Chen, Yanguang
2015-01-01
An analogy between the fractal nature of networks of arteries and that of systems of rivers has been drawn in the previous works. However, the deep structure of the hierarchy of blood vessels has not yet been revealed. This paper is devoted to researching the fractals, allometric scaling, and hierarchy of blood vessels. By analogy with Horton-Strahler's laws of river composition, three exponential laws have been put forward. These exponential laws can be reconstructed and transformed into three linear scaling laws, which can be named composition laws of blood vessels network. From these linear scaling laws it follows a set of power laws, including the three-parameter Zipf's law on the rank-size distribution of blood vessel length and the allometric scaling law on the length-diameter relationship of blood vessels in different orders. The models are applied to the observed data on human beings and animals early given by other researchers, and an interesting finding is that human bodies more conform to natural r...
Directory of Open Access Journals (Sweden)
Leandro Redin Vestena
2010-08-01
Full Text Available Os objetivos deste trabalho foram estimar e avaliar a dimensão fractal da rede de drenagem da bacia hidrográfica do Caeté, em Alfredo Wagner, SC, a partir de diferentes métodos, com o propósito de caracterizar as formas geomorfológicas irregulares. A rede de drenagem apresenta propriedades multifractais. As dimensões fractais para os segmentos individuais (df e para a rede de drenagem inteira (Df foram determinadas por métodos que se fundamentaram nas razões de Horton e pelo método da contagem de caixas (Box-Counting. A rede de drenagem tem característica de autoafinidade. A dimensão fractal proveniente da relação de parâmetros obtidos pelas Leis de Horton apresentou resultados dentro dos limiares da teoria da geometria fractal.The objective of the present work was to evaluate the fractal dimensions of the drainage network of the Caeté river watershed, Alfredo Wagner/SC, with different methods in order to characterize the irregular geomorphologic forms. The drainage network possesses multi-fractal properties. That is why the fractal dimensions for the individual segments (df and for the entire network (Df were evaluated with Horton's Laws and the Box-Counting method. The drainage network has self-affinity characteristics. The fractal dimension obtained through the parameters relationship of Horton's Laws showed the results within the thresholds of the fractal geometry theory.
Patricio, Pedro; Duarte, Jorge; Januario, Cristina
2015-01-01
We investigate the rheology of a fractal network, in the framework of the linear theory of viscoelasticity. We identify each segment of the network with a simple Kelvin-Voigt element, with a well defined equilibrium length. The final structure retains the elastic characteristics of a solid or a gel. By considering a very simple regular self-similar structure of segments in series and in parallel, in 1, 2 or 3 dimensions, we are able to express the viscoelasticity of the network as an effective generalised Kelvin-Voigt model with a power law spectrum of retardation times, $\\phi\\sim\\tau^{\\alpha-1}$. We relate the parameter $\\alpha$ with the fractal dimension of the gel. In some regimes ($0<\\alpha<1$), we recover the weak power law behaviours of the elastic and viscous moduli with the angular frequencies, $G'\\sim G''\\sim w^\\alpha$, that occur in a variety of soft materials, including living cells. In other regimes, we find different and interesting power laws for $G'$ and $G''$.
Emergence of fractal scaling in complex networks
Wei, Zong-Wen; Wang, Bing-Hong
2016-09-01
Some real-world networks are shown to be fractal or self-similar. It is widespread that such a phenomenon originates from the repulsion between hubs or disassortativity. Here we show that this common belief fails to capture the causality. Our key insight to address it is to pinpoint links critical to fractality. Those links with small edge betweenness centrality (BC) constitute a special architecture called fractal reference system, which gives birth to the fractal structure of those reported networks. In contrast, a small amount of links with high BC enable small-world effects, hiding the intrinsic fractality. With enough of such links removed, fractal scaling spontaneously arises from nonfractal networks. Our results provide a multiple-scale view on the structure and dynamics and place fractality as a generic organizing principle of complex networks on a firmer ground.
Fractal and multifractal analyses of bipartite networks.
Liu, Jin-Long; Wang, Jian; Yu, Zu-Guo; Xie, Xian-Hua
2017-03-31
Bipartite networks have attracted considerable interest in various fields. Fractality and multifractality of unipartite (classical) networks have been studied in recent years, but there is no work to study these properties of bipartite networks. In this paper, we try to unfold the self-similarity structure of bipartite networks by performing the fractal and multifractal analyses for a variety of real-world bipartite network data sets and models. First, we find the fractality in some bipartite networks, including the CiteULike, Netflix, MovieLens (ml-20m), Delicious data sets and (u, v)-flower model. Meanwhile, we observe the shifted power-law or exponential behavior in other several networks. We then focus on the multifractal properties of bipartite networks. Our results indicate that the multifractality exists in those bipartite networks possessing fractality. To capture the inherent attribute of bipartite network with two types different nodes, we give the different weights for the nodes of different classes, and show the existence of multifractality in these node-weighted bipartite networks. In addition, for the data sets with ratings, we modify the two existing algorithms for fractal and multifractal analyses of edge-weighted unipartite networks to study the self-similarity of the corresponding edge-weighted bipartite networks. The results show that our modified algorithms are feasible and can effectively uncover the self-similarity structure of these edge-weighted bipartite networks and their corresponding node-weighted versions.
Fractal and multifractal analyses of bipartite networks
Liu, Jin-Long; Wang, Jian; Yu, Zu-Guo; Xie, Xian-Hua
2017-01-01
Bipartite networks have attracted considerable interest in various fields. Fractality and multifractality of unipartite (classical) networks have been studied in recent years, but there is no work to study these properties of bipartite networks. In this paper, we try to unfold the self-similarity structure of bipartite networks by performing the fractal and multifractal analyses for a variety of real-world bipartite network data sets and models. First, we find the fractality in some bipartite networks, including the CiteULike, Netflix, MovieLens (ml-20m), Delicious data sets and (u, v)-flower model. Meanwhile, we observe the shifted power-law or exponential behavior in other several networks. We then focus on the multifractal properties of bipartite networks. Our results indicate that the multifractality exists in those bipartite networks possessing fractality. To capture the inherent attribute of bipartite network with two types different nodes, we give the different weights for the nodes of different classes, and show the existence of multifractality in these node-weighted bipartite networks. In addition, for the data sets with ratings, we modify the two existing algorithms for fractal and multifractal analyses of edge-weighted unipartite networks to study the self-similarity of the corresponding edge-weighted bipartite networks. The results show that our modified algorithms are feasible and can effectively uncover the self-similarity structure of these edge-weighted bipartite networks and their corresponding node-weighted versions. PMID:28361962
Fractal and multifractal analyses of bipartite networks
Liu, Jin-Long; Wang, Jian; Yu, Zu-Guo; Xie, Xian-Hua
2017-03-01
Bipartite networks have attracted considerable interest in various fields. Fractality and multifractality of unipartite (classical) networks have been studied in recent years, but there is no work to study these properties of bipartite networks. In this paper, we try to unfold the self-similarity structure of bipartite networks by performing the fractal and multifractal analyses for a variety of real-world bipartite network data sets and models. First, we find the fractality in some bipartite networks, including the CiteULike, Netflix, MovieLens (ml-20m), Delicious data sets and (u, v)-flower model. Meanwhile, we observe the shifted power-law or exponential behavior in other several networks. We then focus on the multifractal properties of bipartite networks. Our results indicate that the multifractality exists in those bipartite networks possessing fractality. To capture the inherent attribute of bipartite network with two types different nodes, we give the different weights for the nodes of different classes, and show the existence of multifractality in these node-weighted bipartite networks. In addition, for the data sets with ratings, we modify the two existing algorithms for fractal and multifractal analyses of edge-weighted unipartite networks to study the self-similarity of the corresponding edge-weighted bipartite networks. The results show that our modified algorithms are feasible and can effectively uncover the self-similarity structure of these edge-weighted bipartite networks and their corresponding node-weighted versions.
Institute of Scientific and Technical Information of China (English)
李彪; 许贵林; 卢远
2016-01-01
利用南流江流域30 m分辨率的DEM数据，介绍了ArcGIS中进行河网提取的一系列过程，并利用其图解建模工具，提取南流江流域的不同汇流累积面积的水系河网，实现了提取过程的流程化处理。分别统计河源密度和沟壑密度，并分别计算它们与汇流累积面积的几何函数关系，并对其进行二阶求导，确定其二阶导数关系，得到合适的汇流累积阈值，并借助分形分维理论对河网的分维值进行了验证。利用函数关系和分形分维确定汇流累积面积提取水系河网的方法有效地避免了人工选择汇流累积面积的主观性，提高了研究结果的准确性和可靠性，在知道研究流域河网分维值的前提下，可快速获取准确的汇流累计面积阈值。%Using Nanliu river basin 30 m resolution of DEM data, this paper introduces the ArcGIS for river network in extraction of a series of process, and use its graphical modeling tool, and extract the NanLiu river basins of different river confluence area of water system, realizes the extraction process routing process.Statistical heyuan density and gully density respectively, and calculate their geometric function relation with the accumulated flow area, and carries on the second order derivative calculation, determine its second derivative relationship, to get the right bus accumulation threshold, and with the help of fractal dimension fractal theory calculating fractal dimension value of the river network is verified.Function relation and the fractal dimension is used to determine the flow accu-mulation methods of extracting drainage river network area is effective to avoid the subjectivity of the convergence of artificial selection accumulation area and improve the veracity and reliability of the results of the study, under the premise that know river fractal dimen-sion is worth study basin, can quickly get accurate confluence area threshold.
Fractal modeling of natural fracture networks
Energy Technology Data Exchange (ETDEWEB)
Ferer, M.; Dean, B.; Mick, C.
1995-06-01
West Virginia University will implement procedures for a fractal analysis of fractures in reservoirs. This procedure will be applied to fracture networks in outcrops and to fractures intersecting horizontal boreholes. The parameters resulting from this analysis will be used to generate synthetic fracture networks with the same fractal characteristics as the real networks. Recovery from naturally fractured, tight-gas reservoirs is controlled by the fracture network. Reliable characterization of the actual fracture network in the reservoir is severely limited. The location and orientation of fractures intersecting the borehole can be determined, but the length of these fractures cannot be unambiguously determined. Because of the lack of detailed information about the actual fracture network, modeling methods must represent the porosity and permeability associated with the fracture network, as accurately as possible with very little a priori information. In the sections following, the authors will (1) present fractal analysis of the MWX site, using the box-counting procedure; (2) review evidence testing the fractal nature of fracture distributions and discuss the advantages of using the fractal analysis over a stochastic analysis; and (3) present an efficient algorithm for producing a self-similar fracture networks which mimic the real MWX outcrop fracture network.
Unveiling the Multi-fractal Structure of Complex Networks
Jalan, Sarika; Sarkar, Camellia; Boccaletti, Stefano
2016-01-01
The fractal nature of graphs has traditionally been investigated by using the nodes of networks as the basic units. Here, instead, we propose to concentrate on the graph edges, and introduce a practical and computationally not demanding method for revealing changes in the fractal behavior of networks, and particularly for allowing distinction between mono-fractal, quasi mono-fractal, and multi-fractal structures. We show that degree homogeneity plays a crucial role in determining the fractal nature of the underlying network, and report on six different protein-protein interaction networks along with their corresponding random networks. Our analysis allows to identify varying levels of complexity in the species.
Fractal parameters and vascular networks: facts & artifacts
Directory of Open Access Journals (Sweden)
Maniero Fabrizio
2008-07-01
Full Text Available Abstract Background Several fractal and non-fractal parameters have been considered for the quantitative assessment of the vascular architecture, using a variety of test specimens and of computational tools. The fractal parameters have the advantage of being scale invariant, i.e. to be independent of the magnification and resolution of the images to be investigated, making easier the comparison among different setups and experiments. Results The success of several commercial and/or free codes in computing the fractal parameters has been tested on well known exact models. Based on such a preliminary study, we selected the code Frac-lac in order to analyze images obtained by visualizing the angiogenetic process occurring in chick Chorio Allontoic Membranes (CAM, assumed to be paradigmatic of a realistic 2D vascular network. Among the parameters investigated, the fractal dimension Df proved to be the most robust estimator for CAM vascular networks. Moreover, only Df was able to discriminate between effective and elusive increases in vascularization after drug-induced angiogenic stimulations on CAMs. Conclusion The fractal dimension Df is likely to be the most promising tool for monitoring the effectiveness of anti-angiogenic therapies in various clinical contexts.
The Fractal Dimensions of Complex Networks
Institute of Scientific and Technical Information of China (English)
GUO Long; CAI Xu
2009-01-01
It is shown that many real complex networks share distinctive features,such as the small-world effect and the heterogeneous property of connectivity of vertices,which are different from random networks and regular lattices.Although these features capture the important characteristics of complex networks,their applicability depends on the style of networks.To unravel the universal characteristics many complex networks have in common,we study the fractal dimensions of complex networks using the method introduced by Shanker.We lind that the average 'density' (p(r)) of complex networks follows a better power-law function as a function of distance r with the exponent df,which is defined as the fractal dimension,in some real complex networks.Furthermore,we study the relation between df and the shortcuts Nadd in small-world networks and the size N in regular lattices.Our present work provides a new perspective to understand the dependence of the fractal dimension df on the complex network structure.
Fractals on IPv6 Network Topology
Directory of Open Access Journals (Sweden)
Bo Yang
2013-02-01
Full Text Available The coarse-grained renormalization and the fractal analysis of the Internet macroscopic topology can help people better understand the relationship between the part and whole of the Internet, and it is significant for people to understand the essence of the research object through a small amount of information. Aiming at the complexity of Internet IPv6 IP-level topology, we put forward a method of core-threshold coarse-grained to renormalize its topology. By analyzing the degree distribution and degree correlation characteristics in each k-core network topology, the scale invariance of the networks of coarse-grained renormalization was illustrated. The fractal dimension of Internet IPv6 IP-level topology was further computed which shows that the Internet IPv6 IP-level topology has got fractals.
Fractal analysis of flow of the river Warta
Radziejewski, Maciej; Kundzewicz, Zbigniew W.
1997-12-01
A long time series (170 years) of daily flows of the river Warta (Poland) are subject to fractal analysis. A binary variable (renewal stream) illustrating excursions of the process of flow is examined. The raw series is subject to de-seasonalization and normalization. Fractal dimensions of crossings of Warta flows are determined using a novel variant of the box-counting method. Temporal variability of the flow process is studied by determination of fractal dimensions for shifted horizons of 10 or 30 years length. Spectral properties are compared between the time series of flows, and the fractional Brownian motion which describes both the fractal structure of the process and the Hurst phenomenon. The approach may be useful in further studies of non-stationary of the process of flow, analysis of extreme hydrological events and synthetic flow generation.
Non-homogeneous fractal hierarchical weighted networks.
Dong, Yujuan; Dai, Meifeng; Ye, Dandan
2015-01-01
A model of fractal hierarchical structures that share the property of non-homogeneous weighted networks is introduced. These networks can be completely and analytically characterized in terms of the involved parameters, i.e., the size of the original graph Nk and the non-homogeneous weight scaling factors r1, r2, · · · rM. We also study the average weighted shortest path (AWSP), the average degree and the average node strength, taking place on the non-homogeneous hierarchical weighted networks. Moreover the AWSP is scrupulously calculated. We show that the AWSP depends on the number of copies and the sum of all non-homogeneous weight scaling factors in the infinite network order limit.
Wireless Fractal Ultra-Dense Cellular Networks.
Hao, Yixue; Chen, Min; Hu, Long; Song, Jeungeun; Volk, Mojca; Humar, Iztok
2017-04-12
With the ever-growing number of mobile devices, there is an explosive expansion in mobile data services. This represents a challenge for the traditional cellular network architecture to cope with the massive wireless traffic generated by mobile media applications. To meet this challenge, research is currently focused on the introduction of a small cell base station (BS) due to its low transmit power consumption and flexibility of deployment. However, due to a complex deployment environment and low transmit power of small cell BSs, the coverage boundary of small cell BSs will not have a traditional regular shape. Therefore, in this paper, we discuss the coverage boundary of an ultra-dense small cell network and give its main features: aeolotropy of path loss fading and fractal coverage boundary. Simple performance analysis is given, including coverage probability and transmission rate, etc., based on stochastic geometry theory and fractal theory. Finally, we present an application scene and discuss challenges in the ultra-dense small cell network.
Institute of Scientific and Technical Information of China (English)
陈彦光; 刘继生
2001-01-01
Based on standard fractal stream system model and mirror-im agesymmetry of series of channel classes, the first three models of Horton's la ws of network composition can be ‘reconstructed’ by mirror writing the ordinal numbers of channels,i.e., writing ordinals from the highest level to the grass roots. ① From the first and the second laws, we deduce out a three-p arameter Zipf's model, L(r)=C(r-a)-dz,where r is the rank of a river in a network which is marked in order of size, L(r) is the length o f the rth river, as for parameters C=L1[Rb/(Rb-1 )]dz, a=1/(1-Rb),and dz=lnRl/lnRb=1 /D. I n the parameter expressions, Rb and Rl are the bifurcation ratio and length ratio respectively, and D is the fractal dimension of river hierarch ies. ② From the second and the third laws, a generalized Hack's model is derive d out as Lm=μAbm, where Lm is the lengt h of the mth order river, Am is the corresponding catchment area , μ =L1A-b1，b=lnRl/lnRa, and in the parameters, Ra is basin area ratio, L1 is the main stream length, and A1 is the drain age area of the mainstream. It is evident that L1=μAb1 is the classic al Hack model. ③ From the first and the third laws, an allometric relationship is deduced as Nm=ηA-σm,where Nm is the number of mth order rivers, Am is corresponding catchment area, η=N1Aσ1,σ=lnRb/lnRa. As an attempt, the geographical space is divided into three: Space 1, existence space-real space; Space 2, evolution space-phase space; Space 3, correlation s pace-order space. Defining Dr, Dn, and Ds as the fractal di mension of rivel, network, and catchment area in real space, and Dl, D b, and Da as the generalized dimension corresponding to Dr, Dn, and Ds, we can construct a set of fractal dimension equations as fo llows, dz=Dl/Db=lnRl/lnRb≈Dr/Dn, b= Dl/Da=lnRl/lnRa≈Dr/Ds, and σ=Db/Da=lnRb/lnRa≈Dn/Ds. These equations show the physical distinction and mathematical relationships between varied dimensions of a system of rivers.%基于标准分
Origins of fractality in the growth of complex networks
Song, Chaoming; Havlin, Shlomo; Makse, Hernán A.
2006-04-01
Complex networks from such different fields as biology, technology or sociology share similar organization principles. The possibility of a unique growth mechanism promises to uncover universal origins of collective behaviour. In particular, the emergence of self-similarity in complex networks raises the fundamental question of the growth process according to which these structures evolve. Here we investigate the concept of renormalization as a mechanism for the growth of fractal and non-fractal modular networks. We show that the key principle that gives rise to the fractal architecture of networks is a strong effective `repulsion' (or, disassortativity) between the most connected nodes (that is, the hubs) on all length scales, rendering them very dispersed. More importantly, we show that a robust network comprising functional modules, such as a cellular network, necessitates a fractal topology, suggestive of an evolutionary drive for their existence.
The quantization of river network morphology based on the Tokunaga network
Institute of Scientific and Technical Information of China (English)
2009-01-01
River network morphology not only reflects the structure of river stream but also has great effects on hydrological process, soil erosion, river evolution, and watershed topography. Here we propose and define a new sequence of self-similar networks and corresponding parameters for the generated Tokunaga network. We also discuss the topological and numerical characteristics of self-similar networks with different iteration rules by utilizing links and fractal dimension. Application results indicate that the proposed method could be used to generate river network, which is much consistent with natural river network. The proposed parameter λ could well reflect the river network morphology.
A new hypercube variant: Fractal Cubic Network Graph
Directory of Open Access Journals (Sweden)
Ali Karci
2015-03-01
Full Text Available Hypercube is a popular and more attractive interconnection networks. The attractive properties of hypercube caused the derivation of more variants of hypercube. In this paper, we have proposed two variants of hypercube which was called as “Fractal Cubic Network Graphs”, and we have investigated the Hamiltonian-like properties of Fractal Cubic Network Graphs FCNGr(n. Firstly, Fractal Cubic Network Graphs FCNGr(n are defined by a fractal structure. Further, we show the construction and characteristics analyses of FCNGr(n where r=1 or r=2. Therefore, FCNGr(n is a Hamiltonian graph which is obtained by using Gray Code for r=2 and FCNG1(n is not a Hamiltonian Graph. Furthermore, we have obtained a recursive algorithm which is used to label the nodes of FCNG2(n. Finally, we get routing algorithms on FCNG2(n by utilizing routing algorithms on the hypercubes.
The fractal octahedron network of the large scale structure
Battaner, E
1998-01-01
In a previous article, we have proposed that the large scale structure network generated by large scale magnetic fields could consist of a network of octahedra only contacting at their vertexes. Assuming such a network could arise at different scales producing a fractal geometry, we study here its properties, and in particular how a sub-octahedron network can be inserted within an octahedron of the large network. We deduce that the scale of the fractal structure would range from $\\approx$100 Mpc, i.e. the scale of the deepest surveys, down to about 10 Mpc, as other smaller scale magnetic fields were probably destroyed in the radiation dominated Universe.
a Fractal Network Model for Fractured Porous Media
Xu, Peng; Li, Cuihong; Qiu, Shuxia; Sasmito, Agus Pulung
2016-04-01
The transport properties and mechanisms of fractured porous media are very important for oil and gas reservoir engineering, hydraulics, environmental science, chemical engineering, etc. In this paper, a fractal dual-porosity model is developed to estimate the equivalent hydraulic properties of fractured porous media, where a fractal tree-like network model is used to characterize the fracture system according to its fractal scaling laws and topological structures. The analytical expressions for the effective permeability of fracture system and fractured porous media, tortuosity, fracture density and fraction are derived. The proposed fractal model has been validated by comparisons with available experimental data and numerical simulation. It has been shown that fractal dimensions for fracture length and aperture have significant effect on the equivalent hydraulic properties of fractured porous media. The effective permeability of fracture system can be increased with the increase of fractal dimensions for fracture length and aperture, while it can be remarkably lowered by introducing tortuosity at large branching angle. Also, a scaling law between the fracture density and fractal dimension for fracture length has been found, where the scaling exponent depends on the fracture number. The present fractal dual-porosity model may shed light on the transport physics of fractured porous media and provide theoretical basis for oil and gas exploitation, underground water, nuclear waste disposal and geothermal energy extraction as well as chemical engineering, etc.
Delay Bound: Fractal Traffic Passes through Network Servers
Directory of Open Access Journals (Sweden)
Ming Li
2013-01-01
Full Text Available Delay analysis plays a role in real-time systems in computer communication networks. This paper gives our results in the aspect of delay analysis of fractal traffic passing through servers. There are three contributions presented in this paper. First, we will explain the reasons why conventional theory of queuing systems ceases in the general sense when arrival traffic is fractal. Then, we will propose a concise method of delay computation for hard real-time systems as shown in this paper. Finally, the delay computation of fractal traffic passing through severs is presented.
Scale-free networks embedded in fractal space
Yakubo, K.; Korošak, D.
2011-06-01
The impact of an inhomogeneous arrangement of nodes in space on a network organization cannot be neglected in most real-world scale-free networks. Here we propose a model for a geographical network with nodes embedded in a fractal space in which we can tune the network heterogeneity by varying the strength of the spatial embedding. When the nodes in such networks have power-law distributed intrinsic weights, the networks are scale-free with the degree distribution exponent decreasing with increasing fractal dimension if the spatial embedding is strong enough, while the weakly embedded networks are still scale-free but the degree exponent is equal to γ=2 regardless of the fractal dimension. We show that this phenomenon is related to the transition from a noncompact to compact phase of the network and that this transition accompanies a drastic change of the network efficiency. We test our analytically derived predictions on the real-world example of networks describing the soil porous architecture.
River Network Evolution Based on Fluid-Erosion Model
2010-01-01
A new landscape evolution model is proposed which is composed of the shallow water equations for the fluid above the sediment and the mass conservation equation of the sediment. Numerical simulations of the formation of landscape and river network are carried out based on these equations. It is shown that steady patterns of river network are formed for the initial inclinations of slopes within 0.00005 and 0.005. The fractal dimensions of the river network and the exponent of Hack's law are ob...
SPECTRAL CALCULATIONS OF HAMILTONIAN FOR A QUANTUM FRACTAL NETWORK
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
A general formulation for the spectral calculations of the Hamiltonian operator of a Quantum Fractal Network(QFN) is presented. The QFN can be constructed by placing artificial neurons on each site of the fractal lattice. An artificial neuron may consist of a cell of a quantum cellular automaton or a quantum dot, which confines a single electron. The Coulomb interaction or the spin-spin interaction between neurons can be used to transmit signals and perform logic operations.The recursive formulas of the eigenvalues and eigenvectors between sub-lattices are obtained explicitly. As the application of the formulations,the eigenvalues and eigenvectors of the Hamiltonian operator for the Sierpinski gasket are calculated.
A fractal growth model: Exploring the connection pattern of hubs in complex networks
Li, Dongyan; Wang, Xingyuan; Huang, Penghe
2017-04-01
Fractal is ubiquitous in many real-world networks. Previous researches showed that the strong disassortativity between the hub-nodes on all length scales was the key principle that gave rise to the fractal architecture of networks. Although fractal property emerged in some models, there were few researches about the fractal growth model and quantitative analyses about the strength of the disassortativity for fractal model. In this paper, we proposed a novel inverse renormalization method, named Box-based Preferential Attachment (BPA), to build the fractal growth models in which the Preferential Attachment was performed at box level. The proposed models provided a new framework that demonstrated small-world-fractal transition. Also, we firstly demonstrated the statistical characteristic of connection patterns of the hubs in fractal networks. The experimental results showed that, given proper growing scale and added edges, the proposed models could clearly show pure small-world or pure fractal or both of them. It also showed that the hub connection ratio showed normal distribution in many real-world networks. At last, the comparisons of connection pattern between the proposed models and the biological and technical networks were performed. The results gave useful reference for exploring the growth principle and for modeling the connection patterns for real-world networks.
Small-world to fractal transition in complex networks: a renormalization group approach.
Rozenfeld, Hernán D; Song, Chaoming; Makse, Hernán A
2010-01-15
We show that renormalization group (RG) theory applied to complex networks is useful to classify network topologies into universality classes in the space of configurations. The RG flow readily identifies a small-world-fractal transition by finding (i) a trivial stable fixed point of a complete graph, (ii) a nontrivial point of a pure fractal topology that is stable or unstable according to the amount of long-range links in the network, and (iii) another stable point of a fractal with shortcuts that exist exactly at the small-world-fractal transition. As a collateral, the RG technique explains the coexistence of the seemingly contradicting fractal and small-world phases and allows us to extract information on the distribution of shortcuts in real-world networks, a problem of importance for information flow in the system.
Hu, Kun; Meijer, Johanna H; Shea, Steven A; vanderLeest, Henk Tjebbe; Pittman-Polletta, Benjamin; Houben, Thijs; van Oosterhout, Floor; Deboer, Tom; Scheer, Frank A J L
2012-01-01
The mammalian central circadian pacemaker (the suprachiasmatic nucleus, SCN) contains thousands of neurons that are coupled through a complex network of interactions. In addition to the established role of the SCN in generating rhythms of ~24 hours in many physiological functions, the SCN was recently shown to be necessary for normal self-similar/fractal organization of motor activity and heart rate over a wide range of time scales--from minutes to 24 hours. To test whether the neural network within the SCN is sufficient to generate such fractal patterns, we studied multi-unit neural activity of in vivo and in vitro SCNs in rodents. In vivo SCN-neural activity exhibited fractal patterns that are virtually identical in mice and rats and are similar to those in motor activity at time scales from minutes up to 10 hours. In addition, these patterns remained unchanged when the main afferent signal to the SCN, namely light, was removed. However, the fractal patterns of SCN-neural activity are not autonomous within the SCN as these patterns completely broke down in the isolated in vitro SCN despite persistence of circadian rhythmicity. Thus, SCN-neural activity is fractal in the intact organism and these fractal patterns require network interactions between the SCN and extra-SCN nodes. Such a fractal control network could underlie the fractal regulation observed in many physiological functions that involve the SCN, including motor control and heart rate regulation.
RESEARCH ON FRACTAL CHARACTERISTICS OF URBAN TRAFFIC NETWORK STRUCTURE BASED ON GIS
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
Traffic network is an importance aspect of researching controllable parameters of an urban spatial morpholo-gy. Based on GIS, traffic network structure complexity can be understood by using fractal geometry in which thelength-radius dimension describes change of network density, and ramification-radius dimension describes complexity andaccessibility of urban network. It is propitious to analyze urban traffic network and to understand dynamic change processof traffic network using expanding fractal-dimension quantification. Meanwhile the length-radius dimension and ramifica-tion-radius dimension could be regard as reference factor of quantitative describing urban traffic network.
Energy Technology Data Exchange (ETDEWEB)
Hein, F. J. [Alberta Geological Survey, Calgary, AB (Canada)
1999-12-01
Published hydrocarbon-field and pool data on the Granite Wash, and data on lineaments within the Peace River area and more regionally, throughout the Western Canadian Sedimentary Basin (WCSB), have been statistically analyzed and synthesized. Numerical correlation within each dataset provides compelling evidence that for both types of data there is a fractal/mixed('multi')fractal property. Fractal analysis allows the combination of data from fault-networks of different ages to assess the cumulative spatial and size distributions of faults within a given study area. Estimates of undiscovered hydrocarbon potential of the Granite Wash in the Peace River Arch area based on fractal geometry show encouraging preliminary results, suggesting the potential presence and discovery of future small pools and fields. Although these results are preliminary and tentative, it is reasonable to suggest that fractal analysis of pool and field data is a potential tool that can be used to differentiate those hydrocarbon plays in which there are simple controls on reservoir formation compared to those in which the controls are more complex. The estimations of undiscovered hydrocarbon potential in the Peace River Arch area through fractal geometry are encouraging, but the validity of this inference may be questioned, given the relatively small sample size of the fields. Further documentation of fractal and mixed fractal distributions of oil and gas fields in immature play areas remains to be done. Such analysis should involve an analysis which 'peels away' the various multi-fractal layers and their effects, using canonical trend surface mapping techniques in combination with fractal analysis of paleotopographic and paleostructural reconstruction. 84 refs., 11 figs.
Fractal and Small-World Networks Formed by Self-Organized Critical Dynamics
Watanabe, Akitomo; Mizutaka, Shogo; Yakubo, Kousuke
2015-11-01
We propose a dynamical model in which a network structure evolves in a self-organized critical (SOC) manner and explain a possible origin of the emergence of fractal and small-world networks. Our model combines a network growth and its decay by failures of nodes. The decay mechanism reflects the instability of large functional networks against cascading overload failures. It is demonstrated that the dynamical system surely exhibits SOC characteristics, such as power-law forms of the avalanche size distribution, the cluster size distribution, and the distribution of the time interval between intermittent avalanches. During the network evolution, fractal networks are spontaneously generated when networks experience critical cascades of failures that lead to a percolation transition. In contrast, networks far from criticality have small-world structures. We also observe the crossover behavior from fractal to small-world structure in the network evolution.
Fractal and Small-World Networks Formed by Self-Organized Critical Dynamics
Watanabe, Akitomo; Yakubo, Kousuke
2015-01-01
We propose a dynamical model in which a network structure evolves in a self-organized critical (SOC) manner and explain a possible origin of the emergence of fractal and small-world networks. Our model combines a network growth and its decay by failures of nodes. The decay mechanism reflects the instability of large functional networks against cascading overload failures. It is demonstrated that the dynamical system surely exhibits SOC characteristics, such as power-law forms of the avalanche size distribution, the cluster size distribution, and the distribution of the time interval between intermittent avalanches. During the network evolution, fractal networks are spontaneously generated when networks experience critical cascades of failures that lead to a percolation transition. In contrast, networks far from criticality have small-world structures. We also observe the crossover behavior from fractal to small-world structure in the network evolution.
Self-organized network of fractal-shaped components coupled through statistical interaction.
Ugajin, R
2001-09-01
A dissipative dynamics is introduced to generate self-organized networks of interacting objects, which we call coupled-fractal networks. The growth model is constructed based on a growth hypothesis in which the growth rate of each object is a product of the probability of receiving source materials from faraway and the probability of receiving adhesives from other grown objects, where each object grows to be a random fractal if isolated, but connects with others if glued. The network is governed by the statistical interaction between fractal-shaped components, which can only be identified in a statistical manner over ensembles. This interaction is investigated using the degree of correlation between fractal-shaped components, enabling us to determine whether it is attractive or repulsive.
The conundrum of functional brain networks: small-world efficiency or fractal modularity
Gallos, Lazaros K; Makse, Hernan A
2012-01-01
The human brain has been studied at multiple scales, from neurons, circuits, areas with well defined anatomical and functional boundaries, to large-scale functional networks which mediate coherent cognition. In a recent work, we addressed the problem of the hierarchical organization in the brain through network analysis. Our analysis identified functional brain modules of fractal structure that were inter-connected in a small-world topology. Here, we provide more details on the use of network science tools to elaborate on this behavior. We indicate the importance of using percolation theory to highlight the modular character of the functional brain network. These modules present a fractal, self-similar topology, identified through fractal network methods. When we lower the threshold of correlations to include weaker ties, the network as a whole assumes a small-world character. These weak ties are organized precisely as predicted by theory maximizing information transfer with minimal wiring costs.
IMDB network revisited: unveiling fractal and modular properties from a typical small-world network.
Directory of Open Access Journals (Sweden)
Lazaros K Gallos
Full Text Available We study a subset of the movie collaboration network, http://www.imdb.com, where only adult movies are included. We show that there are many benefits in using such a network, which can serve as a prototype for studying social interactions. We find that the strength of links, i.e., how many times two actors have collaborated with each other, is an important factor that can significantly influence the network topology. We see that when we link all actors in the same movie with each other, the network becomes small-world, lacking a proper modular structure. On the other hand, by imposing a threshold on the minimum number of links two actors should have to be in our studied subset, the network topology becomes naturally fractal. This occurs due to a large number of meaningless links, namely, links connecting actors that did not actually interact. We focus our analysis on the fractal and modular properties of this resulting network, and show that the renormalization group analysis can characterize the self-similar structure of these networks.
Fractal modeling of natural fracture networks. Final report, June 1994--June 1995
Energy Technology Data Exchange (ETDEWEB)
Ferer, M.V.; Dean, B.H.; Mick, C.
1996-04-01
Recovery from naturally fractured, tight-gas reservoirs is controlled by the fracture network. Reliable characterization of the actual fracture network in the reservoir is severely limited. The location and orientation of fractures intersecting the borehole can be determined, but the length of these fractures cannot be unambiguously determined. Fracture networks can be determined for outcrops, but there is little reason to believe that the network in the reservoir should be identical because of the differences in stresses and history. Because of the lack of detailed information about the actual fracture network, modeling methods must represent the porosity and permeability associated with the fracture network, as accurately as possible with very little apriori information. Three rather different types of approaches have been used: (1) dual porosity simulations; (2) `stochastic` modeling of fracture networks, and (3) fractal modeling of fracture networks. Stochastic models which assume a variety of probability distributions of fracture characteristics have been used with some success in modeling fracture networks. The advantage of these stochastic models over the dual porosity simulations is that real fracture heterogeneities are included in the modeling process. In the sections provided in this paper the authors will present fractal analysis of the MWX site, using the box-counting procedure; (2) review evidence testing the fractal nature of fracture distributions and discuss the advantages of using their fractal analysis over a stochastic analysis; (3) present an efficient algorithm for producing a self-similar fracture networks which mimic the real MWX outcrop fracture network.
Aon, Miguel Antonio; O'Rourke, Brian; Cortassa, Sonia
2004-01-01
In this work, we highlight the links between fractals and scaling in cells and explore the kinetic consequences for biochemical reactions operating in fractal media. Based on the proposal that the cytoskeletal architecture is organized as a percolation lattice, with clusters emerging as fractal forms, the analysis of kinetics in percolation clusters is especially emphasized. A key consequence of this spatiotemporal cytoplasmic organization is that enzyme reactions following Michaelis-Menten or allosteric type kinetics exhibit higher rates in fractal media (for short times and at lower substrate concentrations) at the percolation threshold than in Euclidean media. As a result, considerably faster and higher amplification of enzymatic activity is obtained. Finally, we describe some of the properties bestowed by cytoskeletal organization and dynamics on metabolic networks.
Fractal characterization of fracture networks: An improved box-counting technique
Roy, Ankur; Perfect, Edmund; Dunne, William M.; McKay, Larry D.
2007-12-01
Box counting is widely used for characterizing fracture networks as fractals and estimating their fractal dimensions (D). If this analysis yields a power law distribution given by N ∝ r-D, where N is the number of boxes containing one or more fractures and r is the box size, then the network is considered to be fractal. However, researchers are divided in their opinion about which is the best box-counting algorithm to use, or whether fracture networks are indeed fractals. A synthetic fractal fracture network with a known D value was used to develop a new algorithm for the box-counting method that returns improved estimates of D. The method is based on identifying the lower limit of fractal behavior (rcutoff) using the condition ds/dr → 0, where s is the standard deviation from a linear regression equation fitted to log(N) versus log(r) with data for r sequentially excluded. A set of 7 nested fracture maps from the Hornelen Basin, Norway was used to test the improved method and demonstrate its accuracy for natural patterns. We also reanalyzed a suite of 17 fracture trace maps that had previously been evaluated for their fractal nature. The improved estimates of D for these maps ranged from 1.56 ± 0.02 to 1.79 ± 0.02, and were much greater than the original estimates. These higher D values imply a greater degree of fracture connectivity and thus increased propensity for fracture flow and the transport of miscible or immiscible chemicals.
Renormalization and small-world model of fractal quantum repeater networks
Wei, Zong-Wen; Wang, Bing-Hong; Han, Xiao-Pu
2013-01-01
Quantum networks provide access to exchange of quantum information. The primary task of quantum networks is to distribute entanglement between remote nodes. Although quantum repeater protocol enables long distance entanglement distribution, it has been restricted to one-dimensional linear network. Here we develop a general framework that allows application of quantum repeater protocol to arbitrary quantum repeater networks with fractal structure. Entanglement distribution across such networks is mapped to renormalization. Furthermore, we demonstrate that logarithmical times of recursive such renormalization transformations can trigger fractal to small-world transition, where a scalable quantum small-world network is achieved. Our result provides new insight into quantum repeater theory towards realistic construction of large-scale quantum networks. PMID:23386977
Renormalization and small-world model of fractal quantum repeater networks.
Wei, Zong-Wen; Wang, Bing-Hong; Han, Xiao-Pu
2013-01-01
Quantum networks provide access to exchange of quantum information. The primary task of quantum networks is to distribute entanglement between remote nodes. Although quantum repeater protocol enables long distance entanglement distribution, it has been restricted to one-dimensional linear network. Here we develop a general framework that allows application of quantum repeater protocol to arbitrary quantum repeater networks with fractal structure. Entanglement distribution across such networks is mapped to renormalization. Furthermore, we demonstrate that logarithmical times of recursive such renormalization transformations can trigger fractal to small-world transition, where a scalable quantum small-world network is achieved. Our result provides new insight into quantum repeater theory towards realistic construction of large-scale quantum networks.
Fractal gene regulatory networks for robust locomotion control of modular robots
DEFF Research Database (Denmark)
Zahadat, Payam; Christensen, David Johan; Schultz, Ulrik Pagh;
2010-01-01
Designing controllers for modular robots is difficult due to the distributed and dynamic nature of the robots. In this paper fractal gene regulatory networks are evolved to control modular robots in a distributed way. Experiments with different morphologies of modular robot are performed and the ......Designing controllers for modular robots is difficult due to the distributed and dynamic nature of the robots. In this paper fractal gene regulatory networks are evolved to control modular robots in a distributed way. Experiments with different morphologies of modular robot are performed...
Sensor-coupled fractal gene regulatory networks for locomotion control of a modular snake robot
DEFF Research Database (Denmark)
Zahadat, Payam; Christensen, David Johan; Katebi, Serajeddin
2013-01-01
In this paper we study fractal gene regulatory network (FGRN) controllers based on sensory information. The FGRN controllers are evolved to control a snake robot consisting of seven simulated ATRON modules. Each module contains three tilt sensors which represent the direction of gravity in the co......In this paper we study fractal gene regulatory network (FGRN) controllers based on sensory information. The FGRN controllers are evolved to control a snake robot consisting of seven simulated ATRON modules. Each module contains three tilt sensors which represent the direction of gravity...
Pelletier, J D
1997-01-01
The power spectrum S of linear transects of the earth's topography is often observed to be a power-law function of wave number k with exponent close to -2: S(k) is proportional to k^-2. In addition, river networks are fractal trees that satisfy many power-law or fractal relationships between their morphologic components. A model equation for the evolution of the earth's topography by erosional processes which produces fractal topography and fractal river networks is presented and its solutions compared in detail to real topography. The model is the diffusion equation for sediment transport on hillslopes and channels with the local diffusivity proportional to the square of the discharge. The dependence of diffusivity on discharge follows from fundamental equations of sediment transport. We study the model in two ways. In the first analysis the diffusivity is parameterized as a function of relief and a Taylor expansion procedure is carried out to obtain a differential equation for the landform elevation which i...
International trade network: fractal properties and globalization puzzle.
Karpiarz, Mariusz; Fronczak, Piotr; Fronczak, Agata
2014-12-12
Globalization is one of the central concepts of our age. The common perception of the process is that, due to declining communication and transport costs, distance becomes less and less important. However, the distance coefficient in the gravity model of trade, which grows in time, indicates that the role of distance increases rather than decreases. This, in essence, captures the notion of the globalization puzzle. Here, we show that the fractality of the international trade system (ITS) provides a simple solution for the puzzle. We argue that the distance coefficient corresponds to the fractal dimension of ITS. We provide two independent methods, the box counting method and spatial choice model, which confirm this statement. Our results allow us to conclude that the previous approaches to solving the puzzle misinterpreted the meaning of the distance coefficient in the gravity model of trade.
International trade network: fractal properties and globalization puzzle
Karpiarz, Mariusz; Fronczak, Agata
2014-01-01
Globalization is one of the central concepts of our age. The common perception of the process is that, due to declining communication and transport costs, distance becomes less and less important. However, the distance coefficient in the gravity model of trade, which grows in time, indicates that the role of distance increases rather than decreases. This, in essence, captures the notion of the globalization puzzle. Here, we show that the fractality of the international trade system (ITS) provides a simple solution for the puzzle. We argue, that the distance coefficient corresponds to the fractal dimension of ITS. We provide two independent methods, box counting method and spatial choice model, which confirm this statement. Our results allow us to conclude that the previous approaches to solving the puzzle misinterpreted the meaning of the distance coefficient in the gravity model of trade.
From homogeneous to fractal normal and tumorous microvascular networks in the brain.
Risser, Laurent; Plouraboué, Franck; Steyer, Alexandre; Cloetens, Peter; Le Duc, Géraldine; Fonta, Caroline
2007-02-01
We studied normal and tumorous three-dimensional (3D) microvascular networks in primate and rat brain. Tissues were prepared following a new preparation technique intended for high-resolution synchrotron tomography of microvascular networks. The resulting 3D images with a spatial resolution of less than the minimum capillary diameter permit a complete description of the entire vascular network for volumes as large as tens of cubic millimeters. The structural properties of the vascular networks were investigated by several multiscale methods such as fractal and power-spectrum analysis. These investigations gave a new coherent picture of normal and pathological complex vascular structures. They showed that normal cortical vascular networks have scale-invariant fractal properties on a small scale from 1.4 mum up to 40 to 65 mum. Above this threshold, vascular networks can be considered as homogeneous. Tumor vascular networks show similar characteristics, but the validity range of the fractal regime extend to much larger spatial dimensions. These 3D results shed new light on previous two dimensional analyses giving for the first time a direct measurement of vascular modules associated with vessel-tissue surface exchange.
Fractal and multifractal analysis of human retinal vascular network: a review
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Ştefan Ţălu
2011-12-01
Full Text Available The objective of this paper is to present a synthesis concerning the results obtained in fractaland multifractal analysis of vascular network geometry of the human retina. The numerical results areuseful in mathematical models based on parametric representations, used in vitreo-retinal biomechanicalstudies. The fractal and multifractal analysis of retinal vascular network provides noninvasive powerfultools that allow physicians the early detection of patients with different retinal vascular diseases.
An inkjet-printed UWB antenna on paper substrate utilizing a novel fractal matching network
Cook, Benjamin Stassen
2012-07-01
In this work, the smallest reported inkjet-printed UWB antenna is proposed that utilizes a fractal matching network to increase the performance of a UWB microstrip monopole. The antenna is inkjet-printed on a paper substrate to demonstrate the ability to produce small and low-cost UWB antennas with inkjet-printing technology which can enable compact, low-cost, and environmentally friendly wireless sensor network. © 2012 IEEE.
Long-term Trend and Fractal of Annual Runoff Process in Mainstream of Tarim River
Institute of Scientific and Technical Information of China (English)
XU Jianhua; CHEN Yaning; LI Weihong; DONG Shan
2008-01-01
Based on the time series data from the Aral hydrological station for the period of 1958-2005, the paper re-veals the long-term trend and fractal of the annual runoff process in the mainstream of the Tarim River by using thewavelet analysis method and the fractal theory. The main conclusions are as follows: 1) From a large time scale pointof view, i.e. the time scale of 16 (24) years, the annual runoff basically shows a slightly decreasing trend as a wholefrom 1958 to 2005. If the time scale is reduced to 8 (23) or 4 (22) years, the annual runoff still displays the basic trendas the large time scale, but it has fluctuated more obviously during the period. 2) The correlation dimension for theannual runoff process is 3.4307, non-integral, which indicates that the process has both fractal and chaotic characteris-tics. The correlation dimension is above 3, which means that at least four independent variables are needed to describethe dynamics of the annual runoff process. 3) The Hurst exponent for the first period (1958-1973) is 0.5036, whichequals 0.5 approximately and indicates that the annual runoff process is in chaos. The Hurst exponents for the second(1974-1989) and third (1990-2005) periods are both greater than 0.50, which indicate that the annual runoff processshowed a long-enduring characteristic in the two periods. The Hurst exponent for the period from 1990 to 2005 indi-cates that the annual runoffwill show a slightly increasing trend in the 16 years after 2005.
Fractal dimension, walk dimension and conductivity exponent of karst networks around Tulum.
Hendrick, Martin; Renard, Philippe
2016-06-01
Understanding the complex structure of karst networks is a challenge. In this work, we characterize the fractal properties of some of the largest coastal karst network systems in the world. They are located near the town of Tulum (Quintana Roo, Mexico). Their fractal dimension d_f, conductivity exponent ˜{μ} and walk dimension d_w are estimated using real space renormalization and numerical simulations. We obtain the following values for these exponents: d_f≈ 1.5, d_w≈ 2.4, ˜{μ}≈ 0.9. We observe that the Einstein relation holds for these structures ˜{μ} ≈ -d_f + d_w. These results indicate that coastal karst networks can be considered as critical systems and this provides some foundations to model them within this framework.
Decision and feature fusion over the fractal inference network using camera and range sensors
Erkmen, Ismet; Erkmen, Aydan M.; Ucar, Ekin
1998-10-01
The objective of the ongoing work is to fuse information from uncertain environmental data taken by cameras, short range sensors including infrared and ultrasound sensors for strategic target recognition and task specific action in Mobile Robot applications. Our present goal in this paper is to demonstrate target recognition for service robot in a simple office environment. It is proposed to fuse all sensory signals obtained from multiple sensors over a fully layer-connected sensor network system that provides an equal opportunity competitive environment for sensory data where those bearing less uncertainty, less complexity and less inconsistencies with the overall goal survive, while others fade out. In our work, this task is achieved as a decision fusion using the Fractal Inference Network (FIN), where information patterns or units--modeled as textured belief functions bearing a fractal dimension due to uncertainty-- propagate while being processed at the nodes of the network. Each local process of a node generates a multiresolutional feature fusion. In this model, the environment is observed by multisensors of different type, different resolution and different spatial location without a prescheduled sensing scenario in data gathering. Node activation and flow control of information over the FIN is performed by a neuro- controller, a concept that has been developed recently as an improvement over the classical Fractal Inference Network. In this paper, the mathematical closed form representation for decision fusion over the FIN is developed in a way suitable for analysis and is applied to a NOMAD mobile robot servicing an office environment.
Data-driven detrending of nonstationary fractal time series with echo state networks
Maiorino, Enrico; Livi, Lorenzo; Rizzi, Antonello; Sadeghian, Alireza
2015-01-01
In this paper, we propose a data-driven approach to the problem of detrending fractal and multifractal time series. We consider a time series as the measurements elaborated from a dynamical process over time. We assume that such a dynamical process is predictable to a certain degree, by means of a class of recurrent networks called echo state networks. Such networks have been shown to be able to predict the outcome of a number of dynamical processes. Here we propose to perform a data-driven detrending of nonstationary, fractal and multifractal time series by using an echo state network operating as a filter. Notably, we predict the trend component of a given input time series, which is superimposed to the (multi)fractal component of interest. Such a (estimated) trend is then removed from the original time series and the residual signal is analyzed with the Multifractal Detrended Fluctuation Analysis for a quantitative verification of the correctness of the proposed detrending procedure. In order to demonstrat...
A Fractal and Scale-free Model of Complex Networks with Hub Attraction Behaviors
Kuang, Li; Li, Deyi; Li, Yuanxiang; Sun, Yu
2013-01-01
It is widely believed that fractality of complex networks origins from hub repulsion behaviors (anticorrelation or disassortativity), which means large degree nodes tend to connect with small degree nodes. This hypothesis was demonstrated by a dynamical growth model, which evolves as the inverse renormalization procedure proposed by Song et al. Now we find that the dynamical growth model is based on the assumption that all the cross-boxes links has the same probability e to link to the most connected nodes inside each box. Therefore, we modify the growth model by adopting the flexible probability e, which makes hubs have higher probability to connect with hubs than non-hubs. With this model, we find some fractal and scale-free networks have hub attraction behaviors (correlation or assortativity). The results are the counter-examples of former beliefs.
Tahavvor, Ali Reza
2016-06-01
In the present study artificial neural network and fractal geometry are used to predict frost thickness and density on a cold flat plate having constant surface temperature under forced convection for different ambient conditions. These methods are very applicable in this area because phase changes such as melting and solidification are simulated by conventional methods but frost formation is a most complicated phase change phenomenon consists of coupled heat and mass transfer. Therefore conventional mathematical techniques cannot capture the effects of all parameters on its growth and development because this process influenced by many factors and it is a time dependent process. Therefore, in this work soft computing method such as artificial neural network and fractal geometry are used to do this manner. The databases for modeling are generated from the experimental measurements. First, multilayer perceptron network is used and it is found that the back-propagation algorithm with Levenberg-Marquardt learning rule is the best choice to estimate frost growth properties due to accurate and faster training procedure. Second, fractal geometry based on the Von-Koch curve is used to model frost growth procedure especially in frost thickness and density. Comparison is performed between experimental measurements and soft computing methods. Results show that soft computing methods can be used more efficiently to determine frost properties over a flat plate. Based on the developed models, wide range of frost formation over flat plates can be determined for various conditions.
Tahavvor, Ali Reza
2017-03-01
In the present study artificial neural network and fractal geometry are used to predict frost thickness and density on a cold flat plate having constant surface temperature under forced convection for different ambient conditions. These methods are very applicable in this area because phase changes such as melting and solidification are simulated by conventional methods but frost formation is a most complicated phase change phenomenon consists of coupled heat and mass transfer. Therefore conventional mathematical techniques cannot capture the effects of all parameters on its growth and development because this process influenced by many factors and it is a time dependent process. Therefore, in this work soft computing method such as artificial neural network and fractal geometry are used to do this manner. The databases for modeling are generated from the experimental measurements. First, multilayer perceptron network is used and it is found that the back-propagation algorithm with Levenberg-Marquardt learning rule is the best choice to estimate frost growth properties due to accurate and faster training procedure. Second, fractal geometry based on the Von-Koch curve is used to model frost growth procedure especially in frost thickness and density. Comparison is performed between experimental measurements and soft computing methods. Results show that soft computing methods can be used more efficiently to determine frost properties over a flat plate. Based on the developed models, wide range of frost formation over flat plates can be determined for various conditions.
Topological Vulnerability Evaluation Model Based on Fractal Dimension of Complex Networks.
Gou, Li; Wei, Bo; Sadiq, Rehan; Sadiq, Yong; Deng, Yong
2016-01-01
With an increasing emphasis on network security, much more attentions have been attracted to the vulnerability of complex networks. In this paper, the fractal dimension, which can reflect space-filling capacity of networks, is redefined as the origin moment of the edge betweenness to obtain a more reasonable evaluation of vulnerability. The proposed model combining multiple evaluation indexes not only overcomes the shortage of average edge betweenness's failing to evaluate vulnerability of some special networks, but also characterizes the topological structure and highlights the space-filling capacity of networks. The applications to six US airline networks illustrate the practicality and effectiveness of our proposed method, and the comparisons with three other commonly used methods further validate the superiority of our proposed method.
Topological Vulnerability Evaluation Model Based on Fractal Dimension of Complex Networks.
Directory of Open Access Journals (Sweden)
Li Gou
Full Text Available With an increasing emphasis on network security, much more attentions have been attracted to the vulnerability of complex networks. In this paper, the fractal dimension, which can reflect space-filling capacity of networks, is redefined as the origin moment of the edge betweenness to obtain a more reasonable evaluation of vulnerability. The proposed model combining multiple evaluation indexes not only overcomes the shortage of average edge betweenness's failing to evaluate vulnerability of some special networks, but also characterizes the topological structure and highlights the space-filling capacity of networks. The applications to six US airline networks illustrate the practicality and effectiveness of our proposed method, and the comparisons with three other commonly used methods further validate the superiority of our proposed method.
Analysis of microseismicity using fuzzy logic and fractals for fracture network characterization
Aminzadeh, F.; Ayatollahy Tafti, T.; Maity, D.; Boyle, K.; Sahimi, M.; Sammis, C. G.
2010-12-01
The area where microseismic events occur may be correlated with the fracture network at a geothermal field. For an Enhanced Geothermal System (EGS) reservoir, an extensive fracture network with a large aerial distribution is required. Pore-pressure increase, temperature changes, volume change due to fluid withdrawal/injection and chemical alteration of fracture surfaces are all mechanisms that may explain microseismic events at a geothermal field. If these mechanisms are operative, any fuzzy cluster of the microseismic events should represent a connected fracture network. Drilling new EGS wells (both injection and production wells) in these locations may facilitate the creation of an EGS reservoir. In this article we use the fuzzy clustering technique to find the location and characteristics of fracture networks in the Geysers geothermal field. We also show that the centers of these fuzzy clusters move in time, which may represent fracture propagation or fluid movement within the fracture network. Furthermore, analyzing the distribution of fuzzy hypocenters and quantifying their fractal structure helps us to develop an accurate fracture map for the reservoir. Combining the fuzzy clustering results with the fractal analysis allows us to better understand the mechanisms for fracture stimulation and better characterize the evolution of the fracture network. We also show how micro-earthquake date collected in different time periods can be correlated with drastic changes in the distribution of active fractures resulting from injection, production or other transient events.
Directory of Open Access Journals (Sweden)
Franceschini Barbara
2005-02-01
Full Text Available Abstract Background Modeling the complex development and growth of tumor angiogenesis using mathematics and biological data is a burgeoning area of cancer research. Architectural complexity is the main feature of every anatomical system, including organs, tissues, cells and sub-cellular entities. The vascular system is a complex network whose geometrical characteristics cannot be properly defined using the principles of Euclidean geometry, which is only capable of interpreting regular and smooth objects that are almost impossible to find in Nature. However, fractal geometry is a more powerful means of quantifying the spatial complexity of real objects. Methods This paper introduces the surface fractal dimension (Ds as a numerical index of the two-dimensional (2-D geometrical complexity of tumor vascular networks, and their behavior during computer-simulated changes in vessel density and distribution. Results We show that Ds significantly depends on the number of vessels and their pattern of distribution. This demonstrates that the quantitative evaluation of the 2-D geometrical complexity of tumor vascular systems can be useful not only to measure its complex architecture, but also to model its development and growth. Conclusions Studying the fractal properties of neovascularity induces reflections upon the real significance of the complex form of branched anatomical structures, in an attempt to define more appropriate methods of describing them quantitatively. This knowledge can be used to predict the aggressiveness of malignant tumors and design compounds that can halt the process of angiogenesis and influence tumor growth.
Topological phase transition of a fractal spin system: The relevance of the network complexity
Torres, Felipe; Rogan, José; Kiwi, Miguel; Valdivia, Juan Alejandro
2016-05-01
A new type of collective excitations, due to the topology of a complex random network that can be characterized by a fractal dimension DF, is investigated. We show analytically that these excitations generate phase transitions due to the non-periodic topology of the DF > 1 complex network. An Ising system, with long range interactions, is studied in detail to support the claim. The analytic treatment is possible because the evaluation of the partition function can be decomposed into closed factor loops, in spite of the architectural complexity. The removal of the infrared divergences leads to an unconventional phase transition, with spin correlations that are robust against thermal fluctuations.
Topological phase transition of a fractal spin system: The relevance of the network complexity
Directory of Open Access Journals (Sweden)
Felipe Torres
2016-05-01
Full Text Available A new type of collective excitations, due to the topology of a complex random network that can be characterized by a fractal dimension DF, is investigated. We show analytically that these excitations generate phase transitions due to the non-periodic topology of the DF > 1 complex network. An Ising system, with long range interactions, is studied in detail to support the claim. The analytic treatment is possible because the evaluation of the partition function can be decomposed into closed factor loops, in spite of the architectural complexity. The removal of the infrared divergences leads to an unconventional phase transition, with spin correlations that are robust against thermal fluctuations.
Circulating persistent current and induced magnetic field in a fractal network
Energy Technology Data Exchange (ETDEWEB)
Saha, Srilekha [Condensed Matter Physics Division, Saha Institute of Nuclear Physics, Sector-I, Block-AF, Bidhannagar, Kolkata 700 064 (India); Maiti, Santanu K., E-mail: santanu.maiti@isical.ac.in [Physics and Applied Mathematics Unit, Indian Statistical Institute, 203 Barrackpore Trunk Road, Kolkata 700 108 (India); Karmakar, S.N. [Condensed Matter Physics Division, Saha Institute of Nuclear Physics, Sector-I, Block-AF, Bidhannagar, Kolkata 700 064 (India)
2016-04-29
We present the overall conductance as well as the circulating currents in individual loops of a Sierpinski gasket (SPG) as we apply bias voltage via the side attached electrodes. SPG being a self-similar structure, its manifestation on loop currents and magnetic fields is examined in various generations of this fractal and it has been observed that for a given configuration of the electrodes, the physical quantities exhibit certain regularity as we go from one generation to another. Also a notable feature is the introduction of anisotropy in hopping causes an increase in magnitude of overall transport current. These features are a subject of interest in this article. - Highlights: • Voltage driven circular current is analyzed in a fractal network. • Current induced magnetic field is strong enough to flip a spin. • Anisotropy in hopping enhances overall transport current.
Institute of Scientific and Technical Information of China (English)
Jia Yonggang; Fu Yuanbin; Xu Guohui; Shan Hongxian; Cao Xueqing
2003-01-01
The study area lies in the subaqueous delta, which came into being in 1964～1976. One oil-field road has been built for exploring petroleum to form a wave barrier. The hydrodynamic conditions on the north side of the road are relatively violent, on the contrary the hydrodynamic conditions on the south side of the road are nearly placid. This makes the study area a natural laboratory for studying the influence of the hydrodynamic conditions on the fractal characteristics of the tidal flat. Selecting an area is named Case Ⅰ on the side of stronger hydrodynamic activities and an area is named Case Ⅱ on the other side. Measuring the topography and sampling and analyzing the granulometrical composition, it is found that the hydrodynamic conditions have fatal influence on the surface fractal dimensions and the granulometrical fractal dimensions of the area. In Case Ⅰ, which has strong hydrodynamic conditions, the surface fractal dimensions are obviously larger than those of Case Ⅱ, and the granulometrical fractal dimensions are relatively smaller than those of Case Ⅱ, the surface fractal dimensions of Case Ⅰ decrease quickly with the increase of grid size; the granulometrical fractal dimensions are disperse, while the hydrodynamic conditions of Case Ⅱ are just reverse. A sampling line and a core sampling on each side of the road are selected. It is found that on the south side of the road the granulometrical fractal dimensions vary regularly in the line and with the depth, the farther apart from the road, the smaller the fractal dimensions, and the deeper the sampling position the larger the fractal dimensions, while granulometrical fractal dimensions on the north side of the road have no such regularity pattern. The mechanism of the influence of the hydrodynamic conditions on the fractal characteristics is discussed.
Modified box dimension and average weighted receiving time on the weighted fractal networks
Dai, Meifeng; Sun, Yanqiu; Shao, Shuxiang; Xi, Lifeng; Su, Weiyi
2015-12-01
In this paper a family of weighted fractal networks, in which the weights of edges have been assigned to different values with certain scale, are studied. For the case of the weighted fractal networks the definition of modified box dimension is introduced, and a rigorous proof for its existence is given. Then, the modified box dimension depending on the weighted factor and the number of copies is deduced. Assuming that the walker, at each step, starting from its current node, moves uniformly to any of its nearest neighbors. The weighted time for two adjacency nodes is the weight connecting the two nodes. Then the average weighted receiving time (AWRT) is a corresponding definition. The obtained remarkable result displays that in the large network, when the weight factor is larger than the number of copies, the AWRT grows as a power law function of the network order with the exponent, being the reciprocal of modified box dimension. This result shows that the efficiency of the trapping process depends on the modified box dimension: the larger the value of modified box dimension, the more efficient the trapping process is.
