Comparing multi-objective optimization techniques to calibrate a conceptual hydrological model using in situ runoff and daily GRACE data

Hydrological models are necessary tools for simulating the water cycle and for understanding changes in water resources. To achieve realistic model simulation results, real-world observations are used to determine model parameters within a “calibration” procedure. Optimization techniques are usually applied in the model calibration step, which assures a maximum similarity between model outputs and observations. Practical experiences of hydrological model calibration have shown that single-objective approaches might not be adequate to tune different aspects of model simulations. These limitations can be as a result of (i) using observations that do not sufficiently represent the dynamics of the water cycle, and/or (ii) due to restricted efficiency of the applied calibration techniques. To address (i), we assess how adding daily Total Water Storage (dTWS) changes derived from the Gravity Recovery And Climate Experiment (GRACE) as an extra observations, besides the traditionally used runoff data, improves calibration of a simple 4-parameter conceptual hydrological model (GR4J, in French: modèle du Génie Rural à 4 paramètres Journalier) within the Danube River Basin. As selecting a proper calibration approach (in ii) is a challenging task and might have significant influence on the quality of model simulations, for the first time, four evolutionary optimization techniques, including the Non-dominated Sorting Genetic Algorithm II (NSGA-II), the Multi-objective Particle Swarm Optimization (MPSO), the Pareto Envelope-Based Selection Algorithm II (PESA-II), and the Strength Pareto Evolutionary Algorithm II (SPEA-II) along with the Combined objective function and Genetic Algorithm (CGA) are tested to calibrate the model in (i). A number of quality measures are applied to assess cardinality, accuracy, and diversity of solutions, which include the Number of Pareto Solutions (NPS), Generation Distance (GD), Spacing (SP), and Maximum Spread (MS). Our results indicate that according to MS and SP, NSGA-II performs better than other techniques for calibrating GR4J using GRACE dTWS and in situ runoff data. Considering GD as a measure of efficiency, MPSO is found to be the best technique. CGA is found to be an efficient method, while considering the statistics of the GR4J’s 4 calibrated parameters to rank the optimization techniques. The Nash-Sutcliffe model efficiency coefficient is also used to assess the predictive power of the calibrated hydrological models, for which our results indicate satisfactory performance of the assessed calibration experiments.     

Assessing the suitability of benthic foraminiferal morpho-groups to reconstruct paleomonsoon from Bay of Bengal

Temporal changes in benthic foraminiferal morpho-groups were suggested as an effective proxy to reconstruct past monsoon intensity from the Arabian Sea. Here, in order to test the applicability of temporal variation in morpho-groups to reconstruct past monsoon intensity from the Bay of Bengal, we have documented recent benthic foraminiferal distribution from the continental shelf region of the northwestern Bay of Bengal. Based on the external morphology, benthic foraminifera were categorized into rounded symmetrical (RSBF) and angular asymmetrical benthic foraminifera (AABF). Additionally, a few other dominant groups were also identified based on test composition (agglutinated, calcareous) and abundance (Asterorotalids and Nonions). The relative abundance of each group was compared with the ambient physico-chemical conditions, including dissolved oxygen, organic matter, salinity and temperature. We report that the RSBF are abundant in comparatively warm and well oxygenated waters of low salinity, suggesting a preference for high energy environment, whereas AABF dominate relatively cold, hypersaline deeper waters with low dissolved oxygen, indicating a low energy environment. The agglutinated foraminifera, Asterorotalids and Nonions dominate shallow water, low salinity regions, whereas the calcareous benthic foraminiferal abundance increases away from the riverine influx regions. Food availability, as estimated from organic carbon abundance in sediments, has comparatively less influence on faunal distribution in the northwestern Bay of Bengal, as compared to dissolved oxygen, temperature and salinity. We conclude that the factors associated with freshwater influx affect the distribution of benthic foraminiferal morpho-groups in the northwestern Bay of Bengal and thus it can be used to reconstruct past monsoon intensity from the Bay of Bengal.     

