Space-time modeling of soil moisture: Stochastic rainfall forcing with heterogeneous vegetation

The present paper complements that of Isham et al. (2005), who introduced a space-time soil moisture model driven by stochastic space-time rainfall forcing with homogeneous vegetation and in the absence of topographical landscape effects. However, the spatial variability of vegetation may significantly modify the soil moisture dynamics with important implications for hydrological modeling. In the present paper, vegetation heterogeneity is incorporated through a two dimensional Poisson process representing the coexistence of two functionally different types of plants (e.g., trees and grasses). The space-time statistical structure of relative soil moisture is characterized through its covariance function which depends on soil, vegetation, and rainfall patterns. The statistical properties of the soil moisture process averaged in space and time are also investigated. These properties are especially important for any modeling that aggregates soil moisture characteristics over a range of spatial and temporal scales. It is found that particularly at small scales, vegetation heterogeneity has a significant impact on the averaged process as compared with the uniform vegetation case. Also, averaging in space considerably smoothes the soil moisture process, but in contrast, averaging in time up to 1 week leads to little change in the variance of the averaged process

Regional analysis of runoff thresholds behaviour in Southern Italy based on theoretically derived distributions

The analysis of runoff thresholds and, more in general, the identification of main mechanisms of runoff generation controlling the flood frequency distribution is investigated, by means of theoretically derived flood frequency distributions, in the framework of regional analysis. Two nested theoretically-derived distributions are fitted to annual maximum flood series recorded in several basins of Southern Italy. Results are exploited in order to investigate heterogeneities and homogeneities and to obtain useful information for improving the available methods for regional analysis of flood frequency

Flood quantiles estimation based on theoretically derived distributions: regional analysis in Southern Italy

A regional probabilistic model for the estimation of medium-high return period flood quantiles is presented. The model is based on the use of theoretically derived probability distributions of annual maximum flood peaks (DDF). The general model is called TCIF (Two-Component IF model) and encompasses two different threshold mechanisms associated with ordinary and extraordinary events, respectively. Based on at-site calibration of this model for 33 gauged sites in Southern Italy, a regional analysis is performed obtaining satisfactory results for the estimation of flood quantiles for return periods of technical interest, thus suggesting the use of the proposed methodology for the application to ungauged basins. The model is validated by using a jack-knife cross-validation technique taking all river basins into consideration

Best Fit and Selection of Theoretical Flood Frequency Distributions Based on Different Runoff Generation Mechanisms

Theoretically derived distributions allow the detection of dominant runoff generation mechanisms as key signatures of hydrologic similarity. We used two theoretically derived distributions of flood peak annual maxima: the first is the ―IF‖ distribution, which exploits the variable source area concept, coupled with a runoff threshold having scaling properties; the second is the Two Component-IF (TCIF) distribution, which generalizes the IF distribution, and is based on two different threshold mechanisms, associated with ordinary and extraordinary events, respectively. By focusing on the application of both models to two river basins, of sub-humid and semi-arid climate in Southern Italy, we present an ad hoc procedure for the estimation of parameters and we discuss the use of appropriate techniques for model selection, in the case of nested distributions

Effects of runoff thresholds on flood frequency distributions

International audienceRunoff generation during extreme floods usually occurs whenever rainfall forcing exceeds a given threshold. In many cases, different thresholds may be identified as responsible of the hydrological losses during ordinary events or extraordinary events at the basin scale. Such thresholds are shown to be related to the dynamics of soil saturation of the river basin and to account for the high skewness of their annual flood distributions. In basins where ordinary floods are mostly due to a small portion of the surface which is particularly prone to produce runoff, depending on permeability of a river basin and its antecedent soil moisture conditions, severe rainfall may exceed a basin-wide soil storage threshold and produce the so-called outlier events responsible of the high skewness of floods distributions. In this context, the derived theoretical model based on the concept of variable contributing area to peak flow proposed by Iacobellis and Fiorentino (2000) was generalized with the aim of incorporating such kind of dynamics in the description of the phenomena. The work produced a new formulation of the derived distribution where the two runoff components are explicitly considered. The present work was validated by using as test site a group of basins belonging to Southern Italy and characterized by flood distributions with high skewness. The application of the proposed model provided a good fitting to the observed distributions. Moreover, model parameters were found to be strongly related to physiographic basin characteristics giving consistency to the modelling assumptions

