Studies on Calf Diarrhoea in Mozambique: Prevalence of Bacterial Pathogens

The prevalence of diarrhoea in calves was investigated in 8 dairy farms in Mozambique at 4 occasions during 2 consecutive years. A total of 1241 calves up to 6 months of age were reared in the farms, and 63 (5%) of them had signs of diarrhoea. Two farms had an overall higher prevalence (13% and 21%) of diarrhoea. Faecal samples were collected from all diarrhoeal calves (n = 63) and from 330 healthy calves and analysed for Salmonella species, Campylobacter jejuni and enterotoxigenic Escherichia coli (ETEC). Salmonella spp. was isolated in only 2% of all calves. Campylobacter was isolated in 11% of all calves, irrespective of health condition, and was more frequent (25%) in one of the 2 diarrhoeal farms (p = 0.001). 80% of the isolates were identified as C. jejuni. No ETEC strains were detected among the 55 tested strains from diarrhoeal calves, but 22/55 (40%) strains from diarrhoeal calves and 14/88 (16%) strains from healthy calves carried the K99 adhesin (p = 0.001). 6,757 E. coli isolates were typed with a biochemical fingerprinting method (the PhenePlate™) giving the same E. coli diversity in healthy and diarrhoeal calves. Thus it was concluded: i) the overall prevalence of diarrhoea was low, but 2 farms had a higher prevalence that could be due to an outbreak situation, ii) Salmonella did not seem to be associated with diarrhoea, iii) Campylobacter jejuni was common at one of the 2 diarrhoeal farms and iv) ETEC strains were not found, but K99 antigen was more prevalent in E. coli strains from diarrhoeal calves than from healthy, as well as more prevalent in one diarrhoeal farm

Exploiting the information content of hydrological "outliers" for goodness-of-fit testing.

Abstract. Validation of probabilistic models based on goodness-of-fit tests is an essential step for the frequency analysis of extreme events. The outcome of standard testing techniques, however, is mainly determined by the behavior of the hypothetical model, FX(x), in the central part of the distribution, while the behavior in the tails of the distribution, which is indeed very relevant in hydrological applications, is relatively unimportant for the results of the tests. The maximum-value test, originally proposed as a technique for outlier detection, is a suitable, but seldom applied, technique that addresses this problem. The test is specifically targeted to verify if the maximum (or minimum) values in the sample are consistent with the hypothesis that the distribution FX(x) is the real parent distribution. The application of this test is hindered by the fact that the critical values for the test should be numerically obtained when the parameters of FX(x) are estimated on the same sample used for verification, which is the standard situation in hydrological applications. We propose here a simple, analytically explicit, technique to suitably account for this effect, based on the application of censored L-moments estimators of the parameters. We demonstrate, with an application that uses artificially generated samples, the superiority of this modified maximum-value test with respect to the standard version of the test. We also show that the test has comparable or larger power with respect to other goodness-of-fit tests (e.g., chi-squared test, Anderson-Darling test, Fung and Paul test), in particular when dealing with small samples (sample size lower than 20–25) and when the parent distribution is similar to the distribution being tested

Effects of disregarding seasonality on the distribution of hydrological extremes

Abstract. This paper deals with the seasonality of hydroclimatic extremes and with the problem of accounting for their non-homogeneous character in determining the design value. To this aim we devise a simple stochastic experiment in which extremes are produced by a non-homogeneous extreme value generation process. The design values are estimated in closed analytical form both in a peak over threshold framework and by using the standard annual maxima approach. In this completely controlled world of generated hydrological extremes, a statistical measure of the error associated to the adoption of a homogeneous model is introduced. The sensitivity of this measure, named return period ratio, to the typology and strength of seasonality is investigated. We find that neglecting seasonality induces a downward bias in design value estimators. The magnitude of the bias may be large when the peak over threshold approach is adopted, while the return period distortion is limited when the annual maxima are considered. An application to rainfall data from a 30 000 km2 region located in North-Western Italy is presented to better clarify the effects of disregarding seasonality in a real case

