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Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds
12:50

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Published on: September 26, 2017

Forecasting natural aquifer discharge using a numerical model and convolution.

Kevin G Boggs1, Gary S Johnson, Rob Van Kirk

  • 1Department of Geological Sciences, University of Idaho, Moscow, ID, 83844, USA.

Ground Water
|August 7, 2013
PubMed
Summary
This summary is machine-generated.

Forecasting natural aquifer discharge is possible by predicting groundwater sources and sinks. This method accurately predicts spring discharge using recharge components and initial aquifer heads.

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A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump
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Area of Science:

  • Hydrology
  • Hydrogeology
  • Water Resource Management

Background:

  • Understanding groundwater dynamics is crucial for predicting water availability.
  • Aquifer discharge is influenced by recharge sources, sinks, and head levels.

Purpose of the Study:

  • To develop and validate a procedure for forecasting natural aquifer discharge.
  • To determine the relative contributions of individual aquifer sources and sinks.

Main Methods:

  • Utilizing a numerical model and convolution to forecast monthly spring discharge.
  • Incorporating dominant aquifer recharge sources and initial aquifer heads (January levels).
  • Applying a jackknife procedure to estimate forecast performance.

Main Results:

  • A reliable 1-year monthly spring discharge forecast can be generated.
  • The forecast relies on dominant recharge sources and initial aquifer head conditions.
  • The forecasting procedure demonstrated good future performance with a Nash-Sutcliffe efficiency of 0.81.

Conclusions:

  • The developed procedure effectively forecasts natural aquifer discharge.
  • Accurate prediction of groundwater sources and sinks is key to forecasting discharge.
  • The method is applicable to real-world scenarios, as shown by the Eastern Snake Plain Aquifer case study.