Estimation of total sediment load concentration obtained by experimental study using artificial neural networks

Estimation of sediment concentration in rivers is very important for water resources projects planning and managements. The sediment concentration is generally determined from the direct measurement of sediment concentration of river or from sediment transport equations. Direct measurement is very expensive and cannot be conducted for all river gauge stations. However, sediment transport equations do not agree with each other and require many detailed data on the flow and sediment characteristics. The main purpose of the study is to establish an effective model which includes nonlinear relations between dependent (total sediment load concentration) and independent (bed slope, flow discharge, and sediment particle size) variables. In the present study, by performing 60 experiments for various independent data, dependent variables were obtained, because of the complexity of the phenomena, as a soft computing method artificial neural networks (ANNs) which is the powerful tool for input–output mapping is used. However, ANN model was compared with total sediment transport equations. The results show that ANN model is found to be significantly superior to total sediment transport equations.     

Potential Impacts of Global Warming on the Diversity and Distribution of Stream Insects in South Korea

Globally, the East Asian monsoon region is one of the richest environments in terms of biodiversity. The region is undergoing rapid human development, yet its river ecosystems have not been well studied. Global warming represents a major challenge to the survival of species in this region and makes it necessary to assess and reduce the potential consequences of warming on species of conservation concern. We projected the effects of global warming on stream insect (Ephemeroptera, Odonata, Plecoptera, and Trichoptera [EOPT]) diversity and predicted the changes of geographical ranges for 121 species throughout South Korea. Plecoptera was the most sensitive (decrease of 71.4% in number of species from the 2000s through the 2080s) order, whereas Odonata benefited (increase of 66.7% in number of species from the 2000s through the 2080s) from the effects of global warming. The impact of global warming on stream insects was predicted to be minimal prior to the 2060s; however, by the 2080s, species extirpation of up to 20% in the highland areas and 2% in the lowland areas were predicted. The projected responses of stream insects under global warming indicated that species occupying specific habitats could undergo major reductions in habitat. Nevertheless, habitat of 33% of EOPT (including two‐thirds of Odonata and one‐third of Ephemeroptera, Plecoptera, and Trichoptera) was predicted to increase due to global warming. The community compositions predicted by generalized additive models varied over this century, and a large difference in community structure in the highland areas was predicted between the 2000s and the 2080s. However, stream insect communities, especially Odonata, Plecoptera, and Trichoptera, were predicted to become more homogenous under global warming. Impacto Potencial del Calentamiento Global sobre la Diversidad y la Distribución de Insectos de Arroyo en Corea del Sur     

A spatially explicit estimate of the prewhaling abundance of the endangered North Atlantic right whale

The North Atlantic right whale (NARW) (Eubalaena glacialis) is one of the world's most threatened whales. It came close to extinction after nearly a millennium of exploitation and currently persists as a population of only approximately 500 individuals. Setting appropriate conservation targets for this species requires an understanding of its historical population size, as a baseline for measuring levels of depletion and progress toward recovery. This is made difficult by the scarcity of records over this species’ long whaling history. We sought to estimate the preexploitation population size of the North Atlantic right whale and understand how this species was distributed across its range. We used a spatially explicit data set on historical catches of North Pacific right whales (NPRWs) (Eubalaena japonica) to model the relationship between right whale relative density and the environment during the summer feeding season. Assuming the 2 right whale species select similar environments, we projected this model to the North Atlantic to predict how the relative abundance of NARWs varied across their range. We calibrated these relative abundances with estimates of the NPRW total prewhaling population size to obtain high and low estimates for the overall NARW population size prior to exploitation. The model predicted 9,075–21,328 right whales in the North Atlantic. The current NARW population is thus <6% of the historical North Atlantic carrying capacity and has enormous potential for recovery. According to the model, in June–September NARWs concentrated in 2 main feeding areas: east of the Grand Banks of Newfoundland and in the Norwegian Sea. These 2 areas may become important in the future as feeding grounds and may already be used more regularly by this endangered species than is thought.     

Most Influential Parameters for the Bed-Load Sediment Flux Equations Used in Alluvial Rivers1

Khorram, Saeed and Mustafa Ergil, 2010. Most Influential Parameters for the Bed-Load Sediment Flux Equations Used in Alluvial Rivers. Journal of the American Water Resources Association (JAWRA): 46(6):1065–1090. DOI: 10.1111/j.1752-1688.2010.00468.x Abstract: Problems of bed-load sediment transport equations in alluvial rivers are addressed in this study where user-friendly parameters were developed. To determine the influences of 300 parameters on the final result, 52 selected bed-load equations for noncohesive particles (sand and gravel separately) were gathered and individually investigated. The influences of discrepancies among the computed and measured datasets were obtained by sensitivity analysis through multilinear regression method. The most influential parameters for the bed-load sediment flux equations used to describe sand particles in alluvial rivers are: the gravitational power due to Shields’ parameter with an energy slope, the universal stream power due to critical Shields’ parameter with an energy slope, the Shields’ parameter ratio, the critical unit stream power, and the Shields’ parameter with energy slope. For gravel particles, the most influential parameters are: the universal stream power due to critical Shields’ parameter with an energy slope, the Shields’ parameter ratio, the gravitational power due to Shields’ parameter with an energy slope, the Shields’ parameter with an energy slope, and the Froude number of the channel. It is expected that researchers working in this field will be able to use these predicted parameters to generate new bed-load sediment flux equations that give results that more closely agree with the actual values measured in alluvial rivers.     

