Assessment of temporal dynamics of snow cover and its validation with hydro-meteorological data in parts of Chenab Basin,western Himalayas

The present investigation was conducted to analyze the temporal patterns of snow cover area%(SCA%), air temperature, snowfall and river discharge in parts of Chenab basin, western Himalayas. The relationship of mean SCA% with mean air temperature and river discharge was also tested using Pearson's product-moment correlation at 95% confidence limit and further sensitivity analysis of river discharge to SCA and SCA to air temperature was performed. Moderate Resolution Imaging Spectroradiometer(MODIS) 8-day surface reflectance product MOD09A1 was used to delineate SCA during the period 2000–2013. Moreover, variation in the lowest elevation from where snow cover area starts(LESCA) was also analyzed and its relationship with mean air temperature was also studied. Non-parametric method, Mann-Kendall test was employed to determine the trend in the SCA%, air temperature, snowfall and river discharge. The investigation carried out for three meteorological stations i.e. Batote, Reasi and Tandi revealed significant findings. At Batote and Reasi, statistically significant decreasing trends were observed over the period 2000 to 2012, for maximum, minimum and mean air temperature. Mean minimum SCA% exhibited a significant upward trend during 2000–2013 which is corroborated by the significantly increasing trend of mean annual snowfall(Tandi station) from 2000 to 2010. Further, significant decreasing trend of river discharge for the winter season at Batote station from 2000 to 2011 and decreasing trends in the maximum, minimum and mean air temperature at Batote and Reasi stations are also consistent with the increasing trend of SCA%. At both Batote and Reasi stations, mean SCA% exhibited significant negative relationship with the mean air temperature. On the other hand, LESCA exhibited positive correlation with the mean air temperature except in a few months, where negative relationship was seen. Sensitivity analysis of river discharge to SCA exhibited very low values of sensitivity coefficient in most of the months, indicating less sensitivity of river discharge to SCA. On the other hand, sensitivity coefficient of SCA to air temperature exhibited comparatively higher values which indicate SCA is more sensitive to air temperature.     

煤矿微震监测台网优化布设研究

煤矿冲击矿压现象日益严峻,作为矿山动力灾害的主要监测手段,微震监测系统已在许多矿井广泛使用,为保证矿震定位和能量计算的准确,提高预测预报煤矿冲击矿压的可行性,应建立一套台网布设优化及评价系统.应用微震定位和D值优化设计理论,结合煤矿实际条件研究了影响矿震定位精度的主要因素和不利条件,并提出了采用综合指数法确定煤矿高微震活动区域和区域内矿震发生的概率,制定了台站候选点和监测区域确定的一般原则.通过理论分析震中和震源标准差反映台网定位能力的不足,建立基于数值仿真实验方法的震中与震源误差期望值模型,最终形成台网布设优化及评价系统.实验和现场应用结果表明,该系统能够快速确定台网最优布设方案,准确评价台网定位能力,满足煤矿微震监测的需要.     

区域台网地震监测能力评估算法的Matlab实现

采用近震震级公式方法,在已知台站噪声水平和震中距的情况下,计算出该台能记录到的最小地震震级,在震中距最近的6个台中,通过组合排序法选取布局最优的4个台进行定位,并取这4个台站中震级最大值作为最小监测能力震级,从而得到局域台网的地震监测能力。运用Matlab软件来实现该算法,并对其中的核心处理技巧进行说明。     

Partially constrained ant colony optimization algorithm for the solution of constrained optimization problems: Application to storm water network design

This paper exploits the unique feature of the Ant Colony Optimization Algorithm (ACOA), namely incremental solution building mechanism, to develop partially constraint ACO algorithms for the solution of optimization problems with explicit constraints. The method is based on the provision of a tabu list for each ant at each decision point of the problem so that some constraints of the problem are satisfied. The application of the method to the problem of storm water network design is formulated and presented. The network nodes are considered as the decision points and the nodal elevations of the network are used as the decision variables of the optimization problem. Two partially constrained ACO algorithms are formulated and applied to a benchmark example of storm water network design and the results are compared with those of the original unconstrained algorithm and existing methods. In the first algorithm the positive slope constraints are satisfied explicitly and the rest are satisfied by using the penalty method while in the second one the satisfaction of constraints regarding the maximum ratio of flow depth to the diameter are also achieved explicitly via the tabu list. The method is shown to be very effective and efficient in locating the optimal solutions and in terms of the convergence characteristics of the resulting ACO algorithms. The proposed algorithms are also shown to be relatively insensitive to the initial colony used compared to the original algorithm. Furthermore, the method proves itself capable of finding an optimal or near-optimal solution, independent of the discretisation level and the size of the colony used.     

