Vladimir J. Alarcon

Bio: Vladimir J. Alarcon is an academic researcher from Diego Portales University. The author has contributed to research in topics: Watershed & Water quality. The author has an hindex of 9, co-authored 45 publications receiving 290 citations. Previous affiliations of Vladimir J. Alarcon include Mississippi State University.

Water Distribution Network Analysis Using Excel

Abstract: The analysis of water distribution networks has been and will continue to be a core component of civil engineering water resources curricula. Since its introduction in 1936, the Hardy Cross method has been used in virtually every water resources engineering text to introduce students to network analysis. The technique gained widespread popularity primarily because it is amenable to manual calculation techniques. However, the same subtle elegance that facilitates manual calculations often obscures the primary engineering and physical principles of water distribution systems relative to the nuances of algorithm implementation. Herein, the authors illustrate the application of commonly available spreadsheet software (MicroSoft Excel) to more concisely and effectively solve typical undergraduate network distribution problems using linear theory. Application development is much more efficient and straightforward than the corresponding Hardy Cross implementation enabling students to concentrate upon the enginee...

Nested Hydrodynamic Modeling of a Coastal River Applying Dynamic-Coupling

Abstract: This paper presents a nested hydrodynamic model of the Fish River, a tributary of the sub-estuary Weeks Bay located in Mobile Bay, Alabama. The Environmental Fluid Dynamics Code (EFDC) and a novel dynamic-coupling tool were used to link three EFDC hydrodynamic models corresponding to Mobile Bay, Weeks Bay, and the Fish River. The dynamically-coupled models were used to simulate inundation scenarios for combinations of 2-, 7.5-, 10-, 25-, and 100-year floods, and the hurricane surge that occurred during hurricane Katrina. The nested and dynamically-coupled model was developed using available public-access bathymetry and topography databases (National Elevation Dataset, and NOAA bathymetry), and run without recurring to calibration techniques. The simulation of combined scenarios showed that inundated areas increase from 0.07 % up to 189 % with respect to the actual flood that took place during the Katrina event (Katrina + 1-year flood). The results suggest that increases in inundated area are relatively much higher from a 1-year flood to a 7.5 year-flood (128 % flooded area increase) than for higher return periods. For the 25-year and the 100-year floods, inundated areas almost triple from the area corresponding to the base-case (Katrina event), with percent increases of 182 % and 189 % respectively.

A Strategy for Estimating Nutrient Concentrations Using Remote Sensing Datasets and Hydrological Modeling

Abstract: This paper presents a methodology for estimating nutrient concentrations of total phosphorus (TP) and total nitrogen (TN) through the use of hydrological modeling, remote sensing datasets, and nutrient export coefficients. The strategy is applied to the Upper Tombigbee watershed, located in the northern region of the states of Mississippi and Alabama, USA. USGS GIRAS (1986), NASA MODIS MOD12Q1 (2001-2004) land use datasets, and USGS-DEM topographical datasets were used to characterize the physiography of the watershed. TN and TP concentration values estimated using the methodology were compared to values reported in the literature.

Climate Change 2007: The Physical Science Basis.

Abstract: Cause, conseguenze e strategie di mitigazione Proponiamo il primo di una serie di articoli in cui affronteremo l’attuale problema dei mutamenti climatici. Presentiamo il documento redatto, votato e pubblicato dall’Ipcc - Comitato intergovernativo sui cambiamenti climatici - che illustra la sintesi delle ricerche svolte su questo tema rilevante.

Soil erosion prediction in the Grande River Basin, Brazil using distributed modeling

