圖書典藏及影音數位平台

本署與中央氣象局合作發展多重觀測工具之定量降水估計與分類技術(QPESUMS)，可有效利用雷達、衛星及雨量計等觀測資料，推測定量降雨數值預報及其空間分布趨勢，為有效加值應用該相關資料，爰辦理本計畫。

The Water Resources Agency (WRA) and Central Weather Bureau (CWB) have a long-term collaboration on the Quantitative Precipitation Estimation and Segregation Using Multiple Sensor (QPESUMS). Currently, the QPESUMS precipitation data was the main rainfall data source in WRA. In traditional hydrologic analysis uses rainfall gauge data to calculate the catchment rainfall. However, the process of rainfall spatial-temporal distribution was affected by a different kind of the interpolation algorithm, resulting in the rainfall distribution are not consistent. This project tries to use QPESUMS precipitationd in the hydrological analysis process. In order to provide better spatial-temporal distribution pattern in the basin. This year, we continued to expand the results of rivers, and thorough study of radar rainfall data, the impact of hydrological system flow simulation. Established with the set streamflow simulation process, and the automatic Computing architecture. It will help to assist the data of the existing flowmeter to effectively supplement the flow situation and trends in the catchment area. Next, we continue to expand the hydrological analysis results in Lanyang River, Beigang River, Yanshui River, and Agongdian River and complete the new station monitoring mechanism in the non-rain gauge catchment area, and conduct flow case tests in the watersheds. In addition, the completion of radar rainfall is applied to the hydrological system flow simulation process and structure, and the flow simulation test is completed in Shihmen Reservoir and Zengwun Reservoir. Finally, using Wflow open source the distributed rainfall runoff model, with the work to open source hydrology model to import operational hydrological analysis workflows. This project will keep the FEWS_Taiwan to update and reference the international standards. And the hydrological model could run 24 hours per day, seven days each week in WRA. And sustainable development using radar rainfall data in the hydrological analysis and increase the data quality.