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Juan Chen - One of the best experts on this subject based on the ideXlab platform.

  • Improved Risk-Assessment Model for Real-Time Reservoir Flood-Control Operation
    Journal of Water Resources Planning and Management, 2020
    Co-Authors: Juan Chen, Ping-an Zhong, Feilin Zhu, Weiguo Zhang, Yu Zhang
    Abstract:

    AbstractThis paper puts forward an improved risk assessment model for a real-time reservoir flood Control Operation according to the stochastic differential equation (SDE). The model is composed of...

  • Risk analysis for real-time flood Control Operation of a multi-reservoir system using a dynamic Bayesian network
    Environmental Modelling & Software, 2019
    Co-Authors: Juan Chen, Ping-an Zhong, Feilin Zhu
    Abstract:

    Abstract This paper proposes a model for risk analysis of real-time flood Control Operation of a multi-reservoir system using a dynamic Bayesian network. The proposed model consists of three components: Monte Carlo simulations, dynamic Bayesian network establishing, and risk-informed inference for decision making. The Monte Carlo simulations provide basic data inputs for the dynamic Bayesian network establishing using the historical floods and Operation models of the multi-reservoir system. The dynamic Bayesian network is built with expert knowledge and the relationships among the uncertainties. The component of risk-informed inference for decision making is to provide risk information about the Operation schedules using the trained dynamic Bayesian network. We apply the proposed model to a multi-reservoir system in China. The results show that the proposed method has a capability for bi-directional inferences and can be served as a risk-informed decision-making tool under uncertainties in the real-time flood Control Operation of a multi-reservoir system.

  • SMAA-based stochastic multi-criteria decision making for reservoir flood Control Operation
    Stochastic Environmental Research and Risk Assessment, 2016
    Co-Authors: Feilin Zhu, Juan Chen, Ping-an Zhong, Wu Yenan, Yimeng Sun, Benyou Jia
    Abstract:

    In reservoir flood Control Operation, candidate alternatives are generally evaluated, ranked and selected through multi-criteria decision making (MCDM) techniques, yet stochastic uncertainties both in the criteria performance values (PVs) and criteria weights (CWs) exist in the MCDM process. This paper extends the traditional MCDM methods to stochastic environments for reservoir flood Control Operation. The criteria PVs and CWs are treated as stochastic variables with certain probability distributions. The stochastic multicriteria acceptability analysis (SMAA) theory is introduced and the differences between conventional MCDM models and the SMAA-2 model are discussed. Methods for quantifying stochastic uncertainties in the criteria PVs are discussed and four kinds of CWs are proposed. Moreover, we define the concept of the risk of decision making errors and propose the corresponding quantitative calculation method. A three-stage MCDM procedure is recommended to guide decision makers to solve MCDM problems under stochastic environments. We apply the proposed methodology to a case study through Monte Carlo simulation to demonstrate its effectiveness and advantage. The results show that the proposed methodology can provide significant risk information for decision makers and improve the reliability of decisions for reservoir flood Control Operation.

  • risk analysis for real time flood Control Operation of a reservoir
    Journal of Water Resources Planning and Management, 2015
    Co-Authors: Juan Chen, Ping-an Zhong, Yunfa Zhao
    Abstract:

    AbstractThere are many uncertainties in real-time flood Control Operation of a reservoir, which create risks in flood Control decision making. In this paper, three uncertainty factors—reservoir inflow-forecasting errors, outflow errors, and observation errors of reservoir storage capacity curve—are taken into account and quantified methods are proposed. With consideration of the three uncertainties and correlation between inflow-forecasting errors, reservoir water-level errors are derived using the stochastic differential equation of reservoir flood routing. Then the definition and calculation methods for flood risk at each moment and the integrated risk of the entire flood process are proposed. The Dahuofang reservoir in China is selected as the case study. The results shows that the risk resulting from the uncertainties is decreased by the reservoir flood regulation function and that the proposed method can provide a useful way to estimate the risks in real-time reservoir flood Control.

