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洪水监测和预测方法的最新进展:系统审查
Adrita Talapatra1,2, Narendra Kumar Rana3
1Department of Geography, Institute of Science, Banaras Hindu University, Varanasi, Uttar Pradesh, 221005, India. adritatalapatra@gmail.com.
Environmental science and pollution research international
|January 7, 2026
概括
本综述详细介绍了17年来洪水监测和预测技术的进展. 机器学习模型在洪水预测方面显示出更高的准确性,改善了风险评估和缓解策略.
科学领域:
- 环境科学 环境科学
- 水文学的水文学
- 地理空间技术是什么
背景情况:
- 洪水对生命和财产构成重大威胁,需要先进的管理策略.
- 有效的洪水危险管理需要准确的监测和预测系统.
研究的目的:
- 从2007年到2024年,系统地审查洪水监测和预测技术的趋势和进展.
- 对洪水相关问题的脆弱性和风险评估方法进行比较.
主要方法:
- 按照系统性审查和元分析 (PRISMA) 准则的首选报告项目进行系统性文献审查.
- 分析监控技术,包括无人机,传感器,遥感和数字图像分析.
- 评估使用地理空间工具,GIS和机器学习 (ML) 算法 (如合体模型,ANN和CNN) 的预测技术.
主要成果:
- 监控技术增强空间风险可视化和影响感知.
- 与传统方法相比,机器学习模型,特别是集体ML,在洪水预测中显示出10-15%的更高准确性.
- 混合方法提供优质的实时预测,特别是在数据稀缺的地区.
结论:
- 最近的进展显著提高了洪水监测和预测能力.
- 机器学习和混合模型是提高洪水预测准确性和实时应用的关键.
- 本综述为研究人员和决策者提供了全面的资源,以改善洪水风险管理和适应性战略.
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