Developing a comprehensive modeling framework to assess the impacts of agricultural activities on the fate and transport of sediment

Lee, Sanghyun

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https://hdl.handle.net/2142/114812 Copy

Description

Title

Developing a comprehensive modeling framework to assess the impacts of agricultural activities on the fate and transport of sediment

Author(s)

Lee, Sanghyun

Issue Date

2022-04-18

Director of Research (if dissertation) or Advisor (if thesis)

Chu, Maria L.

Doctoral Committee Chair(s)

Chu, Maria L.

Committee Member(s)

• Guzman, Jorge A.
• Schmidt, Arthur R.
• Garcia, Marcelo H.

Department of Study

Engineering Administration

Discipline

Agricultural & Biological Engr

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph. D.

Degree Level

Dissertation

Keyword(s)

• Soil erosion
• sediment transport
• erosion model
• watershed management
• no-till
• tillage
• WEPP
• distributed model
• physics-based model

Abstract

A sustainable agro-production system can be achieved by minimizing soil erosion, one of the major threats to soil fertility and water quality worldwide. However, the rate of soil erosion is significantly increased and accelerated by unsustainable agricultural activities. This process can adversely affect not only soil fertility and consequently food production but also can impose a threat to downstream water quality and infrastructure. It is estimated that 75 billion tons of topsoil are annually eroded worldwide from agricultural lands, exacerbating land degradation, soil fertility, sedimentation, and eutrophication in rivers and water bodies. Even though soil erosion can occur at various scales, many computer models estimate the erosion processes in lumped scales or have issues to simulate sediment transport at watershed scales. To advance our ability to predict soil erosion by water in agricultural landscapes, the development of a modeling platform that can integrate sediment production and transport processes at a scale that sufficiently captures the variability of these processes is needed. The overall goal of this study was to develop a modeling framework that can improve modeling capabilities to capture the spatio-temporal dynamics of soil erosion processes to better understand the impacts of agricultural activities on soil erosion at a watershed scale. To accomplish this general goal, four specific objectives were proposed in this research. First, a modeling framework for estimating soil loss at a field scale, and its sediment transport at the watershed scale, was developed. Using this modeling framework, the impacts of no-till practices on sediment production and yield were examined. Second, the impacts of spatially varied input datasets on sediment predictions were evaluated. Four models were developed with different types of precipitation datasets (e.g. multi-sensor precipitation vs. gauge network) and sediment sources (distributed vs. semi-distributed). Third, non-linear regression models for topsoil’s resistance to soil erosion were derived, considering different types of crops and management practices. These models were used to estimate the interrill and rill erodibilities, and critical shear stress, which are important parameters for predicting soil loss from the agricultural fields. Last, a modeling interface was developed to seamlessly integrate field-scale erosion processes and a sediment transport concept based on the advection-dispersion equation. The new modeling interface was tested using the Water Resources and Erosion (WRE) watersheds in the USDA-ARS Grazinglands Research Laboratory, El Reno, OK. Overall, the research presented in this dissertation enables the evaluation of field-scale processes, for instance management practices, and their regional-scale impacts, that become the basis of regulatory policies and decisions. This research also serves as a starting point for the establishment of advanced approaches to predict the complex dynamics of sediment production and transport at watershed scales, capturing the spatio-temporal variations of soil erosion by water to reduce uncertainties associated with sediment predictions and advance our understanding of the impacts of agricultural activities on soil erosion.

Graduation Semester

• 2022-10-11T15:34:33-05:00
• 2022-05

Type of Resource

text

Handle URL

https://hdl.handle.net/2142/114812

Copyright and License Information

Copyright 2022 Sanghyun Lee

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