquifer in Sinai, it is not yet precisely evaluated.Spatially distributed areas of good groundwater quality suitablefor various types of development are not identified.The current article presents a comprehensive assessment of thehydrogeological information and hydrological data. Accordingly,three aquifer zones have been identified. Groundwater reserve wasestimated and groundwater balance has been developed. Developmentpotential was evaluated. Development criteria were proposed and applied.Suitable areas for domestic and irrigation purposes weredelineated. Results indicated that the aquifer contains 308 billion m³ ofgroundwater of which a considerable volume is of good quality. Bylowering the present water level some 200 meters, the aquiferyielded 3643 million m³, which is sufficient to supply thepresent rate of withdrawal for 445 years. The results are considered to be usefulfor preparing groundwater master plans in Sinai. Under the properwater management, Sinai could be self sufficient in satisfying itsdomestic water demand.     

纳污河补排关系变化时污染物迁移规律研究

多环芳烃是危害较大的一种水体污染物,以菲为特征污染物,利用纳污河流和地下水系统模拟装置,对其在河流与地下水补排关系变化时的迁移过程进行了研究,以探索纳污河流与地下水间多环芳烃的迁移变化规律。采用Sufer软件分析了菲在地层中的迁移变化情况,并计算了其迁移速度,结果表明:模拟纳污河水补给地下水时,菲迁移速度缓慢,污染物扩散范围小,水平迁移速度为1.33 cm/d;模拟清洁地下水向河流排泄时,菲的水平迁移速度为1.67 cm/d,并在河流附近发生了短暂富集。     

隔水边界附近围岩渗透性变化时隧道涌水的渗流模型

根据各向同性岩石中隔水边界与水平方向的夹角,在岩石渗透性随深度呈负指数衰减条件下,分两种情况给出了二维稳定流隧道涌水量的解析解和数值解.分别对隔水边界距离和隧道埋深对隧道涌水强度的影响,以及岩体中上下水位的巨大差异进行了理论分析.此法可用于预测隧道涌水量,并给出了算例及关系曲线.     

Correction to: Monitoring and Predicting Saltwater Intrusion via Temporal Aquifer Vulnerability Maps and Surrogate Models

Water Resources Management -     

天山四棵树河暴雨及洪水分类初步研究

四棵树河是发源于天山北坡河流中洪水灾害最为严重的河流之一,该河洪水成因复杂、类型多样,历来颇受国内外学者的关注。在四棵树河流域,根据形成暴雨的环流形势与天气系统的不同,暴雨类型分为西风环流型暴雨及局地强对流型暴雨两种。四棵树河具有内陆河流的洪水特性,按其洪水成因及灾害特点,可分为冰雪融水洪水、暴雨洪水、冰雪融水与暴雨混合型洪水、冰凌洪水(即"冰洪")4种大的类型,其中,根据影响暴雨的天气系统成因及及暴雨过程分类,暴雨洪水又分为大范围强降雨洪水和局部地区暴雨洪水。     

Urbanisation and Shallow Groundwater: Predicting Changes in Catchment Hydrological Responses

The impact of urbanisation on catchment hydrological response was investigated by using a process-based coupled surface water–groundwater model (MODHMS). The modelling estimated likely changes in river discharge as a result of land-use change in the Southern River catchment in Western Australia, underlined by a highly transmissive aquifer, has permeable soils and a shallow watertable. A significant increase in total annual discharge was predicted as a result of urbanisation area with the runoff coefficient rising from 0.01 to more than 0.40. In contrast with urban areas elsewhere, these changes were mainly due to a shift in the subsurface water balance, leading to significant reduction in evaporative losses from the soil profile and shallow watertable after urbanisation (from nearly 80 % of infiltration to less than 20 %). The infiltration of roof and road runoff and establishment of subsurface drainage adopted in local construction practice leads to higher groundwater recharge rates and subsequently groundwater discharge to the urban drainage network. Urban density and groundwater abstraction for urban irrigation most strongly influence the urbanisation impact on catchment fluxes. The results shows that urban development leads to a production of ‘harvestable’ water; and depending on local needs, this water could be used for public and private water supply or to improve environmental flows.     

