Polynomial Surrogates for Open-Channel Flows in Random Steady State

Assessing epistemic uncertainties is considered as a milestone for improving numerical predictions of a dynamical system. In hydrodynamics, uncertainties in input parameters translate into uncertainties in simulated water levels through the shallow water equations. We investigate the ability of generalized polynomial chaos (gPC) surrogate to evaluate the probabilistic features of water level simulated by a 1-D hydraulic model (MASCARET) with the same accuracy as a classical Monte Carlo method but at a reduced computational cost. This study highlights that the water level probability density function and covariance matrix are better estimated with the polynomial surrogate model than with a Monte Carlo approach on the forward model given a limited budget of MASCARET evaluations. The gPC-surrogate performance is first assessed on an idealized channel with uniform geometry and then applied on the more realistic case of the Garonne River (France) for which a global sensitivity analysis using sparse least-angle regression was performed to reduce the size of the stochastic problem. For both cases, Galerkin projection approximation coupled to Gaussian quadrature that involves a limited number of forward model evaluations is compared with least-square regression for computing the coefficients when the surrogate is parameterized with respect to the local friction coefficient and the upstream discharge. The results showed that a gPC-surrogate with total polynomial degree equal to 6 requiring 49 forward model evaluations is sufficient to represent the water level distribution (in the sense of the \(\ell _2\) norm), the probability density function and the water level covariance matrix for further use in the framework of data assimilation. In locations where the flow dynamics is more complex due to bathymetry, a higher polynomial degree is needed to retrieve the water level distribution. The use of a surrogate is thus a promising strategy for uncertainty quantification studies in open-channel flows and should be extended to unsteady flows. It also paves the way toward cost-effective ensemble-based data assimilation for flood forecasting and water resource management.     

Air Quality Modeling Using the PSO-SVM-Based Approach,MLP Neural Network,and M5 Model Tree in the Metropolitan Area of Oviedo (Northern Spain)

The main aim of this study was to construct several regression models of air quality using techniques based on the statistical learning, in the metropolitan area of Oviedo, in northern Spain. In this research, a hybrid particle swarm optimization-based evolutionary support vector regression is implemented to predict the air quality from the experimental dataset (specifically, nitrogen oxides, carbon monoxide, sulfur dioxide, ozone, and dust) collected from 2013 to 2015 in the metropolitan area of Oviedo. Furthermore, a multilayer perceptron network (MLP) and the M5 model tree were also fitted to the experimental dataset for comparison purposes. Finally, the predicted results show that the hybrid proposed model is more robust than the MLP and M5 model tree prediction methods in terms of statistical estimators and testing performances.     

Influence of Clear Fellings on the Bryophyte Component of the Broad-leaved Forests of the Bashkir Cis-Ural Region

The change in the composition of the bryophyte component of succession communities that occur in the process of natural regeneration at the site of clear felling of the indigenous elm—maple–linden forests of the Bashkir Cis-Ural Region has been studied. The vulnerability of species to the consequences of felling is affected by their substrate confinement, ecological amplitude in relation to the factors of temperature, humidity, variability of soil moisture, and type of life strategy. In the secondary aspen forests, the absence or low constancy of nemoral epiphytic and ground mosses was noted.     

Effects of Topographical Heterogeneity and Dispersal Limitation on Species Turnover in a Temperate Mountane Ecosystem: a Case Study in the Henan Province,China

Species turnover patterns can be inconsistent due to differences in the dispersal ability of different growth forms. Here, species of trees, shrubs, herbs, and bryophytes in the Xiaoqinling National Nature Reserve in China were analyzed to determine patterns of species turnover along an elevation and spatial gradient. Variance partitioning was used to assess the relative contribution of topographic heterogeneity and dispersal limitation to species turnover. Our results suggest that the effect of dispersal limitation is more important than topographic heterogeneity on species turnover in temperate mountane ecosystems in the study area. Dispersal limitation has a greater effect on trees species turnover than on shrubs, herbs or bryophytes species turnover.     

Factors Affecting Predator-Prey Distribution in a Protected Area,Tehran, Iran (a Case with Wolves and Wild Sheep)

We tried to model habitat suitability of two prey and predator species including wild sheep (Ovis orientalis) and wolf (Canis lupus) in Varjin protected area located in northern east of Tehran using a presence only method, maximum entropy (MaxEnt). Totally 11 environmental variables were measured in the species presence points which can be classified in three groups including topographical, vegetation and distal variables. Resulted maps indicated that habitat variables such as slope (ranging from 35 to 40 percent) and elevation (lower than 1700 meters above sea level) are both institute those factors which mostly affect studied prey and predator habitat use. Our results regarding prey and predator geographical range of used habitat indicated that wolves cover most area than wild sheep which show more dispersed habitat resources for the prey species. ENMTools test revealed that wolf’s niche breadth is more than twice as much as wild sheep’s. Wild sheep in Varjin protected area has a relatively narrow geographical extent and shows a tendency to marginal habitats while wolves cover obviously more areas which denotes its high mobility and low dependency to specific habitats.     

