Projections of climate change impacts on central America tropical rainforest

Tropical rainforest plays an important role in the global carbon cycle, accounting for a large part of global net primary productivity and contributing to CO₂ sequestration. The objective of this work is to simulate potential changes in the rainforest biome in Central America subject to anthropogenic climate change under two emissions scenarios, RCP4.5 and RCP8.5. The use of a dynamic vegetation model and climate change scenarios is an approach to investigate, assess or anticipate how biomes respond to climate change. In this work, the Inland dynamic vegetation model was driven by the Eta regional climate model simulations. These simulations accept boundary conditions from HadGEM2-ES runs in the two emissions scenarios. The possible consequences of regional climate change on vegetation properties, such as biomass, net primary production and changes in forest extent and distribution, were investigated. The Inland model projections show reductions in tropical forest cover in both scenarios. The reduction of tropical forest cover is greater in RCP8.5. The Inland model projects biomass increases where tropical forest remains due to the CO₂ fertilization effect. The future distribution of predominant vegetation shows that some areas of tropical rainforest in Central America are replaced by savannah and grassland in RCP4.5. Inland projections under both RCP4.5 and RCP8.5 show a net primary productivity reduction trend due to significant tropical forest reduction, temperature increase, precipitation reduction and dry spell increments, despite the biomass increases in some areas of Costa Rica and Panama. This study may provide guidance to adaptation studies of climate change impacts on the tropical rainforests in Central America.     

An experimental study on active tendon control of cable-stayed bridges

Active tendon control of cable-stayed bridges subject to a vertical sinusoidal force is experimentally and analytically studied. Emphasis is placed on the effects of linear and non-linear internal resonances on the control (due to the presence of the cable vibration). A simple cable-supported cantilever beam is used as a model. It is found that active tendon control is very effective in vertical girder motion with small cable vibration (girder dominated motion), whereas it is not effective in vertical girder motion with large cable vibration (cable dominated motion). Analytical prediction is very satisfactory except for the latter case.     

Synchronization of human walking observed during lateral vibration of a congested pedestrian bridge

Observation of human-induced large-amplitude lateral vibration of an actual pedestrian bridge in an extremely congested condition is reported. Walking motions of pedestrians recorded by a video camera are analysed. It is found that walking among 20 per cent or more of the pedestrians on the bridge was synchronized to the girder lateral vibration. With this synchronization, the total lateral force from the pedestrians to the girder is evidently increased and it acts as a resonant force on the girder lateral vibration.     

An investigation of ensemble-based assimilation of satellite altimetry and tide gauge data in storm surge prediction

Cyclogenesis and long-fetched winds along the southeastern coast of South America may lead to floods in populated areas, as the Buenos Aires Province, with important economic and social impacts. A numerical model (SMARA) has already been implemented in the region to forecast storm surges. The propagation time of the surge in such extensive and shallow area allows the detection of anomalies based on observations from several hours up to the order of a day prior to the event. Here, we investigate the impact and potential benefit of storm surge level data assimilation into the SMARA model, with the objective of improving the forecast. In the experiments, the surface wind stress from an ensemble prediction system drives a storm surge model ensemble, based on the operational 2-D depth-averaged SMARA model. A 4-D Local Ensemble Transform Kalman Filter (4D-LETKF) initializes the ensemble in a 6-h cycle, assimilating the very few tide gauge observations available along the northern coast and satellite altimeter data. The sparse coverage of the altimeters is a challenge to data assimilation; however, the 4D-LETKF evolving covariance of the ensemble perturbations provides realistic cross-track analysis increments. Improvements on the forecast ensemble mean show the potential of an effective use of the sparse satellite altimeter and tidal gauges observations in the data assimilation prototype. Furthermore, the effects of the localization scale and of the observational errors of coastal altimetry and tidal gauges in the data assimilation approach are assessed.     

Parallel distributed computing using Python

This work presents two software components aimed to relieve the costs of accessing high-performance parallel computing resources within a Python programming environment: MPI for Python and PETSc for Python.MPI for Python is a general-purpose Python package that provides bindings for the Message Passing Interface (MPI) standard using any back-end MPI implementation. Its facilities allow parallel Python programs to easily exploit multiple processors using the message passing paradigm. PETSc for Python provides access to the Portable, Extensible Toolkit for Scientific Computation (PETSc) libraries. Its facilities allow sequential and parallel Python applications to exploit state of the art algorithms and data structures readily available in PETSc for the solution of large-scale problems in science and engineering.MPI for Python and PETSc for Python are fully integrated to PETSc-FEM, an MPI and PETSc based parallel, multiphysics, finite elements code developed at CIMEC laboratory. This software infrastructure supports research activities related to simulation of fluid flows with applications ranging from the design of microfluidic devices for biochemical analysis to modeling of large-scale stream/aquifer interactions.     

