Qijia Zhao
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Qijia Zhao has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Tiantian Su
Zhengzhou University
1 shared publication - Wenjie Zhao
Sichuan Province Zipingpu Development Co., Ltd., Chengdu 610091, China
1 shared publication - Xingping Wang
Sichuan Province Zipingpu Development Co., Ltd., Chengdu 610091, China
1 shared publication - Yang Zhao
College of Geosciences and Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
1 shared publication - Yuan Guo
School of Water Conservancy Engineering, Zhengzhou University, Zhengzhou 450001, China
1 shared publication
Latest Publications
- Open Access
Simulating Rainfall for Flood Forecasting in the Upper Minjiang River
The accuracy and timeliness of precipitation inputs have significant impact on flood forecasting. Upstream Minjiang River Basin is characterized by complex terrain and highly variable climatic conditions, posing a significant challenge for runoff forecasting. This study proposes a combined forecasting approach integrating numerical weather prediction (NWP) models with hydrodynamic models to enhance flood process simulation. The most appropriate initial field data for the Weather Research and Forecasting Model (WRF) exist in time and space resolution. Compared with the measured series, the characteristics of precipitation forecasting are summarized from practical and scientific perspectives. InfoWorks ICM is then used to implement runoff generation calculations and flooding processes. The results indicate that the WRF model effectively simulates the spatial distribution and peak timing of precipitation in the upper Minjiang River. The model systematically underestimates both peak rainfall intensity and cumulative precipitation compared to observations. Initial field data with 0.25° spatial resolution and 3 h temporal intervals demonstrate good performance and the 10–14 h forecast period exhibits superior predictive capability in numerical simulations. Updates to elevation and land use conditions yield increased cumulative rainfall estimates, though simulated peaks remain lower than measured values. The runoff results could indicate peak flow but rely on the precipitation inputs.
Open AccessSimulating Rainfall for Flood Forecasting in the Upper Minjiang River
The accuracy and timeliness of precipitation inputs have significant impact on flood forecasting. Upstream Minjiang River Basin is characterized by complex terrain and highly variable climatic conditions, posing a significant challenge for runoff forecasting. This study proposes a combined forecasting approach integrating numerical weather prediction (NWP) models with hydrodynamic models to enhance flood process simulation. The most appropriate initial field data for the Weather Research and Forecasting Model (WRF) exist in time and space resolution. Compared with the measured series, the characteristics of precipitation forecasting are summarized from practical and scientific perspectives. InfoWorks ICM is then used to implement runoff generation calculations and flooding processes. The results indicate that the WRF model effectively simulates the spatial distribution and peak timing of precipitation in the upper Minjiang River. The model systematically underestimates both peak rainfall intensity and cumulative precipitation compared to observations. Initial field data with 0.25° spatial resolution and 3 h temporal intervals demonstrate good performance and the 10–14 h forecast period exhibits superior predictive capability in numerical simulations. Updates to elevation and land use conditions yield increased cumulative rainfall estimates, though simulated peaks remain lower than measured values. The runoff results could indicate peak flow but rely on the precipitation inputs.