Identification of physical processes inherent in artificial neural network rainfall runoff models

The emergence of artificial neural network (ANN) technology has provided many promising results in the field of hydrology and water resources simulation. However, one of the major criticisms of ANN hydrologic models is that they do not consider/explain the underlying physical processes in a watershed, resulting in them being labelled as black‐box models. This paper discusses a research study conducted in order to examine whether or not the physical processes in a watershed are inherent in a trained ANN rainfall‐runoff model. The investigation is based on analysing definite statistical measures of strength of relationship between the disintegrated hidden neuron responses of an ANN model and its input variables, as well as various deterministic components of a conceptual rainfall‐runoff model. The approach is illustrated by presenting a case study for the Kentucky River watershed. The results suggest that the distributed structure of the ANN is able to capture certain physical behaviour of the rainfall‐runoff process. The results demonstrate that the hidden neurons in the ANN rainfall‐runoff model approximate various components of the hydrologic system, such as infiltration, base flow, and delayed and quick surface flow, etc., and represent the rising limb and different portions of the falling limb of a flow hydrograph. Copyright © 2004 John Wiley & Sons, Ltd.     

EMERGY ANALYSIS OF GRAIN PRODUCTION SYSTEM IN JIANGSU AND SHAANXI PROVINCE

1INTRODUCTIONGrain production has always been top-priority issue con-cerned by government and people (MA etal., 2002). Af-ter China put household contract responsibility system in force, its domestic issue of grain was basically settled in the mid 1980s (MA and XU, 1999). However, in the days when idea of sustainable development is broadly accepted, efficiency and sustainability of grain produc-tion are now in question, which have prompted interest in reviewing grain production patterns…     

Automatic Determination of Stellar Atmospheric Parameters Using Neural Networks and Instance-Based Machine Learning

In this article we show how machine learning methods can beeffectively applied to the problem of automatically predictingstellar atmospheric parameters from spectral information, a veryimportant problem in stellar astronomy. We apply feedforwardneural networks, Kohonen's self-organizing maps andlocally-weighted regression to predict the stellar atmosphericparameters effective temperature, surface gravity and metallicityfrom spectral indices. Our experimental results show that thethree methods are capable of predicting the parameters with verygood accuracy. Locally weighted regression gives slightly betterresults than the other methods using the original dataset asinput, while self-organizing maps outperform the other methods when significant amounts of noise are added. We also implemented a heterogeneous ensemble of predictors, combining the results given by the three algorithms. This ensemble yields better results than any of the three algorithms alone, using both the original and the noisy data.     

Observations on the ecological importance of salt marshes in the Cumberland Basin,a macrotidal estuary in the Bay of Fundy

The Cumberland Basin, a 118 km² estuary at the head of the Bay of Fundy which has an average tidal range of about 11m, contains large tracts of salt marsh (15% of the area below highest high water). Low marsh (below about 0·9 m above mean high water) is composed almost exclusively of Spartina alterniflora while the vegetation on high marsh is more diverse but dominated by Spartina patens. Because of its higher elevation, high marsh is flooded infrequently for short periods by only extreme high tides. Low marsh is inundated much more frequently by water as much as 4m deep for periods as long as 4 h per tide. Temporal variability in the occurrence of extreme tides influences the flooding frequency of high marsh for any given month and year. Using a modification of Smalley's method, the mean annual net aerial primary production (NAPP) of low and high marsh is estimated to be 272 and 172 g C m^?2, respectively. Vegetation turnover times average 1·0 and 2·0 y for low and high marsh, respectively. Because of abundant tidal energy, much of the low marsh production appears to be exported and distributed widely about the estuary. Since high levels of turbidity suppress phytoplankton production, salt marshes produce approximately half of the carbon fixed photosynthetically in the Cumberland Basin. It is concluded that salt marshes play a major ecological role in the Cumberland Basin.     

Reliability assessment of serviceability performance of braced retaining walls using a neural network approach

In urban environments, one major concern with deep excavations in soft clay is the potentially large ground deformations in and around the excavation. Excessive movements can damage adjacent buildings and utilities. There are many uncertainties associated with the calculation of the ultimate or serviceability performance of a braced excavation system. These include the variabilities of the loadings, geotechnical soil properties, and engineering and geometrical properties of the wall. A risk‐based approach to serviceability performance failure is necessary to incorporate systematically the uncertainties associated with the various design parameters. This paper demonstrates the use of an integrated neural network–reliability method to assess the risk of serviceability failure through the calculation of the reliability index. By first performing a series of parametric studies using the finite element method and then approximating the non‐linear limit state surface (the boundary separating the safe and ‘failure’ domains) through a neural network model, the reliability index can be determined with the aid of a spreadsheet. Two illustrative examples are presented to show how the serviceability performance for braced excavation problems can be assessed using the reliability index. Copyright © 2005 John Wiley & Sons, Ltd.     

