951 resultados para São Luís-Grajaú basin
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In this study, we applied the integration methodology developed in the companion paper by Aires (2014) by using real satellite observations over the Mississippi Basin. The methodology provides basin-scale estimates of the four water budget components (precipitation P, evapotranspiration E, water storage change Delta S, and runoff R) in a two-step process: the Simple Weighting (SW) integration and a Postprocessing Filtering (PF) that imposes the water budget closure. A comparison with in situ observations of P and E demonstrated that PF improved the estimation of both components. A Closure Correction Model (CCM) has been derived from the integrated product (SW+PF) that allows to correct each observation data set independently, unlike the SW+PF method which requires simultaneous estimates of the four components. The CCM allows to standardize the various data sets for each component and highly decrease the budget residual (P - E - Delta S - R). As a direct application, the CCM was combined with the water budget equation to reconstruct missing values in any component. Results of a Monte Carlo experiment with synthetic gaps demonstrated the good performances of the method, except for the runoff data that has a variability of the same order of magnitude as the budget residual. Similarly, we proposed a reconstruction of Delta S between 1990 and 2002 where no Gravity Recovery and Climate Experiment data are available. Unlike most of the studies dealing with the water budget closure at the basin scale, only satellite observations and in situ runoff measurements are used. Consequently, the integrated data sets are model independent and can be used for model calibration or validation.
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Models of river flow time series are essential in efficient management of a river basin. It helps policy makers in developing efficient water utilization strategies to maximize the utility of scarce water resource. Time series analysis has been used extensively for modeling river flow data. The use of machine learning techniques such as support-vector regression and neural network models is gaining increasing popularity. In this paper we compare the performance of these techniques by applying it to a long-term time-series data of the inflows into the Krishnaraja Sagar reservoir (KRS) from three tributaries of the river Cauvery. In this study flow data over a period of 30 years from three different observation points established in upper Cauvery river sub-basin is analyzed to estimate their contribution to KRS. Specifically, ANN model uses a multi-layer feed forward network trained with a back-propagation algorithm and support vector regression with epsilon intensive-loss function is used. Auto-regressive moving average models are also applied to the same data. The performance of different techniques is compared using performance metrics such as root mean squared error (RMSE), correlation, normalized root mean squared error (NRMSE) and Nash-Sutcliffe Efficiency (NSE).
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Detailed pedofacies characterization along-with lithofacies investigations of the Mio-Pleistocene Siwalik sediments exposed in the Ramnagar sub-basin have been studied so as to elucidate variability in time and space of fluvial processes and the role of intra- and extra-basinal controls on fluvial sedimentation during the evolution of the Himalayan foreland basin (HFB). Dominance of multiple, moderately to strongly developed palaeosol assemblages during deposition of Lower Siwalik (similar to 12-10.8 Ma) sediments suggest that the HFB was marked by Upland set-up of Thomas et al. (2002). Activity of intra-basinal faults on the uplands and deposition of terminal fans at different times caused the development of multiple soils. Further, detailed pedofacies along-with lithofacies studies indicate prevalence of stable tectonic conditions and development of meandering streams with broad floodplains. However, the Middle Siwalik (similar to 10.8-4.92 Ma) sub-group is marked by multistoried sandstones and minor mudstone and mainly weakly developed palaeosols, indicating deposition by large braided rivers in the form of megafans in a Lowland set-up of Thomas et al. (2002). Significant change in nature and size of rivers from the Lower to Middle Siwalik at similar to 10 Ma is found almost throughout of the basin from Kohat Plateau (Pakistan) to Nepal because the Himalayan orogeny witnessed its greatest tectonic upheaval at this time leading to attainment of great heights by the Himalaya, intensification of the monsoon, development of large rivers systems and a high rate of sedimentation, hereby a major change from the Upland set-up to the Lowland set-up over major parts of the HFB. An interesting geomorphic environmental set-up prevailed in the Ramnagar sub-basin during deposition of the studied Upper Siwalik (similar to 4.92 to <1.68 Ma) sediments as observed from the degree of pedogenesis and the type of palaeosols. In general, the Upper Siwalik sub-group in the Ramnagar sub-basin is subdivided from bottom to top into the Purmandal sandstone (4.92-4.49 Ma), Nagrota (4.49-1.68 Ma) and Boulder Conglomerate (<1.68 Ma) formations on the basis of sedimentological characters and change in dominant lithology. Presence of mudstone, a few thin gravel beds and dominant sandstone lithology with weakly to moderately developed palaeosols in the Purmandal sandstone Fm. indicates deposition by shallow braided fluvial streams. The deposition of mudstone dominant Nagrota Fm. with moderately to some well developed palaeosols and a zone of gleyed palaeosols with laminated mudstones and thin sandstones took place in an environment marked by numerous small lakes, water-logged regions and small streams in an environment just south of the Piedmont zone, perhaps similar to what is happening presently in the Upland region/the Upper Gangetic plain. This area is locally called the `Trai region' (Pascoe, 1964). Deposition of Boulder Conglomerate Fm. took place by gravelly braided river system close to the Himalayan Ranges. Activity along the Main Boundary Fault led to progradation of these environments distal-ward and led to development of on the whole a coarsening upward sequence. (C) 2014 Elsevier B.V. All rights reserved.