On the Fractality of Complex Networks: Covering Problem, Algorithms and Ahlfors Regularity
Wang, Lihong; Wang, Qin; Xi, Lifeng; Chen, Jin; Wang, Songjing; Bao, Liulu; Yu, Zhouyu; Zhao, Luming
2017-01-01
In this paper, we revisit the fractality of complex network by investigating three dimensions with respect to minimum box-covering, minimum ball-covering and average volume of balls. The first two dimensions are calculated through the minimum box-covering problem and minimum ball-covering problem. For minimum ball-covering problem, we prove its NP-completeness and propose several heuristic algorithms on its feasible solution, and we also compare the performance of these algorithms. For the third dimension, we introduce the random ball-volume algorithm. We introduce the notion of Ahlfors regularity of networks and prove that above three dimensions are the same if networks are Ahlfors regular. We also provide a class of networks satisfying Ahlfors regularity. PMID:28128289
Hayashi, Yukio
2012-01-01
Since a spatial distribution of communication requests is inhomogeneous and related to a population, in constructing a network, it is crucial for delivering packets on short paths through the links between proximity nodes and for distributing the load of nodes how to locate the nodes as base-stations on a realistic wireless environment. In this paper, from viewpoints of complex network science and biological foraging, we propose a scalably self-organized geographical network, in which the proper positions of nodes and the network topology are simultaneously determined according to the population, by iterative divisions of rectangles for load balancing of nodes in the adaptive change of their territories. In particular, we consider a decentralized routing by using only local information,and show that, for searching targets around high population areas, the routing on the naturally embedded fractal-like structure by population has higher efficiency than the conventionally optimal strategy on a square lattice.
Relevance between abutment pressure and fractal dimension of crack network induced by mining
Institute of Scientific and Technical Information of China (English)
Gao Mingzhong; Jin Wencheng; Dai Zhixu; Xie Jing
2013-01-01
Based on the geological conditions of coal mining face No. 15-14120 at No. 8 mine of Pingdingshan coal mining group, the real-time evolution of coal-roof crack network with working face advancing was collected with the help of intrinsically safe borehole video instrument. And according to the geology of this working face, a discrete element model was calculated by UDEC. Combining in situ experimental data with numerical results, the relationship between the fractal dimension of boreholes’ wall and the distri-bution of advanced abutment pressure was studied under the condition of mining advance. The results show that the variation tendency of fractal dimension and the abutment pressure has the same charac-teristic value. The distance between working face and the peak value of the abutment pressure has a slight increasing trend with the advancing of mining-face. When the working face is set as the original point, the trend of fractal dimension from the far place to the origin can be divided into three phases:constant, steady increasing and constant. And the turning points of these phases are the max-influencing distance (50 m) and peak value (15 m) of abutment pressure.
EEG signal classification method based on fractal features and neural network.
Phothisonothai, Montri; Nakagawa, Masahiro
2008-01-01
In this paper, we propose a method to classify electroencephalogram (EEG) signal recorded from left- and right-hand movement imaginations. Three subjects (two males and one female) are volunteered to participate in the experiment. We use a technique of complexity measure based on fractal analysis to reveal feature patterns in the EEG signal. Effective algorithm, namely, detrended fluctuation analysis (DFA) has been selected to estimate embedded fractal dimension (FD) values between relaxing and imaging states of the recorded EEG signal. To show the waveform of FDs, we use a windowing-based method or called time-dependent fractal dimension (TDFD) and the Kullback-Leibler (K-L) divergence. Two feature parameters; K-L divergence and different expected values are proposed to be input variables of the classifier. Finally, featured data are classified by a three-layer feed-forward neural network based on a simple backpropagation algorithm. Experimental results can be considerably applied in a brain-computer interface (BCI) application and show that the proposed method is more effective than the conventional method by improving average classification rates of 87.5% and 88.3% for left- and right-hand movement imagery tasks, respectively.
Reuveni, Shlomi; Granek, Rony; Klafter, Joseph
2010-10-01
We present an approach to mapping between random walks and vibrational dynamics on general networks. Random walk occupation probabilities, first passage time distributions and passage probabilities between nodes are expressed in terms of thermal vibrational correlation functions. Recurrence is demonstrated equivalent to the Landau-Peierls instability. Fractal networks are analyzed as a case study. In particular, we show that the spectral dimension governs whether or not the first passage time distribution is well represented by its mean. We discuss relevance to universal features arising in protein vibrational dynamics.
Model for the evolution of river networks
Energy Technology Data Exchange (ETDEWEB)
Leheny, R.L.; Nagel, S.R. (The James Franck Institute and the Department of Physics, The University of Chicago, 5640 South Ellis Avenue, Chicago, Illinois 60637 (United States))
1993-08-30
We have developed a model, which includes the effects of erosion both from precipitation and from avalanching of soil on steep slopes, to simulate the formation and evolution of river networks. The avalanches provide a mechanism for competition in growth between neighboring river basins. The changing morphology follows many of the characteristics of evolution set forth by Glock. We find that during evolution the model maintains the statistical characteristics measured in natural river systems.
River Network Modeling Beyond Discharge at Gauges
David, C. H.; Famiglietti, J. S.; Salas, F. R.; Whiteaker, T. L.; Maidment, D. R.; Tolle, K.
2014-12-01
Over the past two decades, the estimation of water flow in river networks within hydro-meteorological models has mostly focused on simulations of natural processes and on their verification at available river gauges. Despite valuable existing skills in hydrologic modeling the accounting for anthropogenic actions in current models remains limited. The emerging availability of datasets containing measured dam outflows and reported irrigation withdrawals motivates their inclusion into simulations of flow in river networks. However, the development of advanced river network models accounting for such datasets of anthropogenic influences requires a detailed data model and a thorough handling of the various data types, sources and time scales. This contribution details the development of a consistent data model suitable for accounting some observations of anthropogenic modifications of the surface water cycle and presents the impact of such inclusion on simulations using the Routing Application for Parallel computatIon of Discharge (RAPID).
Average weighted trapping time of the node- and edge- weighted fractal networks
Dai, Meifeng; Ye, Dandan; Hou, Jie; Xi, Lifeng; Su, Weiyi
2016-10-01
In this paper, we study the trapping problem in the node- and edge- weighted fractal networks with the underlying geometries, focusing on a particular case with a perfect trap located at the central node. We derive the exact analytic formulas of the average weighted trapping time (AWTT), the average of node-to-trap mean weighted first-passage time over the whole networks, in terms of the network size Ng, the number of copies s, the node-weight factor w and the edge-weight factor r. The obtained result displays that in the large network, the AWTT grows as a power-law function of the network size Ng with the exponent, represented by θ(s , r , w) =logs(srw2) when srw2 ≠ 1. Especially when srw2 = 1 , AWTT grows with increasing order Ng as log Ng. This also means that the efficiency of the trapping process depend on three main parameters: the number of copies s > 1, node-weight factor 0 < w ≤ 1, and edge-weight factor 0 < r ≤ 1. The smaller the value of srw2 is, the more efficient the trapping process is.
Nonlinear random resistor diode networks and fractal dimensions of directed percolation clusters.
Stenull, O; Janssen, H K
2001-07-01
We study nonlinear random resistor diode networks at the transition from the nonpercolating to the directed percolating phase. The resistor-like bonds and the diode-like bonds under forward bias voltage obey a generalized Ohm's law V approximately I(r). Based on general grounds such as symmetries and relevance we develop a field theoretic model. We focus on the average two-port resistance, which is governed at the transition by the resistance exponent straight phi(r). By employing renormalization group methods we calculate straight phi(r) for arbitrary r to one-loop order. Then we address the fractal dimensions characterizing directed percolation clusters. Via considering distinct values of the nonlinearity r, we determine the dimension of the red bonds, the chemical path, and the backbone to two-loop order.
Automatic River Network Extraction from LIDAR Data
Maderal, E. N.; Valcarcel, N.; Delgado, J.; Sevilla, C.; Ojeda, J. C.
2016-06-01
National Geographic Institute of Spain (IGN-ES) has launched a new production system for automatic river network extraction for the Geospatial Reference Information (GRI) within hydrography theme. The goal is to get an accurate and updated river network, automatically extracted as possible. For this, IGN-ES has full LiDAR coverage for the whole Spanish territory with a density of 0.5 points per square meter. To implement this work, it has been validated the technical feasibility, developed a methodology to automate each production phase: hydrological terrain models generation with 2 meter grid size and river network extraction combining hydrographic criteria (topographic network) and hydrological criteria (flow accumulation river network), and finally the production was launched. The key points of this work has been managing a big data environment, more than 160,000 Lidar data files, the infrastructure to store (up to 40 Tb between results and intermediate files), and process; using local virtualization and the Amazon Web Service (AWS), which allowed to obtain this automatic production within 6 months, it also has been important the software stability (TerraScan-TerraSolid, GlobalMapper-Blue Marble , FME-Safe, ArcGIS-Esri) and finally, the human resources managing. The results of this production has been an accurate automatic river network extraction for the whole country with a significant improvement for the altimetric component of the 3D linear vector. This article presents the technical feasibility, the production methodology, the automatic river network extraction production and its advantages over traditional vector extraction systems.
Carbon nanotube-based polymer nanocomposites: Fractal network to hierarchical morphology
Chatterjee, Tirtha
The dispersion of anisotropic nanoparticles such as single-walled carbon nanotubes in polymeric matrices promises the ability to develop advanced materials with controlled and tailored combinations of properties. However, dispersion of such nanotubes in a polymer matrix is an extremely challenging task due to strong attractive interactions between the nanotubes. The successful dispersion of single-walled carbon nanotubes in poly(ethylene oxide) using an anionic surfactant (lithium dodecyl sulfate) as compatibilizer is reported here. The geometrical percolation threshold (pc, in vol %) of nanotubes, as revealed by melt-state rheological measurements, is found to be at ˜ 0.09 vol % loading, which corresponds to an effective tube anisotropy of ˜ 650. The system shows an even earlier development of the electrical percolation at 0.03 vol % SWNT loading as obtained by electrical conductivity measurements. In their quiescent state, the nanotubes show hierarchical fractal network (mass fractal dimension ˜ 2.3 +/- 0.2) made of aggregated flocs. Inside the floc, individual or small bundles of nanotubes overlap each other to form a dense mesh. The interfloc interactions provides the stress bearing capacity for these nano composites and are responsible for the unique modulus scaling of these systems (˜(p-pc)delta, 3.0 ≤ delta ≤ 4.5). The interaction is inversely related to the particle dispersion state, which influences the absolute values of the viscoelastic parameters. As a direct consequence of the self-similar fractal network, the linear flow properties display 'time-temperature-composition' superposition. This superposability can be extended for non-linear deformations when the non-linear properties are scaled by the local strain experienced by the elements of the network. More interestingly, under steady shear, these nanocomposites show network-independent behavior. The absolute stress value is a function of the nanotube loading, but the characteristic time
Flat electronic bands in fractal-kagomé network and the effect of perturbation
Energy Technology Data Exchange (ETDEWEB)
Nandy, Atanu, E-mail: atanunandy1989@gmail.com; Chakrabarti, Arunava, E-mail: arunava-chakrabarti@yahoo.co.in [Department of Physics, University of Kalyani, Kalyani, West Bengal - 741235 (India)
2016-05-06
We demonstrate an analytical prescription of demonstrating the flat band [FB] states in a fractal incorporated kagomé type network that can give rise to a countable infinity of flat non-dispersive eigenstates with a multitude of localization area. The onset of localization can, in principle, be delayed in space by an appropriate choice of energy regime. The length scale, at which the onset of localization for each mode occurs, can be tuned at will following the formalism developed within the framework of real space renormalization group. This scheme leads to an exact determination of energy eigenvalue for which one can have dispersionless flat electronic bands. Furthermore, we have shown the effect ofuniform magnetic field for the same non-translationally invariant network model that has ultimately led to an‘apparent invisibility’ of such staggered localized states and to generate absolutely continuous sub-bands in the energy spectrum and again an interesting re-entrant behavior of those FB states.
On the Mass Fractal Character of Si-Based Structural Networks in Amorphous Polymer Derived Ceramics
Sen, Sabyasachi; Widgeon, Scarlett
2015-01-01
The intermediate-range packing of SiNxC4−x (0 ≤ x ≤ 4) tetrahedra in polysilycarbodiimide and polysilazane-derived amorphous SiCN ceramics is investigated using 29Si spin-lattice relaxation nuclear magnetic resonance (SLR NMR) spectroscopy. The SiCN network in the polysilylcarbodiimide-derived ceramic consists predominantly of SiN4 tetrahedra that are characterized by a 3-dimensional spatial distribution signifying compact packing of such units to form amorphous Si3N4 clusters. On the other hand, the SiCN network of the polysilazane-derived ceramic is characterized by mixed bonded SiNxC4−x tetrahedra that are inefficiently packed with a mass fractal dimension of Df ~2.5 that is significantly lower than the embedding Euclidean dimension (D = 3). This result unequivocally confirms the hypothesis that the presence of dissimilar atoms, namely, 4-coordinated C and 3-coordinated N, in the nearest neighbor environment of Si along with some exclusion in connectivity between SiCxN4−x tetrahedra with widely different N:C ratios and the absence of bonding between C and N result in steric hindrance to an efficient packing of these structural units. It is noted that similar inefficiencies in packing are observed in polymer-derived amorphous SiOC ceramics as well as in proteins and binary hard sphere systems.
On the Mass Fractal Character of Si-Based Structural Networks in Amorphous Polymer Derived Ceramics
Directory of Open Access Journals (Sweden)
Sabyasachi Sen
2015-03-01
Full Text Available The intermediate-range packing of SiNxC4−x (0 ≤ x ≤ 4 tetrahedra in polysilycarbodiimide and polysilazane-derived amorphous SiCN ceramics is investigated using 29Si spin-lattice relaxation nuclear magnetic resonance (SLR NMR spectroscopy. The SiCN network in the polysilylcarbodiimide-derived ceramic consists predominantly of SiN4 tetrahedra that are characterized by a 3-dimensional spatial distribution signifying compact packing of such units to form amorphous Si3N4 clusters. On the other hand, the SiCN network of the polysilazane-derived ceramic is characterized by mixed bonded SiNxC4−x tetrahedra that are inefficiently packed with a mass fractal dimension of Df ~2.5 that is significantly lower than the embedding Euclidean dimension (D = 3. This result unequivocally confirms the hypothesis that the presence of dissimilar atoms, namely, 4-coordinated C and 3-coordinated N, in the nearest neighbor environment of Si along with some exclusion in connectivity between SiCxN4−x tetrahedra with widely different N:C ratios and the absence of bonding between C and N result in steric hindrance to an efficient packing of these structural units. It is noted that similar inefficiencies in packing are observed in polymer-derived amorphous SiOC ceramics as well as in proteins and binary hard sphere systems.
Chełminiak, Przemysław
2012-10-01
A new approach to the assemblage of complex networks displaying the scale-free architecture is proposed. While the growth and the preferential attachment of incoming nodes assure an emergence of such networks according to the Barabási-Albert model, it is argued here that the preferential linking condition needs not to be a principal rule. To assert this statement a simple computer model based on random walks on fractal lattices is introduced. It is shown that the model successfully reproduces the degree distributions, the ultra-small-worldness and the high clustering arising from the topology of scale-free networks.
Simple model for river network evolution
Energy Technology Data Exchange (ETDEWEB)
Leheny, R.L. [The James Franck Institute and The Department of Physics, The University of Chicago, 5640 South Ellis Avenue, Chicago, Illinois 60637 (United States)
1995-11-01
We simulate the evolution of a drainage basin by erosion from precipitation and avalanching on hillslopes. The avalanches create a competition in growth between neighboring basins and play the central role in driving the evolution. The simulated landscapes form drainage systems that share many qualitative features with Glock`s model for natural network evolution and maintain statistical properties that characterize real river networks. We also present results from a second model with a modified, mass conserving avalanche scheme. Although the terrains from these two models are qualitatively dissimilar, their drainage networks share the same general evolution and statistical features.
Esbenshade, Donald H., Jr.
1991-01-01
Develops the idea of fractals through a laboratory activity that calculates the fractal dimension of ordinary white bread. Extends use of the fractal dimension to compare other complex structures as other breads and sponges. (MDH)
Esbenshade, Donald H., Jr.
1991-01-01
Develops the idea of fractals through a laboratory activity that calculates the fractal dimension of ordinary white bread. Extends use of the fractal dimension to compare other complex structures as other breads and sponges. (MDH)
Directory of Open Access Journals (Sweden)
Bocewicz Grzegorz
2017-06-01
Full Text Available The problems of designing supply networks and traffic flow routing and scheduling are the subject of intensive research. The problems encompass the management of the supply of a variety of goods using multi-modal transportation. This research also takes into account the various constraints related to route topology, the parameters of the available fleet of vehicles, order values, delivery due dates, etc. Assuming that the structure of a supply network, constrained by a transport network topology that determines its behavior, we develop a declarative model which would enable the analysis of the relationships between the structure of a supply network and its potential behavior resulting in a set of desired delivery-flows. The problem in question can be reduced to determining sufficient conditions that ensure smooth flow in a transport network with a fractal structure. The proposed approach, which assumes a recursive, fractal network structure, enables the assessment of alternative delivery routes and associated schedules in polynomial time. An illustrative example showing the quantitative and qualitative relationships between the morphological characteristics of the investigated supply networks and the functional parameters of the assumed delivery-flows is provided.
Berejnov, Viatcheslav; Sinton, David; Djilali, Ned
2009-01-01
Experimental two-phase invasion percolation flow patterns were observed in hydrophobic micro-porous networks designed to model fuel cell specific porous media. In order to mimic the operational conditions encountered in the porous electrodes of polymer electrolyte membrane fuel cells (PEMFCs), micro-porous networks were fabricated with corresponding microchannel size distributions. The inlet channels were invaded homogeneously with flow rates corresponding to fuel cell current densities of 1.0 to 0.1 A/cm2 (Ca 10e-7-10e-8). A variety of fractal breakthrough patterns were observed and analyzed to quantify flooding density and geometrical diversity in terms of the total saturation, St, local saturations, s, and fractal dimension, D. It was found that St increases monotonically during the invasion process until the breakthrough point is reached, and s profiles indicate the dynamic distribution of the liquid phase during the process. Fractal analysis confirmed that the experiments fall within the flow regime of i...
Phothisonothai, Montri; Nakagawa, Masahiro
In this study, we propose a method of classifying a spontaneous electroencephalogram (EEG) approach to a brain-computer interface. Ten subjects, aged 21-32 years, volunteered to imagine left-and right- hand movements. An independent component analysis based on a fixed-point algorithm is used to eliminate the activities found in the EEG signals. We use a fractal dimension value to reveal the embedded potential responses in the human brain. The different fractal dimension values between the relaxing and imaging periods are computed. Featured data is classified by a three-layer feed-forward neural network based on a simple backpropagation algorithm. Two conventional methods, namely, the use of the autoregressive (AR) model and the band power estimation (BPE) as features, and the linear discriminant analysis (LDA) as a classifier, are selected for comparison in this study. Experimental results show that the proposed method is more effective than the conventional methods.
Energy Technology Data Exchange (ETDEWEB)
Chełminiak, Przemysław, E-mail: geronimo@amu.edu.pl [Faculty of Physics, A. Mickiewicz University, Umultowska 85, 61-614 Poznań (Poland)
2012-10-01
A new approach to the assemblage of complex networks displaying the scale-free architecture is proposed. While the growth and the preferential attachment of incoming nodes assure an emergence of such networks according to the Barabási–Albert model, it is argued here that the preferential linking condition needs not to be a principal rule. To assert this statement a simple computer model based on random walks on fractal lattices is introduced. It is shown that the model successfully reproduces the degree distributions, the ultra-small-worldness and the high clustering arising from the topology of scale-free networks. -- Highlights: ► A new mechanism of evolution for scale-free complex networks is proposed. ► The preferential attachment rule is not necessary to construct such networks. ► It is shown that they reveal some basic properties of classical scale-free nets.
Drifters for New Measurements Along River Networks
Davies, J. L.; Niemeier, J. J.; Kruger, A.; Mantilla, R. G.; Ceynar, D. L.
2008-12-01
Inexpensive floating devices and techniques have been developed for a variety of river measurements, including surface flow velocity, water temperature, and light measurements, which serve as a proxy for turbidity. These devices, called Drifters, provide measurements in a Lagrangian reference frame. A Drifter consists of an inexpensive microcontroller, sensors, on-board data storage, a temperature-controlled clock, low-power radio transceiver, two AA batteries, all housed in a small plastic boat hull. As a Drifter floats down a river, the microcontroller periodically awakens and performs a series of measurements. Radio beacons placed on the riverbank transmit location information to the Drifters for georeferencing. Drifters are collected downstream where the data are downloaded for analysis. Drifters can also transmit collected data to the beacons in real time, but at the cost of higher power consumption. The design of the Drifters recognizes the need for accurate determination of travel times along the river network to an outlet of interest. Drifters have the potential to provide a full picture of the spatial distribution of travel times in a basin, opening the door to new understanding of the runoff transport phenomena, and removing the need of calibrated parameters in runoff transport equations of hydrological models. Acquired measurements are overlaid on maps, which provide a new perspective of the spatial distribution of water quality, temperature and velocity in large regions. Drifters have been used to make measurements over a 3-mile stretch of the Iowa River in Iowa City, Iowa, as preparation for a large-scale experiment on the river network of the Clear Creek basin in Iowa.
Modeling sediment transport in river networks
Wang, Xu-Ming; Hao, Rui; Huo, Jie; Zhang, Jin-Feng
2008-11-01
A dynamical model is proposed to study sediment transport in river networks. A river can be divided into segments by the injection of branch streams of higher rank. The model is based on the fact that in a real river, the sediment-carrying capability of the stream in the ith segment may be modulated by the undergone state, which may be erosion or sedimentation, of the i-1th and ith segments, and also influenced by that of the ith injecting branch of higher rank. We select a database about the upper-middle reach of the Yellow River in the lower-water season to test the model. The result shows that the data, produced by averaging the erosion or sedimentation over the preceding transient process, are in good agreement with the observed average in a month. With this model, the steady state after transience can be predicted, and it indicates a scaling law that the quantity of erosion or sedimentation exponentially depends on the number of the segments along the reach of the channel. Our investigation suggests that fluctuation of the stream flow due to random rainfall will prevent this steady state from occurring. This is owing to the phenomenon that the varying trend of the quantity of erosion or sedimentation is opposite to that of sediment-carrying capability of the stream.
Wei, Mao-Hong; Lin, Hui-Long
2014-03-01
The alpine meadow in the source region of the Yangtze and Yellow River is suffering serious deterioration. Though great efforts have been put into, the restoration for the degraded grassland is far from being effective, mainly due to poor understanding of the degradation mechanism of alpine meadow in this region. In order to clarify the formation mechanism of degradation grassland and provide the new ideas for restoration, degradation sequences of the alpine meadow in the source region of the Yangtze and Yellow River were taken as target systems to analyze the soil particle size distribution, the fractal dimension of the soil particle size, and the relationship between soil erosion modulus and fractal dimension. The results showed that, with increasing grassland degradation, the percentage contents of clay increased while the percentage contents of silt sand and very fine sand showed a decreasing trend. The fractal dimension presented a positive correlation with clay among the degradation sequences while negative correlations were found with very fine sand and silt sand. The curvilinear regression of fractal dimension and erosion modulus fitted a quadratic function. Judged by the function, fractal dimension 2.81 was the threshold value of soil erosion. The threshold value has an indicative meaning on predicting the breakout of grazing-induced erosion and on restoration of the degraded grassland. Taking fractal dimension of 2.81 as the restoration indicator, adoption of corresponding measures to make fractal dimension less than 2.81, would an effective way to restore the degradation grassland.
A new global river network database for macroscale hydrologic modeling
Wu, Huan; Kimball, John S.; Li, Hongyi; Huang, Maoyi; Leung, L. Ruby; Adler, Robert F.
2012-09-01
Coarse-resolution (upscaled) river networks are critical inputs for runoff routing in macroscale hydrologic models. Recently, Wu et al. (2011) developed a hierarchical dominant river tracing (DRT) algorithm for automated extraction and spatial upscaling of river networks using fine-scale hydrography inputs. We applied the DRT algorithms using combined HydroSHEDS and HYDRO1k global fine-scale hydrography inputs and produced a new series of upscaled global river network data at multiple (1/16° to 2°) spatial resolutions. The new upscaled results are internally consistent and congruent with the baseline fine-scale inputs and should facilitate improved regional to global scale hydrologic simulations.
DEFF Research Database (Denmark)
Bruun Jensen, Casper
2007-01-01
. Instead, I outline a fractal approach to the study of space, society, and infrastructure. A fractal orientation requires a number of related conceptual reorientations. It has implications for thinking about scale and perspective, and (sociotechnical) relations, and for considering the role of the social...... and a fractal social theory....
Fluid temperatures: Modeling the thermal regime of a river network
Rhonda Mazza; Ashley Steel
2017-01-01
Water temperature drives the complex food web of a river network. Aquatic organisms hatch, feed, and reproduce in thermal niches within the tributaries and mainstem that comprise the river network. Changes in water temperature can synchronize or asynchronize the timing of their life stages throughout the year. The water temperature fluctuates over time and place,...
Nandy, Atanu; Pal, Biplab; Chakrabarti, Arunava
2015-04-01
We demonstrate, by explicit construction, that a single band tight binding Hamiltonian defined on a class of deterministic fractals of the b = 3N Sierpinski type can give rise to an infinity of dispersionless, flat-band like states which can be worked out analytically using the scale invariance of the underlying lattice. The states are localized over clusters of increasing sizes, displaying the existence of a multitude of localization areas. The onset of localization can, in principle, be 'delayed' in space by an appropriate choice of the energy of the electron. A uniform magnetic field threading the elementary plaquettes of the network is shown to destroy this staggered localization and generate absolutely continuous sub-bands in the energy spectrum of these non-translationally invariant networks.
Geometry of River Networks; 3, Characterization of Component Connectivity
Dodds, P S; Dodds, Peter Sheridan; Rothman, Daniel H.
2000-01-01
River networks serve as a paradigmatic example of all branching networks. Essential to understanding the overall structure of river networks is a knowledge of their detailed architecture. Here we show that sub-branches are distributed exponentially in size and that they are randomly distributed in space, thereby completely characterizing the most basic level of river network description. Specifically, an averaged view of network architecture is first provided by a proposed self-similarity statement about the scaling of drainage density, a local measure of stream concentration. This scaling of drainage density is shown to imply Tokunaga's law, a description of the scaling of side branch abundance along a given stream, as well as a scaling law for stream lengths. This establishes the scaling of the length scale associated with drainage density as the basic signature of self-similarity in river networks. We then consider fluctuations in drainage density and consequently the numbers of side branches. Data is anal...
Technical Note: Automatic river network generation for a physically-based river catchment model
2010-01-01
SHETRAN is a physically-based distributed modelling system that gives detailed simulations in time and space of water flow and sediment and solute transport in river catchments. Standard algorithms for the automatic generation of river channel networks from digital elevation data are impossible to apply in SHETRAN and other similar models because the river channels are assumed to run along the edges of grid cells. In this work a new algorithm for the automatic generation of a river cha...
Technical Note: Automatic river network generation for a physically-based river catchment model
2010-01-01
SHETRAN is a physically-based distributed modelling system that gives detailed simulations in time and space of water flow and sediment and solute transport in river catchments. Standard algorithms for the automatic generation of river channel networks from digital elevation data are impossible to apply in SHETRAN and other similar models because the river channels are assumed to run along the edges of grid cells. In this work a new algorithm for the automatic generation of a river channel ne...
Fractal Branching in Vascular Trees and Networks by VESsel GENeration Analysis (VESGEN)
Parsons-Wingerter, Patricia A.
2016-01-01
Vascular patterning offers an informative multi-scale, fractal readout of regulatory signaling by complex molecular pathways. Understanding such molecular crosstalk is important for physiological, pathological and therapeutic research in Space Biology and Astronaut countermeasures. When mapped out and quantified by NASA's innovative VESsel GENeration Analysis (VESGEN) software, remodeling vascular patterns become useful biomarkers that advance out understanding of the response of biology and human health to challenges such as microgravity and radiation in space environments.
Species turnover and geographic distance in an urban river network
DEFF Research Database (Denmark)
Rouquette, James R.; Dallimer, Martin; Armsworth, Paul R.
2013-01-01
of the habitat or topographic features of the landscape and the means of dispersal of the organism. River networks, in particular in human-modified landscapes, are a striking example of such a situation. Here, we use data for both aquatic and terrestrial organisms across an urban river network to examine...... patterns of species turnover and to determine whether these patterns differ between different taxonomic groups. LocationSheffield area, UK. MethodsAquatic (macroinvertebrates, diatoms) and terrestrial (birds, plants, butterflies) organisms were surveyed at 41 sites across an urban river network. We...
Study of hydrodynamic model in sluice controlled river networks
Li, Yan; Zeng, Fantang
2010-05-01
Shiqi river network ,is situated in the Zhongshan city of Guangdong province in the P.R.China. The river network covers approximately 702.55km2 ,with a total river length of over 500km and extending over 34km from north to south and over 46km from east to west. The river network overlaps with the most densely populated and economically developed region in the Pear River Delta Economic Zone. In 2008 the region had a population of 1 846.9 thousands And a GDP of more than 8 2500 million RMB. All branches of the river network are encircled by the main rivers of Pear River Delta(PRD) network. With the economic and social development, all natural connections with the external rivers are controlled by the sluices, water body exchanges between the Shiqi river network and external rivers are significantly changed by human activities. The overall objective the research is to develop a tool for the local Environmental Protection Bureau to Understand and quantify the impact of the artificial construction on the hydrological cycle. The developed model can accurate representation of the water levels and flows in the study area, to allow accurate representation of the transport of pollutants. The river network topography is derived directly from the available database. Only the "major" rivers were included in the model, because cross-section data for the "minor" rivers are currently not available. In general, the 1D hydrodynamic model is provided with flow boundary conditions ("Q") at its upstream boundaries and with water level boundary conditions ("z") at its downstream boundaries. For all boundaries of Shiqi river network, there are no flow records available, all records are water level. To reflect the hydrodynamic process accurately, the author developed a new methods to set the hydrodynamic model's boundary. For each boundary, the boundary condition is "Z" when the sluice is open, and the boundary condition is "Q" while it is closed. The open or close condition is identified
Technical Note: Automatic river network generation for a physically-based river catchment model
Directory of Open Access Journals (Sweden)
S. J. Birkinshaw
2010-09-01
Full Text Available SHETRAN is a physically-based distributed modelling system that gives detailed simulations in time and space of water flow and sediment and solute transport in river catchments. Standard algorithms for the automatic generation of river channel networks from digital elevation data are impossible to apply in SHETRAN and other similar models because the river channels are assumed to run along the edges of grid cells. In this work a new algorithm for the automatic generation of a river channel network in SHETRAN is described and its use in an example catchment demonstrated.
Technical Note: Automatic river network generation for a physically-based river catchment model
Birkinshaw, S. J.
2010-09-01
SHETRAN is a physically-based distributed modelling system that gives detailed simulations in time and space of water flow and sediment and solute transport in river catchments. Standard algorithms for the automatic generation of river channel networks from digital elevation data are impossible to apply in SHETRAN and other similar models because the river channels are assumed to run along the edges of grid cells. In this work a new algorithm for the automatic generation of a river channel network in SHETRAN is described and its use in an example catchment demonstrated.
Technical Note: Automatic river network generation for a physically-based river catchment model
Directory of Open Access Journals (Sweden)
S. J. Birkinshaw
2010-05-01
Full Text Available SHETRAN is a physically-based distributed modelling system that gives detailed simulations in time and space of water flow and sediment and solute transport in river catchments. Standard algorithms for the automatic generation of river channel networks from digital elevation data are impossible to apply in SHETRAN and other similar models because the river channels are assumed to run along the edges of grid cells. In this work a new algorithm for the automatic generation of a river channel network in SHETRAN is described and its use in an example catchment demonstrated.
A model of the sediment transport on a river network
Wang, Xu-Ming; Hao, Rui; Zhang, Jin-Feng; Huo, Jie
2007-03-01
A dynamical model is proposed to mimic the sediment transport on a river network. A river can be divided into some segments. For the ith segment the schlepping sediment ability of the flow may be scouring or depositing, which is influenced by that of the (i- 1)th segment. In order to compare our model simulation results with the empirical data obtained in Yellow River, the model is equipped with an experiential relation between the flow rate and the depositing rate of the Yellow River. After this, the simulation results show an excellent agreement with the empirical conclusions obtained with the upper and middle parts of Yellow River when it is in the low-water periods (for instance, in Dec., Jan. and Feb.). This indicates that our model may successfully describe the scouring-depositing of river networks.
Turcotte, Donald L.
Tectonic processes build landforms that are subsequently destroyed by erosional processes. Landforms exhibit fractal statistics in a variety of ways; examples include (1) lengths of coast lines; (2) number-size statistics of lakes and islands; (3) spectral behavior of topography and bathymetry both globally and locally; and (4) branching statistics of drainage networks. Erosional processes are dominant in the development of many landforms on this planet, but similar fractal statistics are also applicable to the surface of Venus where minimal erosion has occurred. A number of dynamical systems models for landforms have been proposed, including (1) cellular automata; (2) diffusion limited aggregation; (3) self-avoiding percolation; and (4) advective-diffusion equations. The fractal statistics and validity of these models will be discussed. Earthquakes also exhibit fractal statistics. The frequency-magnitude statistics of earthquakes satisfy the fractal Gutenberg-Richter relation both globally and locally. Earthquakes are believed to be a classic example of self-organized criticality. One model for earthquakes utilizes interacting slider-blocks. These slider block models have been shown to behave chaotically and to exhibit self-organized criticality. The applicability of these models will be discussed and alternative approaches will be presented. Fragmentation has been demonstrated to produce fractal statistics in many cases. Comminution is one model for fragmentation that yields fractal statistics. It has been proposed that comminution is also responsible for much of the deformation in the earth's crust. The brittle disruption of the crust and the resulting earthquakes present an integrated problem with many fractal aspects.
Physical Heterogeneity and Aquatic Community Function in River Networks
The geomorphological character of a river network provides the template upon which evolution acts to create unique biological communities. Deciphering commonly observed patterns and processes within riverine landscapes resulting from the interplay between physical and biological...
Upscaling river networks for use in climate models
Arora, Vivek K.; Harrison, Stephen
2007-11-01
Upscaling fine resolution river networks in a realistic manner is a cumbersome process and manual corrections are difficult to avoid. A modified algorithm is presented that offers improvement over the existing approaches and requires comparatively fewer manual corrections. The algorithm uses fine resolution flow directions to find the adjacent coarse resolution grid cell in which the majority of water drains and then corrects for increased occurrences of river flow through the sides of the grid cells. Visual comparison remains an acceptable way to assess the success of various upscaling algorithms given the complex nature of rivers and in the absence of a method for comprehensive quantitative comparison. Here, the fraction of ordinal river flow directions (a measure of side-to-corner preference) and the fraction of grid cells that only drain themselves (a measure of connectivity of low order river segments) are used to provide information about the nature of upscaled coarse resolution river networks in comparison to the fine resolution networks. For both visual evaluation and these more quantitative measures, the modified algorithm presented here yields the best comparison with the 0.5° resolution river networks on which the upscaled coarse resolution networks are based.
A Topological Phase Transition in Models of River Networks
Oppenheim, Jacob; Magnasco, Marcelo
2012-02-01
The classical Scheidegger model of river network formation and evolution is investigated on non-Euclidean geometries, which model the effects of regions of convergent and divergent flows - as seen around lakes and drainage off mountains, respectively. These new models may be differentiated by the number of basins formed. Using the divergence as an order parameter, we see a phase transition in the number of distinct basins at the point of a flat landscape. This is a surprising property of the statistics of river networks and suggests significantly different properties for riverine networks in uneven topography and vascular networks of arteries versus those of veins among others.
Dynamic ANN Modeling for Flood Forecasting in a River Network
Roy, Parthajit; Choudhury, P. S.; Saharia, Manabendra
2010-10-01
An experiment on predicting flood flows at each of the upstream and a down stream section of a river network is presented using focused Time Lagged Recurrent Neural Network with three different memories like TDNN memory, Gamma memory and Laguarre memory. This paper focuses on application of memory to the input layer of a TLRN in developing flood forecasting models for multiple sections in a river system. The study shows the Gamma memory has better applicability followed by TDNN and Laguarre memory.
Geometry of River Networks; 1, Scaling, Fluctuations, and Deviations
Dodds, P S; Dodds, Peter Sheridan; Rothman, Daniel H.
2000-01-01
This article is the first in a series of three papers investigating the detailed geometry of river networks. Large-scale river networks mark an important class of two-dimensional branching networks, being not only of intrinsic interest but also a pervasive natural phenomenon. In the description of river network structure, scaling laws are uniformly observed. Reported values of scaling exponents vary suggesting that no unique set of scaling exponents exists. To improve this current understanding of scaling in river networks and to provide a fuller description of branching network structure, we report here a theoretical and empirical study of fluctuations about and deviations from scaling. We examine data for continent-scale river networks such as the Mississippi and the Amazon and draw inspiration from a simple model of directed, random networks. We center our investigations on the scaling of the length of sub-basin's dominant stream with its area, a characterization of basin shape known as Hack's law. We gene...
Automated upscaling of river networks for macroscale hydrological modeling
Wu, Huan; Kimball, John S.; Mantua, Nate; Stanford, Jack
2011-03-01
We developed a hierarchical dominant river tracing (DRT) algorithm for automated extraction and spatial upscaling of basin flow directions and river networks using fine-scale hydrography inputs (e.g., flow direction, river networks, and flow accumulation). In contrast with previous upscaling methods, the DRT algorithm utilizes information on global and local drainage patterns from baseline fine-scale hydrography to determine upscaled flow directions and other critical variables including upscaled basin area, basin shape, and river lengths. The DRT algorithm preserves the original baseline hierarchical drainage structure by tracing each entire flow path from headwater to river mouth at fine scale while prioritizing successively higher order basins and rivers for tracing. We applied the algorithm to produce a series of global hydrography data sets from 1/16° to 2° spatial scales in two geographic projections (WGS84 and Lambert azimuthal equal area). The DRT results were evaluated against other alternative upscaling methods and hydrography data sets for continental U.S. and global domains. These results show favorable DRT upscaling performance in preserving baseline fine-scale river network information including: (1) improved, automated extraction of flow directions and river networks at any spatial scale without the need for manual correction; (2) consistency of river network, basin shape, basin area, river length, and basin internal drainage structure between upscaled and baseline fine-scale hydrography; and (3) performance largely independent of spatial scale, geographic region, and projection. The results of this study include an initial set of DRT upscaled global hydrography maps derived from HYDRO1K baseline fine-scale hydrography inputs; these digital data are available online for public access at ftp://ftp.ntsg.umt.edu/pub/data/DRT/.
Dewdney, A. K.
1991-01-01
Explores the subject of fractal geometry focusing on the occurrence of fractal-like shapes in the natural world. Topics include iterated functions, chaos theory, the Lorenz attractor, logistic maps, the Mandelbrot set, and mini-Mandelbrot sets. Provides appropriate computer algorithms, as well as further sources of information. (JJK)
Osler, Thomas J.
1999-01-01
Because fractal images are by nature very complex, it can be inspiring and instructive to create the code in the classroom and watch the fractal image evolve as the user slowly changes some important parameter or zooms in and out of the image. Uses programming language that permits the user to store and retrieve a graphics image as a disk file.…
Directory of Open Access Journals (Sweden)
Tatjana eStadnitski
2012-05-01
Full Text Available When investigating fractal phenomena, the following questions are fundamental for the applied researcher: (1 What are essential statistical properties of 1/f noise? (2 Which estimators are available for measuring fractality? (3 Which measurement instruments are appropriate and how are they applied? The purpose of this article is to give clear and comprehensible answers to these questions. First, theoretical characteristics of a fractal pattern (self-similarity, long memory, power law and the related fractal parameters (the Hurst coefficient, the scaling exponent, the fractional differencing parameter d of the ARFIMA methodology, the power exponent of the spectral analysis are discussed. Then, estimators of fractal parameters from different software packages commonly used by applied researchers (R, SAS, SPSS are introduced and evaluated. Advantages, disadvantages, and constrains of the popular estimators are illustrated by elaborate examples. Finally, crucial steps of fractal analysis (plotting time series data, autocorrelation and spectral functions; performing stationarity tests; choosing an adequate estimator; estimating fractal parameters; distinguishing fractal processes from short memory patterns are demonstrated with empirical time series.
Stadnitski, Tatjana
2012-01-01
WHEN INVESTIGATING FRACTAL PHENOMENA, THE FOLLOWING QUESTIONS ARE FUNDAMENTAL FOR THE APPLIED RESEARCHER: (1) What are essential statistical properties of 1/f noise? (2) Which estimators are available for measuring fractality? (3) Which measurement instruments are appropriate and how are they applied? The purpose of this article is to give clear and comprehensible answers to these questions. First, theoretical characteristics of a fractal pattern (self-similarity, long memory, power law) and the related fractal parameters (the Hurst coefficient, the scaling exponent α, the fractional differencing parameter d of the autoregressive fractionally integrated moving average methodology, the power exponent β of the spectral analysis) are discussed. Then, estimators of fractal parameters from different software packages commonly used by applied researchers (R, SAS, SPSS) are introduced and evaluated. Advantages, disadvantages, and constrains of the popular estimators ([Formula: see text] power spectral density, detrended fluctuation analysis, signal summation conversion) are illustrated by elaborate examples. Finally, crucial steps of fractal analysis (plotting time series data, autocorrelation, and spectral functions; performing stationarity tests; choosing an adequate estimator; estimating fractal parameters; distinguishing fractal processes from short-memory patterns) are demonstrated with empirical time series.
Euclidean and fractal geometry of microvascular networks in normal and neoplastic pituitary tissue.
Di Ieva, Antonio; Grizzi, Fabio; Gaetani, Paolo; Goglia, Umberto; Tschabitscher, Manfred; Mortini, Pietro; Rodriguez y Baena, Riccardo
2008-07-01
In geometrical terms, tumour vascularity is an exemplary anatomical system that irregularly fills a three-dimensional Euclidean space. This physical characteristic and the highly variable shapes of the vessels lead to considerable spatial and temporal heterogeneity in the delivery of oxygen, nutrients and drugs, and the removal of metabolites. Although these biological characteristics are well known, quantitative analyses of newly formed vessels in two-dimensional histological sections still fail to view their architecture as a non-Euclidean geometrical entity, thus leading to errors in visual interpretation and discordant results from different laboratories concerning the same tumour. We here review the literature concerning microvessel density estimates (a Euclidean-based approach quantifying vascularity in normal and neoplastic pituitary tissues) and compare the results. We also discuss the limitations of Euclidean quantitative analyses of vascularity and the helpfulness of a fractal geometry-based approach as a better means of quantifying normal and neoplastic pituitary microvasculature.
RSMM: a network language for modeling pollutants in river systems
Energy Technology Data Exchange (ETDEWEB)
Rao, N.B.; Standridge, C.R.; Schnoor, J.L.
1983-06-01
Predicting the steady state distribution of pollutants in rivers is important for water quality managers. A new simulation language, the River System Modeling Methodology (RSMM), helps users construct simulation models for analyzing river pollution. In RSMM, a network of nodes and branches represents a river system. Nodes represent elements such as junctions, dams, withdrawals, and pollutant sources; branches represent homogeneous river segments, or reaches. The RSMM processor is a GASP V program. Models can employ either the embedded Streeter-Phelps equations or user supplied equations. The user describes the network diagram with GASP-like input cards. RSMM outputs may be printed or stored in an SDL database. An interface between SDL and DISSPLA provides high quality graphical output.
Fractal actors and infrastructures
DEFF Research Database (Denmark)
Bøge, Ask Risom
2011-01-01
-network-theory (ANT) into surveillance studies (Ball 2002, Adey 2004, Gad & Lauritsen 2009). In this paper, I further explore the potential of this connection by experimenting with Marilyn Strathern’s concept of the fractal (1991), which has been discussed in newer ANT literature (Law 2002; Law 2004; Jensen 2007). I...... under surveillance. Based on fieldwork conducted in 2008 and 2011 in relation to my Master’s thesis and PhD respectively, I illustrate fractal concepts by describing the acts, actors and infrastructure that make up the ‘DNA surveillance’ conducted by the Danish police....
Fractal Weyl law for Linux Kernel architecture
Ermann, L.; Chepelianskii, A. D.; Shepelyansky, D. L.
2011-01-01
We study the properties of spectrum and eigenstates of the Google matrix of a directed network formed by the procedure calls in the Linux Kernel. Our results obtained for various versions of the Linux Kernel show that the spectrum is characterized by the fractal Weyl law established recently for systems of quantum chaotic scattering and the Perron-Frobenius operators of dynamical maps. The fractal Weyl exponent is found to be ν ≈ 0.65 that corresponds to the fractal dimension of the network d ≈ 1.3. An independent computation of the fractal dimension by the cluster growing method, generalized for directed networks, gives a close value d ≈ 1.4. The eigenmodes of the Google matrix of Linux Kernel are localized on certain principal nodes. We argue that the fractal Weyl law should be generic for directed networks with the fractal dimension d < 2.
Energy Efficient Networks for Monitoring Water Quality in Subterranean Rivers
Directory of Open Access Journals (Sweden)
Fei Ge
2016-05-01
Full Text Available The fresh water in rivers beneath the Earth’s surface is as significant to humans as that on the surface. However, the water quality is difficult to monitor due to its unapproachable nature. In this work, we consider building networks to monitor water quality in subterranean rivers. The network node is designed to have limited functions of floating and staying in these rivers when necessary. We provide the necessary conditions to set up such networks and a topology building method, as well as the communication process between nodes. Furthermore, we provide every an node’s energy consumption model in the network building stage, the data acquiring and transmission stage. The numerical results show that the energy consumption in every node is different, and the node number should be moderate to ensure energy efficiency.
Denitrification in the Mississippi River network controlled by flow through river bedforms
Gomez-Velez, Jesus D.; Harvey, Judson W.; Cardenas, M. Bayani; Kiel, Brian
2015-12-01
Increasing nitrogen concentrations in the world's major rivers have led to over-fertilization of sensitive downstream waters. Flow through channel bed and bank sediments acts to remove riverine nitrogen through microbe-mediated denitrification reactions. However, little is understood about where in the channel network this biophysical process is most efficient, why certain channels are more effective nitrogen reactors, and how management practices can enhance the removal of nitrogen in regions where water circulates through sediment and mixes with groundwater--hyporheic zones. Here we present numerical simulations of hyporheic flow and denitrification throughout the Mississippi River network using a hydrogeomorphic model. We find that vertical exchange with sediments beneath the riverbed in hyporheic zones, driven by submerged bedforms, has denitrification potential that far exceeds lateral hyporheic exchange with sediments alongside river channels, driven by river bars and meandering banks. We propose that geomorphic differences along river corridors can explain why denitrification efficiency varies between basins in the Mississippi River network. Our findings suggest that promoting the development of permeable bedforms at the streambed--and thus vertical hyporheic exchange--would be more effective at enhancing river denitrification in large river basins than promoting lateral exchange through induced channel meandering.
Barnsley, Michael F
2012-01-01
""Difficult concepts are introduced in a clear fashion with excellent diagrams and graphs."" - Alan E. Wessel, Santa Clara University""The style of writing is technically excellent, informative, and entertaining."" - Robert McCartyThis new edition of a highly successful text constitutes one of the most influential books on fractal geometry. An exploration of the tools, methods, and theory of deterministic geometry, the treatment focuses on how fractal geometry can be used to model real objects in the physical world. Two sixteen-page full-color inserts contain fractal images, and a bonus CD of
以DEM提取流域水系河源的最小误差分析%Analysis of Minimum Error at River Source to Extract River Network Based on DEM
Institute of Scientific and Technical Information of China (English)
陈冬平; 陈莹; 陈兴伟
2011-01-01
With the development of hydrological model, extraction of river drainage network has been a hot topic in hydrology research. River drainage network was extracted based on topographic maps or drainage maps by digitization in the early years, but the result was influenced by data source resolution. There are presently two kinds of methods to extract river drainage network based on DEM. One is to overlay the extracted river drainage network based on DEM on the river digitalized maps which came from drainage maps or vector layer of river, to make the extract drainage network more similar to the actual river networks.But the accuracy of river drainage network depends on the resolution of drainage maps or vector layer of river. The other one is based on “inflection point” to extract river drainage network, however, the assumption of “inflection point” exists the problem of choice of scale-free interval. To solve the above problems, the river source minimum error (RSME) method was presented based on DEM in this paper. First,the relationship between the distance error of the actual river source and the extracted river network source and the size of grid was established; second, the minimum distance error was adopted as the principle to solve the problem of the uniqueness in watershed drainage network extraction, and then the river network was determined. Taking Jinjiang River as an example and using DEM with 30m resolution as data source, the RSME method was adopted to extract Jinjiang River drainage network on the platform of ArcGIS9.2. The result showed that the distance error between the river source and the extracted river network source is the smallest one when the grid numbers are up to 5814 and the minimum river length is 42m, the corresponding fractal dimension is 1. 389. Moreover, the result indicated that the proposed RSME method is reasonable to extract watershed drainage network.%目前,以水文模型提取流域水系已成为水文科学研究中的
Astaneh, Amin Faraji
2015-01-01
We use the Heat Kernel method to calculate the Entanglement Entropy for a given entangling region on a fractal. The leading divergent term of the entropy is obtained as a function of the fractal dimension as well as the walk dimension. The power of the UV cut-off parameter is (generally) a fractional number which indeed is a certain combination of these two indices. This exponent is known as the spectral dimension. We show that there is a novel log periodic oscillatory behavior in the entropy which has root in the complex dimension of a fractal. We finally indicate that the Holographic calculation in a certain Hyper-scaling violating bulk geometry yields the same leading term for the entanglement entropy, if one identifies the effective dimension of the hyper-scaling violating theory with the spectral dimension of the fractal. We provide more supports with comparing the behavior of the thermal entropy in terms of the temperature in these two cases.
Kinetic Signature of Fractal-like Filament Networks Formed by Orientational Linear Epitaxy
Hwang, Wonmuk; Eryilmaz, Esma
2014-07-01
We study a broad class of epitaxial assembly of filament networks on lattice surfaces. Over time, a scale-free behavior emerges with a 2.5-3 power-law exponent in filament length distribution. Partitioning between the power-law and exponential behaviors in a network can be used to find the stage and kinetic parameters of the assembly process. To analyze real-world networks, we develop a computer program that measures the network architecture in experimental images. Application to triaxial networks of collagen fibrils shows quantitative agreement with our model. Our unifying approach can be used for characterizing and controlling the network formation that is observed across biological and nonbiological systems.
Optimal box-covering algorithm for fractal dimension of complex networks
Schneider, Christian M; Andrade, Jose S; Herrmann, Hans J
2012-01-01
The self-similarity of complex networks is typically investigated through computational algorithms the primary task of which is to cover the structure with a minimal number of boxes. Here we introduce a box-covering algorithm that not only outperforms previous ones, but also finds optimal solutions. For the two benchmark cases tested, namely, the E. Coli and the WWW networks, our results show that the improvement can be rather substantial, reaching up to 15% in the case of the WWW network.
River network routing on the NHDPlus dataset
David, Cédric; Maidment, David,; Niu, Guo-Yue; Yang, Zong-Liang; Habets, Florence; Eijkhout, Victor
2011-01-01
International audience; The mapped rivers and streams of the contiguous United States are available in a geographic information system (GIS) dataset called National Hydrography Dataset Plus (NHDPlus). This hydrographic dataset has about 3 million river and water body reaches along with information on how they are connected into net- works. The U.S. Geological Survey (USGS) National Water Information System (NWIS) provides stream- ﬂow observations at about 20 thousand gauges located on theNHDP...
River network routing on the NHDPlus dataset
David, Cédric; Maidment, David,; Niu, Guo-Yue; Yang, Zong-Liang; Habets, Florence; Eijkhout, Victor
2011-01-01
International audience; The mapped rivers and streams of the contiguous United States are available in a geographic information system (GIS) dataset called National Hydrography Dataset Plus (NHDPlus). This hydrographic dataset has about 3 million river and water body reaches along with information on how they are connected into net- works. The U.S. Geological Survey (USGS) National Water Information System (NWIS) provides stream- ﬂow observations at about 20 thousand gauges located on theNHDP...
Fractal Inequality: A Social Network Analysis of Global and Regional International Student Mobility
Macrander, Ashley
2017-01-01
Literature on global international student mobility (ISM) highlights the uneven nature of student flows--from the developing to the developed world--however, studies have yet to address whether this pattern is replicated within expanding regional networks. Utilizing social network analysis, UNESCO ISM data, and World Bank income classifications,…
Search for the optimality signature of river network development.
Paik, Kyungrock
2012-10-01
Whether the evolution of natural river networks pursues a certain optimal state has been a most intriguing and fundamental question. There have been many optimality hypotheses proposed but it has yet to be proved which of these best serves as a quantitative signature of river network development. Here, this fundamental question is investigated for the five hypotheses of "minimum total energy expenditure," "minimum total energy dissipation rate," "minimum total stream power," "minimum global energy expenditure rate," and "minimum topological energy." Using simple example landscapes, I examined whether any of these hypotheses pursues both the treelike river network formation and the concave stream longitudinal profile, the two characteristic patterns of natural landscapes. It is found that none of these hypotheses captures both patterns under the steady-state condition where the balance between tectonic uplift and sediment loss is satisfied. These findings are further verified through simulations of landscapes that satisfy given optimality criteria using an optimization method.
Causes and consequences of habitat fragmentation in river networks.
Fuller, Matthew R; Doyle, Martin W; Strayer, David L
2015-10-01
Increases in river fragmentation globally threaten freshwater biodiversity. Rivers are fragmented by many agents, both natural and anthropogenic. We review the distribution and frequency of these major agents, along with their effects on connectivity and habitat quality. Most fragmentation research has focused on terrestrial habitats, but theories and generalizations developed in terrestrial habitats do not always apply well to river networks. For example, terrestrial habitats are usually conceptualized as two-dimensional, whereas rivers often are conceptualized as one-dimensional or dendritic. In addition, river flow often leads to highly asymmetric effects of barriers on habitat and permeability. New approaches tailored to river networks can be applied to describe the network-wide effects of multiple barriers on both connectivity and habitat quality. The net effects of anthropogenic fragmentation on freshwater biodiversity are likely underestimated, because of time lags in effects and the difficulty of generating a single, simple signal of fragmentation that applies to all aquatic species. We conclude by presenting a decision tree for managing freshwater fragmentation, as well as some research horizons for evaluating fragmented riverscapes. © 2015 New York Academy of Sciences.
Water quality modeling for a tidal river network: A case study of the Suzhou River
Institute of Scientific and Technical Information of China (English)
Le FENG; Deguan WANG; Bin CHEN
2011-01-01
Combined with the basic characteristics of Suzhou plain river network,two modules are established,one of which is the hydrodynamic module using the water level node method involving gate operation,while the other is the water quality module based on the principle of WASP5 (water quality analysis simulation program5).These two modules were coupled and verified by the monitoring data of Suzhou River network.The results showed that calculation errors ofNH+4 -N and DO for the model were in the ranges of-15％-13％ and -18％-16％,respectively.Despite of the deviations between the monitoring data and simulation result,the calculation accuracy of the model conforms to the practical engineering requirement.Therefore,the proposed coupling model may be useful for water quality simulation and assessment for river network under tidal influences.
Water quality modeling for a tidal river network: A case study of the Suzhou River
Feng, Le; Wang, Deguan; Chen, Bin
2011-12-01
Combined with the basic characteristics of Suzhou plain river network, two modules are established, one of which is the hydrodynamic module using the water level node method involving gate operation, while the other is the water quality module based on the principle of WASP5 (water quality analysis simulation program5). These two modules were coupled and verified by the monitoring data of Suzhou River network. The results showed that calculation errors of NH{4/+}-N and DO for the model were in the ranges of -15%-13% and -18%-16%, respectively. Despite of the deviations between the monitoring data and simulation result, the calculation accuracy of the model conforms to the practical engineering requirement. Therefore, the proposed coupling model may be useful for water quality simulation and assessment for river network under tidal influences.
Surface Deformation Analysis by Means of Fractal Dimension and Lacunarity Approaches
Mahmood, S.; Shahzad, F.; Glaouguen, R.
2009-05-01
Fractals and scaling laws such as river networks and runoff series are abundant in nature, and geometry of river networks and basins is a superb example of this. The unrelenting competition between tectonics, surface uplift and erosional processes on the earth has resulted in a variety of drainage patterns by linearizing the normal flow patterns of river networks. These patterns are fractals and their variable spatial distribution can be used to examine the vulnerability of surface deformation. At first we extract the drainage network from Shuttle Radar Topographic Mission's digital elevation data (SRTM-90m) using D8 algorithm. We convert the drainage network into a binary image where the area of interests (AOIs) i.e. drainage are represented with pixels value of 1. The fractal dimension (D) analysis using Box Counting method is used to identify the anomalous drainage patterns of vulnerable sites. We prepare a D distribution map using a moving window of 1 arc sec. by 1 arc sec. on the binary image of river network. The space occupied by AOIs reveals variable distribution of D and lower values suggest that the drainage pattern has become linearized due to the influence of tectonics and surface processes. We use lacunarity analysis using Gliding Box method to see the relative vulnerability as two AOIs can have similar D values. The AOIs with a high lacunarity of drainage pattern are more vulnerable than AOIs with lower lacunarity values. Three AOIs i.e. Vanch and Yazgulem Basin (VYB) in northwestern Pamir, Tirch Mir Fault Zone (TMFZ) in Hindukush region, and Central Badakhshan (CB) with high vulnerability and three sites i.e. Central Pamir, Shiveh Lake Region in Afghanistan and Darvaz Fault Zone with medium vulnerability were identified using fractal dimension. The lacunarity analysis was used to diferentiate between the relative vulnerability of these AOIs. Results from Pyanj river network and adjacent areas show that VYB, TMFZ, and CB have relatively high
Cantorian Fractal Spacetime and Quantum-like Chaos in Neural Networks of the Human Brain
Selvam, A M
1998-01-01
The neural networks of the human brain act as very efficient parallel processing computers co-ordinating memory related responses to a multitude of input signals from sensory organs. Information storage, update and appropriate retrieval are controlled at the molecular level by the neuronal cytoskeleton which serves as the internal communication network within neurons. Information flow in the highly ordered parallel networks of the filamentous protein polymers which make up the cytoskeleton may be compared to atmospheric flows which exhibit long-range spatiotemporal correlations, i.e. long-term memory. Such long-range spatiotemporal correlations are ubiquitous to real world dynamical systems and is recently identified as signature of self-organized criticality or chaos. The signatures of self-organized criticality i.e. long-range temporal correlations have recently been identified in the electrical activity of the brain. A recently developed non-deterministic cell dynamical system model for atmospheric flows p...
River network solution for a distributed hydrological model and applications
Jha, Raghunath; Herath, Srikantha; Musiake, Katumi
2000-02-01
A simultaneous solution for one-dimensional unsteady flow routing for a network of rivers has been developed, which can be used either with a complete distributed hydrological model, a simple rainfall-runoff model or as a stand alone river routing model. Either dynamic or kinematic solution schemes can be selected to simulate the river flows. The river network is either generated from the Digital Elevation Model (DEM) or directly input to the model. The model can handle any number of upstream channels and computational points. A sparse matrix solution algorithm is used to solve the 2N×2N matrix resulting from N nodes in the network. A submodule generates the initial water depth and discharge at each computational point from equilibrium discharge in the absence of observed initial conditions. The model is applied in three sub-catchments of the Chao Phraya river basin, Thailand, considering three different conditions. The simulated results show good agreement with observed discharges and provide insight to water level fluctuations, especially where tributaries join the main channel.
Spatial identification of tributary impacts in river networks
Christian E. Torgersen; Robert E. Gresswell; Douglas S. Bateman; Kelly M. Burnett
2008-01-01
The ability to assess spatial patterns of ecological conditions in river networks has been confounded by difficulties of measuring and perceiving features that are essentially invisible to observers on land and to aircraft and satellites from above. The nature of flowing water, which is opaque or at best semi-transparent, makes it difficult to visualize fine-scale...
ARPA LOMBARDIA river gauging network: a great daily effort
Cislaghi, Matteo; Calabrese, Michele; Condemi, Leonardo; Di Priolo, Sara; Parravicini, Paola; Rondanini, Chiara; Russo, Michele; Cazzuli, Orietta; Mussin, Mauro; Serra, Roberto
2017-04-01
ARPA Lombardia is the Environmental Protection Agency of Lombardy, a wide region in northern Italy. ARPA is in charge of river monitoring either for Civil Protection or water balance purposes. Lombardy is characterized by a very complex territory; rivers start from the alpine areas and end in the Po river plain. Each mountain or plain area has specific hydrological features that has to be considered when planning a monitoring network. Moreover, human activities (such as lake regulation, agriculture diversions, hydropower plants with regulation structure etc) add anthropic interferences on the natural river system and can invalidate the collected data. In the last 10 years ARPA performed a major revision of the river gauging network. Each station was analysed using well defined criteria based on the required information (water balance or flood monitoring) and on the suitability of the gauging site (hydraulic characteristic or accessibility for spot measures). In the end more than 30% of the network was revised, many stations were closed and other installed. Particular attention was given to the discharge estimation. Many sites are characterized by backflow effect due to river confluences or to hydropower plants with water regulation structures. In these cases the classic rating curve approach can not be applied. Thus, for the first time in Italy, water velocity side looking doppler sensors were installed on natural rivers and the discharge is estimated with the index velocity method. The Italian Civil Protection Agency requires high transmission standards. No data can be lost for transmission failures and data has to be available every 30 minutes. For these reasons ARPA implemented a double transmission system: the first is based on the existing GPRS network managed by private operators, the second is based on a radio network directly installed by ARPA and totally dedicated to data transmission. This double approach ensures a very robust transmission and it allows
The conundrum of functional brain networks: small-world or fractal modularity
Gallos, Lazaros K; Sigman, Mariano
2011-01-01
The human brain is organized in functional modules. Such an organization poses a conundrum: modules ought to be sufficiently independent to guarantee functional specialization and sufficiently connected to bind multiple processors for efficient information transfer. It is commonly accepted that small-world architecture may solve this problem. However, there is intrinsic tension between shortcuts generating small-worlds and the persistence of modules. Here we provide a solution to this puzzle. We show that the functional brain network formed by percolation of strong links is highly modular. Contrary to the common view, modules are self-similar and therefore are very far from being small-world. Incorporating the weak ties to the network converts it into a small-world preserving an underlying backbone of well-defined modules. Weak ties are organized precisely as predicted by theory maximizing information transfer with minimal wiring costs. This trade-off architecture is reminiscent of the "strength of weak ties"...