重点地震监视区敏感台站的识别研究

识别显著影响重点监视区地震检测能力的“敏感台站”, 对有针对性地开展地震台网运行维护和加强相关区域天然地震与非天然地震的监视跟踪工作有重要意义。 利用基于概率的最小完整性震级(PMC)方法, 通过对研究区地震台站进行“检测能力评分”(Dscore)和“缺失评分”(Missing Score)方式进行识别研究, 以龙门山断裂南段强震危险区为例的重点监视区“敏感台站”识别结果表明, 研究区内51个台站的“检测能力评分”及“缺失评分”, 可识别对重点监视区地震检测能力影响最大的台站, 给出台站停止运行引起的最小完整性震级的变化, 并探讨了多台站停止运行等造成影响的极限情况。 上述“敏感台站”的识别方式, 可为地震台网运行维护、 针对特定目标区的地震监视跟踪和进一步的台网优化改造提供参考。     

Estimation of efficiency of the modern and planning optimal network of seismic stations within the Vietnam territory

Efficiency of the modern network of seismological observations in Vietnam is estimated, and an optimal design of planning network, consisted of 14 seismic stations is proposed. At the same sensitivity of network, but with a less number of stations, the new network would enable to determine hypocenter parameters in a more precise at a more uniform distribution of errating band within observation area.     

Raingauge network optimization in a tropical urban area by coupling cross-validation with the geostatistical technique

An adequate and reliable raingauge network is essential for observing rainfall data in hydrology and water resource applications. A raingauge network developed for a catchment area is commonly extended periodically to increase data accuracy. Due to financial constraints, the network is reviewed for the optimal number of stations. A new optimization approach is developed in this study by coupling a cross-validation technique with a geostatistical method for raingauge network optimization to prioritize raingauge stations. The spatial interpolation error of the spatial rainfall distribution, measured as the root mean square error (E_rms) optimization criterion is applied to a raingauge network in a tropical urban area. The results indicate that this method can successfully optimize the number of rainfall stations in an existing raingauge network, as the stations are prioritized based on their importance in the network.     

Improving the reliability of groundwater monitoring networks using combined numerical,geostatistical and neural network-based simulation models

ABSTRACT

A new methodology is proposed for improving the accuracy of groundwater-level estimations and increasing the efficiency of groundwater-level monitoring networks. Three spatio-temporal (S-T) simulation models, numerical groundwater flow, artificial neural network and S-T kriging, are implemented to simulate water-table level variations. Individual models are combined using model fusion techniques and the more accurate of the individual and combined simulation models is selected for the estimation. Leave-one-out cross-validation shows that the estimation error of the best fusion model is significantly less than that of the three individual models. The selected fusion model is then considered for optimal S-T redesign of the groundwater monitoring network of the Dehgolan Plain (Iran). Using a Bayesian maximum entropy interpolation technique, soft data are included in the geostatistical analyses. Different scenarios are defined to incorporate economic considerations and different levels of precision in selecting the best monitoring network; a network of 37 wells is proposed as the best configuration. The mean variance estimation errors of all scenarios decrease significantly compared to that of the existing monitoring network. A reduction in equivalent uniform annual costs of different scenarios is achieved.     

Thermal, pressure and wind fields at ground level in the area of the Italian base at Terra Nova Bay, Victoria Land, Antarctica, as observed by a network of automatic weather stations

Ground temperature, pressure and wind speed monthly averages in the area of the Italian Station at Terra Nova Bay, Antarctica, were analyzed for the period 1987–1991 by means of a network of nine AWS (automatic weather stations). Spatial configurations of temperature show a well-defined, relatively warm island in the area of Terra Nova Bay, between Drygalsky and Campbell ice tongues, throughout the year. A second warm island is present to the north along the coast, between Aviator and Mariner ice tongues, for most of the year. From February to March a rapid drop in temperature is observed at all stations. A strong thermal gradient develops during February, March, April and October, November, December, between the coastal region and inner highlands. The baric configuration follows the elevation of the area. Annual average pressure and temperature as functions of stations altitude show linear trends. Severe katabatic wind episodes are recorded at all stations, with wind speed exceeding 25 ms^–1 and direction following the orographic features of the inner areas. Co-occurrences of these episodes were observed for stations located along stream lines of cold air drainage. The autocorrelation function of maximum wind speed time series shows wind persistence of 2–3 days and wind periodicity of about one week.     