Petrographical and petrophysical properties of sandstones: statistical analysis as an approach to predict material behaviour and construction suitability

Most studies dealing with material properties of sandstones are based on a small data set. The present study utilizes petrographical and petrophysical data from 22 selected sandstones and ~300 sandstones from the literature to estimate/predict the material and weathering behaviour of characteristic sandstones. Composition and fabric properties were determined from detailed thin section analyses. Statistical methods applied consist of data distributions with whisker plots and linear regression with confidence regions for the petrophysical and weathering properties. To identify similarities between individual sandstones and to define groups of specific sandstone types, principal component and cluster analyses were applied. The results confirm an interaction between the composition, depositional environment, stratigraphic association and diagenesis, which leads to a particular material behaviour of sandstones. Three different types of pore radii distributions are observed, whereby each is derived from different pore space modifications during diagenesis and is associated with specific sandstone types: (1) bimodal with a maximum in capillary and micropores, (2) unimodal unequal with a maximum in smaller capillary pores and (3) unimodal equable with a maximum in larger capillary pores. Each distribution shows specific dependencies to water absorption, salt loading and hygric dilatation. The strength–porosity relationship shows dependence on the content of unstable lithic fragments, grain contact and type of pore radii distribution, cementation and degree of alteration. Sandstones showing a maximum of capillary pores and micropores (bimodal) exhibit a distinct hygric dilatation and low salt resistance. These sandstones are highly immature sublitharenites–litharenites, characterized by altered unstable rock fragments, which show pointed-elongated grain contacts, and some pseudomatrix. Quartz arenites and sublitharenites–litharenites which are strongly compacted and cemented, show unimodal unequal pore radii distributions, low porosity, high strength and a high salt resistance. The presence of swellable clay minerals in sublitharenites–litharenites leads to a medium to high hygric dilatation, whereas quartz arenites show little hygric dilatation. Sandstones with unimodal equal pore radii distribution mostly belong to weakly compacted and cemented mature quartz arenites. These are characterized by high water absorption and high porosity, low to medium strength and a low salt resistance. The data compiled in this study are used to create a sandstone quality catalogue. Since material properties are dependent on many different parameters of influence, the transition between different lithotypes is fluent.     

Performance evaluation of the M8 algorithm to predict M7+ earthquakes in Turkey

The M8 algorithm is one of the most reliable intermediate-term middle-range earthquake prediction algorithms. The present study evaluates the ability of the M8 algorithm and its modified versions for predicting major events (M7+) in Turkey. Thirty different algorithms were developed by changing the radius of circle of investigation (CI) and the lower magnitude cutoff of the M8 algorithm. These modified algorithms were executed all over the territory of Turkey, and the results were evaluated using the error diagram. Each modified algorithm was executed for consecutive half-year intervals over a specified period of time. Subsequently, the seismic catalog was updated, and failures-to-predict ratio and the fraction of alarm were considered. Results showed that the location of areas of alarm change gradually over consecutive intervals, and no sudden changes can be observed. In addition, the annual changes of areas of alarm are not random and follow a pattern. This study also showed that the modified algorithm having a three to six annual average of events and a 393-km CI radius is an efficient algorithm for predicting the future seismic events in Turkey. This algorithm predicted six out of six target events, retrospectively, with a confidence level of 96.4 %. According to the obtained results, it will be possible to rely on this modified algorithm to predict near future earthquakes of Turkey. Furthermore, this study proves that it is possible to alter the M8 algorithm for being used in regional studies.     

混合加速遗传算法在流域模型参数优化中的应用

在实编码遗传算法中加入单纯形搜索算子和加速搜索算子,提出了混合加速遗传算法.通过实例对该法与其它一些遗传算法进行了比较.并在大坳流域模型的参数优选中得到成功的应用.结果表明,混合加速遗传算法具有直观、简便、快速及适用性强等特点,是一种既可以较大概率搜索全局最优解,又能进行局部细致搜索的优秀非线性优化方法.     

