scholarly journals A stepwise surrogate model for parameter calibration of the Variable Infiltration Capacity model: the case of the upper Brahmaputra, Tibet Plateau

2020 ◽  
Author(s):  
Haiting Gu ◽  
Li Liu ◽  
Zhixu Bai ◽  
Suli Pan ◽  
Yue-Ping Xu
Keyword(s):  
Surrogate Model ◽  
Tibet Plateau ◽  
Optimal Solutions ◽  
Objective Functions ◽  
Variable Infiltration Capacity ◽  
Parameter Calibration ◽  
Infiltration Capacity ◽  
Nsga Ii ◽  
Capacity Model ◽  
Simulation Step

Abstract To alleviate the computational burden of parameter calibration of the Variable Infiltration Capacity (VIC) model, a stepwise surrogate model (SM) is developed based on AdaBoost. An SM first picks out the parameter sets in the range that the values of objective functions are close to the optimization objectives and then approximates the values of objective functions with these parameter sets. The ɛ-NSGA II (Nondominated Sorting Genetic Algorithm II) algorithm is used to search the optimal solutions of SM. The SM is tested with a case study in the upper Brahmaputra River basin, Tibet Plateau, China. The results show that the stepwise SM performed well with the rate of misclassification less than 2.56% in the global simulation step and the root mean square error less than 0.0056 in the local simulation step. With no large difference in the optimal solutions between VIC and the SM, the SM-based algorithm saves up to 90% time.

A two-stage surrogate model based on ANN and AdaBoost for multi-objective parameter optimization of the Variable Infiltration Capacity model

2020 ◽  
Author(s):  
Yue-Ping Xu ◽  
Haiting Gu ◽  
Ma Di
Keyword(s):  
River Basin ◽  
Surrogate Model ◽  
Stage Model ◽  
Variable Infiltration Capacity ◽  
Infiltration Capacity ◽  
Two Stage ◽  
Nsga Ii ◽  
Xiangjiang River ◽  
Vic Model ◽  
Multi Objective

<p>Distributed hydrologic models have been widely used for its functional diversity and rationality in theory. However, calibration of distributed models is computationally expensive with a large number of model runs, even if an efficient multi-objective algorithm is employed. To alleviate the burden of computation, we develop a two-stage surrogate model by coupling backpropagation neural network with AdaBoost to calibrate the parameters of the Variable Infiltration Capacity (VIC) model. The first stage model selects the parameter sets with simulated outputs in the crucial range and the second stage model estimates the values of outputs accurately with the parameter sets picked out by the first stage model. The developed surrogate model is tested in three different river basins in China, namely the Lanjiang River basin (LJR), the Xiangjiang River basin (XJR) and the Upper Brahmaputra River basin (UBR). With sufficient samples generated by ε-NSGA II, the surrogate model performs very well with a low error rate of classification (ER) and root mean square error (RMSE). The streamflow simulated with the surrogate model is nearly the same as that from the original VIC model, indicating that the surrogate model does gain a remarkable speedup compared with the original VIC model.</p>

Multi Objective Design Optimization of Two Bar Truss Using NSGA II and TOPSIS

2014 ◽  
Vol 984-985 ◽  
pp. 419-424
Author(s):  
P. Sabarinath ◽  
M.R. Thansekhar ◽  
R. Saravanan
Keyword(s):  
Design Optimization ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Optimal Solutions ◽  
Objective Functions ◽  
Nsga Ii ◽  
Multi Objective ◽  
Total Displacement ◽  
Design Variables ◽  
Conflicting Objectives

Arriving optimal solutions is one of the important tasks in engineering design. Many real-world design optimization problems involve multiple conflicting objectives. The design variables are of continuous or discrete in nature. In general, for solving Multi Objective Optimization methods weight method is preferred. In this method, all the objective functions are converted into a single objective function by assigning suitable weights to each objective functions. The main drawback lies in the selection of proper weights. Recently, evolutionary algorithms are used to find the nondominated optimal solutions called as Pareto optimal front in a single run. In recent years, Non-dominated Sorting Genetic Algorithm II (NSGA-II) finds increasing applications in solving multi objective problems comprising of conflicting objectives because of low computational requirements, elitism and parameter-less sharing approach. In this work, we propose a methodology which integrates NSGA-II and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for solving a two bar truss problem. NSGA-II searches for the Pareto set where two bar truss is evaluated in terms of minimizing the weight of the truss and minimizing the total displacement of the joint under the given load. Subsequently, TOPSIS selects the best compromise solution.

scholarly journals Application of Variable Infiltration Capacity Model (Vic) for Calculatingdrought Iindicators for Binh Thuan Province

2018 ◽  
Vol 34 (1S) ◽  
Author(s):  
Nguyen Quang Hung ◽  
Le Duc Khanh
Keyword(s):  
Water Exchange ◽  
Water Resources Planning ◽  
Variable Infiltration Capacity ◽  
Drought Forecasting ◽  
Infiltration Capacity ◽  
Vic Model ◽  
Variable Infiltration Capacity Model ◽  
Capacity Model ◽  
Exchange Processes ◽  
Resources Planning

Abstract: Drought is a complex natural hazard;so far, there have been some different ways to assess the level of drought in different aspects. In this study, the Variable Infiltration Capacity Model (VIC) was used to calculate the relative humidity changes of soil in Binh Thuan province based on surface water exchange processes. The simulation results of the VIC model are then used to calculate drought indicators to assess the drought situation in Binh Thuan province. The results of the study show that drought occurrences of the study basin are high, complicated, clearly showing the effect of rainfall, temperature and vegetation cover to water exchange, soil moisture. The results of the study serve as a basis for the development of drought forecasting tools for agricultural production planning and water resources planning and planning.   Keyword: Drought, VIC model, relative soil humidity, Bình Thuận

Modelling the dynamics of evapotranspiration using Variable Infiltration Capacity model and regionally calibrated Hargreaves approach

2018 ◽  
Vol 36 (4-5) ◽  
pp. 289-300 ◽  
Author(s):  
Ankur Srivastava ◽  
Bhabagrahi Sahoo ◽  
Narendra Singh Raghuwanshi ◽  
Chandranath Chatterjee
Keyword(s):  
Variable Infiltration Capacity ◽  
Infiltration Capacity ◽  
Variable Infiltration Capacity Model ◽  
Capacity Model
Sign in / Sign up

Export Citation Format

Share Document