Connecting European snow cover variability with large scale atmospheric patterns

Abstract. Winter snowfall and its temporal variability are important factors in the development of water management strategies for snow-dominated regions. For example, mountain regions of Europe rely on snow for recreation, and on snowmelt for water supply and hydropower. It is still unclear whether in these regions the snow regime is undergoing any major significant change. Moreover, snow interannual variability depends on different climatic variables, such as precipitation and temperature, and their interplay with atmospheric and pressure conditions. This paper uses the EASE Grid weekly snow cover and Ice Extent database from the National Snow and Ice Data Center to assess the possible existence of trends in snow cover across Europe. This database provides a representation of snow cover fields in Europe for the period 1972–2006 and is used here to construct snow cover indices, both in time and space. These indices allow us to investigate the historical spatial and temporal variability of European snow cover fields, and to relate them to the modes of climate variability that are known to affect the European climate. We find that both the spatial and temporal variability of snow cover are strongly related to the Arctic Oscillation during wintertime. In the other seasons, weaker correlation appears between snow cover and the other patterns of climate variability, such as the East Atlantic, the East Atlantic West Russia, the North Atlantic Oscillation, the Polar Pattern and the Scandinavian Pattern

Climatic control on the variability of flood distribution

International audienceThe variability of the second order moments of flood peaks with respect to geomorphoclimatic basin characteristics was investigated. In particular, the behaviour of the coefficient of variation (Cv) of the series of annual maximum floods was analysed with respect to its dependence on physically consistent quantities. The results achieved were in fairly good agreement with real world observed characteristics and interesting insights on the relationship between Cv and basin size were found. It appears that Cv is controlled mainly by the climate and by some water loss features. Many observations reported in the literature show a decrease of Cv with basin area A, usually ascribed to the limited spatial extent of extreme events, which leads to a decrease with area of the Cv of areal rainfall intensity. An increase of Cv with the area is also sometimes observed for small basins. Such different behaviours were accounted for by the concurrent effect on two parameters that affect the Cv (A) relationship, representative of the way rainfall losses and effective rainfall intensity scale with the basin area.</p

Time-Dependent Z-R Relationships for Estimating Rainfall Fields from Radar Measurements

Abstract. The operational use of weather radars has become a widespread and useful tool for estimating rainfall fields. The radar-gauge adjustment is a commonly adopted technique which allows one to reduce bias and dispersion between radar rainfall estimates and the corresponding ground measurements provided by rain gauges. This paper investigates a new methodology for estimating radar-based rainfall fields by recalibrating at each time step the reflectivity-rainfall rate (Z-R) relationship on the basis of ground measurements provided by a rain gauge network. The power-law equation for converting reflectivity measurements into rainfall rates is readjusted at each time step, by calibrating its parameters using hourly Z-R pairs collected in the proximity of the considered time step. Calibration windows with duration between 1 and 24 h are used for estimating the parameters of the Z-R relationship. A case study pertaining to 19 rainfall events occurred in the north-western Italy is considered, in an area located within 25 km from the radar site, with available measurements of rainfall rate at the ground and radar reflectivity aloft. Results obtained with the proposed method are compared to those of three other literature methods. Applications are described for a posteriori evaluation of rainfall fields and for real-time estimation. Results suggest that the use of a calibration window of 2–5 h yields the best performances, with improvements that reach the 28% of the standard error obtained by using the most accurate fixed (climatological) Z-R relationship

Virtuous and Vicious Virtual Water Trade with Application to Italy

The current trade of agricultural goods, with connections involving all continents, entails for global exchanges of ‘‘virtual’’ water, i.e. water used in the production process of alimentary products, but not contained within. Each trade link translates into a corresponding virtual water trade, allowing quantification of import and export fluxes of virtual water. The assessment of the virtual water import for a given nation, compared to the national consumption, could give an approximate idea of the country’s reliance on external resources from the food and the water resources point of view. A descriptive approach to the understanding of a nation’s degree of dependency from overseas food and water resources is first proposed, and indices of water trade virtuosity, as opposed to inefficiency, are devised. Such indices are based on the concepts of self-sufficiency and relative export, computed systematically on all products from the FAOSTAT database, taking Italy as the first case study. Analysis of time series of the self-sufficiency and relative export can demonstrate effects of market tendencies and influence water-related policies at the international level. The goal of this approach is highlighting incongruent terms in the virtual water balances by the viewpoint of single products. Specific products, which are here referred to as ‘‘swap products’’, are in fact identified as those that lead to inefficiencies in the virtual water balance due to their contemporaneously high import and export. The inefficiencies due to the exchanges of the same products between two nations are calculated in terms of virtual water volumes. Furthermore, the cases of swap products are investigated by computing two further indexes denoting the ratio of virtual water exchanged in the swap and the ratio of the economic values of the swapped products. The analysis of these figures can help examine the reasons behind the swap phenomenon in trade

