This study evaluated the application of the European flood forecasting operational real time system （EFFORTS） to the Yellow River. An automatic data pre-processing program was developed to provide real-time hydromet...This study evaluated the application of the European flood forecasting operational real time system （EFFORTS） to the Yellow River. An automatic data pre-processing program was developed to provide real-time hydrometeorological data. Various GIS layers were collected and developed to meet the demands of the distributed hydrological model in the EFFORTS. The model parameters were calibrated and validated based on more than ten years of historical hydrometeorological data from the study area. The San-Hua Basin （from the Sanmenxia Reservoir to the Huayuankou Hydrological Station）, the most geographically important area of the Yellow River, was chosen as the study area. The analysis indicates that the EFFORTS enhances the work efficiency, extends the flood forecasting lead time, and attains an acceptable level of forecasting accuracy in the San-Hua Basin, with a mean deterministic coefficient at Huayuankou Station, the basin outlet, of 0.90 in calibration and 0.96 in validation. The analysis also shows that the ;simulation accuracy is better for the southern part than for the northern part of the San-Hua Basin. This implies that, along with the characteristics of the basin and the mechanisms of runoff generation of the hydrological model, the hydrometeorological data play an important role in simulation of hydrological behavior.展开更多
随着水文行业信息化程度的不断提高,对数据的需求逐渐从单一、具体化向多源、综合化方向发展。当前,在水文行业内,对数据按照大类分而治之的管理模式已渐与用户需求脱节,给数据的综合利用带来困难。针对该问题,梳理了现有数据结构与管...随着水文行业信息化程度的不断提高,对数据的需求逐渐从单一、具体化向多源、综合化方向发展。当前,在水文行业内,对数据按照大类分而治之的管理模式已渐与用户需求脱节,给数据的综合利用带来困难。针对该问题,梳理了现有数据结构与管理模式,提出一种水文数据整合与索引模型(Hydrological Data Integration and Index Model, HDIIM),利用该模型在多个水文数据库与水文应用之间搭建水文数据整合层,建立多库统一的一体化水文索引,实现对多库信息的整合与快速查询。该方法有效屏蔽了多个水文数据库之间的异构性,支持跨库的数据检索与应用,从而提高水文数据的获取与使用效率。实验证明,HDIIM能够有效提高水文数据的检索效率,特别是针对批量检索操作,HDIIM的表现较现有方法更加高效和稳定。展开更多
基金supported by the ADB Loan for Flood Management Project in the Yellow River Basin (Grant No. YH-SW-XH-02)
文摘This study evaluated the application of the European flood forecasting operational real time system （EFFORTS） to the Yellow River. An automatic data pre-processing program was developed to provide real-time hydrometeorological data. Various GIS layers were collected and developed to meet the demands of the distributed hydrological model in the EFFORTS. The model parameters were calibrated and validated based on more than ten years of historical hydrometeorological data from the study area. The San-Hua Basin （from the Sanmenxia Reservoir to the Huayuankou Hydrological Station）, the most geographically important area of the Yellow River, was chosen as the study area. The analysis indicates that the EFFORTS enhances the work efficiency, extends the flood forecasting lead time, and attains an acceptable level of forecasting accuracy in the San-Hua Basin, with a mean deterministic coefficient at Huayuankou Station, the basin outlet, of 0.90 in calibration and 0.96 in validation. The analysis also shows that the ;simulation accuracy is better for the southern part than for the northern part of the San-Hua Basin. This implies that, along with the characteristics of the basin and the mechanisms of runoff generation of the hydrological model, the hydrometeorological data play an important role in simulation of hydrological behavior.
文摘随着水文行业信息化程度的不断提高,对数据的需求逐渐从单一、具体化向多源、综合化方向发展。当前,在水文行业内,对数据按照大类分而治之的管理模式已渐与用户需求脱节,给数据的综合利用带来困难。针对该问题,梳理了现有数据结构与管理模式,提出一种水文数据整合与索引模型(Hydrological Data Integration and Index Model, HDIIM),利用该模型在多个水文数据库与水文应用之间搭建水文数据整合层,建立多库统一的一体化水文索引,实现对多库信息的整合与快速查询。该方法有效屏蔽了多个水文数据库之间的异构性,支持跨库的数据检索与应用,从而提高水文数据的获取与使用效率。实验证明,HDIIM能够有效提高水文数据的检索效率,特别是针对批量检索操作,HDIIM的表现较现有方法更加高效和稳定。
