Response surface and genetic method of deformation back analysis for high core rockfill dams

High core rockfill dams exhibit complex deformation mechanisms because of complicated geological conditions, many material partitions and severe weather conditions. When realistic parameters cannot be obtained through laboratory tests or engineering analogies because of effects of size or time, back analysis is necessary to predict deformation characteristics. This paper proposes a method of deformation back analysis based on the response surface method and genetic optimization theory. The parameters of the creep and Duncan–Chang models for the Pubugou gravelly soil core rockfill dam are sequentially calculated. Back analysis performed using this method efficiently yields more precise results than those obtained from laboratory-determined parameters.     

Sedimentology,clay mineralogy and grain-size as indicators of 65 ka of climate change from El’gygytgyn Crater Lake,Northeastern Siberia

El’gygytgyn Crater Lake, NE Siberia was investigated for sedimentological proxies for regional climate change with a focus on the past 65 ka. Sedimentological parameters assessed relative to magnetic susceptibility include stratigraphy, grain size, clay mineralogy and crystallinity. Earlier work suggests that intervals of high susceptibility in these sediments are coincident with warmer (interglacial-like) conditions and well-mixed oxygenated bottom waters. In contrast, low susceptibility intervals correlate with cold (glacial-like) conditions when perennial ice-cover resulted in anoxia and the dissolution of magnetic carrier minerals. The core stratigraphy contains both well-laminated to non-laminated sequences. Reduced oxygen and lack of water column mixing preserved laminated sequences in the core. A bioturbation index based upon these laminated and non- laminated sequences co-varies with total organic carbon (TOC) and magnetic susceptibility. Clay mineral assemblages include illite, highly inter-stratified illite/smectite, and chlorite. Under warm or hydrolyzing conditions on the landscape around the lake, chlorite weathers easily and illite/smectite abundance increase, which produces an inverse relationship in the relative abundance of these clays. Trends in relative abundance show distinct down-core changes that correlate with shifts in susceptibility. The mean grain-size (6.92 μm) is in the silt-size fraction, with few grains larger than 65 μm. Terrigenous input to the lake comes from over 50 streams that are filtered through storm berms, which limits clastic deposition into the lake system. The sedimentation rate and terrigenous input grain-size is reduced during glacial intervals. Measurements of particle-size distribution indicate that the magnetic susceptibility fluctuations are not related to grain size. Lake El’gygytgyn’s magnetic susceptibility and clay mineralogy preserves regional shifts in climate including many globally recognized␣events like the Younger Dryas and Bolling/Allerod. The sedimentary deposits reflect the climatic transitions starting with MIS4 through the Holocene transition. This work represents the first extensive sedimentological study of limnic sediment proxies of this age from Chukotka (Fig. 1). This is the tenth in a series of eleven papers published in this special issue dedicated to initial studies of El'gygytgyn Crater Lake and its catchment in NE Russia. Julie Brigham-Grette, Martin Melles, Pavel Minyuk were guest editors of this special issue.     

Evolutionary computation-based approach for model error correction and calibration

Calibration is typically used for improving the predictability of mechanistic simulation models by adjusting a set of model parameters and fitting model predictions to observations. Calibration does not, however, account for or correct potential misspecifications in the model structure, limiting the accuracy of modeled predictions. This paper presents a new approach that addresses both parameter error and model structural error to improve the predictive capabilities of a model. The new approach simultaneously conducts a numeric search for model parameter estimation and a symbolic (regression) search to determine a function to correct misspecifications in model equations. It is based on an evolutionary computation approach that integrates genetic algorithm and genetic programming operators. While this new approach is designed generically and can be applied to a broad array of mechanistic models, it is demonstrated for an illustrative case study involving water quality modeling and prediction. Results based on extensive testing and evaluation, show that the new procedure performs consistently well in fitting a set of training data as well as predicting a set of validation data, and outperforms a calibration procedure and an empirical model fitting procedure.     

Multiscale island injection genetic algorithms for groundwater remediation

Genetic algorithms have been shown to be powerful tools for solving a wide variety of water resources optimization problems. Applying these approaches to complex, large-scale water resources applications can be difficult due to computational limitations, especially when a numerical model is needed to evaluate different solutions. This problem is particularly acute for solving field-scale groundwater remediation design problems, where fine spatial grids are often needed for accuracy. Finer grids usually improve the accuracy of the solutions, but they are also computationally expensive. In this paper we present multiscale island injection genetic algorithms (IIGAs), in which the optimization algorithms have different multiscale populations working on different islands (groups of processors) and periodically exchanging information. This new approach is tested using a field-scale pump-and-treat design problem at the Umatilla Army Depot in Oregon, USA. The performance of several variations of this approach is compared with the results of a simple genetic algorithm. The new approach found the same solution as much as 81% faster than the simple genetic algorithm and 9–53% faster than other previously formulated multiscale strategies. These findings indicate substantial promise for multiscale IIGA approaches to improve solution of complex water resources applications at the field scale.     

基于遗传算法(GA)的地应力有限元反演研究

由于地应力的反演是一个不断逼近最优解的过程，计算量较大，收敛速度较慢。为解决该问题，本文引入遗传算法确定地应力反演中的边界条件，从而提高收敛速度。本文利用改进的反演算法确定河北平原区的边界条件，并在此基础上采用有限元方法计算出该地区的地应力。结果表明，本文提出的算法计算速度快、且其计算结果与地震机制解及活动断裂的分布具有良好的一致性。     

CLUSTERING ANALYSIS OF DEBRIS-FLOW STREAMS

The Chi-Chi earthquake in 1999 caused disastrous landslides, which triggered numerous debris flows and killed hundreds of people, A critical rainfall intensity line for each debris-flow stream is studied to prevent such a disaster. However, setting rainfall lines from incomplete data is difficult, so this study considered eight critical factors to group streams, such that streams within a cluster have similar rainfall lines. A genetic algorithm is applied to group 377 debris-flow streams selected from the center of an area affected by the Chi-Chi earthquake, These streams are grouped into seven clusters with different characteristics, The results reveal that the proposed method effectively groups debris-flow streams.     

Mineralogy and lithostratigraphy of Harris Lake,southwestern Saskatchewan,Canada

Harris Lake, a small, groundwater fed lake in the Cypress Hills area of Saskatchewan, is one of the few lacustrine basins in the Great Plains that contains a complete, uninterrupted record of Holocene sedimentation. The lithostratigraphy and variation in the mineralogical composition of the sediments in this basin provide insight into the paleolimnology and paleohydrology of the lake and surrounding watershed. Although there is no evidence that the basin was dry for extended periods during the Holocene, the lake did experience numerous short-lived episodes of high salinity, as well as significant changes in solute composition during the early to mid-Holocene. An abrupt change, from a lake dominated by detrital sediments to one characterized almost entirely by endogenic deposition, occurred about 4000 years ago in response to the combined influence of forestation of the watershed and diversion of major fluvial and detrital influx by landsliding. These adjustments to the Harris Lake drainage basin were likely the result of the onset of cooler and wetter climatic conditions after 4500 B.P. During the late Holocene, slope failure continued to sporadically provide fresh clastic material to the otherwise endogenic-sediment dominated lake.