1,721,025 research outputs found
Simulazione stocastica dei deflussi giornalieri: metodi di determinazione delle stime inverse di pioggia efficace e relative proprietà statistiche
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A comparison of direct and inverse estimates of effective rainfall at the daily time-scale
No full textPoster at the VII IAHS Scientific Assembl
Charting out the future agricultural trade and its impact on water resources
Full text linkInternational agricultural trade triggers inter-dependency among distant countries, not only in economic terms but also under an environmental perspective. Agricultural trade has been shown to drive environmental threats pertaining to biodiversity loss and depletion and pollution of freshwater resources. Meanwhile, trade can also encourage production where it is most efficient, hence minimizing the use of natural resources required by agriculture. In this study, we provide a country-level assessment of the future international trade for 6 primary crops and 3 animal products composing 70% of the human diet caloric content. We set up four variegate socio-economic scenarios with different level of economic developments, diets habits, population growth dynamics, and levels of market liberalization. Results show that the demand of agricultural goods and the correspondent trade flow will increase with respect to current levels by 10–50% and 74–178% by 2050, respectively. The largest increase in the amount of traded goods is expected under the Economic Optimism scenario that will see an average trade flow of 2830 kcal/cap/day (i.e., nearly doubling the current per-capita flow). Most of the increase will be driven by the trade of crops for animal feeding, particularly maize will be the most traded crop. The trade networks architecture in 2050 and 2080 will be very different from the one we actually know, with a clear shift of the trade pole from the Western toward the Eastern economies. The dramatic changes of global food-sources and trade patterns will jeopardize the water resources of new regions while exacerbating the pressure in those areas that will continue serving food also in the future. In spite of this, trade may annually save around 40–60 m3 of water per person, compared to a situation where countries are self-sufficient
Model selection techniques for the frequency analysis of hydrological extremes
No full textThe frequency analysis of hydrological extremes requires fitting a probability distribution to the observed data to suitably represent the frequency of occurrence of rare events. The choice of the model to be used for statistical inference is often based on subjective criteria, or it is considered a matter of probabilistic hypotheses testing. In contrast, specific tools for model selection, like the well-known Akaike information criterion (AIC) and the Bayesian information criterion (BIC), are seldom used in hydrological applications. The objective of this study is to verify whether the AIC and BIC work correctly when they are applied to identifying the probability distribution of hydrological extremes, i.e., when the available samples are small and the parent distribution is highly asymmetric. An additional model selection criterion, based on the Anderson-Darling goodness-of-fit test statistic, is here proposed, and the performances of the three methods are compared through an extensive numerical analysis. The capability of the three criteria to recognize the correct parent distribution from the available data samples varies from case to case, and it is rather good in some cases (in particular when the parent is a two-parameter distribution) and unsatisfactory in others. An application to flood peak time series from 1000 catchments located in the United Kingdom provides some further information on the qualities and drawbacks of the considered criteria. From the numerical simulations and data-based analyses it can be concluded that the three model selection techniques considered here produce results of comparable quality
Measuring economic water scarcity in agriculture: a cross-country empirical investigation
Full text linkHigh water availability enhances agricultural performance and food security. However, many countries where water is abundant according to hydrological indicators face difficulties in the utilization of water in agriculture, being in a situation of economic water scarcity (EWS), due to lack of institutional and material means for water management and governance. EWS faces a stronger challenge of measurability, if compared to physical water scarcity. Since the Sustainable Development Goal Indicator on Integrated management of domestic and transboundary water resources (IWRM) is a unique attempt to quantify information on water management at a national level, we explore whether it can represent a valid metric for EWS measurement. We first show that a high level of water management is neither necessarily associated to high economic power of the country nor to low physical water availability. Then, we analyze whether the indicator can predict typical EWS situations such as low agricultural productivity and inefficient water use. Although the importance of water institutions for agriculture is well known through case studies at the local level, we make the first attempt to quantify the strengths of this relation at a global scale for different crops in climatic diverse countries. We detect a positive and significant association between IWRM level and yield, and consequently a negative and equally significant association between the IWRM level and the crop water footprint. Statistical significance holds also when potentially confounding variables are included in a multiple regression analysis. We infer from this analysis that good water management, as detectable through the IWRM indicator, improves land productivity and water saving, in turn mitigating EWS. Our findings pave the way toward the use of the IWRM indicator as a valuable tool for measuring EWS in agriculture, bridging the measurability gap of economic water scarcity, with straightforward policy implications in favour of investments in water management as a lever for enhancing food security and development
Ever-increasing agricultural land and water productivity: A global multi-crop analysis
Full text linkProducing more nutritious food with less resources, while preserving the natural ecosystems, is a key challenge of our society. In this paper we propose a macronutrient-based indicator of productivity, the nutrient land productivity (NLP), to measure the amount of calories, proteins, and fats produced per hectare of cropland. Over the period 1961-2016, we find that the global NLP has increased by 2.7-2.9% per year for calories and proteins, and between 2.1 and 4.6% for fats. However, such rates exhibit significant spatial patterns throughout the world depending on whether farmers adopted intensification (e.g. Eastern and South Asia, North America) or extensification (e.g. Sub-Saharan Africa) practices to boost nutrients production. Our outcomes, based on a production basket including 144 crops, show that cereals and pulses cultivations have been dominated by intensification practices coupled with a stable or decreasing harvested area. Conversely, for fruits and nuts cultivations extensification prevailed over intensification, while for oil crops most cultivations experienced a coupled action of the two practises. Finally, by coupling the NLP indicator with its nutrient water productivity (NWP) counterpart, we find that NWP has mainly changed following land patterns, with the exception of locations having undergone significant crop substitutions, namely from less toward more water demanding crops. Indeed, the transition toward perennial crops has increased the evapotranspiration demand over cultivated land by 14% on a global average
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