东南沿海地震带的地震丛集窗及震级结构特征分析

基于东南沿海地震带的地震活动特点和构造背景, 确定了若干个地震活动特别集中的区域, 并引入地震丛集窗和震级结构的概念分析这些区域的局部特点。结果表明, 这些地震丛集窗的地震活动水平变化反映了所属大区的应力状态, 当某个地震丛集窗发生震级结构异常, 具备前兆震群特征的地震密集事件时, 该地震丛集窗内或其相关部位的介质性状可能发生了变化, 这对以后可能对应发生中强地震或强震具有一定的中期预测效能。     

断裂韧度试样CCNBD宽范围应力强度因子标定

国际岩石力学学会（ISRM）在1995年提出了一种新型岩石断裂韧度试样--人字形切槽巴西圆盘试样CCNBD,但是,其断裂韧度计算公式中的重要参数（即无量纲应力强度因子的标定）仍存在问题。采用一种新的分片合成方法并结合有限元法,参照ISRM给出的CCNBD试样的尺寸限制,对该范围试样的应力强度因子进行了宽范围的标定,以便在试验中能因地制宜地选用不同几何参数的CCNBD试样。结果表明：分片合成方法的计算值有很高的精度,不但减少了工作量,也使标定的无量纲应力强度因子比现有文献值更加准确、可靠。     

Multiple criteria rainfall–runoff model calibration using a parallel genetic algorithm in a cluster of computers / Calage multi-critères en modélisation pluie–débit par un algorithme génétique parallèle mis en œuvre par une grappe d'ordinateurs

Abstract

Genetic algorithms are among of the global optimization schemes that have gained popularity as a means to calibrate rainfall–runoff models. However, a conceptual rainfall–runoff model usually includes 10 or more parameters and these are interdependent, which makes the optimization procedure very time-consuming. This may result in the premature termination of the optimization process which will prejudice the quality of the results. Therefore, the speed of optimization procedure is crucial in order to improve the calibration quality and efficiency. A hybrid method that combines a parallel genetic algorithm with a fuzzy optimal model in a cluster of computers is proposed. The method uses the fuzzy optimal model to evaluate multiple alternatives with multiple criteria where chromosomes are the alternatives, whilst the criteria are flood performance measures. In order to easily distinguish the performance of different alternatives and to address the problem of non-uniqueness of optimum, two fuzzy ratios are defined. The new approach has been tested and compared with results obtained by using a two-stage calibration procedure. The current single procedure produces similar results, but is simpler and automatic. Comparison of results between the serial and parallel genetic algorithms showed that the current methodology can significantly reduce the overall optimization time and simultaneously improve the solution quality.     

Assessing SWAT's performance in the Kaskaskia River watershed as influenced by the number of calibration stations used

The Future Midwestern Landscapes (FML) project is part of the U.S. Environmental Protection Agency's Ecosystem Services Research Program. The goal of the FML project is to quantify changes in ecosystem services across the Midwestern region as a result of the growing demand for biofuels. Watershed models are an efficient way to quantify ecosystem services of water quality and quantity. By calibrating models, we can better capture watershed characteristics before they are applied to make predictions. The Kaskaskia River watershed in Illinois was selected to investigate the effectiveness of different calibration strategies (single‐site and multi‐site calibrations) for streamflow, total suspended sediment (TSS) and total nitrogen (TN) loadings using the Soil and Water Assessment Tool. Four USGS gauges were evaluated in this study. Single‐site calibration was performed from a downstream site to an upstream site, and multi‐site calibration was performed and fine‐tuned based on the single‐site calibration results. Generally, simulated streamflow and TSS were not much affected by different calibration strategies. However, when single‐site calibration was performed at the most downstream site, the Nash–Sutcliffe efficiency (NSE) values for TN ranged between ?0.09 and 0.53 at the other sites; and when single‐site calibration was performed at the most upstream site, the NSE values ranged between ?8.38 and ?0.07 for the other sites. The NSE values for TN were improved to 0.5 – 0.59 for all four sites when multi‐site calibration was performed. The results of the multi‐site calibration and validation showed an improvement on model performance on TN and highlighted that multi‐site calibrations are needed to assess the hydrological and water quality processes at various spatial scales. Copyright © 2012 John Wiley & Sons, Ltd.     