Mishra, Jibitesh
2007-01-01
The book covers all the fundamental aspects of generating fractals through L-system. Also it provides insight to various researches in this area for generating fractals through L-system approach & estimating dimensions. Also it discusses various applications of L-system fractals. Key Features: - Fractals generated from L-System including hybrid fractals - Dimension calculation for L-system fractals - Images & codes for L-system fractals - Research directions in the area of L-system fractals - Usage of various freely downloadable tools in this area - Fractals generated from L-System including hybrid fractals- Dimension calculation for L-system fractals- Images & codes for L-system fractals- Research directions in the area of L-system fractals- Usage of various freely downloadable tools in this area
LANDSCAPE STRUCTURES AND FRACTAL ANALYSES OF GUANSI RIVER WATERSHED%官司河流域景观结构变化及其分形研究
Institute of Scientific and Technical Information of China (English)
陈俊华; 何政伟; 龚固堂; 许辉熙; 朱志芳; 吴雪仙; 慕长龙
2013-01-01
By application of forest distribution map and remote sensing image in 2005 (IKONOS), land usage database was established. Each landscape elements of Guansi river watershed were analyzed by fractal theory. The results showed; 0the cultivated land and forestry land area accounted for absolute advantage, which were the matrix of landscape in this area. The land usage type changed greatly, while the area of forest land, roads, the waters expanded unceasingly. (2)The diversity index of construction land, water and land was the largest, and the advantage degree was also more obvious, while the diversity index and advantage degree of each forest land were also smaller. (3) The fractal dimension of forest land and land was greater than other landscape types, while the stability index was smaller. That illustrated the two landscape type distribution was more complicated and irregular, stability was poorer. The fractal dimension of building lands and waters was low, close to 1, which showed the two types of distribution on a smaller scale, plaques more rules. According to the dynamic change of fractal dimension, besides the road and water area, other landscape types were increased, which showed that human beings to this several types of utilization degree more complicated.%利用1995年森林资源分布图和2005年IKONOS遥感影像构建了土地利用GIS数据库,通过利用分形理论对官司河流域的各景观要素进行分析,结果表明:①耕地和林业用地面积占绝对优势,是该区域景观的基质,土地利用类型变化较大,林地、道路、水域的面积不断扩大；②建筑用地、水域和耕地的多样性指数最大,优势度也较为明显,而各类林业用地多样性指数和优势度均较小；③林地和耕地的分维数大于其它景观类型,而稳定性指数小于其它类型,说明这两种景观类型分布较为复杂和不规则,稳定性较差,建筑用地和水域的分维值较低,接近于“1”,说明这两
Nitrous oxide emission from denitrification in stream and river networks
Beaulieu, J.J.; Tank, J.L.; Hamilton, S.K.; Wollheim, W.M.; Hall, R.O.; Mulholland, P.J.; Peterson, B.J.; Ashkenas, L.R.; Cooper, L.W.; Dahm, Clifford N.; Dodds, W.K.; Grimm, N. B.; Johnson, S.L.; McDowell, W.H.; Poole, G.C.; Maurice, Valett H.; Arango, C.P.; Bernot, M.J.; Burgin, A.J.; Crenshaw, C.L.; Helton, A.M.; Johnson, L.T.; O'Brien, J. M.; Potter, J.D.; Sheibley, R.W.; Sobota, D.J.; Thomas, S.M.
2011-01-01
Nitrous oxide (N2O) is a potent greenhouse gas that contributes to climate change and stratospheric ozone destruction. Anthropogenic nitrogen (N) loading to river networks is a potentially important source of N 2O via microbial denitrification that converts N to N2O and dinitrogen (N2). The fraction of denitrified N that escapes as N2O rather than N2 (i.e., the N2O yield) is an important determinant of how much N2O is produced by river networks, but little is known about the N2O yield in flowing waters. Here, we present the results of whole-stream 15N-tracer additions conducted in 72 headwater streams draining multiple land-use types across the United States. We found that stream denitrification produces N2O at rates that increase with stream water nitrate (NO3-) concentrations, but that production, but does not increase the N2O yield. In our study, most streams were sources of N2O to the atmosphere and the highest emission rates were observed in streams draining urban basins. Using a global river network model, we estimate that microbial N transformations (e.g., denitrification and nitrification) convert at least 0.68 Tg??y -1 of anthropogenic N inputs to N2O in river networks, equivalent to 10% of the global anthropogenic N2O emission rate. This estimate of stream and river N2O emissions is three times greater than estimated by the Intergovernmental Panel on Climate Change.
Modeling Nitrogen Processing in Northeast US River Networks
Whittinghill, K. A.; Stewart, R.; Mineau, M.; Wollheim, W. M.; Lammers, R. B.
2013-12-01
Due to increased nitrogen (N) pollution from anthropogenic sources, the need for aquatic ecosystem services such as N removal has also increased. River networks provide a buffering mechanism that retains or removes anthropogenic N inputs. However, the effectiveness of N removal in rivers may decline with increased loading and, consequently, excess N is eventually delivered to estuaries. We used a spatially distributed river network N removal model developed within the Framework for Aquatic Modeling in the Earth System (FrAMES) to examine the geography of N removal capacity of Northeast river systems under various land use and climate conditions. FrAMES accounts for accumulation and routing of runoff, water temperatures, and serial biogeochemical processing using reactivity derived from the Lotic Intersite Nitrogen Experiment (LINX2). Nonpoint N loading is driven by empirical relationships with land cover developed from previous research in Northeast watersheds. Point source N loading from wastewater treatment plants is estimated as a function of the population served and the volume of water discharged. We tested model results using historical USGS discharge data and N data from historical grab samples and recently initiated continuous measurements from in-situ aquatic sensors. Model results for major Northeast watersheds illustrate hot spots of ecosystem service activity (i.e. N removal) using high-resolution maps and basin profiles. As expected, N loading increases with increasing suburban or agricultural land use area. Network scale N removal is highest during summer and autumn when discharge is low and river temperatures are high. N removal as the % of N loading increases with catchment size and decreases with increasing N loading, suburban land use, or agricultural land use. Catchments experiencing the highest network scale N removal generally have N inputs (both point and non-point sources) located in lower order streams. Model results can be used to better
Darwinian Evolution and Fractals
Carr, Paul H.
2009-05-01
Did nature's beauty emerge by chance or was it intelligently designed? Richard Dawkins asserts that evolution is blind aimless chance. Michael Behe believes, on the contrary, that the first cell was intelligently designed. The scientific evidence is that nature's creativity arises from the interplay between chance AND design (laws). Darwin's ``Origin of the Species,'' published 150 years ago in 1859, characterized evolution as the interplay between variations (symbolized by dice) and the natural selection law (design). This is evident in recent discoveries in DNA, Madelbrot's Fractal Geometry of Nature, and the success of the genetic design algorithm. Algorithms for generating fractals have the same interplay between randomness and law as evolution. Fractal statistics, which are not completely random, characterize such phenomena such as fluctuations in the stock market, the Nile River, rainfall, and tree rings. As chaos theorist Joseph Ford put it: God plays dice, but the dice are loaded. Thus Darwin, in discovering the evolutionary interplay between variations and natural selection, was throwing God's dice!
Directory of Open Access Journals (Sweden)
Andy P. Dedecker
2002-01-01
Full Text Available Modelling has become an interesting tool to support decision making in water management. River ecosystem modelling methods have improved substantially during recent years. New concepts, such as artificial neural networks, fuzzy logic, evolutionary algorithms, chaos and fractals, cellular automata, etc., are being more commonly used to analyse ecosystem databases and to make predictions for river management purposes. In this context, artificial neural networks were applied to predict macroinvertebrate communities in the Zwalm River basin (Flanders, Belgium. Structural characteristics (meandering, substrate type, flow velocity and physical and chemical variables (dissolved oxygen, pH were used as predictive variables to predict the presence or absence of macroinvertebrate taxa in the headwaters and brooks of the Zwalm River basin. Special interest was paid to the frequency of occurrence of the taxa as well as the selection of the predictors and variables to be predicted on the prediction reliability of the developed models. Sensitivity analyses allowed us to study the impact of the predictive variables on the prediction of presence or absence of macroinvertebrate taxa and to define which variables are the most influential in determining the neural network outputs.
Abghari, H.; van de Giesen, N.; Mahdavi, M.; Salajegheh, A.
2009-04-01
Artificial intelligence modeling of nonstationary rainfall-runoff has some restrictions in simulation accuracy due to the complexity and nonlinearity of training patterns. Preprocessing of trainings dataset could determine homogeneity of rainfall-runoff patterns before modeling. In this presentation, a new hybrid model of Artificial Intelligence in conjunction with clustering is introduced and applied to flow prediction. Simulation of Nazloochaei river flow in North-West Iran was the case used for development of a PNN-RBF model. PNN classify a training dataset in two groups based on Parezen theory using unsupervised classification. Subsequently each data group is used to train and test two RBF networks and the results are compared to the application of all data in a RBF network without classification. Results show that classification of rainfall-runoff patterns using PNN and prediction of runoff with RBF increase prediction precise of networks. Keywords: Probabilistic Neural Network, Radial Base Function Neural Network, Parezen theory, River Flow Prediction
Topological phase transition in the Scheidegger model of river networks
Oppenheim, Jacob N.; Magnasco, Marcelo O.
2012-08-01
Transport networks are found at the heart of myriad natural systems, yet are poorly understood, except for the case of river networks. The Scheidegger model, in which rivers are convergent random walks, has been studied only in the case of flat topography, ignoring the variety of curved geometries found in nature. Embedding this model on a cone, we find a convergent and a divergent phase, corresponding to few, long basins and many, short basins, respectively, separated by a singularity, indicating a phase transition. Quantifying basin shape using Hacks law l˜ah gives distinct values for h, providing a method of testing our hypotheses. The generality of our model suggests implications for vascular morphology, in particular, differing number and shapes of arterial and venous trees.
Khokhlov, D L
1999-01-01
The model of the universe is considered in which background of the universe is not defined by the matter but is a priori specified as a homogenous and isotropic flat space. The scale factor of the universe follows the linear law. The scale of mass changes proportional to the scale factor. This leads to that the universe has the fractal structure with a power index of 2.
Institute of Scientific and Technical Information of China (English)
张丽红; 刘永顺; 彭年; 聂保锋
2011-01-01
The values of fractal dimension of river system reflect their degree of development and complexity of river channel. On the basis of remote sensing data, fractal geometry and image analysis software, the values of boxcounting fractal dimension for the radial river system of Changbaishan volcanic area are calculated,and carried out statistical calculations in EXCEL. The region can be subdivided into four distinct areas characterized by different geomorpholo-gic features and their values of fractal dimension also can be obtained respectively. The results show that the maximum value D= 1. 425 of fractal dimension of river system in the Changbai-shan volcanic area appears in the west part of volcanic area while the minimum D = 1. 212 in the eastern part. The differences of fraetal dimension values of the four distinct areas show the erosive degree of the fluvial landform, but in the whole, the degree of development is still in the primary stage. The contributing factors of fluvial landform are related with volcanic topography,volcanic activities and their forming fracture, mass movement and rock of underlying surface,among which the fracture is main.%水系分维反映了水系的发育程度,体现了河道的复杂程度.以TM遥感数据和分形几何理论为基础,应用图像分析软件ENVI对长白山火山区水系进行了盒维数计算,经统计分析得到了该区四个子区域水系及整个区域水系的分维数.结果表明:长白山火山区水系分维数西部最大D=1.425,东部最小D=1.212;四个分区分维数的差异直接反映了其流域地貌侵蚀发育的程度,但从整体上来看仍处于河流地貌发育的初级阶段.流域地貌的发育状态与火山地形、火山活动及其形成的断裂构造、块体运动以及下覆地面岩性有关,其中断裂构造是最主要的.
Population persistence under advection-diffusion in river networks.
Ramirez, Jorge M
2012-11-01
An integro-differential equation on a tree graph is used to model the time evolution and spatial distribution of a population of organisms in a river network. Individual organisms become mobile at a constant rate, and disperse according to an advection-diffusion process with coefficients that are constant on the edges of the graph. Appropriate boundary conditions are imposed at the outlet and upstream nodes of the river network. The local rates of population growth/decay and that by which the organisms become mobile, are assumed constant in time and space. Imminent extinction of the population is understood as the situation whereby the zero solution to the integro-differential equation is stable. Lower and upper bounds for the eigenvalues of the dispersion operator, and related Sturm-Liouville problems are found. The analysis yields sufficient conditions for imminent extinction and/or persistence in terms of the values of water velocity, channel length, cross-sectional area and diffusivity throughout the river network.
Delineating riparian zones for entire river networks using geomorphological criteria
Directory of Open Access Journals (Sweden)
D. Fernández
2012-03-01
Full Text Available Riparian zone delineation is a central issue for riparian and river ecosystem management, however, criteria used to delineate them are still under debate. The area inundated by a 50-yr flood has been indicated as an optimal hydrological descriptor for riparian areas. This detailed hydrological information is, however, not usually available for entire river corridors, and is only available for populated areas at risk of flooding. One of the requirements for catchment planning is to establish the most appropriate location of zones to conserve or restore riparian buffer strips for whole river networks. This issue could be solved by using geomorphological criteria extracted from Digital Elevation Models. In this work we have explored the adjustment of surfaces developed under two different geomorphological criteria with respect to the flooded area covered by the 50-yr flood, in an attempt to rapidly delineate hydrologically-meaningful riparian zones for entire river networks. The first geomorphological criterion is based on the surface that intersects valley walls at a given number of bankfull depths above the channel (BFDAC, while the second is based on the surface defined by a~threshold value indicating the relative cost of moving from the stream up to the valley, accounting for slope and elevation change (path distance. As the relationship between local geomorphology and 50-yr flood has been suggested to be river-type dependant, we have performed our analyses distinguishing between three river types corresponding with three valley morphologies: open, shallow vee and deep vee valleys (in increasing degree of valley constrainment. Adjustment between the surfaces derived from geomorphological and hydrological criteria has been evaluated using two different methods: one based on exceeding areas (minimum exceeding score and the other on the similarity among total area values. Both methods have pointed out the same surfaces when looking for those that
Applying comparative fractal analysis to infer origin and process in channels on Earth and Mars
Balakrishnan, A.; Rice-Snow, S.; Hampton, B. A.
2010-12-01
Recently there has been a large amount of interest in identifying the nature of channels on (extra terrestrial) bodies. These studies are closely linked to the search for water (and ultimately signs of life) and are unarguably important. Current efforts in this direction rely on identifying geomorphic characteristics of these channels through painstaking analysis of multiple high resolution images. Here we present a new and simple technique that shows significant potential in its ability to distinguish between lava and water channels. Channels formed by water or lava on earth (as depicted in map view) display sinuosity over a large scale of range. Their geometries often point to the fluid dynamics, channel gradient, type of sediments in the river channels and for lava channels, it has been suggested that they are indicative of the thermal characteristics of the flow. The degree of this sinuosity in geometry can be measured using the divider method, and represented by fractal dimension (D) values. The higher D value corresponds to higher degree of sinuosity and channel irregularity and vice versa. Here we apply this fractal analysis to compare channels on Earth and Mars using D values extracted from satellite images. The fractal dimensions computed in this work for terrestrial river channels range from 1.04 - 1.38, terrestrial lava channels range from 1.01-1.10 and Martian channels range from 1.01 - 1.18. For terrestrial channels, preliminary results from river networks attain a fractal dimension greater than or equal to 1.1 while lava channels have fractal dimension less than or equal to 1.1. This analysis demonstrates the higher degree of irregularity present in rivers as opposed to lava channels and ratifies the utility of using fractal dimension to identify the source of channels on earth, and by extension, extra terrestrial bodies. Initial estimates of the fractal dimension from Mars fall within the same ranges as the lava channels on Earth. Based on what has
Boutron, Olivier; Got, Patrice; Caro, Audrey; Salles, Christian; Perrin, Jean-Louis; Rodier, Claire; Marchand, Pierre; David, Arthur; Neves, Ramiro; Tournoud, Marie-George
2010-05-01
The sanitary microbiological condition of Mediterranean coastal rivers is a growing concern because of its impacts on the compliance of receiving coastal and transitional waters which are of high recreational and economic values. Due to strong anthropogenic pressures, coastal rivers do not often meet the required standards and guidelines, expressed in terms of coliforms and streptococci abundances. These indicator bacteria themselves are usually not pathogenic, but they allow the tracking of recent faecal contamination and the possible presence of pathogenic micro-organisms in rivers, in an easier and less costly way. Mediterranean coastal rivers are subject to long dry periods cut by short duration flush flood events. During dry and low flow period, faecal bacteria often bound to particulate matter tend to settle in the riverbed and to constitute an in-stream store in which bacteria are able to survive for long durations and even to multiply. During intense rainfall events and floods, peaks of faecal contamination occur in rivers due to entrainment of stored bacteria in river channels by the flood. Modelling these intermittent rivers poses a numerical challenge due to the high spatial and temporal gradients and proximity of zero value. These conditions are not well handled or not simulated at all in most of the currently available watershed and rivers models. The objective of this work is to simulate the transfer and fate of faecal coliforms and faecal streptococci in an intermittent river, considering a dry period followed by a flash flood. The river considered is the French river "La Vène", close to Montpellier, for which data of several dry periods and floods are available. The model considered is Mohid River Network (MRN), (www.mohid.com). MRN is a 1D hydrodynamic model that considers a network of tributaries and allows for dynamic time step. It can also compute properties transport, such as faecal bacteria, and compute water storage in pools, transmission
Evolution and selection of river networks: statics, dynamics, and complexity.
Rinaldo, Andrea; Rigon, Riccardo; Banavar, Jayanth R; Maritan, Amos; Rodriguez-Iturbe, Ignacio
2014-02-18
Moving from the exact result that drainage network configurations minimizing total energy dissipation are stationary solutions of the general equation describing landscape evolution, we review the static properties and the dynamic origins of the scale-invariant structure of optimal river patterns. Optimal channel networks (OCNs) are feasible optimal configurations of a spanning network mimicking landscape evolution and network selection through imperfect searches for dynamically accessible states. OCNs are spanning loopless configurations, however, only under precise physical requirements that arise under the constraints imposed by river dynamics--every spanning tree is exactly a local minimum of total energy dissipation. It is remarkable that dynamically accessible configurations, the local optima, stabilize into diverse metastable forms that are nevertheless characterized by universal statistical features. Such universal features explain very well the statistics of, and the linkages among, the scaling features measured for fluvial landforms across a broad range of scales regardless of geology, exposed lithology, vegetation, or climate, and differ significantly from those of the ground state, known exactly. Results are provided on the emergence of criticality through adaptative evolution and on the yet-unexplored range of applications of the OCN concept.
Olson, C. J.; Reichhardt, C.; Nori, F.
1997-03-01
Vortices moving in dirty superconductors can form intricate flow patterns, resembling fluid rivers, as they interact with the pinning landscape (F. Nori, Science 271), 1373 (1996).. Weaker pinning produces relatively straight nori>vortex channels, while stronger pinning results in the formation of one or more winding channels that carry all flow. This corresponds to a crossover from elastic flow to plastic flow as the pinning strength is increased. For several pinning parameters, we find the fractal dimension of the channels that form, the vortex trail density, the distance travelled by vortices as they pass through the sample, the branching ratio, the sinuosity, and the size distribution of the rivers, and we compare our rivers with physical rivers that follow Horton's laws.
Cui, Baoshan; Wang, Chongfang; Tao, Wendong; You, Zheyuan
2009-08-01
Vulnerability of river channels to urbanization has been lessened by the extensive construction of artificial water control improvements. The challenge, however, is that traditional engineering practices on isolated parts of a river may disturb the hydrologic continuity and interrupt the natural state of ecosystems. Taking the Xiaoqinghe River basin as a whole, we developed a river channel network design to mitigate river risks while sustaining the river in a state as natural as possible. The river channel risk from drought during low-flow periods and flood during high-flow periods as well as the potential for water diversion were articulated in detail. On the basis of the above investigation, a network with "nodes" and "edges" could be designed to relieve drought hazard and flood risk respectively. Subsequently, the shortest path algorithm in the graph theory was applied to optimize the low-flow network by searching for the shortest path. The effectiveness assessment was then performed for the low-flow and high-flow networks, respectively. For the former, the network connectedness was evaluated by calculating the "gamma index of connectivity" and "alpha index of circuitry"; for the latter, the ratio of flood-control capacity to projected flood level was devised and calculated. Results show that the design boosted network connectivity and circuitry during the low-flow periods, indicating a more fluent flow pathway, and reduced the flood risk during the high-flow periods.
Di Ieva, A; Grizzi, F; Ceva-Grimaldi, G; Aimar, E; Serra, S; Pisano, P; Lorenzetti, M; Tancioni, F; Gaetani, P; Crotti, F; Tschabitscher, M; Matula, C; Rodriguez Y Baena, R
2010-06-01
In geometrical terms, tumor vascularity is an exemplary anatomical system that irregularly fills a three-dimensional Euclidean space. This physical characteristic, together with the highly variable vessel shapes and surfaces, leads to considerable spatial and temporal heterogeneity in the delivery of oxygen, nutrients and drugs, and the removal of metabolites. Although these biological features have now been well established, quantitative analyses of neovascularity in two-dimensional histological sections still fail to view tumor architecture in non-Euclidean terms, and this leads to errors in visually interpreting the same tumor, and discordant results from different laboratories. A review of the literature concerning the application of microvessel density (MVD) estimates, an Euclidean-based approach used to quantify vascularity in normal and neoplastic pituitary tissues, revealed some disagreements in the results and led us to discuss the limitations of the Euclidean quantification of vascularity. Consequently, we introduced fractal geometry as a better means of quantifying the microvasculature of normal pituitary glands and pituitary adenomas, and found that the use of the surface fractal dimension is more appropriate than MVD for analysing the vascular network of both. We propose extending the application of this model to the analysis of the angiogenesis and angioarchitecture of brain tumors.
Hydrologic controls on junction angle of river networks
Hooshyar, Milad; Singh, Arvind; Wang, Dingbao
2017-05-01
The formation and growth of river channels and their network evolution are governed by the erosional and depositional processes operating on the landscape due to the movement of water. The branching angles, i.e., the angle between two adjoining channels, in drainage networks are important features related to the network topology and contain valuable information about the forming mechanisms of the landscape. Based on the channel networks extracted from 1 m Digital Elevation Models of 120 catchments with minimal human impacts across the United States, we show that the junction angles have two distinct modes with α1¯≈49.5° and α2¯≈75.0°. The observed angles are physically explained as the optimal angles that result in minimum energy dissipation and are linked to the exponent characterizing the slope-area curve. Our findings suggest that the flow regimes, debris-flow dominated or fluvial, have distinct characteristic angles which are functions of the scaling exponent of the slope-area curve. These findings enable us to understand the geomorphic signature of hydrologic processes on drainage networks and develop more refined landscape evolution models.
Fractal organization of feline oocyte cytoplasm.
De Vico, G; Peretti, V; Losa, G A
2005-01-01
The present study aimed at verifying whether immature cat oocytes with morphologic irregular cytoplasm display self-similar features which can be analytically described by fractal analysis. Original images of oocytes collected by ovariectomy were acquired at a final magnification of 400x with a CCD video camera connected to an optic microscope. After greyscale thresholding segmentation of cytoplasm, image profiles were submitted to fractal analysis using FANAL++, a program which provided an analytical standard procedure for determining the fractal dimension (FD). The presentation of the oocyte influenced the magnitude of the fractal dimension with the highest FD of 1.91 measured on grey-dark cytoplasm characterized by a highly connected network of lipid droplets and intracellular membranes. Fractal analysis provides an effective quantitative descriptor of the real cytoplasm morphology, which can influence the acquirement of in vitro developmental competence, without introducing any bias or shape approximation and thus contributes to an objective and reliable classification of feline oocytes.
Fractal organization of feline oocyte cytoplasm
Directory of Open Access Journals (Sweden)
G De Vico
2009-06-01
Full Text Available The present study aimed at verifying whether immature cat oocytes with morphologic irregular cytoplasm display selfsimilar features which can be analytically described by fractal analysis. Original images of oocytes collected by ovariectomy were acquired at a final magnification of 400 X with a CCD video camera connected to an optic microscope. After greyscale thresholding segmentation of cytoplasm, image profiles were submitted to fractal analysis using FANAL++, a program which provided an analytical standard procedure for determining the fractal dimension (FD. The presentation of the oocyte influenced the magnitude of the fractal dimension with the highest FD of 1.91 measured on grey-dark cytoplasm characterized by a highly connected network of lipid droplets and intracellular membranes. Fractal analysis provides an effective quantitative descriptor of the real cytoplasm morphology, which can influence the acquirement of in vitro developmental competence, without introducing any bias or shape approximation and thus contributes to an objective and reliable classification of feline oocytes.
A RIVER FLOW ROUTING MODEL BASED ON DIGITAL DRAINAGE NETWORK
Institute of Scientific and Technical Information of China (English)
YUAN Fei; REN Li-liang; YU Zhong-bo; XU Jing
2005-01-01
On the basis of Digital Elevation Model (DEM) data, watershed delineation and spatial topological relationship were proposed by the Digital Elevation Drainage Network Model (DEDNM) for the area upstream of the Hanzhong Hydrological Station in the Hanjiang River in China. Then, the Muskingum-Cunge method considering lateral flow into the river was applied to flood routing on the platform of digital basin derived from DEDNM. Because of considering lateral flow into the river, the Muskingum-Cunge method performs better than the Muskingum method in terms of the Nash-Sutcliffe model efficiency coefficient and the relative error of flood discharge peak value. With a routing-after-superposition algorithm, the Muskingum-Cunge method performs better than the Muskingum method in terms of the Nash-Sutcliffe model efficiency coefficient and the relative error of flood discharge peak value. As a result, the digital basin coupled with the Muskingum-Cunge method provides a better platform for water resources management and flood control.
Complex Network Simulation of Forest Network Spatial Pattern in Pearl River Delta
Zeng, Y.
2017-09-01
Forest network-construction uses for the method and model with the scale-free features of complex network theory based on random graph theory and dynamic network nodes which show a power-law distribution phenomenon. The model is suitable for ecological disturbance by larger ecological landscape Pearl River Delta consistent recovery. Remote sensing and GIS spatial data are available through the latest forest patches. A standard scale-free network node distribution model calculates the area of forest network's power-law distribution parameter value size; The recent existing forest polygons which are defined as nodes can compute the network nodes decaying index value of the network's degree distribution. The parameters of forest network are picked up then make a spatial transition to GIS real world models. Hence the connection is automatically generated by minimizing the ecological corridor by the least cost rule between the near nodes. Based on scale-free network node distribution requirements, select the number compared with less, a huge point of aggregation as a future forest planning network's main node, and put them with the existing node sequence comparison. By this theory, the forest ecological projects in the past avoid being fragmented, scattered disorderly phenomena. The previous regular forest networks can be reduced the required forest planting costs by this method. For ecological restoration of tropical and subtropical in south China areas, it will provide an effective method for the forest entering city project guidance and demonstration with other ecological networks (water, climate network, etc.) for networking a standard and base datum.
Adaptive Linear Neural Network Based Fractal Generation of Free Surface%基于自适应神经网络的自由曲面分形生成
Institute of Scientific and Technical Information of China (English)
莫灿林; 谭建荣; 张树有
2001-01-01
通过把自适应线性神经元(adaline)网络与自由曲面的生成原理相结合,提出了一种生成分形曲面的新方法.给出了对自由曲面分形的各种分形方法的数学模型,详细介绍了如何通过设置神经网络可调参数的数值来控制和调整分形曲面形状的方法,实现了在控制神经网络可调参数的情况下,改变确定自由曲面各型值点的线性组合关系,生成可预测、可控制和可调整的分形曲面.%In this paper, a new method of generating fractal surface is presented by combining adaptive linear neural networks with the principle of generating free surface. The mathematical model of various fractal methods on free surface and the methods of controlling and adjusting the fractal surface shape according to different parameters of neural networks are put forward. Thus, the predictable, controllable and adjustable fractal surface can be generated with changing linear combination relation of all control points of the definite free surface.
FRACTAL PATTERN GROWTH OF METAL ATOM CLUSTERS IN ION IMPLANTED POLYMERS
Institute of Scientific and Technical Information of China (English)
ZHANG TONG-HE; WU YU-GUANG; SANG HAI-BO; ZHOU GU
2001-01-01
The fractal and multi-fractal patterns of metal atoms are observed in the surface layer and cross section of a metal ion implanted polymer using TEM and SEM for the first time. The surface structure in the metal ion implanted polyethylene terephthalane (PET) is the random fractal. Certain average quantities of the random geometric patterns contain self-similarity. Some growth origins appeared in the fractal pattern which has a dimension of 1.67. The network structure of the fractal patterns is formed in cross section, having a fractal dimension of 1.87. So it can be seen that the fractal pattern is three-dimensional space fractal. We also find the collision cascade fractal in the cross section of implanted nylon, which is similar to the collision cascade pattern in transverse view calculated by the TRIM computer program. Finally, the mechanism for the formation and growth of the fractal patterns during ion implantation is discussed.
自动化视网膜血管网络的分形维数定量分析%Fractal Dimension Quantitative Analysis of Automatic Retinal Vessel Network
Institute of Scientific and Technical Information of China (English)
吴辉群; 袁莉莉; 吴幻; 倪晓薇; 邹如意; 陈亚兰; 施李丽; 蒋葵; 董建成
2015-01-01
目的:研究眼底视网膜血管网络的分形维数自动化测量方法,比较不同分形维数特点.方法:选取20张眼底图片,分别手动分割图像血管和自动分割血管图像计算盒维数、傅里叶分形维数、Hausdorff维数.比较手动分割和自动分割对这三种分形维数的影响.在前面的20张彩色眼底图像中加入高斯噪声和椒盐噪声,比较加入噪声前后对傅里叶分形维数的影响.结果:手工分割和自动分割相比,自动分割血管得出的三种分形维数曲线变化更平稳一点,不像手工分割的分形维数曲线变化忽高忽低,看不出大致的曲线走势和规律.比较来说,自动分割眼底血管图像所得出的分形维数更规律一点.没有加入噪声前对傅里叶分形维数代码进行改造,计算得出的傅里叶分形维数要比原来的数值整体都低且整体趋势更倾向于平稳.结论:自动化视网膜血管网络的分形维数定量研究能够为视网膜病变的分析提供一定帮助.%Objective: To study the automated measuring method of fractal dimension that related to retinal vascular network, compare characteristics of different fractal dimension and the changes of fractal dimension under different pathological conditions. Methods: In our study, a total of 20 fundus image were selected and the retinal blood vessels were segmented manually and automatically. Then, the box dimension, Fourier fractal dimension, Hausdorff dimensions were calculated respectively. The effects of three dimensions after two different segmentation methods were compared. Gaussian, salt and pepper noise was added on the 20 color fundus images and the influence of them on Fourier fractal dimension was tested. Results: Compared to manual segmentation and automatic segmentation, automatic segmentation of vessels curve that drawn three fractal dimension was a little more stable, unlike the manual segmentation curve that can not see the approximate trend and laws
Generic 2-D River Network Modeling of Flow and Sediment Transports
Guo, W.; Wang, C.; Xiang, X.; Ma, T.
2012-04-01
A generic 2D river network model of flow and sediment transports is proposed for the flow and sediment simulation in the complex river network. The paper expands the three-step method adopted in the 1D river network to the 2D river network simulation. A 2D river network model is divided into several cells, including single river cell, "tree-like" river cell, "ring-like" river cell and "cross-like" river cell, which can reflect the interactive influence of flow field in the bifurcated channel and applies to generic 2D simulation. Based on equation of the 2D shallow water and unsteady non-uniform suspended sediment, the relationship between the variables (water level, discharge and sediment concentration) of each section and those of the boundaries are obtained through the full implicit matrix chase-after method. Through the conservation of water and sediment on the boundaries, the water level and sediment concentration on the nodes can be got by solving the irregular sparse matrix of conservation equation, so as to implement the coupled simulation of flow and sediment in the whole river network. The paper take the Chengtong River Reach located in the low reaches of Yangtze River as the example of "cross-like" river to verify the algorithm. The model is calibrated using the measured data. A comparison of calculated water level, discharge and sediment concentration shows that the generic model can reflex the interactive influence of flow field, with reasonable accuracy, especially in the bifurcated channel.
Fractal Weyl law for Linux Kernel Architecture
Ermann, L; Shepelyansky, D L
2010-01-01
We study the properties of spectrum and eigenstates of the Google matrix of a directed network formed by the procedure calls in the Linux Kernel. Our results obtained for various versions of the Linux Kernel show that the spectrum is characterized by the fractal Weyl law established recently for systems of quantum chaotic scattering and the Perron-Frobenius operators of dynamical maps. The fractal Weyl exponent is found to be $\
Hashemi, S. M.; Jagodič, U.; Mozaffari, M. R.; Ejtehadi, M. R.; Muševič, I.; Ravnik, M.
2017-01-01
Fractals are remarkable examples of self-similarity where a structure or dynamic pattern is repeated over multiple spatial or time scales. However, little is known about how fractal stimuli such as fractal surfaces interact with their local environment if it exhibits order. Here we show geometry-induced formation of fractal defect states in Koch nematic colloids, exhibiting fractal self-similarity better than 90% over three orders of magnitude in the length scales, from micrometers to nanometres. We produce polymer Koch-shaped hollow colloidal prisms of three successive fractal iterations by direct laser writing, and characterize their coupling with the nematic by polarization microscopy and numerical modelling. Explicit generation of topological defect pairs is found, with the number of defects following exponential-law dependence and reaching few 100 already at fractal iteration four. This work demonstrates a route for generation of fractal topological defect states in responsive soft matter. PMID:28117325
Neutron scattering from fractals
DEFF Research Database (Denmark)
Kjems, Jørgen; Freltoft, T.; Richter, D.
1986-01-01
The scattering formalism for fractal structures is presented. Volume fractals are exemplified by silica particle clusters formed either from colloidal suspensions or by flame hydrolysis. The determination of the fractional dimensionality through scattering experiments is reviewed, and recent small...
Fractal Aggregation Under Rotation
Institute of Scientific and Technical Information of China (English)
WU Feng-Min; WU Li-Li; LU Hang-Jun; LI Qiao-Wen; YE Gao-Xiang
2004-01-01
By means of the Monte Carlo simulation, a fractal growth model is introduced to describe diffusion-limited aggregation (DLA) under rotation. Patterns which are different from the classical DLA model are observed and the fractal dimension of such clusters is calculated. It is found that the pattern of the clusters and their fractal dimension depend strongly on the rotation velocity of the diffusing particle. Our results indicate the transition from fractal to non-fractal behavior of growing cluster with increasing rotation velocity, i.e. for small enough angular velocity ω the fractal dimension decreases with increasing ω, but then, with increasing rotation velocity, the fractal dimension increases and the cluster becomes compact and tends to non-fractal.
Thamrin, Cindy; Stern, Georgette; Frey, Urs
2010-06-01
There is increasing interest in the study of fractals in medicine. In this review, we provide an overview of fractals, of techniques available to describe fractals in physiological data, and we propose some reasons why a physician might benefit from an understanding of fractals and fractal analysis, with an emphasis on paediatric respiratory medicine where possible. Among these reasons are the ubiquity of fractal organisation in nature and in the body, and how changes in this organisation over the lifespan provide insight into development and senescence. Fractal properties have also been shown to be altered in disease and even to predict the risk of worsening of disease. Finally, implications of a fractal organisation include robustness to errors during development, ability to adapt to surroundings, and the restoration of such organisation as targets for intervention and treatment.
Hashemi, S. M.; Jagodič, U.; Mozaffari, M. R.; Ejtehadi, M. R.; Muševič, I.; Ravnik, M.
2017-01-01
Fractals are remarkable examples of self-similarity where a structure or dynamic pattern is repeated over multiple spatial or time scales. However, little is known about how fractal stimuli such as fractal surfaces interact with their local environment if it exhibits order. Here we show geometry-induced formation of fractal defect states in Koch nematic colloids, exhibiting fractal self-similarity better than 90% over three orders of magnitude in the length scales, from micrometers to nanometres. We produce polymer Koch-shaped hollow colloidal prisms of three successive fractal iterations by direct laser writing, and characterize their coupling with the nematic by polarization microscopy and numerical modelling. Explicit generation of topological defect pairs is found, with the number of defects following exponential-law dependence and reaching few 100 already at fractal iteration four. This work demonstrates a route for generation of fractal topological defect states in responsive soft matter.
Ji-Huan He
2011-01-01
A new fractal derive is defined, which is very easy for engineering applications to discontinuous problems, two simple examples are given to elucidate to establish governing equations with fractal derive and how to solve such equations, respectively.
Quality Assessment in River Network Generalisation by Preserving the Drainage Pattern
Zhang, L.; Guilbert, E.
2013-05-01
The drainage pattern of a river network is the arrangement in which a stream erodes the channels of its network of tributaries. It can reflect the geographical characteristics of a river network to a certain extent, because it depends on the topography and geology of the land. Whether in cartography or GIS, hydrography is one of the most important feature classes to generalise in order to produce representations at various levels of detail. Cartographic generalisation is an intricate process whereby information is selected and represented on a map at a certain scale, not necessarily preserving all geographical or other cartographic details. There are many methods for river network generalisation, but the generalized results are always inspected by expert cartographers visually. This paper proposes a method that evaluates the quality of a river network generalisation by assessing if drainage patterns are preserved. This method provides a quantitative value that estimates the membership of a river network in different drainage patterns. A set of geometric indicators describing each pattern are presented and the membership of a network is defined based on fuzzy logic. For each pattern, the fuzzy set membership is given by a defined IF-THEN rule composed of several indicators and logical operators. Assessing the quality of a generalisation is done by comparing and analysing the value before and after the network generalisation. This assessment method is tested with several river network generalisation methods on different sets of networks and results are analysed and discussed.
Envisioning, quantifying, and managing thermal regimes on river networks
Steel, E. Ashley; Beechie, Timothy J.; Torgersen, Christian; Fullerton, Aimee H.
2017-01-01
Water temperatures fluctuate in time and space, creating diverse thermal regimes on river networks. Temporal variability in these thermal landscapes has important biological and ecological consequences because of nonlinearities in physiological reactions; spatial diversity in thermal landscapes provides aquatic organisms with options to maximize growth and survival. However, human activities and climate change threaten to alter the dynamics of riverine thermal regimes. New data and tools can identify particular facets of the thermal landscape that describe ecological and management concerns and that are linked to human actions. The emerging complexity of thermal landscapes demands innovations in communication, opens the door to exciting research opportunities on the human impacts to and biological consequences of thermal variability, suggests improvements in monitoring programs to better capture empirical patterns, provides a framework for suites of actions to restore and protect the natural processes that drive thermal complexity, and indicates opportunities for better managing thermal landscapes.
Fraboni, Michael; Moller, Trisha
2008-01-01
Fractal geometry offers teachers great flexibility: It can be adapted to the level of the audience or to time constraints. Although easily explained, fractal geometry leads to rich and interesting mathematical complexities. In this article, the authors describe fractal geometry, explain the process of iteration, and provide a sample exercise.…
Che, Yue; Li, Wen; Shang, Zhaoyi; Liu, Chen; Yang, Kai
2014-09-01
River networks have both ecological and social benefits for urban development. However, river networks have suffered extensive destruction as a result of urbanization and industrialization, especially in China. River restoration is a growth business but suffers poor efficiency due to a lack of social understanding. Assessing the benefits of river system restoration and recognizing public preferences are critical for effective river ecosystem restoration and sustainable river management. This study used a choice experiment with a multinomial logit model and a random parameter logit model to assess respondents' cognitive preferences regarding attributes of river networks, and their possible sources of heterogeneity. Results showed that riverfront condition was the attribute most preferred by respondents, while stream morphology was the least preferred. Results also illustrated that the current status of each of three river network attributes was not desirable, and respondents would prefer a river network with a "branch pattern," that is "limpid with no odor," and "accessible with vegetation." Estimated willingness to pay was mainly affected by household monthly income, residential location, and whether respondents had household members engaged in a water protection career. The assessment results can provide guidance and a reference for managers, sponsors, and researchers.
Carling, P. A.; Meshkova, L.; Robinson, R. A.
2011-12-01
The Mekong River in northern Cambodia is an multi-channel mixed bedrock-alluvial river but it was poorly researched until present. Preliminary study of the Mekong geomorphology was conducted by gathering existing knowledge of its geological and tectonic settings, specific riparian vegetation and ancient alluvial terraces in which the river has incised since the Holocene. Altogether this process has allowed a geomorphological portrait of the river to be composed within the Quaternary context. Following this outline, the planform characteristics of the Mekong River network are compared, using analysis of channel network and islands configurations, with the fluvial patterns of the Orange River (South Africa), Upper Columbia River (Canada) and the Ganga River (India, Bangladesh). These rivers are selected as examples of multi-channel mixed bedrock alluvial, anastomosed alluvial and braided alluvial rivers respectively. Network parameters such as channel bifurcation angles asymmetry, sinuosity, braid intensity and island morphometric shape metrics are compared and contrasted between bedrock and alluvial systems. In addition, regional and local topographic trend surfaces produced for each river planform help explain the local changes in river direction and the degree of anastomosis, and distinguish the bedrock-alluvial rivers from the alluvial rivers. Variations between planform characteristics are to be explained by channel forming processes and in the case of mixed bedrock-alluvial rivers mediated by structural control. Channel metrics (derived at the reach-scale) provide some discrimination between different multi-channel patterns but are not always robust when considered singly. In contrast, island shape metrics (obtained at subreach-scale) allow robust discrimination between alluvial and bedrock systems.
Directory of Open Access Journals (Sweden)
FELICIA RAMONA BIRAU
2012-05-01
Full Text Available In this article, the concept of capital market is analysed using Fractal Market Hypothesis which is a modern, complex and unconventional alternative to classical finance methods. Fractal Market Hypothesis is in sharp opposition to Efficient Market Hypothesis and it explores the application of chaos theory and fractal geometry to finance. Fractal Market Hypothesis is based on certain assumption. Thus, it is emphasized that investors did not react immediately to the information they receive and of course, the manner in which they interpret that information may be different. Also, Fractal Market Hypothesis refers to the way that liquidity and investment horizons influence the behaviour of financial investors.
Directory of Open Access Journals (Sweden)
Jan Sendzimir
2008-06-01
Full Text Available Global sources of change offer unprecedented challenges to conventional river management strategies, which no longer appear capable of credibly addressing a trap: the failure of conventional river defense engineering to manage rising trends of disordering extreme events, including frequency and intensity of floods, droughts, and water stagnation in the Hungarian reaches of the Tisza River Basin. Extreme events punctuate trends of stagnation or decline in the ecosystems, economies, and societies of this river basin that extend back decades, and perhaps, centuries. These trends may be the long-term results of defensive strategies of the historical river management regime that reflect a paradigm dating back to the Industrial Revolution: "Protect the Landscape from the River." Since then all policies have defaulted to the imperatives of this paradigm such that it became the convention underlying the current river management regime. As an exponent of this convention the current river management regimes' methods, concepts, infrastructure, and paradigms that reinforce one another in setting the basin's development trajectory, have proven resilient to change from wars, political, and social upheaval for centuries. Failure to address the trap makes the current river management regime's resilience appear detrimental to the region's future development prospects and prompts demand for transformation to a more adaptive river management regime. Starting before transition to democracy, a shadow network has generated multiple dialogues in Hungary, informally exploring the roots of this trap as part of a search for ideas and methods to revitalize the region. We report on how international scientists joined one dialogue, applying system dynamics modeling tools to explore barriers and bridges to transformation of the current river management regime and develop the capacity for participatory science to expand the range of perspectives that inform, monitor, and
Fractal Aggregation Under Rotation
Institute of Scientific and Technical Information of China (English)
WUFeng-Min; WULi-Li; LUHang-Jun; LIQiao-Wen; YEGao-Xiang
2004-01-01
By means of the Monte Carlo simulation, a fractal growth model is introduced to describe diffusion-limited aggregation (DLA) under rotation. Patterns which are different from the classical DLA model are observed and the fractal dimension of such clusters is calculated. It is found that the pattern of the clusters and their fractal dimension depend strongly on the rotation velocity of the diffusing particle. Our results indicate the transition from fractal to non-fractal behavior of growing cluster with increasing rotation velocity, i.e. for small enough angular velocity ω; thefractal dimension decreases with increasing ω;, but then, with increasing rotation velocity, the fractal dimension increases and the cluster becomes compact and tends to non-fractal.
Nonlinear extensions of a fractal-multifractal approach for environmental modeling
Energy Technology Data Exchange (ETDEWEB)
Cortis, A.; Puente, C.E.; Sivakumar, B.
2008-10-15
We present the extension of a deterministic fractal geometric procedure aimed at representing the complexity of the spatio-temporal patterns encountered in environmental applications. The original procedure, which is based on transformations of multifractal distributions via fractal functions, is extended through the introduction of nonlinear perturbations to the underlying iterated linear maps. We demonstrate how the nonlinear perturbations generate yet a richer collection of patterns by means of various simulations that include evolutions of patterns based on changes in their parameters and in their statistical and multifractal properties. It is shown that the nonlinear extensions yield structures that closely resemble complex hydrologic temporal data sets, such as rainfall and runoff time series, and width-functions of river networks as a function of distance from the basin outlet. The implications of this nonlinear approach for environmental modeling and prediction are discussed.
Fractal Analysis on Human Behaviors Dynamics
Fan, Chao; Zha, Yi-Long
2010-01-01
The study of human dynamics has attracted much interest from many fields recently. In this paper, the fractal characteristic of human behaviors is investigated from the perspective of time series constructed with the amount of library loans. The Hurst exponents and length of non-periodic cycles calculated through Rescaled Range Analysis indicate that the time series of human behaviors is fractal with long-range correlation. Then the time series are converted to complex networks by visibility graph algorithm. The topological properties of the networks, such as scale-free property, small-world effect and hierarchical structure imply that close relationships exist between the amounts of repetitious actions performed by people during certain periods of time, especially for some important days. Finally, the networks obtained are verified to be not fractal and self-similar using box-counting method. Our work implies the intrinsic regularity shown in human collective repetitious behaviors.
Microcosms metacommunities in river network: niche effects and biodiversity
Giometto, A.; Carrara, F.; Altermatt, F.; Rinaldo, A.
2012-04-01
Many highly diverse landscapes exhibit hierarchical spatial structures that are shaped by geomorphological processes. Riverine ecosystems, among the most diverse habitats on Earth, represent an outstanding example of such mechanisms. In these landscapes, in which connectivity directly influences metacommunity processes, habitat capacity contributes to control biodiversity at several levels. A previous study has already highlighted the effect of connectivity on species distribution at local and regional scales, but habitat capacity was kept uniform. We studied the interaction of connectivity and habitat capacity in an aquatic microcosm experiment, in which microbial communities were grown in 36-well culture plates connected by dispersal. Dispersal occurred by periodic transfer of culture medium among connected local communities, following river network topology. The effect of habitat capacity in these landscapes was investigated by comparing three different spatial configurations of local community volumes: 1. Power law distributed volumes, according to drainage area. 2. Spatial random permutation of the volumes in the above configuration. 3. Equal distribution of volumes (preserving the total volume with respect to the above configurations). The net effect of habitat capacity on community composition was isolated in a control treatment in which communities were kept isolated for the whole duration of the experiment. In all treatments we observed that varying volumes induced niche effects: some protozoan species preferentially occupied larger nodes (systematically in isolation). Nevertheless, there is evidence that position along the network played a significant role in shaping biodiversity patterns. Size distribution measurements for each community were taken with a CASY cell counter, and species abundances data on log scale precision were collected by direct microscope observation.
The role of the circadian system in fractal neurophysiological control.
Pittman-Polletta, Benjamin R; Scheer, Frank A J L; Butler, Matthew P; Shea, Steven A; Hu, Kun
2013-11-01
Many neurophysiological variables such as heart rate, motor activity, and neural activity are known to exhibit intrinsic fractal fluctuations - similar temporal fluctuation patterns at different time scales. These fractal patterns contain information about health, as many pathological conditions are accompanied by their alteration or absence. In physical systems, such fluctuations are characteristic of critical states on the border between randomness and order, frequently arising from nonlinear feedback interactions between mechanisms operating on multiple scales. Thus, the existence of fractal fluctuations in physiology challenges traditional conceptions of health and disease, suggesting that high levels of integrity and adaptability are marked by complex variability, not constancy, and are properties of a neurophysiological network, not individual components. Despite the subject's theoretical and clinical interest, the neurophysiological mechanisms underlying fractal regulation remain largely unknown. The recent discovery that the circadian pacemaker (suprachiasmatic nucleus) plays a crucial role in generating fractal patterns in motor activity and heart rate sheds an entirely new light on both fractal control networks and the function of this master circadian clock, and builds a bridge between the fields of circadian biology and fractal physiology. In this review, we sketch the emerging picture of the developing interdisciplinary field of fractal neurophysiology by examining the circadian system's role in fractal regulation.
Fractal lattice of gelatin nanoglobules
Novikov, D. V.; Krasovskii, A. N.
2012-11-01
The globular structure of polymer coatings on a glass, which were obtained from micellar solutions of gelatin in the isooctane-water-sodium (bis-2-ethylhexyl) sulfosuccinate system, has been studied using electron microscopy. It has been shown that an increase in the average globule size is accompanied by the formation of a fractal lattice of nanoglobules and a periodic physical network of macromolecules in the coating. The stability of such system of the "liquid-in-a-solid" type is limited by the destruction of globules and the formation of a homogeneous network structure of the coating.
Communities and classes in symmetric fractals
Krawczyk, M J
2014-01-01
Two aspects of fractal networks are considered: the community structure and the class structure, where classes of nodes appear as a consequence of a local symmetry of nodes. The analysed systems are the networks constructed for two selected symmetric fractals: the Sierpinski triangle and the Koch curve. Communities are searched for by means of a set of differential equations. Overlapping nodes which belong to two different communities are identified by adding some noise to the initial connectivity matrix. Then, a node can be characterized by a spectrum of probabilities of belonging to different communities. Our main goal is that the overlapping nodes with the same spectra belong to the same class.
Thoms, M. C.; Delong, M. D.; Flotemersch, J. E.; Collins, S. E.
2017-08-01
The geomorphological character of a river network provides the template upon which evolution acts to create unique biological communities. Deciphering commonly observed patterns and processes within riverine landscapes resulting from the interplay between physical and biological components is a central tenet for the interdisciplinary field of river science. Relationships between the physical heterogeneity and food web character of functional process zones (FPZs) - large tracts of river with a similar geomorphic character -in the Kanawha River (West Virginia, USA) are examined in this study. Food web character was measured as food chain length (FCL), which reflects ecological community structure and ecosystem function. Our results show that the same basal resources were present throughout the Kanawha River but that their assimilation into the aquatic food web by primary consumers differed between FPZs. Differences in the trophic position of higher consumers (fish) were also recorded between FPZs. Overall, the morphological heterogeneity and heterogeneity of the river bed sediment of FPZs were significantly correlated with FCL. Specifically, FCL increases with greater FPZ physical heterogeneity. The result of this study does not support the current paradigm that ecosystem size is the primary determinant of food web character in river ecosystems.
Applications of Fractal Signals
Directory of Open Access Journals (Sweden)
Ion TUTĂNESCU
2008-05-01
Full Text Available "Fractal" term - which in Latin languagedefines something fragmented anomalous - wasintroduced in mathematics by B. B. Mandelbrot in1975. He avoided to define it rigorously and used it todesignate some "rugged" and "self-similar"geometrical forms. Fractals were involved in the theoryof chaotic dynamic systems and used to designatecertain specific sets; finally, they were “captured” bygeometry and remarked in tackling of the boundaryproblems. It proved that the fractals can be of interesteven in the signal’s theory.
河网演化的一个方格模型%A Lattice Model for the Evolution of River Networks
Institute of Scientific and Technical Information of China (English)
郝睿; 冯国林; 霍杰; 王旭明
2012-01-01
Usually, river patterns are greatly related to the natural factors, such as water erosion, landform, etc. Based on water erosion mechanism and original landform, a lattice model for river networks is proposed in order to simulate the growth process and to understand the selection of the nature, namely, fractal structure and scaling behaviors. The lattice is located at an inclined plane with fluctuant surface. The edges of the lattice are the possible water route. The selection of water route is dominated by the order of nature, that is, water flows downwards. A lattice point might be a "lake point", since its altitude is less than that of all the nearest neighbors. A steady river network might be set up as soon as all of the lake points disappear. Meanwhile, the scaling relationships dominating the fractal structure might be established. The statistical results on the landscape of the surface and the network connected by the water routes which actually mimic the river channels follow the Horton's laws. The laws suggest that the ratio of the average stream lengths of rank (O+\\ to those of rank 0) has a fixed value that is independent of to. The same statements also hold for the ratios of average stream numbers and basin areas. The results show that the cumulative probabilities for the both stream lengths and basin areas conform to the power law distributions. These are in accord with those observed in the real river networks. These power laws indicate that there is no any characteristic scale in a river network. The spirit of the model shows that the dynamical origin of the scaling behavior might lie in both determinacy (erosion) and chance (fluctuations on the surface of the earth).%河网演化过程与地貌特征、水流侵蚀等因素密切相关.结合水流侵蚀作用和原始地貌特征,本文提出了一种河网演化模型.模型将代表侵蚀点的规则点阵分布于高度无规起伏的“坡面”之上,由连接点阵的“四方格子”边
Fractal Geometry of Architecture
Lorenz, Wolfgang E.
In Fractals smaller parts and the whole are linked together. Fractals are self-similar, as those parts are, at least approximately, scaled-down copies of the rough whole. In architecture, such a concept has also been known for a long time. Not only architects of the twentieth century called for an overall idea that is mirrored in every single detail, but also Gothic cathedrals and Indian temples offer self-similarity. This study mainly focuses upon the question whether this concept of self-similarity makes architecture with fractal properties more diverse and interesting than Euclidean Modern architecture. The first part gives an introduction and explains Fractal properties in various natural and architectural objects, presenting the underlying structure by computer programmed renderings. In this connection, differences between the fractal, architectural concept and true, mathematical Fractals are worked out to become aware of limits. This is the basis for dealing with the problem whether fractal-like architecture, particularly facades, can be measured so that different designs can be compared with each other under the aspect of fractal properties. Finally the usability of the Box-Counting Method, an easy-to-use measurement method of Fractal Dimension is analyzed with regard to architecture.
Baryshev, Yuri
2002-01-01
This is the first book to present the fascinating new results on the largest fractal structures in the universe. It guides the reader, in a simple way, to the frontiers of astronomy, explaining how fractals appear in cosmic physics, from our solar system to the megafractals in deep space. It also offers a personal view of the history of the idea of self-similarity and of cosmological principles, from Plato's ideal architecture of the heavens to Mandelbrot's fractals in the modern physical cosmos. In addition, this invaluable book presents the great fractal debate in astronomy (after Luciano Pi
Cai, Huayang; Zhang, Zihao; Yang, Qingshu; Ou, Suying
2016-04-01
Large-scale delta systems, such as the Rhine-Meuse delta, the Mississippi River delta, the Mekong delta, the Yangtze delta and the Pearl River delta etc., usually feature a typical channel networks, where individual channels are interrelated through a networks system, resulting in both longitudinal and transverse variations of residual water level slope (averaged over a lunar day) caused by the river-tide interplay. Enhancing our insight of river-tide dynamics in these channel networks has vital importance for the protection and management of estuarine environment since river-tide interplay is closely related to sediment transport, water quality, water utilization and estuarine ecosystem. In this study, we investigate the impact of river-tide dynamics on the temporal-spatial changes of flow and suspended sediment load in terms of residual water level slope and residual sediment transport in the Pearl River channel networks, which is one of the complex channel networks in the world. Making use of a nonstationary harmonic analysis (NS_TIDE), the continuous time series observations of velocity covering a spring-neap cycle in 1999 (representing flood season) and 2001 (representing dry season) collected from around 60 stations in the Pearl River channel networks have been used to extract the temporal-spatial changes in residual velocity and tidal properties (including amplitudes and phases) as a function of variable river flow debouching into the delta. On the basis of harmonic analysis, the tidally averaged friction is decomposed into contributions made by riverine forcing alone, river-tide interaction and tidal asymmetry using Chebyshev polynomials approach. It is shown that river flow enhances friction via river-tide interaction, which increases the residual water level slope that influences the distribution of suspended sediment load in the Pearl River channel networks.
Forecasting the Colorado River Discharge Using an Artificial Neural Network (ANN) Approach
Mehrkesh, Amirhossein
2014-01-01
Artificial Neural Network (ANN) based model is a computational approach commonly used for modeling the complex relationships between input and output parameters. Prediction of the flow rate of a river is a requisite for any successful water resource management and river basin planning. In the current survey, the effectiveness of an Artificial Neural Network was examined to predict the Colorado River discharge. In this modeling process, an ANN model was used to relate the discharge of the Colorado River to such parameters as the amount of precipitation, ambient temperature and snowpack level at a specific time of the year. The model was able to precisely study the impact of climatic parameters on the flow rate of the Colorado River.
Fractal analysis of scatter imaging signatures to distinguish breast pathologies
Eguizabal, Alma; Laughney, Ashley M.; Krishnaswamy, Venkataramanan; Wells, Wendy A.; Paulsen, Keith D.; Pogue, Brian W.; López-Higuera, José M.; Conde, Olga M.
2013-02-01
Fractal analysis combined with a label-free scattering technique is proposed for describing the pathological architecture of tumors. Clinicians and pathologists are conventionally trained to classify abnormal features such as structural irregularities or high indices of mitosis. The potential of fractal analysis lies in the fact of being a morphometric measure of the irregular structures providing a measure of the object's complexity and self-similarity. As cancer is characterized by disorder and irregularity in tissues, this measure could be related to tumor growth. Fractal analysis has been probed in the understanding of the tumor vasculature network. This work addresses the feasibility of applying fractal analysis to the scattering power map (as a physical modeling) and principal components (as a statistical modeling) provided by a localized reflectance spectroscopic system. Disorder, irregularity and cell size variation in tissue samples is translated into the scattering power and principal components magnitude and its fractal dimension is correlated with the pathologist assessment of the samples. The fractal dimension is computed applying the box-counting technique. Results show that fractal analysis of ex-vivo fresh tissue samples exhibits separated ranges of fractal dimension that could help classifier combining the fractal results with other morphological features. This contrast trend would help in the discrimination of tissues in the intraoperative context and may serve as a useful adjunct to surgeons.
Warchalowski, Wiktor; Krawczyk, Malgorzata J.
2017-03-01
We found the Lindenmayer systems for line graphs built on selected fractals. We show that the fractal dimension of such obtained graphs in all analysed cases is the same as for their original graphs. Both for the original graphs and for their line graphs we identified classes of nodes which reflect symmetry of the graph.
Perepelitsa, VA; Sergienko, [No Value; Kochkarov, AM
1999-01-01
Definitions of prefractal and fractal graphs are introduced, and they are used to formulate mathematical models in different fields of knowledge. The topicality of fractal-graph recognition from the point of view, of fundamental improvement in the efficiency of the solution of algorithmic problems i
Spatial behavior analysis at the global level using fractal geometry.
Sambrook, Roger C
2008-01-01
Previous work has suggested that an estimate of fractal dimension can provide a useful metric for quantifying settlement patterns. This study uses fractal methods to investigate settlement patterns at a global scale showing that the scaling behavior of the pattern of the world's largest cities corresponds to that typically observed for coastlines and rivers. This serves to validate the use of fractal dimension as a scale-independent measure of settlement patterns which can be correlated with other physical features. Such a measure may be a useful validation criterion for models of human settlement and spatial behavior.
Geometry of River Networks; 1, Distributions of Component Size and Number
Dodds, P S; Dodds, Peter Sheridan; Rothman, Daniel H.
2000-01-01
The structure of a river network may be seen as a discrete set of nested sub-networks built out of individual stream segments. These network components are assigned an integral stream order via a hierarchical and discrete ordering method. Exponential relationships, known as Horton's laws, between stream order and ensemble-averaged quantities pertaining to network components are observed. We extend these observations to incorporate fluctuations and all higher moments by developing functional relationships between distributions. The relationships determined are drawn from a combination of theoretical analysis, analysis of real river networks including the Mississippi, Amazon and Nile, and numerical simulations on a model of directed, random networks. Underlying distributions of stream segment lengths are identified as exponential. Combinations of these distributions form single-humped distributions with exponential tails, the sums of which are in turn shown to give power law distributions of stream lengths. Dis...
Mathematical model for flood routing in Jingjiang River and Dongting Lake network
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Zuo-tao XIE
2012-09-01
Full Text Available The main stream of the Yangtze River, Dongting Lake, and the river network in the Jingjiang reach of the Yangtze River constitute a complex water system. This paper develops a one-dimensional (1-D mathematical model for flood routing in the river network of the Jingjiang River and Dongting Lake using the explicit finite volume method. Based on observed data during the flood periods in 1996 and 1998, the model was calibrated and validated, and the results show that the model is effective and has high accuracy. In addition, the one-dimensional mathematical model for the river network and the horizontal two-dimensional (2-D mathematical model for the Jingjiang flood diversion area were coupled to simulate the flood process in the Jingjiang River, Dongting Lake, and the Jingjiang flood diversion area. The calculated results of the coupled model are consistent with the practical processes. Meanwhile, the results show that the flood diversion has significant effects on the decrease of the peak water level at the Shashi and Chenjiawan hydrological stations near the flood diversion gates, and the effect is more obvious in the downstream than in the upstream.
