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Streamflow prediction in ungauged basins by regressive regionalization: a case study in Huai River Basin, China

机译:基于回归区域化的非赋富盆地流量预测-以淮河流域为例

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摘要

Streamflow information is of great significance for flood control, water resources utilization and management, ecological services, etc. Continuous streamflow prediction in ungauged basins remains a challenge, mainly due to data paucity and environmental changes. This study focuses on the modification of a nonlinear hydrological system approach known as the time variant gain model and the development of a regressive method based on the modified approach. This method directly correlates rainfall to runoff through physically based mathematical transformations without requiring additional information of evaporation or soil moisture. Also, it contains parsimonious parameters that can be derived from watershed properties. Both characteristics make this method suitable for practical uses in ungauged basins. The Huai River Basin of China was selected as the study area to test the regressive method. The results show that the proposed methodology provides an effective way to predict streamflow of ungauged basins with reasonable accuracy by incorporating regional watershed information (soil, land use, topography, etc.). This study provides a useful predictive tool for future water resources utilization and management for data-sparse areas or watersheds with environmental changes.
机译:径流信息对于防洪,水资源利用与管理,生态服务等具有重要意义。无数据流域的连续径流预测仍然是一个挑战,主要是由于缺乏数据和环境变化所致。这项研究的重点是对称为时变增益模型的非线性水文系统方法的修改,以及基于该修改方法的回归方法的开发。该方法通过基于物理的数学转换将降雨与径流直接相关,而无需额外的蒸发或土壤水分信息。此外,它还包含可从分水岭特性中得出的简约参数。两种特性都使该方法适用于非流域盆地的实际应用。选择中国淮河流域作为研究区域以测试回归方法。结果表明,通过结合区域分水岭信息(土壤,土地利用,地形等),所提出的方法提供了一种有效的方法来以合理的准确度预测未灌流盆地的径流。这项研究为数据稀疏的地区或流域随环境变化的未来水资源利用和管理提供了有用的预测工具。

著录项

  • 来源
    《Nordic hydrology》 |2016年第5期|1053-1068|共16页
  • 作者单位

    School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ 85287, USA,State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China;

    State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China,Hubei Collaborative Innovation Center for Water Resources Security, Wuhan University, Wuhan 430072, China;

    State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China,Hubei Collaborative Innovation Center for Water Resources Security, Wuhan University, Wuhan 430072, China;

    School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ 85287, USA;

    State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China,Hubei Collaborative Innovation Center for Water Resources Security, Wuhan University, Wuhan 430072, China;

    State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China,Hubei Collaborative Innovation Center for Water Resources Security, Wuhan University, Wuhan 430072, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Huai River Basin; regressive regionalization; streamflow prediction; ungauged basins;

    机译:淮河流域;回归区域化;流量预测;裸露的盆地;
  • 入库时间 2022-08-18 03:34:17

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