Application of ANN, Fuzzy Logic and Decision Tree Algorithms for the Development of Reservoir Operating Rules

Optimal use of scarce water resources is the prime objective for water resources development projects in the developing country like India. Optimal releases have been generally expressed as a function of reservoir state variables and hydrologic inputs by a relationship which ultimately allows the policy/water managers to determine the water to be released as a function of available information. Optimal releases were obtained by using optimal control theory with inflow series and revised reservoir characteristics such as elevation area capacity table, zero elevation level as input in this study. Operating rules for reservoir were developed as a function of demand, water level and inflow. Artificial Neural Network (ANN) with back propagation algorithm, Fuzzy Logic and decision tree algorithms such as M5 and REPTree were used for deriving the operating rules using the optimal releases for an irrigation and power supply reservoir, located in northern India. It was found that fuzzy logic model performed well compared to other soft computing techniques such as ANN, M5P and REPTree investigated in this study.     

Predicting Shallow Water Table Depth at Regional Scale: Optimizing Monitoring Network in Space and Time

Shallow water table levels can be predicted using several approaches, either based on climatic records, on field evidences based on soil morphology, or on the outputs of physically based models. In this study, data from a monitoring network in a relevant agricultural area of Northern Italy (ca. 12,000 Km²) were used to develop a data driven model for predicting water table depth in space and time from meteorological data and long-term water table characteristics and to optimize sampling density in space and time. Evolutionary Polynomial Regressions (EPR) were used to calibrate a predictive tool based on climatic data and on the records from 48 selected sites (N?=?5,611). The model was validated against the water table depths observed in 15 independent sites (N?=?1,739), resulting in a mean absolute error of 30.8 cm (R ²?=?0.61). The model was applied to the whole study area, using the geostatistical estimates of the average water table depth as input, to provide spatio-temporal maps of the water table depth. The impact of the degradation of data input in the temporal and spatial domain was then assessed following two approaches. In the first case, three different EPR models were calibrated based on 25 %, 50 % and 75 % of the available data, and the error indexes compared. In the second case, an increasing number of monitoring sites were removed from the initial data set, and the associated increased kriging standard deviation was assessed. Reducing the average sampling frequency from 1.5 per month to 1 every 40 days did not impact significantly on the prediction capability of the proposed model. Reducing the sampling frequency to 1 every 4 months resulted in a loss of accuracy <3 %, while removing more than half locations from the network, resulted in a global loss of information <15 %.     

Using the Hybrid Simulated Annealing-M5 Tree Algorithms to Extract the If-Then Operation Rules in a Single Reservoir

Water Resources Management - The environmental water demand of the Mahabad River in the Urmia Lake basin in Iran was first estimated, using the flow duration curve shifting method (FDC Shifting) in...     

高寒冻土煤炭开采区含水层保护评价研究

以青海祁连山煤炭基地为例,从含水层敏感性、含水层功能和煤炭开采影响力三方面建立评价指标体系,进行高寒冻土区含水层保护评价。评价结果表明:研究区含水层亟需重点保护的区域面积较小,并且不存在某一种含水层类型普遍处于亟需保护的状态;含水层一级重点保护区零星分布,仅为弧山矿区、江仓煤矿二井田和四井田、冬库矿区的冻结层上含水层以及研究区内主要大泉的补给区;研究区内超过50%的面积为含水层五级保护区,其中绝大多数地区为高山基岩区,虽然保护等级低,但也应加强含水层结构稳定性等方面的监测;木里盆地、江仓盆地与默勒盆地相比较,前者含水层敏感性较强,后者含水层功能较强,虽然保护等级均为二级,但是含水层保护的侧重点不同。     

遗传算法在潜水含水层底高分布确定及参数识别中的应用

笔者提出了给定若干个地下水位观测值,利用遗传算法反求潜水含水层底高及含水层渗透系数及饱和度的识别方法。通过二维潜水含水层地下水的流动计算验证了该方法的有效性。     

努力推进四个转变 建设四型一流企业

大渡河公司成立八年多来，一方面是电力生产经营效益节节攀升，一方面是流域开发事业全面拓展，企业发展态势和成效令人欣慰。但我们企业管理的重心主要还在于工程建设和流域开发本身，企业的经营模式和管控机制还有明显的薄弱环节，工程管理的经营含量和造价控制水平还有差距。因此，我们必须从水电工程建设为主向管理经营企业转变，努力建设效益型企业。努力推进四个转变，建设四型一流企业，既是摆在公司面前的现实课题，又是公司发展的长期任务。     

