Simulating Landscape Hydrologic Connectivity in a Precise Manner Using Hydro-Conditioning

Rallapalli Srinivas; Matt Drewitz; Joe Magner; Ajit Pratap Singh; Dhruv Kumar; Yashwant Bhaskar Katpatal

doi:10.1007/978-981-16-7857-8_17

Simulating Landscape Hydrologic Connectivity in a Precise Manner Using Hydro-Conditioning

Rallapalli Srinivas, Matt Drewitz, Joe Magner, Ajit Pratap Singh, Dhruv Kumar, Yashwant Bhaskar Katpatal

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

High resolution Light Detection and Ranging (LiDAR)-derived Digital Elevation Models (DEMs) have significantly enhanced hydrological modeling and agricultural planning. However, it is important to accurately simulate the landscape flow network by modifying the LiDAR derived DEM. Hydro-conditioning identifies false pools and depressions and places breach lines to ensure continuous flow through the surfaces such as bridges, culverts, and railroads. This study explores the variations in the criteria namely flow network, impeded flows, depression etc. which determine the finest locations of best management practices using watershed models. Study compares different levels of hydro-conditioned DEMs for the Plum Creek sub-watershed, Minnesota. Results indicate that both manual and automated ‘hDEMs’ facilitate field scale planning and practice siting to different degrees. Outcomes help in planning cost-effective precision agriculture activities.

Original language	English (US)
Title of host publication	Advances in Computational Modeling and Simulation
Editors	Rallapalli Srinivas, Rajesh Kumar, Mainak Dutta
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	209-215
Number of pages	7
ISBN (Print)	9789811678561
DOIs	https://doi.org/10.1007/978-981-16-7857-8_17
State	Published - 2022
Event	Global meet on Computational Modelling and Simulation, Recent Innovations, Challenges and Perspectives, 2020 - Virtual, Online Duration: Oct 16 2020 → Nov 7 2020

Publication series

Name	Lecture Notes in Mechanical Engineering
ISSN (Print)	2195-4356
ISSN (Electronic)	2195-4364

Conference

Conference	Global meet on Computational Modelling and Simulation, Recent Innovations, Challenges and Perspectives, 2020
City	Virtual, Online
Period	10/16/20 → 11/7/20

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Keywords

Agricultural planning
Hydro-conditioning
Hydrology
LiDAR

UN SDGs

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

Publisher link

10.1007/978-981-16-7857-8_17

Find It

Find It at U of M Libraries

Cite this

Srinivas, R., Drewitz, M., Magner, J., Singh, A. P., Kumar, D., & Katpatal, Y. B. (2022). Simulating Landscape Hydrologic Connectivity in a Precise Manner Using Hydro-Conditioning. In R. Srinivas, R. Kumar, & M. Dutta (Eds.), Advances in Computational Modeling and Simulation (pp. 209-215). (Lecture Notes in Mechanical Engineering). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-16-7857-8_17

Simulating Landscape Hydrologic Connectivity in a Precise Manner Using Hydro-Conditioning. / Srinivas, Rallapalli; Drewitz, Matt; Magner, Joe et al.
Advances in Computational Modeling and Simulation. ed. / Rallapalli Srinivas; Rajesh Kumar; Mainak Dutta. Springer Science and Business Media Deutschland GmbH, 2022. p. 209-215 (Lecture Notes in Mechanical Engineering).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Srinivas, R, Drewitz, M, Magner, J, Singh, AP, Kumar, D & Katpatal, YB 2022, Simulating Landscape Hydrologic Connectivity in a Precise Manner Using Hydro-Conditioning. in R Srinivas, R Kumar & M Dutta (eds), Advances in Computational Modeling and Simulation. Lecture Notes in Mechanical Engineering, Springer Science and Business Media Deutschland GmbH, pp. 209-215, Global meet on Computational Modelling and Simulation, Recent Innovations, Challenges and Perspectives, 2020, Virtual, Online, 10/16/20. https://doi.org/10.1007/978-981-16-7857-8_17

Srinivas R, Drewitz M, Magner J, Singh AP, Kumar D, Katpatal YB. Simulating Landscape Hydrologic Connectivity in a Precise Manner Using Hydro-Conditioning. In Srinivas R, Kumar R, Dutta M, editors, Advances in Computational Modeling and Simulation. Springer Science and Business Media Deutschland GmbH. 2022. p. 209-215. (Lecture Notes in Mechanical Engineering). doi: 10.1007/978-981-16-7857-8_17

Srinivas, Rallapalli ; Drewitz, Matt ; Magner, Joe et al. / Simulating Landscape Hydrologic Connectivity in a Precise Manner Using Hydro-Conditioning. Advances in Computational Modeling and Simulation. editor / Rallapalli Srinivas ; Rajesh Kumar ; Mainak Dutta. Springer Science and Business Media Deutschland GmbH, 2022. pp. 209-215 (Lecture Notes in Mechanical Engineering).

