Uncertainty in river discharge observations: a quantitative analysis

Abstract. This study proposes a framework for analysing and quantifying the uncertainty of river flow data. Such uncertainty is often considered to be negligible with respect to other approximations affecting hydrological studies. Actually, given that river discharge data are usually obtained by means of the so-called rating curve method, a number of different sources of error affect the derived observations. These include: errors in measurements of river stage and discharge utilised to parameterise the rating curve, interpolation and extrapolation error of the rating curve, presence of unsteady flow conditions, and seasonal variations of the state of the vegetation (i.e. roughness). This study aims at analysing these sources of uncertainty using an original methodology. The novelty of the proposed framework lies in the estimation of rating curve uncertainty, which is based on hydraulic simulations. These latter are carried out on a reach of the Po River (Italy) by means of a one-dimensional (1-D) hydraulic model code (HEC-RAS). The results of the study show that errors in river flow data are indeed far from negligible

Evidences of relationships between statistics of rainfall extremes and mean annual precipitation: an application for design-storm estimation in northern central Italy

International audienceSeveral hydrological analyses need to be founded on a reliable estimate of the design storm, which is the expected rainfall depth corresponding to a given duration and probability of occurrence, usually expressed in terms of return period. The annual series of precipitation maxima for storm duration ranging from 15 min to 1 day are observed at a dense network of raingauges sited in northern central Italy are statistically analyzed using an approach based on L-moments. The study investigates the statistical properties of rainfall extremes and identifies important relationships between these properties and the mean annual precipitation (MAP). On the basis of these relationships, we develop a regional model for estimating the rainfall depth for a given storm duration and recurrence interval in any location of the study region. The reliability of the regional model is assessed through Monte Carlo simulations. The results are relevant given that the proposed model is able to reproduce the statistical properties of rainfall extremes observed for the study region

Increasing flood risk under climate change: a pan-European assessment of the benefits of four adaptation strategies

Future flood risk in Europe is likely to increase due to a combination of climatic and socio-economic drivers. Effective adaptation strategies need to be implemented to limit the impact of river flooding on population and assets. This research builds upon a recently developed flood risk assessment framework at European scale to explore the benefits of adaptation against extreme floods. Four different adaptation measures are simulated in a physically based modeling framework, including the rise of flood protections, reduction of the peak flows through water retention, reduction of vulnerability and relocation to safer areas. Their sensitivity is assessed in several configurations under a high-end global warming scenario over the time range 1976-2100. Results suggest that the future increase in expected damage and population affected by river floods can be compensated by a combination of different adaptation measures. The adaptation efforts should favor measures targeted at reducing the impacts of floods, rather than trying to avoid them. Conversely, adaptation plans only based on rising flood protections have the effect of reducing the frequency of small floods and exposing the society to less-frequent but catastrophic floods and potentially long recovery processes.JRC.H.7-Climate Risk Managemen

Relationships between statistics of rainfall extremes and mean annual precipitation: an application for design-storm estimation in northern central Italy

Several hydrological analyses need to be founded on a reliable estimate of the design storm, which is the expected rainfall depth corresponding to a given duration and probability of occurrence, usually expressed in terms of return period. The annual series of precipitation maxima for storm duration ranging from 15 min to 1 day, observed at a dense network of raingauges sited in northern central Italy, are analyzed using an approach based on L-moments. The analysis investigates the statistical properties of rainfall extremes and detects significant relationships between these properties and the mean annual precipitation (MAP). On the basis of these relationships, we developed a regional model for estimating the rainfall depth for a given storm duration and recurrence interval in any location of the study region. The applicability of the regional model was assessed through Monte Carlo simulations. The uncertainty of the model for ungauged sites was quantified through an extensive cross-validation

Water management for irrigation, crop yield and social attitudes: a socio-agricultural agent-based model to explore a collective action problem