Gomez-Velez, Jesus D.; Harvey, Judson W.
2014-09-01
Hyporheic exchange has been hypothesized to have basin-scale consequences; however, predictions throughout river networks are limited by available geomorphic and hydrogeologic data and by models that can analyze and aggregate hyporheic exchange flows across large spatial scales. We developed a parsimonious but physically based model of hyporheic flow for application in large river basins: Networks with EXchange and Subsurface Storage (NEXSS). We applied NEXSS across a broad range of geomorphic diversity in river reaches and synthetic river networks. NEXSS demonstrates that vertical exchange beneath submerged bed forms rather than lateral exchange through meanders dominates hyporheic fluxes and turnover rates along river corridors. Per kilometer, low-order streams have a biogeochemical potential at least 2 orders of magnitude larger than higher-order streams. However, when biogeochemical potential is examined per average length of each stream order, low- and high-order streams were often found to be comparable. As a result, the hyporheic zone's intrinsic potential for biogeochemical transformations is comparable across different stream orders, but the greater river miles and larger total streambed area of lower order streams result in the highest cumulative impact from low-order streams. Lateral exchange through meander banks may be important in some cases but generally only in large rivers.
Fractal images induce fractal pupil dilations and constrictions.
Moon, P; Muday, J; Raynor, S; Schirillo, J; Boydston, C; Fairbanks, M S; Taylor, R P
2014-09-01
Fractals are self-similar structures or patterns that repeat at increasingly fine magnifications. Research has revealed fractal patterns in many natural and physiological processes. This article investigates pupillary size over time to determine if their oscillations demonstrate a fractal pattern. We predict that pupil size over time will fluctuate in a fractal manner and this may be due to either the fractal neuronal structure or fractal properties of the image viewed. We present evidence that low complexity fractal patterns underlie pupillary oscillations as subjects view spatial fractal patterns. We also present evidence implicating the autonomic nervous system's importance in these patterns. Using the variational method of the box-counting procedure we demonstrate that low complexity fractal patterns are found in changes within pupil size over time in millimeters (mm) and our data suggest that these pupillary oscillation patterns do not depend on the fractal properties of the image viewed.
Construction of Fractal Surfaces by Recurrent Fractal Interpolation Curves
Yun, Chol-Hui; O., Hyong-chol; Choi, Hui-chol
2013-01-01
A method to construct fractal surfaces by recurrent fractal curves is provided. First we construct fractal interpolation curves using a recurrent iterated functions system(RIFS) with function scaling factors and estimate their box-counting dimension. Then we present a method of construction of wider class of fractal surfaces by fractal curves and Lipschitz functions and calculate the box-counting dimension of the constructed surfaces. Finally, we combine both methods to have more flexible con...
Quantifying the effects of tidal amplitude on river delta network flow partitioning
Hiatt, M. R.; Sendrowski, A.; Passalacqua, P.
2014-12-01
Deltas are generally classified as river-, tide-, or wave-dominated systems, but the influences of all environmental forces cannot be ignored when fully addressing the dynamics of the system. For example, in river-dominated deltas, river flow from the feeder channel acts as the primary driver of dynamics within the system by delivering water, sediment, and nutrients through the distributary channels, but tides and waves may affect their allocation within the network. There has been work on the asymmetry of environmental fluxes at bifurcations, but relatively few studies exist on the water partitioning at the network scale. Understanding the network and environmental effects on the flux of water, sediment, and nutrients would benefit delta restoration projects and management practices. In this study, we investigate the allocation of water flow among the five major distributary channels at Wax Lake Delta (WLD), a micro-tidal river-dominated delta in coastal Louisiana, and the effects of tidal amplitude on distributary channel discharges. We collect and compare discharge results from acoustic Doppler current profiler (ADCP) velocity transects between spring and neap tide and between falling and rising tide. The results show that discharges increased from spring to neap tide and from rising to falling tide. We investigate the spatial gradients of tidal influence within the network and validate hydraulic geometry relations for tidally influenced channels. Our results give insight into the control of network structure on flow partitioning and show the degree of tidal influence on channel flow in the river-dominated WLD.
The virtual education fractality: nature and organization
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Osbaldo Turpo Gebera
2013-04-01
Full Text Available The potential generated by ICT in education raises reflect on the underlying frameworks. In this sense, the fractal is an opportunity to explain how it organizes and manages virtual education.This approach recognizes that educational dynamics are recursive and iterative processes instituted as progressive sequences, by way of fractals. This understanding enables becoming as mediated and articulated successive levels. In each dimension are embodied own activities and in turn, involves the recurrence of subsequent levels as possible solving of problem situations. Thus, the knowledge built in response to a collaborative action, participation in networks, ranging from autonomous to the cultural level or conversely.
McAteer, R. T. J.
2013-06-01
When Mandelbrot, the father of modern fractal geometry, made this seemingly obvious statement he was trying to show that we should move out of our comfortable Euclidean space and adopt a fractal approach to geometry. The concepts and mathematical tools of fractal geometry provides insight into natural physical systems that Euclidean tools cannot do. The benet from applying fractal geometry to studies of Self-Organized Criticality (SOC) are even greater. SOC and fractal geometry share concepts of dynamic n-body interactions, apparent non-predictability, self-similarity, and an approach to global statistics in space and time that make these two areas into naturally paired research techniques. Further, the iterative generation techniques used in both SOC models and in fractals mean they share common features and common problems. This chapter explores the strong historical connections between fractal geometry and SOC from both a mathematical and conceptual understanding, explores modern day interactions between these two topics, and discusses how this is likely to evolve into an even stronger link in the near future.
Neural network approach to stream-aquifer modeling for improved river basin management
Triana, Enrique; Labadie, John W.; Gates, Timothy K.; Anderson, Charles W.
2010-09-01
SummaryArtificial neural networks (ANNs) are applied to efficient modeling of stream-aquifer responses in an intensively irrigated river basin under a variety of water management alternatives for improving irrigation efficiency, reducing soil water salinity, increasing crop yields, controlling nonbeneficial consumptive use, and decreasing salt loadings to the river. Two ANNs for the main stem river and the tributary regime are trained and tested using solution datasets from a high resolution, finite difference MODFLOW-MT3DMS groundwater flow and contaminant transport model of a representative subregion within the river basin. Stream-aquifer modeling in the subregion is supported by a dense field data collection network with the ultimate goal of extending knowledge gained from the subregion modeling to the sparsely monitored remainder of the river basin where data insufficiency precludes application of MODFLOW-MT3DMS at the desired spatial resolution. The trained and tested ANNs capture the MODFLOW-MT3DMS modeled subregion stream-aquifer responses to system stresses using geographic information system (GIS) processed explanatory variables correlated with irrigation return flow quantity and quality for basin-wide application. The methodology is applied to the Lower Arkansas River basin in Colorado by training and testing ANNs derived from a MODFLOW-MT3DMS modeled subregion of the Lower Arkansas River basin in Colorado, which includes detailed unsaturated and saturated zone modeling and calibration to the extensive field data monitoring network in the subregion. Testing and validation of the trained ANNs shows good performance in predicting return flow quantities and salinity concentrations. The ANNs are linked with the GeoMODSIM river basin network flow model for basin-wide evaluation of water management alternatives.
Natural fragmentation in river networks as a driver of speciation for freshwater fishes
Dias, Murilo S.; Cornu, Jean-François; Oberdorff, Thierry; Lasso, Carlos A.; Tedesco, Pablo A.
2013-01-01
Although habitat fragmentation fosters extinctions, it also increases the probability of speciation by promoting and maintaining divergence among isolated populations. Here we test for the effects of two isolation factors that may reduce population dispersal within river networks as potential drivers of freshwater fish speciation: 1) the position of subdrainages along the longitudinal river gradient, and 2) the level of fragmentation within subdrainages caused by natural waterfalls. The occur...
A neutral model as a null hypothesis test for river network sinuosity
Gaucherel, C.; Salomon, L.
2014-06-01
Neutral models (NMs) are built to test null hypotheses and to detect properties at work in an object or a system. While several studies in geomorphology have used NMs without explicitly mentioning them or describing how they were built, it must be recognized that neutral models more often concerned theoretical explorations that drove such use. In this paper, we propose a panel of NMs of river (channel) networks based on a well-established relationship between observed and simulated sinuosity properties. We first simulated new instances of river networks with a (one-parameter) neutral model based on optimal channel networks (OCN) and leading to homogeneous sinuosity watersheds. We then proposed a "less neutral" model able to generate a variety of river networks accounting for the spatial heterogeneity of observed properties such as elevation. These models, providing confidence levels, allowed us to certify that some properties played a role in the generation of the observed network. Finally, we demonstrated and illustrated both models on the Bidasoa watershed (Spain-France frontier), with a new dedicated software (called SSM). NMs in geomorphology ensure to progressively help to identify the process operating in an observed object, and to ultimately improve our understanding of it (i.e. intrinsic need). But they also provide simulated samples statistically "similar" to an observed one, thus offering new alternatives to every process carried by the observed object (i.e. extrinsic need). Artificial river networks studied here would be of great value to environmental sciences studying geomorphology and freshwater-related processes.
Suspended sediment dynamics in a tidal channel network under peak river flow
Achete, Fernanda Minikowski; van der Wegen, Mick; Roelvink, Dano; Jaffe, Bruce
2016-05-01
Peak river flows transport fine sediment, nutrients, and contaminants that may deposit in the estuary. This study explores the importance of peak river flows on sediment dynamics with special emphasis on channel network configurations. The Sacramento-San Joaquin Delta, which is connected to San Francisco Bay (California, USA), motivates this study and is used as a validation case. Besides data analysis of observations, we applied a calibrated process-based model (D-Flow FM) to explore and analyze high-resolution (˜100 m, ˜1 h) dynamics. Peak river flows supply the vast majority of sediment into the system. Data analysis of six peak flows (between 2012 and 2014) shows that on average, 40 % of the input sediment in the system is trapped and that trapping efficiency depends on timing and magnitude of river flows. The model has 90 % accuracy reproducing these trapping efficiencies. Modeled deposition patterns develop as the result of peak river flows after which, during low river flow conditions, tidal currents are not able to significantly redistribute deposited sediment. Deposition is quite local and mainly takes place at a deep junction. Tidal movement is important for sediment resuspension, but river induced, tide residual currents are responsible for redistributing the sediment towards the river banks and to the bay. We applied the same forcing for four different channel configurations ranging from a full delta network to a schematization of the main river. A higher degree of network schematization leads to higher peak-sediment export downstream to the bay. However, the area of sedimentation is similar for all the configurations because it is mostly driven by geometry and bathymetry.
Artificial Neural Networks (ANNs for flood forecasting at Dongola Station in the River Nile, Sudan
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Sulafa Hag Elsafi
2014-09-01
Full Text Available Heavy seasonal rains cause the River Nile in Sudan to overflow and flood the surroundings areas. The floods destroy houses, crops, roads, and basic infrastructure, resulting in the displacement of people. This study aimed to forecast the River Nile flow at Dongola Station in Sudan using an Artificial Neural Network (ANN as a modeling tool and validated the accuracy of the model against actual flow. The ANN model was formulated to simulate flows at a certain location in the river reach, based on flow at upstream locations. Different procedures were applied to predict flooding by the ANN. Readings from stations along the Blue Nile, White Nile, Main Nile, and River Atbara between 1965 and 2003 were used to predict the likelihood of flooding at Dongola Station. The analysis indicated that the ANN provides a reliable means of detecting the flood hazard in the River Nile.
Investigation of Shannon and PolyWog Wavelet Neural Networks In Monthly River Flow Modeling
Abghari, H.; van de Giesen, N.; Noury, M.
2009-04-01
Intelligence models consist of distributed parallel processors that learn to reproduce the relationship between input and output signals and present the best topology of patterns simulation. Due to nonlinearity of hydrological events the learning process has restrictions . In this study, using a combination of Wavelet theory and a Multi Layer Perceptron Network, two Wavelet Neural Network models for monthly flow of Nazloochaei River basin in Iran were developed. Instead of using common sigmoid activation functions in the MLP network a wavelet function was used, The hybrid wavelet neural network (WNNs) employing a nonlinear wavelet basis was developed as an alternative approach to nonlinear fitting. Result of MLP base model show the 86% in training and 79% in model testing. Results of the MLP base model show a goodness of fit of 86% in training and 79% in model testing. Results shows that the Polywog neural network with the best topology has a 94% accuracy in the training phase and 89% in testing of model. The Shannon neural network with the best topology produces 79% accuracy in training phase and 61% in testing of model. Comparison of WNN and MLP shows that Polywog wavelet could have better accuracy in time series modeling. Classic sigmoid activation functions in the MLP network show better results than the Shannon wavelet. Keywords: Shannon and PolyWog Wavelet, Wavelet Neural Networks, Nazloochaei River Basin, River Flow Modeling.
A time delay artificial neural network approach for flow routing in a river system
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M. J. Diamantopoulou
2006-09-01
Full Text Available River flow routing provides basic information on a wide range of problems related to the design and operation of river systems. In this paper, three layer cascade correlation Time Delay Artificial Neural Network (TDANN models have been developed to forecast the one day ahead daily flow at Ilarionas station on the Aliakmon river, in Northern Greece. The networks are time lagged feed-formatted with delayed memory processing elements at the input layer. The network topology is using multiple inputs, which include the time lagged daily flow values further up at Siatista station on the Aliakmon river and at Grevena station on the Venetikos river, which is a tributary to the Aliakmon river and a single output, which are the daily flow values at Ilarionas station. The choice of the input variables introduced to the input layer was based on the cross-correlation. The use of cross-correlation between the ith input series and the output provides a short cut to the problem of the delayed memory determination. Kalman's learning rule was used to modify the artificial neural network weights. The networks are designed by putting weights between neurons, by using the hyperbolic-tangent function for training. The number of nodes in the hidden layer was determined based on the maximum value of the correlation coefficient. The results show a good performance of the TDANN approach for forecasting the daily flow values, at Ilarionas station and demonstrate its adequacy and potential for river flow routing. The TDANN approach introduced in this study is sufficiently general and has great potential to be applicable to many hydrological and environmental applications.
Dependence on Initial Conditions in a Numerical Model of River Network Formation
Poore, Geoffrey; Kieffer, Susan
2009-03-01
We investigated the effect of initial conditions on river network formation, using a simple model of erosional dynamics. Previous research suggests that river network scaling and geomorphic properties may be sensitive to initial conditions, but this has not been systematically studied. We used simulations of a stream power law, with initial conditions consisting of a flat or sloping surface combined with random fluctuations in elevation, and considered dependence of steady-state solutions on initial slope and randomness. The sinuosity exponent and the sinuosity are sensitive to these initial conditions, while the Hack exponent and hypsometry show little or no sensitivity. The results suggest that initial conditions deserve greater consideration in attempts to understand the emergence of scaling in river networks.
RESEARCH ON HYDRODYNAMIC AND WATER QUALITY MODEL FOR TIDAL RIVER NETWORKS
Institute of Scientific and Technical Information of China (English)
Xu Zu-xin; Lu Shi-qiang
2003-01-01
Hydrodynamic and water quality model for tidal river network is set up with MIKE11 modeling system, according to the features of tidal river networks in plain area. The model was calibrated using the hydrological and water quality data of 1999, and the results show that the simulated values agree with the measured data very well. This model is used to numerically analyze the effects of low flow augmentation on hydrodynamic and water quality conditions of Suzhou Creek. The simulation results show that the flow augmentation can increase net discharge of Suzhou Creek and improve its ability of re-aeration; and its concentration of dissolved oxygen in the river networks can also increase correspondingly.
Objetos fractales y arquitectura
MARTÍNEZ REQUENA, CELIA ANA
2015-01-01
Este trabajo final de grado versa acerca de la fractalidad y su posible aplicación arquitectónica. Se parte del concepto de fractal quedándose con la idea de que “un fractal es un diseño que se repite indefinidamente hacia el infinito cada vez a escala menor” y se presentan los diferentes conjuntos haciendo especial hincapié en los fractales clásicos. La fractalidad se puede apreciar en la naturaleza (p.e: un árbol tiene un tronco, este se divide en ramas, cada una de ellas en ...
Directory of Open Access Journals (Sweden)
M. A. Navascués
2013-01-01
Full Text Available This paper tackles the construction of fractal maps on the unit sphere. The functions defined are a generalization of the classical spherical harmonics. The methodology used involves an iterated function system and a linear and bounded operator of functions on the sphere. For a suitable choice of the coefficients of the system, one obtains classical maps on the sphere. The different values of the system parameters provide Bessel sequences, frames, and Riesz fractal bases for the Lebesgue space of the square integrable functions on the sphere. The Laplace series expansion is generalized to a sum in terms of the new fractal mappings.
Objetos fractales y arquitectura
MARTÍNEZ REQUENA, CELIA ANA
2015-01-01
Este trabajo final de grado versa acerca de la fractalidad y su posible aplicación arquitectónica. Se parte del concepto de fractal quedándose con la idea de que “un fractal es un diseño que se repite indefinidamente hacia el infinito cada vez a escala menor” y se presentan los diferentes conjuntos haciendo especial hincapié en los fractales clásicos. La fractalidad se puede apreciar en la naturaleza (p.e: un árbol tiene un tronco, este se divide en ramas, cada una de ellas en ...
EFFECTS OF RIVER NETWORK WORKS AND SOIL CONSERVATION MEASURES ON RESERVOIR SILTATION
Institute of Scientific and Technical Information of China (English)
Bruno MOLINO; Rosa VIPARELLI; Annamaria DE VINCENZO
2007-01-01
Knowledge of the morphological dynamics of a water course is essential for management of reservoir siltation. With an example of sedimentation in a reservoir in Basilicata, Italy, this paper demonstrates the effect on reservoir siltation of the hydraulic works, which are aimed to reduce sediment transport along the fluvial network and to prevent part of the sediment discharge from reaching the lake. The effect depends on the river type and on the the geological features of river basin slopes. The paper also shows how mass erosion can significantly contribute to development of reservoir siltation. Finally, preliminary results are provided about the time needed for river training works to be effective.
Fractal Analysis Based on Hierarchical Scaling in Complex Systems
Chen, Yanguang
2016-01-01
A fractal is in essence a hierarchy with cascade structure, which can be described with a set of exponential functions. From these exponential functions, a set of power laws indicative of scaling can be derived. Hierarchy structure and spatial network proved to be associated with one another. This paper is devoted to exploring the theory of fractal analysis of complex systems by means of hierarchical scaling. Two research methods are utilized to make this study, including logic analysis method and empirical analysis method. The main results are as follows. First, a fractal system such as Cantor set is described from the hierarchical angle of view; based on hierarchical structure, three approaches are proposed to estimate fractal dimension. Second, the hierarchical scaling can be generalized to describe multifractals, fractal complementary sets, and self-similar curve such as logarithmic spiral. Third, complex systems such as urban system are demonstrated to be a self-similar hierarchy. The human settlements i...
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DOU Shiqing
2016-04-01
Full Text Available At present, the three dimensional Douglas-Peucker (3D_DP algorithm is mainly used on generalization of a single type of DEM. This paper introduces the "bending adjustment index" to improve the 3D_DP algorithm, and puts forward a new method for generalizing river network and DEM in three-dimensional space. In this method, river network line vector data are extracted into 3D discrete point data sets which are added elevation attributes, and then they are merged with the 3D discrete point data sets of DEM. The generalization operations are made by the improved 3D_DP algorithm after the hierarchical selection of river networks. Through the contrast and analysis of the experimental results, the well experiment results have been achieved. Under the role of bending adjustment index, the overall distribution form of the rivers and the main terrain features can be reserved reasonably on the generalization. The river network and DEM data were generalized under the same simplified factor in this method. It improves the quality of the cartography generalization.
Dynamic Channel Network Extraction from Satellite Imagery of the Jamuna River
Addink, E. A.; Marra, W. A.; Kleinhans, M. G.
2010-12-01
Evolution of the largest rivers on Earth is poorly understood while their response to global change is dramatic, such as severe drought and flooding problems. Rivers with high annual dynamics, like the Jamuna, allow us to study their response to changing conditions. Most remote-sensing work so far focused only on pixel-based analysis of channels and change detection or manual digitisation of channels, which is far from urgently needed quantifiers of pattern and pattern change. Using a series of Landsat TM images taken at irregular intervals showing inter- and intra-annual variation, we demonstrate that braided rivers can be represented as nearly chain-like directional networks. These can be studied with novel methods gleaned from neurology. These networks provide an integral spatial description of the network and should not be confused with hierarchical hydrological stream network descriptions developed in the ’60s to describe drainage basins. The images were first classified into water, bare sediment and vegetation. The contiguous water body of the river was then selected and translated into a network description with bifurcations and confluences at the nodes, and interconnecting channels. Along the entire river the well-known braiding indices were derived from the network. The channel width is a crucial attribute of the channel network as this allows the calculation of bifurcation asymmetry. The width was also used with channel length as weights to all the elements in the network in the calculation of more advanced measures for the nature and evolution of the channel network. The key step here is to describe river network evolution by identifying the same node in multiple subsequent images as well as new and abandoned nodes, in order to distinguish migration of bifurcations from avulsion processes. Once identified through time, the changes in node position and the changes in the connected channels can be quantified. These changes can potentially be linked to
Beeson, H. W.; McCoy, S. W.; Willett, S.
2016-12-01
Erosional river networks dissect much of Earth's surface into drainage basins. Global scaling laws such as Hack's Law suggest that river basins trend toward a particular scale-invariant shape. While erosional instabilities arising from competition between advective and diffusive processes can explain why headwaters branch, the erosional mechanics linking larger scale network branching with evolution towards a characteristic river basin shape remain poorly constrained. We map river steepness and a proxy for the steady-state elevation of river networks, χ, in simulated and real landscapes with a large range in spatial scale (102 -106 m) but with similar inclined, planar surfaces at the time of incipient network formation. We document that the evolution from narrow rill-like networks to dendritic, leaf-shaped river basins follows from drainage area differences between catchments. These serve as instabilities that grow, leading to divide migration, stream capture, lateral branching and network reorganization. As Horton hypothesized, incipient networks formed down gradient on an inclined, planar surface have an unequal distribution of drainage area and nonuniformity in response times such that larger basins erode more rapidly and branch laterally via capture of adjacent streams with lower erosion rates. Positive feedback owing to increase in drainage area furthers the process of branching at the expense of neighboring rivers. We show that drainage area exchange and the degree of network reorganization has a significant effect on river steepness in the Dragon's Back Pressure Ridge, CA, the Sierra Nevada, CA, and the Rocky Mountain High Plains, USA. Similarly, metrics of basin shape reveal that basins are evolving from narrow basins towards more common leaf shapes. Our results suggest that divide migration and stream capture driven by erosional disequilibrium could be fundamental processes by which river basins reach their characteristic geometry and dendritic form.
Directory of Open Access Journals (Sweden)
Chuiqing Zeng
2015-10-01
Full Text Available This study proposed a natural-rule-based-connection (NRBC method to connect river segments after water body detection from remotely sensed imagery. A complete river network is important for many hydrological applications. While water body detection methods using remote sensing are well-developed, less attention has been paid to connect discontinuous river segments and form a complete river network. This study designed an automated NRBC method to extract a complete river network by connecting river segments at polygon level. With the assistance of an image pyramid, neighbouring river segments are connected based on four criteria: gap width (Tg, river direction consistency (Tθ, river width consistency (Tw, and minimum river segment length (Tl. The sensitivity of these four criteria were tested, analyzed, and proper criteria values were suggested using image scenes from two diverse river cases. The comparison of NRBC and the alternative morphological method demonstrated NRBC’s advantage of natural rule based selective connection. We refined a river centerline extraction method and show how it outperformed three other existing centerline extraction methods on the test sites. The extracted river polygons and centerlines have a multitude of end uses including rapidly mapping flood extents, monitoring surface water supply, and the provision of validation data for simulation models required for water quantity, quality and aquatic biota assessments. The code for the NRBC is available on GitHub.
Directory of Open Access Journals (Sweden)
Zhang Weiyang
2016-03-01
Full Text Available Previous empirical research on urban networks has used data on infrastructure networks to guesstimate actual inter-city flows. However, with the exception of recent research on airline networks in the context of the world city literature, relatively limited attention has been paid to the degree to which the outline of these infrastructure networks reflects the actual flows they undergird. This study presents a method to improve our estimation of urban interaction in and through infrastructure networks by focusing on the example of passenger railways, which is arguably a key potential data source in research on urban networks in metropolitan regions. We first review common biases when using infrastructure networks to approximate actual inter-city flows, after which we present an alternative approach that draws on research on operational train scheduling. This research has shown that ‘dwell time’ at train stations reflects the length of the alighting and boarding process, and we use this insight to estimate actual interaction through the application of a bimodal network projection function. We apply our method to the high-speed railway (HSR network within the Yangtze River Delta (YRD region, discuss the difference between our modelled network and the original network, and evaluate its validity through a systemic comparison with a benchmark dataset of actual passenger flows.
Simple stochastic lattice gas automaton model for formation of river networks
Yan, Guangwu; Zhang, Jianying; Wang, Huimin; Guo, Li
2008-12-01
A stochastic lattice gas automata model for formation of river networks is proposed. The model is based on two-dimensional lattice gas automata with three fundamental principles at each node. The water source is regarded as a fixed point where a drop of water drips every time step. This system can be treated as a memory network: the probability of water moving along a direction relies on the history of the channel segment along which water drops have moved. Last, we find that the width of the river channel and the number of channels with this width meet a scaling law when the system reaches a critical status.
Neural Network Model for Prediction of Discharged from the Catchments of Langat River, Malaysia
2010-01-01
Artificial neural networks have been shown to be able to approximate any continuous non-linear functions and have been used to build data base empirical models for non-linear processes. In this study, neural networks models were used to model the daily river flows or discharged in Langat River, Malaysia. Two possible ways of modelling were implemented which is by time series prediction and by the dynamics function of the system which include the past value of the discharged and also th...
Relativistic Fractal Cosmologies
Ribeiro, Marcelo B
2009-01-01
This article reviews an approach for constructing a simple relativistic fractal cosmology whose main aim is to model the observed inhomogeneities of the distribution of galaxies by means of the Lemaitre-Tolman solution of Einstein's field equations for spherically symmetric dust in comoving coordinates. This model is based on earlier works developed by L. Pietronero and J.R. Wertz on Newtonian cosmology, whose main points are discussed. Observational relations in this spacetime are presented, together with a strategy for finding numerical solutions which approximate an averaged and smoothed out single fractal structure in the past light cone. Such fractal solutions are shown, with one of them being in agreement with some basic observational constraints, including the decay of the average density with the distance as a power law (the de Vaucouleurs' density power law) and the fractal dimension in the range 1 <= D <= 2. The spatially homogeneous Friedmann model is discussed as a special case of the Lemait...
Velásquez-Villada, Carlos; Donoso, Yezid
2016-03-25
Communications from remote areas that may be of interest is still a problem. Many innovative projects applied to remote sites face communications difficulties. The GOLDFISH project was an EU-funded project for river pollution monitoring in developing countries. It had several sensor clusters, with floating WiFi antennas, deployed along a downstream river's course. Sensor clusters sent messages to a Gateway installed on the riverbank. This gateway sent the messages, through a backhaul technology, to an Internet server where data was aggregated over a map. The communication challenge in this scenario was produced by the antennas' movement and network backhaul availability. Since the antennas were floating on the river, communications could be disrupted at any time. Also, 2G/3G availability near the river was not constant. For non-real-time applications, we propose a Delay/Disruption Tolerant Network (DTN)-based solution where all nodes have persistent storage capabilities and DTN protocols to be able to wait minutes or hours to transmit. A mechanical backhaul will periodically visit the river bank where the gateway is installed and it will automatically collect sensor data to be carried to an Internet-covered spot. The proposed forwarding protocol delivers around 98% of the messages for this scenario, performing better than other well-known DTN routing protocols.
Trabajando fractales con Winlogo
Sabogal, Sonia; Arenas, Gilberto
2007-01-01
Después de una breve introducción en la cual se establecerán algunos conceptos teóricos básicos de la geometría fractal, se realizarán talleres en los cuales, con ayuda de las herramientas que trabaja el software WinLogo, se construirán diversos fractales, analizando sus principales características (autosimilitud, dimensión, etc.)
Mizukami, Naoki; Clark, Martyn P.; Sampson, Kevin; Nijssen, Bart; Mao, Yixin; McMillan, Hilary; Viger, Roland; Markstrom, Steven; Hay, Lauren E.; Woods, Ross; Arnold, Jeffrey R.; Brekke, Levi D.
2016-01-01
This paper describes the first version of a stand-alone runoff routing tool, mizuRoute. The mizuRoute tool post-processes runoff outputs from any distributed hydrologic model or land surface model to produce spatially distributed streamflow at various spatial scales from headwater basins to continental-wide river systems. The tool can utilize both traditional grid-based river network and vector-based river network data. Both types of river network include river segment lines and the associated drainage basin polygons, but the vector-based river network can represent finer-scale river lines than the grid-based network. Streamflow estimates at any desired location in the river network can be easily extracted from the output of mizuRoute. The routing process is simulated as two separate steps. First, hillslope routing is performed with a gamma-distribution-based unit-hydrograph to transport runoff from a hillslope to a catchment outlet. The second step is river channel routing, which is performed with one of two routing scheme options: (1) a kinematic wave tracking (KWT) routing procedure; and (2) an impulse response function – unit-hydrograph (IRF-UH) routing procedure. The mizuRoute tool also includes scripts (python, NetCDF operators) to pre-process spatial river network data. This paper demonstrates mizuRoute's capabilities to produce spatially distributed streamflow simulations based on river networks from the United States Geological Survey (USGS) Geospatial Fabric (GF) data set in which over 54 000 river segments and their contributing areas are mapped across the contiguous United States (CONUS). A brief analysis of model parameter sensitivity is also provided. The mizuRoute tool can assist model-based water resources assessments including studies of the impacts of climate change on streamflow.
Mizukami, Naoki; Clark, Martyn P.; Sampson, Kevin; Nijssen, Bart; Mao, Yixin; McMillan, Hilary; Viger, Roland J.; Markstrom, Steve L.; Hay, Lauren E.; Woods, Ross; Arnold, Jeffrey R.; Brekke, Levi D.
2016-06-01
This paper describes the first version of a stand-alone runoff routing tool, mizuRoute. The mizuRoute tool post-processes runoff outputs from any distributed hydrologic model or land surface model to produce spatially distributed streamflow at various spatial scales from headwater basins to continental-wide river systems. The tool can utilize both traditional grid-based river network and vector-based river network data. Both types of river network include river segment lines and the associated drainage basin polygons, but the vector-based river network can represent finer-scale river lines than the grid-based network. Streamflow estimates at any desired location in the river network can be easily extracted from the output of mizuRoute. The routing process is simulated as two separate steps. First, hillslope routing is performed with a gamma-distribution-based unit-hydrograph to transport runoff from a hillslope to a catchment outlet. The second step is river channel routing, which is performed with one of two routing scheme options: (1) a kinematic wave tracking (KWT) routing procedure; and (2) an impulse response function - unit-hydrograph (IRF-UH) routing procedure. The mizuRoute tool also includes scripts (python, NetCDF operators) to pre-process spatial river network data. This paper demonstrates mizuRoute's capabilities to produce spatially distributed streamflow simulations based on river networks from the United States Geological Survey (USGS) Geospatial Fabric (GF) data set in which over 54 000 river segments and their contributing areas are mapped across the contiguous United States (CONUS). A brief analysis of model parameter sensitivity is also provided. The mizuRoute tool can assist model-based water resources assessments including studies of the impacts of climate change on streamflow.
The ordered network structure and its prediction for the big floods of the Changjiang River Basins
Energy Technology Data Exchange (ETDEWEB)
Men, Ke-Pei; Zhao, Kai; Zhu, Shu-Dan [Nanjing Univ. of Information Science and Technology, Nanjing (China). College of Mathematics and Statistics
2013-12-15
According to the latest statistical data of hydrology, a total of 21 floods took place over the Changjiang (Yangtze) River Basins from 1827 to 2012 and showed an obvious commensurable orderliness. In the guidance of the information forecasting theory of Wen-Bo Weng, based on previous research results, combining ordered analysis with complex network technology, we focus on the summary of the ordered network structure of the Changjiang floods, supplement new information, further optimize networks, construct the 2D- and 3D-ordered network structure and make prediction research. Predictions show that the future big deluges will probably occur over the Changjiang River Basin around 2013-2014, 2020-2021, 2030, 2036, 2051, and 2058. (orig.)
Fractal physiology and the fractional calculus: a perspective
Directory of Open Access Journals (Sweden)
Bruce J West
2010-10-01
Full Text Available This paper presents a restricted overview of Fractal Physiology focusing on the complexity of the human body and the characterization of that complexity through fractal measures and their dynamics, with fractal dynamics being described by the fractional calculus. We review the allometric aggregation approach to the processing of physiologic time series as a way of determining the fractal character of the underlying phenomena. This straight forward method establishes the scaling behavior of complex physiologic networks and some dynamic models capable of generating such scaling are reviewed. These models include simple and fractional random walks, which describe how the scaling of correlation functions and probability densities are related to time series data. Subsequently, it is suggested that a proper methodology for describing the dynamics of fractal time series may well be the fractional calculus, either through the fractional Langevin equation or the fractional diffusion equation. Fractional operators acting on fractal functions yield fractal functions, allowing us to construct a fractional Langevin equation to describe the evolution of a fractal statistical process. Control of physiologic complexity is one of the goals of medicine. Allometric control incorporates long-time memory, inverse power-law (IPL correlations, and long-range interactions in complex phenomena as manifest by IPL distributions. We hypothesize that allometric control, rather than homeostatic control, maintains the fractal character of erratic physiologic time series to enhance the robustness of physiological networks. Moreover, allometric control can be described using the fractional calculus to capture the dynamics of complex physiologic networks. This hypothesis is supported by a number of physiologic time series data.
Baldassarri, Andrea; Prieto-Ballesteros, Olga; Manrubia, Susanna C; 10.1029/2007JE003066
2008-01-01
Geometrical properties of landscapes result from the geological processes that have acted through time. The quantitative analysis of natural relief represents an objective form of aiding in the visual interpretation of landscapes, as studies on coastlines, river networks, and global topography, have shown. Still, an open question is whether a clear relationship between the quantitative properties of landscapes and the dominant geomorphologic processes that originate them can be established. In this contribution, we show that the geometry of topographic isolines is an appropriate observable to help disentangle such a relationship. A fractal analysis of terrestrial isolines yields a clear identification of trenches and abyssal plains, differentiates oceanic ridges from continental slopes and platforms, localizes coastlines and river systems, and isolates areas at high elevation (or latitude) subjected to the erosive action of ice. The study of the geometrical properties of the lunar landscape supports the exist...
Improved higher lead time river flow forecasts using sequential neural network with error updating
Directory of Open Access Journals (Sweden)
Prakash Om
2014-03-01
Full Text Available This paper presents a novel framework to use artificial neural network (ANN for accurate forecasting of river flows at higher lead times. The proposed model, termed as sequential ANN (SANN, is based on the heuristic that a mechanism that provides an accurate representation of physical condition of the basin at the time of forecast, in terms of input information to ANNs at higher lead time, helps improve the forecast accuracy. In SANN, a series of ANNs are connected sequentially to extend the lead time of forecast, each of them taking a forecast value from an immediate preceding network as input. The output of each network is modified by adding an expected value of error so that the residual variance of the forecast series is minimized. The applicability of SANN in hydrological forecasting is illustrated through three case examples: a hypothetical time series, daily river flow forecasting of Kentucky River, USA and hourly river flow forecasting of Kolar River, India. The results demonstrate that SANN is capable of providing accurate forecasts up to 8 steps ahead. A very close fit (>94% efficiency was obtained between computed and observed flows up to 1 hour in advance for all the cases, and the deterioration in fit was not significant as the forecast lead time increased (92% at 8 steps ahead. The results show that SANN performs much better than traditional ANN models in extending the forecast lead time, suggesting that it can be effectively employed in developing flood management measures.
Modelling runoff dynamics from information on river network and shape of catchment area
Skaugen, T.
2009-12-01
In a new approach, the dynamics of discharge is derived from the distribution of distances to the nearest river reach within a natural catchment. The river network and the shape of catchment provide a unique distribution function for each catchment which can be determined from a GIS. The distribution can be considered as a detailed description of the drainage density, where the location of the river relative to the catchment is taken into account. Within a fixed time interval, water flows through the catchment a certain distance which defines a fractional area. This fraction is estimated as an area enveloping the river network, whose width, perpendicular to the river network, is determined for the time interval of interest by the flow velocity. For a constant flow velocity, the time steps define adjacent areas which , for a sufficient number of time intervals, cover the entire catchment. For different flow velocities, we have different horizontal layers and the total discharge is the sum of discharge from each of the layers for each time step. The proposed principle for modelling the dynamics of discharge is implemented in the Swedish HBV model. The new model, named 3D (distance distribution dynamics), has the same precision as the HBV model but requires fewer parameters and represents thus a step in the right direction for meeting the challenge of predictions in ungauged basins.
DEVELOPMENT AND APPLICATION OF A EUTROPHICATION WATER QUALITY MODEL FOR RIVER NETWORKS
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
The Preissmann implicit scheme was used to discretize the one-dimensional Saint-Venant equations, the river-junction-river method was applied to resolve the hydrodynamic and water quality model for river networks, and the key issues on the model were expatiated particularly in this article. This water quality module was designed to compute time dependent concentrations of a series of constituents, which are primarily governed by the processes of advection, dispersion and chemical reactions. Based on the theory of Water Quality Analysis Simulation Program (WASP) water quality model, emphasis was given to the simulation of the biogeochemical transformations that determine the fate of nutrients, in particular, the simulation of the aquatic cycles of nitrogen and phosphorus compounds. This model also includes procedures for the determination of growth and death of phytoplankton. This hydrodynamic and water quality model was applied to calculate two river networks. As illustrated by the numerical examples, the calculated water level and discharge agree with the measured data and the simulated trends and magnitudes of water quality constituents are generally in good agreement with field observations. It is concluded that the presented model is useful in the pollutant control and in the determination of pollutant-related problems for river networks.
River networks dampen long-term hydrological signals of climate change
Chezik, K. A.; Anderson, S. C.; Moore, J. W.
2017-07-01
River networks may dampen local hydrologic signals of climate change through the aggregation of upstream climate portfolio assets. Here we examine this hypothesis using flow and climate trend estimates (1970-2007) at 55 hydrometric gauge stations and across their contributing watersheds' within the Fraser River basin in British Columbia, Canada. Using a null hypothesis framework, we compared our observed attenuation of river flow trends as a function of increasing area and climate trend diversity, with null-simulated estimates to gauge the likelihood and strength of our observations. We found the Fraser River reduced variability in downstream long-term discharge by >91%, with >3.1 times the attenuation than would be expected under null simulation. Although the strength of dampening varied seasonally, our findings indicate that large free-flowing rivers offer a powerful and largely unappreciated process of climate change mitigation. River networks that integrate a diverse climate portfolio can dampen local extremes and offer climate change relief to riverine biota.
An approximative calculation of the fractal structure in self-similar tilings
Hayashi, Yukio
2010-01-01
Fractal structures emerge from statistical and hierarchical processes in urban development or network evolution. In a class of efficient and robust geographical networks, we derive the size distribution of layered areas, and estimate the fractal dimension by using the distribution without huge computations. This method can be applied to self-similar tilings based on a stochastic process.
Species turnover and geographic distance in an urban river network
DEFF Research Database (Denmark)
Rouquette, James R.; Dallimer, Martin; Armsworth, Paul R.;
2013-01-01
of the geographic distance measures, although network distance remained significant for birds and some plant groups after removing the effect of environmental distance. Water-dispersed and neophyte plant groups were significantly related to network and flow distance. Main conclusionsThe results suggest that aquatic...
Fractal Weyl law for quantum fractal eigenstates.
Shepelyansky, D L
2008-01-01
The properties of the resonant Gamow states are studied numerically in the semiclassical limit for the quantum Chirikov standard map with absorption. It is shown that the number of such states is described by the fractal Weyl law, and their Husimi distributions closely follow the strange repeller set formed by classical orbits nonescaping in future times. For large matrices the distribution of escape rates converges to a fixed shape profile characterized by a spectral gap related to the classical escape rate.
典型约束型河网规划%Typical restricted river network planning
Institute of Scientific and Technical Information of China (English)
周天逸
2014-01-01
Taking a typical restricted river network ( RRN ) located in the Yuxi District of Shanghu Town , in Changshu City , as a case study , we conducted planning research on the structural connectivity of the RRN and the water resources allocation in rivers using the river network hydrodynamic model .The results show that coupling spatial structural connectivity with flow quantification can meet the water resources allocation demands in the Yuxi river network of Shanghu Town under restricted conditions and provide a method for optimizing the functions of local river networks.Of multiple types of schemes for water resources allocation , the optimum scheme , which can fully enhance the water mobility in the river network , was based on the combination of controlling multiple watergates along the Wangyu River and the sleeve gates of the Xibei Canal .In this scheme , the water resources supply and demand balance in each sub-region and potential ecological water demands can be met .This method provides suitable project scale and design parameters for river network planning and provides technical support for the protection of RRNs .%以常熟市尚湖镇虞西片区的典型约束型河网为研究对象，采用河网水动力模型对约束型河网的结构连通性和河流水资源调配进行了规划研究。结果表明，控制条件下，采用空间结构连通和河网水流计算相结合的方法能充分满足尚湖镇虞西河网水资源分配需求，优化局部河系功能；通过多方案的河网水资源配置，望虞河多口门引水和锡北运河套闸联合调度方案能充分增强河网流动性，保证各水系功能区内水资源需求平衡和潜在的生态环境需水。该方法还能为水系调整提供合理的河道工程规模和设计参数，为保护约束型河网提供技术支持。
Developing a new global network of river reaches from merged satellite-derived datasets
Lion, C.; Allen, G. H.; Beighley, E.; Pavelsky, T.
2015-12-01
In 2020, the Surface Water and Ocean Topography satellite (SWOT), a joint mission of NASA/CNES/CSA/UK will be launched. One of its major products will be the measurements of continental water extent, including the width, height, and slope of rivers and the surface area and elevations of lakes. The mission will improve the monitoring of continental water and also our understanding of the interactions between different hydrologic reservoirs. For rivers, SWOT measurements of slope must be carried out over predefined river reaches. As such, an a priori dataset for rivers is needed in order to facilitate analysis of the raw SWOT data. The information required to produce this dataset includes measurements of river width, elevation, slope, planform, river network topology, and flow accumulation. To produce this product, we have linked two existing global datasets: the Global River Widths from Landsat (GRWL) database, which contains river centerline locations, widths, and a braiding index derived from Landsat imagery, and a modified version of the HydroSHEDS hydrologically corrected digital elevation product, which contains heights and flow accumulation measurements for streams at 3 arcsecond spatial resolution. Merging these two datasets requires considerable care. The difficulties, among others, lie in the difference of resolution: 30m versus 3 arseconds, and the age of the datasets: 2000 versus ~2010 (some rivers have moved, the braided sections are different). As such, we have developed custom software to merge the two datasets, taking into account the spatial proximity of river channels in the two datasets and ensuring that flow accumulation in the final dataset always increases downstream. Here, we present our preliminary results for a portion of South America and demonstrate the strengths and weaknesses of the method.
Developing a Global Network of River Reaches in Preparation of SWOT
Lion, C.; Pavelsky, T.; Allen, G. H.; Beighley, E.; Schumann, G.; Durand, M. T.
2016-12-01
In 2020, the Surface Water and Ocean Topography satellite (SWOT), a joint mission of NASA/CNES/CSA/UK will be launched. One of its major products will be the measurements of continental water surfaces, including the width, height, and slope of rivers and the surface area and elevations of lakes. The mission will improve the monitoring of continental water and also our understanding of the interactions between different hydrologic reservoirs. For rivers, SWOT measurements of slope will be carried out over predefined river reaches. As such, an a priori dataset for rivers is needed in order to facilitate analysis of the raw SWOT data. The information required to produce this dataset includes measurements of river width, elevation, slope, planform, river network topology, and flow accumulation. To produce this product, we have linked two existing global datasets: the Global River Widths from Landsat (GRWL) database, which contains river centerline locations, widths, and a braiding index derived from Landsat imagery, and a modified version of the HydroSHEDS hydrologically corrected digital elevation product, which contains heights and flow accumulation measurements for streams at 3 arcseconds spatial resolution. Merging these two datasets requires considerable care. The difficulties, among others, lie in the difference of resolution: 30m versus 3 arseconds, and the age of the datasets: 2000 versus 2010 (some rivers have moved, the braided sections are different). As such, we have developed custom software to merge the two datasets, taking into account the spatial proximity of river channels in the two datasets and ensuring that flow accumulation in the final dataset always increases downstream. Here, we present our results for the globe.
Riml, J.; Wörman, A.
2009-12-01
Knowledge about both hydrochemical processes and watershed characteristics are key factors when trying to model transportation and retention of nutrients in a river system. The proposed parameterization method opens for the possibility to introduce independently measured parameters in lumped (compartmental) models. The analysis provides a better understanding of the model structure and aids in the calculation of optimal parameter values. The investigation uses a 1D distributed network model and parameterizes the result in a form appropriate for a compartmental model structure that has been developed for Swedish conditions during decades. The main tool for the analysis is the comparison of temporal moments between the two model structures. The parameterization gives information about the importance of river hydraulics but also about the effect of geomorphological processes such as the river network structure and parameter variability within the watershed. The methodology does also reveal information about predominating processes during distinctive hydrological conditions.
Fractal Characteristics and Prediction of Ti-15-3 Alloy Recrystallized Microstructure
Institute of Scientific and Technical Information of China (English)
Ping LI; Qing ZHANG; Kemin XUE
2008-01-01
Grain shape of the hot deforming alloy is an important index to character the microstructure and performance of material.The fractal theory was applied to analyze the recrystallized microstructure of Ti-15-3 alloy after hot deformation and solution treatment.The fractal dimensions of recrystallized grains were calculated by slit island method.The influence of processing parameters on fractal dimension and grain size was studied.It has been shown that the shapes of recrystallized grain boundaries are self-similar,and the fractal dimension varies from 1 to 2.With increasing deformation degree and strain rate or decreasing deformation temperature,the fractal dimension of grain boundaries increased and the grain size decreased.So the fractal dimension could characterize the grain shape and size.A neural network model was trained to predict the fractal dimension of recrystallized microstructure and the result is in excellent agreement with the experimental data.
[Recent progress of research and applications of fractal and its theories in medicine].
Cai, Congbo; Wang, Ping
2014-10-01
Fractal, a mathematics concept, is used to describe an image of self-similarity and scale invariance. Some organisms have been discovered with the fractal characteristics, such as cerebral cortex surface, retinal vessel structure, cardiovascular network, and trabecular bone, etc. It has been preliminarily confirmed that the three-dimensional structure of cells cultured in vitro could be significantly enhanced by bionic fractal surface. Moreover, fractal theory in clinical research will help early diagnosis and treatment of diseases, reducing the patient's pain and suffering. The development process of diseases in the human body can be expressed by the fractal theories parameter. It is of considerable significance to retrospectively review the preparation and application of fractal surface and its diagnostic value in medicine. This paper gives an application of fractal and its theories in the medical science, based on the research achievements in our laboratory.
River Networks As Ecological Corridors for Species, Populations and Pathogens of Water-Borne Disease
Rinaldo, A.
2014-12-01
River basins are a natural laboratory for the study of the integration of hydrological, ecological and geomorphological processes. Moving from morphological and functional analyses of dendritic geometries observed in Nature over a wide range of scales, this Lecture addresses essential ecological processes that take place along dendritic structures, hydrology-driven and controlled, like e.g.: population migrations and human settlements, that historically proceeded along river networks to follow water supply routes; riparian ecosystems composition that owing to their positioning along streams play crucial roles in their watersheds and in the loss of biodiversity proceeding at unprecedented rates; waterborne disease spreading, like epidemic cholera that exhibits epidemic patterns that mirror those of watercourses and of human mobility and resurgences upon heavy rainfall. Moreover, the regional incidence of Schistosomiasis, a parasitic waterborne disease, and water resources developments prove tightly related, and proliferative kidney disease in fish thrives differently in pristine and engineered watercourses: can we establish quantitatively the critical linkages with hydrologic drivers and controls? How does connectivity within a river network affect community composition or the spreading mechanisms? Does the river basin act as a template for biodiversity or for species' persistence? Are there hydrologic controls on epidemics of water-borne disease? Here, I shall focus on the noteworthy scientific perspectives provided by spatially explicit eco-hydrological studies centered on river networks viewed as ecological corridors for species, populations and pathogens of waterborne disease. A notable methodological coherence is granted by the mathematical description of river networks as the support for reactive transport. The Lecture overviews a number of topics idiosyncratically related to my own research work but ideally aimed at a coherent body of materials and methods. A
The architecture of river networks can drive the evolutionary dynamics of aquatic populations.
Thomaz, Andréa T; Christie, Mark R; Knowles, L Lacey
2016-03-01
It is widely recognized that physical landscapes can shape genetic variation within and between populations. However, it is not well understood how riverscapes, with their complex architectures, affect patterns of neutral genetic diversity. Using a spatially explicit agent-based modeling (ABM) approach, we evaluate the genetic consequences of dendritic river shapes on local population structure. We disentangle the relative contribution of specific river properties to observed patterns of genetic variation by evaluating how different branching architectures and downstream flow regimes affect the genetic structure of populations situated within river networks. Irrespective of the river length, our results illustrate that the extent of river branching, confluence position, and levels of asymmetric downstream migration dictate patterns of genetic variation in riverine populations. Comparisons between simple and highly branched rivers show a 20-fold increase in the overall genetic diversity and a sevenfold increase in the genetic differentiation between local populations. Given that most rivers have complex architectures, these results highlight the importance of incorporating riverscape information into evolutionary models of aquatic species and could help explain why riverine fishes represent a disproportionately large amount of global vertebrate diversity per unit of habitable area.
Three-dimensional tumor perfusion reconstruction using fractal interpolation functions.
Craciunescu, O I; Das, S K; Poulson, J M; Samulski, T V
2001-04-01
It has been shown that the perfusion of blood in tumor tissue can be approximated using the relative perfusion index determined from dynamic contrast-enhanced magnetic resonance imaging (DE-MRI) of the tumor blood pool. Also, it was concluded in a previous report that the blood perfusion in a two-dimensional (2-D) tumor vessel network has a fractal structure and that the evolution of the perfusion front can be characterized using invasion percolation. In this paper, the three-dimensional (3-D) tumor perfusion is reconstructed from the 2-D slices using the method of fractal interpolation functions (FIF), i.e., the piecewise self-affine fractal interpolation model (PSAFIM) and the piecewise hidden variable fractal interpolation model (PHVFIM). The fractal models are compared to classical interpolation techniques (linear, spline, polynomial) by means of determining the 2-D fractal dimension of the reconstructed slices. Using FIFs instead of classical interpolation techniques better conserves the fractal-like structure of the perfusion data. Among the two FIF methods, PHVFIM conserves the 3-D fractality better due to the cross correlation that exists between the data in the 2-D slices and the data along the reconstructed direction. The 3-D structures resulting from PHVFIM have a fractal dimension within 3%-5% of the one reported in literature for 3-D percolation. It is, thus, concluded that the reconstructed 3-D perfusion has a percolation-like scaling. As the perfusion term from bio-heat equation is possibly better described by reconstruction via fractal interpolation, a more suitable computation of the temperature field induced during hyperthermia treatments is expected.
The fractal forest: fractal geometry and applications in forest science.
Nancy D. Lorimer; Robert G. Haight; Rolfe A. Leary
1994-01-01
Fractal geometry is a tool for describing and analyzing irregularity. Because most of what we measure in the forest is discontinuous, jagged, and fragmented, fractal geometry has potential for improving the precision of measurement and description. This study reviews the literature on fractal geometry and its applications to forest measurements.
Ramirez, J. M.
2010-12-01
The spatiotemporal evolution of the population density u of a species in a river network is modeled trough an integro-differential equation. Two processes are considered: population growth, and dispersion of mobile individuals at time scales of weeks to days. Namely, the rate of change in u with respect to time at a point x in the river network and istant t, is given by f(u) - μu + μK(u) where f is the population growth function and K is an integral operator with kernel k(x,y). It is assumed that individuals become mobile at a rate μ that remains constant throughout the river network and time. Moreover, the probability of a mobile individual moving from point x to y in the river network is specified by k(x,y). This motion is assumed to happen at instantaneous times compared to the scales of population growth. The behavior of the population at low density values is considered via the stability of the zero solution to the mathematical model, namely, in the case of a stable zero solution the population will face certain extinction. We consider the particular case where individuals disperse through advection-diffusion within the river network for a random exponential time. In this case the kernel k can be explicitly computed via a system of Sturm-Liuville equations. The eigenvalues of the operator K are then used to give explicit conditions for certain extinction in terms of the physical and biological variables of the model.
Directory of Open Access Journals (Sweden)
Carlos Velásquez-Villada
2016-03-01
Full Text Available Communications from remote areas that may be of interest is still a problem. Many innovative projects applied to remote sites face communications difficulties. The GOLDFISH project was an EU-funded project for river pollution monitoring in developing countries. It had several sensor clusters, with floating WiFi antennas, deployed along a downstream river’s course. Sensor clusters sent messages to a Gateway installed on the riverbank. This gateway sent the messages, through a backhaul technology, to an Internet server where data was aggregated over a map. The communication challenge in this scenario was produced by the antennas’ movement and network backhaul availability. Since the antennas were floating on the river, communications could be disrupted at any time. Also, 2G/3G availability near the river was not constant. For non-real-time applications, we propose a Delay/Disruption Tolerant Network (DTN-based solution where all nodes have persistent storage capabilities and DTN protocols to be able to wait minutes or hours to transmit. A mechanical backhaul will periodically visit the river bank where the gateway is installed and it will automatically collect sensor data to be carried to an Internet-covered spot. The proposed forwarding protocol delivers around 98% of the messages for this scenario, performing better than other well-known DTN routing protocols.
Realization of Fractal Affine Transformation
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
This paper gives the definition of fractal affine transformation and presents a specific method for its realization and its cor responding mathematical equations which are essential in fractal image construction.
Fractal Patterns and Chaos Games
Devaney, Robert L.
2004-01-01
Teachers incorporate the chaos game and the concept of a fractal into various areas of the algebra and geometry curriculum. The chaos game approach to fractals provides teachers with an opportunity to help students comprehend the geometry of affine transformations.
Oleshko, Klaudia; de Jesús Correa López, María; Romero, Alejandro; Ramírez, Victor; Pérez, Olga
2016-04-01
The effectiveness of fractal toolbox to capture the scaling or fractal probability distribution, and simply fractal statistics of main hydrocarbon reservoir attributes, was highlighted by Mandelbrot (1995) and confirmed by several researchers (Zhao et al., 2015). Notwithstanding, after more than twenty years, it's still common the opinion that fractals are not useful for the petroleum engineers and especially for Geoengineering (Corbett, 2012). In spite of this negative background, we have successfully applied the fractal and multifractal techniques to our project entitled "Petroleum Reservoir as a Fractal Reactor" (2013 up to now). The distinguishable feature of Fractal Reservoir is the irregular shapes and rough pore/solid distributions (Siler, 2007), observed across a broad range of scales (from SEM to seismic). At the beginning, we have accomplished the detailed analysis of Nelson and Kibler (2003) Catalog of Porosity and Permeability, created for the core plugs of siliciclastic rocks (around ten thousand data were compared). We enriched this Catalog by more than two thousand data extracted from the last ten years publications on PoroPerm (Corbett, 2012) in carbonates deposits, as well as by our own data from one of the PEMEX, Mexico, oil fields. The strong power law scaling behavior was documented for the major part of these data from the geological deposits of contrasting genesis. Based on these results and taking into account the basic principles and models of the Physics of Fractals, introduced by Per Back and Kan Chen (1989), we have developed new software (Muukíl Kaab), useful to process the multiscale geological and geophysical information and to integrate the static geological and petrophysical reservoir models to dynamic ones. The new type of fractal numerical model with dynamical power law relations among the shapes and sizes of mesh' cells was designed and calibrated in the studied area. The statistically sound power law relations were established
Poore, G. M.; Kieffer, S. W.
2008-12-01
Initial conditions affect river network scaling and geomorphic properties, but the effect has not been systematically studied. Previous numerical and experimental studies have found that initial conditions affect river network drainage patterns, determining whether patterns are more parallel or more dendritic. They have also found that some network properties depend on initial conditions. We investigated the effect of initial conditions in the context of numerical models, using simulations of a stream power law. A common initial condition consists of a flat or sloping surface combined with random fluctuations in elevation. We used these initial conditions and focused on the effect of the magnitude of initial slope and the magnitude of initial randomness on standard network scaling and geomorphic properties, such as the Hack exponent, sinuosity, and hypsometry. Preliminary results indicate that some of the scaling and geomorphic properties show a strong dependence on initial conditions, while others exhibit little or no dependence. The strength of dependence can be sensitive to the statistical methods employed. Our results are relevant to numerical and analog modeling methodologies. The results suggest that initial conditions deserve greater consideration in attempts to understand the emergence of scaling in river networks.
Marks-Tarlow, Terry
Linear concepts of time plus the modern capacity to track history emerged out of circular conceptions characteristic of ancient and traditional cultures. A fractal concept of time lies implicitly within the analog clock, where each moment is treated as unique. With fractal geometry the best descriptor of nature, qualities of self-similarity and scale invariance easily model her endless variety and recursive patterning, both in time and across space. To better manage temporal aspects of our lives, a fractal concept of time is non-reductive, based more on the fullness of being than on fragments of doing. By using a fractal concept of time, each activity or dimension of life is multiply and vertically nested. Each nested cycle remains simultaneously present, operating according to intrinsic dynamics and time scales. By adding the vertical axis of simultaneity to the horizontal axis of length, time is already full and never needs to be filled. To attend to time's vertical dimension is to tap into the imaginary potential for infinite depth. To switch from linear to fractal time allows us to relax into each moment while keeping in mind the whole.
Thermodynamics of Fractal Universe
Sheykhi, Ahmad; Wang, Bin
2012-01-01
We investigate the thermodynamical properties of the apparent horizon in a fractal universe. We find that one can always rewrite the Friedmann equation of the fractal universe in the form of the entropy balance relation $ \\delta Q=TdS+Td\\tilde{S}$, where $ \\delta Q $ and $ T $ are the energy flux and Unruh temperature seen by an accelerated observer just inside the apparent horizon, and $d\\tilde{S}$ is the entropy production term due to nonequilibrium thermodynamics of fractal universe. This shows that in a fractal universe, a treatment with nonequilibrium thermodynamics of spacetime may be needed. We also study the generalized second law of thermodynamics in the framework of fractal universe. When the temperature of the apparent horizon and the matter fields inside the horizon are equal, i.e. $T=T_h$, the generalized second law of thermodynamics can be fulfilled provided the deceleration and the equation of state parameters ranges either as $-1 \\leq q < 0 $, $- 1 \\leq w < - 1/3$ or as $q<-1$, $w<...
Neural Network Model for Prediction of Discharged from the Catchments of Langat River, Malaysia
Directory of Open Access Journals (Sweden)
Z. Ahmad
2010-09-01
Full Text Available Artificial neural networks have been shown to be able to approximate any continuous non-linear functions and have been used to build data base empirical models for non-linear processes. In this study, neural networks models were used to model the daily river flows or discharged in Langat River, Malaysia. Two possible ways of modelling were implemented which is by time series prediction and by the dynamics function of the system which include the past value of the discharged and also the rainfall in the input. The sum square error (SSE, residue analysis and correlation coefficient based on the observed and prediction output is chosen as the criteria of selection of which models is appropriate. It was found that the developed neural networks models using dynamics function provided satisfactory model discharges.
Ghost quintessence in fractal gravity
Indian Academy of Sciences (India)
Habib Abedi; Mustafa Salti
2015-04-01
In this study, using the time-like fractal theory of gravity, we mainly focus on the ghost dark energy model which was recently suggested to explain the present acceleration of the cosmic expansion. Next, we establish a connection between the quintessence scalar field and fractal ghost dark energy density. This correspondence allows us to reconstruct the potential and the dynamics of a fractal canonical scalar field (the fractal quintessence) according to the evolution of ghost dark energy density.
Modeling Reservoir-River Networks in Support of Optimizing Seasonal-Scale Reservoir Operations
Villa, D. L.; Lowry, T. S.; Bier, A.; Barco, J.; Sun, A.
