Applying genetic algorithms for calibrating a hexagonal cellular automata model for the simulation of debris flows characterised by strong inertial effects

In modelling complex a-centric phenomena which evolve through local interactions within a discrete time-space, cellular automata (CA) represent a valid alternative to standard solution methods based on differential equations. Flow-type phenomena (such as lava flows, pyroclastic flows, earth flows, and debris flows) can be viewed as a-centric dynamical systems, and they can therefore be properly investigated in CA terms.SCIDDICA S_4a is the last release of a two-dimensional hexagonal CA model for simulating debris flows characterised by strong inertial effects. S_4a has been obtained by progressively enriching an initial simplified model, originally derived for simulating very simple cases of slow-moving flow-type landslides.Using an empirical strategy, in S_4a, the inertial character of the flowing mass is translated into CA terms by means of local rules. In particular, in the transition function of the model, the distribution of landslide debris among the cells is obtained through a double cycle of computation. In the first phase, the inertial character of the landslide debris is taken into account by considering indicators of momentum. In the second phase, any remaining debris in the central cell is distributed among the adjacent cells, according to the principle of maximum possible equilibrium.The complexities of the model and of the phenomena to be simulated suggested the need for an automated technique of evaluation for the determination of the best set of global parameters. Accordingly, the model is calibrated using a genetic algorithm and by considering the May 1998 Curti–Sarno (Southern Italy) debris flow.The boundaries of the area affected by the debris flow are simulated well with the model. Errors computed by comparing the simulations with the mapped areal extent of the actual landslide are smaller than those previously obtained without genetic algorithms. As the experiments have been realised in a sequential computing environment, they could be improved by adopting a parallel environment, which allows the performance of a great number of tests in reasonable times.     

Deformation history inferred from magnetic fabric in the southwestern Okcheon metamorphic belt, Korea

Magnetic fabric and rock-magnetic studies have been carried out for the non-fossiliferous, low- to medium-grade metasedimentary rocks in the southwestern part of the Okcheon metamorphic belt (OMB). Two major metamorphic events in the study area were previously recognized: regional metamorphism (M₁) in the late Carboniferous to early Permian and contact metamorphism (M₂) due to the intrusion of granite in the middle Jurassic. The metamorphic grade of the study area increases from the biotite zone in southeast through the garnet zone to the staurolite zone towards the northwest. Magnetic fabrics of the study area are generally well defined and can be characterized according to the metamorphic zones. Magnetic foliation is the dominant magnetic fabric in the biotite zone, while magnetic lineation prevails in both garnet and staurolite zones. We interpret the metamorphism-related deformation history of the study area based on magnetic fabrics, magnetic mineralogy and previously reported metamorphic evolution as follows. Penetrative NW-dipping cleavage, represented by magnetic foliation, was formed in the study area by prevailing NW–SE shortening event during the M₁ regional metamorphism in the late Carboniferous–early Permian. This shortening event is interpreted to be associated with the collisional event between the North and South China blocks. Cleavages dipping steeply to the southeast in the staurolite zone are attributed to the pressure exerted from the intrusion of Jurassic granite in the northwestern area.     

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.     

Curie Temperature Analyses of Upper Jurassic and Lower Cretaceous Pelagic Limestones

Summary. Magnetic extracts were prepared from samples of Upper Jurassic and Lower Cretaceous pelagic limestones from France and Spain. Thermomagnetic analysis of the magnetic extracts using a microbalance required careful monitoring of base weight changes during heating. Heating in argon gas atmosphere induced production of magnetite during heating while slight oxidation occurred during heating in air. the dominant Curie temperature detected by the thermomagnetic analyses was the 585°C Curie temperature of magnetite. the 680°C Curie temperature of haematite was only detected when isothermal remanent magnetism (IRM) data indicated large concentrations of haematite. Even when IRM data indicated its presence, the thermomagnetic analyses did not detect the Neel temperature of goethite. Although thermomagnetic analyses of magnetic extracts provide more direct identification of the dominant, strongly ferromagnetic minerals, IRM acquisition and subsequent thermal demagnetization is a superior technique in detecting high coercivity, weakly ferromagnetic minerals such as goethite and haematite.     

Using a genetic algorithm for 3-D inversion of gravity data in Fuerteventura (Canary Islands)

The use of genetic algorithms in geophysical inverse problems is a relatively recent development and offers many advantages in dealing with the non-linearity inherent in such applications. We have implemented a genetic algorithm to efficiently invert a set of gravity data. Employing several fixed density contrasts, this algorithm determines the geometry of the sources of the anomaly gravity field in a 3-D context. The genetic algorithms, based on Darwins theory of evolution, seek the optimum solution from an initial population of models, working with a set of parameters by means of modifications in successive iterations or generations. This searching method traditionally consists of three operators (selection, crossover and mutation) acting on each generation, but we have added a further one, which smoothes the obtained models. In this way, we have designed an efficient inversion gravity method, confirmed by both a synthetic example and a real data set from the island of Fuerteventura. In the latter case, we identify crustal structures related to the origin and evolution of the island. The results show a clear correlation between the sources of gravity field in the model and the three volcanic complexes recognized in Fuerteventura by other geological studies.     

Quantitative discrimination between magmatic units of the singhbhum granite

The weight-percent values of four mineralogic variables (quartz, K feldspar, color index, and muscovite) for 10 sets of granitic rocks (20–50 samples in each set) from magmatic units of the Singhbhum granite were used for (1) computation of the Mahalanobis' generalized distance functions (D ²) between all pairs of the 10 sets, (2) testing significance of the difference between the multivariate means, and (3) computation of the linear discriminant functions between all possible pairs of the sets. The 10 data sets are for six magmatic units which belong to three successive but closely related phases of emplacement. The multivariate means for all sets are significantly different except for those between two of the sets of phase I. Cluster analysis on the basis of theD ² values enables the 10 sets to be placed into four distinct groups. Group A includes two subgroups, one of which consists of two sets representing typical members of phase I; the other subgroup includes two sets which are typical of phase II. Group B includes two sets which are typical of phase III. The other four sets do not group with the typical representatives of the three phases, probably because of certain special conditions of their emplacement. A separate series ofD ² computation from the same data, but excluding the color index, was unsuccessful in making the four aberrant sets group with the typical members of the respective phases. Efficient LDF's could be determined for discrimination between most pairs of the 10 sets of granite rocks.