Integrated evaluation of urban development suitability based on remote sensing and GIS techniques: contribution from the analytic hierarchy process

Urban, industrial, and tourist developments are considered of high priority in Egypt. In the current research, the site suitability investigation for rating the different environmental, geological, and geotechnical conditions facing civil engineering projects were assessed using a geographic information system (GIS) multi-criteria approach. The study area is one of the most promising areas for urban and touristic as well as industrial developments in Egypt, which is located on the NW coast of the Gulf of Suez. This area may face several geo-environmental problems that will limit its suitability for civil projects. Weighted GIS model, which integrates different types of data sources, such as land use/cover, geological, geomorphological, geophysical, environmental, remote sensing, and field data, can be achieved to create a site suitability map. In this paper, an analytical hierarchy process approach has been used to develop the weighted model for different factors. As a result of this study, areas of potential geotechnical and geo-environmental hazards that could impact the design and construction of civil projects were identified. Therefore, changes can be made early in the design process before significant design efforts are being invested.     

岩溶洼地抽水蓄能建库适宜性评价体系及目标优选

为解决岩溶洼地修建抽水蓄能电站选址的实际工程问题,利用DEM数据和ArcGIS平台自动提取岩溶洼地并进行属性分析和计算,开展岩溶洼地建库资源评价及上库库址优选研究。提出洼地坡度、库容、岩组类型、断层、水文地质、上下库竖直距离和距高比7个建库决策关键性影响因子,构建模糊综合评判模型和偏最小二乘通径模型,以生态保护红线和自热保护区为限制性因素,对研究区488个候选洼地进行初步筛选排序。研究结果表明,竖直距离、库容、距高比三个因素对选址决策起到关键性作用;应用GIS地图叠加技术能很好排除因环境因素限制的不可行站点。通过两种模型普选出的前10个优选洼地中共有6个吻合,一致性较好说明评价模型适用性强、评价结果可靠性高;优选出的洼地与指标体系的量化标准基本一致,在工程实例中得到了很好的验证,其中白水塘1#洼地最适合建设抽水蓄能电站。     

ANN技术在地下水含水量预测建模中的研究与应用

将人工神经网络(ANN)技术引入到地下水含水量预测工作,以华北平原和河套平原为试验场,以若干已知钻孔为验证,采用激电和电阻率测深等地面物探方法获取视电阻率ρS、视极化率ηS、半衰时Th、衰减度D和偏离度σ等参数为输入神经元对单孔单位涌水量建立人工神经网络预测模型。同时,为消除不同地区矿化度的影响,通过实验对比引入综合参数T",改良了输入神经元的配比。最终建立以半衰时Th、衰减度D、偏离度σ和综合参数T"为输入神经元的含水量预测模型,进一步提高了预测精度。通过检验,发现所建立的模型对平原地区进行含水量的定量预测有着较好的效果,为含水量预测工作研究与发展带来了新理念、打开了新思路。     

进化策略及其改进算法在深基坑支护优化设计中的应用研究

进化策略是一种新的求解全局最优问题的方法,应用该方法对深基坑支护结构进行了优化设计的初步研究。针对进化策略在处理非线性函数的优化问题及高维优化问题时在收敛速度和收敛性方面存在的不足,将禁止搜索与有向搜索相结合,提出了一种快速进化策略算法,有效地克服了传统进化策略的缺点。工程实例分析研究表明,进化策略不受设计空间的可微性、连续性等限制,特别适合于求解支护工程这类具有离散设计变量和非确定性因素的工程设计问题;改进的进化策略具有更好的收敛性,有极强的避免局部极值的全局优化能力。     

