Development of operating rules for a complex multireservoir system by coupling genetic algorithms and network optimization

This is an Accepted Manuscript of an article published in Hydrological Sciences Journal on MAY 1 2013, available online: http://dx.doi.org/10.1080/02626667.2013.779777[EN] An alternative procedure for assessment of reservoir Operation Rules (ORs) under drought situations is proposed. The definition of ORs for multi-reservoir water resources systems (WRSs) is a topic that has been widely studied by means of optimization and simulation techniques. A traditional approach is to link optimization methods with simulation models. Thus the objective here is to obtain drought ORs for a real and complex WRS: the Júcar River basin in Spain, in which one of the main issues is the resource allocation among agricultural demands in periods of drought. To deal with this problem, a method based on the combined use of genetic algorithms (GA) and network flow optimization (NFO) is presented. The GA used was PIKAIA, which has previously been used in other water resources related fields. This algorithm was linked to the SIMGES simulation model, a part of the AQUATOOL decision support system (DSS). Several tests were developed for defining the parameters of the GA. The optimization of various ORs was analysed with the objective of minimizing short-term and long-term water deficits. The results show that simple ORs produce similar results to more sophisticated ones. The usefulness of this approach in the assessment of ORs for complex multi-reservoir systems is demonstrated.The authors wish to thank the Confederacion Hidrogrofica del Jucar (Spanish Ministry of the Environment) for the data provided in developing this study and the Comision Interministerial de Ciencia y Tecnologia, CICYT (Spanish Ministry of Science and Innovation) for funding the projects INTEGRAME (contract CGL2009-11798) and SCARCE (programme Consolider-Ingenio 2010, project CSD2009-00065). The authors also thank the European Commission (Directorate-General for Research and Innovation) for funding the project DROUGHT-R&SPI (programme FP7-ENV-2011, project 282769) and the Seventh Framework Programme of the European Commission for funding the project SIRIUS (FP7-SPACE-2010-1, project 262902). We are grateful to the reviewers for their valuable comments, which have improved this paper.Lerma Elvira, N.; Paredes Arquiola, J.; Andreu Álvarez, J.; Solera Solera, A. (2013). Development of operating rules for a complex multireservoir system by coupling genetic algorithms and network optimization. Hydrological Sciences Journal. 58(4):797-812. https://doi.org/10.1080/02626667.2013.779777S79781258

Implicit Stochastic Optimization for deriving reservoir operating rules in semiarid Brazil

Este artigo investiga a aplicação de Otimização Estocástica Implícita (OEI) para determinar regras de operações mensais em um sistema de reservatórios localizado no nordeste semi-árido brasileiro. OEI emprega um modelo de otimização determinística para encontrar alocações ótimas do reservatório sob vários cenários possíveis de afluências e posteriormente constrói as regras a partir da análise deste conjunto de liberações ótimas. As políticas operacionais fornecem a alocação mensal do reservatório condicionada ao armazenamento no início do mês e a afluência prevista para o mês. Além da clássica análise de regressão, este estudo estabelece as regras por meio de uma estratégia de interpolação bidimensional. Após a sua identificação, as regras são aplicadas para operar o sistema sob novas realizações de afluências e mostram habilidade para produzir políticas semelhantes às obtidas a partir de otimização determinística tendo estas mesmas afluências como previsão perfeita.._________________________________________________________________________________________ ABSTRACT: This paper deals with the application of Implicit Stochastic Optimization (ISO) to determine monthly operating rules for a reservoir system located in the semiarid Northeast of Brazil. ISO employs a deterministic optimization model to find optimal reservoir allocations under several possible inflow scenarios and later constructs the rules by analyzing the ensemble of these optimal releases. The operating policies provide the monthly reservoir release conditioned on the storage at the beginning of the month and the inflow predicted for the month. In addition to the classical regression analysis, this study establishes the rules by a two-dimensional interpolation strategy. After the rules are identified, they are applied to operate the system under new inflow realizations and show ability to produce policies similar to those obtained by deterministic optimization taking the same inflows as perfect forecasts

Groundwater hydrology : engineering, planning, and management

The book develops a system view of groundwater fundamentals and model-making techniques through the application of science, engineering, planning, and management principles. It discusses the classical issues in groundwater hydrology and hydraulics followed by coverage of water quality issues. The authors delineate the process of analyzing data, identification, and parameter estimation; tools and model-building techniques and the conjunctive use of surface and groundwater techniques; aquifer restoration, remediation, and monitoring techniques; and analysis of risk. They touch on groundwater risk and disaster management and then explore the impact of climate change on groundwater and discuss the tools needed for analyzing future data realization and downscaling large-scale low-resolution data to local watershed and aquifer scales for impact studies

Development Of An Entropy- Based Fuzzy Eutrophication Index For Reservoir Water Quality Evaluation

Eutrophication phenomenon is one of the most common water quality problems in reservoirs in many regions. Determining the trophic status of the reservoirs is not a precise process and contains vagueness. Fuzzy set and entropy theories are concepts which can model uncertainty and imprecision in the data and the analysis. In this study, an Entropy-based Fuzzy Eutrophication Index model has been developed for classification of trophic level of Satarkhan Reservoir in the north-western part of Iran. Through the Fuzzy Synthetic Evaluation technique, trophic levels were considered as fuzzy sets and a fuzzy evaluation matrix was formed by defining the membership function of water quality indicators. The indicators were weighed by integrating both objective and subjective criteria. In this regard, the entropy method was used to determine the objective weights of the indicators based on the amount of useful information available in the data set and the subjective weight was determined by the analytical hierarchy process using a pairwise comparison done by the expert judgment. Classification of the trophic status of the reservoir was determined by multiplying the weighed vector by the fuzzy evaluation matrix. The results showed that critical months for eutrophication in Satarkhan reservoir occur in autumn and spring after the overturning phenomena. The strength of the results of developed entrophy-based fuzzy entrophication index is that the trophic level in each month was expressed with a degree of certainty. Also due to the ability of the model to integrate different kinds of objective and subjective quality observations considering the information included in the data, the proposed model is more robust than the previous index models such as Trophic Status Index and fuzzy trophic index