  • risk analysis for the downstream Control section in the real time flood Control Operation of a reservoir
    Stochastic Environmental Research and Risk Assessment, 2015
    Co-Authors: Juan Chen, Ping-an Zhong, Yunfa Zhao
    Abstract:

    Many uncertainty factors are associated with the joint Operation of a reservoir and its downstream river, which create risks in flood Control decisions. Therefore, this paper proposes an analytical method for the estimation of the uncertainties and their risks in real-time flood Control decisions. Three uncertainty factors, including reservoir discharge errors, forecasting errors of lateral inflows and river food routing errors are proposed and modeled as stochastic processes, and their internal transforming formulas are derived based on the theory of routing before combination. The definition and calculation formulas for the risks of each moment and the integrated risk of the entire flood process at the downstream flood Control section are proposed by an analytical approach based on the combination theory of stochastic processes. The Dahuofang reservoir in northern China is selected as the study case. The results indicate that the risk of the flood peak is higher than that of other moments under the same Controlled flood discharge and that the risk that arises from the uncertainties of the reservoir discharge and lateral inflow is decreased by the river storage function. Compared with the Monte Carlo method, the proposed method is effective and efficient for performing risk analysis of the downstream Control section in the real-time flood Control Operation of a reservoir. The risk analysis results could provide important information regarding flood risks for the operators to implement flood Control arrangements.

Ping-an Zhong - One of the best experts on this subject based on the ideXlab platform.

  • Improved Risk-Assessment Model for Real-Time Reservoir Flood-Control Operation
    Journal of Water Resources Planning and Management, 2020
    Co-Authors: Juan Chen, Ping-an Zhong, Feilin Zhu, Weiguo Zhang, Yu Zhang
    Abstract:

    AbstractThis paper puts forward an improved risk assessment model for a real-time reservoir flood Control Operation according to the stochastic differential equation (SDE). The model is composed of...

  • Risk analysis for real-time flood Control Operation of a multi-reservoir system using a dynamic Bayesian network
    Environmental Modelling & Software, 2019
    Co-Authors: Juan Chen, Ping-an Zhong, Feilin Zhu
    Abstract:

    Abstract This paper proposes a model for risk analysis of real-time flood Control Operation of a multi-reservoir system using a dynamic Bayesian network. The proposed model consists of three components: Monte Carlo simulations, dynamic Bayesian network establishing, and risk-informed inference for decision making. The Monte Carlo simulations provide basic data inputs for the dynamic Bayesian network establishing using the historical floods and Operation models of the multi-reservoir system. The dynamic Bayesian network is built with expert knowledge and the relationships among the uncertainties. The component of risk-informed inference for decision making is to provide risk information about the Operation schedules using the trained dynamic Bayesian network. We apply the proposed model to a multi-reservoir system in China. The results show that the proposed method has a capability for bi-directional inferences and can be served as a risk-informed decision-making tool under uncertainties in the real-time flood Control Operation of a multi-reservoir system.

  • Selection of criteria for multi-criteria decision making of reservoir flood Control Operation
    Journal of Hydroinformatics, 2017
    Co-Authors: Feilin Zhu, Ping-an Zhong, Yimeng Sun
    Abstract:

    In reservoir flood Control Operation, selection of criteria is an important part of the multi-criteria decision making (MCDM) procedure. This paper proposes a method to select criteria for MCDM of reservoir flood Control Operation based on the back-propagation (BP) neural network. According to the concept of ideal and anti-ideal points, we propose a method to generate training samples of the BP neural network via stochastic simulation. The topological structure of a three-layer BP neural network used for criteria selection is established. The relative importance of criteria is derived via the learned connection weights of a trained BP neural network, and its calculation method is proposed. The sensitivity curve method is employed to conduct sensitivity analysis, and the relative contribution ratio is defined to quantify the relative sensitivity strength of each criterion. We present the principle and threshold value of criteria selection based on the comprehensive discrimination index defined by the combination of the relative importance and relative contribution ratio. The Pubugou reservoir is selected as the case study. The results show that the proposed method can provide an effective tool for decision makers to select criteria before MCDM modeling of reservoir flood Control Operation.

