Fernando Mainardi Fan

Short-Term Reservoir Optimization for Flood Mitigation under Meteorological and Hydrological Forecast Uncertainty

State-of-the-art applications of short-term reservoir management integrate several advanced components, namely hydrological modelling and data assimilation techniques for predicting streamflow, optimization-based techniques for decision-making on the reservoir operation and the technical framework for integrating these components with data feeds from gauging networks, remote sensing data and meteorological weather predictions. In this paper, we present such a framework for the short-term management of reservoirs operated by the Companhia Energética de Minas Gerais S.A. (CEMIG) in the Brazilian state of Minas Gerais. Our focus is the Três Marias hydropower reservoir in the São Francisco River with a drainage area of approximately 55,000 km and its operation for flood mitigation. Basis for the anticipatory short-term management of the reservoir over a forecast horizon of up to 15 days are streamflow predictions of the MGB hydrological model. The semi-distributed model is well suited to represent the watershed and shows a Nash-Sutcliffe model performance in the order of 0.83-0.90 for most streamflow gauges of the data-sparse basin. A lead time performance assessment of the deterministic and probabilistic ECMWF forecasts as model forcing indicate the superiority of the probabilistic model. The novel short-term optimization approach consists of the reduction of the ensemble forecasts into scenario trees as an input of a multi-stage stochastic optimization. We show that this approach has several advantages over commonly used deterministic methods which neglect forecast uncertainty in the short-term decision-making. First, the probabilistic forecasts have longer forecast horizons that allow an earlier and therefore better anticipation of critical flood events. Second, the stochastic optimization leads to more robust decisions than deterministic procedures which consider only a single future trajectory. Third, the stochastic optimization permits to introduce advanced chance constraints for refining the system operation.

Large-scale analytical water quality model coupled with GIS for simulation of point sourced pollutant discharges

Mathematical modeling is an important tool for water quality studies, and the integration of water quality models with geographic information systems (GIS) is very useful for information extraction and for results interpretation. In this context, this work presents the development of a water quality model coupled with GIS (MapWindow GIS) for representing impacts of point-sourced pollutants released with distinct durations under different flow scenarios, allowing a systemic view of the entire basin, and capable of being used with low data availability. The model is called SIAQUA-IPH and uses a pollutograph convolution scheme to represent multiple discharges and confluences in the basin, based on analytical solutions of the longitudinal advection-dispersion equation. Operational tests presented a full operational performance from all technical solutions adopted, and a representation of plumes considered satisfactory in comparison to observations. Additionally, a simple sensitivity analysis is presented, that gives useful insights about the model application. Water quality decision support model fully coupled with an open GIS.Represents pollutants released with distinct durations using a convolution schema.Useful at low data availability and large scale basins, common on Brazilian cases.Results are compared with observed data and critically analyzed.Considerations are presented about the adopted modeling approach usage.

MGB-IPH model for hydrological and hydraulic simulation of large floodplain river systems coupled with open source GIS

Abstract Large-scale hydrological models are useful tools for water resources studies, however, river network flow routing is generally represented using simplified methods, which may lead to simulation errors in flat regions. We present recent improvements to the large-scale hydrological model MGB-IPH to improve its capability of simulating large river basins with extensive floodplains. We also describe the coupling of MGB-IPH to an open source GIS and a large set of developed pre-processing tools with a user-friendly interface for remote sensing data preparation and output visualization. The new features implemented are demonstrated applying the model to the whole Araguaia river basin (380,000 km2). Results are compared to the previous MGB-IPH routing method, observed flow and water level data and remote sensing imagery, showing improvement in the representation of floodplain inundation dynamics. The test case also shows that the proposed model software framework amplifies possibilities of large-scale simulation of ungauged basins.

