Distribution Of Hydrological Losses For Varying Rainfall And Antecedent Wetness Conditions

Hydrological loss is a vital component in many hydrological models, which are usedin forecasting floods and evaluating water resources for both surface and subsurface flows. Due to the complex and random nature of the rainfall runoff process, hydrological losses are not yet fully understood. Consequently, practitioners often use representative values of the losses for design applications such as rainfall-runoff modelling which has led to inaccurate quantification of water quantities in the resulting applications. The existing hydrological loss models must be revisited and modellers should be encouraged to utilise other available data sets. This study is based on three unregulated catchments situated in Mt. Lofty Ranges of South Australia (SA). The paper focuses on conceptual models for: initial loss (IL), continuing loss (CL) and proportional loss (PL) with rainfall characteristics (total rainfall (TR) and storm duration (D)), and antecedent wetness (AW) conditions. The paper introduces two methods that can be implemented to estimate IL as a function of TR, D and AW. The IL distribution patterns and parameters for the study catchments are determined using multivariate analysis and descriptive statistics. The possibility of generalising the methods and the limitations of this are also discussed. This study will yield improvements to existing loss models and will encourage practitioners to utilise multiple data sets to estimate losses, instead of using hypothetical or representative values to generalise real situations.

Model Configuration And Data Management In The Short-Term Water Information Forecasting Tools

The Short-term Water Information and Forecasting Tools (SWIFT) is a suite of tools for flood and short-term streamflow forecasting, consisting of a collection of hydrologic model components and utilities. Catchments are modeled using conceptual subareas and a node-link structure for channel routing. The tools comprise modules for calibration, model state updating, output error correction, ensemble runs and data assimilation. Given the combinatorial nature of the modelling experiments and the sub-daily time steps typically used for simulations, the volume of model configurations and time series data is substantial and its management is not trivial. SWIFT is currently used mostly for research purposes but has also been used operationally, with intersecting but significantly different requirements. Early versions of SWIFT used mostly ad-hoc text files handled via Fortran code, with limited use of netCDF for time series data. The configuration and data handling modules have since been redesigned. The model configuration now follows a design where the data model is decoupled from the on-disk persistence mechanism. For research purposes the preferred on-disk format is JSON, to leverage numerous software libraries in a variety of languages, while retaining the legacy option of custom tab-separated text formats when it is a preferred access arrangement for the researcher. By decoupling data model and data persistence, it is much easier to interchangeably use for instance relational databases to provide stricter provenance and audit trail capabilities in an operational flood forecasting context. For the time series data, given the volume and required throughput, text based formats are usually inadequate. A schema derived from CF conventions has been designed to efficiently handle time series for SWIFT.

Forecasting electricity demand using generalized long memory

This paper studies the electricity hourly load demand in the area covered by a utility situated in the southeast of Brazil. We propose a stochastic model which employs generalized long memory (by means of Gegenbauer processes) to model the seasonal behavior of the load. The model is proposed for sectional data, that is, each hour’s load is studied separately as a single series. This approach avoids modeling the intricate intra-day pattern (load profile) displayed by the load, which varies throughout days of the week and seasons. The forecasting performance of the model is compared with a SARIMA benchmark using the years of 1999 and 2000 as the out-of-sample. The model clearly outperforms the benchmark. We conclude for general long memory in the series.

Forecasting electricity load demand: analysis of the 2001 rationing period in Brazil

This paper studies the electricity load demand behavior during the 2001 rationing period, which was implemented because of the Brazilian energetic crisis. The hourly data refers to a utility situated in the southeast of the country. We use the model proposed by Soares and Souza (2003), making use of generalized long memory to model the seasonal behavior of the load. The rationing period is shown to have imposed a structural break in the series, decreasing the load at about 20%. Even so, the forecast accuracy is decreased only marginally, and the forecasts rapidly readapt to the new situation. The forecast errors from this model also permit verifying the public response to pieces of information released regarding the crisis.

Analysis of forecasting capabilities of ground surfaces valuation using artificial neural networks

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Artificial neural networks and clustering techniques applied in the reconfiguration of distribution systems

One objective of the feeder reconfiguration problem in distribution systems is to minimize the power losses for a specific load. For this problem, mathematical modeling is a nonlinear mixed integer problem that is generally hard to solve. This paper proposes an algorithm based on artificial neural network theory. In this context, clustering techniques to determine the best training set for a single neural network with generalization ability are also presented. The proposed methodology was employed for solving two electrical systems and presented good results. Moreover, the methodology can be employed for large-scale systems in real-time environment.

Water balance and locomotor performance in three species of neotropical toads that differ in geographical distribution

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Aquatic macrophyte distribution in relation to water and sediment conditions in the Itaipu Reservoir, Brazil

Aquatic macrophyte community distribution along the eastern shoreline of the Itaipu Reservoir (one of the South America's largest impoundments) is described in relation to limnological and sedimentological factors. The central body of the reservoir is mesotrophic, while the arms (flooded influent river valleys) along the eastern shore may be oligo-mesotrophic to eutrophic, depending on time of year and sub-catchment characteristics. Macrophyte community composition and species cover were surveyed at 30 sites in four arms, in relation to sediment total P and organic matter; underwater light regime; and water total P and Kjeldahl N concentration, alkalinity, conductivity, depth and pH. Seventeen euhydrophyte and six emergent macrophyte species were recorded. Large stands of Egeria najas dominated the euhydrophyte vegetation, together with free-floating weed species (Pistia stratiotes Linn., Salvinia auriculata Aublet and Eichhornia crassipes (Mart.) Solms.). Canonical Correspondence Analysis of the data showed that two sets of variables were important predictors of aquatic macrophyte community structure. Floating macrophyte assemblage was closely related to concentration of nutrients in both water and sediment, while light penetration was the strongest predictor of submerged species occurrence. Although a large number of potential nuisance species were present, dense growths were restricted to shallower areas of the Itaipu Reservoir, causing localised problems. The possibility of increasing interference by these plants with fisheries, recreational use, transport and hydroelectricity generation suggests a need for continued monitoring of weed distribution and abundance, and investigation of appropriate management measures.