2011-12-01
HydroSCOPE (Hydropower Seasonal Concurrent Optimization of Power and the Environment) is a seasonal time-scale tool for scenario analysis and optimization of reservoir-river networks. Developed in MATLAB, HydroSCOPE is an object-oriented model that simulates basin-scale dynamics with an objective of optimizing reservoir operations to maximize revenue from power generation, reliability in the water supply, environmental performance, and flood control. HydroSCOPE is part of a larger toolset that is being developed through a Department of Energy multi-laboratory project. This project's goal is to provide conventional hydropower decision makers with better information to execute their day-ahead and seasonal operations and planning activities by integrating water balance and operational dynamics across a wide range of spatial and temporal scales. This presentation details the modeling approach and functionality of HydroSCOPE. HydroSCOPE consists of a river-reservoir network model and an optimization routine. The river-reservoir network model simulates the heat and water balance of river-reservoir networks for time-scales up to one year. The optimization routine software, DAKOTA (Design Analysis Kit for Optimization and Terascale Applications - dakota.sandia.gov), is seamlessly linked to the network model and is used to optimize daily volumetric releases from the reservoirs to best meet a set of user-defined constraints, such as maximizing revenue while minimizing environmental violations. The network model uses 1-D approximations for both the reservoirs and river reaches and is able to account for surface and sediment heat exchange as well as ice dynamics for both models. The reservoir model also accounts for inflow, density, and withdrawal zone mixing, and diffusive heat exchange. Routing for the river reaches is accomplished using a modified Muskingum-Cunge approach that automatically calculates the internal timestep and sub-reach lengths to match the conditions of
USING ARTIFICIAL NEURAL NETWORKS (ANNs FOR SEDIMENT LOAD FORECASTING OF TALKHEROOD RIVER MOUTH
Directory of Open Access Journals (Sweden)
Vahid Nourani
2009-06-01
Full Text Available Without a doubt the carried sediment load by a river is the most important factor in creating and formation of the related Delta in the river mouth. Therefore, accurate forecasting of the river sediment load can play a significant role for study on the river Delta. However considering the complexity and non-linearity of the phenomenon, the classic experimental or physical-based approaches usually could not handle the problem so well. In this paper, Artificial Neural Network (ANN as a non-linear black box interpolator tool is used for modeling suspended sediment load which discharges to the Talkherood river mouth, located in northern west Iran. For this purpose, observed time series of water discharge at current and previous time steps are used as the model input neurons and the model output neuron will be the forecasted sediment load at the current time step. In this way, various schemes of the ANN approach are examined in order to achieve the best network as well as the best architecture of the model. The obtained results are also compared with the results of two other classic methods (i.e., linear regression and rating curve methods in order to approve the efficiency and ability of the proposed method.
USING ARTIFICIAL NEURAL NETWORKS (ANNs FOR SEDIMENT LOAD FORECASTING OF TALKHEROOD RIVER MOUTH
Directory of Open Access Journals (Sweden)
Vahid Nourani
2009-01-01
Full Text Available Without a doubt the carried sediment load by a river is the most important factor in creating and formation of the related Delta in the river mouth. Therefore, accurate forecasting of the river sediment load can play a significant role for study on the river Delta. However considering the complexity and non-linearity of the phenomenon, the classic experimental or physical-based approaches usually could not handle the problem so well. In this paper, Artificial Neural Network (ANN as a non-linear black box interpolator tool is used for modeling suspended sediment load which discharges to the Talkherood river mouth, located in northern west Iran. For this purpose, observed time series of water discharge at current and previous time steps are used as the model input neurons and the model output neuron will be the forecasted sediment load at the current time step. In this way, various schemes of the ANN approach are examined in order to achieve the best network as well as the best architecture of the model. The obtained results are also compared with the results of two other classic methods (i.e., linear regression and rating curve methods in order to approve the efficiency and ability of the proposed method.
Fractal geometry and stochastics IV
Bandt, Christoph
2010-01-01
Over the years fractal geometry has established itself as a substantial mathematical theory in its own right. This book collects survey articles covering many of the developments, like Schramm-Loewner evolution, fractal scaling limits, exceptional sets for percolation, and heat kernels on fractals.
Confluence effects in rivers: Interactions of basin scale, network geometry, and disturbance regimes
Benda, Lee; Andras, Kevin; Miller, Daniel; Bigelow, Paul
2004-05-01
We reviewed 14 studies documenting the effects of tributaries on river morphology at 167 confluences along 730 km of river spanning seven orders of magnitude in drainage area in western United States and Canada. In both humid and semiarid environments the probability of observing significant confluence-related changes in channel and valley morphology due to tributary influxes of sediment (e.g., changes in gradient, particle size, and terraces, etc.) increased with the size of the tributary relative to the main stem. Effects of confluences on river morphology are conditioned by basin shape and channel network patterns, and they include the nonlinear separation of geomorphically significant confluences in river networks. Other modifying factors include local network geometry and drainage density. Confluence-related landforms (i.e., fans, bars, terraces, etc.) are predicted to be dominated by older features in headwaters and younger features downstream, a pattern driven by the frequency and magnitude of floods and punctuated sediment supply that scale with watershed size.
Indian Academy of Sciences (India)
J C Fu; M H Hsu; Y Duann
2016-02-01
Flood is the worst weather-related hazard in Taiwan because of steep terrain and storm. The tropical storm often results in disastrous flash flood. To provide reliable forecast of water stages in rivers is indispensable for proper actions in the emergency response during flood. The river hydraulic model based on dynamic wave theory using an implicit finite-difference method is developed with river roughness updating for flash flood forecast. The artificial neural network (ANN) is employed to update the roughness of rivers in accordance with the observed river stages at each time-step of the flood routing process. Several typhoon events at Tamsui River are utilized to evaluate the accuracy of flood forecasting. The results present the adaptive n-values of roughness for river hydraulic model that can provide a better flow state for subsequent forecasting at significant locations and longitudinal profiles along rivers.
Paiva, Rodrigo C. D.; Durand, Michael T.; Hossain, Faisal
2015-01-01
Recent efforts have sought to estimate river discharge and other surface water-related quantities using spaceborne sensors, with better spatial coverage but worse temporal sampling as compared with in situ measurements. The Surface Water and Ocean Topography (SWOT) mission will provide river discharge estimates globally from space. However, questions on how to optimally use the spatially distributed but asynchronous satellite observations to generate continuous fields still exist. This paper presents a statistical model (River Kriging-RK), for estimating discharge time series in a river network in the context of the SWOT mission. RK uses discharge estimates at different locations and times to produce a continuous field using spatiotemporal kriging. A key component of RK is the space-time river discharge covariance, which was derived analytically from the diffusive wave approximation of Saint Venant's equations. The RK covariance also accounts for the loss of correlation at confluences. The model performed well in a case study on Ganges-Brahmaputra-Meghna (GBM) River system in Bangladesh using synthetic SWOT observations. The correlation model reproduced empirically derived values. RK (R2=0.83) outperformed other kriging-based methods (R2=0.80), as well as a simple time series linear interpolation (R2=0.72). RK was used to combine discharge from SWOT and in situ observations, improving estimates when the latter is included (R2=0.91). The proposed statistical concepts may eventually provide a feasible framework to estimate continuous discharge time series across a river network based on SWOT data, other altimetry missions, and/or in situ data.
Energy Technology Data Exchange (ETDEWEB)
Benenti, Giuliano; Casati, Giulio; Guarneri, Italo; Terraneo, Marcello
2001-07-02
We numerically analyze quantum survival probability fluctuations in an open, classically chaotic system. In a quasiclassical regime and in the presence of classical mixed phase space, such fluctuations are believed to exhibit a fractal pattern, on the grounds of semiclassical arguments. In contrast, we work in a classical regime of complete chaoticity and in a deep quantum regime of strong localization. We provide evidence that fluctuations are still fractal, due to the slow, purely quantum algebraic decay in time produced by dynamical localization. Such findings considerably enlarge the scope of the existing theory.
Deppman, Airton
2016-01-01
The non extensive aspects of $p_T$ distributions obtained in high energy collisions are discussed in relation to possible fractal structure in hadrons, in the sense of the thermofractal structure recently introduced. The evidences of self-similarity in both theoretical and experimental works in High Energy and in Hadron Physics are discussed, to show that the idea of fractal structure of hadrons and fireballs have being under discussion for decades. The non extensive self-consistent thermodynamics and the thermofractal structure allow one to connect non extensivity to intermittence and possibly to parton distribution functions in a single theoretical framework.
Institute of Scientific and Technical Information of China (English)
ZhinhongLi; DongWu; Yuhansun; JunWang; YiLiu; BaozhongDong; Zhinhong
2001-01-01
Silica aggregates were prepared by base-catalyzed hydrolysis and condensation of alkoxides in alcohol.Polyethylene glycol(PEG) was used as organic modifier.The sols were characterized using Small Angle X-ray Scattering (SAXS) with synchrotron radiation as X-ray source.The structure evolution during the sol-gel process was determined and described in terms of the fractal geometry.As-produced silica aggregates were found to be mass fractals.The fractl dimensions spanned the regime 2.1-2.6 corresponding to more branched and compact structures.Both RLCA and Eden models dominated the kinetic growth under base-catalyzed condition.
Predicting groundwater flow system discharge in the river network at the watershed scale
Caruso, Alice; Ridolfi, Luca; Boano, Fulvio
2016-04-01
The interaction between rivers and aquifers affects the quality and the quantity of surface and subsurface water since it plays a crucial role for solute transport, nutrient cycling and microbial transformations. The groundwater-surface water interface, better known as hyporheic zone, has a functional significance for the biogeochemical and ecological conditions of the fluvial ecosystem since it controls the flux of groundwater solutes discharging into rivers, and vice versa. The hyporheic processes are affected by the complex surrounding aquifer because the groundwater flow system obstructs the penetration of stream water into the sediments. The impact of large-scale stream-aquifer interactions on small scale exchange has generally been analyzed at local scales of a river reach, or even smaller. However, a complete comprehension of how hyporheic fluxes are affected by the groundwater system at watershed scale is still missing. Evaluating this influence is fundamental to predict the consequences of hyporheic exchange on water quality and stream ecology. In order to better understand the actual structure of hyporheic exchange along the river network, we firstly examine the role of basin topography complexity in controlling river-aquifer interactions. To reach this target, we focus on the analysis of surface-subsurface water exchange at the watershed scale, taking into account the river-aquifer interactions induced by landscape topography. By way of a mathematical model, we aim to improve the estimation of the role of large scale hydraulic gradients on hyporheic exchange. The potential of the method is demonstrated by the analysis of a benchmark case's study, which shows how the topographic conformation influences the stream-aquifer interaction and induces a substantial spatial variability of the groundwater discharge even among adjacent reaches along the stream. The vertical exchange velocity along the river evidences a lack of autocorrelation. Both the groundwater
Fractal elements and their applications
Gil’mutdinov, Anis Kharisovich; El-Khazali, Reyad
2017-01-01
This book describes a new type of passive electronic components, called fractal elements, from a theoretical and practical point of view. The authors discuss in detail the physical implementation and design of fractal devices for application in fractional-order signal processing and systems. The concepts of fractals and fractal signals are explained, as well as the fundamentals of fractional calculus. Several implementations of fractional impedances are discussed, along with comparison of their performance characteristics. Details of design, schematics, fundamental techniques and implementation of RC-based fractal elements are provided. .
Retinal Vascular Fractals and Cognitive Impairment
Directory of Open Access Journals (Sweden)
Yi-Ting Ong
2014-08-01
Full Text Available Background: Retinal microvascular network changes have been found in patients with age-related brain diseases such as stroke and dementia including Alzheimer's disease. We examine whether retinal microvascular network changes are also present in preclinical stages of dementia. Methods: This is a cross-sectional study of 300 Chinese participants (age: ≥60 years from the ongoing Epidemiology of Dementia in Singapore study who underwent detailed clinical examinations including retinal photography, brain imaging and neuropsychological testing. Retinal vascular parameters were assessed from optic disc-centered photographs using a semiautomated program. A comprehensive neuropsychological battery was administered, and cognitive function was summarized as composite and domain-specific Z-scores. Cognitive impairment no dementia (CIND and dementia were diagnosed according to standard diagnostic criteria. Results: Among 268 eligible nondemented participants, 78 subjects were categorized as CIND-mild and 69 as CIND-moderate. In multivariable adjusted models, reduced retinal arteriolar and venular fractal dimensions were associated with an increased risk of CIND-mild and CIND-moderate. Reduced fractal dimensions were associated with poorer cognitive performance globally and in the specific domains of verbal memory, visuoconstruction and visuomotor speed. Conclusion: A sparser retinal microvascular network, represented by reduced arteriolar and venular fractal dimensions, was associated with cognitive impairment, suggesting that early microvascular damage may be present in preclinical stages of dementia.
A neural network model for short term river flow prediction
2006-01-01
International audience; This paper presents a model using rain gauge and weather radar data to predict the runoff of a small alpine catchment in Austria. The gapless spatial coverage of the radar is important to detect small convective shower cells, but managing such a huge amount of data is a demanding task for an artificial neural network. The method described here uses statistical analysis to reduce the amount of data and find an appropriate input vector. Based on this analysis, radar meas...
Explaining the internal behaviour of artificial neural network river flow models
Sudheer, K. P.; Jain, Ashu
2004-03-01
A novel method of visualizing and understanding the internal functional behaviour of an artificial neural network (ANN) river flow model is presented. The method hypothesizes that an ANN is able to map a function similar to the flow duration curve while modelling the river flow. A mathematical analysis of the hypothesis is presented, and a case study of an ANN river flow model confirms its significance. The proposed approach is also useful within other models that improve the performance of an ANN. The reasons why these models improve a raw ANN can be clearly understood using this approach. While the field of ANN knowledge-extraction is one that continues to attract considerable interest, it is anticipated that the current approach will initiate further research and make ANNs more useful to the hydrologic community.
Hamshaw, S. D.; Underwood, K.; Rizzo, D.; Wemple, B. C.; Dewoolkar, M.
2013-12-01
Over 1,000 river miles in Vermont are either impaired or stressed by excessive sedimentation. The higher streamflows and incised river channels have resulted in increased bed and bank erosion. As the climate in Vermont is expected to feature greater and more frequent precipitation events and winter rainfall, the potential for increased sediment loading from erosion processes in the watershed and along the channel are high and a major concern for water resource managers. Typical sediment monitoring comprises periodic sampling during storm events and is often limited to gauged streams with flow data. Continuous turbidity monitoring enhances our understanding of river dynamics by offering high-resolution, temporal measurements to better quantify the total sediment loading occurring during and between storm events. Artificial neural networks, that mimic learning patterns of the human brain, have been effective at predicting flow in small, ungauged rivers using local climate data. This study advances this technology by using an ANN algorithm known as a counter-propagation neural network (CPNN) to predict discharge and suspended sediment in small streams. The first distributed network of continuous turbidity sensors (DTS-12) was deployed in Vermont in the Mad River Watershed, located in Central Vermont. The Mad River and five tributaries were selected as a test bed because seven years of periodic turbidity sampling data are available, it represents a range of watershed characteristics, and because the watershed is also being used for hydrologic model development using the Distributed-Hydrology-Soils-Vegetation Model (DHSVM). Comparison with the DHSVM simulations will allow estimation of the most-likely sources of sediment from the entire watershed and individual subwatersheds. In addition, recent field studies have commenced the quantification of erosion occurring from unpaved roads and streambanks in the same watershed. Periodic water quality sampling during storm
Fractal Representation of Exergy
Directory of Open Access Journals (Sweden)
Yvain Canivet
2016-02-01
Full Text Available We developed a geometrical model to represent the thermodynamic concepts of exergy and anergy. The model leads to multi-scale energy lines (correlons that we characterised by fractal dimension and entropy analyses. A specific attention will be paid to overlapping points, rising interesting remarks about trans-scale dynamics of heat flows.
Earnshow, R; Jones, H
1991-01-01
This volume is based upon the presentations made at an international conference in London on the subject of 'Fractals and Chaos'. The objective of the conference was to bring together some of the leading practitioners and exponents in the overlapping fields of fractal geometry and chaos theory, with a view to exploring some of the relationships between the two domains. Based on this initial conference and subsequent exchanges between the editors and the authors, revised and updated papers were produced. These papers are contained in the present volume. We thank all those who contributed to this effort by way of planning and organisation, and also all those who helped in the production of this volume. In particular, we wish to express our appreciation to Gerhard Rossbach, Computer Science Editor, Craig Van Dyck, Production Director, and Nancy A. Rogers, who did the typesetting. A. J. Crilly R. A. Earnshaw H. Jones 1 March 1990 Introduction Fractals and Chaos The word 'fractal' was coined by Benoit Mandelbrot i...
Hiatt, M. R.; Castaneda, E.; Twilley, R.; Hodges, B. R.; Passalacqua, P.
2015-12-01
River deltas have the potential to mitigate increased nutrient loading to coastal waters by acting as biofilters that reduce the impact of nutrient enrichment on downstream ecosystems. Hydraulic residence time (HRT) is known to be a major control on biogeochemical processes and deltaic floodplains are hypothesized to have relatively long HRTs. Hydrological connectivity and delta floodplain inundation induced by riverine forces, tides, and winds likely alter surface water flow patterns and HRTs. Since deltaic floodplains are important elements of delta networks and receive significant fluxes of water, sediment, and nutrients from distributary channels, biogeochemical transformations occurring within these zones could significantly reduce nutrient loading to coastal receiving waters. However, network-scale estimates of HRT in river deltas are lacking and little is known about the effects of tides, wind, and the riverine input on the HRT distribution. Subsequently, there lacks a benchmark for evaluating the impact of engineered river diversions on coastal nutrient ecology. In this study, we estimate the HRT of a coastal river delta by using hydrodynamic modeling supported by field data and relate the HRT to spatial and temporal patterns in nitrate levels measured at discrete stations inside a delta island at Wax Lake Delta. We highlight the control of the degree of hydrological connectivity between distributary channels and interdistributary islands on the network HRT distribution and address the roles of tides and wind on altering the shape of the distribution. We compare the observed nitrate concentrations to patterns of channel-floodplain hydrological connectivity and find this connectivity to play a significant role in the nutrient removal. Our results provide insight into the potential role of deltaic wetlands in reducing the nutrient loading to near-shore waters in response to large-scale river diversions.
Van Looy, Kris; Piffady, Jérémy
2017-11-01
Floodplain landscapes are highly fragmented by river regulation resulting in habitat degradation and flood regime perturbation, posing risks to population persistence. Climate change is expected to pose supplementary risks in this context of fragmented landscapes, and especially for river systems adaptation management programs are developed. The association of habitat quality and quantity with the landscape dynamics and resilience to human-induced disturbances is still poorly understood in the context of species survival and colonization processes, but essential to prioritize conservation and restoration actions. We present a modelling approach that elucidates network connectivity and landscape dynamics in spatial and temporal context to identify vital corridors and conservation priorities in the Loire river and its tributaries. Alteration of flooding and flow regimes is believed to be critical to population dynamics in river ecosystems. Still, little is known of critical levels of alteration both spatially and temporally. We applied metapopulation modelling approaches for a dispersal-limited tree species, white elm; and a recruitment-limited tree species, black poplar. In different model steps the connectivity and natural dynamics of the river landscape are confronted with physical alterations (dams/dykes) to species survival and then future scenarios for climatic changes and potential adaptation measures are entered in the model and translated in population persistence over the river basin. For the two tree species we highlighted crucial network zones in relation to habitat quality and connectivity. Where the human impact model already shows currently restricted metapopulation development, climate change is projected to aggravate this persistence perspective substantially. For both species a significant drawback to the basin population is observed, with 1/3 for elm and ¼ for poplar after 25 years already. But proposed adaptation measures prove effective to even
Aquatic Plant Dynamics in Lowland River Networks: Connectivity, Management and Climate Change
Directory of Open Access Journals (Sweden)
Benoît O.L. Demars
2014-04-01
Full Text Available The spatial structure and evolution of river networks offer tremendous opportunities to study the processes underlying metacommunity patterns in the wild. Here we explore several fundamental aspects of aquatic plant biogeography. How stable is plant composition over time? How similar is it along rivers? How fast is the species turnover? How does that and spatial structure affect our species richness estimates across scales? How do climate change, river management practices and connectivity affect species composition and community structure? We answer these questions by testing twelve hypotheses and combining two spatial surveys across entire networks, a long term temporal survey (21 consecutive years, a trait database, and a selection of environmental variables. From our river reach scale survey in lowland rivers, hydrophytes and marginal plants (helophytes showed contrasting patterns in species abundance, richness and autocorrelation both in time and space. Since patterns in marginal plants reflect at least partly a sampling artefact (edge effect, the rest of the study focused on hydrophytes. Seasonal variability over two years and positive temporal autocorrelation at short time lags confirmed the relatively high regeneration abilities of aquatic plants in lowland rivers. Yet, from 1978 to 1998, plant composition changed quite dramatically and diversity decreased substantially. The annual species turnover was relatively high (20%–40% and cumulated species richness was on average 23% and 34% higher over three and five years respectively, than annual survey. The long term changes were correlated to changes in climate (decreasing winter ice scouring, increasing summer low flows and management (riparian shading. Over 21 years, there was a general erosion of species attributes over time attributed to a decrease in winter ice scouring, increase in shading and summer low flows, as well as a remaining effect of time which may be due to an erosion of
A neural network model for short term river flow prediction
Teschl, R.; Randeu, W. L.
2006-07-01
This paper presents a model using rain gauge and weather radar data to predict the runoff of a small alpine catchment in Austria. The gapless spatial coverage of the radar is important to detect small convective shower cells, but managing such a huge amount of data is a demanding task for an artificial neural network. The method described here uses statistical analysis to reduce the amount of data and find an appropriate input vector. Based on this analysis, radar measurements (pixels) representing areas requiring approximately the same time to dewater are grouped.
A neural network model for short term river flow prediction
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R. Teschl
2006-01-01
Full Text Available This paper presents a model using rain gauge and weather radar data to predict the runoff of a small alpine catchment in Austria. The gapless spatial coverage of the radar is important to detect small convective shower cells, but managing such a huge amount of data is a demanding task for an artificial neural network. The method described here uses statistical analysis to reduce the amount of data and find an appropriate input vector. Based on this analysis, radar measurements (pixels representing areas requiring approximately the same time to dewater are grouped.
Sediment Transport Dynamics in River Networks: A Model for Higher-Water Seasons
Huo, Jie; Wang, Xu-Ming; Hao, Rui; Zhang, Jin-Feng
A dynamical model is proposed to study sediment transport in river networks in higher-water seasons. The model emphasizes the difference between the sediment-carrying capability of the stream in higher-water seasons and that in lower-water seasons. The dynamics of sediment transport shows some complexities such as the complex dependence of the sediment-carrying capability on sediment concentration, the response of the channel(via erosion or sedimentation) to the changes of discharge.
A Wavelet Neural Network Hybrid Model for Monthly Ammonia Forecasting in River Water
2013-01-01
Forecasting water quality is always an effective approach for water environmental management. This study presents a combined Wavelet transform (WA) and Artificial Neural Network (ANN) model for monthly ammonia nitrogen series prediction in river water. The WA decomposed original time series into different subseries, in which the most significant one was chosen as the training data instead of the original series. Compared to the traditional ANN, the WA-ANN models were found more accurate and r...
Fractal Analysis of Drainage Basins on Mars
Stepinski, T. F.; Marinova, M. M.; McGovern, P. J.; Clifford, S. M.
2002-01-01
We used statistical properties of drainage networks on Mars as a measure of martian landscape morphology and an indicator of landscape evolution processes. We utilize the Mars Orbiter Laser Altimeter (MOLA) data to construct digital elevation maps (DEMs) of several, mostly ancient, martian terrains. Drainage basins and channel networks are computationally extracted from DEMs and their structures are analyzed and compared to drainage networks extracted from terrestrial and lunar DEMs. We show that martian networks are self-affine statistical fractals with planar properties similar to terrestrial networks, but vertical properties similar to lunar networks. The uniformity of martian drainage density is between those for terrestrial and lunar landscapes. Our results are consistent with the roughening of ancient martian terrains by combination of rainfall-fed erosion and impacts, although roughening by other fluvial processes cannot be excluded. The notion of sustained rainfall in recent Mars history is inconsistent with our findings.
Fractal Analysis of Drainage Basins on Mars
Stepinski, T. F.; Marinova, M. M.; McGovern, P. J.; Clifford, S. M.
2002-01-01
We used statistical properties of drainage networks on Mars as a measure of martian landscape morphology and an indicator of landscape evolution processes. We utilize the Mars Orbiter Laser Altimeter (MOLA) data to construct digital elevation maps (DEMs) of several, mostly ancient, martian terrains. Drainage basins and channel networks are computationally extracted from DEMs and their structures are analyzed and compared to drainage networks extracted from terrestrial and lunar DEMs. We show that martian networks are self-affine statistical fractals with planar properties similar to terrestrial networks, but vertical properties similar to lunar networks. The uniformity of martian drainage density is between those for terrestrial and lunar landscapes. Our results are consistent with the roughening of ancient martian terrains by combination of rainfall-fed erosion and impacts, although roughening by other fluvial processes cannot be excluded. The notion of sustained rainfall in recent Mars history is inconsistent with our findings.
Shift in the chemical composition of dissolved organic matter in the Congo River network
Lambert, Thibault; Bouillon, Steven; Darchambeau, François; Massicotte, Philippe; Borges, Alberto V.
2016-09-01
The processing of terrestrially derived dissolved organic matter (DOM) during downstream transport in fluvial networks is poorly understood. Here, we report a dataset of dissolved organic carbon (DOC) concentrations and DOM composition (stable carbon isotope ratios, absorption and fluorescence properties) acquired along a 1700 km transect in the middle reach of the Congo River basin. Samples were collected in the mainstem and its tributaries during high-water (HW) and falling-water (FW) periods. DOC concentrations and DOM composition along the mainstem were found to differ between the two periods because of a reduced lateral mixing between the central water masses of the Congo River and DOM-rich waters from tributaries and also likely because of a greater photodegradation during FW as water residence time (WRT) increased. Although the Cuvette Centrale wetland (one of the world's largest flooded forests) continuously releases highly aromatic DOM in streams and rivers of the Congo Basin, the downstream transport of DOM was found to result in an along-stream gradient from aromatic to aliphatic compounds. The characterization of DOM through parallel factor analysis (PARAFAC) suggests that this transition results from (1) the losses of aromatic compounds by photodegradation and (2) the production of aliphatic compounds by biological reworking of terrestrial DOM. Finally, this study highlights the critical importance of the river-floodplain connectivity in tropical rivers in controlling DOM biogeochemistry at a large spatial scale and suggests that the degree of DOM processing during downstream transport is a function of landscape characteristics and WRT.
Multiscale analysis of river networks using the R package linbin
Welty, Ethan Z.; Torgersen, Christian E.; Brenkman, Samuel J.; Duda, Jeffrey J.; Armstrong, Jonathan B.
2015-01-01
Analytical tools are needed in riverine science and management to bridge the gap between GIS and statistical packages that were not designed for the directional and dendritic structure of streams. We introduce linbin, an R package developed for the analysis of riverscapes at multiple scales. With this software, riverine data on aquatic habitat and species distribution can be scaled and plotted automatically with respect to their position in the stream network or—in the case of temporal data—their position in time. The linbin package aggregates data into bins of different sizes as specified by the user. We provide case studies illustrating the use of the software for (1) exploring patterns at different scales by aggregating variables at a range of bin sizes, (2) comparing repeat observations by aggregating surveys into bins of common coverage, and (3) tailoring analysis to data with custom bin designs. Furthermore, we demonstrate the utility of linbin for summarizing patterns throughout an entire stream network, and we analyze the diel and seasonal movements of tagged fish past a stationary receiver to illustrate how linbin can be used with temporal data. In short, linbin enables more rapid analysis of complex data sets by fisheries managers and stream ecologists and can reveal underlying spatial and temporal patterns of fish distribution and habitat throughout a riverscape.
Tejedor, A.; Foufoula-Georgiou, E.; Longjas, A.; Zaliapin, I. V.
2014-12-01
River deltas are intricate landscapes with complex channel networks that self-organize to deliver water, sediment, and nutrients from the apex to the delta top and eventually to the coastal zone. The natural balance of material and energy fluxes which maintains a stable hydrologic, geomorphologic, and ecological state of a river delta, is often disrupted by external factors causing topological and dynamical changes in the delta structure and function. A formal quantitative framework for studying river delta topology and transport dynamics and their response to change is lacking. Here we present such a framework based on spectral graph theory and demonstrate its value in quantifying the complexity of the delta network topology, computing its steady state fluxes, and identifying upstream (contributing) and downstream (nourishment) areas from any point in the network. We use this framework to construct vulnerability maps that quantify the relative change of sediment and water delivery to the shoreline outlets in response to possible perturbations in hundreds of upstream links. This enables us to evaluate which links (hotspots) and what management scenarios would most influence flux delivery to the outlets, paving the way of systematically examining how local or spatially distributed delta interventions can be studied within a systems approach for delta sustainability.
Zakermoshfegh, M.; Ghodsian, M.; Salehi Neishabouri, S. A. A.; Shakiba, M.
River flow forecasting is required to provide important information on a wide range of cases related to design and operation of river systems. Since there are a lot of parameters with uncertainties and non-linear relationships, the calibration of conceptual or physically-based models is often a difficult and time consuming procedure. So it is preferred to implement a heuristic black box model to perform a non-linear mapping between the input and output spaces without detailed consideration of the internal structure of the physical process. In this study, the capability of artificial neural networks for stream flow forecasting in Kashkan River in West of Iran is investigated and compared to a NAM model which is a lumped conceptual model with shuffled complex evolution algorithm for auto calibration. Multi Layer Perceptron and Radial Basis Function neural networks are introduced and implemented. The results show that the discharge can be more adequately forecasted by Multi Layer Perceptron neural network, compared to other implemented models, in case of both peak discharge and base flow forecasting.
Tayyab, Muhammad; Zhou, Jianzhong; Dong, Xiaohua; Ahmad, Ijaz; Sun, Na
2017-09-01
Artificial neural network (ANN) models combined with time series decomposition are widely employed to calculate the river flows; however, the influence of the application of diverse decomposing approaches on assessing correctness is inadequately compared and examined. This study investigates the certainty of monthly streamflow by applying ANNs including feed forward back propagation neural network and radial basis function neural network (RBFNN) models integrated with discrete wavelet transform (DWT), at Jinsha River basin in the upper reaches of Yangtze River of China. The effect of the noise factor of the decomposed time series on the prediction correctness has also been argued in this paper. Data have been analyzed by comparing the simulation outputs of the models with the correlation coefficient (R) root mean square errors, mean absolute errors, mean absolute percentage error and Nash-Sutcliffe Efficiency. Results show that time series decomposition technique DWT contributes in improving the accuracy of streamflow prediction, as compared to single ANN's. The detailed comparative analysis showed that the RBFNN integrated with DWT has better forecasting capabilities as compared to other developed models. Moreover, for high-precision streamflow prediction, the high-frequency section of the original time series is very crucial, which is understandable in flood season.
Potential of commercial microwave link network derived rainfall for river runoff simulations
Smiatek, Gerhard; Keis, Felix; Chwala, Christian; Fersch, Benjamin; Kunstmann, Harald
2017-03-01
Commercial microwave link networks allow for the quantification of path integrated precipitation because the attenuation by hydrometeors correlates with rainfall between transmitter and receiver stations. The networks, operated and maintained by cellphone companies, thereby provide completely new and country wide precipitation measurements. As the density of traditional precipitation station networks worldwide is significantly decreasing, microwave link derived precipitation estimates receive increasing attention not only by hydrologists but also by meteorological and hydrological services. We investigate the potential of microwave derived precipitation estimates for streamflow prediction and water balance analyses, exemplarily shown for an orographically complex region in the German Alps (River Ammer). We investigate the additional value of link derived rainfall estimations combined with station observations compared to station and weather radar derived values. Our river runoff simulation system employs a distributed hydrological model at 100 × 100 m grid resolution. We analyze the potential of microwave link derived precipitation estimates for two episodes of 30 days with typically moderate river flow and an episode of extreme flooding. The simulation results indicate the potential of this novel precipitation monitoring method: a significant improvement in hydrograph reproduction has been achieved in the extreme flooding period that was characterized by a large number of local strong precipitation events. The present rainfall monitoring gauges alone were not able to correctly capture these events.
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Yu Jiang
2012-10-01
Full Text Available River networks have experienced serious degradation because of rapid urbanization and population growth in developing countries such as China, and the protection of these networks requires the integration of evaluation with ecology and economics. In this study, a structured questionnaire survey of local residents in Shanghai (China was conducted in urban and suburban areas. The study examined residents’ awareness of the value of the river network, sought their attitude toward the current status, and employed a logistic regression analysis based on the contingent valuation method (CVM to calculate the total benefit and explain the socioeconomic factors influencing the residents’ willingness to pay (WTP. The results suggested that residents in Shanghai had a high degree of recognition of river network value but a low degree of satisfaction with the government’s actions and the current situation. The study also illustrated that the majority of respondents were willing to pay for river network protection. The mean WTP was 226.44 RMB per household per year. The number of years lived in Shanghai, the distance from the home to the nearest river, and the amount of the bid were important factors that influenced the respondents’ WTP. Suggestions for comprehensive management were proposed for the use of policy makers in river network conservation.
Estimation of Daily Stream Temperatures in a Mountain River Network
Sohrabi, M.; Benjankar, R. M.; Isaak, D.; Wenger, S.; Tonina, D.
2013-12-01
Stream temperature plays an important role in aquatic ecosystems. Concentrations of dissolved oxygen, water and spawning habitat quality, growth of fish populations are functions of stream temperature. Therefore, accurate estimates of daily stream temperatures can provide beneficial information for water resource managers and decision makers. Here, we develop a model for precise daily water temperature estimates that is applicable even in places lacking various meteorological and hydrological data. The water temperature model in this study is a piecewise model that considers both linear and non-linear relationships between dependent and independent variables including maximum and minimum temperature (meteorological derivers) and precipitation (hydrological deriver). We demonstrated the model in the Boise River Basin, in central Idaho, USA. The hydrology of this basin is snow-dominated and complex due to the mountainous terrain. We predicted daily stream temperature at 34 sites using 12 weather and Snowtel stations for deriving variables. Results of the stream temperature model indicate average Root Mean Square Error of 1.28 degree of Celsius along with average 0.91 of Nash-Sutcliffe coefficient for all stations. Comparison of the results of this study to Mohseni et al.'s model (1998), which is widely applied in water temperature studies, shows better performance of the model presented in this study. Our approach can be used to provide historical reconstructions of daily stream temperatures or projections of stream temperatures under climate change scenarios in any location with at least one year of daily stream temperature observations and with contemporaneous regional air temperature and precipitation data.
Paper-based inkjet-printed ultra-wideband fractal antennas
Maza, Armando Rodriguez
2012-01-01
For the first time, paper-based inkjet-printed ultra-wideband (UWB) fractal antennas are presented. Two new designs, a miniaturised UWB monopole, which utilises a fractal matching network and is the smallest reported inkjet-printed UWB printed antenna to date, and a fourth-order Koch Snowflake monopole, which utilises a Sierpinski gasket fractal for ink reduction, are demonstrated. It is shown that fractals prove to be a successful method of reducing fabrication costs in inkjet-printed antennas, while retaining or enhancing printed antenna performance. © 2012 The Institution of Engineering and Technology.
Dynamic versus static neural network model for rainfall forecasting at Klang River Basin, Malaysia
Directory of Open Access Journals (Sweden)
A. El-Shafie
2012-04-01
Full Text Available Rainfall is considered as one of the major components of the hydrological process; it takes significant part in evaluating drought and flooding events. Therefore, it is important to have an accurate model for rainfall forecasting. Recently, several data-driven modeling approaches have been investigated to perform such forecasting tasks as multi-layer perceptron neural networks (MLP-NN. In fact, the rainfall time series modeling involves an important temporal dimension. On the other hand, the classical MLP-NN is a static and has a memoryless network architecture that is effective for complex nonlinear static mapping. This research focuses on investigating the potential of introducing a neural network that could address the temporal relationships of the rainfall series.
Two different static neural networks and one dynamic neural network, namely the multi-layer perceptron neural network (MLP-NN, radial basis function neural network (RBFNN and input delay neural network (IDNN, respectively, have been examined in this study. Those models had been developed for the two time horizons for monthly and weekly rainfall forecasting at Klang River, Malaysia. Data collected over 12 yr (1997–2008 on a weekly basis and 22 yr (1987–2008 on a monthly basis were used to develop and examine the performance of the proposed models. Comprehensive comparison analyses were carried out to evaluate the performance of the proposed static and dynamic neural networks. Results showed that the MLP-NN neural network model is able to follow trends of the actual rainfall, however, not very accurately. RBFNN model achieved better accuracy than the MLP-NN model. Moreover, the forecasting accuracy of the IDNN model was better than that of static network during both training and testing stages, which proves a consistent level of accuracy with seen and unseen data.
Dynamic versus static neural network model for rainfall forecasting at Klang River Basin, Malaysia
Directory of Open Access Journals (Sweden)
A. El-Shafie
2011-07-01
Full Text Available Rainfall is considered as one of the major component of the hydrological process, it takes significant part of evaluating drought and flooding events. Therefore, it is important to have accurate model for rainfall forecasting. Recently, several data-driven modeling approaches have been investigated to perform such forecasting task such as Multi-Layer Perceptron Neural Networks (MLP-NN. In fact, the rainfall time series modeling involves an important temporal dimension. On the other hand, the classical MLP-NN is a static and memoryless network architecture that is effective for complex nonlinear static mapping. This research focuses on investigating the potential of introducing a neural network that could address the temporal relationships of the rainfall series.
Two different static neural networks and one dynamic neural network namely; Multi-Layer Peceptron Neural network (MLP-NN, Radial Basis Function Neural Network (RBFNN and Input Delay Neural Network (IDNN, respectively, have been examined in this study. Those models had been developed for two time horizon in monthly and weekly rainfall basis forecasting at Klang River, Malaysia. Data collected over 12 yr (1997–2008 on weekly basis and 22 yr (1987–2008 for monthly basis were used to develop and examine the performance of the proposed models. Comprehensive comparison analyses were carried out to evaluate the performance of the proposed static and dynamic neural network. Results showed that MLP-NN neural network model able to follow the similar trend of the actual rainfall, yet it still relatively poor. RBFNN model achieved better accuracy over the MLP-NN model. Moreover, the forecasting accuracy of the IDNN model outperformed during training and testing stage which prove a consistent level of accuracy with seen and unseen data. Furthermore, the IDNN significantly enhance the forecasting accuracy if compared with the other static neural network model as they could memorize the
Dynamic versus static neural network model for rainfall forecasting at Klang River Basin, Malaysia
El-Shafie, A.; Noureldin, A.; Taha, M.; Hussain, A.; Mukhlisin, M.
2012-04-01
Rainfall is considered as one of the major components of the hydrological process; it takes significant part in evaluating drought and flooding events. Therefore, it is important to have an accurate model for rainfall forecasting. Recently, several data-driven modeling approaches have been investigated to perform such forecasting tasks as multi-layer perceptron neural networks (MLP-NN). In fact, the rainfall time series modeling involves an important temporal dimension. On the other hand, the classical MLP-NN is a static and has a memoryless network architecture that is effective for complex nonlinear static mapping. This research focuses on investigating the potential of introducing a neural network that could address the temporal relationships of the rainfall series. Two different static neural networks and one dynamic neural network, namely the multi-layer perceptron neural network (MLP-NN), radial basis function neural network (RBFNN) and input delay neural network (IDNN), respectively, have been examined in this study. Those models had been developed for the two time horizons for monthly and weekly rainfall forecasting at Klang River, Malaysia. Data collected over 12 yr (1997-2008) on a weekly basis and 22 yr (1987-2008) on a monthly basis were used to develop and examine the performance of the proposed models. Comprehensive comparison analyses were carried out to evaluate the performance of the proposed static and dynamic neural networks. Results showed that the MLP-NN neural network model is able to follow trends of the actual rainfall, however, not very accurately. RBFNN model achieved better accuracy than the MLP-NN model. Moreover, the forecasting accuracy of the IDNN model was better than that of static network during both training and testing stages, which proves a consistent level of accuracy with seen and unseen data.
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D. Yamazaki
2009-07-01
Full Text Available This paper proposes an improved method to convert a fine-resolution flow direction map into a coarse-resolution river network map for the use in global river routing models. The proposed method attempts to preserve the river network structure of an original fine-resolution map in upscaling procedures, which has not been achieved by previous methods. It is found that the problem in previous methods is mainly due to the traditional way of describing downstream cells of a river network map with a direction toward one of the eight neighboring cells. Instead in the improved method, the downstream cell can be flexibly located onto any cells in the river network map. The improved method is applied to derive global river network maps at various resolutions. It succeeded to preserve the river network structure of the original flow direction map, and consequently realizes automatic construction of river network maps at any resolutions. This enables both higher-resolution approach in global river routing models and inclusion of sub-grid scale topographic features, such as realistic river meanderings and catchment boundaries. Those advantages of the proposed method are expected to enhance ability of global river routing models, providing ways to represent surface water storage and movement such as river discharge and inundated area extent in much finer-scale than ever modeled.
Strahm, Ivo; Munz, Nicole; Braun, Christian; Gälli, René; Leu, Christian; Stamm, Christian
2014-05-01
Water quality in the Swiss river network is affected by many micropollutants from a variety of diffuse sources. This study compares, for the first time, in a comprehensive manner the diffuse sources and the substance groups that contribute the most to water contamination in Swiss streams and highlights the major regions for water pollution. For this a simple but comprehensive model was developed to estimate emission from diffuse sources for the entire Swiss river network of 65 000 km. Based on emission factors the model calculates catchment specific losses to streams for more than 15 diffuse sources (such as crop lands, grassland, vineyards, fruit orchards, roads, railways, facades, roofs, green space in urban areas, landfills, etc.) and more than 130 different substances from 5 different substance groups (pesticides, biocides, heavy metals, human drugs, animal drugs). For more than 180 000 stream sections estimates of mean annual pollutant loads and mean annual concentration levels were modeled. This data was validated with a set of monitoring data and evaluated based on annual average environmental quality standards (AA-EQS). Model validation showed that the estimated mean annual concentration levels are within the range of measured data. Therefore simulations were considered as adequately robust for identifying the major sources of diffuse pollution. The analysis depicted that in Switzerland widespread pollution of streams can be expected. Along more than 18 000 km of the river network one or more simulated substances has a concentration exceeding the AA-EQS. In single stream sections it could be more than 50 different substances. Moreover, the simulations showed that in two-thirds of small streams (Strahler order 1 and 2) at least one AA-EQS is always exceeded. The highest number of substances exceeding the AA-EQS are in areas with large fractions of arable cropping, vineyards and fruit orchards. Urban areas are also of concern even without considering
Insights and issues with simulating terrestrial DOC loading of Arctic river networks
Kicklighter, David W.; Hayes, Daniel J.; McClelland, James W.; Peterson, Bruce J.; McGuire, A. David; Melillo, Jerry M.
2013-01-01
Terrestrial carbon dynamics inﬂuence the contribution of dissolved organic carbon (DOC) to river networks in addition to hydrology. In this study, we use a biogeochemical process model to simulate the lateral transfer of DOC from land to the Arctic Ocean via riverine transport. We estimate that, over the 20th century, the pan-Arctic watershed has contributed, on average, 32 Tg C/yr of DOC to river networks emptying into the Arctic Ocean with most of the DOC coming from the extensive area of boreal deciduous needle-leaved forests and forested wetlands in Eurasian watersheds. We also estimate that the rate of terrestrial DOC loading has been increasing by 0.037 Tg C/yr2 over the 20th century primarily as a result of climate-induced increases in water yield. These increases have been offset by decreases in terrestrial DOC loading caused by wildﬁres. Other environmental factors (CO2 fertilization, ozone pollution, atmospheric nitrogen deposition, timber harvest, agriculture) are estimated to have relatively small effects on terrestrial DOC loading to Arctic rivers. The effects of the various environmental factors on terrestrial carbon dynamics have both offset and enhanced concurrent effects on hydrology to inﬂuence terrestrial DOC loading and may be changing the relative importance of terrestrial carbon dynamics on this carbon ﬂux. Improvements in simulating terrestrial DOC loading to pan-Arctic rivers in the future will require better information on the production and consumption of DOC within the soil proﬁle, the transfer of DOC from land to headwater streams, the spatial distribution of precipitation and its temporal trends, carbon dynamics of larch-dominated ecosystems in eastern Siberia, and the role of industrial organic efﬂuents on carbon budgets of rivers in western Russia.
Gomez-Velez, J. D.; Harvey, J. W.
2014-12-01
Hyporheic exchange has been hypothesized to have basin-scale consequences; however, predictions throughout river networks are limited by available geomorphic and hydrogeologic data as well as models that can analyze and aggregate hyporheic exchange flows across large spatial scales. We developed a parsimonious but physically-based model of hyporheic flow for application in large river basins: Networks with EXchange and Subsurface Storage (NEXSS). At the core of NEXSS is a characterization of the channel geometry, geomorphic features, and related hydraulic drivers based on scaling equations from the literature and readily accessible information such as river discharge, bankfull width, median grain size, sinuosity, channel slope, and regional groundwater gradients. Multi-scale hyporheic flow is computed based on combining simple but powerful analytical and numerical expressions that have been previously published. We applied NEXSS across a broad range of geomorphic diversity in river reaches and synthetic river networks. NEXSS demonstrates that vertical exchange beneath submerged bedforms dominates hyporheic fluxes and turnover rates along the river corridor. Moreover, the hyporheic zone's potential for biogeochemical transformations is comparable across stream orders, but the abundance of lower-order channels results in a considerably higher cumulative effect for low-order streams. Thus, vertical exchange beneath submerged bedforms has more potential for biogeochemical transformations than lateral exchange beneath banks, although lateral exchange through meanders may be important in large rivers. These results have implications for predicting outcomes of river and basin management practices.
Modelling Nitrate uptake in river networks using the new mHM water quality model
Yang, Xiaoqiang; Sinha, Sumit; Samaniego, Luis; Kumar, Rohini; Jomaa, Seifeddine; Rode, Michael
2016-04-01
To understand the spatial distribution and temporal dynamics of nitrate uptake in river networks under different land use are critical for the protection of river ecosystem and drinking water supply. To this end, distributed grid-based hydrological water quality models are required. The multi-scale Hydrological Model (mHM) was integrated with the nitrate transport and reaction (NTR) routines. The main equations of NTR routines were introduced from the HYPE (Hydrological Predictions for the Environment) model, which has been fully verified in the literature. The new coupled mHM model with the NTR routines is able to calculate the hydrographs at any point and also the distribution of state variables, which makes it possible to present the distribution of inorganic nitrogen uptake in the whole river network. First, the model is successfully calibrated and validated in the Selke catchment (463 km2) using three gauging stations during the period of 1994-2004 in terms of hydrographs and inorganic nitrogen concentrations. Then, the model performance for in-stream Nitrate uptake predictions are presented and analyzed temporally and spatially, considering the Selke river network characteristics. Particularly, how much the land use affects the amount and the intra-annual dynamics of in-stream uptake are discussed using one forest-dominant sub-catchment (Meisdorf, where forest share is about 72%) with another agriculture-dominant sub-catchment (Hausneindorf, where agriculture share is about 76%). In addition, the seasonal variation of model in-stream nitrate uptake predictions are compared with calculated values using the nitrate assimilatory uptake approach generated from high frequency sensor measurements.
Multilayer adsorption on fractal surfaces.
Vajda, Péter; Felinger, Attila
2014-01-10
Multilayer adsorption is often observed in liquid chromatography. The most frequently employed model for multilayer adsorption is the BET isotherm equation. In this study we introduce an interpretation of multilayer adsorption measured on liquid chromatographic stationary phases based on the fractal theory. The fractal BET isotherm model was successfully used to determine the apparent fractal dimension of the adsorbent surface. The nonlinear fitting of the fractal BET equation gives us the estimation of the adsorption equilibrium constants and the monolayer saturation capacity of the adsorbent as well. In our experiments, aniline and proline were used as test molecules on reversed phase and normal phase columns, respectively. Our results suggest an apparent fractal dimension 2.88-2.99 in the case of reversed phase adsorbents, in the contrast with a bare silica column with a fractal dimension of 2.54.
Kinetic properties of fractal media
Chumak, Oleg V
2016-01-01
Kinetic processes in fractal stellar media are analyzed in terms of the approach developed in our earlier paper (Chumak, Rastorguev, 2016) involving a generalization of the nearest neighbor and random force distributions to fractal media. Diffusion is investigated in the approximation of scale-dependent conditional density based on an analysis of the solutions of the corresponding Langevin equations. It is shown that kinetic parameters (time scales, coefficients of dynamic friction, diffusion, etc.) for fractal stellar media can differ significantly both qualitatively and quantitatively from the corresponding parameters for a quasi-uniform random media with limited fluctuations. The most important difference is that in the fractal case kinetic parameters depend on spatial scale length and fractal dimension of the medium studied. A generalized kinetic equation for stellar media (fundamental equation of stellar dynamics) is derived in the Fokker-Planck approximation with the allowance for the fractal properties...
Fractals in geology and geophysics
Turcotte, Donald L.
1989-01-01
The definition of a fractal distribution is that the number of objects N with a characteristic size greater than r scales with the relation N of about r exp -D. The frequency-size distributions for islands, earthquakes, fragments, ore deposits, and oil fields often satisfy this relation. This application illustrates a fundamental aspect of fractal distributions, scale invariance. The requirement of an object to define a scale in photograhs of many geological features is one indication of the wide applicability of scale invariance to geological problems; scale invariance can lead to fractal clustering. Geophysical spectra can also be related to fractals; these are self-affine fractals rather than self-similar fractals. Examples include the earth's topography and geoid.
Fractals in several electrode materials
Energy Technology Data Exchange (ETDEWEB)
Zhang, Chunyong, E-mail: zhangchy@njau.edu.cn [Department of Chemistry, College of Science, Nanjing Agricultural University, Nanjing 210095 (China); Suzhou Key Laboratory of Environment and Biosafety, Suzhou Academy of Southeast University, Dushuhu lake higher education town, Suzhou 215123 (China); Wu, Jingyu [Department of Chemistry, College of Science, Nanjing Agricultural University, Nanjing 210095 (China); Fu, Degang [Suzhou Key Laboratory of Environment and Biosafety, Suzhou Academy of Southeast University, Dushuhu lake higher education town, Suzhou 215123 (China); State Key Laboratory of Bioelectronics, Southeast University, Nanjing 210096 (China)
2014-09-15
Highlights: • Fractal geometry was employed to characterize three important electrode materials. • The surfaces of all studied electrodes were proved to be very rough. • The fractal dimensions of BDD and ACF were scale dependent. • MMO film was more uniform than BDD and ACF in terms of fractal structures. - Abstract: In the present paper, the fractal properties of boron-doped diamond (BDD), mixed metal oxide (MMO) and activated carbon fiber (ACF) electrode have been studied by SEM imaging at different scales. Three materials are self-similar with mean fractal dimension in the range of 2.6–2.8, confirming that they all exhibit very rough surfaces. Specifically, it is found that MMO film is more uniform in terms of fractal structure than BDD and ACF. As a result, the intriguing characteristics make these electrodes as ideal candidates for high-performance decontamination processes.
Eliazar, Iddo; Klafter, Joseph
2008-06-01
We explore six classes of fractal probability laws defined on the positive half-line: Weibull, Frechét, Lévy, hyper Pareto, hyper beta, and hyper shot noise. Each of these classes admits a unique statistical power-law structure, and is uniquely associated with a certain operation of renormalization. All six classes turn out to be one-dimensional projections of underlying Poisson processes which, in turn, are the unique fixed points of Poissonian renormalizations. The first three classes correspond to linear Poissonian renormalizations and are intimately related to extreme value theory (Weibull, Frechét) and to the central limit theorem (Lévy). The other three classes correspond to nonlinear Poissonian renormalizations. Pareto's law--commonly perceived as the "universal fractal probability distribution"--is merely a special case of the hyper Pareto class.
A hybrid deep neural network and physically based distributed model for river stage prediction
hitokoto, Masayuki; sakuraba, Masaaki
2016-04-01
We developed the real-time river stage prediction model, using the hybrid deep neural network and physically based distributed model. As the basic model, 4 layer feed-forward artificial neural network (ANN) was used. As a network training method, the deep learning technique was applied. To optimize the network weight, the stochastic gradient descent method based on the back propagation method was used. As a pre-training method, the denoising autoencoder was used. Input of the ANN model is hourly change of water level and hourly rainfall, output data is water level of downstream station. In general, the desirable input of the ANN has strong correlation with the output. In conceptual hydrological model such as tank model and storage-function model, river discharge is governed by the catchment storage. Therefore, the change of the catchment storage, downstream discharge subtracted from rainfall, can be the potent input candidate of the ANN model instead of rainfall. From this point of view, the hybrid deep neural network and physically based distributed model was developed. The prediction procedure of the hybrid model is as follows; first, downstream discharge was calculated by the distributed model, and then estimates the hourly change of catchment storage form rainfall and calculated discharge as the input of the ANN model, and finally the ANN model was calculated. In the training phase, hourly change of catchment storage can be calculated by the observed rainfall and discharge data. The developed model was applied to the one catchment of the OOYODO River, one of the first-grade river in Japan. The modeled catchment is 695 square km. For the training data, 5 water level gauging station and 14 rain-gauge station in the catchment was used. The training floods, superior 24 events, were selected during the period of 2005-2014. Prediction was made up to 6 hours, and 6 models were developed for each prediction time. To set the proper learning parameters and network
Turbulent wakes of fractal objects.
Staicu, Adrian; Mazzi, Biagio; Vassilicos, J C; van de Water, Willem
2003-06-01
Turbulence of a windtunnel flow is stirred using objects that have a fractal structure. The strong turbulent wakes resulting from three such objects which have different fractal dimensions are probed using multiprobe hot-wire anemometry in various configurations. Statistical turbulent quantities are studied within inertial and dissipative range scales in an attempt to relate changes in their self-similar behavior to the scaling of the fractal objects.
Suwannee River flow variability 1550-2005 CE reconstructed from a multispecies tree-ring network
Harley, Grant L.; Maxwell, Justin T.; Larson, Evan; Grissino-Mayer, Henri D.; Henderson, Joseph; Huffman, Jean
2017-01-01
Understanding the long-term natural flow regime of rivers enables resource managers to more accurately model water level variability. Models for managing water resources are important in Florida where population increase is escalating demand on water resources and infrastructure. The Suwannee River is the second largest river system in Florida and the least impacted by anthropogenic disturbance. We used new and existing tree-ring chronologies from multiple species to reconstruct mean March-October discharge for the Suwannee River during the period 1550-2005 CE and place the short period of instrumental flows (since 1927 CE) into historical context. We used a nested principal components regression method to maximize the use of chronologies with varying time coverage in the network. Modeled streamflow estimates indicated that instrumental period flow conditions do not adequately capture the full range of Suwannee River flow variability beyond the observational period. Although extreme dry and wet events occurred in the gage record, pluvials and droughts that eclipse the intensity and duration of instrumental events occurred during the 16-19th centuries. The most prolonged and severe dry conditions during the past 450 years occurred during the 1560s CE. In this prolonged drought period mean flow was estimated at 17% of the mean instrumental period flow. Significant peaks in spectral density at 2-7, 10, 45, and 85-year periodicities indicated the important influence of coupled oceanic-atmospheric processes on Suwannee River streamflow over the past four centuries, though the strength of these periodicities varied over time. Future water planning based on current flow expectations could prove devastating to natural and human systems if a prolonged and severe drought mirroring the 16th and 18th century events occurred. Future work in the region will focus on updating existing tree-ring chronologies and developing new collections from moisture-sensitive sites to improve
Statistical mechanics and fractals
Dobrushin, Roland Lvovich
1993-01-01
This book is composed of two texts, by R.L. Dobrushin and S. Kusuoka, each representing the content of a course of lectures given by the authors. They are pitched at graduate student level and are thus very accessible introductions to their respective subjects for students and non specialists. CONTENTS: R.L. Dobrushin: On the Way to the Mathematical Foundations of Statistical Mechanics.- S. Kusuoka: Diffusion Processes on Nested Fractals.
Martin, Demetri
2015-03-01
Demetri Maritn prepared this palindromic poem as his project for Michael Frame's fractal geometry class at Yale. Notice the first, fourth, and seventh words in the second and next-to-second lines are palindromes, the first two and last two lines are palindromes, the middle line, "Be still if I fill its ebb" minus its last letter is a palindrome, and the entire poem is a palindrome...
Fractal multifiber microchannel plates
Cook, Lee M.; Feller, W. B.; Kenter, Almus T.; Chappell, Jon H.
1992-01-01
The construction and performance of microchannel plates (MCPs) made using fractal tiling mehtods are reviewed. MCPs with 40 mm active areas having near-perfect channel ordering were produced. These plates demonstrated electrical performance characteristics equivalent to conventionally constructed MCPs. These apparently are the first MCPs which have a sufficiently high degree of order to permit single channel addressability. Potential applications for these devices and the prospects for further development are discussed.
Fractal analysis of lumbar vertebral cancellous bone architecture.
Feltrin, G P; Macchi, V; Saccavini, C; Tosi, E; Dus, C; Fassina, A; Parenti, A; De Caro, R
2001-11-01
Osteoporosis is characterized by bone mineral density (BMD) decreasing and spongy bone rearrangement with consequent loss of elasticity and increased bone fragility. Quantitative computed tomography (QCT) quantifies bone mineral content but does not describe spongy architecture. Analysis of trabecular pattern may provide additional information to evaluate osteoporosis. The aim of this study was to determine whether the fractal analysis of the microradiography of lumbar vertebrae provides a reliable assessment of bone texture, which correlates with the BMD. The lumbar segment of the spine was removed from 22 cadavers with no history of back pain and examined with standard x-ray, traditional tomography, and quantitative computed tomography to measure BMD. The fractal dimension, which quantifies the image fractal complexity, was calculated on microradiographs of axial sections of the fourth lumbar vertebra to determine its characteristic spongy network. The relationship between the values of the BMD and those of the fractal dimension was evaluated by linear regression and a statistically significant correlation (R = 0.96) was found. These findings suggest that the application of fractal analysis to radiological analyses can provide valuable information on the trabecular pattern of vertebrae. Thus, fractal dimensions of trabecular bone structure should be considered as a supplement to BMD evaluation in the assessment of osteoporosis.
Spina, Maria E; Saraceno, Marcos
2010-01-01
It has been conjectured that for a class of piecewise linear maps the closure of the set of images of the discontinuity has the structure of a fat fractal, that is, a fractal with positive measure. An example of such maps is the sawtooth map in the elliptic regime. In this work we analyze this problem quantum mechanically in the semiclassical regime. We find that the fraction of states localized on the unstable set satisfies a modified fractal Weyl law, where the exponent is given by the exterior dimension of the fat fractal.
Fractals a very short introduction
Falconer, Kenneth
2013-01-01
Many are familiar with the beauty and ubiquity of fractal forms within nature. Unlike the study of smooth forms such as spheres, fractal geometry describes more familiar shapes and patterns, such as the complex contours of coastlines, the outlines of clouds, and the branching of trees. In this Very Short Introduction, Kenneth Falconer looks at the roots of the 'fractal revolution' that occurred in mathematics in the 20th century, presents the 'new geometry' of fractals, explains the basic concepts, and explores the wide range of applications in science, and in aspects of economics.This is esse
The River Network, Active Tectonics and the Mexican Subduction Zone, Southwest Mexico
Gaidzik, K.; Ramirez-Herrera, M. T.; Kostoglodov, V.; Basili, R.
2014-12-01
Rivers, their profiles and network reflect the integration of multiple processes and forces that are part of the fundamental controls on the relief structure of mountain belts. The motivation of this study is to understand active tectonic processes in the forearc region of subduction zones, by distinguishing evidence of active deformation using the river network and topography. To this end, morphotectonic and structural studies have been conducted on fifteen drainage basins on the mountain front, parallel to the Mexican subduction zone, where the Cocos plate underthrusts the North American plate. The southwest - northeast Cocos plate subduction stress regime initiated ca. 20 MA. NE-SW to NNE-SSW normal faults as well as sub-latitudinal to NW-SE strike-slip faults (both dextral and sinistral) constitute the majority of mesofaults recorded in the field within the studied drainage basins. Occasionally dextral N-S strike-slip faults also occur. The stress tensor reconstruction suggests two main evolution stages of these faults: 1) the older is dominated by a NW-SE to WNW-ESE extensional regime and 2) the younger is a transcurrent regime, with NNE-SSW σ1 axis. The drainage pattern is strongly controlled by tectonic features, whereas lithology is only a subordinate factor, with only one exception (Petatlán river). Generally, major rivers flow from north to south mainly through NE-SW and NNE-SSW normal faults, and/or sub-longitudinal dextral (also locally sinistral) strike-slip faults. In the central and eastern part of the studied area, rivers also follow NW-SE structures, which are generally normal or sinistral strike-slip faults (rarely reverse). In most cases, local deflections of the river main courses are related to sub-latitudinal strike-slip faults, both dextral and sinistral. Within the current stress field related to the active Cocos subduction, both normal and strike-slip fault sets could be reactivated. Our analysis suggests that strike-slip faults, mainly
River-Network Numerical Model Base on Flux Difference Split Method
Xiang, X. H.; Wu, X. L.; Wang, C. H.
2012-04-01
The paper proposes an implementation of river-network numerical model in computational hydraulics study. The numerical basis of the model is the high resolution method which was usually used in gas dynamics. A high accurate numerical scheme for saint-venant was introduced base on flux difference split method, coupled with wave transportation, Limiter and entropy fixed. Two different problems were discussed for the model, the first is the method for construct the boundary conditions and the second is the method for connecting the network. A partial flux difference split method was employed for the discrete on boundary; the characteristic direction is critical factor to decide which partial to use. Among network coupling process, conservation laws was applied including mass conservation and energy conservation for all river connection points. The scheme can keep high accurate and good stability in the mean time. The present numerical method was applied to two different benchmark problems, one is ideal dam-break and another is irregular channel, both reflected that the introduced method was confirmed to be effective. And then a real river-network was tested, the comparison of observation and the numerical results show the high reliable of the introduced model. This research was supported by the National Natural Science Foundation of China (No. 51009045; 40930635; 41001011; 41101018; 51079038), the National Key Program for Developing Basic Science (No. 2009CB421105), the Fundamental Research Funds for the Central Universities (No. 2009B06614; 2010B00414), the National Non Profit Research Program of China (No. 200905013-8; 201101024; 20101224).
In situ low-relief landscape formation as a result of river network disruption.
