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

Srinivas Rallapalli, Matt Drewitz, Joe Magner, Ajit Pratap Singh, Ashantha Goonetilleke
Author Information
  1. Srinivas Rallapalli: Birla Institute of Technology and Science, Pilani, Rajasthan, India; Department of Bioproducts and Biosystems Engineering, University of Minnesota, USA. Electronic address: r.srinivas@pilani.bits-pilani.ac.in.
  2. Matt Drewitz: Minnesota Board of Water and Soil Resources, USA. Electronic address: matt.drewitz@state.mn.us.
  3. Joe Magner: Department of Bioproducts and Biosystems Engineering, University of Minnesota, USA. Electronic address: jmagner@umn.edu.
  4. Ajit Pratap Singh: Birla Institute of Technology and Science, Pilani, Rajasthan, India. Electronic address: aps@pilani.bits-pilani.ac.in.
  5. Ashantha Goonetilleke: School of Civil and Environmental Engineering, Queensland University of Technology (QUT), Australia. Electronic address: a.goonetilleke@qut.edu.au.

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.

Keywords

MeSH Term

Agriculture
Cost-Benefit Analysis
Hydrology
Water Movements
Water Pollution
Water Quality

Word Cloud

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