地震阈值监测技术的研究与应用

阈值监测技术是一种利用地震台站实时数据反映台网监测能力变化的方法。对台站数据进行预处理后,计算短时平均值STA作为信号能量的估计来计算震级,由概率统计方法实现对地震台网监测能力变化的动态监测。文中给出了利用短时平均值STA和震中距计算震级的公式;采用新疆地区部分地震台站的数据,并以新疆地震目录给定的ML为准,对相关的地震台站计算震级所需参数进行了标定;最后结合实例说明定点阈值监测技术的应用,分析了新疆专用地震台网在某一时间段内对定点区域的监测能力。     

甘肃祁连山主动源不同枪组激发效果对比

大容量气枪震源激发探测因具绿色环保、传播距离远和高度重复性等特点成为地下介质探测的新方法,利用其进行地下介质物性变化高精度探测,则对不同激发条件下气枪传播信号的一致性提出要求。本文选取了祁连山主动源不同枪组（4支和3支气枪）在激发环境一致情况下分别激发时各远台波形记录,通过信号叠加、互相关及频谱分析等方法,对比分析了各台站记录的不同枪组激发信号,及其与震中距的关系,并讨论了不同枪组激发对地下介质走时变化观测的影响。结果表明：（1）不同枪组的激发信号波形相关度随震中距增大而降低,信号震相随激发能量有微弱的变化,震中距超过50 km后其变化几乎分辨不出;（2）远台接收信号的能量大小随主动源激发能量变化,各台站能量变化主要体现在优势频率范围内;（3）接收台站台基越坚固不同激发能量均方根振幅比越小;（4）叠加一定数量的波形可以有效提高远台记录信号的信噪比,增加气枪激发能量则相对更容易提高信号信噪比。     

Dimensionality reduction in drought modelling

For monitoring hydrological events characterized by high spatial and temporal variability, the number and location of recording stations must be carefully selected to ensure that the necessary information is collected. Depending on the characteristics of each natural process, certain stations may be spurious or redundant, whereas others may provide most of the relevant data. With the objective of reducing the costs of the monitoring system and, at the same time, improving its operational effectiveness, three procedures were applied to identify the minimum network of rain gauge stations able to capture the characteristics of droughts in mainland Portugal. Drought severity is characterized by the standardized precipitation index applied to the timescales of 1, 3, 6 and 12 consecutive months. The three techniques used to reduce the dimensionality of the network of rain gauges were as follows: (i) artificial neural networks with sensitivity analysis, (ii) application of the mutual information criterion and (iii) K‐means cluster analysis using Euclidean distances. The results demonstrated that the best dimensionality reduction method was case dependent in the three regions of Portugal (northern, central and southern) previously identified by cluster analysis. All the reduction techniques lead to the selection of a subset of rain gauges capable of reproducing the original temporal patterns of drought. For specific severe drought events in Portugal in the past, the comparison between drought spatial patterns obtained with the original stations and the selected subset indicated that the subset produced statistically satisfactory results (correlation coefficients higher than 0.6 and efficiency coefficients higher than 0.5). Copyright © 2012 John Wiley & Sons, Ltd.     

基于PMC方法的上海测震台网地震监测能力评估

采用基于概率的完整性震级（PMC）方法,选取上海测震台网13个地震台站及周边省市地震台2008-2019年记录的171个地震,计算各地震台及上海测震台网地震监测能力,并模拟增加新的地震台站后台网监测能力的变化。结果显示：①地表基岩台的监测能力较深井台强,且受噪声和地铁影响,市区深井台监测能力较低;②整体上,台站密布的松江和青浦地区,地震监测能力较强,最小完整性震级为M_L 0.7。台站稀疏的浦东、奉贤、崇明地区,地震监测能力较弱,最小完整性震级为M_L 1.3;③若在上海南部增设奉贤海湾台,可整体提高上海测震台网的监测能力。     