Natural recolonization of a productive tropical pond: Day to day variations in the photosynthetic parameters

Chlorophyll pigments (CHL), primary productivity (PP) and particulate nitrogen (N_p) in relation to several environmental factors were monitored during planktonic colonization of an aquaculture pond (Layo, Côte d'Ivoire). How interactions between the organisms are established in an initially azoic environment were investigated. From March, 15 (D1) to March, 31 (D16), the system transformation went through three stages. First, a precolonization by heterotrophic microbial community from D1 to D2 (N_p < 1 m maximum at D2: 243 mg m^–2; CHL around 0). Then, a pioneer microalgal community developped from D3 to D7 (maximum CHL on D6: 19 mg m^–2; PP: 1.0 g C m^–2 d^–1) with a significant contribution of picoplankton (CHL and PP < 3 m: 33 and 23% of the total, respectively). Finally, a second microalgal colonization was noticed from D9 to D12 (maximum CHL: 55 mg m^–2, PP: 2.8 g C m^–2 d^–1), largely dominated by nanoplankton (CHL and PP > 3 m: 95 and 99% of the total, respectively). Overall, photosynthetic activity appeared to be closely linked to algal biomass. The study of autotrophic biomass and activity in different size classes in relation to the other parameters allowed us to precise the origin of the biomass fluctuations. The first bloom appeared to be controlled by selective grazing on small algae. The second algal development ended when N requirement represented at least 69% of N supply (in the N — NH₄ form). This control was enhanced by the appearance of rotifers, leading to a more complex equilibrium.     

Water and power networks and urban fragmentation in Los Angeles: Rethinking assumed mechanisms

Los Angeles is often described as the epitome of urban fragmentation, a notion which in this context is frequently connected to, or even conflated with urban sprawl. At the same time, the city features integrated water and power networks which have been under public ownership for over 70 years. We thus have an apparent paradox in the context of the debate on ‘splintering urbanism’, between socio-spatial fragmentation and the integration of networks. In discussing the idea that deregulation of infrastructural networks exacerbates urban fragmentation, the authors use the case of Los Angeles in order to highlight the central role of private interests in management decisions concerning infrastructure networks. The authors carry out their analysis in an historical perspective, revealing that network integration and universal access can often serve private interests more than the public good. Urban fragmentation in Los Angeles, they conclude, is the result of a complex process of instrumentalisation of network development and management.     

Church-based social capital, networks and geographical scale: Katrina evacuation, relocation, and recovery in a New Orleans Vietnamese American community

This research examines the role of social capital and networks to explain the evacuation, relocation, and recovery experiences of a Vietnamese American community in New Orleans, Louisiana in the aftermath of Hurricane Katrina. As the single largest community institution, the parish church’s complex bonding and bridging social capital and networks proved particularly critical in part because of its historically based ontological security. The process of evacuation, but especially relocation and recovery, was dependent on deploying co-ethnic social capital and networks at a variety of geographical scales. Beyond the local or community scale, extra-local, regional, and national scales of social capital and networks reproduced a spatially redefined Vietnamese American community. Part of the recovery process included constructing discursive place-based collective-action frames to successfully contest a nearby landfill that in turn engendered social capital and networks crossing ethnic boundaries to include the extra-local African American community. Engaging social capital and networks beyond the local geographical scale cultivated a Vietnamese American community with an emergent post-Katrina cultural and political identity.     

北方泥炭沼泽中酚类物质释放的热敏感性研究:以英国威尔士地区雨养和矿养泥炭沼泽为例

利用高精度多梯度热培养系统,对英国威尔士地区两类典型的北方泥炭沼泽中酚类物质和溶解有机碳释放的热敏感性进行了为期1年的调查研究.研究结果表明,雨养泥炭沼泽(Bog)酚类物质释放的热敏感性Q10(总酚)月变化为0.92～1.57,而矿养泥炭沼泽(Fen)的月变化范围为0.93～1.30.酚类释放的热敏感性与土壤温度大致呈正相关关系.此外,土壤温度与溶解有机碳释放的热敏感性Q10(DOC)也呈正相关关系.总体上,雨养泥炭沼泽的热敏感性比矿养泥炭沼泽略高.除温度外,水文条件和植被等多种环境因子对酚类物质和溶解有机碳释放的热敏感性也有较大影响.研究结果还表明酚碳热敏感性比值Q10o(总酚)/Q10(DOC)相对稳定,土壤温度的变化对其影响有限.     

Identifying China’s leading world city: a network approach

This paper reports our research on China’s world cities. Formal network analysis of air passenger linkages for recent years among China’s most populous cities and among many of the world’s largest cities allows us to identify the country’s leading world city from among the leading Mainland candidates, Beijing, Shanghai and Guangzhou. We theorize our findings about China’s world cities in relation to both global forces (and China’s increasing entanglement with them) and the policies and actions of the national state. We examine the national and global urban network through a longitudinal, two-level analysis of airline passenger travel for four time points between about 1990 and 2005. We show that Beijing was China’s leading world city at the beginning of the time period, a status it lost nationally in as early as 1995, and then globally 10 years later. On the other hand Shanghai became China’s leading world city, and it acquired this status first nationally in 2000, and then globally in 2005. The changing status of the Chinese capital corresponds to the country’s increasing involvement with the capitalist world economy. Shanghai’s ascendance as the leading world city in China may indicate that global forces have come to play an increasingly important role relative to that of the developmental state.