Evidence for increasing rainfall extremes remains elusive at large spatial scales: the case of Italy

The widespread perception of an increase in the severity of extreme rainstorms has not found yet clear confirmation in the scientific literature, often showing vastly different results. Especially for short‐duration extremes, spatial heterogeneities can affect the outcomes of large‐scale trend analyses, providing misleading results dependent on the adopted spatial domain. Based on the availability of a renewed and comprehensive database, the present work assesses the presence of regional trends in the magnitude and frequency of annual rainfall maxima for sub‐daily durations in Italy. Versions of the Mann‐Kendall test and a record‐breaking analysis, that considers the spatial correlation, have been adopted for the scope. Significant trends do not appear at the whole‐country scale, but distinct patterns of change emerge in smaller domains having homogeneous geographical characteristics. Results of the study underline the importance of a multi‐scale approach to regional trend analysis and the need of more advanced explanations of localized trends

Interannual variability of winter precipitation in the European Alps: relations with the North Atlantic Oscillation.

Abstract. The European Alps rely on winter precipitation for various needs in terms of hydropower and other water uses. Major European rivers originate from the Alps and depend on winter precipitation and the consequent spring snow melt for their summer base flows. Understanding the fluctuations in winter rainfall in this region is crucially important to the study of changes in hydrologic regime in river basins, as well as to the management of their water resources. Despite the recognized relevance of winter precipitation to the water resources of the Alps and surrounding regions, the magnitude and mechanistic explanation of interannual precipitation variability in the Alpine region remains unclear and poorly investigated. Here we use gridded precipitation data from the CRU TS 1.2 to study the interannual variability of winter alpine precipitation. We found that the Alps are the region with the highest interannual variability in winter precipitation in Europe. This variability cannot be explained by large scale climate patterns such as the Arctic Oscillation (AO), North Atlantic Oscillation (NAO) or the East Atlantic/West Russia (EA/WR), even though regions below and above the Alps demonstrate connections with these patterns. Significant trends were detected only in small regions located in the Eastern part of the Alps

Runoff regime estimation at high-elevation sites: a parsimonious water balance approach

Abstract. We develop a water balance model, parsimonious both in terms of parameterization and of required input data, to characterize the average runoff regime of high-elevation and scarcely monitored basins. The model uses a temperature threshold to partition precipitation into rainfall and snowfall, and to estimate evapotranspiration volumes. The role of snow in the transformation of precipitation into runoff is investigated at the monthly time scale through a specific snowmelt module that estimates melted quantities by a non-linear function of temperature. A probabilistic representation of temperature is also introduced, in order to mimic its sub-monthly variability. To account for the commonly reported rainfall underestimation at high elevations, a two-step precipitation adjustment procedure is implemented to guarantee the closure of the water balance. The model is applied to a group of catchments in the North-Western Italian Alps, and its performances are assessed by comparing measured and simulated runoff regimes both in terms of total bias and anomalies, by means of a new metric, specifically conceived to compare the shape of the two curves. The obtained results indicates that the model is able to predict the observed runoff seasonality satisfactorily, notwithstanding its parsimony (the model has only two parameters to be estimated). In particular, when the parameter calibration is performed separately for each basin, the model proves to be able to reproduce the runoff seasonality. At the regional scale (i.e., with uniform parameters for the whole region), the performance is less positive, but the model is still able to discern among different mechanisms of runoff formation that depend on the role of the snow storage. Because of its parsimony and the robustness in the approach, the model is suitable for application in ungauged basins and for large scale investigations of the role of climatic variables on water availability and runoff timing in mountainous regions