196,115 research outputs found
Preface: HS01 – Changes in Flood Risk and Perception in Catchments and Cities
No abstract available
R.E.Correa2020_et al_Supporting information S1.xlsx
CO2-rich
hydrothermal groundwater discharge to a healthy coral reef
Rogger E. Correa1,2*, M. Bayani Cardenas3, Raymond
S. Rodolfo4,5, Mark R. Lapus5, Kay L. Davis1,
Anna Giles1, Jose C. Fullon6,Mithra-Christin Hajati7,
Nils Moosdorf7,8, Christian J. Sanders1,
Isaac R. Santos1,9
1 National Marine Science Centre, Southern
Cross University, P.O. Box 4321,
Coffs Harbour, NSW 2450, Australia
2 Corporación Merceditas - Merceditas
Corporation, Medellín 050021, Colombia
3Department of Geological Sciences, University
of Texas at Austin, Austin, Texas, USA
4 Department of Environmental Sciences,
Ateneo de Manila University, Quezon City, Philippines
5 Agricultural Sustainability Initiatives
for Nature, Inc., Quezon City, Philippines
6 Planet Dive Resort, Anilao, Batangas,
Philippines
7 Department of Biogeochemistry/Geology,
Leibniz Centre for Tropical Marine Research (ZMT), Germany.
8 Institute for Geosciences, Kiel
University, Kiel, Germany
9 Department of Marine Sciences, University
of Gothenburg, Gothenburg, SwedenThis data base was collected during 2 weeks of January 2019 (11 tydal cycles), on a coral reef in the Coral Triangle. The place is an iconic diving site called Twin Rocks in Philippines. Time series were collected at two sites and groundwater samples were collected at 5 boreholes (50cm deph) in hydrothermal springs. In this dataset are included radon 222, co2 and anciliary data measurements at 30 minutes time steps.*Corresponding author email:[email protected] </div
Extreme rainstorms: Comparing regional envelope curves to stochastically generated events
The depth-duration envelope curves (DDECs) are regional upper bounds on observed rainfall maxima for several durations. Recently, a probabilistic interpretation has been proposed in the literature in order to associate a recurrence interval T to the DDECs and, consequently, to retrieve point rainfall quantiles for ungauged sites. Alternatively, extreme rainfall quantiles can be retrieved from long synthetic rainfall series obtained with stochastic rainfall generators calibrated to local time series of rainfall events. While DDECs are sensitive to outliers and data errors, the stochastic rainfall generator performance is affected by the limited record lengths used for calibration. The objective of this study is to assess the reliability of the two alternative methods by verifying if they give consistent results for a wide study region in Austria. Relative to previous studies, we propose some generalizations of the DDEC procedure in order to better represent the Austrian data. The comparison of rainfall quantiles estimated with the two methods for large T shows an excellent agreement for intermediate durations (from 1 to 6 h), while the agreement worsen for very short (15 min) and long (24 h) durations. The results are scrupulously analyzed and discussed in light of the exceptionality of rainfall events that set the regional envelopes and the characteristics of the stochastic generator used. Our study points out that the combined use of these regional and local methods can be very useful for estimating reliable point rainfall quantiles associated with large T within regions where many rain gauges are available, but with limited record lengths
Conceptual model building inspired by field-mapped runoff generation mechanisms
Since the beginning of hydrological research hydrologists have developed models that reflect their perception about how the catchments work and make use of the available information in the most efficient way. In this paper we develop hydrologic models based on field-mapped runoff generation mechanisms as identified by a geologist. For four different catchments in Austria, we identify four different lumped model structures and constrain their parameters based on the field-mapped information. In order to understand the usefulness of geologic information, we test their capability to predict river discharge in different cases: (i) without calibration and (ii) using the standard split-sample calibration/ validation procedure. All models are compared against each other. Results show that, when no calibration is involved, using the right model structure for the catchment of interest is valuable. A-priori information on model parameters does not always improve the results but allows for more realistic model parameters. When all parameters are calibrated to the discharge data, the different model structures do not matter, i.e., the differences can largely be compensated by the choice of parameters. When parameters are constrained based on field-mapped runoff generation mechanisms, the results are not better but more consistent between different calibration periods. Models selected by runoff generation mechanisms are expected to be more robust and more suitable for extrapolation to conditions outside the calibration range than models that are purely based on parameter calibration to runoff data
