1,720,962 research outputs found
Modelling of water balance and crop growth based on Earth Observation and re-analysis data
Full text linkL'abstract è presente nell'allegato / the abstract is in the attachmen
Spatio-temporal variability of global crop water requirement, during 1950-2020
Full text linkIntensification of studies of the agricultural water requirement is a main challenge in a globalizedworld, where food production is pushed to meet the needs of a growing population and theinternational trade network requires large-scale planning policies. Agriculture is the human activitythat consumes most of the withdrawn freshwater and climate change can greatly influence theamount of irrigation required by crops. In recent years, the widespread availability of satelliteimages is providing an important contribution to water resources management, offering data athigh spatio-temporal resolution over an interestingly long period of time.This study deals with the temporal variability of global water requirement of the main crops, whichis assessed through a comprehensive model, driven by climate forcings, that estimates the dailycrop water requirement on a spatial resolution of 5 arc-min (or 0.0833°) from 1950 to 2020. Themodel computes a soil water balance using daily input data of precipitation andevapotranspiration, based on the high-resolution ERA5 reanalysis dataset from the ClimateChange Service of the Copernicus Program, which combines satellite information and groundmeasurements. The distribution of harvested areas and the length of crop development phasesare kept constant, to analyze the variability of crop water requirement strictly related to climateforcings, both in terms of precipitation (green water) and irrigation (blue water). The modelconsiders the separation between irrigated and rainfed areas, in order to provide a consistentspatial distribution of irrigation requirements. Examining the spatio-temporal variability of thecrop water requirement can support considerations on the effects of global warming in differentareas in the world
Improved large-scale crop water requirement estimation through new high-resolution reanalysis dataset
Full text linkEstimation of crop water needs is essential to understand the role of agriculture in the waterbalance modeling at various scales. In turn, this is relevant for water management purposes andfor the fulfilling of water-related environmental regulations. In this study, a comprehensiveassessment of crop water requirement at large scale is presented, both in terms of rainfall (greenwater) and irrigation (blue water).A water-balance model is built to provide estimates of actual evapotranspiration andaccompanying soil moisture by using high space-time resolution data. The new ERA5 reanalysisdataset, published by the ECMWF within the Copernicus monitoring system and obtained fromsatellite data and ground measurements, provides the precipitation and temperature inputvariables to the model. Data available at the hourly time scale are all aggregated on a daily scaleand used in the water balance model over a grid of cultivated areas from the MIRCA2000 dataset.Cultivated areas are available for 26 crops for year 2000 at a spatial resolution of 5 arcmin (about 9km at the Equator). Data from MIRCA2000 are separated between rainfed areas and areasequipped for irrigation and are characterized by specific monthly calendars of the crop growingseasons.The model performs the daily soil water balance throughout the whole year, considering all cropsat their growth stage and assuming as initial condition at each crop sowing date a monthlyaverage soil moisture. Results quantify the volumes of green and blue water necessary for cropgrowth and describe the spatial variability of the water requirements of each individual crop. Thehigh spatial and temporal resolution of Copernicus ERA5 data enables a great improvement in thecharacterization of hydro-climatic forcings with respect to previous assessments and a greateraccuracy in the crop water requirement estimates.Finally, the knowledge of water requirements is an important step to quantify the irrigationvolumes used in agriculture, on which there is a high uncertainty and little spatially distributedinformation. The model proposed enables the investigation of spatio-temporal variabilityassociated to varying meteorological forcings and of the effects of different irrigation techniques,enabling an improved management of water resources
Green and blue water use for agricultural production: Volumes and efficiencies
No full textThis chapter analyzes the evolution of water footprint associated to four major crops to define trends of water use and efficiency in agriculture. In particular, the separation of water use by source is considered, differentiating between green water (soil moisture originated from precipitation) and blue water (withdrawals from surface- and ground-water). Blue water contributes to about 10% of the total (green + blue) water footprint; however, it is central for humanity as it provides 42% of the global food production. The chapter focuses on the spatial and temporal variability of the blue water use and on the different role played by climate and anthropic factors in the definition of blue as well as total crop water footprint through a sensitivity analysis. The chapter presents the results about the variability in space of crop water footprint (green and blue) using maize to exemplify the discussion
ERA5-based global assessment of irrigation requirement and validation.
Full text linkWhile only 20% of harvested lands are actually irrigated, 40% of global agricultural production originates from irrigated areas. Therefore, assessing irrigation requirements is essential for the development of effective water-related policies for an efficient management of water resources. Moreover, global-scale analyses are becoming increasingly relevant, motivated by globalized production and international trade of food as well as by the need of common strategies to address climate change. In this study, a comprehensive model to estimate crop growth and irrigation requirements of 26 main crops at global scale is presented. The model computes a soil water balance using daily precipitation and reference evapotranspiration based on a high-resolution ERA5 reanalysis dataset from the European Copernicus Program. The irrigation requirement, defined as the minimum water volume to avoid water stress, is computed for year 2000 at the resolution of 5 arc-min (or 0.0833°) and aggregated at different spatial and temporal scales for relevant analyses. The estimated global irrigation requirements for 962 km3 is described in detail, also in relation to the spatial variability and to the monthly variation of the requirements. A focus on different areas of the world (California, Northern Italy and India) highlights the wealth of information provided by the model in different climatic conditions. National data of irrigation withdrawals have been used for an extensive comparison with model results. A crop-specific validation has also been made for the State of California, comparing model results with local data of irrigation volume and independent estimates of crop water use. In both cases, we found a good agreement between model results and real data
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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