A large dataset of fluvial hydraulic and geometry attributes derived from USGS field measurement records

IF 4.8 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Environmental Modelling & Software Pub Date : 2024-07-10 DOI:10.1016/j.envsoft.2024.106136
Seyed Mohammad Hassan Erfani , Mahdi Erfani , Sagy Cohen , Austin R.J. Downey , Erfan Goharian
{"title":"A large dataset of fluvial hydraulic and geometry attributes derived from USGS field measurement records","authors":"Seyed Mohammad Hassan Erfani ,&nbsp;Mahdi Erfani ,&nbsp;Sagy Cohen ,&nbsp;Austin R.J. Downey ,&nbsp;Erfan Goharian","doi":"10.1016/j.envsoft.2024.106136","DOIUrl":null,"url":null,"abstract":"<div><p>Accurate representation of river channel geometry is important for hydrologic and hydraulic modeling of fluvial systems. Often, channel geometry is estimated using simple rating curves that can be applied across various spatial scales. However, such methods are limited to power law relations that do not employ many potentially relevant catchment and river attributes. This paper introduce a new dataset, IFMHA (Inventory of Field Measurement of Hydraulic Attributes), to enable research studies on channel geometry and streamflow characteristics. IFMHA is derived from the National Water Information System (NWIS) site inventory for surface water field measurements and stream attributes from the National Hydrography Dataset (NHD). IFMHA includes 2,802,532 records from 10,050 sites (NWIS streamgaging stations). The dataset utility is demonstrated here by presenting a series of conceptual models for estimating channel geometry parameters (i.e., channel mean depth, channel maximum depth, wetted perimeter, and roughness) based on the available field attributes within IFMHA. Such a dataset and attributed channel geometry parameters can enhance the performance of operational flood forecasting frameworks (e.g. National Water Model) by providing more accurate initial conditions used in hydrologic and hydraulic routing models.</p></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"180 ","pages":"Article 106136"},"PeriodicalIF":4.8000,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Modelling & Software","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S136481522400197X","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

Abstract

Accurate representation of river channel geometry is important for hydrologic and hydraulic modeling of fluvial systems. Often, channel geometry is estimated using simple rating curves that can be applied across various spatial scales. However, such methods are limited to power law relations that do not employ many potentially relevant catchment and river attributes. This paper introduce a new dataset, IFMHA (Inventory of Field Measurement of Hydraulic Attributes), to enable research studies on channel geometry and streamflow characteristics. IFMHA is derived from the National Water Information System (NWIS) site inventory for surface water field measurements and stream attributes from the National Hydrography Dataset (NHD). IFMHA includes 2,802,532 records from 10,050 sites (NWIS streamgaging stations). The dataset utility is demonstrated here by presenting a series of conceptual models for estimating channel geometry parameters (i.e., channel mean depth, channel maximum depth, wetted perimeter, and roughness) based on the available field attributes within IFMHA. Such a dataset and attributed channel geometry parameters can enhance the performance of operational flood forecasting frameworks (e.g. National Water Model) by providing more accurate initial conditions used in hydrologic and hydraulic routing models.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
从美国地质调查局实地测量记录中提取的大量河道水力和几何属性数据集
准确表示河道几何形状对于河川系统的水文和水力模型制作非常重要。通常情况下,河道几何形状是通过可应用于各种空间尺度的简单额定曲线估算出来的。然而,这种方法仅限于幂律关系,没有采用许多潜在的相关流域和河流属性。本文介绍了一个新的数据集 IFMHA(水力属性实地测量清单),用于河道几何和溪流特征的研究。IFMHA 源自国家水信息系统 (NWIS) 的地表水实地测量站点清单和国家水文数据集 (NHD) 的溪流属性。IFMHA 包括来自 10,050 个站点(国家水信息系统测流站)的 2,802,532 条记录。在此,我们将根据 IFMHA 中的可用现场属性,提出一系列估算河道几何参数(即河道平均深度、河道最大深度、润湿周长和粗糙度)的概念模型,以展示该数据集的实用性。这样的数据集和归因的河道几何参数可以为水文和水力路由模型提供更准确的初始条件,从而提高运行中的洪水预报框架(如国家水模型)的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
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.
期刊最新文献
Probability analysis of shallow landslides in varying vegetation zones with random soil grain-size distribution Variable sensitivity analysis in groundwater level projections under climate change adopting a hybrid machine learning algorithm Taxonomy of purposes, methods, and recommendations for vulnerability analysis Canopy height Mapper: A google earth engine application for predicting global canopy heights combining GEDI with multi-source data Integrated STL-DBSCAN algorithm for online hydrological and water quality monitoring data cleaning
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1