Hydro-conditioning: Advanced approaches for cost-effective water quality management in agricultural watersheds

Srinivas Rallapalli; Matt Drewitz; Joe Magner; Ajit Pratap Singh; Ashantha Goonetilleke

doi:10.1016/j.watres.2022.118647

Hydro-conditioning: Advanced approaches for cost-effective water quality management in agricultural watersheds

Srinivas Rallapalli, Matt Drewitz, Joe Magner, Ajit Pratap Singh, Ashantha Goonetilleke

Bioproducts and Biosystems Engineering

Research output: Contribution to journal › Article › peer-review

12 Scopus citations

Abstract

Accurate simulation of landscape hydrological connectivity is pivotal for planning practices required for treating agricultural farm pollution. This study assesses the role of an advanced geospatial approach, namely, ‘hydro-conditioning’ employed for modifying Digital Elevation Models, termed hDEMs to replicate landscape hydrology by simulating continuous downslope flow through drainage structures such as bridges and culverts. The capabilities of manual and automated hDEMs in delineating optimal locations and water treatment potential of Best Management Practices (BMPs) in a typical agricultural watershed were evaluated. Parallel processing of both hDEMs revealed that ‘ground truthing’ plays a critical role in the accurate placement of breach lines for allowing water movement through digitally elevated surfaces. Outcomes guide the practitioners in selecting appropriate hDEM (manual or automated) depending on the complexity of modeled hydrological pathways, which is essential for planning BMPs in a cost-effective manner at different spatial scales. Modeling results show that hDEMs greatly influence hydrological connectivity, catchment boundaries, BMP locations, treatment capacities, and related costs. The accuracy of hDEMs was verified using a robust sub-basin scale validation approach. The study recommends a hybrid approach for utilizing the strengths of both, automated and manual hDEMs for efficient agricultural farm pollution in an economical manner.

Original language	English (US)
Article number	118647
Journal	Water Research
Volume	220
DOIs	https://doi.org/10.1016/j.watres.2022.118647
State	Published - Jul 15 2022

Bibliographical note

Funding Information:
The authors thank University of Minnesota, and Board of Water and Soil Resources, Minnesota, U.S.A. and Birla Institute of Technology and Science (BITS) Pilani, India for providing necessary funding and facilities to carry out this research work. BITS provided funds through ‘Research Initiation Grant’ (2020/156). The relevant datasets have been procured from MNDNR, MPCA, USDA, and U S EPA. Authors appreciate BWSR and Houston Engineering Inc. Minnesota for providing the software PTMApp. In addition, authors are especially thankful to Dr. Brian Gelder, Iowa State University and Houston Engineering Inc. for providing the procedures to develop automated and manual ‘hDEM’, respectively.

Publisher Copyright:
© 2022 Elsevier Ltd

Keywords

Agricultural pollution
Best Management Practices
Hydro-conditioning
Water quality
Watershed modeling

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.watres.2022.118647

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title = "Hydro-conditioning: Advanced approaches for cost-effective water quality management in agricultural watersheds",

abstract = "Accurate simulation of landscape hydrological connectivity is pivotal for planning practices required for treating agricultural farm pollution. This study assesses the role of an advanced geospatial approach, namely, {\textquoteleft}hydro-conditioning{\textquoteright} employed for modifying Digital Elevation Models, termed hDEMs to replicate landscape hydrology by simulating continuous downslope flow through drainage structures such as bridges and culverts. The capabilities of manual and automated hDEMs in delineating optimal locations and water treatment potential of Best Management Practices (BMPs) in a typical agricultural watershed were evaluated. Parallel processing of both hDEMs revealed that {\textquoteleft}ground truthing{\textquoteright} plays a critical role in the accurate placement of breach lines for allowing water movement through digitally elevated surfaces. Outcomes guide the practitioners in selecting appropriate hDEM (manual or automated) depending on the complexity of modeled hydrological pathways, which is essential for planning BMPs in a cost-effective manner at different spatial scales. Modeling results show that hDEMs greatly influence hydrological connectivity, catchment boundaries, BMP locations, treatment capacities, and related costs. The accuracy of hDEMs was verified using a robust sub-basin scale validation approach. The study recommends a hybrid approach for utilizing the strengths of both, automated and manual hDEMs for efficient agricultural farm pollution in an economical manner.",

keywords = "Agricultural pollution, Best Management Practices, Hydro-conditioning, Water quality, Watershed modeling",

author = "Srinivas Rallapalli and Matt Drewitz and Joe Magner and Singh, {Ajit Pratap} and Ashantha Goonetilleke",

