全球气象预报驱动流域水文预报研究进展与展望
Research progresses and prospects of catchment hydrological forecasting driven by global climate forecasts
赵铜铁钢 1张弛 2田雨 3李昱 2陈泽鑫 1陈晓宏1
作者信息
- 1. 中山大学水资源与环境研究中心,广东广州 510275
- 2. 大连理工大学水利工程学院,辽宁大连 116024
- 3. 中国水利水电科学研究院,北京 100038
- 折叠
摘要
全球气象模型及新兴人工智能模型为流域水文预报提供了日、次季节、季节等不同时间尺度的海量气象预报数据.与此同时,基于气象预报开展水文预报,涉及到数据获取、模型构建、评估检验等技术问题.本文以全球气象预报相关的研究计划为切入点,调研现有的1 d至2周小时尺度中短期天气预报、1～60d次季节尺度气象预报、1～12个月季节尺度气象预报以及新兴的人工智能气象预报;梳理气象预报驱动下流域水文预报模型方法,阐述气象预报订正、水文模型设置和预报评估检验等技术环节.基于全球气象预报生成实时和回顾性流域水文预报,定量检验不同预见期下预报精度以评估相关模型方法的预报性能,为水利工程预报-调度实践应用打下坚实的基础.
Abstract
Global climate models and emerging artificial intelligence models generate big climate forecasts data for catchment hydrological forecasting at daily,sub-seasonal and seasonal timescales.The utilization of global climate forecasts to drive catchment hydrological models are confronted with the technical issues of climate forecast data retrieval,hydrological forecasting model set-up and verification of hydro-climatic forecasts.Starting with international collaborative research projects on global climate forecasting,this paper conducts a survey of short-term weather forecasts for the next 1 day to 2 weeks,sub-seasonal climate forecasts for the next 1 to 60 days,seasonal climate forecasts for the next 1 to 12 months and artificial intelligence-based climate forecasts.Furthermore,the processes of catchment hydrological forecasting driven by global climate forecasts are illustrated by detailing the technical aspects on the calibration of climate forecasts,the setting-up of hydrological models and the verification of predictive performance.By generating real-time and retrospective catchment hydrological forecasts from global climate forecasts,the efficacy of forecasting models can be quantitatively examined by verifying forecast skill at different lead times,laying a solid basis for practical forecasts-based operations of hydraulic infrastructure.
关键词
全球气象模型/气象预报/流域水文模型/水文预报/实时预报/回顾性预报/预报检验Key words
global climate model/climate forecasts/catchment hydrological model/hydrological forecasts/real-time forecasts/retrospective forecasts/forecast verification引用本文复制引用
基金项目
国家重点研发计划资助项目(2023YFF0804900)
国家自然科学基金资助项目(52379033)
出版年
2024
国家科技期刊平台
NSTL
万方数据