Carlos Eduardo Morelli Tucci

Bio: Carlos Eduardo Morelli Tucci is an academic researcher from Universidade Federal do Rio Grande do Sul. The author has contributed to research in topics: Drainage basin & Structural basin. The author has an hindex of 25, co-authored 103 publications receiving 2581 citations.

The MGB-IPH model for large-scale rainfall—runoff modelling

Abstract: Recent developments in hydrological modelling of river basins are focused on prediction in ungauged basins, which implies the need to improve relationships between model parameters and easily-obtainable information, such as satellite images, and to test the transferability of model parameters. A large-scale distributed hydrological model is described, which has been used in several large river basins in Brazil. The model parameters are related to classes of physical characteristics, such as soil type, land use, geology and vegetation. The model uses two basin space units: square grids for flow direction along the basin and GRU—group response units—which are hydrological classes of the basin physical characteristics for water balance. Expected ranges of parameter values are associated with each of these classes during the model calibration. Results are presented of the model fitting in the Taquari-Antas River basin in Brazil (26 000 km2 and 11 flow gauges). Based on this fitting, the model was the...

Uncertainty in climate change impacts on water resources in the Rio Grande Basin, Brazil

Abstract: . We quantify uncertainty in the impacts of climate change on the discharge of Rio Grande, a major tributary of the Parana River in South America and one of the most important basins in Brazil for water supply and hydro-electric power generation. We consider uncertainty in climate projections associated with the greenhouse-gas emission scenarios (A1b, A2, B1, B2) and increases in global mean air temperature of 1 to 6° C for the HadCM3 GCM (Global Circulation Model) as well as uncertainties related to GCM structure. For the latter, multimodel runs using 6 GCMs (CCCMA CGCM31, CSIRO Mk30, IPSL CM4, MPI ECHAM5, NCAR CCSM30, UKMO HadGEM1) and HadCM3 as baseline, for a +2° C increase in global mean temperature. Pattern-scaled GCM-outputs are applied to a large-scale hydrological model (MGB-IPH) of Rio Grande Basin. Based on simulations using HadCM3, mean annual river discharge increases, relative to the baseline or control run period (1961–1990), by +5% to +10% under the SRES emissions scenarios and from +8% to +51% with prescribed increases in global mean air temperature of between 1 and 6° C. Substantial uncertainty in projected changes to mean river discharge (−28% to +13%) under the 2° C warming scenario is, however, associated with the choice of GCM. We conclude that, in the case of Rio Grande Basin, the most important source of uncertainty derives from the GCM rather than the emission scenario or the magnitude of rise in mean global temperature.

Genes expressed in human tumor endothelium

Abstract: To gain a molecular understanding of tumor angiogenesis, we compared gene expression patterns of endothelial cells derived from blood vessels of normal and malignant colorectal tissues. Of over 170 transcripts predominantly expressed in the endothelium, 79 were differentially expressed, including 46 that were specifically elevated in tumor-associated endothelium. Several of these genes encode extracellular matrix proteins, but most are of unknown function. Most of these tumor endothelial markers were expressed in a wide range of tumor types, as well as in normal vessels associated with wound healing and corpus luteum formation. These studies demonstrate that tumor and normal endothelium are distinct at the molecular level, a finding that may have significant implications for the development of anti-angiogenic therapies.

A decade of Predictions in Ungauged Basins (PUB)—a review

Abstract: The Prediction in Ungauged Basins (PUB) initiative of the International Association of Hydrological Sciences (IAHS), launched in 2003 and concluded by the PUB Symposium 2012 held in Delft (23–25 October 2012), set out to shift the scientific culture of hydrology towards improved scientific understanding of hydrological processes, as well as associated uncertainties and the development of models with increasing realism and predictive power. This paper reviews the work that has been done under the six science themes of the PUB Decade and outlines the challenges ahead for the hydrological sciences community.Editor D. KoutsoyiannisCitation Hrachowitz, M., Savenije, H.H.G., Bloschl, G., McDonnell, J.J., Sivapalan, M., Pomeroy, J.W., Arheimer, B., Blume, T., Clark, M.P., Ehret, U., Fenicia, F., Freer, J.E., Gelfan, A., Gupta, H.V., Hughes, D.A., Hut, R.W., Montanari, A., Pande, S., Tetzlaff, D., Troch, P.A., Uhlenbrook, S., Wagener, T., Winsemius, H.C., Woods, R.A., Zehe, E., and Cudennec, C., 2013. A d...

Global river hydrography and network routing: baseline data and new approaches to study the world's large river systems

Abstract: Despite significant recent advancements, global hydrological models and their input databases still show limited capabilities in supporting many spatially detailed research questions and integrated assessments, such as required in freshwater ecology or applied water resources management. In order to address these challenges, the scientific community needs to create improved large-scale datasets and more flexible data structures that enable the integration of information across and within spatial scales; develop new and advanced models that support the assessment of longitudinal and lateral hydrological connectivity; and provide an accessible modeling environment for researchers, decision makers, and practitioners. As a contribution, we here present a new modeling framework that integrates hydrographic baseline data at a global scale (enhanced HydroSHEDS layers and coupled datasets) with new modeling tools, specifically a river network routing model (HydroROUT) that is currently under development. The resulting ‘hydro-spatial fabric’ is designed to provide an avenue for advanced hydro-ecological applications at large scales in a consistent and highly versatile way. Preliminary results from case studies to assess human impacts on water quality and the effects of dams on river fragmentation and downstream flow regulation illustrate the potential of this combined data-and-modeling framework to conduct novel research in the fields of aquatic ecology, biogeochemistry, geo-statistical modeling, or pollution and health risk assessments. The global scale outcomes are at a previously unachieved spatial resolution of 500 m and can thus support local planning and decision making in many of the world's large river basins. Copyright © 2013 John Wiley & Sons, Ltd.

MSWEP: 3-hourly 0.25° global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data

Abstract: . Current global precipitation (P) datasets do not take full advantage of the complementary nature of satellite and reanalysis data. Here, we present Multi-Source Weighted-Ensemble Precipitation (MSWEP) version 1.1, a global P dataset for the period 1979–2015 with a 3-hourly temporal and 0.25° spatial resolution, specifically designed for hydrological modeling. The design philosophy of MSWEP was to optimally merge the highest quality P data sources available as a function of timescale and location. The long-term mean of MSWEP was based on the CHPclim dataset but replaced with more accurate regional datasets where available. A correction for gauge under-catch and orographic effects was introduced by inferring catchment-average P from streamflow (Q) observations at 13 762 stations across the globe. The temporal variability of MSWEP was determined by weighted averaging of P anomalies from seven datasets; two based solely on interpolation of gauge observations (CPC Unified and GPCC), three on satellite remote sensing (CMORPH, GSMaP-MVK, and TMPA 3B42RT), and two on atmospheric model reanalysis (ERA-Interim and JRA-55). For each grid cell, the weight assigned to the gauge-based estimates was calculated from the gauge network density, while the weights assigned to the satellite- and reanalysis-based estimates were calculated from their comparative performance at the surrounding gauges. The quality of MSWEP was compared against four state-of-the-art gauge-adjusted P datasets (WFDEI-CRU, GPCP-1DD, TMPA 3B42, and CPC Unified) using independent P data from 125 FLUXNET tower stations around the globe. MSWEP obtained the highest daily correlation coefficient (R) among the five P datasets for 60.0 % of the stations and a median R of 0.67 vs. 0.44–0.59 for the other datasets. We further evaluated the performance of MSWEP using hydrological modeling for 9011 catchments ( http://www.gloh2o.org .