Surface wave tomography method based on data from distant earthquakes

The standard method of surface wave tomography assumes the use of data on surface wave velocities measured on paths wholly located inside the region being investigated and oriented in different directions. If the data on group velocities obtained in the regional network of stations are used for this purpose, then the earthquake sources also should be situated within the limits of this region. If the region is small, then this requirement restricts the range of periods of surface waves and, correspondingly, the depth of research. The use of data from distant earthquakes enlarges the range of periods. However, it does not enable one to use the usual tomography method because of an inappropriate configuration of the system of paths: outside of the region in which the stations are located, the paths do not intersect, but, at the same time, the paths from a particular earthquake source toward the different stations of networks are very close over a large distance, and the mean correction to the velocity in the path sections outside of the network of stations can be accepted as identical. This assumption forms the basis of the proposed modification of the method of surface wave tomography, in which group velocities measured at stations of the local network from distant earthquakes are used. The lateral variations in the velocity are determined within the limits of the network, and the mean corrections to the velocity are determined on the paths from different earthquake sources in the sections outside of the network. As earlier, the condition of smoothness is imposed on the distribution of velocity variations, and the condition of smallness of the sum of their squares is imposed on the values of the corrections to the velocity. Testing of this method based on model examples and on real data obtained in the network of stations in Tibet showed its advantage over the standard tomography method.     

内蒙古区域地震台网监测能力研究

国际上新近发展的“基于概率的完整性震级”(PMC)方法,具有可考察地震定位中由于台站人为选择等造成的台网监测能力下降,以及避免传统基于G-R关系的统计算法因地震数目过少而无法评估等优点.本研究利用PMC方法,计算得到内蒙古区域地震台网39个台站对周边地震事件的检测概率及台网检测概率.单台检测概率结果显示:PMC方法能够客观地反映39个台站对地震事件的检测能力;因台网布局等影响,内蒙古区域地震台网中西部和中东部地区的台站检测能力较强,而靠近蒙古、俄罗斯边境的台站, 阿拉善右旗附近地区的台站,以及邻近吉林、黑龙江等地区的台站检测能力较低.合成检测概率结果显示,由于邻省台站的引入,全区80%的地区基于概率的最小完整性震级M_P达到2.2左右,其余地区M_P达到3.3左右.为提高地震台网监测能力,建议在监测能力较弱的中蒙交界地区、东北部地区,以及阿拉善左旗以西地区适度加密台站,进一步优化台网布局.      

Detection capability of seismic network based on noise analysis and magnitude of completeness

Assessing the detection threshold of seismic networks becomes of increased importance namely in the context of monitoring induced seismicity due to underground operations. Achieving the maximum possible sensitivity of industrial seismic monitoring is a precondition for successful control of technological procedures. Similarly, the lowest detection threshold is desirable when monitoring the natural seismic activity aimed to imaging the fault structures in 3D and to understanding the ongoing processes in the crust. We compare the application of two different methods to the data of the seismic network WEBNET that monitors the earthquake swarm activity of the West-Bohemia/Vogtland region. First, we evaluate the absolute noise level and its possible non-stationary character that results in hampering the detectability of the seismic network by producing false alarms. This is realized by the statistical analysis of the noise amplitudes using the ratio of 99 and 95 percentiles. Second, the magnitude of completeness is determined for each of the nine stations by analysing the automatic detections of an intensive swarm period from August 2011. The magnitude–frequency distributions of all detected events and events detected at individual stations are compared to determine the magnitude of completeness at a selected completeness level. The resulting magnitude of completeness M _c of most of the stations varies between ?0.9 and ?0.5; an anomalous high M _c of 0.0 is found at the most distant station, which is probably due to inadequate correction for attenuation. We find that while the absolute noise level has no significant influence to the station sensitivity, the noise stationarity correlates with station sensitivity expressed in low magnitude of completeness and vice versa. This qualifies the method of analysing the stationary character of seismic noise as an effective tool for site surveying during the seismic station deployment.     

Frequency analysis of droughts using the Plackett copula and parameter estimation by genetic algorithm

This study aims to model the joint probability distribution of drought duration, severity and inter-arrival time using a trivariate Plackett copula. The drought duration and inter-arrival time each follow the Weibull distribution and the drought severity follows the gamma distribution. Parameters of these univariate distributions are estimated using the method of moments (MOM), maximum likelihood method (MLM), probability weighted moments (PWM), and a genetic algorithm (GA); whereas parameters of the bivariate and trivariate Plackett copulas are estimated using the log-pseudolikelihood function method (LPLF) and GA. Streamflow data from three gaging stations, Zhuangtou, Taian and Tianyang, located in the Wei River basin, China, are employed to test the trivariate Plackett copula. The results show that the Plackett copula is capable of yielding bivariate and trivariate probability distributions of correlated drought variables.     

