Characterizing large‐scale preferential flow across Continental United States

Author:

Kocian Leah1,Mohanty Binayak P.1ORCID

Affiliation:

1. Biological and Agricultural Engineering Texas A&M University College Station Texas USA

Abstract

AbstractUnderstanding preferential flow (PF) at large scales is critical for improving land management and groundwater (GW) quality. However, limited knowledge of this process, due to soil surface heterogeneity and observational constraints, hampers progress. In this study, we propose estimating effective PF at remote sensing footprint scale (4–9 km) by examining its impact on soil moisture (SM) distribution and shallow groundwater (SGW) table fluctuations (depth 5 m). Effective PF encompasses macropore, funnel, and finger flow pathways influencing SGW table fluctuations. We compiled daily SGW observations (2019–2021) from 19 Continental United States (CONUS) sites through United States Geological Survey. Using inverse modeling in HYDRUS‐1D, SGW data, and climate hazards group infrared precipitation with station data precipitation, we inversely estimated soil hydraulic parameters of the dual‐porosity model (DPM) simulating vertical flow from soil surface to subsurface. Effective PF presence was inferred using three criteria: (1) daily precipitation equal to or exceeding the site‐specific average across multiple (calibration) years, (2) daily observed SGW table increase, and (3) daily difference between observed and DPM simulated SGW tables 50% of the site‐specific root mean square error. Leveraging optimized DPM parameters and associated soil texture, classified PF events, and soil moisture active passive (SMAP L3E) satellite‐based SM, a random forest algorithm with 10‐fold cross validation predicted large‐scale effective PF events. Results indicate seasonal dependence, with spring having the highest occurrence of PF events. The random forest model achieved 98% accuracy in predicting large‐scale PF events, with SMAP SM and saturated hydraulic conductivity (Ks) among the four most impactful variables. Our approach provides a soil hydraulic property, site characteristic, soil texture, and remote sensing‐based generalized tool to analyze large‐scale effective PF.

Funder

National Aeronautics and Space Administration

Publisher

Wiley

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3