Yang, Rong; Willett, Sean D; Goren, Liran
2015-04-23
Landscapes on Earth retain a record of the tectonic, environmental and climatic history under which they formed. Landscapes tend towards an equilibrium in which rivers attain a stable grade that balances the tectonic production of elevation and with hillslopes that attain a gradient steep enough to transport material to river channels. Equilibrium low-relief surfaces are typically found at low elevations, graded to sea level. However, there are many examples of high-elevation, low-relief surfaces, often referred to as relict landscapes, or as elevated peneplains. These do not grade to sea level and are typically interpreted as uplifted old landscapes, preserving former, more moderate tectonic conditions. Here we test this model of landscape evolution through digital topographic analysis of a set of purportedly relict landscapes on the southeastern margin of the Tibetan Plateau, one of the most geographically complex, climatically varied and biologically diverse regions of the world. We find that, in contrast to theory, the purported surfaces are not consistent with progressive establishment of a new, steeper, river grade, and therefore they cannot necessarily be interpreted as a remnant of an old, low relief surface. We propose an alternative model, supported by numerical experiments, in which tectonic deformation has disrupted the regional river network, leaving remnants of it isolated and starved of drainage area and thus unable to balance tectonic uplift. The implication is that the state of low relief with low erosion rate is developing in situ, rather than preserving past erosional conditions.
In situ low-relief landscape formation as a result of river network disruption
Yang, Rong; Willett, Sean D.; Goren, Liran
2015-04-01
Landscapes on Earth retain a record of the tectonic, environmental and climatic history under which they formed. Landscapes tend towards an equilibrium in which rivers attain a stable grade that balances the tectonic production of elevation and with hillslopes that attain a gradient steep enough to transport material to river channels. Equilibrium low-relief surfaces are typically found at low elevations, graded to sea level. However, there are many examples of high-elevation, low-relief surfaces, often referred to as relict landscapes, or as elevated peneplains. These do not grade to sea level and are typically interpreted as uplifted old landscapes, preserving former, more moderate tectonic conditions. Here we test this model of landscape evolution through digital topographic analysis of a set of purportedly relict landscapes on the southeastern margin of the Tibetan Plateau, one of the most geographically complex, climatically varied and biologically diverse regions of the world. We find that, in contrast to theory, the purported surfaces are not consistent with progressive establishment of a new, steeper, river grade, and therefore they cannot necessarily be interpreted as a remnant of an old, low relief surface. We propose an alternative model, supported by numerical experiments, in which tectonic deformation has disrupted the regional river network, leaving remnants of it isolated and starved of drainage area and thus unable to balance tectonic uplift. The implication is that the state of low relief with low erosion rate is developing in situ, rather than preserving past erosional conditions.
Ceola, Serena; Montanari, Alberto; Parajka, Juraj; Viglione, Alberto; Blöschl, Günter; Laio, Francesco
2016-05-01
Understanding how human settlements and economic activities are distributed with reference to the geographical location of streams and rivers is of fundamental relevance for several issues, such as flood risk management, drought management related to increased water demands by human population, fluvial ecosystem services, water pollution and water exploitation. Besides the spatial distribution, the evolution in time of the human presence constitutes an additional key question. This work aims at understanding and analysing the spatial and temporal evolution of human settlements and associated economic activity, derived from nighttime lights, in the Eastern Alpine region. Nightlights, available at a fine spatial resolution and for a 22-year period, constitute an excellent data base, which allows one to explore in details human signatures. In this experiment, nightlights are associated to five distinct distance-from-river classes. Our results clearly point out an overall enhancement of human presence across the considered distance classes during the last 22 years, though presenting some differences among the study regions. In particular, the river network delineation, by considering different groups of river pixels based on the Strahler order, is found to play a central role in the identification of nightlight spatio-temporal trends.
A Model of Biocomplexity in River Networks - Part I: General Theory
Thorp, J. H.; Thoms, M. C.; Delong, M. D.
2005-05-01
We are proposing an integrated, heuristic model of lotic biocomplexity that encompasses spatiotemporal scales from headwaters to large rivers and from main channels to floodplains. Our hope is that this model will provide a foundation for understanding both broad, often discontinuous patterns along longitudinal and lateral dimensions of river networks and local ecological patterns across various temporal and smaller spatial scales. The model represents a conceptual marriage of eco-geomorphology with a terrestrial landscape model describing hierarchical patch dynamics (HPD). Contrasting with a common view of rivers as continuous, longitudinal gradients in physical conditions, our model portrays rivers as downstream arrays of large hydrogeomorphic patches formed by catchment geomorphology and climate. Unique "functional process zones" (FPZs) will be formed within individual types of hydrogeomorphic patches because of physiochemical habitat differences affecting ecosystem structure and function. Our conceptual model blends our perspectives on biocomplexity with aspects of aquatic models proposed from 1980-2004. In Part I of our oral presentation, we will give an overview of this biocomplexity model and discuss how it varies from our perspectives on the ecology of lotic ecosystems.
Modelling macroinvertebrate and fish biotic indices: From reaches to entire river networks.
Álvarez-Cabria, Mario; González-Ferreras, Alexia M; Peñas, Francisco J; Barquín, José
2017-01-15
We modelled three macroinvertebrate (IASPT, EPT number of families and LIFE) and one fish (percentage of salmonid biomass) biotic indices to river networks draining a large region (110,000km(2)) placed in Northern and Eastern Spain. Models were developed using Random Forest and 26 predictor variables (19 predictors to model macroinvertebrate indices and 22 predictors to model the fish index). Predictor variables were related with different environmental characteristics (water quality, physical habitat characteristics, hydrology, topography, geology and human pressures). The importance and effect of predictors on the 4 biotic indices was evaluated with the IncNodePurity index and partial dependence plots, respectively. Results indicated that the spatial variability of macroinvertebrate and fish indices were mostly dependent on the same environmental variables. They decreased in river reaches affected by high mean annual nitrate concentration (>4mg/l) and temperature (>12°C), with low flow water velocity (macrophytes. These indices were higher in the Atlantic region than in the Mediterranean. This study provides a continuous image of river biological communities used as indicators, which turns very useful to identify the main sources of change in the ecological status of water bodies and assist both, the integrated catchment management and the identification of river reaches for recovery. Copyright © 2016 Elsevier B.V. All rights reserved.
A multiple fractal model for estimating permeability of dual-porosity media
Li, Bo; Liu, Richeng; Jiang, Yujing
2016-09-01
A multiple fractal model that considers the fractal properties of both porous matrices and fracture networks is proposed for the permeability of dual-porosity media embedded with randomly distributed fractures. In this model, the aperture distribution is verified to follow the fractal scaling law, and the porous matrix is assumed to comprise a bundle of tortuous capillaries that also follow the fractal scaling law. Analytical expressions for fractal aperture distribution, total flow rate, total equivalent permeability, and dimensionless permeability are established, where the dimensionless permeability is defined as the ratio of permeability of the porous matrices to that of the fracture networks. The dimensionless permeability is closely correlated to the structural parameters (i.e., α, θ, Dtf, Dtp, De, Dp, emax, λmax) of the dual-porosity media, and it is more sensitive to the fractal dimension for the size distribution of fracture aperture than to that for the size distribution of pore/capillary diameter. The maximum pore/capillary diameter has a greater impact on the dimensionless permeability than that of the maximum fracture aperture. The dimensionless permeability of fracture networks constructed by the fractal aperture distribution has close values with those of models with lognormal aperture distribution. The proposed multiple fractal model does not involve any empirical constants that do not have clear physical meanings, which could serve as a quick estimation method for assessing permeability of dual-porosity media.
Hu, Jiatang; Li, Shiyu; Geng, Bingxu
2011-11-01
A coupled physical and sediment transport model was used to study the mass flux budgets of water and suspended sediments in the Pearl River Delta (PRD). The coupled model incorporates the Pearl River network, the Pearl River Estuary (PRE) and adjacent coastal waters in one overall modeling system. The results indicate that the river network and the PRE both have pronounced temporal and spatial variability in water and sediment fluxes, in hydrodynamic features and in sediment depositional patterns. In the river network, the riverine fluxes of water and suspended sediments are dominated by the West River, and those that are exported to the PRE (defined as the estuarine fluxes) are primarily contributed by Modaomen. The river outlets are highly responsive to the main tributaries in terms of water and sediment fluxes, revealing a close coupling between the upstream and the downstream boundaries. Most of the annual riverine and estuarine fluxes occur in the wet season, approximately 74% of the water flux and riverine and estuarine fluxes of suspended sediments of 94% and 87%, respectively. Although the water and sediment transport is dominated by river discharge, the tides are also an important factor, especially in regulating the structures of seasonal deposits in the river network (deposition in the wet season and erosion in the dry season). In the PRE, various types of physical forcing, including river discharge, monsoon winds, tides, coastal currents and the gravitational circulation associated with a density gradient, operate in concert to control the water and sediment transport in the estuary. Most of the oceanic fluxes of water and suspended sediments entering the South China Sea take place in the dry season and are primarily conveyed by strong western coastal currents. The PRE is a sedimentary system characterized by intricate depositional structures in space and time. Several depositional patterns and the associated driving mechanisms were identified. A fan
Thermodynamic fractals and formalism. Fractales y formalismo termodinamico
Energy Technology Data Exchange (ETDEWEB)
Chacon, R.; Morales, J.J.
1994-01-01
We give a brief introduction to the so called ''thermodynamical description of fractals'' restricting our attention to Cantor sets generated by chaotic motion of a dynamical system. In particular, an entropy function and a free energy are introduced for multi fractals. (Author) 14 refs.
Güner, Hüseyin Tuncay; Köse, Nesibe; Harley, Grant L.
2017-03-01
The Sakarya River Basin (SRB) contains one of the most important agricultural areas for Turkey. Here, we use a network of 18 tree-ring chronologies and present a reconstruction of the mean June-July Kocasu River discharge, one of the main channels in the SRB, during the period 1803-2002 CE, and place the short period of instrumental flows (since 1953 CE) into historical context. Over the past two centuries, we found 33 dry and 28 wet events and observed the longest wet period between the years 1880 and 1920. The driest years were 1845 and 1873, and the wettest years were 1859 and 1960. Our reconstruction showed that the extreme short-term drought events that occurred in recent years were minor compared to the severity and duration of droughts that occurred previous to instrumental data. We found four pre-instrumental severe and sustained low streamflow events during the periods 1819-1834, 1840-1852, 1861-1875, and 1925-1931, during which historical records show reduced agricultural production, death, famine, plague, economic crisis, and widespread human migrations. More concerning, however, are current hydroclimate conditions in the SRB, marked by decadal-scale mean flows that dip below the long-term mean (1803-1953) in the late 1970s and have since failed to recover. With the Mediterranean region currently likely experiencing the worst drought in the past ca 1000 years due to human-induced climate change, the future outlook of water resource availability in the SRB could prove catastrophic for human and natural systems.
Güner, Hüseyin Tuncay; Köse, Nesibe; Harley, Grant L.
2016-08-01
The Sakarya River Basin (SRB) contains one of the most important agricultural areas for Turkey. Here, we use a network of 18 tree-ring chronologies and present a reconstruction of the mean June-July Kocasu River discharge, one of the main channels in the SRB, during the period 1803-2002 CE, and place the short period of instrumental flows (since 1953 CE) into historical context. Over the past two centuries, we found 33 dry and 28 wet events and observed the longest wet period between the years 1880 and 1920. The driest years were 1845 and 1873, and the wettest years were 1859 and 1960. Our reconstruction showed that the extreme short-term drought events that occurred in recent years were minor compared to the severity and duration of droughts that occurred previous to instrumental data. We found four pre-instrumental severe and sustained low streamflow events during the periods 1819-1834, 1840-1852, 1861-1875, and 1925-1931, during which historical records show reduced agricultural production, death, famine, plague, economic crisis, and widespread human migrations. More concerning, however, are current hydroclimate conditions in the SRB, marked by decadal-scale mean flows that dip below the long-term mean (1803-1953) in the late 1970s and have since failed to recover. With the Mediterranean region currently likely experiencing the worst drought in the past ca 1000 years due to human-induced climate change, the future outlook of water resource availability in the SRB could prove catastrophic for human and natural systems.
Energy Technology Data Exchange (ETDEWEB)
Yeh, G.T.
1982-01-01
A description is given of the development of a channel hydrodynamic model for simulating the behavior of flows and water surface elevations in a river network that may consist of any number of joined and branched rivers/streams, including both tidal and nontidal rivers. The model employs a numerical method, an integrated compartment method (ICM). The basic procedures of the ICM are first to discretize the river/stream system into compartments of various sizes, then to apply three integral theorems of vectors to transform the n-dimensional volume integral into an (n - 1)-dimensional surface integral, and finally to close the system by using simple interpolation to relate the interfacial values in terms of the compartment values. Thus, the method greatly facilitates the setup of algebraic equations for the discrete field approximating the corresponding continuous field. Most of the possible boundary conditions that may be anticipated in real-world problems are considered. These include junctions, prescribed flow, prescribed water surface elevation (or cross-sectional area), and rating curve boundaries. The use of ICM makes the implementation of these four types of boundary conditions relatively easy. The model is applied to two case studies: first to a single river and then to a network of five river channels in a watershed. Results indicate that the model can definitely simulate the behavior of the hydrodynamic variables that are required to compute chemical transport in a river/stream network.
Aguilera, Rosana; Marcé, Rafael; Sabater, Sergi
2013-06-01
are conveyed from terrestrial and upstream sources through drainage networks. Streams and rivers contribute to regulate the material exported downstream by means of transformation, storage, and removal of nutrients. It has been recently suggested that the efficiency of process rates relative to available nutrient concentration in streams eventually declines, following an efficiency loss (EL) dynamics. However, most of these predictions are based at the reach scale in pristine streams, failing to describe the role of entire river networks. Models provide the means to study nutrient cycling from the stream network perspective via upscaling to the watershed the key mechanisms occurring at the reach scale. We applied a hybrid process-based and statistical model (SPARROW, Spatially Referenced Regression on Watershed Attributes) as a heuristic approach to describe in-stream nutrient processes in a highly impaired, high stream order watershed (the Llobregat River Basin, NE Spain). The in-stream decay specifications of the model were modified to include a partial saturation effect in uptake efficiency (expressed as a power law) and better capture biological nutrient retention in river systems under high anthropogenic stress. The stream decay coefficients were statistically significant in both nitrate and phosphate models, indicating the potential role of in-stream processing in limiting nutrient export. However, the EL concept did not reliably describe the patterns of nutrient uptake efficiency for the concentration gradient and streamflow values found in the Llobregat River basin, posing in doubt its complete applicability to explain nutrient retention processes in stream networks comprising highly impaired rivers.
Fractal analysis: methodologies for biomedical researchers.
Ristanović, Dusan; Milosević, Nebojsa T
2012-01-01
Fractal analysis has become a popular method in all branches of scientific investigations including biology and medicine. Although there is a growing interest in the application of fractal analysis in biological sciences, questions about the methodology of fractal analysis have partly restricted its wider and comprehensible application. It is a notable fact that fractal analysis is derived from fractal geometry, but there are some unresolved issues that need to be addressed. In this respect, we discuss several related underlying principles for fractal analysis and establish the meaningful relationship between fractal analysis and fractal geometry. Since some concepts in fractal analysis are determined descriptively and/or qualitatively, this paper provides their exact mathematical definitions or explanations. Another aim of this study is to show that nowadays fractal analysis is an independent mathematical and experimental method based on Mandelbrot's fractal geometry, Euclidean traditiontal geometry and Richardson's coastline method.
Lee, Bum Han; Lee, Sung Keun
2013-07-01
Despite the importance of understanding and quantifying the microstructure of porous networks in diverse geologic settings, the effects of the specific surface area and porosity on the key structural parameters of the networks have not been fully understood. We performed cube-counting fractal dimension (Dcc) and lacunarity analyses of 3D porous networks of model sands and configurational entropy analysis of 2D cross sections of model sands using random packing simulations and nuclear magnetic resonance (NMR) micro-imaging. We established relationships among porosity, specific surface area, structural parameters (Dcc and lacunarity), and the corresponding macroscopic properties (configurational entropy and permeability). The Dcc of the 3D porous networks increases with increasing specific surface area at a constant porosity and with increasing porosity at a constant specific surface area. Predictive relationships correlating Dcc, specific surface area, and porosity were also obtained. The lacunarity at the minimum box size decreases with increasing porosity, and that at the intermediate box size (∼0.469 mm in the current model sands) was reproduced well with specific surface area. The maximum configurational entropy increases with increasing porosity, and the entropy length of the pores decreases with increasing specific surface area and was used to calculate the average connectivity among the pores. The correlation among porosity, specific surface area, and permeability is consistent with the prediction from the Kozeny-Carman equation. From the relationship between the permeability and the Dcc of pores, the permeability can be expressed as a function of the Dcc of pores and porosity. The current methods and these newly identified correlations among structural parameters and properties provide improved insights into the nature of porous media and have useful geophysical and hydrological implications for elasticity and shear viscosity of complex composites of rock
Fine-resolution Modeling of Urban-Energy Systems' Water Footprint in River Networks
McManamay, R.; Surendran Nair, S.; Morton, A.; DeRolph, C.; Stewart, R.
2015-12-01
Characterizing the interplay between urbanization, energy production, and water resources is essential for ensuring sustainable population growth. In order to balance limited water supplies, competing users must account for their realized and virtual water footprint, i.e. the total direct and indirect amount of water used, respectively. Unfortunately, publicly reported US water use estimates are spatially coarse, temporally static, and completely ignore returns of water to rivers after use. These estimates are insufficient to account for the high spatial and temporal heterogeneity of water budgets in urbanizing systems. Likewise, urbanizing areas are supported by competing sources of energy production, which also have heterogeneous water footprints. Hence, a fundamental challenge of planning for sustainable urban growth and decision-making across disparate policy sectors lies in characterizing inter-dependencies among urban systems, energy producers, and water resources. A modeling framework is presented that provides a novel approach to integrate urban-energy infrastructure into a spatial accounting network that accurately measures water footprints as changes in the quantity and quality of river flows. River networks (RNs), i.e. networks of branching tributaries nested within larger rivers, provide a spatial structure to measure water budgets by modeling hydrology and accounting for use and returns from urbanizing areas and energy producers. We quantify urban-energy water footprints for Atlanta, GA and Knoxville, TN (USA) based on changes in hydrology in RNs. Although water intakes providing supply to metropolitan areas were proximate to metropolitan areas, power plants contributing to energy demand in Knoxville and Atlanta, occurred 30 and 90km outside the metropolitan boundary, respectively. Direct water footprints from urban landcover primarily comprised smaller streams whereas indirect footprints from water supply reservoirs and energy producers included
Servais, P.; Billen, G.; Goncalves, A.; Garcia-Armisen, T.
2007-09-01
The Seine river watershed is characterized by a high population density and intense agricultural activities. Data show low microbiological water quality in the main rivers (Seine, Marne, Oise) of the watershed. Today, there is an increasing pressure from different social groups to restore microbiological water quality in order to both increase the safety of drinking water production and to restore the possible use of these rivers for bathing and rowing activities, as they were in the past. A model, appended to the hydro-ecological SENEQUE/Riverstrahler model describing the functioning of large river systems, was developed to describe the dynamics of faecal coliforms (FC), the most usual faecal contamination indicator. The model is able to calculate the distribution of FC concentrations in the whole drainage network resulting from land use and wastewater management in the watershed. The model was validated by comparing calculated FC concentrations with available field data for some well-documented situations in different river stretches of the Seine drainage network. Once validated, the model was used to test various predictive scenarios, as, for example, the impact of the modifications in wastewater treatment planned at the 2012 horizon in the Seine watershed in the scope of the implementation of the european water framework directive. The model was also used to investigate past situations. In particular, the variations of the microbiological water quality in the Parisian area due to population increase and modifications in wastewater management were estimated over the last century. It was shown that the present standards for bathing and other aquatic recreational activities are not met in the large tributaries upstream from Paris since the middle of the 1950's, and at least since the middle of the XIXth century in the main branch of the Seine river downstream from Paris. Efforts carried out for improving urban wastewater treatment in terms or organic matter and
Directory of Open Access Journals (Sweden)
P. Servais
2007-05-01
Full Text Available The Seine river watershed is characterized by a high population density and intense agricultural activities. Data show low microbiological water quality in the main rivers (Seine, Marne, Oise of the watershed. Today, there is an increasing pressure from different social groups to restore microbiological water quality in order to both increase the safety of drinking water production and to restore the possible use of these rivers for bathing and rowing activities, as they were in the past. A model, appended to the hydro-ecological SENEQUE/Riverstrahler model describing the functioning of large river systems, was developed to describe the dynamics of faecal coliforms (FC, the most usual faecal contamination indicator. The model is able to calculate the distribution of FC abundance in the whole drainage network resulting from land use and wastewater management in the watershed. The model was validated by comparing calculated FC concentrations with available field data for some well-documented situations in different river stretches of the Seine drainage network. Once validated, the model was used to test various predictive scenarios, as, for example, the impact of the modifications in wastewater treatment planned at the 2012 horizon in the Seine watershed in the scope of the implementation of the European Water Framework Directive. The model was also used to investigate past situations. In particular, the variations of the microbiological water quality in the Parisian area due to population increase and modifications in wastewater management were estimated over the last century. It was shown that the present standards for bathing and other aquatic recreational activities are not met in the large tributaries upstream from Paris since the middle of the 1950's, and at least since the middle of the XIXth century in the main branch of the Seine river downstream from Paris. Efforts carried out for improving urban wastewater treatment in terms or
Directory of Open Access Journals (Sweden)
P. Servais
2007-09-01
Full Text Available The Seine river watershed is characterized by a high population density and intense agricultural activities. Data show low microbiological water quality in the main rivers (Seine, Marne, Oise of the watershed. Today, there is an increasing pressure from different social groups to restore microbiological water quality in order to both increase the safety of drinking water production and to restore the possible use of these rivers for bathing and rowing activities, as they were in the past. A model, appended to the hydro-ecological SENEQUE/Riverstrahler model describing the functioning of large river systems, was developed to describe the dynamics of faecal coliforms (FC, the most usual faecal contamination indicator. The model is able to calculate the distribution of FC concentrations in the whole drainage network resulting from land use and wastewater management in the watershed. The model was validated by comparing calculated FC concentrations with available field data for some well-documented situations in different river stretches of the Seine drainage network. Once validated, the model was used to test various predictive scenarios, as, for example, the impact of the modifications in wastewater treatment planned at the 2012 horizon in the Seine watershed in the scope of the implementation of the european water framework directive. The model was also used to investigate past situations. In particular, the variations of the microbiological water quality in the Parisian area due to population increase and modifications in wastewater management were estimated over the last century. It was shown that the present standards for bathing and other aquatic recreational activities are not met in the large tributaries upstream from Paris since the middle of the 1950's, and at least since the middle of the XIXth century in the main branch of the Seine river downstream from Paris. Efforts carried out for improving urban wastewater treatment in terms
Spatial spread of Eurasian beavers in river networks: a comparison of range expansion rates.
Barták, Vojtěch; Vorel, Aleš; Símová, Petra; Puš, Vladimír
2013-05-01
1. Accurately measuring the rate of spread for expanding populations is important for reliably predicting their future spread, as well as for evaluating the effect of different conditions and management activities on that rate of spread. 2. Although a number of methods have been developed for such measurement, all these are designed only for one- or two-dimensional spread. Species dispersing along rivers, however, require specific methods due to the distinctly branching structure of river networks. 3. In this study, we analyse data regarding Eurasian beavers' modern recolonization of the Czech Republic. We developed a new methodology for quantifying spread of species dispersing along streams based on representation of the river network by means of a weighted graph. 4. We defined two different network-based spread rate measures, one estimating the rate of range expansion, with the range defined as the total length of occupied streams, and the second, named range diameter, quantifying the progress along one or several main streams. In addition, we estimated the population growth rates, and, dividing the population size by the range size, we measured the density of beaver records within their overall range. Using linear regression, we compared four beaver populations under different environmental conditions in terms of each of these measures. Finally, we discuss the differences between our method and the classical approaches. 5. Our method provided substantially higher spread rate values than did the classical methods. Both population growth and range expansion were found to follow logistic growth. In cases of there being no considerable barriers in dispersal routes, the rate of progress along main streams did not differ significantly among populations. In homogeneous environments, population densities remained relatively constant over time even though overall population sizes increased. This indicates that at large spatial scales, the population growth of beavers
Energy Technology Data Exchange (ETDEWEB)
Ye, Sheng; Covino, Timothy P.; Sivapalan, Murugesu; Basu, Nandita; Li, Hongyi; Wang, Shaowen
2012-06-30
In this paper, we use a dynamic network flow model, coupled with a transient storage zone biogeochemical model, to simulate dissolved nutrient removal processes at the channel network scale. We have explored several scenarios in respect of the combination of rainfall variability, and the biological and geomorphic characteristics of the catchment, to understand the dominant controls on removal and delivery of dissolved nutrients (e.g., nitrate). These model-based theoretical analyses suggested that while nutrient removal efficiency is lower during flood events compared to during baseflow periods, flood events contribute significantly to bulk nutrient removal, whereas bulk removal during baseflow periods is less. This is due to the fact that nutrient supply is larger during flood events; this trend is even stronger in large rivers. However, the efficiency of removal during both periods decreases in larger rivers, however, due to (i) increasing flow velocities and thus decreasing residence time, and (ii) increasing flow depth, and thus decreasing nutrient uptake rates. Besides nutrient removal processes can be divided into two parts: in the main channel and in the hyporheic transient storage zone. When assessing their relative contributions the size of the transient storage zone is a dominant control, followed by uptake rates in the main channel and in the transient storage zone. Increasing size of the transient storage zone with downstream distance affects the relative contributions to nutrient removal of the water column and the transient storage zone, which also impacts the way nutrient removal rates scale with increasing size of rivers. Intra-annual hydrologic variability has a significant impact on removal rates at all scales: the more variable the streamflow is, compared to mean discharge, the less nutrient is removed in the channel network. A scale-independent first order uptake coefficient, ke, estimated from model simulations, is highly dependent on the
Directory of Open Access Journals (Sweden)
Wei Zhang
2014-01-01
Full Text Available River networks and estuaries are very common in coastal areas. Runoff from the upper stream interacts with tidal current from open sea in these two systems, leading to a complex hydrodynamics process. Therefore, it is necessary to consider the two systems as a whole to study the flow and suspended sediment transport. Firstly, a 1D model is established in the Pearl River network and a 3D model is applied in its estuary. As sufficient mass exchanges between the river network and its estuary, a strict mathematical relationship of water level at the interfaces can be adopted to couple the 1D model with the 3D model. By doing so, the coupled model does not need to have common nested grids. The river network exchanges the suspended sediment with its estuary by adding the continuity conditions at the interfaces. The coupled model is, respectively, calibrated in the dry season and the wet season. The results demonstrate that the coupled model works excellently in simulating water level and discharge. Although there are more errors in simulating suspended sediment concentration due to some reasons, the coupled model is still good enough to evaluate the suspended sediment transport in river network and estuary systems.
Simoson, Andrew J.
2009-01-01
This article presents a fun activity of generating a double-minded fractal image for a linear algebra class once the idea of rotation and scaling matrices are introduced. In particular the fractal flip-flops between two words, depending on the level at which the image is viewed. (Contains 5 figures.)
Brothers, Harlan J.
2015-03-01
Benoit Mandelbrot always had a strong feeling that music could be viewed from a fractal perspective. However, without our eyes to guide us, how do we gain this perspective? Here we discuss precisely what it means to say that a piece of music is fractal.
Gashi, Fatbardh; Frančišković-Bilinski, Stanislav; Bilinski, Halka; Troni, Naser; Bacaj, Mustafë; Jusufi, Florim
2011-04-01
The main goal of this work was to suggest to authorities concerned a monitoring network on main rivers of Kosovo. We aim to suggest application of WFD (Water Framework Directive) in Kosovo as soon as possible. Our present chemical research could be the first step towards it, giving an opportunity to plan the monitoring network in which pollution locations will be highlighted. In addition to chemical, future ecological studies could be performed. Waters of the rivers Drini i Bardhë, Morava e Binçës, Lepenc and Sitnica, which are of supra-regional interest, are investigated systematically along the river course. Sediments of these rivers were also investigated at the same monitoring points and results have recently been published by us. In this paper we present results of mass concentrations of eco-toxic metals: Cu(II), Pb(II), Cd(II), Zn(II) and Mn(II) in waters of four main rivers of Kosovo, using Anodic Stripping Voltammetry (ASV), Atomic Absorption Spectrophotometry (AAS) and Ultraviolet-Visible (UV-VIS) Spectrometry. Also some physico-chemical parameters are determined: water temperature, electrical conductivity, pH, alkalinity, total hardness and temporary hardness. Results of concentrations of eco-toxic metals in water are compared with concentrations found in sediments at the same locations. Statistical methods are applied to determine anomalous regions Classification of waters at each sampling station of our work was tentatively performed based on metal indicators, using Croatian standards. Our results are showing that concentrations of Zn in all waters are low and pose no risk for living organisms. Exception is water at S5 station, where concentration is above permanent toxic level. Concentrations of Pb and Mn are high at D5 station on Drini i Bardhë River (14 km from boarder to Albania) and at all stations along Sitnica River. Cadmium in high concentrations which is above permanent toxic level is measured in water only at two stations, one (M1) on
A Wavelet Neural Network Hybrid Model for Monthly Ammonia Forecasting in River Water
Directory of Open Access Journals (Sweden)
Yi Wang
2013-06-01
Full Text Available Forecasting water quality is always an effective approach for water environmental management. This study presents a combined Wavelet transform (WA and Artificial Neural Network (ANN model for monthly ammonia nitrogen series prediction in river water. The WA decomposed original time series into different subseries, in which the most significant one was chosen as the training data instead of the original series. Compared to the traditional ANN, the WA-ANN models were found more accurate and reliable. The results of the study indicate that WA could remove the noise of the original datasets and the WA-ANN could help environment decision-maker manage water quality more effective.
On biodiversity in river networks: A trade-off metapopulation model and comparative analysis
Muneepeerakul, R.; Levin, S. A.; Rinaldo, A.; Rodriguez-Iturbe, I.
2007-07-01
A discrete, structured metapopulation model is coupled with the strictly hierarchical competition-colonization trade-off model, in which competitively superior species have lower fecundity rates and thus lower colonizing ability, to study the resulting biodiversity patterns in river networks. These patterns are then compared with those resulting from the neutral dynamics, in which every species has the same fecundity rate and is competitively equivalent at a per capita level. Significant differences exist between riparian biodiversity patterns and those predicted by theories developed for two-dimensional landscapes. We find that dispersal directionality and network structure promote species that produce a large number of propagules at a species level; such species are considered competitively superior in the neutral model and inferior in the trade-off model. As a result, the two key characteristics of riparian systems, dispersal directionality and network structure, lead to lower and higher overall γ diversity in the former and the latter models, respectively. The network structure, through the containment effect due to limited cross-basin dispersal, always leads to higher between-community, β diversity. The spatial distribution of local, α diversity becomes heterogeneous and thus important under directional dispersal and network structure. A higher degree of dividedness results in higher γ diversity for communities obeying both neutral and trade-off models, but the increase is more dramatic in the latter.
Combinatorial fractal Brownian motion model
Institute of Scientific and Technical Information of China (English)
朱炬波; 梁甸农
2000-01-01
To solve the problem of how to determine the non-scaled interval when processing radar clutter using fractal Brownian motion (FBM) model, a concept of combinatorial FBM model is presented. Since the earth (or sea) surface varies diversely with space, a radar clutter contains several fractal structures, which coexist on all scales. Taking the combination of two FBMs into account, via theoretical derivation we establish a combinatorial FBM model and present a method to estimate its fractal parameters. The correctness of the model and the method is proved by simulation experiments and computation of practial data. Furthermore, we obtain the relationship between fractal parameters when processing combinatorial model with a single FBM model. Meanwhile, by theoretical analysis it is concluded that when combinatorial model is observed on different scales, one of the fractal structures is more obvious.
Contour fractal analysis of grains
Guida, Giulia; Casini, Francesca; Viggiani, Giulia MB
2017-06-01
Fractal analysis has been shown to be useful in image processing to characterise the shape and the grey-scale complexity in different applications spanning from electronic to medical engineering (e.g. [1]). Fractal analysis consists of several methods to assign a dimension and other fractal characteristics to a dataset describing geometric objects. Limited studies have been conducted on the application of fractal analysis to the classification of the shape characteristics of soil grains. The main objective of the work described in this paper is to obtain, from the results of systematic fractal analysis of artificial simple shapes, the characterization of the particle morphology at different scales. The long term objective of the research is to link the microscopic features of granular media with the mechanical behaviour observed in the laboratory and in situ.
Dynamic Baysesian state-space model with a neural network for an online river flow prediction
Ham, Jonghwa; Hong, Yoon-Seok
2013-04-01
-space model formulation. The nonlinear Monte Carlo filtering algorithm is based on recursively constructing the posterior probability density (distribution) of the state variable of neural network's weight, with respect to measured data (in our case, river flow), through a random trajectory of the state by entities called 'particles' in the dynamic state-space model formulation. A weight, which is the probability of the trajectory of the state, is assigned to each particle by a Bayesian correction term based on measurement. The algorithms differ in the way that the swarm of particles evolves and adapts to incoming online measurement data. In order to demonstrate the efficiency and usefulness of the proposed MLP-SMC, a practical application of hydrological modeling is carried out to predict the river flow sequentially in advance on the arrival of each new item of river flow data at intervals of 10 minutes. The performance of the proposed MLP-SMC is compared with the performance of a multi-layer perceptron (MLP) model trained using the back-propagation learning algorithm (MLP-BP) in which a batch off-line learning algorithm is implemented. The results show that the proposed MLP-SMC shows superiority in terms of model accuracy and computational cost compared with MLP-BP. The sequential Monte Carlo learning algorithm implemented in MLP-SMC is shown to have less sensitivity to noisy and sparsely distributed data compared to the batch off-line learning algorithm used in MLP-BP.
Vialidad, conectividad y fractales
Pineda Paz, Eduardo; Guerrero Torrenegra, Alejandro
2014-01-01
La morfología urbana es posible analizarla mediante ecuaciones no lineales que aparentemente reflejan el comportamiento del hombre. La teoría del caos, la incertidumbre y los fractales, aportan nuevas posibilidades al planificador urbano. El estudio es descriptivo y analítico, siguiendo pautas fenomenológicas, combinando teoría y práctica urbanística, con matemática sencilla. La parroquia Olegario Villalobos de Maracaibo es el caso de estudio. La investigación abordó la dimensión ...
Extraction of Characteristics of River Networks in Qinhuai River Basin%秦淮河流域河网特征提取
Institute of Scientific and Technical Information of China (English)
李崇洁; 芮菡艺
2012-01-01
On the basis of terrain data in the Qinhuai River Basin, the methods and procedures of river networks extraction with Arc Hydro Tools are analyzed in this paper. The extraction of stream networks with river vector data is in contrast to the stream extraction without reference data. Based on digital elevation model (DEM) datai the improved stream networks extraction method with the ArcGIS Hydrology module is proposed. The results show that the proposed method is effective to extract the characteristics of the Qinhuai River Basint and the extracted Basin boundary is basically consistent with the actual basin boundary.%以秦淮河流域为例,阐述了Arc Hydro Tools提取流域河网的步骤和方法,分析了有(无)河网辅助条件下提取数字河网的效果,并探讨了利用Arc Hydro Tools提取河网水系的特征,提出了基于ArcGIS Hydrolo gy模块直接处理DEM数据的改进方法.结果表明,该方法有效提取了研究区域内的河网特征,与实际流域边界基本吻合.
Improving peak flow estimates in artificial neural network river flow models
Sudheer, K. P.; Nayak, P. C.; Ramasastri, K. S.
2003-02-01
In this paper, the concern of accuracy in peak estimation by the artificial neural network (ANN) river flow models is discussed and a suitable statistical procedure to get better estimates from these models is presented. The possible cause for underestimation of peak flow values has been attributed to the local variations in the function being mapped due to varying skewness in the data series, and theoretical considerations of the network functioning confirm this. It is envisaged that an appropriate data transformation will reduce the local variations in the function being mapped, and thus any ANN model built on the transformed series should perform better. This heuristic is illustrated and confirmed by many case studies and the results suggest that the model performance is significantly improved by data transformation. The model built on transformed data outperforms the model built on raw data in terms of various statistical performance indices. The peak estimates are improved significantly by data transformation.
Modeling River Networks in the Continental Shelf during Sea Level Cycles
Fagherazzi, S.; Wiberg, P. L.
2003-12-01
Several processes influence the development of fluvial networks in the continental shelf during sea level low stands. In order to understand the specific role of each process and quantify its influence on channel formation and incision, the Detachment Limited Model (DeLiM) (Howard, 1994) has been applied to several shelf configurations and with different sea-level curves. The computer model incorporates deltaic deposition on the continental shelf as well as sea-level oscillations and is parameterized with Virginia coastal plain data. Simulations show that the major factor controlling incision and channel development is the tendency of streams to reach an equilibrium (graded) configuration. If, for a given river discharge and shelf slope, the sediment load is less than that required to be at grade, channel incision will occur in the exposed shelf until the river long profile is in equilibrium with the current sea level (base level). The geometry and thickness of sediments deposited in deltas and estuaries have a minor influence on the total channel incision, but are of fundamental importance for the spatial development of the channel network. Model results show that the detailed structure of sea level oscillations is important for sediment redistribution and channel changes. Conceptual models that consider a mere succession of sea level high stands and low stands are oversimplified and miss the complex response of the system to gradual sea level oscillations. The initial shelf topography strongly characterizes the future network development. During the simulations the drainage network is initially strongly fragmented, but gradually becomes integrated through depression infilling and dissection of steep scarps. Finally the role of coastal processes is of crucial importance for sediment redistribution and shelf topography modification during sea-level oscillations.
A Model of Biocomplexity in River Networks - Part II: Tenets and Predictions
Delong, M. D.; Thorp, J. H.; Thoms, M. C.
2005-05-01
We are proposing a model of lotic biocomplexity encompassing spatiotemporal scales from headwaters to large rivers and from main channels to floodplains. Part I of our presentation in the symposium discusses the general theory and predicted changes along longitudinal gradients in the river network. In Part II, we use the foundation of this theory to make predictions for the ecological behavior of the river ecosystem. These predictions are designed to stimulate research tests of these hypotheses and to obtain data allowing the continuing refinement of the overall model. Fourteen principles or model tenets are included which describe the functioning of epigean portions of lotic ecosystems on ecological time scales; they are focused more on the riverscape than the entire riverine landscape. These 14 tenets predict how patterns of individual species distributions, community regulation, lotic ecosystem processes, and floodplain interactions will vary over spatiotemporal scales, especially as they relate to the functional process zones formed by hydrogeomorphic patches. We make no claim to originality for all these tenets. Some of these ideas are well supported in the scientific literature, others may be acceptable to the scientific community but currently lack empirical support, and some may be very speculative and possibly controversial.
A regional neural network model for predicting mean daily river water temperature
Wagner, Tyler; DeWeber, Jefferson Tyrell
2014-01-01
Water temperature is a fundamental property of river habitat and often a key aspect of river resource management, but measurements to characterize thermal regimes are not available for most streams and rivers. As such, we developed an artificial neural network (ANN) ensemble model to predict mean daily water temperature in 197,402 individual stream reaches during the warm season (May–October) throughout the native range of brook trout Salvelinus fontinalis in the eastern U.S. We compared four models with different groups of predictors to determine how well water temperature could be predicted by climatic, landform, and land cover attributes, and used the median prediction from an ensemble of 100 ANNs as our final prediction for each model. The final model included air temperature, landform attributes and forested land cover and predicted mean daily water temperatures with moderate accuracy as determined by root mean squared error (RMSE) at 886 training sites with data from 1980 to 2009 (RMSE = 1.91 °C). Based on validation at 96 sites (RMSE = 1.82) and separately for data from 2010 (RMSE = 1.93), a year with relatively warmer conditions, the model was able to generalize to new stream reaches and years. The most important predictors were mean daily air temperature, prior 7 day mean air temperature, and network catchment area according to sensitivity analyses. Forest land cover at both riparian and catchment extents had relatively weak but clear negative effects. Predicted daily water temperature averaged for the month of July matched expected spatial trends with cooler temperatures in headwaters and at higher elevations and latitudes. Our ANN ensemble is unique in predicting daily temperatures throughout a large region, while other regional efforts have predicted at relatively coarse time steps. The model may prove a useful tool for predicting water temperatures in sampled and unsampled rivers under current conditions and future projections of climate
Wicks, Keith R
1991-01-01
Addressed to all readers with an interest in fractals, hyperspaces, fixed-point theory, tilings and nonstandard analysis, this book presents its subject in an original and accessible way complete with many figures. The first part of the book develops certain hyperspace theory concerning the Hausdorff metric and the Vietoris topology, as a foundation for what follows on self-similarity and fractality. A major feature is that nonstandard analysis is used to obtain new proofs of some known results much more slickly than before. The theory of J.E. Hutchinson's invariant sets (sets composed of smaller images of themselves) is developed, with a study of when such a set is tiled by its images and a classification of many invariant sets as either regular or residual. The last and most original part of the book introduces the notion of a "view" as part of a framework for studying the structure of sets within a given space. This leads to new, elegant concepts (defined purely topologically) of self-similarity and fracta...
Directory of Open Access Journals (Sweden)
Edwin Kimutai Kanda
2016-11-01
Full Text Available River Nzoia in Kenya, due to its role in transporting industrial and municipal wastes in addition to agricultural runoff to Lake Victoria, is vulnerable to pollution. Dissolved oxygen is one of the most important indicators of water pollution. Artificial neural network (ANN has gained popularity in water quality forecasting. This study aimed at assessing the ability of ANN to predict dissolved oxygen using four input variables of temperature, turbidity, pH and electrical conductivity. Multilayer perceptron network architecture was used in this study. The data consisted of 113 monthly values for the input variables and output variable from 2009–2013 which were split into training and testing datasets. The results obtained during training and testing were satisfactory with R2 varying from 0.79 to 0.94 and RMSE values ranging from 0.34 to 0.64 mg/l which imply that ANN can be used as a monitoring tool in the prediction of dissolved oxygen for River Nzoia considering the non-correlational relationship of the input and output variables. The dissolved oxygen values follow seasonal trend with low values during dry periods.
Network response to internal and external perturbations in large sand-bed braided rivers
Schuurman, F.; Kleinhans, M. G.; Middelkoop, H.
2015-03-01
The intrinsic instability of bars, bifurcations and branches in large braided rivers is a challenge to understand and predict. Even more, the reach-scale effect of human-induced perturbations on the braided channel network is still unresolved. In this study, we used a physics-based model to simulate the hydromorphodynamics in a large braided river and applied different types of perturbations. We analyzed the propagation of the perturbations through the braided channel network. The results showed that the perturbations initiate an instability that propagates in downstream direction by means of bifurcation instability. It alters and rotates the approaching flow of the bifurcations. The propagation celerity is in the same order of magnitude as the theoretical sand wave propagation rate. The adjustments of the bifurcations also change bar migration and reshape, with a feedback to the upstream bifurcation and alteration of the approaching flow to the downstream bifurcation. This way, the morphological effect of a perturbation amplifies in downstream direction. Thus, the interplay of bifurcation instability and asymmetrical reshaping of bars was found to be essential for propagation of the effects of a perturbation. The study also demonstrated that the large-scale bar statistics are hardly affected.
Integrating Neural Networks and Conceptual Modelling for Flood Forecasting on the Tiber River
Napolitano, G.; See, L.; Savi, F.
2009-04-01
The Tiber River has a catchment area of approximately 17,000 km2. The river crosses 6 regions and is about 300 km in length. This study is focused on the bottom part of the catchment, between Rome and the Corbara dam, which is located approximately 150 km north of Rome, with a reservoir active storage of 165 hm3. The area from Corbara dam (11,000 km2) can be subdivided into 37 ungauged and 3 gauged sub-basins. At the bottom of the basin is the city of Rome, which is at risk from flooding when extreme events with a return period of about 200 years occur. Both conceptual modeling and Artificial Neural Networks (ANNS) have already been applied individually to forecasting historical floods for the city of Rome. The results of both models are promising but each one has different strengths. This study considers how hybrid techniques can be applied to the integration of both conceptual and ANN models to improve their performance further. Integration of the individual models using different techniques from the field of data fusion is investigated. Models are developed to predict hourly water levels at Ripetta gauging station in Rome for a lead time of 12 and 18 hours. Model performance is assessed using a series of absolute and relative performance measures as well as a visual inspection of the hydrograph. Keywords: real-time forecasting, flooding, rainfall-runoff modelling, Artificial Neural Networks.
River flow forecasting: use of phase-space reconstruction and artificial neural networks approaches
Sivakumar, B.; Jayawardena, A. W.; Fernando, T. M. K. G.
2002-08-01
The use of two non-linear black-box approaches, phase-space reconstruction (PSR) and artificial neural networks (ANN), for forecasting river flow dynamics is studied and a comparison of their performances is made. This is done by attempting 1-day and 7-day ahead forecasts of the daily river flow from the Nakhon Sawan station at the Chao Phraya River basin in Thailand. The results indicate a reasonably good performance of both approaches for both 1-day and 7-day ahead forecasts. However, the performance of the PSR approach is found to be consistently better than that of ANN. One reason for this could be that in the PSR approach the flow series in the phase-space is represented step by step in local neighborhoods, rather than a global approximation as is done in ANN. Another reason could be the use of the multi-layer perceptron (MLP) in ANN, since MLPs may not be most appropriate for forecasting at longer lead times. The selection of training set for the ANN may also contribute to such results. A comparison of the optimal number of variables for capturing the flow dynamics, as identified by the two approaches, indicates a large discrepancy in the case of 7-day ahead forecasts (1 and 7 variables, respectively), though for 1-day ahead forecasts it is found to be consistent (3 variables). A possible explanation for this could be the influence of noise in the data, an observation also made from the 1-day ahead forecast results using the PSR approach. The present results lead to observation on: (1) the use of other neural networks for runoff forecasting, particularly at longer lead times; (2) the influence of training set used in the ANN; and (3) the effect of noise on forecast accuracy, particularly in the PSR approach.
Mount, N. J.; Dawson, C. W.; Abrahart, R. J.
2013-01-01
In this paper we address the difficult problem of gaining an internal, mechanistic understanding of a neural network river forecasting (NNRF) model. Neural network models in hydrology have long been criticised for their black-box character, which prohibits adequate understanding of their modelling mechanisms and has limited their broad acceptance by hydrologists. In response, we here present a new, data-driven mechanistic modelling (DDMM) framework that incorporates an evaluation of the legitimacy of a neural network's internal modelling mechanism as a core element in the model development process. The framework is exemplified for two NNRF modelling scenarios, and uses a novel adaptation of first order, partial derivate, relative sensitivity analysis methods as the means by which each model's mechanistic legitimacy is explored. The results demonstrate the limitations of standard, goodness-of-fit validation procedures applied by NNRF modellers, by highlighting how the internal mechanisms of complex models that produce the best fit scores can have much lower legitimacy than simpler counterparts whose scores are only slightly inferior. The study emphasises the urgent need for better mechanistic understanding of neural network-based hydrological models and the further development of methods for elucidating their mechanisms.
Relative importance of multiple factors on terrestrial loading of DOC to Arctic river networks
Energy Technology Data Exchange (ETDEWEB)
Kicklighter, David W. [Ecosystem Center, The; Hayes, Daniel J [ORNL; Mcclelland, James W [University of Texas; Peterson, Bruce [Marine Biological Laboratory; Mcguire, David [University of Alaska; Melillo, Jerry [Marine Biological Laboratory
2014-01-01
Terrestrial carbon dynamics influence the contribution of dissolved organic carbon (DOC) to river networks in addition to controlling carbon fluxes between the land surface and the atmosphere. In this study, we use a biogeochemical process model to simulate the lateral transfer of DOC from land to the Arctic Ocean via riverine transport. We estimate that the pan-arctic watershed has contributed, on average, 32 Tg C/yr of DOC to the Arctic Ocean over the 20th century with most coming from the extensive area of boreal deciduous needle-leaved forests and forested wetlands in Eurasian watersheds. We also estimate that the rate of terrestrial DOC loading has been increasing by 0.037 Tg C/yr2 over the 20th century primarily as a result of increases in air temperatures and precipitation. These increases have been partially compensated by decreases in terrestrial DOC loading caused by wildfires. Other environmental factors (CO2 fertilization, ozone pollution, atmospheric nitrogen deposition, timber harvest, agriculture) are estimated to have relatively small effects on terrestrial DOC loading to arctic rivers. The effects of the various environmental factors on terrestrial carbon dynamics have both compensated and enhanced concurrent effects on hydrology to influence terrestrial DOC loading. Future increases in riverine DOC concentrations and export may occur from warming-induced increases in terrestrial DOC production associated with enhanced microbial metabolism and the exposure of additional organic matter from permafrost degradation along with decreases in water yield associated with warming-induced increases in evapotranspiration. Improvements in simulating terrestrial DOC loading to pan-arctic rivers in the future will require better information on the spatial distribution of precipitation and its temporal trends, carbon dynamics of larch-dominated ecosystems in eastern Siberia, and the role of industrial organic effluents on carbon budgets of rivers in western
Bellay, Sybelle; Oliveira, Edson F de; Almeida-Neto, Mário; Abdallah, Vanessa D; Azevedo, Rodney K de; Takemoto, Ricardo M; Luque, José L
2015-07-01
The use of the complex network approach to study host-parasite interactions has helped to improve the understanding of the structure and dynamics of ecological communities. In this study, this network approach is applied to evaluate the patterns of organisation and structure of interactions in a fish-parasite network of a neotropical Atlantic Forest river. The network includes 20 fish species and 73 metazoan parasite species collected from the Guandu River, Rio de Janeiro State, Brazil. According to the usual measures in studies of networks, the organisation of the network was evaluated using measures of host susceptibility, parasite dependence, interaction asymmetry, species strength and complementary specialisation of each species as well as the network. The network structure was evaluated using connectance, nestedness and modularity measures. Host susceptibility typically presented low values, whereas parasite dependence was high. The asymmetry and species strength were correlated with host taxonomy but not with parasite taxonomy. Differences among parasite taxonomic groups in the complementary specialisation of each species on hosts were also observed. However, the complementary specialisation and species strength values were not correlated. The network had a high complementary specialisation, low connectance and nestedness, and high modularity, thus indicating variability in the roles of species in the network organisation and the expected presence of many specialist species.
Fractal analysis of sulphidic mineral
Directory of Open Access Journals (Sweden)
Miklúová Viera
2002-03-01
Full Text Available In this paper, the application of fractal theory in the characterization of fragmented surfaces, as well as the mass-size distributions are discussed. The investigated mineral-chalcopyrite of Slovak provenience is characterised after particle size reduction processes-crushing and grinding. The problem how the different size reduction methods influence the surface irregularities of obtained particles is solved. Mandelbrot (1983, introducing the fractal geometry, offered a new way of characterization of surface irregularities by the fractal dimension. The determination of the surface fractal dimension DS consists in measuring the specific surface by the BET method in several fractions into which the comminuted chalcopyrite is sieved. This investigation shows that the specific surface of individual fractions were higher for the crushed sample than for the short-term (3 min ground sample. The surface fractal dimension can give an information about the adsorption sites accessible to molecules of nitrogen and according to this, the value of the fractal dimension is higher for crushed sample.The effect of comminution processes on the mass distribution of particles crushed and ground in air as well as in polar liquids is also discussed. The estimation of fractal dimensions of particles mass distribution is done on the assumption that the particle size distribution is described by the power-law (1. The value of fractal dimension for the mass distribution in the crushed sample is lower than in the sample ground in air, because it is influenced by the energy required for comminution.The sample of chalcopyrite was ground (10min in ethanol and i-butanol [which according to Ikazaki (1991] are characterized by the parameter µ /V, where µ is its dipole moment and V is the molecular volume. The values of µ /V for the used polar liquids are of the same order. That is why the expressive differences in particle size distributions as well as in the values of
Brown, B.L.; Swan, C.M.; Auerbach, D.A.; Campbell, Grant E.H.; Hitt, N.P.; Maloney, K.O.; Patrick, C.
2011-01-01
Explaining the mechanisms underlying patterns of species diversity and composition in riverine networks is challenging. Historically, community ecologists have conceived of communities as largely isolated entities and have focused on local environmental factors and interspecific interactions as the major forces determining species composition. However, stream ecologists have long embraced a multiscale approach to studying riverine ecosystems and have studied both local factors and larger-scale regional factors, such as dispersal and disturbance. River networks exhibit a dendritic spatial structure that can constrain aquatic organisms when their dispersal is influenced by or confined to the river network. We contend that the principles of metacommunity theory would help stream ecologists to understand how the complex spatial structure of river networks mediates the relative influences of local and regional control on species composition. From a basic ecological perspective, the concept is attractive because new evidence suggests that the importance of regional processes (dispersal) depends on spatial structure of habitat and on connection to the regional species pool. The role of local factors relative to regional factors will vary with spatial position in a river network. From an applied perspective, the long-standing view in ecology that local community composition is an indicator of habitat quality may not be uniformly applicable across a river network, but the strength of such bioassessment approaches probably will depend on spatial position in the network. The principles of metacommunity theory are broadly applicable across taxa and systems but seem of particular consequence to stream ecology given the unique spatial structure of riverine systems. By explicitly embracing processes at multiple spatial scales, metacommunity theory provides a foundation on which to build a richer understanding of stream communities.
Institute of Scientific and Technical Information of China (English)
WANG Chao; WANG Pei-fang
2005-01-01
Based on the analysis of dilution capacity and self-purification capacity of water body, the dilution, dispersion, entrapping and purification principles of pollutants in river system at river network area were discussed in this paper. Also, the one and two dimensional models of water quantity needed for improving water environment quality and pollutant concentrations were developed for rivers and lakes respectively. The calculation method for the quantity of water transfer was given and the forecasting evaluation of the effect of water transfer was carried out. It was took the project, water transfer from Yangtze River to improve the water quality of rivers in Zhangjiagang City, as an example, and changing principles of water quantity and quality were observed in rivers and lakes through site water transfer experiments. The theory of estimating parameters in inverse problem was used to determine parameters in water quantity and quality models. The water quantity and quality coupled models in river system were applied to calculate the minimal water transfer quantity. The theoretical and technical support for the improvement of water environmental quality in Zhangjiagang City and the project "water transfer form Yangtze River to Taihu Lake" were provided.
Fractal and Multifractal Time Series
Kantelhardt, Jan W
2008-01-01
Data series generated by complex systems exhibit fluctuations on many time scales and/or broad distributions of the values. In both equilibrium and non-equilibrium situations, the natural fluctuations are often found to follow a scaling relation over several orders of magnitude, allowing for a characterisation of the data and the generating complex system by fractal (or multifractal) scaling exponents. In addition, fractal and multifractal approaches can be used for modelling time series and deriving predictions regarding extreme events. This review article describes and exemplifies several methods originating from Statistical Physics and Applied Mathematics, which have been used for fractal and multifractal time series analysis.
Exterior dimension of fat fractals
Grebogi, C.; Mcdonald, S. W.; Ott, E.; Yorke, J. A.
1985-01-01
Geometric scaling properties of fat fractal sets (fractals with finite volume) are discussed and characterized via the introduction of a new dimension-like quantity which is called the exterior dimension. In addition, it is shown that the exterior dimension is related to the 'uncertainty exponent' previously used in studies of fractal basin boundaries, and it is shown how this connection can be exploited to determine the exterior dimension. Three illustrative applications are described, two in nonlinear dynamics and one dealing with blood flow in the body. Possible relevance to porous materials and ballistic driven aggregation is also noted.
Thermal collapse of snowflake fractals
Gallo, T.; Jurjiu, A.; Biscarini, F.; Volta, A.; Zerbetto, F.
2012-08-01
Snowflakes are thermodynamically unstable structures that would ultimately become ice balls. To investigate their dynamics, we mapped atomistic molecular dynamics simulations of small ice crystals - built as filled von Koch fractals - onto a discrete-time random walk model. Then the walkers explored the thermal evolution of high fractal generations. The in silico experiments showed that the evolution is not entirely random. The flakes step down one fractal generation before forfeiting their architecture. The effect may be used to trace the thermal history of snow.
Moghilevsky, Débora Estela
2011-01-01
A lo largo de los últimos años del siglo veinte se ha desarrollado la teoría de la complejidad. Este modelo relaciona las ciencias duras tales como la matemática, la teoría del caos, la física cuántica y la geometría fractal con las llamadas seudo ciencias. Dentro de este contexto podemos definir la Psicología Fractal como la ciencia que estudia los aspectos psíquicos como dinámicamente fractales.
On the fractal properties microaccelerations
Sedelnikov, A V
2012-01-01
In this paper the fractal property of the internal environment of space laboratory microaccelerations that occur. Changing the size of the space lab leads to the fact that the dependence of microaccelerations from time to time has the property similar to the self-affinity of fractal functions. With the help of microaccelerations, based on the model of the real part of the fractal Weierstrass-Mandelbrot function is proposed to form the inertial-mass characteristics of laboratory space with a given level of microaccelerations.
Study of desorption in a vapor dominated reservoir with fractal geometry
Energy Technology Data Exchange (ETDEWEB)
Tudor, Monica; Horne, Roland N.; Hewett, Thomas A.
1995-01-26
This paper is an attempt to model well decline in a vapor dominated reservoir with fractal geometry. The fractal network of fractures is treated as a continuum with characteristic anomalous diffusion of pressure. A numerical solver is used to obtain the solution of the partial differential equation including adsorption in the fractal storage space. The decline of the reservoir is found to obey the empirical hyperbolic type relation when adsorption is not present. Desorption does not change the signature of the flow rate decline but shifts it on the time/flow rate axis. Only three out of six model parameters can be estimated from field data, due to the linear correlation between parameters. An application to real well data from The Geysers field is presented together with the estimated reservoir, fractal space and adsorption parameters. Desorption dominated flow is still a questionable approximation for flow in fractal objects.
Islam, M. S.; Bonner, J. S.; Fuller, C.; Kirkey, W.; Ojo, T.
2011-12-01
The Hudson River watershed spans 34,700 km2 predominantly in New York State, including agricultural, wilderness, and urban areas. The Hudson River supports many activities including shipping, supplies water for municipal, commercial, and agricultural uses, and is an important recreational resource. As the population increases within this watershed, so does the anthropogenic impact on this natural system. To address the impacts of anthropogenic and natural activities on this ecosystem, the River and Estuary Observatory Network (REON) is being developed through a joint venture between the Beacon Institute, Clarkson University, General Electric Inc. and IBM Inc. to monitor New York's Hudson and Mohawk Rivers in real-time. REON uses four sensor platform types with multiple nodes within the network to capture environmentally relevant episodic events. Sensor platform types include: 1) fixed robotic vertical profiler (FRVP); 2) mobile robotic undulating platform (MRUP); 3) fixed acoustic Doppler current profiler (FADCP) and 4) Autonomous Underwater Vehicle (AUV). The FRVP periodically generates a vertical profile with respect to water temperature, salinity, dissolved oxygen, particle concentration and size distribution, and fluorescence. The MRUP utilizes an undulating tow-body tethered behind a research vessel to measure the same set of water parameters as the FRVP, but does so 'synchronically' over a highly-resolved spatial regime. The fixed ADCP provides continuous water current profiles. The AUV maps four-dimensional (time, latitude, longitude, depth) variation of water quality, water currents and bathymetry along a pre-determined transect route. REON data can be used to identify episodic events, both anthropogenic and natural, that impact the Hudson River. For example, a strong heat signature associated with cooling water discharge from the Indian Point nuclear power plant was detected with the MRUP. The FRVP monitoring platform at Beacon, NY, located in the
Safavi, Hamid R; Malek Ahmadi, Kian
2015-01-01
Although drought impacts on water quantity are widely recognized, the impacts on water quality are less known. The Zayandehrud River basin in the west-central part of Iran plateau witnessed an increased contamination during the recent droughts and low flows. The river has been receiving wastewater and effluents from the villages, a number of small and large industries, and irrigation drainage systems along its course. What makes the situation even worse is the drought period the river basin has been going through over the last decade. Therefore, a river quality management model is required to include the adverse effects of industrial development in the region and the destructive effects of droughts which affect the river's water quality and its surrounding environment. Developing such a model naturally presupposes investigations into pollution effects in terms of both quality and quantity to be used in such management tools as mathematical models to predict the water quality of the river and to prevent pollution escalation in the environment. The present study aims to investigate electrical conductivity of the Zayandehrud River as a water quality parameter and to evaluate the effect of this parameter under drought conditions. For this purpose, artificial neural networks are used as a modeling tool to derive the relationship between electrical conductivity and the hydrological parameters of the Zayandehrud River. The models used in this research include multi-layer perceptron and radial basis function. Finally, these two models are compared in terms of their performance using the time series of electrical conductivity at eight monitoring-hydrometric stations during drought periods between the years 1997-2012. Results show that artificial neural networks can be used for modeling the relationship between electrical conductivity and hydrological parameters under drought conditions. It is further shown that radial basis function works better for the upstream stretches
Fractal structure and fractal dimension determination at nanometer scale
Institute of Scientific and Technical Information of China (English)
张跃; 李启楷; 褚武扬; 王琛; 白春礼
1999-01-01
Three-dimensional fractures of different fractal dimensions have been constructed with successive random addition algorithm, the applicability of various dimension determination methods at nanometer scale has been studied. As to the metallic fractures, owing to the limited number of slit islands in a slit plane or limited datum number at nanometer scale, it is difficult to use the area-perimeter method or power spectrum method to determine the fractal dimension. Simulation indicates that box-counting method can be used to determine the fractal dimension at nanometer scale. The dimensions of fractures of valve steel 5Cr21Mn9Ni4N have been determined with STM. Results confirmed that fractal dimension varies with direction at nanometer scale. Our study revealed that, as to theoretical profiles, the dependence of fractal dimension with direction is simply owing to the limited data set number, i.e. the effect of boundaries. However, the dependence of fractal dimension with direction at nanometer scale in rea
Comparing M5 Model Trees and Neural Networks for River Level Forecasting
Khan, S.; See, L.