A comparative study of Monte Carlo simple genetic algorithm and noisy genetic algorithm for cost-effective sampling network design under uncertainty

This study evaluates and compares two methodologies, Monte Carlo simple genetic algorithm (MCSGA) and noisy genetic algorithm (NGA), for cost-effective sampling network design in the presence of uncertainties in the hydraulic conductivity (K) field. Both methodologies couple a genetic algorithm (GA) with a numerical flow and transport simulator and a global plume estimator to identify the optimal sampling network for contaminant plume monitoring. The MCSGA approach yields one optimal design each for a large number of realizations generated to represent the uncertain K-field. A composite design is developed on the basis of those potential monitoring wells that are most frequently selected by the individual designs for different K-field realizations. The NGA approach relies on a much smaller sample of K-field realizations and incorporates the average of objective functions associated with all K-field realizations directly into the GA operators, leading to a single optimal design. The efficacy of the MCSGA-based composite design and the NGA-based optimal design is assessed by applying them to 1000 realizations of the K-field and evaluating the relative errors of global mass and higher moments between the plume interpolated from a sampling network and that output by the transport model without any interpolation. For the synthetic application examined in this study, the optimal sampling network obtained using NGA achieves a potential cost savings of 45% while keeping the global mass and higher moment estimation errors comparable to those errors obtained using MCSGA. The results of this study indicate that NGA can be used as a useful surrogate of MCSGA for cost-effective sampling network design under uncertainty. Compared with MCSGA, NGA reduces the optimization runtime by a factor of 6.5.     

Local seismic network for monitoring of a potential nuclear power plant area

This study presents a plan for seismic monitoring of a region around a potential nuclear power plant. Seismic monitoring is needed to evaluate seismic risk. The International Atomic Energy Agency has set guidelines on seismic hazard evaluation and monitoring of such areas. According to these guidelines, we have made a plan for a local network of seismic stations to collect data for seismic source characterization and seismotectonic interpretations, as well as to monitor seismic activity and natural hazards. The detection and location capability of the network were simulated using different station configurations by computing spatial azimuthal coverages and detection threshold magnitudes. Background noise conditions around Pyhäjoki were analyzed by comparing data from different stations. The annual number of microearthquakes that should be detected with a dense local network centered around Pyhäjoki was estimated. The network should be dense enough to fulfill the requirements of azimuthal coverage better than 180° and automatic event location capability down to ML?～?0 within a distance of 25 km from the site. A network of 10 stations should be enough to reach these goals. With this setup, the detection threshold magnitudes are estimated to be ML?=??0.1 and ML?=?0.1 within a radius of 25 and 50 km from Pyhäjoki, respectively. The annual number of earthquakes detected by the network is estimated to be 2 (ML?≥?～ ?0.1) within 25 km radius and 5 (ML?≥?～?0.1 to ～0.1) within 50 km radius. The location accuracy within 25 km radius is estimated to be 1–2 and 4 km for horizontal coordinates and depth, respectively. Thus, the network is dense enough to map out capable faults with horizontal accuracy of 1–2 km within 25 km radius of the site. The estimation is based on the location accuracies of five existing networks in northern Europe. Local factors, such as seismic noise sources, geology and infrastructure might limit the station configuration and detection and location capability of the network.     

A combined simulation–genetic algorithm optimization model for optimal rule curves of a reservoir: a case study of the Nam Oon Irrigation Project,Thailand

A combined simulation–genetic algorithm (GA) optimization model is developed to determine optimal reservoir operational rule curves of the Nam Oon Reservoir and Irrigation Project in Thailand. The GA and simulation models operate in parallel over time with interactions through their solution procedure. A GA is selected as an optimization model, instead of traditional techniques, owing to its powerful and robust performance and simplicity in combining with a simulation technique. A GA is different from conventional optimization techniques in the way that it uses objective function information and does not require its derivatives, whereas in real‐world optimization problems the search space may include discontinuities and may often include a number of sub‐optimum peaks. This may cause difficulties for calculus‐based and enumerative schemes, but not in a GA. The simulation model is run to determine the net system benefit associated with state and control variables. The combined simulation–GA model is applied to determine the optimal upper and lower rule curves on a monthly basis for the Nam Oon Reservoir, Thailand. The objective function is maximum net system benefit subject to given constraints for three scenarios of cultivated areas. The monthly release is calculated by the simulation model in accordance with the given release policy, which depends on water demand. The optimal upper and lower rule curves are compared with the results of the HEC‐3 model (Reservoir System Analysis for Conservation model) calculated by the Royal Irrigation Department, Thailand, and those obtained using the standard operating policy. It was found that the optimal rule curves yield the maximum benefit and minimum damages caused by floods and water shortages. The combined simulation–GA model shows an excellent performance in terms of its optimization results and efficient computation. Copyright © 2007 John Wiley & Sons, Ltd.