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作 者:李巧玲[1] 刘兴文 李致家[1] 黎洪德 LI Qiaoling;LIU Xingwen;LI Zhijia;LI Hongde(College of Hydrology and Water Resources,Hohai University,Nanjing 210098,China)
机构地区:[1]河海大学水文水资源学院,江苏南京210098
出 处:《水科学进展》2024年第5期773-783,共11页Advances in Water Science
基 金:国家自然科学基金资助项目(52079035)。
摘 要:准确获取流域土壤湿度(MS)的初始值及过程状态,对提高实时洪水预报精度具有重要意义和实用价值。从新安江模型参数的物理意义出发,基于站点墒情数据和CLDAS土壤湿度数据构建点面转换模型(WKNN),将点面转换后的实时面尺度MS作为观测数据,采用集合卡尔曼滤波法同化新安江模型预报的MS过程,在五强溪区间流域进行实时洪水预报应用。结果表明:WKNN作为点面转换工具,能够捕捉到不同土层MS的点面关系,具有较好的适用性;较不同化模式,多层MS同化后的平均径流深相对误差下降了12.67%,平均确定性系数提高了41.82%;MS的实时同化可以显著降低汛初期洪水的预报误差,提高洪水预报精度,且多层同化较单一层同化效果更优。Accurate acquisition of the initial soil moisture(MS)values and states within a basin is essential for enhancing real-time flood forecasting accuracy.Based on the physical parameters of the Xinʹanjiang model,a point-sub-basin conversion model(WKNN)was developed.This model facilitates the transition of real-time MS data from point to sub-basin scale,utilizing both point MS measurements and CLDAS MS data.The resulting sub-basin scale data served as observed data for assimilating the MS process forecasted by the Xinʹanjiang model using the ensemble Kalman filtering method,enabling real-time flood forecasting in the middle area of the Wuqiangxi basin.Application results demonstrate that the WKNN effectively captures MS relationships across different soil layers and scales,from point to sub-basin,exhibiting robust applicability as a scale conversion tool.Implementation of a multi-layer assimilation scheme resulted in a 12.67%decrease in average runoff error and a 41.82%increase in average deterministic coefficient.Real-time assimilation of MS efficiently reduced forecast errors in model state variables,consequently improving flood forecast accuracy.Notably,substantial reductions in relative runoff errors were observed during flood events at the onset of the flood season,with the multi-layer assimilation scheme outperforming its single-layer counterpart.
关 键 词:土壤湿度 多源数据 概念性水文模型 多层同化 实时洪水预报
分 类 号:P933[天文地球—自然地理学]
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