2005-12-01
Artificial neural networks (ANNs) have been the subject of much research activity in hydrological modelling over the last decade yet this represents only one data-driven modelling approach from among a very rich set. M5 model trees are an example of a technique that has had little application in the hydrological domain yet the results are promising (Solomatine and Xue, 2004). They are a machine learning approach that combines regression trees and classification. The input space is partitioned into subsets based on entropy measures, and regression equations are then fit to these subsets. The advantages over ANNs are (a) their ability to provide knowledge in the form of a decision tree and (b) much faster training times. This has important implications for operational use as they are not black box models. In this study ANNs, M5 model trees and time series analysis have been used to develop models to predict river levels at a gauging station in the River Ouse catchment in Northern England. Two lead times have been used: t+6 and t+24 hours. The input data consisted of historical levels at the gauging stations, upstream level data and rainfall from five rain gauges across the catchment, determined by correlation with the output. The results of the study showed that the ANNs outperformed both the M5 model trees and time series approaches when considering global goodness-of-fit measures such as root mean squared error and coefficient of efficiency. However, the difference in performance between the ANNs and M5 model trees was not large, e.g. 1 percent difference in coefficient of efficiency for t+6 hours. When considering the longer lead time of t+24 hours, the performance of the ANNs and M5 model trees almost converged. The M5 model tree, however, also provides the rules of operation. The first partition for both the t+6 and t+24 hour models was determined by the value of the river level at one of the upstream stations. The individual regression equations associated with
DEFF Research Database (Denmark)
Malureanu, Radu; Jepsen, Peter Uhd; Xiao, S.
2010-01-01
The concept of metamaterials (MTMs) is acknowledged for providing new horizons for controlling electromagnetic radiations thus their use in frequency ranges otherwise difficult to manage (e.g. THz radiation) broadens our possibility to better understand our world as well as opens the path for new...... frequency range as well as a clear differentiation between one polarisation and another. Based on theoretical predictions we fabricated and measured a fractal based THz metamaterial that shows more than 60% field transmission at around 1THz for TE polarized light while the TM waves have almost 80% field...... wavelength of THz radiation, the resolution requirements for fabrication of metamaterials are within the optical lithography range. However, the high aspect ratio of such structures as well as the substrate thickness pose challenges in the fabrication process. The measurements were made using terahertz time...
Eliazar, Iddo; Klafter, Joseph
2008-09-01
The Central Limit Theorem (CLT) and Extreme Value Theory (EVT) study, respectively, the stochastic limit-laws of sums and maxima of sequences of independent and identically distributed (i.i.d.) random variables via an affine scaling scheme. In this research we study the stochastic limit-laws of populations of i.i.d. random variables via nonlinear scaling schemes. The stochastic population-limits obtained are fractal Poisson processes which are statistically self-similar with respect to the scaling scheme applied, and which are characterized by two elemental structures: (i) a universal power-law structure common to all limits, and independent of the scaling scheme applied; (ii) a specific structure contingent on the scaling scheme applied. The sum-projection and the maximum-projection of the population-limits obtained are generalizations of the classic CLT and EVT results - extending them from affine to general nonlinear scaling schemes.
Diophantine approximations on fractals
Einsiedler, Manfred; Shapira, Uri
2009-01-01
We exploit dynamical properties of diagonal actions to derive results in Diophantine approximations. In particular, we prove that the continued fraction expansion of almost any point on the middle third Cantor set (with respect to the natural measure) contains all finite patterns (hence is well approximable). Similarly, we show that for a variety of fractals in [0,1]^2, possessing some symmetry, almost any point is not Dirichlet improvable (hence is well approximable) and has property C (after Cassels). We then settle by similar methods a conjecture of M. Boshernitzan saying that there are no irrational numbers x in the unit interval such that the continued fraction expansions of {nx mod1 : n is a natural number} are uniformly eventually bounded.
Investigation of H-bonded media by means of Raman scattering in terms of the fractal formalism
Maksymov, A. O.; Yakunov, A. V.; Bily, M. M.
2009-08-01
The structure of associated liquids is proposed to be described in terms of the fractal conception developed for amorphous media. The low-frequency region of Raman scattering spectrum for such liquids is shown to reflect fractal features of these media. Binary H-bonded solutions are taken to gain controlled modifications of the fractal parameters and at the same time to avoid dealing with a number of unknown variables. In particular the glycerol-water fractal parameter at certain concentration reflects the competition between different H-bond networks. This concentration corresponds to the density anomaly 40% concentration.
Yu, Zhongjie; Deng, Huanguang; Wang, Dongqi; Ye, Mingwu; Tan, Yongjie; Li, Yangjie; Chen, Zhenlou; Xu, Shiyuan
2013-10-01
Global nitrogen (N) enrichment has resulted in increased nitrous oxide (N(2)O) emission that greatly contributes to climate change and stratospheric ozone destruction, but little is known about the N(2)O emissions from urban river networks receiving anthropogenic N inputs. We examined N(2)O saturation and emission in the Shanghai city river network, covering 6300 km(2), over 27 months. The overall mean saturation and emission from 87 locations was 770% and 1.91 mg N(2)O-N m(-2) d(-1), respectively. Nitrous oxide (N(2)O) saturation did not exhibit a clear seasonality, but the temporal pattern was co-regulated by both water temperature and N loadings. Rivers draining through urban and suburban areas receiving more sewage N inputs had higher N(2)O saturation and emission than those in rural areas. Regression analysis indicated that water ammonium (NH(4)(+)) and dissolved oxygen (DO) level had great control on N(2)O production and were better predictors of N(2)O emission in urban watershed. About 0.29 Gg N(2)O-N yr(-1) N(2)O was emitted from the Shanghai river network annually, which was about 131% of IPCC's prediction using default emission values. Given the rapid progress of global urbanization, more study efforts, particularly on nitrification and its N(2)O yielding, are needed to better quantify the role of urban rivers in global riverine N(2)O emission. © 2013 John Wiley & Sons Ltd.
Dević, Gordana; Sakan, Sanja; Đorđević, Dragana
2016-01-01
In this paper, the data for ten water quality variables collected during 2009 at 75 monitoring sites along the river network of Serbia are considered. The results are alarming because 48% of the studied sites were contaminated by Ni, Mn, Pb, As, and nutrients, which are key factors impairing the water quality of the rivers in Serbia. Special attention should be paid to Zn and Cu, listed in the priority toxic pollutants of US EPA for aquatic life protection. The employed Q-model cluster analysis grouped the data into three major pollution zones (low, moderate, and high). Most sites classified as "low pollution zones" (LP) were in the main rivers, whereas those classified as "moderate and high pollution zones" (MP and HP, respectively) were in the large and small tributaries/hydro-system. Principal component analysis/factor analysis (PCA/FA) showed that the dissolved metals and nutrients in the Serbian rivers varied depending on the river, the heterogeneity of the anthropogenic activities in the basins (influenced primarily by industrial wastewater, agricultural activities, and urban runoff pollution), and natural environmental variability, such as geological characteristics. In LP dominated non-point source pollution, such as agricultural and urban runoff, whereas mixed source pollution dominated in the MP and HP zones. These results provide information to be used for developing better pollution control strategies for the river network of Serbia.
Landis, Wayne G; Ayre, Kimberley K; Johns, Annie F; Summers, Heather M; Stinson, Jonah; Harris, Meagan J; Herring, Carlie E; Markiewicz, April J
2017-01-01
We have conducted a regional scale risk assessment using the Bayesian Network Relative Risk Model (BN-RRM) to calculate the ecological risks to the South River and upper Shenandoah River study area. Four biological endpoints (smallmouth bass, white sucker, Belted Kingfisher, and Carolina Wren) and 4 abiotic endpoints (Fishing River Use, Swimming River Use, Boating River Use, and Water Quality Standards) were included in this risk assessment, based on stakeholder input. Although mercury (Hg) contamination was the original impetus for the site being remediated, other chemical and physical stressors were evaluated. There were 3 primary conclusions from the BN-RRM results. First, risk varies according to location, type and quality of habitat, and exposure to stressors within the landscape. The patterns of risk can be evaluated with reasonable certitude. Second, overall risk to abiotic endpoints was greater than overall risk to biotic endpoints. By including both biotic and abiotic endpoints, we are able to compare risk to endpoints that represent a wide range of stakeholder values. Third, whereas Hg reduction is the regulatory priority for the South River, Hg is not the only stressor driving risk to the endpoints. Ecological and habitat stressors contribute risk to the endpoints and should be considered when managing this site. This research provides the foundation for evaluating the risks of multiple stressors of the South River to a variety of endpoints. From this foundation, tools for the evaluation of management options and an adaptive management tools have been forged. Integr Environ Assess Manag 2017;13:85-99. © 2016 SETAC.
Kalyanapu, A. J.; Dullo, T. T.; Thornton, J. C.; Auld, L. A.
2015-12-01
Obion River, is located in the northwestern Tennessee region, and discharges into the Mississippi River. In the past, the river system was largely channelized for agricultural purposes that resulted in increased erosion, loss of wildlife habitat and downstream flood risks. These impacts are now being slowly reversed mainly due to wetland restoration. The river system is characterized by a large network of "loops" around the main channels that hold water either from excess flows or due to flow diversions. Without data on each individual channel, levee, canal, or pond it is not known where the water flows from or to. In some segments along the river, the natural channel has been altered and rerouted by the farmers for their irrigation purposes. Satellite imagery can aid in identifying these features, but its spatial coverage is temporally sparse. All the alterations that have been done to the watershed make it difficult to develop hydraulic models, which could predict flooding and droughts. This is especially true when building one-dimensional (1D) hydraulic models compared to two-dimensional (2D) models, as the former cannot adequately simulate lateral flows in the floodplain and in complex terrains. The objective of this study therefore is to study the performance of 1D and 2D flood models in this complex river system, evaluate the limitations of 1D models and highlight the advantages of 2D models. The study presents the application of HEC-RAS and HEC-2D models developed by the Hydrologic Engineering Center (HEC), a division of the US Army Corps of Engineers. The broader impacts of this study is the development of best practices for developing flood models in channelized river systems and in agricultural watersheds.
Fractal geometry and computer graphics
Sakas, Georgios; Peitgen, Heinz-Otto; Englert, Gabriele
1992-01-01
Fractal geometry has become popular in the last 15 years, its applications can be found in technology, science, or even arts. Fractal methods and formalism are seen today as a general, abstract, but nevertheless practical instrument for the description of nature in a wide sense. But it was Computer Graphics which made possible the increasing popularity of fractals several years ago, and long after their mathematical formulation. The two disciplines are tightly linked. The book contains the scientificcontributions presented in an international workshop in the "Computer Graphics Center" in Darmstadt, Germany. The target of the workshop was to present the wide spectrum of interrelationships and interactions between Fractal Geometry and Computer Graphics. The topics vary from fundamentals and new theoretical results to various applications and systems development. All contributions are original, unpublished papers.The presentations have been discussed in two working groups; the discussion results, together with a...
Configuration entropy of fractal landscapes
National Research Council Canada - National Science Library
Rodríguez‐Iturbe, Ignacio; D'Odorico, Paolo; Rinaldo, Andrea
1998-01-01
.... The spatial arrangement of two‐dimensional images is found to be an effective way to characterize fractal landscapes and the configurational entropy of these arrangements imposes demanding conditions for models attempting to represent these fields.
Anomalous diffusion in fractal globules.
Tamm, M V; Nazarov, L I; Gavrilov, A A; Chertovich, A V
2015-05-01
The fractal globule state is a popular model for describing chromatin packing in eukaryotic nuclei. Here we provide a scaling theory and dissipative particle dynamics computer simulation for the thermal motion of monomers in the fractal globule state. Simulations starting from different entanglement-free initial states show good convergence which provides evidence supporting the existence of a unique metastable fractal globule state. We show monomer motion in this state to be subdiffusive described by ⟨X(2)(t)⟩∼t(αF) with αF close to 0.4. This result is in good agreement with existing experimental data on the chromatin dynamics, which makes an additional argument in support of the fractal globule model of chromatin packing.
Fractals endlessy repeated geometrical figures
Lauwerier, Hans
1991-01-01
Provides a basic mathematical introduction to fractal geometry, the mathematics that lie behind chaos theory. This book attempts to communicate the relatively simple understanding of the subject to an audience with a basic mathematical education.
Establishing a Multi-scale Stream Gaging Network in the Whitewater River Basin, Kansas, USA
Clayton, J.A.; Kean, J.W.
2010-01-01
Investigating the routing of streamflow through a large drainage basin requires the determination of discharge at numerous locations in the channel network. Establishing a dense network of stream gages using conventional methods is both cost-prohibitive and functionally impractical for many research projects. We employ herein a previously tested, fluid-mechanically based model for generating rating curves to establish a stream gaging network in the Whitewater River basin in south-central Kansas. The model was developed for the type of channels typically found in this watershed, meaning that it is designed to handle deep, narrow geomorphically stable channels with irregular planforms, and can model overbank flow over a vegetated floodplain. We applied the model to ten previously ungaged stream reaches in the basin, ranging from third- to sixth-order channels. At each site, detailed field measurements of the channel and floodplain morphology, bed and bank roughness, and vegetation characteristics were used to quantify the roughness for a range of flow stages, from low flow to overbank flooding. Rating curves that relate stage to discharge were developed for all ten sites. Both fieldwork and modeling were completed in less than 2 years during an anomalously dry period in the region, which underscores an advantage of using theoretically based (as opposed to empirically based) discharge estimation techniques. ?? 2010 Springer Science+Business Media B.V.
Use of artificial neural networks for electrical conductivity modeling in Asi River
Ghorbani, Mohammad Ali; Aalami, Mohammad Taghi; Naghipour, Leila
2017-07-01
This study aims to model monthly electrical conductivity (EC) values in the Asi River using artificial neural networks (ANNs) to evaluate water quality conditions using pH, temperature, water discharge, sodium, sum of calcium and magnesium concentrations. The results are compared using multiple linear regression (MLR). Recorded data are available at a gauging site in Antakya, Turkey, for the period from 1984 to 2008. Comparing the modeled values by ANNs with the experimental data indicates that neural network model with seven neurons in hidden layer provides accurate results ( R 2 = 0.968, RMSE = 46.927 µS/cm, MAE = 32.462 µS/cm and MRSE = 0.0029 for the training data and R 2 = 0.965, RMSE = 50.810 µS/cm, MAE = 37.495 µS/cm and MRSE = 0.0024 for the testing data). The Garson method of the connection weights of the network was used to study the relative % contribution of each of the input variables. It was found that the sum of calcium and magnesium concentration and temperature had the most effect on the predicted EC. The results indicate that two proposed models were able to approximate the EC parameter reasonably well; however, the ANN was found to perform better than the MLR model.
Use of artificial neural networks for electrical conductivity modeling in Asi River
Ghorbani, Mohammad Ali; Aalami, Mohammad Taghi; Naghipour, Leila
2015-10-01
This study aims to model monthly electrical conductivity (EC) values in the Asi River using artificial neural networks (ANNs) to evaluate water quality conditions using pH, temperature, water discharge, sodium, sum of calcium and magnesium concentrations. The results are compared using multiple linear regression (MLR). Recorded data are available at a gauging site in Antakya, Turkey, for the period from 1984 to 2008. Comparing the modeled values by ANNs with the experimental data indicates that neural network model with seven neurons in hidden layer provides accurate results (R 2 = 0.968, RMSE = 46.927 µS/cm, MAE = 32.462 µS/cm and MRSE = 0.0029 for the training data and R 2 = 0.965, RMSE = 50.810 µS/cm, MAE = 37.495 µS/cm and MRSE = 0.0024 for the testing data). The Garson method of the connection weights of the network was used to study the relative % contribution of each of the input variables. It was found that the sum of calcium and magnesium concentration and temperature had the most effect on the predicted EC. The results indicate that two proposed models were able to approximate the EC parameter reasonably well; however, the ANN was found to perform better than the MLR model.
Jin, Rui; kang, Jian
2017-04-01
Wireless Sensor Networks are recognized as one of most important near-surface components of GEOSS (Global Earth Observation System of Systems), with flourish development of low-cost, robust and integrated data loggers and sensors. A nested eco-hydrological wireless sensor network (EHWSN) was installed in the up- and middle-reaches of the Heihe River Basin, operated to obtain multi-scale observation of soil moisture, soil temperature and land surface temperature from 2012 till now. The spatial distribution of EHWSN was optimally designed based on the geo-statistical theory, with the aim to capture the spatial variations and temporal dynamics of soil moisture and soil temperature, and to produce ground truth at grid scale for validating the related remote sensing products and model simulation in the heterogeneous land surface. In terms of upscaling research, we have developed a set of method to aggregate multi-point WSN observations to grid scale ( 1km), including regression kriging estimation to utilize multi-resource remote sensing auxiliary information, block kriging with homogeneous measurement errors, and bayesian-based upscaling algorithm that utilizes MODIS-derived apparent thermal inertia. All the EHWSN observation are organized as datasets to be freely published at http://westdc.westgis.ac.cn/hiwater. EHWSN integrates distributed observation nodes to achieve an automated, intelligent and remote-controllable network that provides superior integrated, standardized and automated observation capabilities for hydrological and ecological processes research at the basin scale.
Steady laminar flow of fractal fluids
Balankin, Alexander S.; Mena, Baltasar; Susarrey, Orlando; Samayoa, Didier
2017-02-01
We study laminar flow of a fractal fluid in a cylindrical tube. A flow of the fractal fluid is mapped into a homogeneous flow in a fractional dimensional space with metric induced by the fractal topology. The equations of motion for an incompressible Stokes flow of the Newtonian fractal fluid are derived. It is found that the radial distribution for the velocity in a steady Poiseuille flow of a fractal fluid is governed by the fractal metric of the flow, whereas the pressure distribution along the flow direction depends on the fractal topology of flow, as well as on the fractal metric. The radial distribution of the fractal fluid velocity in a steady Couette flow between two concentric cylinders is also derived.
Visible parts of fractal percolation
Arhosalo, I; Järvenpää, M; Rams, M; Shmerkin, P
2009-01-01
We study dimensional properties of visible parts of fractal percolation in the plane. Provided that the dimension of the fractal percolation is at least 1, we show that, conditioned on non-extinction, almost surely all visible parts from lines are 1-dimensional. Furthermore, almost all of them have positive and finite Hausdorff measure. We also verify analogous results for visible parts from points. These results are motivated by an open problem on the dimensions of visible parts.
Miyamoto, H.; Urano, H.; Sugahara, Y.
2012-12-01
Stream temperature is one of the fundamental variables for water quality in a stream network system. It changes in time and space from sources to the river mouth mainly due to the solar radiation and the river discharge. In this presentation, relative contributions of each component in a thermal energy conservation equation are investigated for stream temperatures in different stream reaches along a stream network in a Japanese river basin. The solution of the thermal energy equation is derived using the method of characteristics and Taylor-series approximation. The river basin studied in this research is Ibo River basin located in the western part of Japan, which has 810 km2 in catchment area and 70 km in main stream length. In Ibo River basin, there have been 27 observation points installed for continuously monitoring the stream temperatures every one hour since April, 2006. The spatial distribution of the observed stream temperatures shows their increasing feature from the upper streams to the river mouth, while their time-series indicate that temporal fluctuations longer than the diurnal fluctuation are formed mainly due to the changes in meteorological and hydrological conditions. The components in the thermal energy equation examined are the short wave radiation, long wave radiation, latent and sensitive heat flux on the stream surface, conductive heat flux from the river bed, longitudinal convection, and lateral heat flux from the base flow. In this presentation, they are investigated in different time scales, i.e., one-day, five-day, and one-month time scales as well as at different locations, i.e., upper, middle, and lower reaches of the river network system. The results show that the short wave radiation has the predominant contribution on stream temperature formation for all time scales and all locations, while the effects of long wave radiation become more important for the longer time scale. On the other hand, the latent and sensible heat fluxes as
Hartwell Welsh; Garth Hodgson
2010-01-01
We investigated the aquatic and riparian herpetofauna in a 789 km² river catchment in northwest California to examine competing theories of biotic community structuring in catchment stream networks. Research in fluvial geomorphology has resulted in multi-scale models of dynamic processes that cyclically create, maintain, and destroy environments in stream...
Rowe, Barbara L.; Wilson, Stephen K.; Yager, Lisa; Wilson, Marcia H.
2013-01-01
The National Park Service (NPS) organized more than 270 parks with important natural resources into 32 ecoregional networks to conduct Inventory and Monitoring (I&M) activities for assessment of natural resources within park units. The Missouri National Recreational River (NRR) is among the 13 parks in the NPS Northern Great Plain Network (NGPN). Park managers and NGPN staff identified surface water resources as a high priority vital sign to monitor in park units. The objectives for the Missouri NRR water quality sampling design are to (1) assess the current status and long-term trends of select water quality parameters; and (2) document trends in streamflow at high-priority stream systems. Due to the large size of the Missouri River main stem, the NGPN water quality design for the Missouri NRR focuses on wadeable tributaries within the park unit. To correlate with the NGPN water quality protocols, monitoring of the Missouri NRR consists of measurement of field core parameters including dissolved oxygen, pH, specific conductance, and temperature; and streamflow. The purpose of this document is to discuss factors examined for selection of water quality monitoring on segments of the Missouri River tributaries within the Missouri NRR.Awareness of the complex history of the Missouri NRR aids in the current understanding and direction for designing a monitoring plan. Historical and current monitoring data from agencies and entities were examined to assess potential NGPN monitoring sites. In addition, the U.S. Environmental Protection Agency 303(d) list was examined for the impaired segments on tributaries to the Missouri River main stem. Because major tributaries integrate water quality effects from complex combinations of land use and environmental settings within contributing areas, a 20-mile buffer of the Missouri NRR was used to establish environmental settings that may impact the water quality of tributaries that feed the Missouri River main stem. For selection of
Ryo, Masahiro; Iwasaki, Yuichi; Yoshimura, Chihiro; Saavedra V., Oliver C.
2015-01-01
Alteration of the spatial variability of natural flow regimes has been less studied than that of the temporal variability, despite its ecological importance for river ecosystems. Here, we aimed to quantify the spatial patterns of flow regime alterations along a river network in the Sagami River, Japan, by estimating river discharge under natural and altered flow conditions. We used a distributed hydrological model, which simulates hydrological processes spatiotemporally, to estimate 20-year daily river discharge along the river network. Then, 33 hydrologic indices (i.e., Indicators of Hydrologic Alteration) were calculated from the simulated discharge to estimate the spatial patterns of their alterations. Some hydrologic indices were relatively well estimated such as the magnitude and timing of maximum flows, monthly median flows, and the frequency of low and high flow pulses. The accuracy was evaluated with correlation analysis (r > 0.4) and the Kolmogorov–Smirnov test (α = 0.05) by comparing these indices calculated from both observed and simulated discharge. The spatial patterns of the flow regime alterations varied depending on the hydrologic indices. For example, both the median flow in August and the frequency of high flow pulses were reduced by the maximum of approximately 70%, but these strongest alterations were detected at different locations (i.e., on the mainstream and the tributary, respectively). These results are likely caused by different operational purposes of multiple water control facilities. The results imply that the evaluation only at discharge gauges is insufficient to capture the alteration of the flow regime. Our findings clearly emphasize the importance of evaluating the spatial pattern of flow regime alteration on a river network where its discharge is affected by multiple water control facilities. PMID:26207997
Directory of Open Access Journals (Sweden)
Masahiro Ryo
Full Text Available Alteration of the spatial variability of natural flow regimes has been less studied than that of the temporal variability, despite its ecological importance for river ecosystems. Here, we aimed to quantify the spatial patterns of flow regime alterations along a river network in the Sagami River, Japan, by estimating river discharge under natural and altered flow conditions. We used a distributed hydrological model, which simulates hydrological processes spatiotemporally, to estimate 20-year daily river discharge along the river network. Then, 33 hydrologic indices (i.e., Indicators of Hydrologic Alteration were calculated from the simulated discharge to estimate the spatial patterns of their alterations. Some hydrologic indices were relatively well estimated such as the magnitude and timing of maximum flows, monthly median flows, and the frequency of low and high flow pulses. The accuracy was evaluated with correlation analysis (r > 0.4 and the Kolmogorov-Smirnov test (α = 0.05 by comparing these indices calculated from both observed and simulated discharge. The spatial patterns of the flow regime alterations varied depending on the hydrologic indices. For example, both the median flow in August and the frequency of high flow pulses were reduced by the maximum of approximately 70%, but these strongest alterations were detected at different locations (i.e., on the mainstream and the tributary, respectively. These results are likely caused by different operational purposes of multiple water control facilities. The results imply that the evaluation only at discharge gauges is insufficient to capture the alteration of the flow regime. Our findings clearly emphasize the importance of evaluating the spatial pattern of flow regime alteration on a river network where its discharge is affected by multiple water control facilities.
Ryo, Masahiro; Iwasaki, Yuichi; Yoshimura, Chihiro; Saavedra V, Oliver C
2015-01-01
Alteration of the spatial variability of natural flow regimes has been less studied than that of the temporal variability, despite its ecological importance for river ecosystems. Here, we aimed to quantify the spatial patterns of flow regime alterations along a river network in the Sagami River, Japan, by estimating river discharge under natural and altered flow conditions. We used a distributed hydrological model, which simulates hydrological processes spatiotemporally, to estimate 20-year daily river discharge along the river network. Then, 33 hydrologic indices (i.e., Indicators of Hydrologic Alteration) were calculated from the simulated discharge to estimate the spatial patterns of their alterations. Some hydrologic indices were relatively well estimated such as the magnitude and timing of maximum flows, monthly median flows, and the frequency of low and high flow pulses. The accuracy was evaluated with correlation analysis (r > 0.4) and the Kolmogorov-Smirnov test (α = 0.05) by comparing these indices calculated from both observed and simulated discharge. The spatial patterns of the flow regime alterations varied depending on the hydrologic indices. For example, both the median flow in August and the frequency of high flow pulses were reduced by the maximum of approximately 70%, but these strongest alterations were detected at different locations (i.e., on the mainstream and the tributary, respectively). These results are likely caused by different operational purposes of multiple water control facilities. The results imply that the evaluation only at discharge gauges is insufficient to capture the alteration of the flow regime. Our findings clearly emphasize the importance of evaluating the spatial pattern of flow regime alteration on a river network where its discharge is affected by multiple water control facilities.
Generalizing a nonlinear geophysical flood theory to medium-sized river networks
Gupta, Vijay K.; Mantilla, Ricardo; Troutman, Brent M.; Dawdy, David; Krajewski, Witold F.
2010-01-01
The central hypothesis of a nonlinear geophysical flood theory postulates that, given space-time rainfall intensity for a rainfall-runoff event, solutions of coupled mass and momentum conservation differential equations governing runoff generation and transport in a self-similar river network produce spatial scaling, or a power law, relation between peak discharge and drainage area in the limit of large area. The excellent fit of a power law for the destructive flood event of June 2008 in the 32,400-km2 Iowa River basin over four orders of magnitude variation in drainage areas supports the central hypothesis. The challenge of predicting observed scaling exponent and intercept from physical processes is explained. We show scaling in mean annual peak discharges, and briefly discuss that it is physically connected with scaling in multiple rainfall-runoff events. Scaling in peak discharges would hold in a non-stationary climate due to global warming but its slope and intercept would change.
Cheng, Lv; Li, Xiaofei; Lin, Xianbiao; Hou, Lijun; Liu, Min; Li, Ye; Liu, Sai; Hu, Xiaoting
2016-12-01
Urbanizations have increased the loadings of reactive nitrogen in urban riverine environments. However, limited information about dissimilatory nitrate reduction processes and associated contributions to nitrogen removal is available for urban riverine environments. In this study, sediment slurry experiments were conducted with nitrogen isotope-tracing technique to investigate the potential rates of denitrification, anaerobic ammonium oxidation (anammox) and dissimilatory nitrate reduction to ammonium (DNRA) and their contributions to nitrate reduction in sediments of urban river networks, Shanghai. The potential rates of denitrification, anammox and DNRA measured in the study area ranged from 0.193 to 98.7 nmol N g(-1) h(-1) dry weight (dw), 0.0387-23.7 nmol N g(-1) h(-1) dw and 0-10.3 nmol N g(-1) h(-1) dw, respectively. Denitrification and DNRA rates were higher in summer than in winter, while anammox rates were greater in winter than in summer for most sites. Dissolved oxygen, total organic carbon, nitrate, ammonium, sulfide, Fe(II) and Fe(III) were found to have significant influence on these nitrate reduction processes. Denitrification contributed 11.5-99.5%% to total nitrate reduction, as compared to 0.343-81.6% for anammox and 0-52.3% for DNRA. It is estimated that nitrogen loss of approximately 1.33 × 10(5) t N year(-1) was linked to both denitrification and anammox processes, which accounted for about 20.1% of total inorganic nitrogen transported annually into the urban river networks of Shanghai. Overall, these results show the potential importance of denitrification and anammox in nitrogen removal and provide new insight into the mechanisms of nitrogen cycles in urban riverine environments.
Dynamics of Fractal Cluster Gels with Embedded Active Colloids
Szakasits, Megan E.; Zhang, Wenxuan; Solomon, Michael J.
2017-08-01
We find that embedded active colloids increase the ensemble-averaged mean squared displacement of particles in otherwise passively fluctuating fractal cluster gels. The enhancement in dynamics occurs by a mechanism in which the active colloids contribute to the average dynamics both directly through their own active motion and indirectly through their excitation of neighboring passive colloids in the fractal network. Fractal cluster gels are synthesized by addition of magnesium chloride to an initially stable suspension of 1.0 μ m polystyrene colloids in which a dilute concentration of platinum coated Janus colloids has been dispersed. The Janus colloids are thereby incorporated into the fractal network. We measure the ensemble-averaged mean squared displacement of all colloids in the gel before and after the addition of hydrogen peroxide, a fuel that drives diffusiophoretic motion of the Janus particles. The gel mean squared displacement increases by up to a factor of 3 for an active to passive particle ratio of 1 ∶20 and inputted active energy—defined based on the hydrogen peroxide's effect on colloid swim speed and run length—that is up to 9.5 times thermal energy, on a per particle basis. We model the enhancement in gel particle dynamics as the sum of a direct contribution from the displacement of the Janus particles themselves and an indirect contribution from the strain field that the active colloids induce in the surrounding passive particles.
Fall, C; Hinojosa-Peña, A; Carreño-de-León, M C
2007-02-01
While the 2005 progress report of the United Nations Millennium Development Goals stresses out the need of a dramatic increase in investment to meet the sanitation target in the third world, it is important to anticipate about some parallel negative impacts that may have this optimistic programme (extension of sewer networks without sufficient treatment works). Research was initiated on Lerma River (Mexico), subjected to many rejects disposal, to design a monitoring network and evaluate the impact of wastewaters on its water quality. The discharges was inventorized, geo-positioned with a GPS and mapped, while the physico-chemical characteristics of the river water, its tributaries and main rejects were evaluated. Microtox system was used as an additional screening tool. Along the 60 km of the High Course of Lerma River (HCLR), 51 discharges, with a diameter or width larger than 0.3 m (including 7 small tributaries) were identified. Based on the inventory, a monitoring network of 21 sampling stations in the river and 13 in the important discharges (>2 m) was proposed. A great similitude was found between the average characteristics of the discharges and the river itself, in both the wet and dry seasons. Oxygen was found exhausted (river, with COD and TDS average levels of 390 and 1980 mg/L in the dry season, against 150 and 400 mg/L in the wet season. In the dry season, almost all the sites along the river revealed some toxicity to the bacteria test species (2.9 to 150 TU, with an average of 27 TU). Same septic conditions and toxicity levels were observed in many of the discharges. Four of the six evaluated tributaries, as well as the lagoon (origin of the river), were relatively in better conditions (2 to 8 mg/L D.O., TULerma, acting as diluents and renewal of the HCLR flow rate. The river was shown to be quite a main sewer collector. The high surface water contamination by untreated wastewaters that is depicted in this research should be taken into account in the
Supharatid, Seree
2003-10-01
This paper presents the applicability of neural network (NN) modelling for forecasting and filtering problems. The multilayer feedforward (MLFF) network was first constructed to forecast the tidal-level variations at the mouth of the River Chao Phraya in Thailand. Unlike the well-known conventional harmonic analysis, the NN model uses a set of previous data for learning and then forecasting directly the time-series of tidal levels. It was found that lead time of 1 to 24 hourly tidal levels can be predicted successfully using only a short-time hourly learning data. The MLFF network was further used to establish a stage-discharge relationship for the tidal river. The results show a considerably better performance of the NN model over the conventional models. In addition, the stage-discharge relationship obtained by the NN model can indicate reasonably well the important behaviour of the tidal influences. Copyright
Griffiths, Ronald E.; Topping, David J.; Andrews, Timothy; Bennett, Glenn E.; Sabol, Thomas A.; Melis, Theodore S.
2012-01-01
sufficiently accurate estimates of sediment loads. Finally, conventional suspended-sediment measurements are both labor and cost intensive and may not be possible at the resolution required to resolve discharge-independent changes in suspended-sediment concentration, especially in more remote locations. For these reasons, the U.S. Geological Survey has pursued the use of surrogate technologies (such as acoustic and laser diffraction) for providing higher-resolution measurements of suspended-sediment concentration and grain size than are possible by using conventional suspended-sediment measurements alone. These factors prompted the U.S. Geological Survey's Grand Canyon Monitoring and Research Center to design and construct a network to automatically measure suspended-sediment transport at 15-minute intervals by using acoustic and laser-diffraction surrogate technologies at remote locations along the Colorado River within Marble and Grand Canyons in Grand Canyon National Park. Because of the remoteness of the Colorado River in this reach, this network also included the design of a broadband satellite-telemetry system to communicate with the instruments deployed at each station in this network. Although the sediment-transport monitoring network described in this report was developed for the Colorado River in Grand Canyon National Park, the design of this network can easily be adapted for use on other rivers, no matter how remote. In the Colorado River case-study example described in this report, suspended-sediment concentration and grain size are measured at five remote stations. At each of these stations, surrogate measurements of suspended-sediment concentration and grain size are made at 15-minute intervals using an array of different single-frequency acoustic-Doppler side-looking profilers. Laser-diffraction instruments are also used at two of these stations to measure both suspended-sediment concentrations and grain-size distributions. Cross-section calibrations of these
Directory of Open Access Journals (Sweden)
Fan Zhang
2012-01-01
Full Text Available This paper describes details of an automatic matrix decomposition approach for a reaction-based stream water quality model. The method yields a set of equilibrium equations, a set of kinetic-variable transport equations involving kinetic reactions only, and a set of component transport equations involving no reactions. Partial decomposition of the system of water quality constituent transport equations is performed via Gauss-Jordan column reduction of the reaction network by pivoting on equilibrium reactions to decouple equilibrium and kinetic reactions. This approach minimizes the number of partial differential advective-dispersive transport equations and enables robust numerical integration. Complete matrix decomposition by further pivoting on linearly independent kinetic reactions allows some rate equations to be formulated individually and explicitly enforces conservation of component species when component transport equations are solved. The methodology is demonstrated for a case study involving eutrophication reactions in the Des Moines River in Iowa, USA and for two hypothetical examples to illustrate the ability of the model to simulate sediment and chemical transport with both mobile and immobile water phases and with complex reaction networks involving both kinetic and equilibrium reactions.
Water quality forecasting at Gongju station in Geum River using neural network model
Energy Technology Data Exchange (ETDEWEB)
Ahn, Sang-Jin; Yeon, In-Sung [Chungbuk National University, Cheongju(Korea); Han, Yang-Su [Kyungdong University, Sokcho(Korea); Lee, Jae-Kyung [Daewon Science College, Jecheon(Korea)
2001-12-31
Forecasting of water quality variation is not an easy process due to the complicated nature of various water quality factors and their interrelationships. The objective of this study is to test the applicability of neural network models to the forecasting of the water quality at Gongju station in Geum River. This is done by forecasting monthly water qualities such as DO, BOD, and TN, and comparing with those obtained by ARIMA model. The neural network models of this study use BP(Back Propagation) algorithm for training. In order to improve the performance of the training, the models are tested in three different styles; MANN model which uses the Moment-Adaptive learning rate method, LMNN model which uses the Levenberg-Marquardt method, and MNN model which separates the hidden layers for judgement factors from the hidden layers for water quality data. the results show that the forecasted water qualities are reasonably close to the observed data. And the MNN model shows the best results among the three models tested. (author). 14 refs., 4 tabs., 8 figs.
Simulation of river stage using artificial neural network and MIKE 11 hydrodynamic model
Panda, Rabindra K.; Pramanik, Niranjan; Bala, Biplab
2010-06-01
Simulation of water levels at different sections of a river using physically based flood routing models is quite cumbersome, because it requires many types of data such as hydrologic time series, river geometry, hydraulics of existing control structures and channel roughness coefficients. Normally in developing countries like India it is not easy to collect these data because of poor monitoring and record keeping. Therefore, an artificial neural network (ANN) technique is used as an effective alternative in hydrologic simulation studies. The present study aims at comparing the performance of the ANN technique with a widely used physically based hydrodynamic model in the MIKE 11 environment. The MIKE 11 hydrodynamic model was calibrated and validated for the monsoon periods (June-September) of the years 2006 and 2001, respectively. Feed forward neural network architecture with Levenberg-Marquardt (LM) back propagation training algorithm was used to train the neural network model using hourly water level data of the period June-September 2006. The trained ANN model was tested using data for the same period of the year 2001. Simulated water levels by the MIKE 11HD were compared with the corresponding water levels predicted by the ANN model. The results obtained from the ANN model were found to be much better than that of the MIKE 11HD results as indicated by the values of the goodness of fit indices used in the study. The Nash-Sutcliffe index ( E) and root mean square error (RMSE) obtained in case of the ANN model were found to be 0.8419 and 0.8939 m, respectively, during model testing, whereas in case of MIKE 11HD, the values of E and RMSE were found to be 0.7836 and 1.00 m, respectively, during model validation. The difference between the observed and simulated peak water levels obtained from the ANN model was found to be much lower than that of MIKE 11HD. The study reveals that the use of Levenberg-Marquardt algorithm with eight hidden neurons in the hidden layer
Analysis of fractals with combined partition
Dedovich, T. G.; Tokarev, M. V.
2016-03-01
The space—time properties in the general theory of relativity, as well as the discreteness and non-Archimedean property of space in the quantum theory of gravitation, are discussed. It is emphasized that the properties of bodies in non-Archimedean spaces coincide with the properties of the field of P-adic numbers and fractals. It is suggested that parton showers, used for describing interactions between particles and nuclei at high energies, have a fractal structure. A mechanism of fractal formation with combined partition is considered. The modified SePaC method is offered for the analysis of such fractals. The BC, PaC, and SePaC methods for determining a fractal dimension and other fractal characteristics (numbers of levels and values of a base of forming a fractal) are considered. It is found that the SePaC method has advantages for the analysis of fractals with combined partition.
Parkin, G.; Birkinshaw, S. J.; Younger, P. L.; Rao, Z.; Kirk, S.
2007-06-01
SummaryEvaluation of the impacts of groundwater abstractions on surface water systems is a necessary task in integrated water resources management. A range of hydrological, hydrogeological, and geomorphological factors influence the complex processes of interaction between groundwater and rivers. This paper presents an approach which uses numerical modeling of generic river-aquifer systems to represent the interaction processes, and neural networks to capture the impacts of the different controlling factors. The generic models describe hydrogeological settings representing most river-aquifer systems in England and Wales: high diffusivity (e.g. Chalk) and low diffusivity (e.g. Triassic Sandstone) aquifers with flow to rivers mediated by alluvial gravels; the same aquifers where they are in direct connection with the river; and shallow alluvial aquifers which are disconnected from regional aquifers. Numerical model simulations using the SHETRAN integrated catchment modeling system provided outputs including time-series and spatial variations in river flow depletion, and spatially distributed groundwater levels. Artificial neural network models were trained using input parameters describing the controlling factors and the outputs from the numerical model simulations, providing an efficient tool for representing the impacts of groundwater abstractions across a wide range of conditions. There are very few field data sets of accurately quantified river flow depletion as a result of groundwater abstraction under controlled conditions. One such data set from an experimental study carried out in 1967 on the Winterbourne stream in the Lambourne catchment over a Chalk aquifer was used successfully to test the modeling tool. This modeling approach provides a general methodology for rapid simulations of complex hydrogeological systems which preserves the physical consistency between multiple and diverse model outputs.
Fractals and finite scales; Fractales et echelles finies
Energy Technology Data Exchange (ETDEWEB)
Aubry, J.M
1997-08-01
Fractal description is used in various scientific domains and in particular in the modeling of particle aggregates and in the modeling of the Rayleigh-Taylor instabilities in turbulent two-phase flows. In particular, the interface geometry between fluids in a turbulent mixing is a crucial parameter for the modeling of mixtures in inertial confinement fusion devices. In this paper, a review of the various fractal dimensions is given first. Then, for a more rigorous use, a probabilistic description of the dimension of an ensemble which is known only up to a finite scale is proposed. This description is based on a probabilistic measurement of the overall fractals. (J.S.) 22 refs.
The fractal aggregation of asphaltenes.
Hoepfner, Michael P; Fávero, Cláudio Vilas Bôas; Haji-Akbari, Nasim; Fogler, H Scott
2013-07-16
This paper discusses time-resolved small-angle neutron scattering results that were used to investigate asphaltene structure and stability with and without a precipitant added in both crude oil and model oil. A novel approach was used to isolate the scattering from asphaltenes that are insoluble and in the process of aggregating from those that are soluble. It was found that both soluble and insoluble asphaltenes form fractal clusters in crude oil and the fractal dimension of the insoluble asphaltene clusters is higher than that of the soluble clusters. Adding heptane also increases the size of soluble asphaltene clusters without modifying the fractal dimension. Understanding the process of insoluble asphaltenes forming fractals with higher fractal dimensions will potentially reveal the microscopic asphaltene destabilization mechanism (i.e., how a precipitant modifies asphaltene-asphaltene interactions). It was concluded that because of the polydisperse nature of asphaltenes, no well-defined asphaltene phase stability envelope exists and small amounts of asphaltenes precipitated even at dilute precipitant concentrations. Asphaltenes that are stable in a crude oil-precipitant mixture are dispersed on the nanometer length scale. An asphaltene precipitation mechanism is proposed that is consistent with the experimental findings. Additionally, it was found that the heptane-insoluble asphaltene fraction is the dominant source of small-angle scattering in crude oil and the previously unobtainable asphaltene solubility at low heptane concentrations was measured.
Characterisation of human non-proliferative diabetic retinopathy using the fractal analysis
Institute of Scientific and Technical Information of China (English)
Stefan; Tǎlu; Dan; Mihai; Cǎlugǎru; Carmen; Alina; Lupascu
2015-01-01
· AIM: To investigate and quantify changes in the branching patterns of the retina vascular network in diabetes using the fractal analysis method.·METHODS: This was a clinic-based prospective study of 172 participants managed at the Ophthalmological Clinic of Cluj-Napoca, Romania, between January 2012 and December 2013. A set of 172 segmented and skeletonized human retinal images, corresponding to both normal(24 images) and pathological(148 images)states of the retina were examined. An automatic unsupervised method for retinal vessel segmentation was applied before fractal analysis. The fractal analyses of the retinal digital images were performed using the fractal analysis software Image J. Statistical analyses were performed for these groups using Microsoft Office Excel2003 and Graph Pad In Stat software.·RESULTS: It was found that subtle changes in the vascular network geometry of the human retina are influenced by diabetic retinopathy(DR) and can be estimated using the fractal geometry. The average of fractal dimensions D for the normal images(segmented and skeletonized versions) is slightly lower than the corresponding values of mild non-proliferative DR(NPDR) images(segmented and skeletonized versions).The average of fractal dimensions D for the normal images(segmented and skeletonized versions) is higher than the corresponding values of moderate NPDR images(segmented and skeletonized versions). The lowestvalues were found for the corresponding values of severe NPDR images(segmented and skeletonized versions).· CONCLUSION: The fractal analysis of fundus photographs may be used for a more complete understanding of the early and basic pathophysiological mechanisms of diabetes. The architecture of the retinal microvasculature in diabetes can be quantitative quantified by means of the fractal dimension.Microvascular abnormalities on retinal imaging may elucidate early mechanistic pathways for microvascular complications and distinguish patients with DR from
Fractal differential equations and fractal-time dynamical systems
Indian Academy of Sciences (India)
Abhay Parvate; A D Gangal
2005-03-01
Differential equations and maps are the most frequently studied examples of dynamical systems and may be considered as continuous and discrete time-evolution processes respectively. The processes in which time evolution takes place on Cantor- like fractal subsets of the real line may be termed as fractal-time dynamical systems. Formulation of these systems requires an appropriate framework. A new calculus called -calculus, is a natural calculus on subsets ⊂ R of dimension , 0 < ≤ 1. It involves integral and derivative of order , called -integral and -derivative respectively. The -integral is suitable for integrating functions with fractal support of dimension , while the -derivative enables us to differentiate functions like the Cantor staircase. The functions like the Cantor staircase function occur naturally as solutions of -differential equations. Hence the latter can be used to model fractal-time processes or sublinear dynamical systems. We discuss construction and solutions of some fractal differential equations of the form $$D^{}_{F,t} x = h(x, t),$$ where ℎ is a vector field and $D^{}_{F,t}$ is a fractal differential operator of order in time . We also consider some equations of the form $$D^{}_{F,t} W(x, t) = L[W(x, t)],$$ where is an ordinary differential operator in the real variable , and $(t, x) F × \\mathbf{R}^{n}$ where is a Cantor-like set of dimension . Further, we discuss a method of finding solutions to -differential equations: They can be mapped to ordinary differential equations, and the solutions of the latter can be transformed back to get those of the former. This is illustrated with a couple of examples.
Enhanced Graphene Photodetector with Fractal Metasurface
DEFF Research Database (Denmark)
Fan, Jieran; Wang, Di; DeVault, Clayton
2016-01-01
We designed and fabricated a broadband, polarization-independent photodetector by integrating graphene with a fractal Cayley tree metasurface. Our measurements show an almost uniform, tenfold enhancement in photocurrent generation due to the fractal metasurface structure.......We designed and fabricated a broadband, polarization-independent photodetector by integrating graphene with a fractal Cayley tree metasurface. Our measurements show an almost uniform, tenfold enhancement in photocurrent generation due to the fractal metasurface structure....
Fractal Structures For Fixed Mems Capacitors
Elshurafa, Amro M.
2014-08-28
An embodiment of a fractal fixed capacitor comprises a capacitor body in a microelectromechanical system (MEMS) structure. The capacitor body has a first plate with a fractal shape separated by a horizontal distance from a second plate with a fractal shape. The first plate and the second plate are within the same plane. Such a fractal fixed capacitor further comprises a substrate above which the capacitor body is positioned.
Fractal harmonic law and waterproof/dustproof
Directory of Open Access Journals (Sweden)
Kong Hai-Yan
2014-01-01
Full Text Available The fractal harmonic law admits that the friction between the pure water and the moving surface is the minimum when fractal dimensions of water in Angstrom scale are equal to fractal dimensions of the moving surface in micro scale. In the paper, the fractal harmonic law is applied to demonstrate the mechanism of waterproof/ dustproof. The waterproof phenomenon of goose feathers and lotus leaves is illustrated to verify our results and experimental results agree well with our theoretical analysis.
Ye, Sheng; Covino, Timothy P.; Sivapalan, Murugesu; Basu, Nandita B.; Li, Hong-Yi; Wang, Shao-Wen
2012-06-01
We have used a dynamic hydrologic network model, coupled with a transient storage zone solute transport model, to simulate dissolved nutrient retention processes during transient flow events at the channel network scale. We explored several scenarios with a combination of rainfall variability, and biological and geomorphic characteristics of the catchment, to understand the dominant factors that control the transport of dissolved nutrients (e.g., nitrate) along channel networks. While much experimental work has focused on studying nutrient retention during base flow periods in headwater streams, our model-based theoretical analyses, for the given parameter combinations used, suggest that high-flow periods can contribute substantially to overall nutrient retention, and that bulk nutrient retention is greater in larger rivers compared to headwaters. The relative efficiencies of nutrient retention during high- and low-flow periods vary due to changes in the relative sizes of the main channel and transient storage zones, as well as due to differences in the relative strengths of the various nutrient retention mechanisms operating in both zones. Our results also indicate that nutrient retention efficiency at all spatial scales of observation has strong dependence on within-year variability of streamflow (e.g., frequency and duration of high and low flows), as well as on the relative magnitudes of the coefficients that govern biogeochemical uptake processes: the more variable the streamflow, the greater the export of nutrients. Despite limitations of the model parameterizations, our results suggest that increased attention must be paid to field observations of the interactions between process hydrology and nutrient transport and reaction processes at a range of scales to assist with extrapolation of understandings and estimates gained from site-specific studies to ungauged basins across gradients in climate, human impacts, and landscape characteristics.
Fractal characterization of fracture surfaces in concrete
Saouma, V.E.; Barton, C.C.; Gamaleldin, N.A.
1990-01-01
Fractal geometry is used to characterize the roughness of cracked concrete surfaces through a specially built profilometer, and the fractal dimension is subsequently correlated to the fracture toughness and direction of crack propagation. Preliminary results indicate that the fracture surface is indeed fractal over two orders of magnitudes with a dimension of approximately 1.20. ?? 1990.
Fractal Electronic Circuits Assembled From Nanoclusters
Fairbanks, M. S.; McCarthy, D.; Taylor, R. P.; Brown, S. A.
2009-07-01
Many patterns in nature can be described using fractal geometry. The effect of this fractal character is an array of properties that can include high internal connectivity, high dispersivity, and enhanced surface area to volume ratios. These properties are often desirable in applications and, consequently, fractal geometry is increasingly employed in technologies ranging from antenna to storm barriers. In this paper, we explore the application of fractal geometry to electrical circuits, inspired by the pervasive fractal structure of neurons in the brain. We show that, under appropriate growth conditions, nanoclusters of Sb form into islands on atomically flat substrates via a process close to diffusion-limited aggregation (DLA), establishing fractal islands that will form the basis of our fractal circuits. We perform fractal analysis of the islands to determine the spatial scaling properties (characterized by the fractal dimension, D) of the proposed circuits and demonstrate how varying growth conditions can affect D. We discuss fabrication approaches for establishing electrical contact to the fractal islands. Finally, we present fractal circuit simulations, which show that the fractal character of the circuit translates into novel, non-linear conduction properties determined by the circuit's D value.
Fractal analysis of time varying data
Vo-Dinh, Tuan; Sadana, Ajit
2002-01-01
Characteristics of time varying data, such as an electrical signal, are analyzed by converting the data from a temporal domain into a spatial domain pattern. Fractal analysis is performed on the spatial domain pattern, thereby producing a fractal dimension D.sub.F. The fractal dimension indicates the regularity of the time varying data.
Fractal Structures For Mems Variable Capacitors
Elshurafa, Amro M.
2014-08-28
In accordance with the present disclosure, one embodiment of a fractal variable capacitor comprises a capacitor body in a microelectromechanical system (MEMS) structure, wherein the capacitor body has an upper first metal plate with a fractal shape separated by a vertical distance from a lower first metal plate with a complementary fractal shape; and a substrate above which the capacitor body is suspended.
Speaker Identification Based on Fractal Dimensions
Institute of Scientific and Technical Information of China (English)
侯丽敏; 王朔中
2003-01-01
This paper discusses application of fractal dimensions to speech processing. Generalized dimensions of arbitrary orders and associated fractal parameters are used in speaker identification. A characteristic vactor based on these parameters is formed, and a recognition criterion definded in order to identify individual speakers. Experimental results show the usefulness of fractal dimensions in characterizing speaker identity.
Steady laminar flow of fractal fluids
Energy Technology Data Exchange (ETDEWEB)
Balankin, Alexander S., E-mail: abalankin@ipn.mx [Grupo Mecánica Fractal, ESIME, Instituto Politécnico Nacional, México D.F., 07738 (Mexico); Mena, Baltasar [Laboratorio de Ingeniería y Procesos Costeros, Instituto de Ingeniería, Universidad Nacional Autónoma de México, Sisal, Yucatán, 97355 (Mexico); Susarrey, Orlando; Samayoa, Didier [Grupo Mecánica Fractal, ESIME, Instituto Politécnico Nacional, México D.F., 07738 (Mexico)
2017-02-12
We study laminar flow of a fractal fluid in a cylindrical tube. A flow of the fractal fluid is mapped into a homogeneous flow in a fractional dimensional space with metric induced by the fractal topology. The equations of motion for an incompressible Stokes flow of the Newtonian fractal fluid are derived. It is found that the radial distribution for the velocity in a steady Poiseuille flow of a fractal fluid is governed by the fractal metric of the flow, whereas the pressure distribution along the flow direction depends on the fractal topology of flow, as well as on the fractal metric. The radial distribution of the fractal fluid velocity in a steady Couette flow between two concentric cylinders is also derived. - Highlights: • Equations of Stokes flow of Newtonian fractal fluid are derived. • Pressure distribution in the Newtonian fractal fluid is derived. • Velocity distribution in Poiseuille flow of fractal fluid is found. • Velocity distribution in a steady Couette flow is established.
Fractal Structure of Debris Flow
Institute of Scientific and Technical Information of China (English)
LI Yong; LIU Jingjing; HU Kaiheng; CHEN Xiaoqing
2007-01-01
One of the most remarkable characteristics of debris flow is the competence for supporting boulders on the surface of flow, which strongly suggests that there should be some structure in the fluid body. This paper analyzed the grain compositions from various samples of debris flows and then revealed the fractal structure. Specifically, the fractality holds in three domains that can be respectively identified as the slurry, matrix, and the coarse content. Furthermore, the matrix fractal, which distinguishes debris flow from other kinds of flows, involves a hierarchical structure in the sense that it might contain ever increasing grains while the total range of grain size increases. It provides a possible mechanism for the boulder suspension.
A Data Model for Hydrologic Sensor Networks Monitoring River- Groundwater Interactions
Schneider, Philipp; Wombacher, Andreas
2010-05-01
Real-time operated wireless sensor networks produce large amounts of data, so that typical eyeball based analysis of data comes to its limits. Consequently we have to adapt and automate our data handling and archiving procedures, as well as our data analysis tools. Management of sensor data requires metadata to understand the semantics of observations. While modelers have high demands on metadata, experimentalists prefer to minimize entering metadata, as this is an additional effort. Quite often this is done on subjective basis ("field notes") without following a strict and predefined structure with transparent criteria and consistent vocabulary. Nevertheless, data has to be semantically annotated. The claim of this presentation is to focus on the essentials, being described by location, time, owner, instrument and measurement. The applicability is demonstrated in a case study focussing on monitoring changes of river-groundwater interactions in the context of river restoration. Fundamental steps are (i) a proper storage in a database, (ii) traceable link between data and meta-data and (iii) semantically annotation tagged to the data, e.g. concerning data quality and data interpretation. To some extend this can be done automatically (e.g. plausibility check, if values are in expected range). The scientific challenge lies in identifying periods (data strings) where high resolution data stresses expected system behavior and established process representations/conceptualizations used in well accepted and widely used models. When and where do we measure data which do not match our expectations? As the amount of data will increase dramatically, pre-aggregation and visualization have to be automated to focus on critical parts of time series which needs interpretation with further expert knowledge.
Neural network river forecasting through baseflow separation and binary-coded swarm optimization
Taormina, Riccardo; Chau, Kwok-Wing; Sivakumar, Bellie
2015-10-01
The inclusion of expert knowledge in data-driven streamflow modeling is expected to yield more accurate estimates of river quantities. Modular models (MMs) designed to work on different parts of the hydrograph are preferred ways to implement such approach. Previous studies have suggested that better predictions of total streamflow could be obtained via modular Artificial Neural Networks (ANNs) trained to perform an implicit baseflow separation. These MMs fit separately the baseflow and excess flow components as produced by a digital filter, and reconstruct the total flow by adding these two signals at the output. The optimization of the filter parameters and ANN architectures is carried out through global search techniques. Despite the favorable premises, the real effectiveness of such MMs has been tested only on a few case studies, and the quality of the baseflow separation they perform has never been thoroughly assessed. In this work, we compare the performance of MM against global models (GMs) for nine different gaging stations in the northern United States. Binary-coded swarm optimization is employed for the identification of filter parameters and model structure, while Extreme Learning Machines, instead of ANN, are used to drastically reduce the large computational times required to perform the experiments. The results show that there is no evidence that MM outperform global GM for predicting the total flow. In addition, the baseflow produced by the MM largely underestimates the actual baseflow component expected for most of the considered gages. This occurs because the values of the filter parameters maximizing overall accuracy do not reflect the geological characteristics of the river basins. The results indeed show that setting the filter parameters according to expert knowledge results in accurate baseflow separation but lower accuracy of total flow predictions, suggesting that these two objectives are intrinsically conflicting rather than compatible.
Kalteh, Aman Mohammad
2013-04-01
Reliable and accurate forecasts of river flow is needed in many water resources planning, design development, operation and maintenance activities. In this study, the relative accuracy of artificial neural network (ANN) and support vector regression (SVR) models coupled with wavelet transform in monthly river flow forecasting is investigated, and compared to regular ANN and SVR models, respectively. The relative performance of regular ANN and SVR models is also compared to each other. For this, monthly river flow data of Kharjegil and Ponel stations in Northern Iran are used. The comparison of the results reveals that both ANN and SVR models coupled with wavelet transform, are able to provide more accurate forecasting results than the regular ANN and SVR models. However, it is found that SVR models coupled with wavelet transform provide better forecasting results than ANN models coupled with wavelet transform. The results also indicate that regular SVR models perform slightly better than regular ANN models.
Improved visibility graph fractality with application for the diagnosis of Autism Spectrum Disorder
Ahmadlou, Mehran; Adeli, Hojjat; Adeli, Amir
2012-10-01
Recently, the visibility graph (VG) algorithm was proposed for mapping a time series to a graph to study complexity and fractality of the time series through investigation of the complexity of its graph. The visibility graph algorithm converts a fractal time series to a scale-free graph. VG has been used for the investigation of fractality in the dynamic behavior of both artificial and natural complex systems. However, robustness and performance of the power of scale-freeness of VG (PSVG) as an effective method for measuring fractality has not been investigated. Since noise is unavoidable in real life time series, the robustness of a fractality measure is of paramount importance. To improve the accuracy and robustness of PSVG to noise for measurement of fractality of time series in biological time-series, an improved PSVG is presented in this paper. The proposed method is evaluated using two examples: a synthetic benchmark time series and a complicated real life Electroencephalograms (EEG)-based diagnostic problem, that is distinguishing autistic children from non-autistic children. It is shown that the proposed improved PSVG is less sensitive to noise and therefore more robust compared with PSVG. Further, it is shown that using improved PSVG in the wavelet-chaos neural network model of Adeli and c-workers in place of the Katz fractality dimension results in a more accurate diagnosis of autism, a complicated neurological and psychiatric disorder.
Fractal Structure of Molecular Clouds
Datta, Srabani
2001-01-01
Compelling evidence exists to show that the structure of molecular clouds is fractal in nature. In this paper, the author reiterates this view and, in addition, asserts that not only is cloud geometry fractal, but that they also have a common characteristic - they are similar in shape to the Horsehead nebula in Orion. This shape can be described by the Julia function f(x)= z^2 + c,where both z and c are complex quantities and c = -0.745429 + 0.113008i. The dynamical processes responsible for ...
Time evolution of quantum fractals
Wojcik; Bialynicki-Birula; Zyczkowski
2000-12-11
We propose a general construction of wave functions of arbitrary prescribed fractal dimension, for a wide class of quantum problems, including the infinite potential well, harmonic oscillator, linear potential, and free particle. The box-counting dimension of the probability density P(t)(x) = |Psi(x,t)|(2) is shown not to change during the time evolution. We prove a universal relation D(t) = 1+Dx/2 linking the dimensions of space cross sections Dx and time cross sections D(t) of the fractal quantum carpets.
Time Evolution of Quantum Fractals
Wójcik, D; Zyczkowski, K; Wojcik, Daniel; Bialynicki-Birula, Iwo; Zyczkowski, Karol
2000-01-01
We propose a general construction of wave functions of arbitrary prescribed fractal dimension, for a wide class of quantum problems, including the infinite potential well, harmonic oscillator, linear potential and free particle. The box-counting dimension of the probability density $P_t(x)=|\\Psi(x,t)|^2$ is shown not to change during the time evolution. We prove a universal relation $D_t=1+D_x/2$ linking the dimensions of space cross-sections $D_x$ and time cross-sections $D_t$ of the fractal quantum carpets.
Synergetics and fractals in tribology
Janahmadov, Ahad Kh
2016-01-01
This book examines the theoretical and practical aspects of tribological process using synergy, fractal and multifractal methods, and the fractal and multifractal models of self-similar tribosystems developed on their basis. It provides a comprehensive analysis of their effectiveness, and also considers the method of flicker noise spectroscopy with detailed parameterization of surface roughness friction. All models, problems and solutions are taken and tested on the set of real-life examples of oil-gas industry. The book is intended for researchers, graduate students and engineers specialising in the field of tribology, and also for senior students of technical colleges.
Fractality of Massive Graphs: Scalable Analysis with Sketch-Based Box-Covering Algorithm
Akiba, Takuya; Takaguchi, Taro
2016-01-01
Analysis and modeling of networked objects are fundamental pieces of modern data mining. Most real-world networks, from biological to social ones, are known to have common structural properties. These properties allow us to model the growth processes of networks and to develop useful algorithms. One remarkable example is the fractality of networks, which suggests the self-similar organization of global network structure. To determine the fractality of a network, we need to solve the so-called box-covering problem, where preceding algorithms are not feasible for large-scale networks. The lack of an efficient algorithm prevents us from investigating the fractal nature of large-scale networks. To overcome this issue, we propose a new box-covering algorithm based on recently emerging sketching techniques. We theoretically show that it works in near-linear time with a guarantee of solution accuracy. In experiments, we have confirmed that the algorithm enables us to study the fractality of million-scale networks fo...