秦皇岛地区干旱趋势分析及人工增雨条件

通过分析秦皇岛地区水资源及人均占有率、气候干旱化之现状及秦皇岛地区降水的特点,发现秦皇岛降水有明显日变化特征（凌晨1～2时和傍晚17～18时降水量较大）。从化学制剂的选择、碘化银成核环境确定、积云增雨的高度判断三个方面提出了人工增雨作业条件,在作业实践中取得了良好效果。     

Assessing Linkages in Stream Habitat,Geomorphic Condition,and Biological Integrity Using a Generalized Regression Neural Network

Watershed managers often use physical geomorphic and habitat assessments in making decisions about the biological integrity of a stream, and to reduce the cost and time for identifying stream stressors and developing mitigation strategies. Such analysis is difficult since the complex linkages between reach‐scale geomorphic and habitat conditions, and biological integrity are not fully understood. We evaluate the effectiveness of a generalized regression neural network (GRNN) to predict biological integrity using physical (i.e., geomorphic and habitat) stream‐reach assessment data. The method is first tested using geomorphic assessments to predict habitat condition for 1,292 stream reaches from the Vermont Agency of Natural Resources. The GRNN methodology outperforms linear regression (69% vs. 40% classified correctly) and improves slightly (70% correct) with additional data on channel evolution. Analysis of a subset of the reaches where physical assessments are used to predict biological integrity shows no significant linear correlation, however the GRNN predicted 48% of the fish health data and 23% of macroinvertebrate health. Although the GRNN is superior to linear regression, these results show linking physical and biological health remains challenging. Reasons for lack of agreement, including spatial and temporal scale differences, are discussed. We show the GRNN to be a data‐driven tool that can assist watershed managers with large quantities of complex, nonlinear data.     

Logging Concessions Can Extend the Conservation Estate for Central African Tropical Forests

Abstract:  The management of tropical forest in timber concessions has been proposed as a solution to prevent further biodiversity loss. The effectiveness of this strategy will likely depend on species-specific, population-level responses to logging. We conducted a survey (749 line transects over 3450 km) in logging concessions (1.2 million ha) in the northern Republic of Congo to examine the impact of logging on large mammal populations, including endangered species such as the elephant ( Loxodonta africana ), gorilla ( Gorilla gorilla ), chimpanzee ( Pan troglodytes ), and bongo ( Tragelaphus eurycerus ). When we estimated species abundance without consideration of transect characteristics, species abundances in logged and unlogged forests were not different for most species. When we modeled the data with a hurdle model approach, however, analyzing species presence and conditional abundance separately with generalized additive models and then combining them to calculate the mean species abundance, species abundance varied strongly depending on transect characteristics. The mean species abundance was often related to the distance to unlogged forest, which suggests that intact forest serves as source habitat for several species. The mean species abundance responded nonlinearly to logging history, changing over 30 years as the forest recovered from logging. Finally the distance away from roads, natural forest clearings, and villages also determined the abundance of mammals. Our results suggest that logged forest can extend the conservation estate for many of Central Africa's most threatened species if managed appropriately. In addition to limiting hunting, logging concessions must be large, contain patches of unlogged forest, and include forest with different logging histories.     

Bayesian Nonstationary Frequency Analysis of Hydrological Variables1

Ouarda, T.B.M.J. and S. El‐Adlouni, 2011. Bayesian Nonstationary Frequency Analysis of Hydrological Variables. Journal of the American Water Resources Association (JAWRA) 47(3):496‐505. DOI: 10.1111/j.1752‐1688.2011.00544.x Abstract: The present paper provides a discussion of nonstationary frequency analysis models in hydrology with a focus on the Bayesian approach. The Bayesian model provides an efficient estimation framework of hydrological quantiles in the presence of nonstationarity. In nonstationary frequency analysis models, the parameters are functions of covariates, allowing for dependent parameters and trends. The use of the nonstationary Generalized Maximum Likelihood Estimation method in hydrologic frequency analysis is discussed. This model allows using prior information concerning the variables under study and considering a number of models (linear, quadratic, etc.) of the dependence of the parameters on covariates. A discussion is also provided concerning the use of the reversible jump Monte Carlo Markov Chain procedure which allows carrying out the estimation of the posterior distributions of the parameters and the selection of the Bayesian model at the same time. An application to a case study is presented to illustrate the potential of the model.     

城市重大危机事件演化的动力学模型研究

建立了城市重大危机事件的＂事件链＂,并分析了＂事件链＂中各状态的相互关系。基于SEIS传染病模型的思想,提出了一类城市重大危机事件的动力学模型。分别在不考虑外部因素对事件链的影响和考虑外部因素对事件链的影响的情况下,对事件从正常状态到危机状态沿时间的发展趋势和规律进行了分析,并对解进行Lyapunov稳定性分析以及计算机模拟仿真。研究表明：系统自身的修复能力和外部因素对系统的影响是控制危机事件的重要因素。     

Modeling fecundity in birds: Conceptual overview, current models, and considerations for future developments

Fecundity is fundamental to the fitness, population dynamics, conservation, and management of birds. For all the efforts made to measure fecundity or its surrogates over the past century of avian research, it is still mismeasured, misrepresented, and misunderstood. Fundamentally, these problems arise because of partial observability of underlying processes such as renesting, multiple brooding, and temporary emigration. Over the last several decades, various analytical approaches have been developed to estimate fecundity from incomplete and biased data. These, include scalar arithmetic formulae, partial differential equations, individual-based simulations, and Markov chain methodology. In this paper, we: (1) identify component processes of avian reproduction; (2) review existing methods for modeling fecundity; (3) place these diverse models under a common conceptual framework; (4) describe the parameterization, validation, and limitations of such models; and (5) point out future considerations and challenges in the application of fecundity models. We hope this synthesis of existing literature will help direct researchers toward the most appropriate methods to assess avian reproductive success for answering questions in evolutionary ecology, natural history, population dynamics, reproductive toxicology, and management.