梯级水电站优化调度的分形与混沌嵌套搜索算法

考虑到梯级水电站水库联合优化调度模型的高非线性、强约束特点,提出了分形分割与混沌嵌套搜索算法的求解方法。该算法利用嵌套结构把确定性搜索和随机搜索有机结合起来,按照自身的运动规律,直接在优化区间内通过逐步的插值映射来对被优化问题进行优化搜索。通过在南桠河梯级水电站联合优化运行中的成功应用,显示该算法具有参数配置简单、普适性强、稳定性高、全局优化和易于编程等特点,并取得了与POA算法一致的收敛精度且计算速度有优势,从而为求解诸如水库优化调度等具有复杂约束条件的非线性优化问题提供了新的探索。     

Assessing water erosion in Mediterranean tree crops using GIS techniques and field measurements: the effect of climate change

In this work, a dynamic GIS modeling approach is presented that incorporates: a) geoinformatic techniques, b) 55-year historical meteorological data, and c) field measurements, in order to estimate soil erosion risk in intensively cultivated regions. The proposed GIS-based modeling approach includes the estimation of soil erosion rates due to surface water flow under current and future climate change scenarios A2 and B1 for the years 2030 and 2050. The soil erosion was estimated using the Universal Soil Loss Equation (USLE). The proposed soil erosion model was validated using field measurements at different sites of the study area. The results show that an extended part of the study area is under intense erosion with the mean annual loss to be 4.85 t/ha year⁻¹. Moreover, an increase in rainfall intensity, especially for scenario B1, can generate a significant increase (32.44 %) in soil loss for the year 2030 and a much more (50.77 %) for the year 2050 in comparison with the current conditions. Regarding the scenario A2, a slight decrease (1.85 %) in soil loss was observed for the year 2030, while for 2050 the results show an adequate increase (7.31 %) in comparison with the present. All these approaches were implemented at one of the most productive agricultural areas of Crete in Greece dominated by olive and citrus crops.

     

带岛屿约束的三角形空间剖分算法的改进方法

本文针对数值模拟中三角形有限元网格的具体要求，对经典的Bowyer-watson算法作了局部改进，利用具有岛屿约束的Delaunay剖分方法来构建三角形网格，使其适用于有岛屿、关键点和特征线约束的区域剖分的要求。此方法在（苏州，无锡，常州）以下简称苏锡常地区地下水流数值模拟中得到了应用，结果表明此方法自动生成带岛屿约束的三角形网格是可行的。     

Evaluating the accuracy of ANN and LR models to estimate the water quality in Zarivar International Wetland,Iran

One of the most important qualitative aspects of wetland ecosystem management is preserving the natural quality of water in such environments. This would not be achievable unless continuous water quality monitoring is implemented. With the recent advances in remote sensing technology, this technology could assist us to produce accurate models for estimating water quality variables in the ecosystem of wetlands. The present study was carried out to evaluate the capability of remote sensing data to estimate the water quality variables [pH, total suspended solids (TSS), total dissolved solids (TDS), turbidity, nitrate, sulfate, phosphate, chloride and the concentration of chlorophyll a] in Zarivar International Wetland using linear regression (LR) and artificial neural network (ANN) models. For this purpose, spectral reflectance of bands 2, 3, 4 and 5 of the OLI sensor of Landsat 8 was utilized as the input data and the collected chemical and physical data of water samples were selected as the objective data for both ANN and LR models. Based on our results overall, ANN model was the proper model compared with LR model. The spectral reflectance in bands 5 and 4 of OLI sensor revealed the best results to estimate TDS, TSS, turbidity and chlorophyll in comparison with other used bands in ANN model, respectively. We conclude that OLI sensor data are an excellent means for studying physical properties of water quality and comparing its chemical properties.     