Abstract: Mapping and assessment of erosion risk is an important tool for planning of natural resources management, allowing researchers to modify land-use properly and implement management strategies more sustainable in the long-term. The Grande River Basin (GRB), located in Minas Gerais State, is one of the Planning Units for Management of Water Resources (UPGRH) and is divided into seven smaller units of UPGRH. GD1 is one of them that is essential for the future development of Minas Gerais State due to its high water yield capacity and potential for electric energy production. The objective of this study is to apply the Universal Soil Loss Equation (USLE) with GIS PCRaster in order to estimate potential soil loss from the Grande River Basin upstream from the Itutinga/Camargos Hydroelectric Plant Reservoir (GD1), allowing identification of the susceptible areas to water erosion and estimate of the sediment delivery ratio for the adoption of land management so that further soil loss can be minimized. For the USLE model, the following factors were used: rainfall–runoff erosivity ( R ), erodibility ( K ), topographic (LS), cover-management ( C ) and support practice ( P ). The Fournier Index was applied to estimate R for the basin using six pluviometric stations. Maps of the K , C , LS and P factors were derived from the digital elevation model (DEM), and soil and land-use maps, taking into account information available in the literature. In order to validate the simulation process, Sediment Delivery Ratio (SDR) was estimated, which is based on transported sediment (TS) to basin outlet and mean soil loss in the basin (MSL). The SDR calculation included data (total solids in the water and respective discharge) between 1996 and 2003 which were measured at a gauging station located on the Grande River and a daily flow data set was obtained from the Brazilian National Water Agency (ANA). It was possible to validate the erosion process based on the USLE and SDR application for the basin conditions, since absolute errors of estimate were low. The major area of the basin (about 53%) had an average annual soil loss of less than 5 t ha − 1 yr − 1 . With the results obtained we were able to conclude that 49% of the overall basin presently has soil loss greater than the tolerable rate, thus indicating that there are zones where the erosion process is critical, meaning that both management and land-use have not been used appropriately in these areas of the basin. The methodology applied showed acceptable precision and allowed identification of the most susceptible areas to water erosion, constituting an important predictive tool for soil and environmental management in this region, which is highly relevant for prediction of varying development scenarios for Minas Gerais State due to its hydroelectric energy potential. This approach can be applied to other areas for simple, reliable identification of critical areas of soil erosion in watersheds.

Application of Excel Solver for Parameter Estimation of the Nonlinear Muskingum Models

Abstract: The Muskingum model continues to be a popular procedure for river flood routing. An important aspect in nonlinear Muskingum models is the calibration of the model parameters. The current study presents the application of commonly available spreadsheet software, Microsoft Excel 2010, for the purpose of estimating the parameters of nonlinear Muskingum routing models. Main advantage of this approach is that it can calibrate the parameters using two different ways without knowing the exact details of optimization techniques. These procedures consist of (1) Generalized Reduced Gradient (GRG) solver and (2) evolutionary solver. The first one needs the initial values assumption for the parameter estimation while the latter requires the determination of the algorithm parameters. The results of the simulation of an example that is a benchmark problem for parameter estimation of the nonlinear Muskingum models indicate that Excel solver is a promising way to reduce problems of the parameter estimation of the nonlinear Muskingum routing models. Furthermore, the results indicate that the efficiency of Excel solver for the parameter estimation of the models can be increased, if both GRG and evolutionary solvers are used together.

Rhizosphere Engineering With Plant Growth-Promoting Microorganisms for Agriculture and Ecological Sustainability

Abstract: The rhizosphere is undoubtedly the most complex microhabitat, comprised of an integrated network of plant roots, soil, and a diverse consortium of bacteria, fungi, eukaryotes, and archaea. The rhizosphere conditions have a direct impact on crop growth and yield. Nutrient-rich rhizosphere environments stimulate plant growth and yield and vice versa. Extensive cultivation exhaust most of the soils which needs to be nurtured before or during next crop. Chemical fertilizers are the major source of crop nutrients but their uncontrolled and widespread usage has posed a serious threat to sustainability of agriculture and stability of ecosystem. These chemicals are accumulated in soil, drained in water, and emitted to the air where they persist for decades causing serious threat to overall ecosystem. Plant growth promoting rhizobacteria (PGPR) present in the rhizosphere convert many plant-unavailable essential nutrients e.g., nitrogen, phosphorous, zinc etc. into available forms. PGPR produce certain plant growth hormones (such as auxin, cytokinin, and gibberellin), cell lytic enzymes (chitinase, protease, hydrolases etc.), secondary metabolites and antibiotics, and stress alleviating compounds (e.g., 1-Aminocyclopropane-1- carboxylate deaminase), chelating agents (siderophores). They different signaling compouds (e.g., N-Acyl homoserine lactones to interaction with the beneficial or pathogenic counterparts in the rhizosphere. These multifarious activities of PGPR improve the soil structure, health, fertility and functioning which directly or indirectly support plant growth under normal and stressed environments. Rhizosphere engineering with these PGPR has a wide ranging application not only for crop fertilization but developing eco-friendly sustainable agriculture. Due to severe climate change effects on plants and rhizosphere biology, there is growing interest in stress-resilient PGPM and their subsequent application to induce stress (drought, salinity, and heat) tolerance mechanism in plants. This review describes the three components of rhizosphere engineering with an explicit focus on the broader perspective of PGPM that could facilitate rhizosphere engineering in selected hosts to serve as an efficient component for sustainable agriculture.