  • SMAA-based stochastic multi-criteria decision making for reservoir flood Control Operation
    Stochastic Environmental Research and Risk Assessment, 2016
    Co-Authors: Feilin Zhu, Juan Chen, Ping-an Zhong, Wu Yenan, Yimeng Sun, Benyou Jia
    Abstract:

    In reservoir flood Control Operation, candidate alternatives are generally evaluated, ranked and selected through multi-criteria decision making (MCDM) techniques, yet stochastic uncertainties both in the criteria performance values (PVs) and criteria weights (CWs) exist in the MCDM process. This paper extends the traditional MCDM methods to stochastic environments for reservoir flood Control Operation. The criteria PVs and CWs are treated as stochastic variables with certain probability distributions. The stochastic multicriteria acceptability analysis (SMAA) theory is introduced and the differences between conventional MCDM models and the SMAA-2 model are discussed. Methods for quantifying stochastic uncertainties in the criteria PVs are discussed and four kinds of CWs are proposed. Moreover, we define the concept of the risk of decision making errors and propose the corresponding quantitative calculation method. A three-stage MCDM procedure is recommended to guide decision makers to solve MCDM problems under stochastic environments. We apply the proposed methodology to a case study through Monte Carlo simulation to demonstrate its effectiveness and advantage. The results show that the proposed methodology can provide significant risk information for decision makers and improve the reliability of decisions for reservoir flood Control Operation.

  • risk analysis for real time flood Control Operation of a reservoir
    Journal of Water Resources Planning and Management, 2015
    Co-Authors: Juan Chen, Ping-an Zhong, Yunfa Zhao
    Abstract:

    AbstractThere are many uncertainties in real-time flood Control Operation of a reservoir, which create risks in flood Control decision making. In this paper, three uncertainty factors—reservoir inflow-forecasting errors, outflow errors, and observation errors of reservoir storage capacity curve—are taken into account and quantified methods are proposed. With consideration of the three uncertainties and correlation between inflow-forecasting errors, reservoir water-level errors are derived using the stochastic differential equation of reservoir flood routing. Then the definition and calculation methods for flood risk at each moment and the integrated risk of the entire flood process are proposed. The Dahuofang reservoir in China is selected as the case study. The results shows that the risk resulting from the uncertainties is decreased by the reservoir flood regulation function and that the proposed method can provide a useful way to estimate the risks in real-time reservoir flood Control.

Yunfa Zhao - One of the best experts on this subject based on the ideXlab platform.

  • risk analysis for real time flood Control Operation of a reservoir
    Journal of Water Resources Planning and Management, 2015
    Co-Authors: Juan Chen, Ping-an Zhong, Yunfa Zhao
    Abstract:

    AbstractThere are many uncertainties in real-time flood Control Operation of a reservoir, which create risks in flood Control decision making. In this paper, three uncertainty factors—reservoir inflow-forecasting errors, outflow errors, and observation errors of reservoir storage capacity curve—are taken into account and quantified methods are proposed. With consideration of the three uncertainties and correlation between inflow-forecasting errors, reservoir water-level errors are derived using the stochastic differential equation of reservoir flood routing. Then the definition and calculation methods for flood risk at each moment and the integrated risk of the entire flood process are proposed. The Dahuofang reservoir in China is selected as the case study. The results shows that the risk resulting from the uncertainties is decreased by the reservoir flood regulation function and that the proposed method can provide a useful way to estimate the risks in real-time reservoir flood Control.

  • risk analysis for the downstream Control section in the real time flood Control Operation of a reservoir
    Stochastic Environmental Research and Risk Assessment, 2015
    Co-Authors: Juan Chen, Ping-an Zhong, Yunfa Zhao
    Abstract:

    Many uncertainty factors are associated with the joint Operation of a reservoir and its downstream river, which create risks in flood Control decisions. Therefore, this paper proposes an analytical method for the estimation of the uncertainties and their risks in real-time flood Control decisions. Three uncertainty factors, including reservoir discharge errors, forecasting errors of lateral inflows and river food routing errors are proposed and modeled as stochastic processes, and their internal transforming formulas are derived based on the theory of routing before combination. The definition and calculation formulas for the risks of each moment and the integrated risk of the entire flood process at the downstream flood Control section are proposed by an analytical approach based on the combination theory of stochastic processes. The Dahuofang reservoir in northern China is selected as the study case. The results indicate that the risk of the flood peak is higher than that of other moments under the same Controlled flood discharge and that the risk that arises from the uncertainties of the reservoir discharge and lateral inflow is decreased by the river storage function. Compared with the Monte Carlo method, the proposed method is effective and efficient for performing risk analysis of the downstream Control section in the real-time flood Control Operation of a reservoir. The risk analysis results could provide important information regarding flood risks for the operators to implement flood Control arrangements.

Feilin Zhu - One of the best experts on this subject based on the ideXlab platform.

