An open online simulation strategy for hydrological ensemble forecasting

被引:0
|
作者
He, Yuanqing [1 ,2 ,3 ]
Chen, Min [1 ,2 ,3 ,6 ]
Wen, Yongning [1 ,2 ,3 ]
Duan, Qingyun [4 ]
Yue, Songshan [1 ,2 ,3 ]
Zhang, Jiapeng [4 ]
Li, Wentao [4 ]
Sun, Ruochen [4 ]
Zhang, Zizhuo [1 ,2 ,3 ]
Tao, Ruoyu [1 ,2 ,3 ]
Tang, Wei [5 ]
Lue, Guonian [1 ,2 ,3 ]
机构
[1] Nanjing Normal Univ, Minist Educ PR China, Key Lab Virtual Geog Environm, Nanjing 210023, Peoples R China
[2] Jiangsu Ctr Collaborat Innovat Geog Informat Resou, Nanjing 210023, Peoples R China
[3] State Key Lab Cultivat Base Geog Environm Evolut, Nanjing 210023, Peoples R China
[4] Hohai Univ, Coll Hydrol & Water Resources, Nanjing 210098, Peoples R China
[5] China Meteorol Adm, Publ Meteorol Serv Ctr, Beijing 100081, Peoples R China
[6] Nanjing Normal Univ, Sch Geog, 1 Wenyuan Rd, Nanjing 210023, Peoples R China
关键词
Flood forecasting; Hydrological ensemble forecasting; Environmental simulation; Model sharing and integration; OpenGMS; ANALYSIS MODELS; DESIGN; ENVIRONMENT;
D O I
10.1016/j.envsoft.2024.105975
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Hydrological ensemble forecasting is crucial for flood forecasting. However, the centralized architecture of hydrological ensemble forecasting systems requires time- and labour-intensive downloads and the installation of executable models and methods. This usage pattern impedes the reusability of forecasting models and techniques. To address these limitations, we propose an open online simulation strategy with three components: model sharing and integration, data sharing and adaptation, and parameter optimization and recommendation. The model sharing and integration method helps researchers publish forecasting models as web services for online simulation and integration. A reusable data sharing and adaptation method is established for managing and processing data to meet model requirements. In addition, the optimization and recommendation methods are intended to assist researchers in optimizing and recommending model parameters online based on the characteristics of different research regions. Finally, a prototype system and case study are constructed to verify the strategy's feasibility and capability.
引用
收藏
页数:18
相关论文
共 50 条
  • [1] Application of quantitative precipitation forecasting and precipitation ensemble prediction for hydrological forecasting
    Peng Tao
    Shen Tie-Yuan
    Yin Zhi-Yuan
    Wang Jun-Chao
    REMOTE SENSING AND GIS FOR HYDROLOGY AND WATER RESOURCES, 2015, 368 : 96 - 101
  • [2] Online Ensemble Learning for Load Forecasting
    Von Krannichfeldt, Leandro
    Wang, Yi
    Hug, Gabriela
    IEEE TRANSACTIONS ON POWER SYSTEMS, 2021, 36 (01) : 545 - 548
  • [3] Accounting for three sources of uncertainty in ensemble hydrological forecasting
    Thiboult, Antoine
    Anctil, Francois
    Boucher, Marie-Amelie
    HYDROLOGY AND EARTH SYSTEM SCIENCES, 2016, 20 (05) : 1809 - 1825
  • [4] Comparison of hydrological model ensemble forecasting based on multiple members and ensemble methods
    Wang, Jie
    Wang, Guoqing
    Elmahdi, Amgad
    Bao, Zhenxin
    Yang, Qinli
    Shu, Zhangkang
    Song, Mingming
    OPEN GEOSCIENCES, 2021, 13 (01) : 401 - 415
  • [5] Landslide forecasting based on hydrological process simulation for a dump slope in an open mining pit
    Guo Jin-xing
    Graeber, Peter-Wolfgang
    JOURNAL OF GROUNDWATER SCIENCE AND ENGINEERING, 2018, 6 (02): : 92 - 103
  • [6] Assessment of a multimodel ensemble against an operational hydrological forecasting system
    Thiboult, A.
    Anctil, F.
    CANADIAN WATER RESOURCES JOURNAL, 2015, 40 (03) : 272 - 284
  • [7] Hydrological ensemble forecasting using a multi-model framework
    Dion, Patrice
    Martel, Jean-Luc
    Arsenault, Richard
    JOURNAL OF HYDROLOGY, 2021, 600 (600)
  • [8] An Adaptive Forecasting Strategy with Hybrid Ensemble Models
    Wichard, Joerg D.
    2016 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2016, : 1495 - 1498
  • [9] A novel ensemble method for residential electricity demand forecasting based on a novel sample simulation strategy
    Zhang, Guoqiang
    Guo, Jifeng
    ENERGY, 2020, 207 (207)
  • [10] Sequential streamflow assimilation for short-term hydrological ensemble forecasting
    Abaza, Mabrouk
    Anctil, Francois
    Fortin, Vincent
    Turcotte, Richard
    JOURNAL OF HYDROLOGY, 2014, 519 : 2692 - 2706