1,720,993 research outputs found
Climate change and watershed planning : understanding the related impacts and risks
No full textThis dissertation consists in studying the possible effects of climate change in watershed management. Specifically, the dissertation explores the possibility of using a Artificial Neural Networks – ANN models coupled with physically based hydrological models as method for improving the description of the regional hydrologic cycle of a watershed by considering the relationships among geophysical and human systems when stressed by both climatic and anthropogenic factors and under long-term time periods. The selected physically-based model is named Soil and Water Assessment Tool -- SWAT,
As watershed management is a broad theme involving the consideration of several interconnected systems, such as biogeophysical and socio-economic systems, the dissertation first reviews basic concepts regarding the management of watersheds, the utilisation of hydrological models as tool in supporting the development of integrated watershed management plans, and the presentation of two case studies: i. The first one, named the Venice Lagoon Watershed – VLW, in Italy, consisting in the study of the possible impacts of climate and land-use changes on the availability of water for irrigation water, both in terms of quantity and quality, and; The second case study, focusing in the study of the possible effects of climate and land-use changes on river flood events the Itajaí River Watershed – IRW, in Brazil.
In terms of structure the thesis is divided into five chapters: i. The first chapter reviews concepts of watershed management, while introducing hydrological modelling techniques and proposed innovations to be used throughout the dissertation, such as the consideration of the carbon dioxide fertilisation effect due to an increase concentration of carbon dioxide in the atmosphere; ii. The second chapter presents a literature review and a case study describing the uncertainty in employing ANN models in hydrologic systems; iii. The third chapter describes the complexity of the VLW while presenting two case studies evaluating the feasibility of coupling the two considered models (i.e. ANN and SWAT models); iv. The fourth chapter presents the Italian case study, covering the topic of climate change impacts on irrigation water, and; v. The fifth chapter presents the Brazilian case study, covering the topic of climate change effects on river flood risk. The source code of the proposed ANN model and the modifications in the SWAT model are presented as Annex information, as well as a detailed description of the ANN model
Mapping the exposure of tourism to weather extremes: the need for a spatially-explicit gridded dataset for disaster risk reduction
Full text linkTourism is a highly important economic sector worldwide, yet it is often less than optimally represented in terms of detailed spatial information. An accurate spatial representation of tourism can provide valuable insights into the spatial distribution of tourism vulnerabilities and exposure, allowing policymakers to make informed decisions and develop effective strategies for disaster risk reduction and climate change adaptation policies. Here, we stress the need for and propose a first prototype of an open-access spatially-explicit gridded database based on social media data for over 150 different tourism-related classes that depicts tourism density (supply and demand) and perceived satisfaction in Europe. We showcase the potential benefits of such database by mapping the exposure of specific tourism sectors to a range of weather extremes, including floods, windstorms, and heat stress. Based on these results, we argue that a homogeneous spatially-explicit database of tourism is essential to support efficient investments in preparedness and disaster resilience
Expert-driven explainable artificial intelligence models can detect multiple climate hazards relevant for agriculture
No full textConcurrent climate extremes have severe consequences on societies, economies, and natural systems. Multi-hazard risk-oriented early warning systems are essential to reduce impacts, enhance preparedness, and boost adaptation. Yet, the growing volume and variety of spatio-temporal data combined with the increasing frequency of concurrent extremes pose challenges to the rapid detection and tracking of harmful events. Artificial intelligence offers an opportunity to deal with these challenges, especially when interpretability and explainability are ensured. Here, we show how expert-driven and explainable artificial intelligence models can probabilistically detect multiple agriculture-related hazards. The models are trained using the work of agro-climatic experts who, over decades, operationally identified multiple climate hazards affecting agriculture in Europe. The models identify the main drivers leading to the detection of affected areas while effectively dealing with large datasets to provide probabilistic results and uncertainty estimation. Results highlight the added value of expert-driven and explainable artificial intelligence models in supporting risk management as well as effective and sustainable adaptation, particularly when integrated into early warning systems and sectoral climate services. Grounded on expert-driven information, the models contribute to a better understanding of the complex dynamics behind the onset and spatio-temporal evolution of climate extremes and to enhanced trust in defining and communicating affected areas.JRC.E.1 - Disaster Risk Managemen
A dataset for monitoring agricultural drought in Europe
No full textAbstract This paper introduces the Combined Drought Indicator dataset, a collection of raster maps generated by the Copernicus European Drought Observatory for monitoring agricultural drought in Europe. Computationally, the CDI involves three indicators: the Standardized Precipitation Index, the Soil Moisture Anomaly and the Fraction of the Photosyntetically Active Radiation anomaly. These are complemented by the use of crop and snow masks. The CDI dataset has a spatial resolution of 1/24 decimal degrees (∼5 km), a temporal resolution of 10 days and is available from 2012 onward. As drought effects are variegated both in space and time, the CDI provides an effective instrument for assessing the different stages of propagation of agricultural drought and their spatial extent. Furthermore, the CDI maps provide relevant information for those private and public actors (water resource agencies, farmers, land managers and so on) involved both in drought preparedness and planning to mitigate drought impacts. Users can access and download the dataset from the Copernicus European Drought Observatory web portal, where an online mapviewer and clickable maps facilitate its interactive exploration
Rationalising Systems Analysis for the Evaluation of Adaptation Strategies in Complex Human-Water Systems
Full text linkWater resources management is a non-trivial process requiring a holistic understanding of the factors driving the dynamics of human-water systems. Policy-induced or autonomous behavioural changes in human systems may affect water and land management, which may affect water systems and feedback to human systems, further impacting on water and land management. Currently, hydro-economic models lack the ability in describing such complex dynamics by either not accounting for the multi-factor/multi-output nature of these systems, and/or not being designed to operate at a river basin scale. This paper presents a methodological framework for the integration of a microeconomic multi-factor/multi-output Positive Multi-Attribute Utility Programming (PMAUP) model with the eco-hydrologic Soil and Water Assessment Tool (SWAT) model. The connection between the two models is done under a sequential modular approach and is provided by a common spatial unit, named Hydrologic-Economic Representative Units (HERUs) and defined as rational entities resulting from the unique combination of hydrologic responsive units and socio-economic agents. The resulting SWAT-PMAUP model aims to provide the means for exploring the dynamics between the behaviour and self-organisation of socio-economic agents, and its connections with the water system through water and land management (i.e. HERUs). Methods are illustrated with an irrigation restriction policy applied to the Río Mundo sub-basin in south-eastern Spain. Results suggest that the consideration of the proposed methodological framework can capture changes in the dynamics of human-water systems following the implementation of adaptation strategies and can be a valuable tool to support decision making in a context of water resources management
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe 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
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