曹孟,刘艳丽,陈鑫,等. 基于星地融合降水的中小流域洪水模拟[J]. 水利水运工程学报,2023(3):47-56. doi: 10.12170/20220624001
引用本文: 曹孟,刘艳丽,陈鑫,等. 基于星地融合降水的中小流域洪水模拟[J]. 水利水运工程学报,2023(3):47-56. doi: 10.12170/20220624001
(CAO Meng, LIU Yanli, CHEN Xin, et al. Merging satellite and gauge precipitation for flood forecasting in a small and medium-sized watershed[J]. Hydro-Science and Engineering, 2023(3): 47-56. (in Chinese)). doi: 10.12170/20220624001
Citation: (CAO Meng, LIU Yanli, CHEN Xin, et al. Merging satellite and gauge precipitation for flood forecasting in a small and medium-sized watershed[J]. Hydro-Science and Engineering, 2023(3): 47-56. (in Chinese)). doi: 10.12170/20220624001

基于星地融合降水的中小流域洪水模拟

Merging satellite and gauge precipitation for flood forecasting in a small and medium-sized watershed

  • 摘要: 我国气象站点分布不均,导致众多中小流域的降水资料不足,给中小流域的洪水模拟带来一定困难。融合星地降水是提高降水时空分辨率和精度的有效方法,但在中小流域洪水模拟中的适应性需进一步研究。以屯溪流域为例,采用BP神经网络模型,分别将实测降水与GPM时代两种近实时卫星降水产品IMERG_Early及GSMaP_NRT融合,并探讨融合降水在场次洪水模拟中的适用性。通过减少流域内降水站点数量,探讨在缺乏资料地区星地融合降水的应用潜力。结果表明:在不同数量实测站点条件下,融合降水模拟场次洪水的结果均可靠,确定性系数可达0.8,洪峰相对误差合格率在70%以上,峰现时间误差合格率达90%;当站点信息较少时,融合降水相较于实测降水的确定性系数及洪峰相对误差合格率更高。基于千河流域的模拟结果表明,融合了4个站点信息的融合降水的模拟结果与基于12个实测站点的模拟结果一致。融合降水能为中小流域,特别是缺乏降水资料的中小流域,提供可靠的降水数据支撑。

     

    Abstract: The distribution of meteorological stations in China is sparse and uneven, which can bring some difficulties for flood simulation of many small and medium-sized watersheds, where station-based precipitation information is usually insufficient. Merging satellite and ground-measured datasets is an effective method to obtain high spatiotemporal precipitation datasets, but the adaptability of the merged precipitation in flood simulation needs further studies. In this paper, Tunxi Basin is taken as an example to evaluate the capacity of these merged precipitations in flood simulation. Two important near-real-time satellite precipitation products in GPM era, IMERG_Early and GSMaP_NRT, are applied in this study. BP neural network model is adopted to merge them with ground measurements separately and then the two merged precipitation datasets are employed into Xin’anjiang model for flood simulation. Furthermore, in order to represent potential application of merged precipitation in the poor-gauged catchment, the number of meteorological stations in this area is reduced gradually to explore whether merged precipitation is still appliable when fusing only a little measured information. The results show that the merged precipitation is reliable no matter how much the in-situ information is available. Specifically, the averaged DC was above 0.8 and the qualification rate of Qm and ΔH was larger than 70% and 90%, respectively. When there are limited meteorological stations within the watershed, the merged precipitation can provide more reliable simulation results compared with gauged observations. Moreover, the simulation results in Qianyang basin show that merged precipitation based on 4 stations could present as reliable performance as 12 meteorological stations did in forecasting flood events. Therefore, merging satellite precipitation and station-based information can provide reliable precipitation datasets for flood forecasting, especially for small and medium-sized watersheds with limited in-situ information.

     

/

返回文章
返回