1,721,028 research outputs found
Linking water resources to food security through virtual water
Full text linkThe largest use of global freshwater resources is related to food production. While each day we drink about 2 liters of water, we consume (eating) about 4000 liters of "virtual water", which represents the freshwater used to produce crop-based and livestock-based food. Considering human water consumption as a whole, most part originates from agriculture (85.8%), and only minor parts come from industry (9.6%) or households (4.6%). These numbers shed light on the great pressure of humanity on global freshwater resources and justify the increasing interest towards this form of environmental impact, usually known as "water footprint". Virtual water is a key variable in establishing the nexus between water and food. In fact, water resources used for agricultural production determine local food availability, and impact the international trade of agricultural goods. Trade, in turn, makes food commodities available to nations which are not otherwise self-sufficient, in terms of water resources or food, and it establishes an equilibrium between food demand and production at the global scale. Therefore, food security strongly relies on international food trade, but also on the use of distant and foreign water resources, which need to be acknowledged and investigated. Virtual water embedded in production and international trade follows the fate of food on the trade network, generating virtual flows of great magnitude (e.g., 2800 km^3 in 2010) and defining local and global virtual water balances worldwide. The resulting water-food nexus is critical for the societal and economic development, and it has several implications ranging from population dynamics to the competing use of freshwater resources, from dietary guidelines to globalization of trade, from externalization of pollution to policy making and to socio-economic wealth. All these implications represent a great challenge for future research, not only in hydrology but in the many fields related to this interdisciplinary topic. Virtual water and water footprint accounting provide the tools for understanding such implications and to describe, quantify, and investigate the inextricable link existing between water resources and food securit
Modello stocastico per le fluttuazioni della falda superficiale con condizioni esterne variabili
No full textStochastic description of infiltration between aquifers
Full text linkAim of this work is to propose a stochastic description of the leakage between two aquifers separated by a semi-permeable layer with low hydraulic conductivity. The source of uncertainty here considered is the random fluctuation of the phreatic surface of surficial aquifer, originated from random rainfall events. The study focuses on an area surrounding a pumping well penetrating the deep aquifer and impacting its piezometric level, where infiltration from the surficial aquifer can be more harmful. Closed form expressions for the leakage between the surficial and the deep aquifer are used to obtain the long-term probability distribution of leakage flow rate, assuming the shallow phreatic surface dynamics modeled with a Poisson- driven stochastic process. A sensitivity analysis is performed to verify the variability of the probability distribution of leakage within the range of feasible parameter values, then the stochastic model is applied to three field cases where time series of the piezometric levels of the phreatic aquifer are available. Results show that the induced variability of the discharge flowing between aquifers is remarkable and that in general it cannot be neglected despite the low hydraulic conductivity of the semi-permeable layer. The proposed probabilistic model is a useful tool for evaluating the risk associated to contaminant transport into deep aquifers and its fate in relation to groundwater withdrawal
Food-water security and virtual water trade in the Middle East and North Africa
No full textThe purpose of this study is to analyze the political economy of food-water security in the water-scarce Middle East and North Africa region. The study deploys the lens of virtual water trade to determine how the region's economies have met their rising food-water requirements over the past three decades. It is shown that the region's water and food security currently depend to a considerable extent on water from outside the region, ‘embedded' in food imports and accessed through trade. The analysis includes blue (surface and groundwater) and green water resource
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
Dinamica della soggiacenza della falda superficiale piemontese in relazione alle precipitazioni
Full text linkQuesto studio si pone l’obbiettivo di identificare, a partire dalle serie temporali delle precipitazioni e della soggiacenza dell’acquifero freatico della pianura piemontese, il trend della soggiacenza e successivamente la correlazione tra soggiacenza e precipitazioni, per identificare le caratteristiche della risposta della falda superficiale alle precipitazioni. L’area di riferimento riguarda la pianura piemontese, circa 6850 km2, caratterizzata dalla presenza del bacino del Po e notevolmente influenzata dalla presenza di infrastrutture e derivazioni irrigue per uso agricolo. Negli ultimi anni, la relazione tra precipitazioni e livello piezometrico in quest’area è stata oggetto di diversi studi che hanno considerato serie temporali di durata minore o aree di estensione inferiore a quelle qui considerate
Significant drivers of the virtual water trade evaluated with a multivariate regression analysis
Full text linkInternational trade of food is vital for the food security of many countries, which rely on trade to compensate for an agricultural production insufficient to feed the population. At the same time, food trade has implications on the distribution and use of water resources, because through the international trade of food commodities, countries virtually displace the water used for food production, known as "virtual water". Trade thus implies a network of virtual water fluxes from exporting to importing countries, which has been estimated to displace more than 2 billions of m3 of water per year, or about the 2% of the annual global precipitation above land. It is thus important to adequately identify the dynamics and the controlling factors of the virtual water trade in that it supports and enables the world food security. Using the FAOSTAT database of international trade and the virtual water content available from the Water Footprint Network, we reconstructed 25 years (1986-2010) of virtual water fluxes. We then analyzed the dependence of exchanged fluxes on a set of major relevant factors, that includes: population, gross domestic product, arable land, virtual water embedded in agricultural production and dietary consumption, and geographical distance between countries. Significant drivers have been identified by means of a multivariate regression analysis, applied separately to the export and import fluxes of each country; temporal trends are outlined and the relative importance of drivers is assessed by a commonality analysis. Results indicate that population, gross domestic product and geographical distance are the major drivers of virtual water fluxes, with a minor (but non-negligible) contribution given by the agricultural production of exporting countries. Such drivers have become relevant for an increasing number of countries throughout the years, with an increasing variance explained by the distance between countries and a decreasing role of the gross domestic product. The worldwide adjusted coefficient of determination of fitted gravity-law model is 0.57 (in 2010), and it has increased in time, confirming the good descriptive capability of selected drivers for the virtual water trad
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
Probabilistic nonlinear prediction of river flows
Full text linkIn the recent past the Nonlinear Prediction (NLP) method, initially developed in the context of nonlinear system dynamics, has been successfully applied to river flow deterministic forecasting. In this work we propose a probabilistic approach to the NLP method, which allows to estimate the full probability distribution of the predicted discharge values, thus providing a useful information to quantify the uncertainty related to the forecast. The ineffective search of the best point prediction is therefore abandoned in favour of the quantification of the forecast process reliability. An ensemble technique is also applied to the choice of the parameter values in order to optimise the prediction and to avoid problems of model calibration. This probabilistic NLP method is applied to a river flow time series, and the obtained results underline the effectiveness and reliability of the proposed approac
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