  • Improved Risk-Assessment Model for Real-Time Reservoir Flood-Control Operation
    Journal of Water Resources Planning and Management, 2020
    Co-Authors: Juan Chen, Ping-an Zhong, Feilin Zhu, Weiguo Zhang, Yu Zhang
    Abstract:

    AbstractThis paper puts forward an improved risk assessment model for a real-time reservoir flood Control Operation according to the stochastic differential equation (SDE). The model is composed of...

  • Risk analysis for real-time flood Control Operation of a multi-reservoir system using a dynamic Bayesian network
    Environmental Modelling & Software, 2019
    Co-Authors: Juan Chen, Ping-an Zhong, Feilin Zhu
    Abstract:

    Abstract This paper proposes a model for risk analysis of real-time flood Control Operation of a multi-reservoir system using a dynamic Bayesian network. The proposed model consists of three components: Monte Carlo simulations, dynamic Bayesian network establishing, and risk-informed inference for decision making. The Monte Carlo simulations provide basic data inputs for the dynamic Bayesian network establishing using the historical floods and Operation models of the multi-reservoir system. The dynamic Bayesian network is built with expert knowledge and the relationships among the uncertainties. The component of risk-informed inference for decision making is to provide risk information about the Operation schedules using the trained dynamic Bayesian network. We apply the proposed model to a multi-reservoir system in China. The results show that the proposed method has a capability for bi-directional inferences and can be served as a risk-informed decision-making tool under uncertainties in the real-time flood Control Operation of a multi-reservoir system.

  • Selection of criteria for multi-criteria decision making of reservoir flood Control Operation
    Journal of Hydroinformatics, 2017
    Co-Authors: Feilin Zhu, Ping-an Zhong, Yimeng Sun
    Abstract:

    In reservoir flood Control Operation, selection of criteria is an important part of the multi-criteria decision making (MCDM) procedure. This paper proposes a method to select criteria for MCDM of reservoir flood Control Operation based on the back-propagation (BP) neural network. According to the concept of ideal and anti-ideal points, we propose a method to generate training samples of the BP neural network via stochastic simulation. The topological structure of a three-layer BP neural network used for criteria selection is established. The relative importance of criteria is derived via the learned connection weights of a trained BP neural network, and its calculation method is proposed. The sensitivity curve method is employed to conduct sensitivity analysis, and the relative contribution ratio is defined to quantify the relative sensitivity strength of each criterion. We present the principle and threshold value of criteria selection based on the comprehensive discrimination index defined by the combination of the relative importance and relative contribution ratio. The Pubugou reservoir is selected as the case study. The results show that the proposed method can provide an effective tool for decision makers to select criteria before MCDM modeling of reservoir flood Control Operation.

  • SMAA-based stochastic multi-criteria decision making for reservoir flood Control Operation
    Stochastic Environmental Research and Risk Assessment, 2016
    Co-Authors: Feilin Zhu, Juan Chen, Ping-an Zhong, Wu Yenan, Yimeng Sun, Benyou Jia
    Abstract:

    In reservoir flood Control Operation, candidate alternatives are generally evaluated, ranked and selected through multi-criteria decision making (MCDM) techniques, yet stochastic uncertainties both in the criteria performance values (PVs) and criteria weights (CWs) exist in the MCDM process. This paper extends the traditional MCDM methods to stochastic environments for reservoir flood Control Operation. The criteria PVs and CWs are treated as stochastic variables with certain probability distributions. The stochastic multicriteria acceptability analysis (SMAA) theory is introduced and the differences between conventional MCDM models and the SMAA-2 model are discussed. Methods for quantifying stochastic uncertainties in the criteria PVs are discussed and four kinds of CWs are proposed. Moreover, we define the concept of the risk of decision making errors and propose the corresponding quantitative calculation method. A three-stage MCDM procedure is recommended to guide decision makers to solve MCDM problems under stochastic environments. We apply the proposed methodology to a case study through Monte Carlo simulation to demonstrate its effectiveness and advantage. The results show that the proposed methodology can provide significant risk information for decision makers and improve the reliability of decisions for reservoir flood Control Operation.

Gabriele Leng - One of the best experts on this subject based on the ideXlab platform.

