1,720,993 research outputs found
Water footprint assessment in space and time to support local and global sustainability
Full text linkCrop production vastly dominates global freshwater use, accounting for nearly 70% of the total withdrawal and around 90% of the total consumption. Human beings are currently using 30% of precipitation-recharged soil moisture and less than 10% (i.e., 3800 km3yr-1}) of the maximum available renewable freshwater resources in the word. Notwithstanding, water resource availability is highly variable in space and time, and different studies have shown a significant mismatch between water use and availability. Accordingly, two-third of global population live under conditions of sever water scarcity for at least one month per year. Moreover, as a consequence of larger food demand and changing living standards, toward more caloric and protein intense diets, global water use has increased by 6-8 times during the past century. At the same time, areas equipped for irrigation have doubled with actual irrigation having unavoidable consequences for aquifers and river ecosystems. Future scenarios of climate change are expected to worsen this picture. Indeed, the rising trends of water demand may continue in the future, harshening the conditions in areas reaching critical thresholds of acceptable water balance. In this context, the goals of this thesis are (i) to identify the main determinants of water use efficiency in agriculture; (ii) to introduce a link prediction algorithm applied to the international trade of agricultural goods; (iii) to introduce a novel indicator to monitor the (mis)match between water use and supply. This thesis quantifies the crop water footprint (CWF, or amount of water use per unit weight of crop) of nine major crops (i.e., wheat, rice, maize, soybean, barley, potatoes, sugar cane, sugar beet, and cotton) through a daily soil water balance run on a grid with a 5’x5’ spatial resolution. The model considers scenarios of rainfed and irrigated crops, also exploring multi-cropping patterns. Quantitative assessments of green and blue (separated into surface and ground) CWF are mapped and analysed in order to identify and monitor the major local drivers of water use, such as climatic conditions, precipitation rate during the growing season, cropping calendar, soil properties, crop yields and agricultural management practises. Results show that crop yield is the most important determinant of the total CWF. Moreover, results of a first-order sensitivity analysis show that, e.g., wheat CWF is mostly sensitive to the length of the growing period, rice CWF to the reference evapotranspiration depth, soybean and maize CWF to the planting date. The CWF model has been adopted also to validate a Fast Track approach, recently developed to study the CWF changes in time, which are generally kept aside in Water Footprint assessments. This approach ascribes the temporal CWF changes only to the yield variations, while it assumes the evapotranspiration depth as time-invariant. This thesis shows the good performance of this approach and also provides an uncertainty analysis. Accordingly, the Fast Track approach shows an error three times smaller than the uncertainty associated with the CWF model. Following the yields patterns, CWF has significantly decreased along the period 1961-2013, but with different rates depending on the crop and the location of the production sites. In the second part of the thesis, the crop water footprint is compared to the local water availability, to assess the sustainability of crop production. In order to understand the size of local (mis)match between crop water use and available water resources, we introduce a water debt repayment time indicator (WD). The WD quantifies the time the hydrological cycle takes to replenish the water resources used for annual crop production, distinguishing the different sustainability levels of soil-, surface-, and ground-water. This indicator highlights the locations and typology of threats imposed by agricultural production on water resources. On a global average, we found that wheat and rice production critically overuses ground water resources, especially in China and the US, and cotton production overuses both surface -and ground-water, particularly in the US. Locally, unsustainable annual crop production is found over the Sabarmati basin (due to wheat) in India, and in the Chao Phraya basin (due to rice and sugarcane) in Thailand, where the water debt repayment time exceeds 5 years in many cultivated areas. Including in the same framework analyses on water use efficiencies (through the CWF) and measure of water use (un)sustainability (through the WD) enables screening analyses at finding specific solutions in cases of low water use efficiencies and/or in critical situation of overuses. While local drivers monitor the water use for production, global drivers attempt to explore the globalization of water resources that happens through the international trade of agricultural goods. Why do countries become trade patterns, hence establishing a more or less stable relation, which implies externalization of water resources use? The third part of this thesis answers to this question through the elaboration of a threshold-based link prediction algorithm, aiming at finding the drivers behind link activation. Accordingly, a link is expected to exist depending on the predicted virtual water volume traded from the source node to the target node: the link is modelled as active when the volume is higher than 1000 m3y-1, non-active otherwise. This algorithm is able to capture 84% of the currently active links and 93% of non-active links. Country population, geographical distance between countries and fertilizers use are the major drivers to explain link existence. The link prediction model may be applied to build future scenarios of virtual water trade, in order to understand how local consumption and production patterns could affect the trade network.