Plant Species Richness and Developmental Morphology Stage Influence Mycorrhizal Patagonia Plants Root Colonization

The objectives of this study were to determine the percentage of root colonization by arbuscular mycorrhizal (AM) fungi at various levels of plant species richness and developmental morphology stages in various perennial grass, and herbaceous and woody dicots species using experimental plots during 2013 and 2014. An auger was used to obtain six replicate root + soil samples at each sampling time on each of the study parameters. Roots were washed free of soil, and percentage AM was determined. The shrub Larrea divaricata was the species which showed the lowest percentage of colonization by AM at the vegetative developmental morphology stage at the monocultures and six-species-mixtures on the experimental plots. Dicots, but not grass, species showed a greater percentage colonization by AM fungi at the greatest (i.e., six-species-mixtures) than lowest (i.e., monocultures) species richness. Although at different degrees of species richness and developmental morphology stages, the perennial grasses Nassella longiglumis and N. tenuis, the herbaceous dicot Atriplex semibaccata, and the shrubs L. divaricata and Schinus fasciculatus showed a greater (p < 0.050) percentage colonization by AM fungi during the second than the first study year. Even though it was species- and sampling time-dependent, percentage colonization by AM fungi increased as species richness also increased most of the times. Our results demonstrated that the plant species differences in percentage colonization by AM fungi in the experimental plots were species richness-, developmental morphology stage-, and sampling-time dependents.     

Variation in the Composition of Secondary Metabolites in <Emphasis Type="Italic">Flavocetraria</Emphasis> Lichens from Western Siberia

The composition and contents of secondary metabolites in Flavocetraria lichens from Eastern Siberia were analyzed using herbarium specimens. Based on the composition of identified metabolites, three F. cucullata chemotypes and two F. nivalis chemotypes were distinguished. Distinct geographic differentiation between the F. cucullata chemotypes was revealed, probably reflecting their adaptation to environmental conditions. The content of usnic acid in F. cucullata thalli was found to correlate with the latitude of growing region. This may be regarded as evidence for a protective role of this metabolite in lichens growing at high latitudes and exposed to excess solar irradiation during the polar day.     

Socio-environmental consideration of phosphorus flows in the urban sanitation chain of contrasting cities

Understanding how cities can transform organic waste into a valuable resource is critical to urban sustainability. The capture and recycling of phosphorus (P), and other essential nutrients, from human excreta is particularly important as an alternative organic fertilizer source for agriculture. However, the complex set of socio-environmental factors influencing urban human excreta management is not yet sufficiently integrated into sustainable P research. Here, we synthesize information about the pathways P can take through urban sanitation systems along with barriers and facilitators to P recycling across cities. We examine five case study cities by using a sanitation chains approach: Accra, Ghana; Buenos Aires, Argentina; Beijing, China; Baltimore, USA; and London, England. Our cross-city comparison shows that London and Baltimore recycle a larger percentage of P from human excreta back to agricultural lands than other cities, and that there is a large diversity in socio-environmental factors that affect the patterns of recycling observed across cities. Our research highlights conditions that may be “necessary but not sufficient” for P recycling, including access to capital resources. Path dependencies of large sanitation infrastructure investments in the Global North contrast with rapidly urbanizing cities in the Global South, which present opportunities for alternative sanitation development pathways. Understanding such city-specific social and environmental barriers to P recycling options could help address multiple interacting societal objectives related to sanitation and provide options for satisfying global agricultural nutrient demand.

     

Modeling of agricultural drought risk pattern using Markov chain and GIS in the western part of Bangladesh

The aim of the study is to assess the agricultural drought risk condition in the context of global climate change in the western part of Bangladesh that covers about 45% area of the country for the period of 1960–2011. Drought Index (DI) and Drought Hazard Index (DHI) have been calculated by Markov Chain analysis and that of Drought Vulnerability Index (DVI) from socioeconomic and physical indicators. The DI values show that the northern part in general is more drought-prone, having less crops prospect, whereas the southern part is less drought-prone with high crop potentiality. The probability of extreme drought occurrence increases in recent decades in some parts as a result the drought events become more frequent in the areas. The DHI ranges from 15 to 32, and northern part suffers from more extreme drought hazards than that of southern part. DVI also indicates that northern part is exposed to high to very high drought vulnerability as higher percentage of illiterate people are involved in agricultural practices and high percentage of irrigation to cultivable land, but southern part exposed to moderate to low vulnerability because of low values of vulnerability indicators. Finally, agricultural drought exists at high risk condition in northern part and low in southern parts and 21.63, 26.54 and 29.68% of the area poses very high, high and moderate risk, respectively. So, immediate adaptation measures are needed keeping in mind climate features like rainfall and temperature variability, drought risk and risk ranking to make viable adaptation measures.