When rainfall does not meet crop water requirements, supplemental irrigation is needed to maintain productivity. On-farm ponds can prevent excessive groundwater exploitation - to the benefit of the whole community - but they reduce the cultivated area and require investments by each farmer. Thus, choosing the source of water for irrigation (groundwatervson-farm pond) is a problem of collective action. An agent-based model is developed to simulate a smallholder farming system; the farmers' long-/short-view orientation determines the choice of the water source. We identify the most beneficial water source for economic gain and its stability, and how it can change across communities and under future climate scenarios. By using on-farm ponds, long-view-oriented farmers provide collective advantages but have individual advantages only under extreme climates; a tragedy of the commons is always possible. Changes in farmers' attitudes (and hence sources of water) based on previous experiences can worsen the economic outcome

The seventh facet of uncertainty:wrong assumptions, unknowns and surprises in the dynamics of human–water systems

The scientific literature has focused on uncertainty as randomness, while limited credit has been given to what we call here the “seventh facet of uncertainty”, i.e. lack of knowledge. This paper identifies three types of lack of understanding: (i) known unknowns, which are things we know we don’t know; (ii) unknown unknowns, which are things we don’t know we don’t know; and (iii) wrong assumptions, things we think we know, but we actually don’t know. Here we discuss each of these with reference to the study of the dynamics of human–water systems, which is one of the main topics of Panta Rhei, the current scientific decade of the International Association of Hydrological Sciences (IAHS), focusing on changes in hydrology and society. In the paper, we argue that interdisciplinary studies of socio-hydrological dynamics leading to a better understanding of human–water interactions can help in coping with wrong assumptions and known unknowns. Also, being aware of the existence of unknown unknowns, and their potential capability to generate surprises or black swans, suggests the need to complement top-down approaches, based on quantitative predictions of water-related hazards, with bottom-up approaches, based on societal vulnerabilities and possibilities of failure

Eat Healthy to Live Healthy: Habits and Trends

“Eat healthy to live healthy” is a fundamental mantra for long-term wellbeing. This Special Issue was developed to address challenges in prevention strategies based on nutritional interventions and lifestyle changes throughout one’s life, from fetus to adulthood

Non elementary methods in combinatorial number theory: Roth's and Sarkozy's theorems

Roth's theorem states that every set A with positive density has an arithmetic progression of length 3, i.e. x, x+r, x+2r are in A. In this work we present two different arguments used to proof Roth's theorem and we translate them to the nonstandard framework. The first argument, called density increment, aims to recursively find arithmetic progressions on which the set A has increased density. The second argument, called energy increment, aims to decompose the set in a "structured" component plus a "random" component. Using the transfer principle we translate the density increment argument to the nonstandard setting where we obtain a slightly easier argument at the cost of losing the estimate found in the standard case. For the energy increment argument, we use the Loeb measure and the conditional expectation in nonstandard context to find a decomposition. In the last chapter we adapt the density increment argument to Sarkozy's theorem (which states that a set of positive density contains two elements whose difference is a perfect square) using an estimate on Weyl sums and a theorem on quadratic recurrence

Multiple hazards and risk perceptions over time: the availability heuristic in Italy and Sweden under COVID-19

The severe impact of global crises, such as COVID-19 and climate change, is plausibly reshaping the way in which people perceive risks. In this paper, we examine and compare how global crises and local disasters influence public perceptions of multiple hazards in Italy and Sweden. To this end, we integrate information about the occurrence of hazardous events with the results of two nationwide surveys. These included more than 4000 participants and were conducted in two different phases of the COVID-19 pandemic corresponding to low (August 2020) and high (November 2020) levels of infection rates. We found that, in both countries, people are more worried about risks related to experienced events. This is in line with the cognitive process known as the availability heuristic: individuals assess the risk associated with a given hazard based on how easily it comes to their mind. Epidemics, for example, are perceived as less likely and more impactful in Italy compared to Sweden. This outcome can be explained by cross-country differences in the impact of, as well as governmental responses to, COVID-19. Notwithstanding the ongoing pandemic, people in both Italy and Sweden are highly concerned about climate change, and they rank it as the most likely threat