Finally, in order to understand how close water demand to water availability is, we introduce a water debt (WD) indicator. The WD quantifies the payback time the hydrological cycle takes to replenish the water resources used for annual crop production. Hence, it highlights the locations and typology of threats imposed by agricultural production on water resources. E.g., the annual production of the nine study crops arise a WD of 10 years with the ground water resources of the US High Plain aquifer, mostly as a consequence of maize and soybean production. This indicator intends to connect and integrate water resource management with other environmental issues, such as the carbon footprint. In short, the thesis contributes advancing our knowledge in the spatio-temporal explicit water footprint assessments, virtual water trade network, sustainable water use. The models developed in this thesis and the results shown in the following chapters allow (i) to explore pathways toward improved water use efficiencies and more sustainable water withdrawals, (ii) to model backward and forward trade network dynamics, and (iii) to project future water use scenarios
High-income countries dietary trajectories diverge from the global nutrition transition
No full textCountries with rising incomes typically undergo a nutrition transition, marked by increasing consumption of animal-sourced foods and declining intakes of cereals and other plant-based products. However, large-scale, data-driven assessments of how diets worldwide align with this transition remain scarce. Here, we analyse dietary regimes in 188 countries, from 1970 to 2021, covering 370 food products, and identify a nutrition transition occurring at the global scale. On average, every tenfold increase in a country’s per capita gross domestic product corresponds to a 13% rise in the dietary share of calories supplied by animal products and to a 15% decline in the share supplied by cereals. Nonetheless, in several high-income countries, such as Canada, Finland, Norway, New Zealand, Switzerland, and the UK, the dietary composition diverges from global trends, exhibiting declining caloric shares from animal-sourced foods alongside rising contributions from cereals and plant-based product
Efficient agricultural practices in Africa reduce crop water footprint despite climate change, but rely on blue water resources
Full text linkGreen 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
Temporal variability of green and blue water footprint worldwide
Full text linkWater footprint assessment is becoming widely used in the scientific literature and it is proving useful in a number of multidisciplinary contexts. Given this increasing popularity, measures of green and blue water footprint (or virtual water content, VWC) require evaluations of uncertainty and variability to quantify the reliability of proposed analyses. As of today, no studies are known to assess the temporal variability of crop VWC at the global scale; the present contribution aims at filling this gap. We use a global high-resolution distributed model to compute the VWC of staple crops (wheat and maize), basing on the soil water balance, forced by hydroclimatic imputs, and on the total crop evapotranspiration in multiple growing seasons. Crop actual yield is estimated using country-based yield data, adjusted to account for spatial variability, allowing for the analysis of the different role played by climatic and management factors in the definition of crop yield. The model is then run using hydroclimatic data, i.e. precipitation and potential evapotranspiration, for the period 1961-2013 as taken from the CRU database (CRU TS v. 3.23) and using the corresponding countrybased yield data from FAOSTAT. Results provide the time series of total evapotranspiration, actual yield and VWC, with separation between green and blue VWC, and the overall volume of water used for crop production, both at the cell scale (5x5 arc-min) and aggregated at the country scale. Preliminary results indicate that total (green+blue) VWC is, in general, weekly dependent on hydroclimatic forcings if water for irrigation is unlimited, because irrigated agriculture allows to compensate temporary water shortage. Conversely, most part of the VWC variability is found to be determined by the temporal evolution of crop yield. At the country scale, the total water used by countries for agricultural production has seen a limited change in time, but the marked increase in the water-use efficiency expressed by VWC has determined an increase of production. Such increase has helped to meet the increasing global food demand in the past 50 years
To trade or not to trade: Link prediction in the virtual water network