Analysis on flood generation processes by means of a continuous simulation model

International audienceIn the present research, we exploited a continuous hydrological simulation to investigate on key variables responsible of flood peak formation. With this purpose, a distributed hydrological model (DREAM) is used in cascade with a rainfall generator (IRP-Iterated Random Pulse) to simulate a large number of extreme events providing insight into the main controls of flood generation mechanisms. Investigated variables are those used in theoretically derived probability distribution of floods based on the concept of partial contributing area (e.g. Iacobellis and Fiorentino, 2000). The continuous simulation model is used to investigate on the hydrological losses occurring during extreme events, the variability of the source area contributing to the flood peak and its lag-time. Results suggest interesting simplification for the theoretical probability distribution of floods according to the different climatic and geomorfologic environments. The study is applied to two basins located in Southern Italy with different climatic characteristics

Runoff thresholds in derived flood frequency distributions

In general, different mechanisms may be identified as responsible of runoff generation during ordinary events or extraordinary events at the basin scale. In a simplified scheme these mechanisms may be represented by different runoff thresholds. In this context, the derived flood frequency model, based on the effect of partial contributing areas on peak flow, proposed by Iacobellis and Fiorentino (2000), was generalized by providing a new formulation of the derived distribution where two runoff components are explicitly considered. The model was tested on a group of basins in Southern Italy characterized by annual maximum flood distributions highly skewed. The application of the proposed model provided good results in terms of descriptive ability. Model parameters were also found to be well correlated with geomorphological basin descriptors. Two different threshold mechanisms, associated respectively to ordinary and extraordinary events, were identified. In fact, we found that ordinary floods are mostly due to rainfall events exceeding a threshold infiltration rate in a small source area, while the so-called outlier events, responsible of the high skewness of flood distributions, are triggered when severe rainfalls exceed a threshold storage in a large portion of the basin

Enumeration and identity of Campylobacter spp. in Italian broilers

Abstract Transmission of Campylobacter to humans has been prominently associated with mishandling or improperly preparing contaminated poultry carcasses. The number of organisms per carcass represents an important measure of human exposure to the agent. Therefore, we wished to estimate this public exposure over 1 yr among Italian broiler carcasses. We sampled 213 broiler carcasses from rinse water samples collected from a single slaughterhouse. Groups of carcasses had mean processed weights ranging from 1.2 to 2.7 kg. These were produced from 22 commercial broiler chicken flocks collected from 12 different farms, 3 of which were seasonally tested. Carcasses were rinsed with sterile water, and the rinse suspension was then serially diluted and spread-plated directly onto Campy-Cefex agar plates. One to 5 typical Campylobacter colonies per plate were identified by polymerase chain reaction as Campylobacter thermo-tolerant species. The overall estimated mean count per carcass in our study was 5.16 ± 0.80 log10 cfu. This value increased in summer and autumn, as well as on carcasses collected from farms located > 100 km far from the slaughterhouse. A total of 678 Campylobacter colonies were identified by polymerase chain reaction. The majority of isolates were classified as Campylobacter jejuni (49.2%) or Campylobacter coli (47.5%). The overall number of C. jejuni was significantly higher on 1) carcasses weighing > 2 kg, 2) carcasses belonging to flocks with > 10,000 birds, and 3) carcasses collected from farms located > 100 km from the slaughterhouse. Moreover, among farms tested seasonally, C. jejuni was significantly greater than C. coli in winter. These data provide the first results of a continuing survey on Campylobacter loads and species identification from Italian broiler carcasses and represents an important baseline to estimate the human exposure to Campylobacter in Italy