Comparing CFSR and conventional weather data for discharge and soil loss modelling with SWAT in small catchments in the Ethiopian Highlands

Accurate rainfall data are the key input parameter for modelling river discharge and soil loss. Remote areas of Ethiopia often lack adequate precipitation data and where these data are available, there might be substantial temporal or spatial gaps. To counter this challenge, the Climate Forecast System Reanalysis (CFSR) of the National Centers for Environmental Prediction (NCEP) readily provides weather data for any geographic location on earth between 1979 and 2014. This study assesses the applicability of CFSR weather data to three watersheds in the Blue Nile Basin in Ethiopia. To this end, the Soil and Water Assessment Tool (SWAT) was set up to simulate discharge and soil loss, using CFSR and conventional weather data, in three small-scale watersheds ranging from 112 to 477 ha. Calibrated simulation results were compared to observed river discharge and observed soil loss over a period of 32 years. The conventional weather data resulted in very good discharge outputs for all three watersheds, while the CFSR weather data resulted in unsatisfactory discharge outputs for all of the three gauging stations. Soil loss simulation with conventional weather inputs yielded satisfactory outputs for two of three watersheds, while the CFSR weather input resulted in three unsatisfactory results. Overall, the simulations with the conventional data resulted in far better results for discharge and soil loss than simulations with CFSR data. The simulations with CFSR data were unable to adequately represent the specific regional climate for the three watersheds, performing even worse in climatic areas with two rainy seasons. Hence, CFSR data should not be used lightly in remote areas with no conventional weather data where no prior analysis is possible.

Regression with autocorrelated data: A study of time trend of global infant mortality rate

The infant mortality rate (IMR) is considered to be one of the most important indices of a country's well-being. Countries around the world and other health organizations like the World Health Organization are dedicating their resources, knowledge and energy to reduce the infant mortality rates. The well-known Millennium Development Goal 4 (MDG 4), whose aim is to archive a two thirds reduction of the under-five mortality rate between 1990 and 2015, is an example of the commitment. ^ In this study our goal is to model the trends of IMR between the 1950s to 2010s for selected countries. We would like to know how the IMR is changing overtime and how it differs across countries. ^ IMR data collected over time forms a time series. The repeated observations of IMR time series are not statistically independent. So in modeling the trend of IMR, it is necessary to account for these correlations. We proposed to use the generalized least squares method in general linear models setting to deal with the variance-covariance structure in our model. In order to estimate the variance-covariance matrix, we referred to the time-series models, especially the autoregressive and moving average models. Furthermore, we will compared results from general linear model with correlation structure to that from ordinary least squares method without taking into account the correlation structure to check how significantly the estimates change.^

Sample locations, CTD data, mean spring and annual temperatures and salinities from World Ocean Atlas (WOA, 2001), and ICP-OES Mg/Ca data

Due to its strong gradient in salinity and small temperature gradient the Mediterranean provides an ideal setting to study the impact of salinity on the incorporation of Mg into foraminiferal tests. We have investigated tests of Globorotalia inflata and Globigerina bulloides in plankton tow and core top samples from the Western Mediterranean using ICP-OES for bulk analyses and LA-ICP-MS for analyses of individual chambers in single specimens. Mg/Ca observed in G. inflata are consistent with existing calibrations, whereas G. bulloides had significantly higher Mg/Ca than predicted, particularly in core top samples from the easterly stations. Scanning Electron Microscopy and Laser Ablation ICP-MS revealed secondary overgrowths on some tests, which could explain the observed high core top Mg/Ca. We suggest that the Mediterranean intermediate and deep water supersaturated with respect to calcite cause these overgrowths and therefore increased bulk Mg/Ca. However, the different species are influenced by diagenesis to different degrees probably due to different test morphologies. Our results provide new perspectives on reported anomalously high Mg/Ca in sedimentary foraminifera and the applicability of the Mg/Ca paleothermometry in high salinity settings, by showing that (1) part of the signal is generated by precipitation of inorganic calcite on the foraminifer test due to increased calcite saturation state of the water and (2) species with high surface-to-volume shell surfaces are potentially more affected by secondary Mg-rich calcite encrustation.

Amino acid data of catchment and sediment core samples of four Indian lakes

In the present study, we report the results of comprehensive amino acid (AA) analyses of four Indian lakes from different climate regimes. We focus on the investigation of sediment cores retrieved from the lakes but data of modern sediment as well as vascular plant, soil, and suspended particulate matter samples from individual lakes are also presented. Commonly used degradation and organic matter source indices are tested for their applicability to the lake sediments, and we discuss potential reasons for possible limitations. A principal component analysis including the monomeric AA composition of organic matter of all analysed samples indicates that differences in organic matter sources and the environmental properties of the individual lakes are responsible for the major variability in monomeric AA distribution of the different samples. However, the PCA also gives a factor that most probably separates the samples according to their state of organic matter degradation. Using the factor loadings of the individual AA monomers, we calculate a lake sediment degradation index (LI) that might be applicable to other palaeo-lake investigations.