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Probable maximum precipitation (PMP) is a theoretical concept that is widely used by hydrologists to arrive at estimates for probable maximum flood (PMF) that find use in planning, design and risk assessment of high-hazard hydrological structures such as flood control dams upstream of populated areas. The PMP represents the greatest depth of precipitation for a given duration that is meteorologically possible for a watershed or an area at a particular time of year, with no allowance made for long-term climatic trends. Various methods are in use for estimation of PMP over a target location corresponding to different durations. Moisture maximization method and Hershfield method are two widely used methods. The former method maximizes the observed storms assuming that the atmospheric moisture would rise up to a very high value estimated based on the maximum daily dew point temperature. On the other hand, the latter method is a statistical method based on a general frequency equation given by Chow. The present study provides one-day PMP estimates and PMP maps for Mahanadi river basin based on the aforementioned methods. There is a need for such estimates and maps, as the river basin is prone to frequent floods. Utility of the constructed PMP maps in computing PMP for various catchments in the river basin is demonstrated. The PMP estimates can eventually be used to arrive at PMF estimates for those catchments. (C) 2015 The Authors. Published by Elsevier B.V.
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Streamflow forecasts at daily time scale are necessary for effective management of water resources systems. Typical applications include flood control, water quality management, water supply to multiple stakeholders, hydropower and irrigation systems. Conventionally physically based conceptual models and data-driven models are used for forecasting streamflows. Conceptual models require detailed understanding of physical processes governing the system being modeled. Major constraints in developing effective conceptual models are sparse hydrometric gauge network and short historical records that limit our understanding of physical processes. On the other hand, data-driven models rely solely on previous hydrological and meteorological data without directly taking into account the underlying physical processes. Among various data driven models Auto Regressive Integrated Moving Average (ARIMA), Artificial Neural Networks (ANNs) are most widely used techniques. The present study assesses performance of ARIMA and ANNs methods in arriving at one-to seven-day ahead forecast of daily streamflows at Basantpur streamgauge site that is situated at upstream of Hirakud Dam in Mahanadi river basin, India. The ANNs considered include Feed-Forward back propagation Neural Network (FFNN) and Radial Basis Neural Network (RBNN). Daily streamflow forecasts at Basantpur site find use in management of water from Hirakud reservoir. (C) 2015 The Authors. Published by Elsevier B.V.
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The spatial error structure of daily precipitation derived from the latest version 7 (v7) tropical rainfall measuring mission (TRMM) level 2 data products are studied through comparison with the Asian precipitation highly resolved observational data integration toward evaluation of the water resources (APHRODITE) data over a subtropical region of the Indian subcontinent for the seasonal rainfall over 6 years from June 2002 to September 2007. The data products examined include v7 data from the TRMM radiometer Microwave Imager (TMI) and radar precipitation radar (PR), namely, 2A12, 2A25, and 2B31 (combined data from PR and TMI). The spatial distribution of uncertainty from these data products were quantified based on performance metrics derived from the contingency table. For the seasonal daily precipitation over a subtropical basin in India, the data product of 2A12 showed greater skill in detecting and quantifying the volume of rainfall when compared with the 2A25 and 2B31 data products. Error characterization using various error models revealed that random errors from multiplicative error models were homoscedastic and that they better represented rainfall estimates from 2A12 algorithm. Error decomposition techniques performed to disentangle systematic and random errors verify that the multiplicative error model representing rainfall from 2A12 algorithm successfully estimated a greater percentage of systematic error than 2A25 or 2B31 algorithms. Results verify that although the radiometer derived 2A12 rainfall data is known to suffer from many sources of uncertainties, spatial analysis over the case study region of India testifies that the 2A12 rainfall estimates are in a very good agreement with the reference estimates for the data period considered.
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Registra, em ordem cronológica, a tramitação dos trabalhos na Assembléia Constituinte, nas comissões especializadas e no plenário das duas Casas do Congresso Nacional, até a reunião conjunta destinada ao conhecimento do veto presidencial. Reúne debates de plenários e comissões, vetos, discursos, atas de reuniões e outros documentos parlamentares.
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A Ciência Política tem se preocupado nos últimos anos em compreender o comportamento dos partidos políticos no interior do Poder Legislativo. Ao contrário do que afirma a opinião pública, seria possível encontrar lógica na atuação das legendas? O que seria capaz de explicar uma eventual ordem? Na Câmara dos Deputados, estudos comprovam que os partidos agem conforme as indicações de suas lideranças. Mas como funcionam as Assembleias Legislativas? O intuito desse artigo é verificar como se comportam as bancadas partidárias na Assembleia Legislativa do Estado de São Paulo, notando que além do comportamento dos parlamentares em torno das votações nominais, houve a preocupação de avaliar o que ocorre com a atuação do deputado estadual que muda de partido.
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Consultoria Legislativa - Área IX - Política e Planejamento Econômicos, Desenvolvimento Econômico, Economia Internacional.
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Consultoria Legislativa - Área XII - Recursos Minerais, Hídricos e Energéticos.
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Consultoria Legislativa - Área XI - Meio Ambiente e Direito Ambiental, Organização Territorial, Desenvolvimento Urbano e Regional.
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Consultoria Legislativa - Área XI - Meio Ambiente e Direito Ambiental, Organização Territorial, Desenvolvimento Urbano e Regional.