Simultaneous optimization of the performance of flotation circuits and their simplification using the jumping gene adaptations of genetic algorithm

The elitist non-dominated sorting genetic algorithm with the modified jumping gene operator (NSGA-II-mJG) is used to optimize the performance of froth flotation circuits. Four example optimization problems (Mehrotra and Kapur, 1974; Green, 1984; Dey et al., 1989) [Mehrotra, S.P., Kapur, P.C., 1974. Optimal–sub-optimal synthesis and design of flotation circuits. Sep. Sci. 9, 167–184; Green, J.C.A., 1984. The optimization of flotation networks. Int. J. Miner. Process. 13, 83–103; Dey, A.K., Kapur, P.C., Mehrotra, S.P., 1989. A search strategy for optimization of flotation circuits. Int. J. Miner. Process. 26, 73-93.] of varying complexity are solved using single-objective functions. In one example, the overall recovery of the concentrate stream is maximized for a desired grade of the concentrate and a fixed total cell volume. The interconnecting cell linkage parameters (fraction flow rates) and the mean cell residence times are the decision variables. In all these cases, the optimal solutions obtained using NSGA-II-mJG are superior to those obtained by earlier techniques (which converged to local optimal solutions). Thereafter, a few two-objective optimization problems are solved. In these, the performance of the circuit is optimized, and simultaneously, the number of connecting streams is minimized so as to give simple circuits. Pareto optimal sets of equally good (non-dominating) solutions are obtained. This is probably the first study involving the multi-objective optimization of flotation circuits with one aim being to simplify them.     

日流量预测的小波网络模型初探

针对日流量时间序列的非线性和多时间尺度特性,提出了将小波分析与人工神经网络相结合进行日流量预测的新方法——小波网络模型。该模型吸取了小波分析的多分辨功能和人工神经网络的非线性逼近能力。以长江寸滩站日流量预测为例,研究表明,所构造的模型各预见期的拟合、检验精度较高。小波网络模型延长了预见期,提高了预报精度,具有广阔的应用前景。     

祁连山及河西走廊潜在蒸发量的时空变化

利用20个气象站1960-2006年的逐日气象资料,应用FAO Penman-Monteith模型,分析了祁连山及河西走廊潜在蒸发量的变化趋势,并在ArcGIS环境下通过Spline插值法分析了潜在蒸发量变化的空间分异,此外运用多元回归分析法对影响潜在蒸发量变化的主导因素进行了探讨。结果表明:祁连山及河西走廊的年潜在蒸发量在20世纪80年代之前偏高,之后偏低,在1967年之前呈减小趋势,之后呈增加趋势,1974年之后又呈减小趋势,1993年之后又呈增加趋势;年潜在蒸发量的年际变化率为-1.67mm,表明潜在蒸发量总体上呈减小趋势;从季节来看,秋季的潜在蒸发量呈增加趋势,其它季节呈减小趋势,其中春季的减小幅度最大;风速是影响潜在蒸发量变化的主导因素,影响秋季潜在蒸发量变化的主导因素是气温。     

基于最大特征值估计的C3算法及应用

第三代相干体算法(C3算法)具有分辨率高、压制噪声能力强的优点,但是该算法需要计算协方差矩阵的特征值,所以耗时较多。为提高大矩阵特征值分解的运算速度,提出了一种估计最大特征值的快速收敛算法,通过运用A2k矩阵的迹来构造一种收敛速度更快的特征值估计方法,并给出了这种方法的误差估计表达式,实现计算精度的有效控制。文中还讨论了地震数据体边缘补地震道方法,解决了将递推算法应用到平面方向时空间窗越过边界的问题。实例表明,本算法的计算效率明显高于常规的C3算法。     

基于GIS和RS的黔南喀斯特地区人居环境自然适应性评价

运用GIS和RS技术,建立包括地形起伏度、温湿指数、水文指数和植被指数的人居环境自然适宜性评价模型,系统评价黔南喀斯特地区人居环境自然适宜性与限制性。结果表明:①黔南喀斯特地区人居环境以临界适宜和一般适宜为主要特征,人居环境自然适宜程度大致呈现出由山地向丘陵、河谷、平原递增的趋势,其中43%的地区为一般适宜区,57%的地区为临界适宜区。②黔南州人居环境自然条件,包括地形、气候、水文和植被不同程度地对人口分布产生影响,其中气候对人口分布的限制性最强,其次是地形条件。科学评价黔南喀斯特地区人居环境自然适宜性,能够引导该区的功能定位、人口分布,促进人口与环境的协调发展。