GPS raw data (control points and ground control points) from the Liguria Region, Borghetto Santo Spirito, Italy

Monitoring the impact of sea storms on coastal areas is fundamental to study beach evolution and the vulnerability of low-lying coasts to erosion and flooding. Modelling wave runup on a beach is possible, but it requires accurate topographic data and model tuning, that can be done comparing observed and modeled runup. In this study we collected aerial photos using an Unmanned Aerial Vehicle after two different swells on the same study area. We merged the point cloud obtained with photogrammetry with multibeam data, in order to obtain a complete beach topography. Then, on each set of rectified and georeferenced UAV orthophotos, we identified the maximum wave runup for both events recognizing the wet area left by the waves. We then used our topography and numerical models to simulate the wave runup and compare the model results to observed values during the two events. Our results highlight the potential of the methodology presented, which integrates UAV platforms, photogrammetry and Geographic Information Systems to provide faster and cheaper information on beach topography and geomorphology compared with traditional techniques without losing in accuracy. We use the results obtained from this technique as a topographic base for a model that calculates runup for the two swells. The observed and modeled runups are consistent, and open new directions for future research.

Integration of embedded data processing algorithms inside PAMELA devices

PAMELA (Phased Array Monitoring for Enhanced Life Assessment) SHMTM System is an integrated embedded ultrasonic guided waves based system consisting of several electronic devices and one system manager controller. The data collected by all PAMELA devices in the system must be transmitted to the controller, who will be responsible for carrying out the advanced signal processing to obtain SHM maps. PAMELA devices consist of hardware based on a Virtex 5 FPGA with a PowerPC 440 running an embedded Linux distribution. Therefore, PAMELA devices, in addition to the capability of performing tests and transmitting the collected data to the controller, have the capability of perform local data processing or pre-processing (reduction, normalization, pattern recognition, feature extraction, etc.). Local data processing decreases the data traffic over the network and allows CPU load of the external computer to be reduced. Even it is possible that PAMELA devices are running autonomously performing scheduled tests, and only communicates with the controller in case of detection of structural damages or when programmed. Each PAMELA device integrates a software management application (SMA) that allows to the developer downloading his own algorithm code and adding the new data processing algorithm to the device. The development of the SMA is done in a virtual machine with an Ubuntu Linux distribution including all necessary software tools to perform the entire cycle of development. Eclipse IDE (Integrated Development Environment) is used to develop the SMA project and to write the code of each data processing algorithm. This paper presents the developed software architecture and describes the necessary steps to add new data processing algorithms to SMA in order to increase the processing capabilities of PAMELA devices.An example of basic damage index estimation using delay and sum algorithm is provided.

Algorithms hardware implementation for ultrasonic data processing in SHM system

Nowadays, devices that monitor the health of structures consume a lot of power and need a lot of time to acquire, process, and send the information about the structure to the main processing unit. To decrease this time, fast electronic devices are starting to be used to accelerate this processing. In this paper some hardware algorithms implemented in an electronic logic programming device are described. The goal of this implementation is accelerate the process and diminish the information that has to be send. By reaching this goal, the time the processor needs for treating all the information is reduced and so the power consumption is reduced too.

Kinetic study and thermal decomposition behavior of viscoelastic memory foam

A systematic investigation of the thermal decomposition of viscoelastic memory foam (VMF) was performed using thermogravimetric analysis (TGA) to obtain the kinetic parameters, and thermogravimetric analysis coupled to Fourier Transformed Infrared Spectrometry (TGA-FTIR) and thermogravimetric analysis coupled to Mass Spectrometry (TGA-MS) to obtain detailed information of evolved products on pyrolysis and oxidative degradations. Two consecutive nth-order reactions were employed to correlate the experimental data from dynamic and isothermal runs performed at three different heating rates (5, 10 and 20 K/min) under an inert atmosphere. On the other hand, for the kinetic study of the oxidative decomposition, the data from combustion (synthetic air) and poor oxygen combustion (N2:O2 = 9:1) runs, at three heating rates and under dynamic and isothermal conditions, were correlated simultaneously. A kinetic model consisting of three consecutive reactions presented a really good correlation in all runs. TGA-FTIR analysis showed that the main gases released during the pyrolysis of VMF were determined as ether and aliphatic hydrocarbons, whereas in combustion apart from the previous gases, aldehydes, amines and CO2 have also been detected as the main gases. These results were confirmed by the TGA-MS.

Review of automatic data processing developments in the Federal Government.

Mode of access: Internet.

Pilot medical engineering accident analysis study. Final report.

Mode of access: Internet.

Evaluation of seismometer wave gage and comparative analysis of wave data at Yaquina and Coquille Bays, Oregon /

"September 1985."

Guide to reporting highway statistics: procedures for the compilation, analysis and reporting of: state motor-fuel, motor-vehicle, driver-license and motor-carrier data; highway finance data of state and local governments.

Mode of access: Internet.

Test facility inventory data processing system - procedure.

National Highway Safety Bureau, Washington, D.C.