Simulation of stream flow components in a mountainous catchment in northern Thailand with SWAT,using the ANSELM calibration approach

Highland agriculture is intensifying rapidly in South‐East Asia, leading to alarmingly high applications of agrochemicals. Understanding the fate of these contaminants requires carefully planned monitoring programmes and, in most cases, accurate simulation of hydrological pathways into and through water bodies. We simulate run‐off in a steep mountainous catchment in tropical South‐East Asia. To overcome calibration difficulties related to the mountainous topography, we introduce a new calibration method, named A Nash–Sutcliffe Efficiency Likelihood Match (ANSELM), that allows the assignment of optimal parameters to different hydrological response units in simulations of stream discharge with the Soil and Water Assessment Tool (SWAT) hydrological model. ANSELM performed better than the Parasol calibration tool built into SWAT in terms of model efficiency and computation time. In our simulation, the most sensitive model parameters were those related to base flow generation, surface run‐off generation, flow routing and soil moisture change. The coupling of SWAT with ANSELM yielded reasonable simulations of both wet‐season and dry‐season storm hydrographs. Nash–Sutcliffe model efficiencies for daily stream flow during two validation years were 0.77 and 0.87. These values are in the upper range or even higher than those reported for other SWAT model applications in temperate or tropical regions. The different flow components were realistically simulated by SWAT, and showed a similar behaviour in all the study years, despite inter‐annual climatic differences. The realistic partitioning of total stream flow into its contributing components will be an important factor for using this hydrological model to simulate solute transport in the future. Copyright © 2014 John Wiley & Sons, Ltd.     

Automatic calibration of HEC‐HMS using single‐objective and multi‐objective PSO algorithms

This study presents single‐objective and multi‐objective particle swarm optimization (PSO) algorithms for automatic calibration of Hydrologic Engineering Center‐ Hydrologic Modeling Systems rainfall‐runoff model of Tamar Sub‐basin of Gorganroud River Basin in north of Iran. Three flood events were used for calibration and one for verification. Four performance criteria (objective functions) were considered in multi‐objective calibration where different combinations of objective functions were examined. For comparison purposes, a fuzzy set‐based approach was used to determine the best compromise solutions from the Pareto fronts obtained by multi‐objective PSO. The candidate parameter sets determined from different single‐objective and multi‐objective calibration scenarios were tested against the fourth event in the verification stage, where the initial abstraction parameters were recalibrated. A step‐by‐step screening procedure was used in this stage while evaluating and comparing the candidate parameter sets, which resulted in a few promising sets that performed well with respect to at least three of four performance criteria. The promising sets were all from the multi‐objective calibration scenarios which revealed the outperformance of the multi‐objective calibration on the single‐objective one. However, the results indicated that an increase of the number of objective functions did not necessarily lead to a better performance as the results of bi‐objective function calibration with a proper combination of objective functions performed as satisfactorily as those of triple‐objective function calibration. This is important because handling multi‐objective optimization with an increased number of objective functions is challenging especially from a computational point of view. Copyright © 2012 John Wiley & Sons, Ltd.     

Watershed modelling of hydrology and water quality in the Sacramento River watershed,California

Agricultural pollutant runoff is a major source of water contamination in California's Sacramento River watershed where 8500 km² of agricultural land influences water quality. The Soil and Water Assessment Tool (SWAT) hydrology, sediment, nitrate and pesticide transport components were assessed for the Sacramento River watershed. To represent flood conveyance in the area, the model was improved by implementing a flood routing algorithm. Sensitivity/uncertainty analyses and multi‐objective calibration were incorporated into the model application for predicting streamflow, sediment, nitrate and pesticides (chlorpyrifos and diazinon) at multiple watershed sites from 1992 to 2008. Most of the observed data were within the 95% uncertainty interval, indicating that the SWAT simulations were capturing the uncertainties that existed, such as model simplification, observed data errors and lack of agricultural management data. The monthly Nash–Sutcliffe coefficients at the watershed outlet ranged from 0.48 to 0.82, indicating that the model was able to successfully predict streamflow and agricultural pollutant transport after calibration. Predicted sediment loads were highly correlated to streamflow, whereas nitrate, chlorpyrifos and diazinon were moderately correlated to streamflow. This indicates that timing of agricultural management operations plays a role in agricultural pollutant runoff. Best management practices, such as pesticide use limits during wet seasons, could improve water quality in the Sacramento River watershed. The calibrated model establishes a modelling framework for further studies of hydrology, water quality and ecosystem protection in the study area. Copyright © 2012 John Wiley & Sons, Ltd.     

MVO曲线方法在海洋可控源电磁数值模拟中的应用研究

采用有限差分方法,对水平电偶极子源在海洋二维介质情况下电磁响应进行数值模拟。利用油气高阻异常体模型的数值模拟结果,研究MVO(Magnitude Versus Offset)曲线解释方法的有效性,进而分析高阻油气异常体的水平位置的变化,对电场和磁场幅值的MVO曲线产生的影响,得出了通过MVO曲线定性分析高阻油气异常体相对水平位置的方法。本研究可为海洋可控源电磁法数据的定性分析提供部份理论依据。