Ensemble flood forecasting based on operational forecasts of the regional Eta EPS in the Taquari-Antas basin

Hydrological Ensemble Prediction Systems (HEPS) play an important role on operational flood forecasting. Unlike in deterministic approach, which relies on a single prediction of future river flows, these systems can represent the forecast uncertainty and provide a better detection of extreme hydro-meteorological events. In this context, the present study aimed to assess both the quality of ensemble flood forecasts on Taquari-Antas basin and its potential to provide additional information to a local Flood Alert System. The hydrological model MGB-IPH was coupled to the high-resolution meteorological EPS Eta model with five members of different parameterization schemes and boundary conditions, as well as to the deterministic version of Eta regional model. On a single event evaluation, the peak discharge was reasonable well predicted by at least one ensemble member, in nearly all forecasts, with a good prediction of the flood timing for the considered lead times. In a comparison with deterministic forecasts, the ensemble ones showed higher accuracy and higher probability of detection (POD) for the reference thresholds, preserving false alarm rates at reasonably low levels. An overall tendency of underestimation was also identified, with most observations falling between the higher ranks of the ensemble. Furthermore, the combination of previous forecasts (t-12h) with the recent ones leads to a slight increase of ensemble spread and POD, despite the performance reduction in terms of accuracy and bias for the ensemble mean. Results suggest that there is a benefit in having hydrological ensemble forecasts obtained from the high resolution EPS Eta model, which can be used as a complementary information to a local Flood Alert System supporting pre-alert issues and Civil Defense internal planning actions.

IPH-Hydro Tools: uma ferramenta open source para determinação de informações topológicas em bacias hidrográficas integrada a um ambiente SIG

A delimitação de bacias hidrográficas, geração da rede de drenagem e determinação de características hidráulicas de um rio de interesse são partes importantes de estudos na área de hidrologia. Atualmente muitas dessas informações são obtidas com o processamento de modelos digitais de elevação (MDEs) em softwares comerciais de SIG, como o ArcGIS e o IDRISI. Por outro lado, pacotes de SIG para uso livre, ou seja, gratuitos e de código aberto, têm aumentado significativamente nos últimos anos, e as vantagens desses pacotes incluem ampla distribuição e customização, desenvolvimento continuado pela comunidade de usuários e atendimento a necessidades específicas. Este trabalho apresenta o pacote livre (open-source) denominado IPH-Hydro Tools, um conjunto de ferramentas acoplado ao software livre MapWindow GIS criado para facilitar a aquisição de informações topológicas em bacias hidrográficas, bem como realização de etapas de pré-processamento em modelos hidrológicos a exemplo do MGB-IPH. Para avaliar a aplicabilidade e o desempenho da ferramenta desenvolvida foram realizados testes específicos, através da comparação dos resultados do IPH-Hydro Tools em relação a outros pacotes de SIG (ArcGIS, IDRISI, WhiteBox) disponíveis para esta finalidade. O IPH-Hydro Tools apresentou qualidade de rede de drenagem geralmente superior aos demais pacotes e menor tempo de processamento necessário para delimitação de bacias, apesar de algumas limitações como incompatibilidade em relação a matrizes muito grandes e dificuldade na representação da rede de drenagem em áreas extensas de mesma cota, a exemplo de reservatórios e rios muito largos.

Performance of Deterministic and Probabilistic Hydrological Forecasts for the Short-Term Optimization of a Tropical Hydropower Reservoir

Hydropower is the most important source of electricity in Brazil. It is subject to the natural variability of water yield. One building block of the proper management of hydropower assets is the short-term forecast of reservoir inflows as input for an online, event-based optimization of its release strategy. While deterministic forecasts and optimization schemes are the established techniques for short-term reservoir management, the use of probabilistic ensemble forecasts and multi-stage stochastic optimization techniques is receiving growing attention. The present work introduces a novel, mass conservative scenario tree reduction in combination with a detailed hindcasting and closed-loop control experiments for a multi-purpose hydropower reservoir in a tropical region in Brazil. The case study is the hydropower project Três Marias, which is operated with two main objectives: (i) hydroelectricity generation and (ii) flood control downstream. In the experiments, precipitation forecasts based on observed data, deterministic and probabilistic forecasts are used to generate streamflow forecasts in a hydrological model over a period of 2 years. Results for a perfect forecast show the potential benefit of the online optimization and indicate a desired forecast lead time of 30 days. In comparison, the use of actual forecasts of up to 15 days shows the practical benefit of operational forecasts, where stochastic optimization (15 days lead time) outperforms the deterministic version (10 days lead time) significantly. The range of the energy production rate between the different approaches is relatively small, between 78% and 80%, suggesting that the use of stochastic optimization combined with ensemble forecasts leads to a significantly higher level of flood protection without compromising the energy production.