No full textIn the international trade network, links express the (temporary) presence of a commercial exchange of goods between any two countries. Given the dynamical behaviour of the trade network, where links are created and dismissed every year, predicting the link activation/deactivation is an open research question. Through the international trade network of agricultural goods, water resources are ‘virtually’ transferred from the country of production to the country of consumption. We propose a novel methodology for link prediction applied to the network of virtual water trade. Starting from the assumption of having links between any two countries, we estimate the associated virtual water flows by means of a gravity-law model using country and link characteristics as drivers. We consider the links with estimated flows higher than 1000 m3/year as active links, while the others as non-active links. Flows traded along estimated active links are then re-estimated using a similar but differently-calibrated gravity-law model. We were able to correctly model 84% of the existing links and 93% of the non-existing links in year 2011. It is worth to note that the predicted active links carry 99% of the global virtual water flow; hence, missed links are mainly those where a minimum volume of virtual water is exchanged. Results indicate that, over the period from 1986 to 2011, population, geographical distances between countries, and agricultural efficiency (through fertilizers use) are the major factors driving the link activation and deactivation. As opposed to other (network-based) models for link prediction, the proposed method is able to reconstruct the network architecture without any prior knowledge of the network topology, using only the nodes and links attributes; it thus represents a general method that can be applied to other networks such as food or value trade networks
Water to Food : A data-viz book about the water footprint of food production and trade
Full text linkEnvironmental Footprints of Red Wine Production in Piedmont, Italy
Full text linkItaly is a global top wine producer, with emphasis on high-quality wines. This study
investigates the Carbon Footprint (CF), Water Footprint (WF), and Ecological Footprint
(EF) of twelve red wine producers in Piedmont, Northern Italy. The analysis was based
on a 0.75 L wine bottle as functional unit (FU). Twelve producers were interviewed and
given questionnaires, which made it possible to gather primary data for the environmental
evaluation that described vineyard and agricultural operations and wine production. The
average CF was 0.88 ± 0.3 kg CO2eq, with 44% of CF associated with the glass bottle,
20% to the diesel fuel fed to the agricultural machines, 32% to electricity consumption, and
4% to other contributions. The average WF was 881 ± 252.4 L, with 98% Green WF due
to evapotranspiration, and 2% Blue and Grey WF. The average EF was 81.3 ± 57.2 global
ha, 73% ascribed to the vineyard area and 27% to CO2 assimilation. The obtained CF and
WF values align with existing literature, while no comparison is possible for the EF data,
which are previously unknown. To reduce the environmental impacts of wine production,
actions like using recycled glass bottles, electric agricultural machines and renewable
energy can help. However, high-quality wine production in Piedmont is deeply rooted in
tradition and mostly managed by small producers. Further research should investigate the
social acceptance of such actions, and policies supporting economic incentives could be
key enablers
Spatial heterogeneity and sensitivity analysis of crop virtual water content at a global scale
No full textIn this study, the green and blue virtual water content (VWC) of four staple crops (i.e., wheat, rice, maize, and soybean) are quantified at a high resolution scale, for the period 1996-2005, and a sensitivity analysis is performed for model parameters. In each grid cell, the crop VWC is obtained by the ratio between the total crop evapotranspiration over the growing season and the crop actual yield. The evapotranspiration is determined with a daily soil water balance that takes into account crop and soil properties, production conditions, and climate. The actual yield is estimated using country-based values provided by the FAOSTAT database multiplied by a coefficient adjusting for the spatial variability within countries. The model improves on previous works by using the newest available data and including multi-cropping practices in the evaluation. The overall water use (blue+green) for the global production of the four grains investigated is 2673 km3/yr. Food production almost entirely depends on green water (>90%), but, when applied, irrigation makes production more water efficient, thus requiring lower VWC. The spatial variability of the virtual water content is partly driven by the yield pattern with an average correlation coefficient of 0.83, and partly by reference evapotranspiration with correlation coefficient of 0.27. Wheat shows the highest spatial variability since it is grown under a wide range of climatic conditions, soil properties, and agricultural practices. The sensitivity analysis is performed to understand how uncertainties in input data propagate and impact the virtual water content accounting. In each cell fixed changes are introduced to one input parameters at a time, and a sensitivity index, SI, is determined as the ratio between the variation of VWC referred to its baseline value and the variation of the input parameter with respect to its reference value. VWC is found to be most sensitive to planting date (PD), followed by the length of the growing period (LGP) and the crop actual yield (Ya), while it is less sensitive to the reference evapotranspiration (ET0) and available soil water content (AWC)
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