A technique for stream geometry estimation based on watershed morphometric characteristics

IF 4.8 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Orlando M. Viloria-Marimón , Felix L. Santiago-Collazo , Brian P. Bledsoe , Walter F. Silva-Araya
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引用次数: 0

Abstract

This study presents an approach for deriving stream geometry from watershed morphometric characteristics, addressing data scarcity for hydrologic and hydraulic modeling. The approach was tested in Puerto Rico and involves subdividing the study area into homogeneous regions and developing region-specific stream geometry predictive equations using ordinary least squares regression to correlate morphometric characteristics with the stream width and depth for a 2-year return period flow. The resulting equations were verified and validated by applying them to generate cross-sections for eight Storm Water Management Models. Results showed a correlation between drainage area and channel morphology, attributed to the presence of areal/shape characteristics in all the specific-region equations. Verification with an independent watershed sample demonstrated the predictive equations’ robustness and reliability. The study found that subdividing homogeneous regions improved accuracy compared to previous studies. Validation demonstrated up to 45.9 % (∼1.29 m3 s-1) differences in peak flow modeling, corroborating their applicability for modeling purposes.

Abstract Image

基于流域形态特征的河流几何估计技术
本研究提出了一种从流域形态特征中推导溪流几何形状的方法,解决了水文和水力建模的数据稀缺问题。该方法在波多黎各进行了测试,包括将研究区域细分为均匀区域,并使用普通最小二乘回归建立特定区域的河流几何预测方程,将形态特征与2年回复期的河流宽度和深度相关联。通过将所得方程应用于生成八个暴雨水管理模型的横截面,对所得方程进行了验证。结果表明,由于在所有特定区域方程中存在面积/形状特征,流域面积与河道形态之间存在相关性。独立流域样本验证了预测方程的稳健性和可靠性。研究发现,与之前的研究相比,细分均匀区域提高了准确性。验证表明峰值流量建模的差异高达45.9% (~ 1.29 m3 s-1),证实了它们在建模目的中的适用性。
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来源期刊
Environmental Modelling & Software
Environmental Modelling & Software 工程技术-工程:环境
CiteScore
9.30
自引率
8.20%
发文量
241
审稿时长
60 days
期刊介绍: Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.
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