@inproceedings{8b585720cf7f4932becb3794ad337a2b,

title = "Simulating Landscape Hydrologic Connectivity in a Precise Manner Using Hydro-Conditioning",

abstract = "High resolution Light Detection and Ranging (LiDAR)-derived Digital Elevation Models (DEMs) have significantly enhanced hydrological modeling and agricultural planning. However, it is important to accurately simulate the landscape flow network by modifying the LiDAR derived DEM. Hydro-conditioning identifies false pools and depressions and places breach lines to ensure continuous flow through the surfaces such as bridges, culverts, and railroads. This study explores the variations in the criteria namely flow network, impeded flows, depression etc. which determine the finest locations of best management practices using watershed models. Study compares different levels of hydro-conditioned DEMs for the Plum Creek sub-watershed, Minnesota. Results indicate that both manual and automated {\textquoteleft}hDEMs{\textquoteright} facilitate field scale planning and practice siting to different degrees. Outcomes help in planning cost-effective precision agriculture activities.",

keywords = "Agricultural planning, Hydro-conditioning, Hydrology, LiDAR",

author = "Rallapalli Srinivas and Matt Drewitz and Joe Magner and Singh, \{Ajit Pratap\} and Dhruv Kumar and Katpatal, \{Yashwant Bhaskar\}",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; Global meet on Computational Modelling and Simulation, Recent Innovations, Challenges and Perspectives, 2020 ; Conference date: 16-10-2020 Through 07-11-2020",

year = "2022",

doi = "10.1007/978-981-16-7857-8\_17",

language = "English (US)",

isbn = "9789811678561",

series = "Lecture Notes in Mechanical Engineering",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "209--215",

editor = "Rallapalli Srinivas and Rajesh Kumar and Mainak Dutta",

booktitle = "Advances in Computational Modeling and Simulation",

address = "Germany",

}

TY - GEN

T1 - Simulating Landscape Hydrologic Connectivity in a Precise Manner Using Hydro-Conditioning

AU - Srinivas, Rallapalli

AU - Drewitz, Matt

AU - Magner, Joe

AU - Singh, Ajit Pratap

AU - Kumar, Dhruv

AU - Katpatal, Yashwant Bhaskar

PY - 2022

Y1 - 2022

N2 - High resolution Light Detection and Ranging (LiDAR)-derived Digital Elevation Models (DEMs) have significantly enhanced hydrological modeling and agricultural planning. However, it is important to accurately simulate the landscape flow network by modifying the LiDAR derived DEM. Hydro-conditioning identifies false pools and depressions and places breach lines to ensure continuous flow through the surfaces such as bridges, culverts, and railroads. This study explores the variations in the criteria namely flow network, impeded flows, depression etc. which determine the finest locations of best management practices using watershed models. Study compares different levels of hydro-conditioned DEMs for the Plum Creek sub-watershed, Minnesota. Results indicate that both manual and automated ‘hDEMs’ facilitate field scale planning and practice siting to different degrees. Outcomes help in planning cost-effective precision agriculture activities.

AB - High resolution Light Detection and Ranging (LiDAR)-derived Digital Elevation Models (DEMs) have significantly enhanced hydrological modeling and agricultural planning. However, it is important to accurately simulate the landscape flow network by modifying the LiDAR derived DEM. Hydro-conditioning identifies false pools and depressions and places breach lines to ensure continuous flow through the surfaces such as bridges, culverts, and railroads. This study explores the variations in the criteria namely flow network, impeded flows, depression etc. which determine the finest locations of best management practices using watershed models. Study compares different levels of hydro-conditioned DEMs for the Plum Creek sub-watershed, Minnesota. Results indicate that both manual and automated ‘hDEMs’ facilitate field scale planning and practice siting to different degrees. Outcomes help in planning cost-effective precision agriculture activities.

KW - Agricultural planning

KW - Hydro-conditioning

KW - Hydrology

KW - LiDAR

UR - http://www.scopus.com/inward/record.url?scp=85125323362&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85125323362&partnerID=8YFLogxK

U2 - 10.1007/978-981-16-7857-8_17

DO - 10.1007/978-981-16-7857-8_17

M3 - Conference contribution

AN - SCOPUS:85125323362

SN - 9789811678561

T3 - Lecture Notes in Mechanical Engineering

SP - 209

EP - 215

BT - Advances in Computational Modeling and Simulation

A2 - Srinivas, Rallapalli

A2 - Kumar, Rajesh

A2 - Dutta, Mainak

PB - Springer Science and Business Media Deutschland GmbH

T2 - Global meet on Computational Modelling and Simulation, Recent Innovations, Challenges and Perspectives, 2020

Y2 - 16 October 2020 through 7 November 2020

ER -

Simulating Landscape Hydrologic Connectivity in a Precise Manner Using Hydro-Conditioning

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Publisher link

Find It

Other files and links

Fingerprint

Cite this