scholarly journals Classifying Streamflow Duration: The Scientific Basis and an Operational Framework for Method Development

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2545 ◽  
Author(s):  
Ken M. Fritz ◽  
Tracie-Lynn Nadeau ◽  
Julia E. Kelso ◽  
Whitney S. Beck ◽  
Raphael D. Mazor ◽  
...  
Keyword(s):  
Water Resource Management ◽  
Method Development ◽  
Biological Indicators ◽  
Scientific Basis ◽  
Data Driven ◽  
Science Data ◽  
Development Indicators ◽  
Flow Duration ◽  
Collection Data ◽  
Operational Frameworks

Streamflow duration is used to differentiate reaches into discrete classes (e.g., perennial, intermittent, and ephemeral) for water resource management. Because the depiction of the extent and flow duration of streams via existing maps, remote sensing, and gauging is constrained, field-based tools are needed for use by practitioners and to validate hydrography and modeling advances. Streamflow Duration Assessment Methods (SDAMs) are rapid, reach-scale indices or models that use physical and biological indicators to predict flow duration class. We review the scientific basis for indicators and present conceptual and operational frameworks for SDAM development. Indicators can be responses to or controls of flow duration. Aquatic and terrestrial responses can be integrated into SDAMs, reflecting concurrent increases and decreases along the flow duration gradient. The conceptual framework for data-driven SDAM development shows interrelationships among the key components: study reaches, hydrologic data, and indicators. We present a generalized operational framework for SDAM development that integrates the data-driven components through five process steps: preparation, data collection, data analysis, evaluation, and implementation. We highlight priorities for the advancement of SDAMs, including expansion of gauging of nonperennial reaches, use of citizen science data, adjusting for stressor gradients, and statistical and monitoring advances to improve indicator effectiveness.

scholarly journals Data Papers as a New Form of Knowledge Organization in the Field of Research Data

2019 ◽  
Vol 46 (8) ◽  
pp. 622-638
Author(s):  
Joachim Schöpfel ◽  
Dominic Farace ◽  
Hélène Prost ◽  
Antonella Zane
Keyword(s):  
Business Models ◽  
Open Science ◽  
Research Data ◽  
Data Driven ◽  
Academic Publishing ◽  
Science Data ◽  
Research Data Management ◽  
Fair Principles ◽  
New Form ◽  
Machine Readable

Data papers have been defined as scholarly journal publications whose primary purpose is to describe research data. Our survey provides more insights about the environment of data papers, i.e., disciplines, publishers and business models, and about their structure, length, formats, metadata, and licensing. Data papers are a product of the emerging ecosystem of data-driven open science. They contribute to the FAIR principles for research data management. However, the boundaries with other categories of academic publishing are partly blurred. Data papers are (can be) generated automatically and are potentially machine-readable. Data papers are essentially information, i.e., description of data, but also partly contribute to the generation of knowledge and data on its own. Part of the new ecosystem of open and data-driven science, data papers and data journals are an interesting and relevant object for the assessment and understanding of the transition of the former system of academic publishing.

scholarly journals Hydro-Morphological Characteristics Using Flow Duration Curve, Historical Data and Remote Sensing: Effects of Land Use and Climate

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 309 ◽  
Author(s):  
Philip Kibet Langat ◽  
Lalit Kumar ◽  
Richard Koech ◽  
Manoj Kumer Ghosh
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Active Sites ◽  
Water Resource Management ◽  
Morphological Characteristics ◽  
Flow Duration Curve ◽  
Flow Duration ◽  
Tana River ◽  
Downstream Reach ◽  
History Of