Comparative Evaluation of Genetic Programming and Neural Network as Potential Surrogate Models for Coastal Aquifer Management

Determining the optimal rates of groundwater extraction for the sustainable use of coastal aquifers is a complex water resources management problem. It necessitates the application of a 3D simulation model for coupled flow and transport simulation together with an optimization algorithm in a linked simulation-optimization framework. The use of numerical models for aquifer simulation within optimization models is constrained by the huge computational burden involved. Approximation surrogates are widely used to replace the numerical simulation model, the widely used surrogate model being Artificial Neural Networks (ANN). This study evaluates genetic programming (GP) as a potential surrogate modeling tool and compares the advantages and disadvantages with the neural network based surrogate modeling approach. Two linked simulation optimization models based on ANN and GP surrogate models are developed to determine the optimal groundwater extraction rates for an illustrative coastal aquifer. The surrogate models are linked to a genetic algorithm for optimization. The optimal solutions obtained using the two approaches are compared and the advantages of GP over the ANN surrogates evaluated.     

Predicting Long‐Term Changes in Riparian Bird Communities in Floodplain Landscapes

As anthropogenic impacts on riverine ecosystems expand, both aquatic and terrestrial ecosystems are influenced over large spatiotemporal scales. We predicted how riparian bird communities changed in response to long‐term changes in floodplain landscapes such as woodland expansion (i.e. rapid increases in vegetation cover on gravel bars and the progress of vegetation succession due to a decrease in the frequency and magnitude of flood disturbance). To test the hypothesis that woodland expansion after dam construction reduces the abundance of gravel bar‐nesting birds and increases the abundance of forest‐nesting birds, we estimated historical changes between past and present bird abundances using species distribution models across multiple rivers that were either unregulated or regulated by dams. We created past and present vegetation maps from remote sensing images and used habitat quantities as explanatory variables in the species distribution models. As we hypothesized, the estimated abundance of gravel bar‐nesting birds decreased and that of forest‐nesting birds increased because of woodland expansion in some regulated rivers. This suggests that anthropogenic alterations of riverine conditions (e.g. dam construction) can affect terrestrial ecosystems (e.g. riparian bird communities) through changes in floodplains (e.g. woodland expansion). In addition, our findings highlight the efficacy of combining spatial and temporal analyses when examining long‐term ecological dynamics. Copyright © 2013 John Wiley & Sons, Ltd.     

An Evaluation of Four Reference Evapotranspiration Models in a Subtropical Climate

This paper describes a detailed evaluation of the performance and characteristic behaviour of four equations for estimating reference evapotranspiration (ET₀) at eight meteorological sites in a subtropical climate. The equations assessed were: Makkink (MK), Turc (TC), Priestley?CTaylor (PT) and Hargreaves (HG). The sites were distributed throughout the north of Iran and represent an intermediate humidity regime. The Penman?CMonteith (PM) method was chosen as the standard for comparison and calibration of the above??mentioned four equations. Good correlation was found between the ET₀ values estimated by each of the four empirical equations and the PM method for all the locations; however MK and TC equations produced considerable underestimations. The performance of the PT and HG equations improved slightly after region-specific coefficients were developed for each equation, and the TC and MK equations were improved greatly. The modified PT equation turned out to be the most precise method, demonstrating superiority over the other methods evaluated (0.48?mm?d^?1 of root mean square error (RMSE)). Good performance from the modified HG equation (0.53?mm?d^?1 of RMSE) must be emphasized, given the simplicity of that method, which only requires maximum and minimum air temperature data.     

Development and Evaluation of Hybrid Artificial Neural Network Architectures for Modeling Spatio-Temporal Groundwater Fluctuations in a Complex Aquifer System

Water Resources Management - The proper design, development, and appropriate tuning of the Hybrid Neural Network architecture, mainly for its parsimoniousity and optimal training can help...