Addressing disasters in smart cities through UAVs path planning and 5G communications: A systematic review

Multi-objective metaheuristics for discrete optimization problems: A review of the state-of-the-art

Future changes in Yuan River ecohydrology: Individual and cumulative impacts of climates change and cascade hydropower development on runoff and aquatic habitat quality.

Optimizing the sizes of wind and photovoltaic power plants integrated into a hydropower station based on power output complementarity

The effect of rain gauge density and distribution on runoff simulation using a lumped hydrological modelling approach

A multi-objective differential evolution-chaos shuffled frog leaping algorithm (MODE-CSFLA) is proposed for water resources system optimization to overcome the shortcomings of easily falling into local minima and premature convergence in SFLA. The performance of MODE-CSFLA in solving benchmark problems is compared with that of non-dominated sorting genetic algorithm II (NSGA-II) and multi-objective particle swarm optimization (MOPSO). At last, the proposed MODE-CSFLA is used to optimize the water resources allocation plan of the East Route of the South-to-North Water Transfer Project in the normal, dry, and extremely dry years. The results reveal that MODE-CSFLA performs better than NSGA-II and MOPSO under all conditions. Compared with shuffled frog leaping algorithm (SFLA), MODE-CSFLA can result in a 29.39, 27.47 and 22.55% increase in water supply when the single objective is to minimize the water pumpage; and a 41.01, 39.63 and 30.94% decrease in total pumpage when the single objective is to maximize the water supply in the normal, dry, and extremely dry conditions, respectively. Thus, MODE-CSFLA has the potential to be used for solving complex optimization problems of water resources systems.

Multi-Objective Differential Evolution-Chaos Shuffled Frog Leaping Algorithm for Water Resources System Optimization

Adapting the operation of cascaded reservoirs on Yuan River for fish habitat conservation

Urban agglomeration polders type of flood control pattern (UAPFCP) is an extensively used pattern for urban flood control in plain water system areas. Urbanization and polders are two main factors that affect the runoff process in these regions. The Qinhuai River basin, one of the representative watersheds of this flood control pattern in East China, was selected to perform the study. Five urbanization scenarios (the historical, current, and three assumed future urbanization scenarios) of the basin were defined in this paper. The Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) was used to simulate basin runoff. The results indicate that the UAPFCP increased the flood volume (Qv) and peak flow (Qp) compared to the results under the condition without polders. With the constant improvement of the urbanization level of the basin, Qv and Qp under the with polder condition increased correspondingly, and the potential changes show a linear relationship. The urbanization and urban agglomeration polders have interactions with flood events. The effect of urbanization on the flood process is weakened because of the existence of urban agglomeration polders. With the constant improvement of the urbanization level, the effect on the flood process caused by urban agglomeration polders becomes gradually weaker.

Assessing the Effects of Urbanization on Flood Events with Urban Agglomeration Polders Type of Flood Control Pattern Using the HEC-HMS Model in the Qinhuai River Basin, China

The ongoing cascading hydropower exploitation in southwestern China has been the subject of debate and conflict in recent years. This study aims to assess the climate change impacts on the hydropower system of Yuan River and to quantify the future potential in operation optimization of Gasa-Madushan (GS-MDS) Reservoir system. The Community Climate System Model version 4 (CCSM4) projections are bias-corrected and downscaled to drive the Soil Water Assessment Tool hydrological model, aiming to predict the climate and runoff changes for the future. Then, an adaptive operation chart model of cascaded reservoirs is established to balance hydropower generation and ecological requirements under climate change. In the future, the decadal average temperature and annual average precipitation will possibly increase by 0.80–2.22 °C and 2.56–4.65%, respectively; the monthly average runoff may increase by 6.89%, 6.17%, and 18.26% for GS Reservoir Basin, and by 8.89%, 8.14%, and 23.14% for MDS Reservoir Basin under Representative Concentration Pathways 2.6, 4.5, and 8.5, respectively. The adaptive operation chart results in a reduction of 52.66–70.77% in the total water shortage at a cost of 2.09–4.54% decrease in total power generation of the GS-MDS cascaded hydropower system compared to that of non-adaptive operation chart.

/pdf/hydrological-responses-and-adaptive-potential-of-cascaded-1tg1kue9fx.pdf

Hydrological responses and adaptive potential of cascaded reservoirs under climate change in Yuan River Basin

Various regression models are currently applied to derive functional forms of operating rules for hydropower reservoirs. It is necessary to analyze and evaluate the model selecting uncertainty involved in reservoir operating rules for efficient hydropower generation. Moreover, selecting the optimal input variables from a large number of candidates to characterize an output variable can lead to a more accurate operation simulation. Therefore, this paper combined the Grey Relational Analysis (GRA) method and the Bayesian Model Averaging (BMA) method to select input variables and derive the monthly optimal operating rules for a hydropower reservoir. The monthly input variables were first filtered according to the relationship between the preselected output and input variables based on the reservoir optimal deterministic trajectory using GRA. Three models, Particle Swarm Optimization-Least Squares Support Vector Machine (PSO-LSSVM), Adaptive Neural Fuzzy Inference System (ANFIS), and Multiple Linear Regression Analysis (MLRA) model, were further implemented to derive individual monthly operating rules. BMA was applied to determine the final monthly operating rules by analyzing the uncertainty of selecting individual models with different weights. A case study of Xinanjiang Reservoir in China shows that the combination of the two methods can achieve high-efficiency hydropower generation and optimal utilization of water resources.

Yuxue Guo

Papers

Multi-Objective Differential Evolution-Chaos Shuffled Frog Leaping Algorithm for Water Resources System Optimization

Adapting the operation of cascaded reservoirs on Yuan River for fish habitat conservation

Assessing the Effects of Urbanization on Flood Events with Urban Agglomeration Polders Type of Flood Control Pattern Using the HEC-HMS Model in the Qinhuai River Basin, China

Hydrological responses and adaptive potential of cascaded reservoirs under climate change in Yuan River Basin

Combining Grey Relational Analysis and a Bayesian Model Averaging Method to Derive Monthly Optimal Operating Rules for a Hydropower Reservoir