Vertical distribution of zooplankton in the water column of Lago Amapá, Rio Branco, Acre, Brazil

O objetivo desta investigação foi observar a distribuição vertical da comunidade do zooplâncton no Lago Amapá (10º2'36S e 67º50'24W), localizado na planície de inundação do Rio Acre. Amostragens foram conduzidas em três diferentes profundidades da coluna da água, considerando aspectos sazonais do zooplâncton, parâmetros físicos, químicos e biológicos. Coletas foram realizadas semanalmente com Garrafa de Van Dorn. As espécies apresentaram maiores concentrações no meio da coluna da água. Foram encontradas 38 espécies, assim distribuídas: Rotifera (30), Cladocera (5) e Cyclopoida (3). A temperatura da coluna da água em geral apresentou-se alta, em torno de 30ºC, com pequena variação, resultando em baixa viscosidade. O índice de Jaccard, comparando-se as três estações de coletas, demonstrou que durante a fase de águas baixas, as estações 1 e 3 foram as mais similares (Cj = 0.7058), especialmente no meio da coluna da água. Lago Amapá apresentou características em conformidade com o Modelo do Distúrbio Intermediário, favorecendo a colonização de grupos oportunistas, tais como rotíferos.

Distribution profile and availability of Cr, Ni, Cu, Cd and Pb in different sediments from anhumas surface water collection reservoir, Araraquara-São Paulo State, Brazil

In this work the influence of the anhtropogenic activities in the uptake of metals at a reservoir for public water supply in Araraquara City, São Paulo State, Brazil was studied. For this, the distribution of Cr, Ni, Cu, Cd and Pb in sediments collected from Anhumas reservoir, at seven sampling points and at three depths for each point was investigated. The pseudo-total and available metals contained in the different sediment samples were assessed using an ICP-AES technique. Among the five metals studied, cadmium possesses the largest relative potential availability, with percentages of 20 to 98% for the three different sediment types. In addition, the following decreasing availability order was characterized: Cd > Cu > Pb > Ni > Cr.

Distribution of Cr, Ni, Cu, Cd and Pb in different molecular size of humic fractions extracted from water and sediment samples collected at Anhumas reservoir - Araraquara/SP

In this work was studied the distribution of Cr, Ni, Cu, Cd and Pb in humic fractions with different molecular size. The HS were extracted from waters (AHS), surface sediments (HESS), interface water sediment (HSIS) and bottom sediment (HSBS) collected in the Anhumas surface water collection reservoir, located in the district of Araraquara - São Paulo State Brazil. The humic substances were extracted by procedures recommended by International Humic Substances Society (IHSS). After purification by dialysis, the humic substances were fractionated using a multistage tangential flow ultrafiltration system. The fractionation patterns of HS characterized a mass distribution relatively uniform among the fractions with different molecular sizes, with larger values in the fractions F-2 (20.8%) and F-4 (23.8%), Except for the ions Pb(II) and Cu(II), which presented relatively higher concentrations in the fractions F-2 and F-4, respectively. In general, chromium, nickel, cadmium and lead have similar distributions in the five fractions with larger and medium molecular sizes (F-1 to F-5). With relation to the mass distributions in the different humic substances fractions extracted from sediment samples collected at three depth, they presented 42-48% of HS in the fractions with larger molecular sizes (F-1 and F-2), 29-31% in the middle fractions (F-3 and F-4) and 13-20% in the fractions with smaller molecular sizes (F-5 and F-6). In general, the metallic ions presented distributions similar among the respective fractions F-1 to F-6, Exceptions for Pb(II) and M(II) in surface sediment with concentrations relatively smaller in the fractions F-2 and F-4, respectively,

Spatial distribution of solutes and water in sucrose solution dehydrated apples

Half-fresh apples were immersed in sucrose solution (50% w/w, 27 degrees C) during different times of exposition (2, 4, and 8 h). Then each fruit was sliced from the transversal exposed surface. Density, water, and sugar content were determined for each slice. A mathematical model was fitted to experimental data of water and sucrose content considering the global flux and the tissue shrinkage. By numerical analysis, the binary effective diffusion coefficients as a function of concentration were calculated, using material coordinates and integrating simultaneously two differential equations (for water and sucrose). The coefficients obtained are one or even two orders of magnitude lower than the ones for pure solutions and present an unusual concentration dependence. This comparison shows the influence of the tissue resistance to the diffusion.

WATER BALANCE and SPATIAL DISTRIBUTION of AN ANURAN COMMUNITY FROM BRAZIL

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A fast electric load forecasting using neural networks

The objective of this work is the development of a methodology for electric load forecasting based on a neural network. Here, it is used Backpropagation algorithm with an adaptive process based on fuzzy logic. This methodology results in fast training, when compared to the conventional formulation of Backpropagation algorithm. Results are presented using data from a Brazilian Electric Company and the performance is very good for the proposal objective.

Digital image analysis of root distribution towards improved irrigation water and soil management: Grapevine and date palm study cases

It is presented two study cases about the approach in root analysis at field and laboratory conditions based on digital image analysis. Grapevine (Vitis vinifera L.) and date palm (Phoenix dactylifera L.) root systems were analyzed by both the monolith and trench wall method aided by digital image analysis. Correlation between root parameters and their fractional distribution over the soil profile were obtained, as well as the root diameter estimation. Results have shown the feasibility of digital image analysis for evaluation of root distribution.