ALBERT

Description: To evaluate the hematologic effects of recombinant human interleukin-6 (rhIL-6, Escherichia coli, SDZ ILS 969, IL-6), and determine its toxicity profile, we performed a phase I trial of IL-6 in 22 patients with various myelodysplastic syndromes (MDS), platelet counts 〈 100,000/microL, and 〈 5% bone marrow (BM) blasts. Patients received one of four doses of IL-6 (1.0, 2.5, 3.75, and 5.0 micrograms/kg/d) as a subcutaneous injection on day 1, followed by a 7-day wash-out period, and then 28 days of IL-6 therapy. Dose-limiting toxicities of fatigue, fever, and elevated alkaline phosphatase were seen at 5.0 micrograms/kg/d; the maximum tolerated dose was 3.75 micrograms/kg/d. All patients experienced at least grade II fever and all had an increase in acute phase proteins. Eight patients (36%) experienced at least a transient improvement in platelet counts; three fulfilled the criteria for response, whereas five others had clinically significant increases that failed to meet response criteria. Various IL-6-related toxicities prevented more than three patients from receiving maintenance therapy. Two of the three patients who received maintenance IL-6 therapy had a persistent increase in platelet counts, during 3 and 12 months of IL-6 therapy, respectively. Laboratory studies indicated that IL-6 increased the frequency of higher ploidy megakaryocytes but did not significantly increase the number of assayable megakaryocytic progenitor cells, suggesting that IL-6 acts as a maturational agent rather than a megakaryocyte colony-stimulating factor. Although IL-6 therapy can promote thrombopoiesis in some MDS patients, its limited activity and significant therapy-related toxicity preclude its use as a single agent in this patient population. Further studies, combining low doses of IL-6 with other hematopoietic growth factors, are underway.

Description: The present paper introduces an analytical approach for the description of the soil water balance and runoff production within a schematic river basin. The model is based on a stochastic differential equation where the rainfall is interpreted as an additive noise in the soil water balance and is assumed uniform over the basin, the basin heterogeneity is characterized by a parabolic distribution of the soil water storage capacity and the runoff production occurs for saturation excess. The model allowed to derive the probability density function of the produced surface runoff highlighting the role played by climate and physical characteristics of a basin on runoff dynamics. Finally, the model have been tested over a humid basin of Southern Italy proposing also a strategy for the parameters estimation.

Description: 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.

Description: In the present work, the role played by vegetation parameters, necessary to the hydrological distributed modeling, is investigated focusing on the correct use of remote sensing products for the evaluation of hydrological losses in the soil water balance. The research was carried out over a medium-sized river basin in Southern Italy, where the vegetation status is characterised through a data-set of multi-temporal NDVI images. The model adopted uses one layer of vegetation whose status is defined by the Leaf Area Index (LAI), which is often obtained from NDVI images. The inherent problem is that the vegetation heterogeneity – including soil disturbances – has a large influence on the spectral bands and so the relation between LAI and NDVI is not unambiguous. We present a rationale for the basin scale calibration of a non-linear NDVI-LAI regression, based on the comparison between NDVI values and literature LAI estimations of the vegetation cover in recognized landscape elements of the study catchment. Adopting a process-based model (DREAM) with a distributed parameterisation, the influence of different NDVI-LAI regression models on main features of water balance predictions is investigated. The results show a significant sensitivity of the hydrological losses and soil water regime to the alternative LAI estimations. These crucially affects the model performances especially in low-flows simulation and in the identification of the intermittent regime.

Description: Characterizing the dynamics of soil moisture fields is a key issue in hydrology, offering a strategy to improve our understanding of complex climate-soil-vegetation interactions. Besides in-situ measurements and hydrological models, soil moisture dynamics can be inferred by analyzing data acquired by sensors on board of airborne and/or satellite platforms. In this work, we investigated the use of the National Oceanic and Atmospheric Administration – Advanced Microwave Sounding Unit-A (NOAA-AMSU-A) radiometer for the remote characterization of soil water content. To this aim, a field measurement campaign, lasted about three months (3 March 2010–18 May 2010), was carried out using a portable time-domain reflectometer (TDR) to get soil water content measures over five different locations within an experimental basin of 32.5 km2, located in the South of Italy. In detail, soil moisture measurements were carried out systematically at the times of satellite overpasses, over two square areas of 400 m2, a triangular area of 200 m2 and two transects of 60 and 170 m, respectively. Each monitored site is characterized by different land covers and soil textures, to account for spatial heterogeneity of land surface. Afterwards, a more extensive comparison (i.e. analyzing a 5 yr data time series) was made using soil moisture simulated by a hydrological model. Measured and modeled soil moisture data were compared with two AMSU-based indices: the Surface Wetness Index (SWI) and the Soil Wetness Variation Index (SWVI). Both time series of indices have been filtered by means of an exponential filter to account for the fact that microwave sensors only provide information at the skin surface. This allowed to understand the ability of each satellite-based index to account for soil moisture dynamics and to understand its performances under different conditions. As a general remark, the comparison shows a higher ability of the filtered SWI to describe the general trend of soil moisture, while the SWVI can capture soil moisture variations with a precision that increases at the higher values of SWVI.

