Interest has been growing in the study of the role played by university-industry links in the development and strengthening of economic systems. It is commonly agreed that universityindustry links play a crucial role in the economy, and many studies have examined the factors that influence their occurrence. Two sets of factors can be identified from these studies: demand-side factors (i.e. relating to industry) and supply-side factors (i.e. relating to universities). This paper reviews the literature covering these issues, concentrating on the influence of long-term patterns in R&D formalisation on university-industry links. This is done for selected advanced and late-industrialising countries. The literature reviewed indicated that, in advanced countries, university-industry links become more varied as R&D becomes for- KEYWORDSUniversity-industry links, R&D. JEL-CODES O39; O32 RESUMOTem sido crescente o interesse no estudo do papel das relações universidade-empresa no desenvolvimento e fortalecimento de sistemas econômicos. Tornou-se consenso que estas relações possuem papel crucial na economia e muitos estudos examinam os fatores que influenciam sua ocorrência. Dois conjuntos de fatores podem ser identificados a partir destes estudos: fatores relacionados com a demanda (empresas); e fatores relacionados com a oferta (universidades). Este artigo revisa esta literatura, concentrando-se na influência dos padrões de longo prazo na formalização da P&D sobre a relação universidade-empresa. Esta revisão cobre países avançados e de industrialização tardia. Em países avançados, as relações entre universidades e empresas tornam-se mais variadas quando a P&D é mais formalizada. Nos países de industrialização tardia, as relações entre universidades e empresas tornam-se mais intensas quando a P&D é mais formalizada. PALAVRAS-CHAVERelação universidade-empresa; P&D.
Hydrological modeling is an important tool for water resources management, providing a feasible solution to represent the main hydrological processes and predict future streamflow regimes. The literature presents a set of hydrological models commonly used to represent the rainfall-runoff process in watersheds with different meteorological and geomorphological characteristics. The response of such models could differ significantly for a single precipitation event, given the uncertainties associated with the input data, parameters, and model structure. In this way, a correct hydrological representation of a watershed should include the evaluation of different hydrological models. This study explores the use and performance of five hydrological models to represent daily streamflow regimes at six hydropower plants located in the Tocantins river basin (Brazil). The adopted models include the GR4J, HYMOD, HBV, SMAP, and MGB-IPH. The evaluation of each model was elaborated considering the calibration (2014–2019) and validation period (2005–2010) using observed data of precipitation and climatological variables. Deterministic metrics and statistical tests were used to measure the performance of each model. For the calibration stage, results show that all models achieved a satisfactory performance with NSE values greater than 0.6. For the validation stage, only the MGB-IPH model present a good performance with NSE values greater than 0.7. A bias correction procedure were applied to correct the simulated data of conceptual models. However, the statistical tests exposed that only the MGB-IPH model could preserve the main statistical properties of the observed data. Thus, this study discusses and presents some limitations of the lumped model to represent daily streamflows in large-scale river basins (>50,000 km2).
<p>The Electric Energy Company of Parana (COPEL GeT), the Meteorological System of Parana (SIMEPAR) and RHAMA Consulting company are undertaking the research project PD-6491- 0503/2018 for the development of a hydrometeorological seasonal forecasting for Brazilian reservoirs. The project, sponsored by the Brazilian Electricity Regulatory Agency (ANEEL) under its research and development program, aims the forecasting of streamflow, at temporal scales ranging from 1 to 270 days, at hydro power enterprises, which are integrated by the National Power System Operator (ONS) through its Interconnected System (SIN). With the aim of implement a seasonal forecasting system using different hydrological modeling approaches, it is necessary first to validate the use of different hydrological models during the calibration and validation stages. This work evaluates the performance of four conceptual hydrological models to represent daily streamflow regimes at four hydropower plants located in the Teles Pires river basin (Brazil). The adopted models included the GR4J, HYMOD, HBV, and the SMAP. The calibration of the parameters for each hydrological model was performed using the SCE-UA method and a triangular weighting function was adopted for routing the hydrograph between sub-watersheds. The evaluation of each model was elaborated by the comparison of the observed and simulated streamflow time series during the calibration (2010-2016) and the validation period (2016-2019) using deterministic metrics and statistical tests. A post-processing procedure based on the quantile-quantile method was applied in order to correct the simulated data and reduce the bias with respect the observed data. In general, the results show that the SMAP model present a better performance to simulate the daily streamflow regimes at the simulated hydropower plants, with Nash-Sutcliffe coefficient (NSE) greater than 0.65, and NSElog values greater than 0.8. In addition, the bias correct procedure shows a significant improvement in the adjust of the simulated data to represent the periodic streamflow regimes in the selected river basin.</p>