Ecohydrological changes in large rivers of the world result from a long history of humandimensions and climate. The increasing human population, intensified land use, and climate change haveled to a decline in the most critical aspect of achieving sustainable development, namely, that of waterresources. This study assessed recent hydromorphological characteristics of the tropical Tana River inKenya using flow duration curve, and geospatial techniques to gain a better understanding of humanimpacts over the last two decades and their consequences for new development projects. The results showthat all extremal peak, low, and mean discharges exhibited significant increasing trends over a period of17 years. Dam construction represents a 13% reduction of the maximum discharge and a 30% decrease inlow flows, while post-regulation hydrological changes indicated an increase of 56 and 40% of high flowsand low flows respectively. Dominant flow was observed to be higher for the current decade than theprevious decade, representing a rise of the dominant streamflow by 33%. The assessment of fourmorphologically active sites at the downstream reach showed channel adjustments which support thechanges in the flow regimes observed. The channel width increased by 8.7 and 1.9% at two sites butdecreased by 31.5 and 16.2% for the other two sites under study during the time period. The resultsunderscore the contribution of other main human modifications, apart from regulation, such as increasedwater abstraction and inter basin transfer, up-stream land use and anthropogenic climate change to assessthe ecohydrological status in this river basin. Such streamflow regime dynamics may have implicationson water resource management, riverine environments, and development of new water projects.

scholarly journals Comparison of three data-driven techniques in modelling the evapotranspiration process

2010 ◽  
Vol 12 (4) ◽  
pp. 365-379 ◽  
Author(s):  
I. El-Baroudy ◽  
A. Elshorbagy ◽  
S. K. Carey ◽  
O. Giustolisi ◽  
D. Savic
Keyword(s):  
Case Studies ◽  
Water Resource Management ◽  
Polynomial Regression ◽  
Hydrological Cycle ◽  
Global Scale ◽  
Data Driven ◽  
Actual Evapotranspiration ◽  
Time Lags ◽  
Evolutionary Polynomial Regression ◽  
Input Variables

Evapotranspiration is one of the main components of the hydrological cycle as it accounts for more than two-thirds of the precipitation losses at the global scale. Reliable estimates of actual evapotranspiration are crucial for effective watershed modelling and water resource management, yet direct measurements of the evapotranspiration losses are difficult and expensive. This research explores the utility and effectiveness of data-driven techniques in modelling actual evapotranspiration measured by an eddy covariance system. The authors compare the Evolutionary Polynomial Regression (EPR) performance to Artificial Neural Networks (ANNs) and Genetic Programming (GP). Furthermore, this research investigates the effect of previous states (time lags) of the meteorological input variables on characterizing actual evapotranspiration. The models developed using the EPR, based on the two case studies at the Mildred Lake mine, AB, Canada provided comparable performance to the models of GP and ANNs. Moreover, the EPR provided simpler models than those developed by the other data-driven techniques, particularly in one of the case studies. The inclusion of the previous states of the input variables slightly enhanced the performance of the developed model, which in turn indicates the dynamic nature of the evapotranspiration process.

Data-driven thinking for measuring the human experience in the built environment

2021 ◽  
pp. 147807712110251
Author(s):  
Bige Tunçer ◽  
Francisco Benita
Keyword(s):  
Data Analysis ◽  
Built Environment ◽  
Urban Design ◽  
Learning Experience ◽  
Landscape Design ◽  
Data Driven ◽  
Sensor Data ◽  
Experimental Setup ◽  
Collection Data

This article introduces a methodology to implement Data-driven Thinking in the context of urban design. We present the results of a case study based on a 7-day workshop with 10 participants with landscape design and architecture background. The goal of the workshop was to expose participants to Data-driven Thinking through experimental design, multi-sensor data collection, data analysis, visualization, and insight generation. We evaluate their learning experience in designing an experimental setup, collecting real-time immediate environmental and physiological body reactions data. Our results from the workshop show that participants increased their knowledge about measuring, visualizing and understanding data of the surrounding built environment.

scholarly journals A Data-Driven Approach to Appraisal and Selection at a Domain Data Repository

2018 ◽  
Vol 12 (2) ◽  
Author(s):  
Amy M Pienta ◽  
Dharma Akmon ◽  
Justin Noble ◽  
Lynette Hoelter ◽  
Susan Jekielek
Keyword(s):  
Data Driven ◽  
Data Repository ◽  
Search Activity ◽  
Process Data ◽  
Science Data ◽  
Social Scientists ◽  
Data Repositories ◽  
The Social ◽  
Data Driven Approach ◽  
User Demand