Comparative assessment of predictions in ungauged basins – Part 1: Runoff-hydrograph studies
The objective of this assessment is to compare studies predicting runoff hydrographs in ungauged catchments. The aim is to learn from the differences and similarities between catchments in different locations, and to interpret the differences in performance in terms of the underlying climate and landscape controls. The assessment is performed at two levels. The Level 1 assessment is a meta-analysis of 34 studies reported in the literature involving 3874 catchments. The Level 2 assessment consists of a more focused and detailed analysis of individual basins from selected studies from Level 1 in terms of how the leave-one-out cross-validation performance depends on climate and catchment characteristics as well as on the chosen regionalisation method. The results indicate that runoff-hydrograph predictions in ungauged catchments tend to be more accurate in humid than in arid catchments and more accurate in large than in small catchments. The dependence of performance on elevation differs by regions and depends on how aridity varies with elevation and air temperature. The effect of the parameter regionalisation method on model performance differs between studies. However, there is a tendency towards a somewhat lower performance of regressions than other methods in those studies that apply different methods in the same region. In humid catchments spatial proximity and similarity methods perform best while in arid catchments similarity and parameter regression methods perform slightly better. For studies with a large number of catchments (dense stream gauge network) there is a tendency for spatial proximity and geostatistics to perform better than regression or regionalisation based on simple averaging of model parameters from gauged catchments. There was no clear relationship between predictive performance and the number of regionalised model parameters. The implications of the findings are discussed in the context of model building
Dr. Duane M. Jackson, Morehouse College, July 2011
This video is a conversation with Dr. Duane M. Jackson. Dr. Jackson talks about his paper, "Recall and the Serial Position Effect: The Role of Primacy and Recency on Accounting Students' Performance." Jackie Daniel, AUC Woodruff Library, is the interviewer
"Reflections on the subject of Emigration from Europe with a view to Settlement in the United States" By M. Carey.
"Reflections on the subject of Emigration from Europe with a view to Settlement in the United States: containing bried sketches of the moral and political character of those states.
By M. Carey, member of the American philosophical, and of the American Antiquarian Society, and author of The Olive Branch, Cindiciae Hibernicae, essays on banking, on political economy, and on internal improvement.
To which are now added the English editor's comments on the subject; together with Important Advice to Emigrants, and Cautions Against Impositions Practiced in the Outports
Dispelling the Myths Behind First-author Citation Counts
We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Dr. Glendon Swarthout
Hosted by Roger M. Busfield, MSU Assistant Professor of Speech and Theater, Meet the Author is designed to introduce a general audience to a contemporary author and their work through in-depth interviews. This episode features a conversation between Dr. Glendon Swarthout, prolific author and English professor at MSU, and assistant professors Sam S. Baskett and Theodore B. Strandness
Opportunities for multivariate analysis of open spatial datasets to characterize urban flooding risks
Cities worldwide are challenged by increasing urban flood risks. Precise and realistic measures are required to reduce flooding impacts. However, currently implemented sewer and topographic models do not provide realistic predictions of local flooding occurrence during heavy rain events. Assessing other factors such as spatially distributed rainfall, socioeconomic characteristics, and social sensing, may help to explain probability and impacts of urban flooding. Several spatial datasets have been recently made available in the Netherlands, including rainfall-related incident reports made by citizens, spatially distributed rain depths, semidistributed socioeconomic information, and buildings age. Inspecting the potential of this data to explain the occurrence of rainfall related incidents has not been done yet. Multivariate analysis tools for describing communities and environmental patterns have been previously developed and used in the field of study of ecology. The objective of this paper is to outline opportunities for these tools to explore urban flooding risks patterns in the mentioned datasets. To that end, a cluster analysis is performed. Results indicate that incidence of rainfall-related impacts is higher in areas characterized by older infrastructure and higher population density.Water ResourcesSanitary Engineerin
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