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IPEAT+: A Built-In Optimization and Automatic Calibration Tool of SWAT+

Journal Article · · Water (Basel)
DOI:https://doi.org/10.3390/w11081681· OSTI ID:1577049
 [1];  [1];  [2];  [1];  [3];  [4];  [5];  [6];  [6];  [1];  [7];  [3];  [8];  [9];  [10];  [1];  [11];  [12];  [3];  [13]
  1. Texas A & M Univ., Temple, TX (United States). Blackland Research and Extension Center
  2. USDA-ARS, Temple, TX (United States). Grassland, Soil & Water Research Lab.
  3. Vrije Univ. Brussel, Brussels (Belgium). Dept. of Hydrology and Hydraulic Engineering
  4. Univ. of California, Davis, CA (United States). Dept. of Land, Air and Water Resources
  5. Chinese Academy of Sciences (CAS), Beijing (China). State Key Lab. of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences
  6. Beijing Normal Univ., Beijing (China). State Key Lab. of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science
  7. Univ. of Guelph, Guelph, ON (Canada)
  8. Auburn Univ., Auburn, AL (United States). School of Forestry and Wildlife Sciences
  9. Univ. of Maryland, College Park, MD (United States). Dept. of Environmental Sciences and Technology
  10. Kansas State Univ., Manhattan, KS (United States). Biological & Agricultural Engineering
  11. USEPA/ORD/NERL, Research Triangle Park, NC (United States)
  12. The Univ. of Newcastle, Callaghan (Australia). School of Engineering
  13. Pacific Northwest National Lab. (PNNL), College Park, MD (United States). Joint Global Change Research Inst.

For almost 30 years, the Soil and Water Assessment Tool (SWAT) has been successfully implemented to address issues around various scientific subjects in the world. On the other hand, it has been reaching to the limit of potential flexibility in further development by the current structure. The new generation SWAT, dubbed SWAT+, was released recently with entirely new coding features. SWAT+ is designed to have far more advanced functions and capacities to handle challenging watershed modeling tasks for hydrologic and water quality processes. However, it is still inevitable to conduct model calibration before the SWAT+ model is applied to engineering projects and research programs. The primary goal of this study is to develop an open-source, easy-to-operate automatic calibration tool for SWAT+, dubbed IPEAT+ (Integrated Parameter Estimation and Uncertainty Analysis Tool Plus). There are four major advantages: (i) Open-source code to general users; (ii) compiled and integrated directly with SWAT+ source code as a single executable; (iii) supported by the SWAT developer group; and, (iv) built with efficient optimization technique. The coupling work between IPEAT+ and SWAT+ is fairly simple, which can be conducted by users with minor efforts. IPEAT+ will be regularly updated with the latest SWAT+ revision. If users would like to integrate IPEAT+ with various versions of SWAT+, only few lines in the SWAT+ source code are required to be updated. IPEAT+ is the first automatic calibration tool integrated with SWAT+ source code. Users can take advantage of the tool to pursue more cutting-edge and forward-thinking scientific questions.

Research Organization:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
AC05-76RL01830
OSTI ID:
1577049
Report Number(s):
PNNL-SA--145096
Journal Information:
Water (Basel), Journal Name: Water (Basel) Journal Issue: 8 Vol. 11; ISSN WATEGH; ISSN 2073-4441
Publisher:
MDPICopyright Statement
Country of Publication:
United States
Language:
English

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Impact of model development, calibration and validation decisions on hydrological simulations in West Lake Erie Basin: Impact of Model Development Decisions on Streamflow Simulations journal July 2015
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Evaluating hydrologic responses to soil characteristics using SWAT model in a paired-watersheds in the Upper Blue Nile Basin journal April 2018
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Development and improvement of the simulation of woody bioenergy crops in the Soil and Water Assessment Tool (SWAT) journal December 2019
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Western Lake Erie Basin: Soft-data-constrained, NHDPlus resolution watershed modeling and exploration of applicable conservation scenarios journal November 2016
Linking watershed modeling and bacterial source tracking to better assess E. coli sources journal January 2019
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SWAT: Model Use, Calibration, and Validation journal January 2012
Simulating Establishment Periods of Switchgrass and Miscanthus in the Soil and Water Assessment Tool (SWAT) journal January 2017
Predicting Water Quality in Unmonitored Watersheds Using Artificial Neural Networks journal January 2010
The Role of Interior Watershed Processes in Improving Parameter Estimation and Performance of Watershed Models journal January 2014
Use of Decision Tables to Simulate Management in SWAT+ journal May 2018
Assessment of Optional Sediment Transport Functions via the Complex Watershed Simulation Model SWAT journal January 2017
Integrating multimedia models to assess nitrogen losses from the Mississippi River basin to the Gulf of Mexico journal January 2018

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