Social scientists are producing an ever-expanding volume of data, leading to questions about appraisal and selection of content given finite resources to process data for reuse. We analyze users’ search activity in an established social science data repository to better understand demand for data and more effectively guide collection development. By applying a data-driven approach, we aim to ensure curation resources are applied to make the most valuable data findable, understandable, accessible, and usable. We analyze data from a domain repository for the social sciences that includes over 500,000 annual searches in 2014 and 2015 to better understand trends in user search behavior. Using a newly created search-to-study ratio technique, we identified gaps in the domain data repository’s holdings and leveraged this analysis to inform our collection and curation practices and policies. The evaluative technique we propose in this paper will serve as a baseline for future studies looking at trends in user demand over time at the domain data repository being studied with broader implications for other data repositories.

scholarly journals Russia’s Assistance to Nigerian Economic and Educational Development(1999 – 2019)

2020 ◽  
pp. 1-8
Author(s):  
Kafilat Motunrayo Adebayo
Keyword(s):  
Qualitative Method ◽  
Educational Development ◽  
Development Indicators ◽  
Collection Data ◽  
The Subject ◽  
Democratic Rule ◽  
Nigerian Students ◽  
Russian Universities ◽  
Populous Country

Abolishing poverty and ensuring improvement of educational development indicators have been described as some of the objectives for international assistance. This study seeks to comprehend the role of Russia in the development of the African continent’s most populous country, Nigeria, the factors that limited their success and the opportunities for increasing effectiveness of such efforts. Russia intervention in Nigeria economic and educational development took a new turn after Nigeria returned to democratic rule in 1999. The existence of the largest Russian investor (RUSAL) in the Nigeria, the investments of LUKOIL in Nigeria which currently exceeds $450 million, and other well-known Russian companies, including the largest Russian producer of agricultural machinery "Rostselmash", have all made impact in Nigeria economic development. However, the major problem of this duo cooperation lies in the legal ratification of their framework. In Educational sphere, this study ascertains that yearly, more than 100 Nigerian students are given the opportunity to study at Russian universities through Russia-Nigerian intergovernmental agreements. To date, more than 10,000 Nigerian specialists have been trained in Russia. The study drew upon both modernization and dependency theories in advancing understanding on the subject matter. The study employed qualitative method of data collection. Data was analyzed using content analysis.

Computer-Aided Design Ideation Using InnoGPS

2019 ◽  
Author(s):  
Jianxi Luo ◽  
Serhad Sarica ◽  
Kristin L. Wood
Keyword(s):  
Computer Aided Design ◽  
Data Science ◽  
Design Science ◽  
Data Driven ◽  
Process Data ◽  
Science Data ◽  
Design Concepts ◽  
Patent Classification ◽  
Computer Aided ◽  
Design Ideation

Abstract Traditionally, the ideation of design opportunities and new concepts relies on human expertise or intuition and is faced with high uncertainty. Inexperienced or specialized designers often fail to explore ideas broadly and become fixed on specific ideas early in the design process. Recent data-driven design methods provide external design stimuli beyond one’s own knowledge, but their uses in rapid ideation are still limited. Intuitive and directed ideation techniques, such as brainstorming, mind mapping, Design-by-Analogy, SCAMPER, TRIZ and Design Heuristics may empower designers in rapid ideation but are limited in the designer’s own knowledge base. Herein, we harness data-driven design and rapid ideation techniques to introduce a data-driven computer-aided rapid ideation process using the cloud-based InnoGPS system. InnoGPS integrates an empirical network map of all technology domains based on the international patent classification which are connected according to knowledge distance based on patent data, with a few map-based functions to position technologies, explore neighborhoods, and retrieve knowledge, concepts and solutions in the near or far fields for design analogies and syntheses. The functions of InnoGPS fuse design science, network science, data science and interactive visualization and make the design ideation process data-driven, theoretically-grounded, visually-inspiring, and rapid. We demonstrate the procedures of using InnoGPS as a data-driven rapid ideation tool to generate new rolling toy design concepts.

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