<p>Society&#8217;s increasing demand for water and the need for its long-term management have motivated efforts toward improving seasonal streamflow forecasts. Currently, seasonal climate forecasts are routinely issued in meteorological centers around the world, generating information for decision-making and seasonal streamflow forecasting (SSF) studies that are becoming more frequent. Seasonal streamflow forecast skill derives from land surface initial conditions and atmospheric boundary conditions that mostly depend on large-scale climate phenomena (such as ENSO). Thus, seasonal rainfall predictions produced by dynamic climate models that represent ocean-atmosphere interactions may have a positive impact on streamflow forecasts. In South America, seasonal streamflow forecasts are essential for the hydropower sector, which is responsible for ~65% of the electric energy produced in countries such as Brazil. In this work, we assessed seasonal streamflow forecasts over South America based on a continental-scale application of a hydrologic-hydrodynamic model and precipitation forecasts from the ECMWF's fifth generation seasonal forecast system (SEAS5). Seasonal streamflow forecasts (SEAS5-SF) were evaluated against a reference model run and forecast skill was estimated relative to the Ensemble Streamflow Prediction (ESP) method. The bias correction of SEAS5 predicted precipitation improved the performance of the seasonal streamflow forecasts, frequently turning negative skill results into near null to positive skill. Results indicate that the ESP remains a hard-to-beat method for seasonal streamflow forecasting in South America. SEAS5-SF skill was found to be dependent on initialization month, season, basin and forecast lead time, with greater skill on the initialization month lead time. Rivers where the forecast skill is higher were Amazon, Araguaia, Tocantins and Paran&#225;.</p> <p>&#160;</p> <p>Acknowledgments: This work presents part of the results obtained during the project granted by the Brazilian Agency of Electrical Energy (ANEEL) under its Research and Development program 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. The Hydraulic Research Institute (IPH) from the Federal University of Rio Grande do Sul (UFRGS) contribute to part of the project through an agreement with the RHAMA company (IAP-001313).</p>
The design of water distribution systems includes, above all, the determination of the pipe size that meets the requirements of the system and brings reduced annual costs of installation and operation. Among the existing methodologies for the economic pipe diameter determination, Bresse’s equation is still common among designers. This work aims to analyze the efficiency of Bresse’s equation, the MBPW and the MLVPC, comparing them with the MREC. We recommend that the designers do not use the MBPW and the MLVPC. When referring to water distribution systems of small size, it is possible to use the equation of Bresse, as long as it is used with a proper value for its coefficient k. For HDPE, we propose k = 1.17 or k = 1.18. For PVC DEFOFO and GFRP, we suggest the range of 1.19 to 1.23 and 1.29 to 1.32, respectively. Regarding the water distribution systems of bigger dimensions, we recommend the use of MREC as the methodology for the economic pipe diameter determination, due to the impossibility of finding an appropriate value for the Bresse’s equation coefficient.
<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 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). We present in this work the framework built up as interface to the results of this project, which integrate shapefiles of main river basins in Brazil, hydro meteorological information, forecasts of precipitation from seasonal models (e.g., ECMWF&#8217;s SEAS5) and derived streamflow from hydrological model used in the project (MGB-SA mainly) for the entire electric energy network of the country. The platform encompasses layers of maps and graphics synchronized by date, respectively to locations of hydro power plants in Brazil, which allows users to perform multiple analysis for either energy planning or routine hydraulic operations. We shall demonstrate examples of applications, such analysis of a flood event happened during the 2014/2015 El Ni&#241;o episode, which caused heavy precipitation, increased river level and flow into reservoirs in the Igua&#231;u River basin, disruption of services and economic losses in the South of Brazil. Given the limitations of seasonal precipitation forecasting, the model was successful in predicting the heavy accumulated rainfall in the analyzed period. In parallel, the hydrological model was able to simulate flow peaks well in advance. In addition, the platform allows an overview of the SIN subsystems and respective stored energy, which allows intercomparison and pragmatic analysis of the country's electric energy capacity.</p>
<p align="justify"><span lang="en-US">Short-to-medium range streamflow forecasting is essential for planning and operating hydropower plants (HPPs). The Brazilian National Interconnected System (SIN) is composed of more than 150 HPPs that are located over a wide range of climate and hydrological conditions. Forecasts of natural inflow into the SIN reservoirs are important to establish optimal operating rules to reduce costs with other energy sources, therefore influencing the prices in the energy market. The objective of this work is twofold: (i) evaluate the skill of ensemble streamflow forecasts for the SIN hydropower plants based on continental-scale hydrological modeling (MGB-SA) and medium-range ECWMF rainfall forecasts (MGB-ECMWF), and (ii) compare the MGB-ECMWF forecasts to those produced operationally by the Electric System National Operator (ONS). The MGB-ECMWF predictions were additionally bias-corrected and updated using quantile mapping and auto-regressive model approaches, and were assessed in the period from 2015 to 2020 in terms of weekly averages. The forecast skill was estimated relative to both streamflow climatology and persistency using the CRPS metric, while the comparison between MGB-ECMWF and operational forecasts was performed using deterministic metrics typically adopted by ONS. The skill of MGB-ECMWF forecasts was substantially improved (especially in the first week) by the use of output correction methods, which were demonstrated to be essential for quantitative streamflow forecasting using a continental-scale hydrological model. The relative performance between ONS and MGB-ECMWF forecasts was quite variable (exhibiting positive and negative values) over the geographical extent of the SIN, although in several locations the MGB-ECMWF forecasts have performed equal to or even better than those issued by ONS. Finally, the results presented here provide insights for investigations and applications of streamflow forecasts using continental-scale modeling and simple output correction techniques, which can bring benefits, for example, in the optimization of the reservoir operation and electricity generation.</span></p> <p align="justify"><span lang="en-US">Acknowledgments: This work presents part of the results obtained during the project granted by the Brazilian Agency of Electrical Energy (ANEEL) under its Research and Development program 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. The Hydraulic Research Institute (IPH) from the Federal University of Rio Grande do Sul (UFRGS) contribute to part of the project through an agreement with the RHAMA company (IAP-001313).</span></p>
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