Directory of Open Access Journals (Sweden)
Morel Mathieu
2016-01-01
Full Text Available The OECD report “Boosting Resilience through Innovative Risk Governance” examines the efforts of OECD countries to prevent or reduce future disaster impacts, and highlights several key areas where improvements can be made. International collaboration is insufficiently utilised to address shocks that have increasingly global consequences. Institutional design plays a significant role in facilitating or hampering the engagement and investments of governmental and non-governmental stakeholders in disaster risk prevention and mitigation. To inform the design of “better” institutions, the OECD proposes the application of a diagnostic framework that helps governments identify institutional shortcomings and take actions to improve them. The goal of the case study on the Rhone River is to conduct an analysis of the progress, achievements and existing challenges in designing and implementing disaster risk reduction strategies through the Rhone Plan from a comparative perspective across a set of selected countries of this study, like Austria and Switzerland, will inform how to improve institutional frameworks governing risk prevention and mitigation. The case study will be used to identify examples of successful practice taking into account their specific country contexts, and analyse their potential for policy transfer.
Tessler, Z. D.; Vorosmarty, C. J.; Cohen, S.; Tang, H.
2014-12-01
A loose-coupling of a basin-scale hydrological and sediment flux model with acoastal ocean hydrodynamics model is used to assess the importance ofuncertainties in river mouth locations and fluxes on coastal geomorphology ofthe Mekong river delta. At the land-ocean interface, river deltas mediate theflux of water, sediment, and nutrients from the basin watershed, though thecomplex delta river network, and into the coastal ocean. In the Mekong riverdelta, irrigation networks and surface water storage for rice cultivationredistribute, in space and time, water and sediment fluxes along the coastline.Distribution of fluxes through the delta is important for accurate assessment ofdelta land aggregation, coastline migration, and coastal ocean biogeochemistry.Using a basin-scale hydrological model, WBMsed, interfaced with a coastalhydrodynamics/wave/sediment model, COAWST, we investigate freshwater andsediment plumes and morphological changes to the subaqueous delta front. Thereis considerable uncertainty regarding how the delta spatially filters water andsediment fluxes as they transit through the river and irrigation network. Byadjusting the placement and relative distribution of WBMsed discharge along thecoast, we estimate the resulting bounds on sediment plume structure, timing, andmorphological deposition patterns. The coastal ocean model is validated bycomparing simulated plume structure and seasonality to MERIS and MODIS derivedestimates of surface turbidity. We find good agreement with regards to plumeextent and timing, with plumes weakest in the early spring, extending stronglyto the west in the fall, and toward the east in winter. Uncertainty regardingriver outflow distribution along the coastline leads to substantial uncertaintyin rates of morphological change, particularly away from the main Mekong Riverdistributary channels.
Fat fractal percolation and k-fractal percolation
Broman, Erik; Camia, Federico; Joosten, Matthijs; Meester, Ronald
2011-01-01
We consider two variations on the Mandelbrot fractal percolation model. In the k-fractal percolation model, the d-dimensional unit cube is divided in N^d equal subcubes, k of which are retained while the others are discarded. The procedure is then iterated inside the retained cubes at all smaller scales. We show that the (properly rescaled) percolation critical value of this model converges to the critical value of site percolation in L^d as N tends to infinity. This is analogous to the result of Falconer and Grimmett that the critical value for Mandelbrot fractal percolation converges to the critical value of site percolation in L^d. In the fat fractal percolation model, subcubes are retained with probability p_n at step n of the construction, where (p_n) is a non-decreasing sequence with \\prod p_n > 0. The Lebesgue measure of the limit set is positive a.s. given non-extinction. We show that with probability 1 either the set of "dust" points or the set of connected components larger than one point has positi...
National Research Council Canada - National Science Library
Wen-Cheng Liu; Chuan-En Chung
2014-01-01
...) and genetic algorithm neural network (GANN) techniques, to improve predictions from a one-dimensional flood routing hydrodynamic model regarding the water stages during typhoon events in the Danshuei River system in northern Taiwan...
The Generation of a Sort of Fractal Graphs
Institute of Scientific and Technical Information of China (English)
张钹; 张铃; 等
1995-01-01
We present an approach for generating a sort of fractal graphs by a simple probabilistic logic neuron network and show that the graphs can be represented by a set of compressed codings.An algorithm for quickly finding the codings,i.e.,recognizing the corresponding graphs,is given.The codings are shown to be optimal.The results above possibly give us the clue for studying image compression and pattern recognition.
Designing fractal nanostructured biointerfaces for biomedical applications.
Zhang, Pengchao; Wang, Shutao
2014-06-06
Fractal structures in nature offer a unique "fractal contact mode" that guarantees the efficient working of an organism with an optimized style. Fractal nanostructured biointerfaces have shown great potential for the ultrasensitive detection of disease-relevant biomarkers from small biomolecules on the nanoscale to cancer cells on the microscale. This review will present the advantages of fractal nanostructures, the basic concept of designing fractal nanostructured biointerfaces, and their biomedical applications for the ultrasensitive detection of various disease-relevant biomarkers, such microRNA, cancer antigen 125, and breast cancer cells, from unpurified cell lysates and the blood of patients.
Order-Fractal transition in abstract paintings
De la Calleja, E. M.; Cervantes, F.; De la Calleja, J.
2015-01-01
We report the degree of order of twenty-two Jackson Pollock's paintings using \\emph{Hausdorff-Besicovitch fractal dimension}. Through the maximum value of each multi-fractal spectrum, the artworks are classify by the year in which they were painted. It has been reported that Pollock's paintings are fractal and it increased on his latest works. However our results show that fractal dimension of the paintings are on a range of fractal dimension with values close to two. We identify this behavio...
Schmitt, Rafael J. P.; Bizzi, Simone; Castelletti, Andrea
2016-05-01
Sediment connectivity in fluvial networks results from the transfer of sediment between multiple sources and sinks. Connectivity scales differently between all sources and sinks as a function of distance, source grain size and sediment supply, network topology and topography, and hydrologic forcing. In this paper, we address the challenge of quantifying sediment connectivity and its controls at the network scale. We expand the concept of a single, catchment-scale sediment cascade toward representing sediment transport from each source as a suite of individual cascading processes. We implement this approach in the herein presented CAtchment Sediment Connectivity And DElivery (CASCADE) modeling framework. In CASCADE, each sediment cascade establishes connectivity between a specific source and its multiple sinks. From a source perspective, the fate of sediment is controlled by its detachment and downstream transport capacity, resulting in a specific trajectory of transfer and deposition. From a sink perspective, the assemblage of incoming cascades defines provenance, sorting, and magnitude of sediment deliveries. At the network scale, this information reveals emerging patterns of connectivity and the location of bottlenecks, where disconnectivity occurs. In this paper, we apply CASCADE to quantitatively analyze the sediment connectivity of a major river system in SE Asia. The approach provides a screening model that can support analyses of large, poorly monitored river systems. We test the sensitivity of CASCADE to various parameters and identify the distribution of energy between the multiple, simultaneously active sediment cascades as key control behind network sediment connectivity. To conclude, CASCADE enables a quantitative, spatially explicit analysis of network sediment connectivity with potential applications in both river science and management.
Brennan, Sean R.; Torgersen, Christian E.; Hollenbeck, Jeff P.; Fernandez, Diego P.; Jensen, Carrie K.; Schindler, Daniel E.
2016-05-01
A critical challenge for the Earth sciences is to trace the transport and flux of matter within and among aquatic, terrestrial, and atmospheric systems. Robust descriptions of isotopic patterns across space and time, called "isoscapes," form the basis of a rapidly growing and wide-ranging body of research aimed at quantifying connectivity within and among Earth's systems. However, isoscapes of rivers have been limited by conventional Euclidean approaches in geostatistics and the lack of a quantitative framework to apportion the influence of processes driven by landscape features versus in-stream phenomena. Here we demonstrate how dendritic network models substantially improve the accuracy of isoscapes of strontium isotopes and partition the influence of hydrologic transport versus local geologic features on strontium isotope ratios in a large Alaska river. This work illustrates the analytical power of dendritic network models for the field of isotope biogeochemistry, particularly for provenance studies of modern and ancient animals.
Energy Technology Data Exchange (ETDEWEB)
Kim, Hyun Young; Hwang, Cheol Sang; Kang, Seok Man; Lee, Kwang Ya [Rural Development Corp., Seoul (Korea)
1998-08-31
When various elements of water balance are displayed at several points of a river network, the runoff amounts at an estuary especially tidal influenced are affected from the elements. This problem can be solved by a model that can generalize and formulate the elements and simulate daily runoff and water requirement. The WWASS model was built using DIROM for the simulation of daily runoff and water requirement, and the water balance elements were modeled to be balanced at the each control point of river network. The model was calibrated, verified and applied to the watershed for the Saemankeum tidal land reclamation development project. It showed that the results from the stream flow simulation at the Mankyung and Dongjin estuary were acceptable for the design of the Saemankeum estuary reservoir. (author). 7 refs., 3 tabs., 8 figs.
Brennan, Sean R.; Torgersen, Christian; Hollenbeck, Jeff P.; Fernandez, Diego P.; Jensen, Carrie K; Schindler, Daniel E.
2016-01-01
A critical challenge for the Earth sciences is to trace the transport and flux of matter within and among aquatic, terrestrial, and atmospheric systems. Robust descriptions of isotopic patterns across space and time, called “isoscapes,” form the basis of a rapidly growing and wide-ranging body of research aimed at quantifying connectivity within and among Earth's systems. However, isoscapes of rivers have been limited by conventional Euclidean approaches in geostatistics and the lack of a quantitative framework to apportion the influence of processes driven by landscape features versus in-stream phenomena. Here we demonstrate how dendritic network models substantially improve the accuracy of isoscapes of strontium isotopes and partition the influence of hydrologic transport versus local geologic features on strontium isotope ratios in a large Alaska river. This work illustrates the analytical power of dendritic network models for the field of isotope biogeochemistry, particularly for provenance studies of modern and ancient animals.
Ghani, N. Ab; Abrahart, R. J.; Clifford, N. J.
2009-04-01
Neural networks can be trained to model the sediment-discharge relationship: numerous illustrative applications exist. The standard method of reporting involves using a scatterplot of observed versus predicted records, plus a handful of global statistics, to support an assessment of model skill. This traditional approach will nevertheless result in undesirable side effects since it reinforces the 'black box' criticisms and associated demonisation that is sometimes levelled at computational intelligence solutions: no 'line-of-best-fit' is ever supplied. This paper in contrast compares and evaluates six computational methods for modelling the sediment-discharge relationship from a structural and behavioural standpoint in which the exact nature of each model is visualised for the purposes of diagnostic appraisal and scientific enlightenment. The following methods are compared: backpropagation neural network; corrected power function; simple linear regression; piecewise linear regression using an M5 Model Tree; LOWESS; and Robust LOWESS. Modelling is restricted to a consideration of bivariate relationships. The models were developed on daily river discharge and sediment concentration datasets for two rivers in Missouri: Lower Salt River and Little Black River. Each dataset was divided into two parts using different methods and each model was first calibrated on one sub-set and thereafter tested on the other. The datasets were next swapped over and the process repeated. Each model is also evaluated using statistical measures calculated in HydroTest (http://www.hydrotest.org.uk/). The need for more benchmarking exercises of a similar nature is highlighted.
Xie, Chen; Yang, Fan; Liu, Guoqing; Liu, Yang; Wang, Long; Fan, Ziwu
2017-01-01
Water environment of urban rivers suffers degradation with the impacts of urban expansion, especially in Yangtze River Delta. The water area in cites decreased sharply, and some rivers were cut off because of estate development, which brings the problems of urban flooding, flow stagnation and water deterioration. The approach aims to enhance flood control capability and improve the urban river water quality by planning gate-pump stations surrounding the cities and optimizing the locations and functions of the pumps, sluice gates, weirs in the urban river network. These gate-pump stations together with the sluice gates and weirs guarantee the ability to control the water level in the rivers and creating hydraulic gradient artificially according to mathematical model. Therefore the flow velocity increases, which increases the rate of water exchange, the DO concentration and water body self-purification ability. By site survey and prototype measurement, the river problems are evaluated and basic data are collected. The hydrodynamic model of the river network is established and calibrated to simulate the scenarios. The schemes of water quality improvement, including optimizing layout of the water distribution projects, improvement of the flow discharge in the river network and planning the drainage capacity are decided by comprehensive Analysis. Finally the paper introduces the case study of the approach in Changshu City, where the approach is successfully implemented.
Fractal and its application to sedimentology
Institute of Scientific and Technical Information of China (English)
余继峰; 李增学; 韩美莲
2002-01-01
In the paper,the foundation,development,basic conception and general characteristics of fractal and the calculating method of the fractional dimension are expounded briefly, and the current situation and prospect of the fractal application in sedimentology are discussed stressly. Both sedimentary process and sedimentary record behave the fractal feature of the self-similarity structure. External form and internal texture of the sediments and the distribution of the grain-size of the sediments are of fractal feature very well, and the size of the fractional dimension is the quantitative index of the complexity of the background when they are formed. The further analysis on the multi-fractal feature of the sedimentary body is the base of the fractal simulation and forecast, and it is the key of the application of the fractal theory to sedimentology.
Ghane, Alireza; Mazaheri, Mehdi; Mohammad Vali Samani, Jamal
2016-09-15
The pollution of rivers due to accidental spills is a major threat to environment and human health. To protect river systems from accidental spills, it is essential to introduce a reliable tool for identification process. Backward Probability Method (BPM) is one of the most recommended tools that is able to introduce information related to the prior location and the release time of the pollution. This method was originally developed and employed in groundwater pollution source identification problems. One of the objectives of this study is to apply this method in identifying the pollution source location and release time in surface waters, mainly in rivers. To accomplish this task, a numerical model is developed based on the adjoint analysis. Then the developed model is verified using analytical solution and some real data. The second objective of this study is to extend the method to pollution source identification in river networks. In this regard, a hypothetical test case is considered. In the later simulations, all of the suspected points are identified, using only one backward simulation. The results demonstrated that all suspected points, determined by the BPM could be a possible pollution source. The proposed approach is accurate and computationally efficient and does not need any simplification in river geometry and flow. Due to this simplicity, it is highly recommended for practical purposes. Copyright © 2016. Published by Elsevier Ltd.
Needoba, J. A.; Peterson, T. D.; Riseman, S.; Wilkin, M.; Baptista, A. M.
2015-12-01
The Columbia River estuary is an ecosystem dominated by both a large river discharge and strong tidal forcing that creates fast currents, intense and variable physical stratification, low water residence times, and large gradients in salinity, temperature and water quality across the river to ocean boundary. Assessing ecosystem function and biogeochemical cycling in this environment is hampered by the inherent variability in both temporal and spatial timescales. In recent years the NSF Science and Technology Center for Coastal Margin Observation and Prediction has established a comprehensive in situ observation network that spans the estuarine gradient and captures variability associated with tides, diel cycles, episodic events, and seasonal changes in the river and ocean end-members. Here we describe the major patterns of variability in nitrate, orthophosphate, fluorescent dissolved organic carbon and related variables that demonstrate the dominant physical forcing and the biogeochemical hotspots within the ecosystem. These hotspots include intertidal lateral bays, the tidal freshwater river, and the estuarine turbidity maxima. Improved understanding of the role of these estuarine hotspots has informed ecosystem stewardship activities related to juvenile salmon survival, hypoxia, and food web structure.
Broadband light-scattering spectroscopy on fractal and non-fractal relaxors
Koreeda, Akitoshi; Ogawa, Tomohiro; Katayama, Daisuke; Fujii, Yasuhiro; Tachibana, Makoto
2016-10-01
We show the quasi-elastic light scattering (QELS) spectra of two groups of relaxors: the first group includes relaxors that exhibit glasslike low-temperature thermal conductivity and heat capacity, namely, Pb(Mg1/3Nb2/3)O3 (PMN), (1 - x)Pb(Mg1/3Nb2/3)O3-xPbTiO3 (PMN-xPT), Pb(Zr1/3Nb2/3)O3 (PZN), and (Na1/2Bi1/2)TiO3 (NBT). The other group consists of relaxors exhibiting a normal (crystal) temperature dependence of the thermal conductivity and heat capacity, namely, K1- x Li x TaO3 (KLT) and KTa1- x Nb x O3 (KTN). The crystals of the first group yielded self-similar (power-law) QELS spectra, indicating the existence of fractal networks/clusters of polar nanoregions, while those of the second group did not show any self-similarity in the QELS spectra. These results imply that the glasslike low-temperature thermal conductivity and heat capacity in relaxors can be attributed to the vibrational modes specific to fractal networks/clusters formed by polar nanoregions.
Durer-pentagon-based complex network
Directory of Open Access Journals (Sweden)
Rui Hou
2016-04-01
Full Text Available A novel Durer-pentagon-based complex network was constructed by adding a centre node. The properties of the complex network including the average degree, clustering coefficient, average path length, and fractal dimension were determined. The proposed complex network is small-world and fractal.
Liu, Z.; Kim, H.; Famiglietti, J. S.
2011-12-01
The main motivation of this study is to characterize how accurately we can estimate river discharge, river depth and inundation extent using an explicit representation of the river network with a catchment-based hydrological and routing modeling system (CHARMS) framework. Here we present a macroscale implementation of CHARMS over California. There are two main components in CHARMS: a land surface model based on National Center Atmospheric Research Community Land Model (CLM) 4.0, which is modified for implementation on a catchment template; and a river routing model that considers the water transport of each river reach. The river network is upscaled from the National Hydrography Dataset Plus (NHDPlus) to the Hydrologic Unit Code (HUC8) river basins. Both long-term monthly and daily streamflow simulation are generated and show reasonable results compared with gage observations. With river cross-section profile information derived from empirical relationships between channel dimensions and drainage area, river depth and floodplain extent associated with each river reach are also explicitly represented. Results have implications for assimilation of surface water altimetry and for implementation of the approach at the continental scale.
A radon and meteorological measurement network for the Alligator Rivers Region, Australia
Energy Technology Data Exchange (ETDEWEB)
Martin, P. E-mail: paul.martin@deh.gov.au; Tims, S. E-mail: steve.tims@anu.edu.au; Ryan, B. E-mail: bruce.ryan@ea.gov.au; Bollhoefer, A. E-mail: andreas.bollhoefer@ea.gov.au
2004-07-01
The network described in this paper has been set up to provide detailed time-series data on concentrations of {sup 222}Rn in air at various locations within the Alligator Rivers Region, over a time frame of several years. These data will be important in assessing the effects of uranium mining operations on radon levels in the region, both in providing baseline and monitoring data and in calibrating and verifying predictive models. At present, three stations are operating in the region with a fourth being commissioned. Each station logs half hourly average radon concentrations and relevant meteorological data (wind speed, direction and variability, air pressure and temperature, relative humidity, soil temperature, rain and sunshine rates). It is intended to operate the four stations at selected locations for one- or two-year intervals, at the end of which three will be moved to new locations (one station at Mudginberri will be kept as a constant control station). Sites for which extensive datasets are currently available include: Jabiru Town, Jabiru East, Djarr Djarr, East Alligator Ranger Station and Nabarlek minesite. Illustrative data from these sites are presented.
A new information dimension of complex networks
Energy Technology Data Exchange (ETDEWEB)
Wei, Daijun [School of Computer and Information Science, Southwest University, Chongqing 400715 (China); School of Science, Hubei University for Nationalities, Enshi 445000 (China); Wei, Bo [School of Computer and Information Science, Southwest University, Chongqing 400715 (China); Hu, Yong [Institute of Business Intelligence and Knowledge Discovery, Guangdong University of Foreign Studies, Guangzhou 510006 (China); Zhang, Haixin [School of Computer and Information Science, Southwest University, Chongqing 400715 (China); Deng, Yong, E-mail: ydeng@swu.edu.cn [School of Computer and Information Science, Southwest University, Chongqing 400715 (China); School of Engineering, Vanderbilt University, TN 37235 (United States)
2014-03-01
Highlights: •The proposed measure is more practical than the classical information dimension. •The difference of information for box in the box-covering algorithm is considered. •Results indicate the measure can capture the fractal property of complex networks. -- Abstract: The fractal and self-similarity properties are revealed in many complex networks. The classical information dimension is an important method to study fractal and self-similarity properties of planar networks. However, it is not practical for real complex networks. In this Letter, a new information dimension of complex networks is proposed. The nodes number in each box is considered by using the box-covering algorithm of complex networks. The proposed method is applied to calculate the fractal dimensions of some real networks. Our results show that the proposed method is efficient when dealing with the fractal dimension problem of complex networks.
Fractal black holes and information
Energy Technology Data Exchange (ETDEWEB)
El Naschie, M.S. [Department of Physics, University of Alexandria, Alexandria (Egypt); Department of Astrophysics, Cairo University (Egypt); Department of Physics, Mansura University (Egypt)
2006-07-15
If nature is fractal as it evidently is, at classical resolution and if it is suspected to also be fractal at the quantum resolution as it is now a days generally believed to be, then we must have over looked at least two points or so in our physical model building of mini black holes. To start with at such ultra high resolution, the mini black hole geometry must be a fractal. Consequently we have zero volume and only a fractal surface area. Second because we cannot take the differential limit for the -bar {sub p}{sup 2} covering the transfinite surface area, there will be many gaps between the (-bar {sub p}){sup 2} tilings. In other words we must introduce transfinite corrections to the final result. Proceeding this way the information entropy unit of a black hole should be a=I=(7+{phi}{sup 3})(10){sup -66}cm{sup 2}=7.23606799(10){sup -66}cm{sup 2}The nearest classical result to the above is that obtained by Gerard 't Hoofta=I=(0.724)(10){sup -65}cm{sup 2}The paper ends with a general discussion of E-infinity theory and its possible relation with 't Hooft's holographic principle and his gluons-quark strings.
Fractal Characterization of Hyperspectral Imagery
Qiu, Hon-Iie; Lam, Nina Siu-Ngan; Quattrochi, Dale A.; Gamon, John A.
1999-01-01
Two Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral images selected from the Los Angeles area, one representing urban and the other, rural, were used to examine their spatial complexity across their entire spectrum of the remote sensing data. Using the ICAMS (Image Characterization And Modeling System) software, we computed the fractal dimension values via the isarithm and triangular prism methods for all 224 bands in the two AVIRIS scenes. The resultant fractal dimensions reflect changes in image complexity across the spectral range of the hyperspectral images. Both the isarithm and triangular prism methods detect unusually high D values on the spectral bands that fall within the atmospheric absorption and scattering zones where signature to noise ratios are low. Fractal dimensions for the urban area resulted in higher values than for the rural landscape, and the differences between the resulting D values are more distinct in the visible bands. The triangular prism method is sensitive to a few random speckles in the images, leading to a lower dimensionality. On the contrary, the isarithm method will ignore the speckles and focus on the major variation dominating the surface, thus resulting in a higher dimension. It is seen where the fractal curves plotted for the entire bandwidth range of the hyperspectral images could be used to distinguish landscape types as well as for screening noisy bands.
Marks-Tarlow, Terry
2010-01-01
In this article, the author draws on contemporary science to illuminate the relationship between early play experiences, processes of self-development, and the later emergence of the fractal self. She argues that orientation within social space is a primary function of early play and developmentally a two-step process. With other people and with…
Fractals in DNA sequence analysis
Institute of Scientific and Technical Information of China (English)
Yu Zu-Guo(喻祖国); Vo Anh; Gong Zhi-Min(龚志民); Long Shun-Chao(龙顺潮)
2002-01-01
Fractal methods have been successfully used to study many problems in physics, mathematics, engineering, finance,and even in biology. There has been an increasing interest in unravelling the mysteries of DNA; for example, how can we distinguish coding and noncoding sequences, and the problems of classification and evolution relationship of organisms are key problems in bioinformatics. Although much research has been carried out by taking into consideration the long-range correlations in DNA sequences, and the global fractal dimension has been used in these works by other people, the models and methods are somewhat rough and the results are not satisfactory. In recent years, our group has introduced a time series model (statistical point of view) and a visual representation (geometrical point of view)to DNA sequence analysis. We have also used fractal dimension, correlation dimension, the Hurst exponent and the dimension spectrum (multifractal analysis) to discuss problems in this field. In this paper, we introduce these fractal models and methods and the results of DNA sequence analysis.
Heritability of Retinal Vascular Fractals
DEFF Research Database (Denmark)
Vergmann, Anna Stage; Broe, Rebecca; Kessel, Line
2017-01-01
Purpose: To determine the genetic contribution to the pattern of retinal vascular branching expressed by its fractal dimension. Methods: This was a cross-sectional study of 50 monozygotic and 49 dizygotic, same-sex twin pairs aged 20 to 46 years. In 50°, disc-centered fundus photographs, the reti......Purpose: To determine the genetic contribution to the pattern of retinal vascular branching expressed by its fractal dimension. Methods: This was a cross-sectional study of 50 monozygotic and 49 dizygotic, same-sex twin pairs aged 20 to 46 years. In 50°, disc-centered fundus photographs......, the retinal vascular fractal dimension was measured using the box-counting method and compared within monozygotic and dizygotic twin pairs using Pearson correlation coefficients. Falconer's formula and quantitative genetic models were used to determine the genetic component of variation. Results: The mean......, the branching pattern of the retinal vessels demonstrated a higher structural similarity in monozygotic than in dizygotic twin pairs. The retinal vascular fractal dimension was mainly determined by genetic factors, which accounted for 54% of the variation. The genetically predetermination of the retinal...
Thermal transport in fractal systems
DEFF Research Database (Denmark)
Kjems, Jørgen
1992-01-01
Recent experiments on the thermal transport in systems with partial fractal geometry, silica aerogels, are reviewed. The individual contributions from phonons, fractons and particle modes, respectively, have been identified and can be described by quantitative models consistent with heat capacity...... data. The interpretation in the particle mode regime sheds light on the mechanisms for thermal conductivity in normal vitreous silica....
Analysis, Synthesis, and Estimation of Fractal-Rate Stochastic Point Processes
Thurner, S; Feurstein, M C; Heneghan, C; Feichtinger, H G; Teich, M C; Thurner, Stefan; Lowen, Steven B.; Feurstein, Markus C.; Heneghan, Conor; Feichtinger, Hans G.; Teich, Malvin C.
1997-01-01
Fractal and fractal-rate stochastic point processes (FSPPs and FRSPPs) provide useful models for describing a broad range of diverse phenomena, including electron transport in amorphous semiconductors, computer-network traffic, and sequences of neuronal action potentials. A particularly useful statistic of these processes is the fractal exponent $\\alpha$, which may be estimated for any FSPP or FRSPP by using a variety of statistical methods. Simulated FSPPs and FRSPPs consistently exhibit bias in this fractal exponent, however, rendering the study and analysis of these processes non-trivial. In this paper, we examine the synthesis and estimation of FRSPPs by carrying out a systematic series of simulations for several different types of FRSPP over a range of design values for $\\alpha$. The discrepancy between the desired and achieved values of $\\alpha$ is shown to arise from finite data size and from the character of the point-process generation mechanism. In the context of point-process simulation, reduction ...
Directory of Open Access Journals (Sweden)
Chia-Hung Lin
2010-01-01
Full Text Available This paper proposes combining the biometric fractal pattern and particle swarm optimization (PSO-based classifier for fingerprint recognition. Fingerprints have arch, loop, whorl, and accidental morphologies, and embed singular points, resulting in the establishment of fingerprint individuality. An automatic fingerprint identification system consists of two stages: digital image processing (DIP and pattern recognition. DIP is used to convert to binary images, refine out noise, and locate the reference point. For binary images, Katz's algorithm is employed to estimate the fractal dimension (FD from a two-dimensional (2D image. Biometric features are extracted as fractal patterns using different FDs. Probabilistic neural network (PNN as a classifier performs to compare the fractal patterns among the small-scale database. A PSO algorithm is used to tune the optimal parameters and heighten the accuracy. For 30 subjects in the laboratory, the proposed classifier demonstrates greater efficiency and higher accuracy in fingerprint recognition.
Fault Diagnosis Method Based on Fractal Theory and Its Application in Wind Power Systems
Institute of Scientific and Technical Information of China (English)
赵玲; 黄大荣; 宋军
2012-01-01
The non-linear dynamic theory brought a new method for recognizing and predicting complex non-linear dynamic behaviors. The non-linear behavior of vibration signals can be described by using fractal dimension quantitatively. In this paper, a fractal dimension calculation method for discrete signals in the fractal theory was applied to extract the fractal di- mension feature vectors and classified various fault types. Based on the wavelet packet transform, the energy feature vectors were extracted after the vibration signal was decomposed and reconstructed. Then, a wavelet neural network was used to recognize the mechanical faults. Finally, the fault diagnosis for a wind power system was taken as an example to show the method' s feasibility.
Directory of Open Access Journals (Sweden)
A. Piotrowski
2007-12-01
Full Text Available The prediction of temporal concentration profiles of a transported pollutant in a river is still a subject of ongoing research efforts worldwide. The present paper is aimed at studying the possibility of using Multi-Layer Perceptron Neural Networks to evaluate the whole concentration versus time profile at several cross-sections of a river under various flow conditions, using as little information about the river system as possible. In contrast with the earlier neural networks based work on longitudinal dispersion coefficients, this new approach relies more heavily on measurements of concentration collected during tracer tests over a range of flow conditions, but fewer hydraulic and morphological data are needed. The study is based upon 26 tracer experiments performed in a small river in Edinburgh, UK (Murray Burn at various flow rates in a 540 m long reach. The only data used in this study were concentration measurements collected at 4 cross-sections, distances between the cross-sections and the injection site, time, as well as flow rate and water velocity, obtained according to the data measured at the 1st and 2nd cross-sections.
The four main features of concentration versus time profiles at a particular cross-section, namely the peak concentration, the arrival time of the peak at the cross-section, and the shapes of the rising and falling limbs of the profile are modeled, and for each of them a separately designed neural network was used. There was also a variant investigated in which the conservation of the injected mass was assured by adjusting the predicted peak concentration. The neural network methods were compared with the unit peak attenuation curve concept.
In general the neural networks predicted the main features of the concentration profiles satisfactorily. The predicted peak concentrations were generally better than those obtained using the unit peak attenuation method, and the method with mass
Tejedor, A.; Marra, W. A.; Addink, E. A.; Foufoula-Georgiou, E.; Kleinhans, M. G.
2016-12-01
Advancing quantitative understanding of the structure and dynamics of complex networks has transformed research in many fields as diverse as protein interactions in a cell to page connectivity in the World Wide Web and relationships in human societies. However, Geosciences have not benefited much from this new conceptual framework, although connectivity is at the center of many processes in hydro-geomorphology. One of the first efforts in this direction was the seminal work of Smart and Moruzzi (1971), proposing the use of graph theory for studying the intricate structure of delta channel networks. In recent years, this preliminary work has precipitated in a body of research that examines the connectivity of multiple-channel fluvial systems, such as delta networks and braided rivers. In this work, we compare two approaches recently introduced in the literature: (1) Marra et al. (2014) utilized network centrality measures to identify important channels in a braided section of the Jamuna River, and used the changes of bifurcations within the network over time to explain the overall river evolution; and (2) Tejedor et al. (2015a,b) developed a set of metrics to characterize the complexity of deltaic channel networks, as well as defined a vulnerability index that quantifies the relative change of sediment and water delivery to the shoreline outlets in response to upstream perturbations. Here we present a comparative analysis of metrics of centrality and vulnerability applied to both braided and deltaic channel networks to depict critical channels in those systems, i.e., channels where a change would contribute more substantially to overall system changes, and to understand what attributes of interest in a channel network are most succinctly depicted in what metrics. Marra, W. A., Kleinhans, M. G., & Addink, E. A. (2014). Earth Surface Processes and Landforms, doi:10.1002/esp.3482Smart, J. S., and V. L. Moruzzi (1971), Quantitative properties of delta channel networks
Order-fractal transitions in abstract paintings
Energy Technology Data Exchange (ETDEWEB)
Calleja, E.M. de la, E-mail: elsama79@gmail.com [Instituto de Física, Universidade Federal do Rio Grande do Sul, Caixa Postal 15051, 91501-970, Porto Alegre, RS (Brazil); Cervantes, F. [Department of Applied Physics, CINVESTAV-IPN, Carr. Antigua a Progreso km.6, Cordemex, C.P.97310, Mérida, Yucatán (Mexico); Calleja, J. de la [Department of Informatics, Universidad Politécnica de Puebla, 72640 (Mexico)
2016-08-15
In this study, we determined the degree of order for 22 Jackson Pollock paintings using the Hausdorff–Besicovitch fractal dimension. Based on the maximum value of each multi-fractal spectrum, the artworks were classified according to the year in which they were painted. It has been reported that Pollock’s paintings are fractal and that this feature was more evident in his later works. However, our results show that the fractal dimension of these paintings ranges among values close to two. We characterize this behavior as a fractal-order transition. Based on the study of disorder-order transition in physical systems, we interpreted the fractal-order transition via the dark paint strokes in Pollock’s paintings as structured lines that follow a power law measured by the fractal dimension. We determined self-similarity in specific paintings, thereby demonstrating an important dependence on the scale of observations. We also characterized the fractal spectrum for the painting entitled Teri’s Find. We obtained similar spectra for Teri’s Find and Number 5, thereby suggesting that the fractal dimension cannot be rejected completely as a quantitative parameter for authenticating these artworks. -- Highlights: •We determined the degree of order in Jackson Pollock paintings using the Hausdorff–Besicovitch dimension. •We detected a fractal-order transition from Pollock’s paintings between 1947 and 1951. •We suggest that Jackson Pollock could have painted Teri’s Find.
Lung cancer-a fractal viewpoint.
Lennon, Frances E; Cianci, Gianguido C; Cipriani, Nicole A; Hensing, Thomas A; Zhang, Hannah J; Chen, Chin-Tu; Murgu, Septimiu D; Vokes, Everett E; Vannier, Michael W; Salgia, Ravi
2015-11-01
Fractals are mathematical constructs that show self-similarity over a range of scales and non-integer (fractal) dimensions. Owing to these properties, fractal geometry can be used to efficiently estimate the geometrical complexity, and the irregularity of shapes and patterns observed in lung tumour growth (over space or time), whereas the use of traditional Euclidean geometry in such calculations is more challenging. The application of fractal analysis in biomedical imaging and time series has shown considerable promise for measuring processes as varied as heart and respiratory rates, neuronal cell characterization, and vascular development. Despite the advantages of fractal mathematics and numerous studies demonstrating its applicability to lung cancer research, many researchers and clinicians remain unaware of its potential. Therefore, this Review aims to introduce the fundamental basis of fractals and to illustrate how analysis of fractal dimension (FD) and associated measurements, such as lacunarity (texture) can be performed. We describe the fractal nature of the lung and explain why this organ is particularly suited to fractal analysis. Studies that have used fractal analyses to quantify changes in nuclear and chromatin FD in primary and metastatic tumour cells, and clinical imaging studies that correlated changes in the FD of tumours on CT and/or PET images with tumour growth and treatment responses are reviewed. Moreover, the potential use of these techniques in the diagnosis and therapeutic management of lung cancer are discussed.
Fractal patterns of fractures in granites
Velde, B.; Dubois, J.; Moore, D.; Touchard, G.
1991-01-01
Fractal measurements using the Cantor's dust method in a linear one-dimensional analysis mode were made on the fracture patterns revealed on two-dimensional, planar surfaces in four granites. This method allows one to conclude that: 1. (1)|The fracture systems seen on two-dimensional surfaces in granites are consistent with the part of fractal theory that predicts a repetition of patterns on different scales of observation, self similarity. Fractal analysis gives essentially the same values of D on the scale of kilometres, metres and centimetres (five orders of magnitude) using mapped, surface fracture patterns in a Sierra Nevada granite batholith (Mt. Abbot quadrangle, Calif.). 2. (2)|Fractures show the same fractal values at different depths in a given batholith. Mapped fractures (main stage ore veins) at three mining levels (over a 700 m depth interval) of the Boulder batholith, Butte, Mont. show the same fractal values although the fracture disposition appears to be different at different levels. 3. (3)|Different sets of fracture planes in a granite batholith, Central France, and in experimental deformation can have different fractal values. In these examples shear and tension modes have the same fractal values while compressional fractures follow a different fractal mode of failure. The composite fracture patterns are also fractal but with a different, median, fractal value compared to the individual values for the fracture plane sets. These observations indicate that the fractal method can possibly be used to distinguish fractures of different origins in a complex system. It is concluded that granites fracture in a fractal manner which can be followed at many scales. It appears that fracture planes of different origins can be characterized using linear fractal analysis. ?? 1991.
Fliervoet, J. M.; Geerling, G. W.; Mostert, E.; Smits, A. J. M.
2016-02-01
Until recently, governmental organizations played a dominant and decisive role in natural resource management. However, an increasing number of studies indicate that this dominant role is developing towards a more facilitating role as equal partner to improve efficiency and create a leaner state. This approach is characterized by complex collaborative relationships between various actors and sectors on multiple levels. To understand this complexity in the field of environmental management, we conducted a social network analysis of floodplain management in the Dutch Rhine delta. We charted the current interorganizational relationships between 43 organizations involved in flood protection (blue network) and nature management (green network) and explored the consequences of abolishing the central actor in these networks. The discontinuation of this actor will decrease the connectedness of actors within the blue and green network and may therefore have a large impact on the exchange of ideas and decision-making processes. Furthermore, our research shows the dependence of non-governmental actors on the main governmental organizations. It seems that the Dutch governmental organizations still have a dominant and controlling role in floodplain management. This challenges the alleged shift from a dominant government towards collaborative governance and calls for detailed analysis of actual governance.
Fliervoet, J M; Geerling, G W; Mostert, E; Smits, A J M
2016-02-01
Until recently, governmental organizations played a dominant and decisive role in natural resource management. However, an increasing number of studies indicate that this dominant role is developing towards a more facilitating role as equal partner to improve efficiency and create a leaner state. This approach is characterized by complex collaborative relationships between various actors and sectors on multiple levels. To understand this complexity in the field of environmental management, we conducted a social network analysis of floodplain management in the Dutch Rhine delta. We charted the current interorganizational relationships between 43 organizations involved in flood protection (blue network) and nature management (green network) and explored the consequences of abolishing the central actor in these networks. The discontinuation of this actor will decrease the connectedness of actors within the blue and green network and may therefore have a large impact on the exchange of ideas and decision-making processes. Furthermore, our research shows the dependence of non-governmental actors on the main governmental organizations. It seems that the Dutch governmental organizations still have a dominant and controlling role in floodplain management. This challenges the alleged shift from a dominant government towards collaborative governance and calls for detailed analysis of actual governance.
Coupled One and Two Dimensional Model for River Network Flow and Sediment Transport%一二维耦合河网水沙模型研究
Institute of Scientific and Technical Information of China (English)
吕文丽; 张旭
2011-01-01
Based on previous research, a new one and two-dimensional coupled model of river water and sediment was proposed.With reference to the three-level solution for one-dimensional river network water mode, the two-dimensional river section will be generalized to river section within the river network.One and two dimensional coupled river network sediment model will be established with the balance of flow amount and sediment transport.The model sets up the chasing relationship between variables of water level and sediment content at the end and first section to further establish matrix equations of the whole one and two-dimensional river network node water level and sediment content.Though the verification and calculation for generalized river network from Datong to Zhenjiang in the lower reaches of the Yangtze River, it is found that the model is of great practical value.%借鉴河网水流的三级解法,将二维河段概化为河网内部河段,通过河网节点流量和输沙量的平衡,建立一二维耦合河网水沙模型.模型采用全隐式方法建立二维河段以首末断面的水位和含沙量为中间变量的矩阵追赶关系,进而建立整个一二维河网的节点水位及含沙量的矩阵方程组.对方程组的求解,可实现一二维水沙模型的耦合求解.通过对长江下游大通至镇江概化河网的验证计算,表明模型具有很好的实用价值.
Chen, Yun; Yang, Hui
2016-08-01
Engineered and natural systems often involve irregular and self-similar geometric forms, which is called fractal geometry. For instance, precision machining produces a visually flat surface, while which looks like a rough mountain in the nanometer scale under the microscope. Human heart consists of a fractal network of muscle cells, Purkinje fibers, arteries and veins. Cardiac electrical activity exhibits highly nonlinear and fractal behaviors. Although space-time dynamics occur on the fractal geometry, e.g., chemical etching on the surface of machined parts and electrical conduction in the heart, most of existing works modeled space-time dynamics (e.g., reaction, diffusion and propagation) on the Euclidean geometry (e.g., flat planes and rectangular volumes). This brings inaccurate approximation of real-world dynamics, due to sensitive dependence of nonlinear dynamical systems on initial conditions. In this paper, we developed novel methods and tools for the numerical simulation and pattern recognition of spatiotemporal dynamics on fractal surfaces of complex systems, which include (1) characterization and modeling of fractal geometry, (2) fractal-based simulation and modeling of spatiotemporal dynamics, (3) recognizing and quantifying spatiotemporal patterns. Experimental results show that the proposed methods outperform traditional modeling approaches based on the Euclidean geometry, and provide effective tools to model and characterize space-time dynamics on fractal surfaces of complex systems.
Smith, H. G.; Blake, W. H.
2012-04-01
Fine sediment and associated contaminants transported through river networks can have important impacts on water quality, aquatic habitat and ecosystem function long after catchment remediation measures have been implemented. In this context, the potential role of fine sediment as a secondary source of pollution requires attention. Knowledge of fine sediment transfer and storage in river basins is essential for predicting recovery times of rivers affected by historic or contemporary industrial pollution e.g. mining. It is also vital for determining the effectiveness of management actions in reducing the supply of contaminated sediment to coastal ecosystems. Against this background, we aim to determine the residence/travel times of fine sediment through a river network in south-west England. The approach utilises fallout radionuclides (Cs-137, excess Pb-210, Be-7) to (i) infer diffuse sources of sediment and associated contaminants transported in suspension over event and seasonal timescales and (ii) estimate fine sediment residence times based on differences in radioactive decay rates. Information on downstream changes in sediment sources within basins is critical for interpreting residence times using fallout radionuclide data since changes in source type (e.g. surface versus subsurface) may influence residence time signals. Consequently, analysis of sediment sources for a set of nested monitoring sites is coupled with methods for estimating residence time e.g. comparison of Be-7/excess Pb-210 ratios and a two-compartment radionuclide mass balance model comprising slow and rapid transport components. The present study focuses on the River Tamar (917 km2), an agricultural basin with an extensive history of metal mining and legacy of fine sediment contamination. Sampling of land use and channel bank source material across the basin has been undertaken for the sediment source analysis in conjunction with integrated suspended sediment sampling over monthly intervals
Quantum Fractals: From Heisenberg's Uncertainty to Barnsley's Fractality
Jadczyk, Arkadiusz
2014-07-01
This book brings together two concepts. The first is over a hundred years old -- the "quantum", while the second, "fractals", is newer, achieving popularity after the pioneering work of Benoit Mandelbrot. Both areas of research are expanding dramatically day by day. It is somewhat amazing that quantum theory, in spite of its age, is still a boiling mystery as we see in some quotes from recent publications addressed to non-expert readers:...
Fractal analysis of the retinal vasculature and chronic kidney disease.
Sng, Chelvin C A; Sabanayagam, Charumathi; Lamoureux, Ecosse L; Liu, Erica; Lim, Su Chi; Hamzah, Haslina; Lee, Jeannette; Tai, E Shyong; Wong, Tien Y
2010-07-01
BACKGROUND. Fractal analysis provides a global index of the geometric complexity and optimality of vascular networks. In this study, we investigated the relationship between fractal measurements of the retinal vasculature and chronic kidney disease (CKD). METHODS. This was a population-based case-control study which included participants from the Singapore Prospective Study Program. We identified 261 participants with CKD, defined as estimated glomerular filtration rate of fractal dimension (D(f)) was quantified from digitized fundus photographs using a computer-based programme. RESULTS. The mean D(f) was 1.43 +/- 0.048 in the participants with CKD and 1.44 +/- 0.042 in controls (P = 0.013). Suboptimal D(f) in the lowest (first) and highest (fifth) quintiles were associated with an increased prevalence of CKD after adjusting for age, systolic blood pressure, diabetes and other risk factors [odds ratio (OR) 2.10, 95% confidence interval (CI) 1.15, 3.83 and OR 1.84, 95% CI 1.06, 3.17; compared to the fourth quintile, respectively). This association was present even in participants without diabetes or hypertension. CONCLUSIONS. Our study found that an abnormal retinal vascular network is associated with an increased risk of CKD, supporting the hypothesis that deviations from optimal microvascular architecture may be related to kidney damage.
Fractal structures and fractal functions as disease indicators
Escos, J.M; Alados, C.L.; Emlen, J.M.
1995-01-01
Developmental instability is an early indicator of stress, and has been used to monitor the impacts of human disturbance on natural ecosystems. Here we investigate the use of different measures of developmental instability on two species, green peppers (Capsicum annuum), a plant, and Spanish ibex (Capra pyrenaica), an animal. For green peppers we compared the variance in allometric relationship between control plants, and a treatment group infected with the tomato spotted wilt virus. The results show that infected plants have a greater variance about the allometric regression line than the control plants. We also observed a reduction in complexity of branch structure in green pepper with a viral infection. Box-counting fractal dimension of branch architecture declined under stress infection. We also tested the reduction in complexity of behavioral patterns under stress situations in Spanish ibex (Capra pyrenaica). Fractal dimension of head-lift frequency distribution measures predator detection efficiency. This dimension decreased under stressful conditions, such as advanced pregnancy and parasitic infection. Feeding distribution activities reflect food searching efficiency. Power spectral analysis proves to be the most powerful tool for character- izing fractal behavior, revealing a reduction in complexity of time distribution activity under parasitic infection.
Bayesian Models for Streamflow and River Network Reconstruction using Tree Rings
Ravindranath, A.; Devineni, N.
2016-12-01
Water systems face non-stationary, dynamically shifting risks due to shifting societal conditions and systematic long-term variations in climate manifesting as quasi-periodic behavior on multi-decadal time scales. Water systems are thus vulnerable to long periods of wet or dry hydroclimatic conditions. Streamflow is a major component of water systems and a primary means by which water is transported to serve ecosystems' and human needs. Thus, our concern is in understanding streamflow variability. Climate variability and impacts on water resources are crucial factors affecting streamflow, and multi-scale variability increases risk to water sustainability and systems. Dam operations are necessary for collecting water brought by streamflow while maintaining downstream ecological health. Rules governing dam operations are based on streamflow records that are woefully short compared to periods of systematic variation present in the climatic factors driving streamflow variability and non-stationarity. We use hierarchical Bayesian regression methods in order to reconstruct paleo-streamflow records for dams within a basin using paleoclimate proxies (e.g. tree rings) to guide the reconstructions. The riverine flow network for the entire basin is subsequently modeled hierarchically using feeder stream and tributary flows. This is a starting point in analyzing streamflow variability and risks to water systems, and developing a scientifically-informed dynamic risk management framework for formulating dam operations and water policies to best hedge such risks. We will apply this work to the Missouri and Delaware River Basins (DRB). Preliminary results of streamflow reconstructions for eight dams in the upper DRB using standard Gaussian regression with regional tree ring chronologies give streamflow records that now span two to two and a half centuries, and modestly smoothed versions of these reconstructed flows indicate physically-justifiable trends in the time series.
Directory of Open Access Journals (Sweden)
Zhensheng Wang
2017-06-01
Full Text Available Measuring the spatial distribution of heavy metal contaminants is the basis of pollution evaluation and risk control. Considering the cost of soil sampling and analysis, spatial interpolation methods have been widely applied to estimate the heavy metal concentrations at unsampled locations. However, traditional spatial interpolation methods assume the sample sites can be located stochastically on a plane and the spatial association between sample locations is analyzed using Euclidean distances, which may lead to biased conclusions in some circumstances. This study aims to analyze the spatial distribution characteristics of copper and lead contamination in river sediments of Daye using network spatial analysis methods. The results demonstrate that network inverse distance weighted interpolation methods are more accurate than planar interpolation methods. Furthermore, the method named local indicators of network-constrained clusters based on local Moran’ I statistic (ILINCS is applied to explore the local spatial patterns of copper and lead pollution in river sediments, which is helpful for identifying the contaminated areas and assessing heavy metal pollution of Daye.
Hao, Rui; Zhang, Jin-Feng; Huo, Jie; Wang, Xu-Ming
2007-03-01
We constructed a model to describe the sediment transportation on the river network, which can indicate what state, scouring or deposition, will appear when the system, under certain conditions, evolves after a long time period and finally becomes stable. In the model a river segment, say the ith segment, can be classified into three types. The first one is actively- modulation type where the so-called impact factor of ith segment is larger than that of (i-1)th. The second one is passively- modulation type where the impact factor of ith segment is smaller. The third one is freely-modulation type where the two impact factors are equivalent. For the first type, the states, scouring or depositing, of the segments of the upriver are qualitatively the same as that the river source, while the states of the downriver change and distribute disorderly. For the second type, the states along a lone part of the river can qualitatively keep the same state as that of the source. A simpler case will appear in the third type: the state of the scouring or depositing on each segment equals, and are same as that of the source.
Keyantash, J.; Quinn, N. W.; Hidalgo, H. G.; Dracup, J. A.
2002-12-01
The number of chinook salmon returning to spawn during the fall run (September-November) were separately modeled for three San Joaquin River tributaries-the Stanislaus, Tuolumne, and Merced Rivers-to determine the sensitivity of salmon populations to hydrologic alterations associated with potential climate change. The modeling was accomplished using a feed-forward artificial neural network (ANN) with error backpropagation. Inputs to the ANN included modeled monthly river temperature and streamflow data for each tributary, and were lagged multiple years to include the effects of antecedent environmental conditions upon populations of salmon throughout their life histories. Temperature and streamflow conditions at downstream locations in each tributary were computed using the California Dept. of Water Resources' DSM-2 model. Inputs to the DSM-2 model originated from regional climate modeling under a CO2 doubling scenario. Annual population data for adult chinook salmon (1951-present) were provided by the California Dept. of Fish and Game, and were used for supervised training of the ANN. It was determined that Stanislaus, Tuolumne and Merced River chinook runs could be impacted by alterations to the hydroclimatology of the San Joaquin basin.
Relationship among resonant frequencies of Sierpinski multiband fractal antennas
Directory of Open Access Journals (Sweden)
Gonzalez-Rangel Ivan R.
2017-01-01
Full Text Available In this paper, the relationships between the different resonance frequencies of Sierpinski fractal antennas of four-iterations are studied. In particular, Sierpinski fractal antennas with operating frequencies of the initial triangle of 250 MHz, 350 MHz and 530 MHz were designed and built. The antennas are made of copper tablets with bakelite substrate. The performance of the designed antennas is measured in terms of return losses. The return losses are obtained experimentally with a “RFX” system that measures antenna parameters in conjunction with a network analyzer. These results are compared with numerical simulations of commercial finite-element program that analyzes high frequency electromagnetic structures “HFSS”. Experimental and simulation results show that there is approximately a factor of 2 between the resonance frequencies of the first and second iterations and the second and third iterations.
Flocculation control study based on fractal theory
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
A study on flocculation control based on fractal theory was carried out. Optimization test of chemical coagulant dosage confirmed that the fractal dimension could reflect the flocculation degree and settling characteristics of aggregates and the good correlation with the turbidity of settled effluent. So that the fractal dimension can be used as the major parameter for flocculation system control and achieve self-acting adjustment of chemical coagulant dosage. The fractal dimension flocculation control system was used for further study carried out on the effects of various flocculation parameters, among which are the dependency relationship among aggregates fractal dimension, chemical coagulant dosage, and turbidity of settled effluent under the conditions of variable water quality and quantity. And basic experimental data were obtained for establishing the chemical coagulant dosage control model mainly based on aggregates fractal dimension.
FRACTAL KINEMATICS OF CRACK PROPAGATION IN GEOMATERIALS
Institute of Scientific and Technical Information of China (English)
谢和平
1995-01-01
Experimental results indicate that propagation paths of cracks in geomaterials are often irregular, producing rough fracture surfaces which are fractal. A formula is derived for the fractal kinematics of crack propagation in geomaterials. The formula correlates the dynamic and static fracture toughnesses with crack velocity, crack length and a microstructural parameter, and allows the fractal dimension to be obtained. From the equations for estimating crack velocity and fractal dimension it can be shown that the measured crack velocity, Vo , should be much smaller than the fractal crack velocity, V. It can also be shown that the fractal dimension of the crack propagation path can be calculated directly from Vo and from the fracture toughness.
Conference on Fractals and Related Fields III
Seuret, Stéphane
2017-01-01
This contributed volume provides readers with an overview of the most recent developments in the mathematical fields related to fractals, including both original research contributions, as well as surveys from many of the leading experts on modern fractal theory and applications. It is an outgrowth of the Conference of Fractals and Related Fields III, that was held on September 19-25, 2015 in île de Porquerolles, France. Chapters cover fields related to fractals such as harmonic analysis, multifractal analysis, geometric measure theory, ergodic theory and dynamical systems, probability theory, number theory, wavelets, potential theory, partial differential equations, fractal tilings, combinatorics, and signal and image processing. The book is aimed at pure and applied mathematicians in these areas, as well as other researchers interested in discovering the fractal domain.
Institute of Scientific and Technical Information of China (English)
李斌斌; 李占斌; 李鹏
2015-01-01
for each other. We computerize the difference of NDVI values between each pixel point and the center pixel point in each cell. We calculate NDVI increment value of the watershed points at a certain spatial scale by the moving window statistical method, then computerize mathematics expectations of measure collection, which is composed of all NDVI incremental values. To study the characteristics of fractal dimension of the vegetation cover and its variation at different scales, it is divided into 4 scales according to the area of the basin, with 5 phases per level. The first level is the entire Dali River basin with an area of 3 906 km2, approximately 5 million times of pixel size (30 m × 30 m). At the second stage, Dali River basin will be divided into 3 parts i.e. upstream, midstream and downstream, with an average area of approximately 1 000 km2, approximately 1 million times of pixel size (30 m × 30 m). At the third stage, it will be divided into 14 small basins of Dali River, with an area of 179.4-392.5 km2, about 200 thousand times of pixel size (30 m × 30 m). At the fourth stage, it will be divided into 53 small basins of Dali River (No.1 to 53), with an area of 21.9-108.9 km2, about 40 thousand times of pixel size (30 m × 30 m). Firstly, on the basis of information source from 5 issues of TM/ETM images from 1990 to 2006, the image data are processed, the vegetation information at basin stage is extracted by the platform of geographic information system (GIS), and then watershed DVM is established. FBM (fractional brownian motion) fractal dimension for watershed vegetation cover is between 2.7311 and 2.8499. By calculation and analysis, vegetation cover FBM fractal dimension is increasing from upstream to downstream, so vegetation distribution is more uniform from upstream to downstream. Vegetation cover fractal dimension is increasing with the watershed area. Through analyzing spatial and temporal variation of each sub-watershed at all levels, it presents
Fractal THz slow light metamaterial devices
Ito, Shoichi
Scope and Method of Study: The goal of this study is to investigate the time delay of the fractal H metamaterials in the terahertz regime. This metamaterial contains resonators with two different sizes of H structures which mimic Electromagnetically Induced Transparency and create a transmission window and the corresponding phase dispersion, thus producing slow light. The Al structures were fabricated on silicon wafer and Mylar by using microelectronic lithography and thermal evaporation technique. By using terahertz time-domain spectroscopy, the phase change caused by the slow light system and the actual time delay were obtained. Numerical simulations were carried out to systematize the effect of permittivity and structure dimensions on the optical properties. Findings and Conclusions: We experimentally demonstrated the numerical time delay of the fractal H metamaterial as a slow light device. When permittivity of the substrates increases, the peak position of the transmission window shifts to lower frequency and the bandwidth becomes broader. As a result, silicon performed larger time delay than that of Mylar. By changing the length of the resonator, the bandwidth and the peak position of the transmission window is controllable. At the edges of the transmission window, the negative time delays (fast light) were also observed. Mylar acts as a quaci-free standing structure and allows higher spectral measurement. Moreover, metamaterials fabricated on multiple Mylar films can potentially act as a more effective slow light device. As applications, slow light metamaterials are expected to be used for high-capacity terahertz communication networks, all-optical information processing and sensing devices.
The fractal dimension of architecture
Ostwald, Michael J
2016-01-01
Fractal analysis is a method for measuring, analysing and comparing the formal or geometric properties of complex objects. In this book it is used to investigate eighty-five buildings that have been designed by some of the twentieth-century’s most respected and celebrated architects. Including designs by Le Corbusier, Eileen Gray, Frank Lloyd Wright, Robert Venturi, Frank Gehry, Peter Eisenman, Richard Meier and Kazuyo Sejima amongst others, this book uses mathematics to analyse arguments and theories about some of the world’s most famous designs. Starting with 625 reconstructed architectural plans and elevations, and including more than 200 specially prepared views of famous buildings, this book presents the results of the largest mathematical study ever undertaken into architectural design and the largest single application of fractal analysis presented in any field. The data derived from this study is used to test three overarching hypotheses about social, stylistic and personal trends in design, along...
Chaos, Fractals and Their Applications
Thompson, J. Michael T.
2016-12-01
This paper gives an up-to-date account of chaos and fractals, in a popular pictorial style for the general scientific reader. A brief historical account covers the development of the subject from Newton’s laws of motion to the astronomy of Poincaré and the weather forecasting of Lorenz. Emphasis is given to the important underlying concepts, embracing the fractal properties of coastlines and the logistics of population dynamics. A wide variety of applications include: NASA’s discovery and use of zero-fuel chaotic “superhighways” between the planets; erratic chaotic solutions generated by Euler’s method in mathematics; atomic force microscopy; spontaneous pattern formation in chemical and biological systems; impact mechanics in offshore engineering and the chatter of cutting tools; controlling chaotic heartbeats. Reference is made to a number of interactive simulations and movies accessible on the web.
Fractal model of anomalous diffusion.
Gmachowski, Lech
2015-12-01
An equation of motion is derived from fractal analysis of the Brownian particle trajectory in which the asymptotic fractal dimension of the trajectory has a required value. The formula makes it possible to calculate the time dependence of the mean square displacement for both short and long periods when the molecule diffuses anomalously. The anomalous diffusion which occurs after long periods is characterized by two variables, the transport coefficient and the anomalous diffusion exponent. An explicit formula is derived for the transport coefficient, which is related to the diffusion constant, as dependent on the Brownian step time, and the anomalous diffusion exponent. The model makes it possible to deduce anomalous diffusion properties from experimental data obtained even for short time periods and to estimate the transport coefficient in systems for which the diffusion behavior has been investigated. The results were confirmed for both sub and super-diffusion.
Fractal properties of financial markets
Budinski-Petković, Lj.; Lončarević, I.; Jakšić, Z. M.; Vrhovac, S. B.
2014-09-01
We present an analysis of the USA stock market using a simple fractal function. Financial bubbles preceding the 1987, 2000 and 2007 crashes are investigated using the Besicovitch-Ursell fractal function. Fits show a good agreement with the S&P 500 data when a complete financial growth is considered, starting at the threshold of the abrupt growth and ending at the peak. Moving the final time of the fitting interval towards earlier dates causes growing discrepancy between two curves. On the basis of a detailed analysis of the financial index behavior we propose a method for identifying the stage of the current financial growth and estimating the time in which the index value is going to reach the maximum.
Spatial patterns in CO2 evasion from the global river network
Lauerwald, Ronny; Laruelle, Goulven G.|info:eu-repo/dai/nl/304837830; Hartmann, Jens; Ciais, Philippe; Regnier, Pierre A G|info:eu-repo/dai/nl/304829404
CO2 evasion from rivers (FCO2) is an important component of the global carbon budget. Here we present the first global maps of CO2 partial pressures (pCO2) in rivers of stream orders 3 and higher and the resulting FCO2 at 0.5° resolution constructed with a statistical model. A geographic information
Spatial patterns in CO2 evasion from the global river network
Lauerwald, Ronny; Laruelle, Goulven G.|info:eu-repo/dai/nl/304837830; Hartmann, Jens; Ciais, Philippe; Regnier, Pierre A G|info:eu-repo/dai/nl/304829404
2015-01-01
CO2 evasion from rivers (FCO2) is an important component of the global carbon budget. Here we present the first global maps of CO2 partial pressures (pCO2) in rivers of stream orders 3 and higher and the resulting FCO2 at 0.5° resolution constructed with a statistical model. A geographic information
Fractal methods in image analysis and coding
Neary, David
2001-01-01
In this thesis we present an overview of image processing techniques which use fractal methods in some way. We show how these fields relate to each other, and examine various aspects of fractal methods in each area. The three principal fields of image processing and analysis th a t we examine are texture classification, image segmentation and image coding. In the area of texture classification, we examine fractal dimension estimators, comparing these methods to other methods in use, a...
Fractal characteristics of electric properties of coal
Institute of Scientific and Technical Information of China (English)
LIU Cheng-lun; XU Long-jun; XIAN Xue-fu
2006-01-01
In the light of fractal geometry theory, the characteristics of coal's electric parameters (including dielectric constant, alternating conductivity, dielectric loss angle tangent and electric polarization constant) were studied by using literature data. The results are shown that the electrical properties of coal have fractal characteristic. The fractal dimensions of dielectric, alternating conductivity, dielectric loss angle tangent were obtained, and are relative to the content of pyrite sulfur, heat and ash content of coal.
Wideband irregular-shaped fractal antennas
Kolesov, V. V.; Krupenin, S. V.
2007-01-01
This paper proposes an algorithm of generating fully reproducible irregular fractal structures for antenna design. Three types of pseudorandom fractal clusters are introduced. The multi-frequency behavior of the irregular-shaped fractal antennas is studied by means of numerical analysis. The antenna behavior is studied under feeder displacement. As shown by numerical results feeder displacements allow one to control the spatial-frequency antenna characteristics.
Fractals and Scars on a Compact Octagon
Levin, J; Levin, Janna; Barrow, John D.
2000-01-01
A finite universe naturally supports chaotic classical motion. An ordered fractal emerges from the chaotic dynamics which we characterize in full for a compact 2-dimensional octagon. In the classical to quantum transition, the underlying fractal can persist in the form of scars, ridges of enhanced amplitude in the semiclassical wave function. Although the scarring is weak on the octagon, we suggest possible subtle implications of fractals and scars in a finite universe.