Description: Understanding the spatial variability of key parameters of flood probability distributions represents a strategy to provide insights on hydrologic similarity and building probabilistic models able to reduce the uncertainty in flood prediction in ungauged basins. In this work, we exploited the theoretically derived distribution of floods model TCIF (Two Component Iacobellis and Fiorentino model; Gioia et al., 2008), based on two different threshold mechanisms associated to ordinary and extraordinary events. The model is based on the hypotheses that ordinary floods are generally due to rainfall events exceeding a constant infiltration rate in a small source area, while the so-called outlier events responsible for the high skewness of flood distributions are triggered when severe rainfalls exceed a storage threshold over a large portion of the basin. Within this scheme, a sensitivity analysis was performed with respect to climatic and geomorphologic parameters in order to analyze the effects on the skewness coefficient and provide insights in catchment classification and process conceptualization. The analysis was conducted to investigate the influence on flood distribution of physical factors such as rainfall intensity, basin area, and particular focus on soil behavior.

Description: The present paper introduces an analytical approach for the description of the soil water balance dynamics over a schematic river basin. The model is based on a stochastic differential equation where the rainfall forcing is interpreted as an additive noise in the soil water balance. This equation can be solved assuming known the spatial distribution of the soil moisture over the basin transforming the two-dimensional problem in space in a one dimensional one. This assumption is particularly true in the case of humid and semihumid environments, where spatial redistribution becomes dominant producing a well defined soil moisture pattern. The model allowed to derive the probability density function of the saturated portion of a basin and of its relative saturation. This theory is based on the assumption that the soil water storage capacity varies across the basin following a parabolic distribution and the basin has homogeneous soil texture and vegetation cover. The methodology outlined the role played by the soil water storage capacity distribution of the basin on soil water balance. In particular, the resulting probability density functions of the relative basin saturation were found to be strongly controlled by the maximum water storage capacity of the basin, while the probability density functions of the relative saturated portion of the basin are strongly influenced by the spatial heterogeneity of the soil water storage capacity. Moreover, the saturated areas reach their maximum variability when the mean rainfall rate is almost equal to the soil water loss coefficient given by the sum of the maximum rate of evapotranspiration and leakage loss in the soil water balance. The model was tested using the results of a continuous numerical simulation performed with a semi-distributed model in order to validate the proposed theoretical distributions.

Description: In the present work, we developed a new formulation for the estimation of the soil moisture in the root zone based on the measured value of soil moisture at the surface. The method sheds lights on the relationship between surface and root zone soil moisture and has applications in the use of satellite remote sensing retrievals of soil moisture. It derives from a simplified form of the soil water balance equation and provides a closed form of the relationship between the root zone and the surface soil moisture with a limited number of physically consistent parameters. The approach was first used to interpret soil moisture dynamics at the point scale using soil moisture measurements taken from the African Monsoon Multidisciplinary Analysis (AMMA) database. Thereafter it was also tested over an extended domain using modeled soil moisture data obtained from the North American Land Data Assimilation System (NLDAS). The NLDAS database provides modeled soil moisture data averaged over different depths for the conterminous US covering different climatic and physical conditions. In general, the method performed better than a traditional low pass filter and its results are found to be influenced by rainfall dynamics and also by the observed variance of soil moisture in the lower layer. The limited number of the parameters and their physical interpretation allows a direct application of the procedure to other regions.

Description: Characterizing the dynamics of soil moisture fields is a key issue in hydrology, offering a strategy to improve our understanding of complex climate-soil-vegetation interactions. Apart from in-situ measurements and hydrological models, soil moisture dynamics can be inferred by analyzing data acquired by sensors aboard satellite platforms. In this work, we investigated the use of the National Oceanic and Atmospheric Administration – Advanced Microwave Sounding Unit (NOAA-AMSU) radiometer for the remote characterization of soil water content. To this aim, a field measurement campaign, lasted about three months, was carried out using a portable time-domain reflectometer (TDR) to get soil water content measures over five different locations within an experimental basin of 32.5 km2, located in the South of Italy. In detail, soil moisture measurements have been carried out systematically at the times of satellite overpasses, over two square areas of 400 m2, a triangular area of 200 m2 and two transects of 60 and 170 m, respectively. Each monitored site is characterized by different land covers and soil textures, to account for spatial heterogeneity of land surface. Afterwards, a more extensive comparison (i.e. analyzing a 5-yr data time series) has been made using soil moisture simulated by a hydrological model. Achieved measured and modeled soil moisture data were compared with two AMSU-based indices: the Surface Wetness Index (SWI) and the Soil Wetness Variation Index (SWVI). Both indices have been filtered to account for soil depth by means of an exponential filter. This allowed to understand the ability of each satellite-based index to account for soil moisture dynamics and to understand its performances under different conditions. As a general remark, the comparison shows a higher ability of the filtered SWI to describe the state of the soil, while the SWVI can capture soil moisture variations with a precision that increases at the higher values of SWVI and it may represent a useful and reliable tool to frequently monitor the soil moisture state for flood forecasting purposes.