On the use of multi-objective optimization for multi-site calibration of extensive green roofs

被引:5
|
作者
Abdalla, Elhadi Mohsen Hassan [1 ]
Alfredsen, Knut [1 ]
Muthanna, Tone Merete [1 ]
机构
[1] Norwegian Univ Sci & Technol, Dept Civil & Environm Engn, Andersens Vei 5, N-7031 Trondelag, Norway
关键词
Green roof; Pareto front; Multi site calibration; Multi objective Bayesian optimization; RAINFALL-RUNOFF MODEL; AUTOMATIC CALIBRATION; PERFORMANCE CRITERIA; GLOBAL OPTIMIZATION; HYDROLOGICAL MODEL; ALGORITHM; TRANSFERABILITY; PARAMETERS;
D O I
10.1016/j.jenvman.2022.116716
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Conceptual hydrological models are practical tools for estimating the performance of green roofs. Such models require calibration to obtain parameter values, which limits their use when measured data are not available. One approach that has been thought to be useful is to transfer parameters from a gauged roof calibrated locally (single-site calibration) to a similar ungauged roof in a different location. This study tested this approach by transferring calibrated parameters of a conceptual hydrological model between sixteen extensive green roofs located in four Norwegian cities. The approach was compared with a multi-site calibration scheme that explores trade-offs of model performances between the sites. The results showed that single site calibration could yield optimal parameters for one site and perform poorly in other sites. In contrast, obtaining a common parameter set that yields satisfactory results (Kling Gupta Efficiency >0.5) for different sites, and roof properties could be achieved by multi-site calibration.
引用
收藏
页数:12
相关论文
共 50 条
  • [41] Hyper multi-objective evolutionary algorithm for multi-objective optimization problems
    Weian Guo
    Ming Chen
    Lei Wang
    Qidi Wu
    Soft Computing, 2017, 21 : 5883 - 5891
  • [42] Guide to multi-objective optimization for the green vehicle routing problem
    Ferreira, Julio Cesar
    Arns Steiner, Maria Teresinha
    Canciglieri Junior, Osiris
    REVISTA INTERNACIONAL DE METODOS NUMERICOS PARA CALCULO Y DISENO EN INGENIERIA, 2020, 36 (01):
  • [43] A multi-objective memetic optimization approach for green transportation scheduling
    Guo, Zhaoxia
    Liu, Lingyuan
    Yang, Jing
    2015 INTERNATIONAL CONFERENCE ON INTELLIGENT INFORMATICS AND BIOMEDICAL SCIENCES (ICIIBMS), 2015, : 141 - 147
  • [44] Multi-objective optimization model for a green vehicle routing problem
    Jabir, E.
    Panicker, Vinay V.
    Sridharan, R.
    OPERATIONS MANAGEMENT IN DIGITAL ECONOMY, 2015, 189 : 33 - 39
  • [45] Green maritime: a routing and speed multi-objective optimization strategy
    Ma, Weihao
    Ma, Dongfang
    Ma, Yijia
    Zhang, Jinfeng
    Wang, Dianhai
    JOURNAL OF CLEANER PRODUCTION, 2021, 305
  • [46] How to Use the Metropolis Algorithm for Multi-Objective Optimization?
    Zheng, Weijie
    Li, Mingfeng
    Deng, Renzhong
    Doerr, Benjamin
    THIRTY-EIGHTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 38 NO 18, 2024, : 20883 - 20891
  • [47] Automated multi-objective optimization system for airport site layouts
    Khalafallah, Ahmed
    El-Rayes, Khaled
    AUTOMATION IN CONSTRUCTION, 2011, 20 (04) : 313 - 320
  • [48] Recognition of gene acceptor site based on multi-objective optimization
    Zhao, J
    Zhu, YM
    Song, PM
    Fang, Q
    Luo, JH
    ACTA BIOCHIMICA ET BIOPHYSICA SINICA, 2005, 37 (07) : 435 - 439
  • [49] A Hybrid Framework for Multi-Objective Construction Site Layout Optimization
    Borges, Maria Luiza Abath Escorel
    Granja, Ariovaldo Denis
    Monteiro, Ari
    Buildings, 2024, 14 (12)
  • [50] Participatory multi-objective optimization for planning dense and green cities
    Wicki, Sergio
    Schwaab, Jonas
    Perhac, Jan
    Gret-Regamey, Adrienne
    JOURNAL OF ENVIRONMENTAL PLANNING AND MANAGEMENT, 2021, 64 (14) : 2532 - 2551