Modelo analítico de qualidade da água acoplado com Sistema de Informação Geográfica para simulação de lançamentos com duração variada

This paper presents the development of a water quality model coupled with an open source Geographic Information System (GIS) software representing the impacts of large scale pollutant releases, with a systemic view of the entire basin, and simplified tools to deal with typical data scarcity situations. In the proposed model, called SIAQUA-IPH, a methodology based on the pollutant transport equation analytical solution through a scheme of linear superposition is adopted. The paper also presents tests in which model results were compared to tracer releases experiments in the Paraiba do Sul river, where promising results were obtained considering the uncertainties involved.

Comparison of numerical schemes of river flood routing with an inertial approximation of the Saint Venant equations

The one-dimensional flow routing inertial model, formulated as an explicit solution, has advantages over other explicit models used in hydrological models that simplify the Saint-Venant equations. The main advantage is a simple formulation with good results. However, the inertial model is restricted to a small time step to avoid numerical instability. This paper proposes six numerical schemes that modify the one-dimensional inertial model in order to increase the numerical stability of the solution. The proposed numerical schemes were compared to the original scheme in four situations of river’s slope (normal, low, high and very high) and in two situations where the river is subject to downstream effects (dam backwater and tides). The results are discussed in terms of stability, peak flow, processing time, volume conservation error and RMSE (Root Mean Square Error). In general, the schemes showed improvement relative to each type of application. In particular, the numerical scheme here called Prog Q(k+1)xQ(k+1) stood out presenting advantages with greater numerical stability in relation to the original scheme. However, this scheme was not successful in the tide simulation situation. In addition, it was observed that the inclusion of the hydraulic radius calculation without simplification in the numerical schemes improved the results without increasing the computational time.

Evaluation of upper Uruguay river basin (Brazil) operational flood forecasts

System for hydrological forecasting and alert running in an operational way are important tools for floods impacts reduction. The present study describes the development and results evaluation of an operational discharge forecasting system of the upper Uruguay River basin, sited in Southern Brazil. Developed system was operated every day to provide experimental forecasts with special interest for Barra Grande and Campos Novos hydroelectric power plants reservoirs inflow, with 10 days in advance. We present results of inflow forecasted for floods occurred between July 2013 to July 2016, the period which the system was operated. Forecasts results by visual and performance metrics analysis showed a good fit with observations in most cases, with possibility of floods occurrence being well predicted with antecedence of 2 to 3 days. Comparing the locations, it was noted that the sub-basin of Campos Novos, being slower in rainfall-runoff transformation, is easier forecasted. The difference in predictability between the two basins can be observed by the coefficient of persistence, which is positive from 12h in Barra Grande and from 24h to Campos Novos. These coefficient values also show the value of the rainfall-runoff modeling for forecast horizons of more than one day in the basins.

Sobre o Uso da Persistência de Previsões Determinísticas de Vazão para a Tomada de Decisão

Medium-range streamflow forecasts, which are generated using rainfall-runoff models forced by numerical precipitation predictions, are very useful for the anticipation of hydrological events. Traditionally these predictions are deterministic, but in the last decade the movement for generating ensemble streamflow forecasts has been gaining strength. In the middle ground between these two techniques (deterministic and ensembles) the use of persistence information from deterministic streamflow forecasts for decision making, using it as an uncertainty measurement, appears to be an interesting strategy. This research investigates precisely these possible benefits of using forecasts based on persistence as uncertainty information measurement. Results suggest that the use of forecasts based on persistence have advantages over single deterministic forecasts on the higher lead times.