<p>In rainfall-runoff modeling, the main input variable is precipitation, and the understanding of its temporal and spatial variation is the key for good hydrological simulation results. Conventionally, the precipitated volumes are measured by rain gauges, which are representative of its surroundings and, consequently, it is necessary to apply extrapolation techniques to obtain data in ungauged regions. However, classical techniques are based on mathematical interpolation and do not consider the physical evidence for the occurrence of precipitation. Remote sensing represents a valuable alternative to hydrological modeling due to its wide coverage, and from observations by meteorological satellites and radars, quantitative precipitation estimation is possible. In this sense, the integrated use of data from rain gauges and remote sensing has the potential to improve the accuracy of hydrological simulations. This study aims to evaluate the performance of a hydrological model in the Colider River basin (Brazil), when calibrated with a global product that provides precipitation data based on rain gauges observations, satellite and weather radar. The model used was the MGB-IPH and the data source of precipitation was MSWEP (Multi-Source Weighted-Ensemble Precipitation). Two different calibrations were performed: the first, considering only the precipitation data from rain gauges; the second, considering the precipitation estimated by the product. The comparison between the rain datasets indicates that MSWEP tends to overestimate the precipitation in most cases, except during periods of considerable drought, when it underestimates. Nevertheless, the results in the hydrological simulation were satisfactory, with the model calibrated with MSWEP presenting equivalente or slightly better performance metrics than the one with conventional data. This is an indication that the continuous development of remote sensing products can be the key to increase the reliability of tools that comprise hydrological modeling, such as forecasting hydrological events, climatic hazards and also commercialization of electric energy.</p><p>Acknowledgments: This work presents part of the results obtained during the project granted by the Brazilian National Electricity Regulatory Agency (ANEEL) under its Research and Development Project PD 6491-0503/2018 &#8211; &#8220;Previs&#227;o Hidroclim&#225;tica com Abrang&#234;ncia no Sistema Interligado Nacional de Energia El&#233;trica&#8221; developed by the Paran&#225; State electric company (COPEL GeT), the Meteorological System of Paran&#225; (SIMEPAR) and the RHAMA Consulting company.</p>
<p><span>The Electric Energy Company of Parana (COPEL GeT), the Meteorological System of Parana (SIMEPAR) and RHAMA Consulting company are undertaking the research project PD-6491-0503/2018 for the development of a hydrometeorological seasonal forecasting for Brazilian reservoirs. The project, sponsored by the </span>Brazilian Electricity Regulatory Agency <span>(ANEEL) under its research and development programme, aims the forecasting of streamflow, at temporal scales ranging from 1 to 270 days, at hydro power enterprises, which are integrated by the National Power System Operator (ONS) through its Interconnected System (SIN). In the present work, we verify the precipitation seasonal product from SEAS5 from ECMWF against three references, namely model climatology, ERA5 reanalysis and in-situ observations. In order to achieve the results, we extract the values from the model, respectively to the closest location of observations within Brazilian rain gauge network, corresponding to hydro power plants, and compare them to the observed values and ERA5 results, for the period from 2000 to 2020. The accuracy measurement was performed by settling a contingency matrix to estimate the probability of detection (POD), probability of false detection (POFD), the ROC curve, the area under the ROC (AUC) and other related metrics. The statistics are gathered by monthly and by season and by considering three quantile thresholds of rainfall distribution for forecasting, computed for 153 reservoirs of the SIN. The results describe a good performance of SEAS5 for either monthly or seasonal forecast if compared to climatology or ERA5, but less accuracy if compared to the rain gauges, mainly for low quantiles. Despite this, by considering the large extension of the country and its climate diversity, we noticed the SEAS5 is quite promising for using on hydrological forecasting at seasonal scale.</span></p>
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