note = "Funding Information: The authors thank University of Minnesota, and Board of Water and Soil Resources, Minnesota, U.S.A. and Birla Institute of Technology and Science (BITS) Pilani, India for providing necessary funding and facilities to carry out this research work. BITS provided funds through {\textquoteleft}Research Initiation Grant{\textquoteright} (2020/156). The relevant datasets have been procured from MNDNR, MPCA, USDA, and U S EPA. Authors appreciate BWSR and Houston Engineering Inc. Minnesota for providing the software PTMApp. In addition, authors are especially thankful to Dr. Brian Gelder, Iowa State University and Houston Engineering Inc. for providing the procedures to develop automated and manual {\textquoteleft}hDEM{\textquoteright}, respectively. Publisher Copyright: {\textcopyright} 2022 Elsevier Ltd",

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doi = "10.1016/j.watres.2022.118647",

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AU - Rallapalli, Srinivas

AU - Drewitz, Matt

AU - Magner, Joe

AU - Singh, Ajit Pratap

AU - Goonetilleke, Ashantha

N1 - Funding Information: The authors thank University of Minnesota, and Board of Water and Soil Resources, Minnesota, U.S.A. and Birla Institute of Technology and Science (BITS) Pilani, India for providing necessary funding and facilities to carry out this research work. BITS provided funds through ‘Research Initiation Grant’ (2020/156). The relevant datasets have been procured from MNDNR, MPCA, USDA, and U S EPA. Authors appreciate BWSR and Houston Engineering Inc. Minnesota for providing the software PTMApp. In addition, authors are especially thankful to Dr. Brian Gelder, Iowa State University and Houston Engineering Inc. for providing the procedures to develop automated and manual ‘hDEM’, respectively. Publisher Copyright: © 2022 Elsevier Ltd

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N2 - Accurate simulation of landscape hydrological connectivity is pivotal for planning practices required for treating agricultural farm pollution. This study assesses the role of an advanced geospatial approach, namely, ‘hydro-conditioning’ employed for modifying Digital Elevation Models, termed hDEMs to replicate landscape hydrology by simulating continuous downslope flow through drainage structures such as bridges and culverts. The capabilities of manual and automated hDEMs in delineating optimal locations and water treatment potential of Best Management Practices (BMPs) in a typical agricultural watershed were evaluated. Parallel processing of both hDEMs revealed that ‘ground truthing’ plays a critical role in the accurate placement of breach lines for allowing water movement through digitally elevated surfaces. Outcomes guide the practitioners in selecting appropriate hDEM (manual or automated) depending on the complexity of modeled hydrological pathways, which is essential for planning BMPs in a cost-effective manner at different spatial scales. Modeling results show that hDEMs greatly influence hydrological connectivity, catchment boundaries, BMP locations, treatment capacities, and related costs. The accuracy of hDEMs was verified using a robust sub-basin scale validation approach. The study recommends a hybrid approach for utilizing the strengths of both, automated and manual hDEMs for efficient agricultural farm pollution in an economical manner.

AB - Accurate simulation of landscape hydrological connectivity is pivotal for planning practices required for treating agricultural farm pollution. This study assesses the role of an advanced geospatial approach, namely, ‘hydro-conditioning’ employed for modifying Digital Elevation Models, termed hDEMs to replicate landscape hydrology by simulating continuous downslope flow through drainage structures such as bridges and culverts. The capabilities of manual and automated hDEMs in delineating optimal locations and water treatment potential of Best Management Practices (BMPs) in a typical agricultural watershed were evaluated. Parallel processing of both hDEMs revealed that ‘ground truthing’ plays a critical role in the accurate placement of breach lines for allowing water movement through digitally elevated surfaces. Outcomes guide the practitioners in selecting appropriate hDEM (manual or automated) depending on the complexity of modeled hydrological pathways, which is essential for planning BMPs in a cost-effective manner at different spatial scales. Modeling results show that hDEMs greatly influence hydrological connectivity, catchment boundaries, BMP locations, treatment capacities, and related costs. The accuracy of hDEMs was verified using a robust sub-basin scale validation approach. The study recommends a hybrid approach for utilizing the strengths of both, automated and manual hDEMs for efficient agricultural farm pollution in an economical manner.

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KW - Best Management Practices

KW - Hydro-conditioning

KW - Water quality

KW - Watershed modeling

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Hydro-conditioning: Advanced approaches for cost-effective water quality management in agricultural watersheds

Abstract

Bibliographical note

Keywords

UN SDGs

Publisher link

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