Foraminiferal responses to polluted sediments in the Montevideo coastal zone, Uruguay

A study of foraminiferal assemblages was carried out in 24 sediment samples collected from the Montevideo coastal zone (south-eastern coastal region of South America) to assess the response of the benthic foraminifera to the polluted sediments. The area is affected by different pollutants such as sewage, hydrocarbons and heavy metals derived from different sources. Biological data were analyzed with multivariate techniques of cluster analysis and a principal component analysis (PCA) was performed for abiotic factors. The results allowed the recognition of different species assemblages corresponding to different sub-environments, which reflected the prevalent ecological conditions. The Montevideo Bay, particularly, its inner part showed an extremely poor foraminiferal fauna-including a totally azoic station-and high percentages of abnormal tests, when compared with the adjacent Punta Carretas and Punta Yeguas zones. Mean faunal density showed a strong relationship with organic matter, oxygen and heavy metal concentrations, as well as redox potential and pH values of each sub-environment. Although the adjacent zones presented a moderate pollution degree, it was noticed that a positive effect on the foraminiferal density specially on Ammonia tepida, caused by the sewage pipe located in Punta Carretas, a pure organic contamination. Differences among foraminiferal assemblages seemed to be related to the combined action of the several kinds of pollutants and the natural abiotic variables, like the rapid salinity changes that occurred in this area.     

Hydraulic diffusivity and macrodispersivity calculations embedded in a geographic information system

Abstract

A numerical technique is presented whereby aquifer hydraulic diffusivities (D) and macrodispersivities (α) are calculated by linear equations rewritten from flow and solute transport differential equations. The approach requires a GIS to calculate spatial and temporal hydraulic head (h) and solute concentration gradients. The model is tested in Portugal, in a semi-confined aquifer periodically monitored for h and chloride/sulphate concentrations. Average D (0.46 m²/s) and α (1975 m) compare favourably with literature results. The relationship between α and scale (L) is also investigated. In this context, two aquifer groups could be identified: the first group is heterogeneous at the “macroscopic” scale (solute travelled distances <1 km), but homogeneous at the “megascopic” scale. The overall scale dependency in this case is given by an equation of logarithmic type. The second group is heterogeneous at the macroscopic and megascopic scales, with a scale dependency of linear type.

Citation Pacheco, F.A.L., 2013. Hydraulic diffusivity and macrodispersivity calculations embedded in a geographic information system. Hydrological Sciences Journal, 58 (4), 930–944.     

Urban Dispersion Modelling and Experiments in the Daytime and Nighttime Atmosphere

An analytical model of atmospheric dispersion in urban areas in both daytime and nighttime conditions is presented. The model is based on a Gaussian formulation where the horizontal and vertical diffusion coefficients are determined according to analytical theories. The model is validated with dispersion measurements from field experiments conducted in Oklahoma City, Salt Lake City, St. Louis and London, U.K. The theory is in good agreement with the data for both daytime and nighttime conditions. The data support the conclusion that the magnitude of the nighttime stratification in the urban atmosphere is weak; however, its effects on dispersion are not negligible. The predicted existence of two distinct dispersion regimes, in the near and in the far field, is also confirmed by the data. The good collapse of the data suggests that urban dispersion is governed by the characteristic length scales of atmospheric boundary-layer turbulence, rather than urban canopy length scales that are more likely to affect dispersion only in the vicinity of the source.     

Large-sample hydrology: recent progress,guidelines for new datasets and grand challenges

ABSTRACT

Large-sample hydrology (LSH) relies on data from large sets (tens to thousands) of catchments to go beyond individual case studies and derive robust conclusions on hydrological processes and models. Numerous LSH datasets have recently been released, covering a wide range of regions and relying on increasingly diverse data sources to characterize catchment behaviour. These datasets offer novel opportunities, yet they are also limited by their lack of comparability, uncertainty estimates and characterization of human impacts. This article (i) underscores the key role of LSH datasets in hydrological studies, (ii) provides a review of currently available LSH datasets, (iii) highlights current limitations of LSH datasets and (iv) proposes guidelines and coordinated actions to overcome these limitations. These guidelines and actions aim to standardize and automatize the creation of LSH datasets worldwide, and to enhance the reproducibility and comparability of hydrological studies.