  • pyrethroids used indoor ambient monitoring of pyrethroids following a pest Control Operation
    International Journal of Hygiene and Environmental Health, 2005
    Co-Authors: Gabriele Leng, Edith Bergerpreis, Karsten Levsen, Ulrich Ranft, Dorothee Sugiri, Wolfgang Hadnagy, Helga Idel
    Abstract:

    Abstract House dust and airborne particles (PM) were sampled before (T1) and 1 day (T2), 4–6 months (T3) as well as 10–12 months (T4) after a pest Control Operation (PCO). Cyfluthrin was applied in 11, cypermethrin in 1, deltamethrin in three and permethrin in four interiors. The pyrethroid concentrations in house dust and PM were measured by GC/MS with a detection limit for all pyrethroids of 0.5 mg/kg house dust and of 1 ng/m3 PM for deltamethrin and permethrin and 3 ng/m3 PM for cyfluthrin and cypermethrin. A general background concentration of permethrin (95th percentile: 5.9 mg/kg) and cyfluthrin (95th percentile: 34.9 mg/kg) in house dust was found. In general, an appropriately performed PCO lead to an increase of pyrethroids in house dust as well as in PM, in some cases up to 1 year after application. One day after the application the cyfluthrin concentration increased significantly from 0.25 (T1) to 33.8 mg/kg house dust (T2) and up to 4.9 ng/m3 in PM. The permethrin concentration increased significantly from 4.3 to 70 mg/kg in house dust and up to 18.1 ng/m3 in PM, deltamethrin increased to 54.5 mg/kg and 20.8 ng/m3 and cypermethrin to 14 mg/kg and 45.7 ng/m3. Thereafter a continuous decrease could be observed during the time course of 1 year. After 1 year the permethrin concentration in house dust was still 1/5 of the T2 concentration, whereas for cypermethrin and cyfluthrin only 1/14 and 1/23 of the T2 concentration were found. Deltamethrin was not detected at all after T2. Moreover, the data of this study showed significant, positive correlations between pyrethroids in house dust and in airborne particles especially one day after PCO.

  • pyrethroids used indoors biological monitoring of exposure to pyrethroids following an indoor pest Control Operation
    International Journal of Hygiene and Environmental Health, 2003
    Co-Authors: Gabriele Leng, Edith Bergerpreis, Ulrich Ranft, Dorothee Sugiri, Wolfgang Hadnagy, Helga Idel
    Abstract:

    Abstract A prospective epidemiological study with respect to pyrethroid exposure was carried out combining clinical examination, indoor monitoring and biological monitoring. The results of the biological monitoring are presented. Biological monitoring was performed in 57 persons before (T1) as well as 1 day (T2), 3 days (T3), 4 – 6 months (T4), and 10 – 12 months (T5) following a pest Control Operation (PCO) with pyrethroid containing products such as cyfluthrin, cypermethrin, deltamethrin or permethrin. Pyrethroids in blood were measured by GC-ECD. The respective metabolites cis- and trans-3-(2,2-dichlorovinyl)-2,2-dimethylcyclopropane carboxylic acid (DCCA), cis-3-(2,2-dibromovinyl)-2,2-dimethylcyclopropane carboxylic acid (DBCA), 3-phenoxybenzoic acid (3-PBA) and fluorophenoxybenzoic acid (FPBA) were measured in urine using GC/MS. For all cases the concentrations of pyrethroids in blood were found to be below the detection limit of 5 μg/l before and after the PCO. With a detection limit of 0.2 μg/l of the investigated metabolites, the percentage of positive samples were 7% for cis-DCCA, 3.5% for trans-DCCA and 5.3% for 3-PBA before PCO. One day after PCO (T2) the percentage of positive samples increased remarkably for cis-DCCA (21.5%), trans-DCCA (32.1%) and 3-PBA (25%) showing significantly increased internal doses as compared to pre-existing values. This holds also true for T3, whereas at T4 and T5 the significant increase was no more present. FPBA and DBCA concentrations were below the respective detection limit before PCO and also in most cases after PCO. In 72% of the subjects the route of pyrethroid uptake (measured by determining the DCCA isomeric ratio) was oral/inhalative and in 28% it was dermal. Based on the biological monitoring data it could be shown that appropriately performed pest Control Operations lead to a significant increase of pyrethroid metabolite concentration in the early phase (1 and 3 days) after pyrethroid application as compared to the pre-exposure values. However, evaluated metabolite concentrations 4 – 6 months after PCO did not exceed values of published background levels.