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In concrete preparation, the quality of water is paramount as it affects the strength and durability of the concrete. Potable water is usually preferred; however, it must not have excessive sodium or potassium to prevent compromising the concrete's integrity. Water quality is typically evaluated based on impurities such as dissolved solids, chlorides, and sulfates, and its pH value is ideally between 6 and 8. Even slightly acidic natural water may be acceptable unless it contains harmful...
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Watershed Planning within a Quantitative Scenario Analysis Framework
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HSPF-based watershed-scale water quality modeling and uncertainty analysis.

Maryam Roostaee1, Zhiqiang Deng2

  • 1Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA, 70803, USA.

Environmental Science and Pollution Research International
|February 6, 2019
PubMed
Summary

Digital Elevation Model (DEM) resolution significantly impacts watershed simulations. Coarser resolutions and resampling increase errors, with sediment being most sensitive, guiding water quality management plans.

Keywords:
BASINSDEM resamplingDEM resolutionGLUESensitivity analysisUncertainty analysis

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Area of Science:

  • Hydrology
  • Water Quality Modeling
  • Geospatial Analysis

Background:

  • Digital Elevation Models (DEMs) are crucial for watershed simulations.
  • DEM resolution and resampling introduce uncertainties affecting hydrological and water quality predictions.
  • Understanding these uncertainties is vital for effective watershed management.

Purpose of the Study:

  • To quantify uncertainties in watershed-scale flow and water quality simulations due to DEM resolution and resampling.
  • To compare parameter-induced uncertainties with input data uncertainties.
  • To assess the sensitivity of different water quality parameters to DEM variations.

Main Methods:

  • Utilized the Better Assessment Science Integrating Point and Nonpoint Sources/Hydrological Simulation Program Fortran (BASINS/HSPF) watershed modeling system.
  • Conducted simulations across two watersheds using original and resampled DEMs of varying resolutions (3.5m to 100m).
  • Employed the Generalized Likelihood Uncertainty Estimation (GLUE) approach for parameter uncertainty quantification.

Main Results:

  • Simulation errors increased with coarser DEM resolutions and resampling.
  • Mild-slope watersheds exhibited substantially higher errors (up to 10x) than steep-slope watersheds.
  • Sediment concentration was most sensitive (250% NRMSE), while nitrate (NO3) was least sensitive (11% NRMSE) to DEM resolution changes.

Conclusions:

  • DEM resolution and resampling significantly influence watershed simulation accuracy.
  • Parameter uncertainties often exceed resolution-induced uncertainties, particularly for nitrate and phosphorus.
  • Findings offer critical insights for water quality management and watershed restoration planning.