tenyearsaday / seims

Spatially Explicit Integrated Modeling System --- open-source, cross-platform, and high performance computation

SEIMS: A modular and parallelized watershed modeling framework

Copyright (C) 2013-2019 Lreis, IGSNRR, CAS, and NJNU. All rights reserved.

• SEIMS GitHub
• SEIMS Documentations
  • PDF version
  • Online versions (Will coming soon!)
    • English (powered by Doxygen), English without API references (powered by Gitbook), and Gitbook PDF
    • 简体中文（由Doxygen驱动）, 简体中文，不含 API 参考手册（由Gitbook驱动）, and Gitbook PDF

Build Status

• Windows-MSVC 2013-64bit with MSMPI-v8:
• Linux(Ubuntu xenial)-GCC-5.4.0 with OpenMPI-1.10.2:
• macOS(10.13.3)_AppleClang-10.0 with GDAL-2.3.1, mongo-c-driver-1.14.0, and OpenMPI-4.0.1:

Brief Introduction

The Spatially Explicit Integrated Modeling System (SEIMS), is a lightweight, modular, and parallelized watershed modeling framework for watershed modeling and scenario analysis.

SEIMS is mainly written by C++ with support of GDAL, Mongo-C-Driver, OpenMP and MPI, while Python is used for organizing the preprocessing, postprocessing, scenario analysis, etc. workflows. Theoretically, SEIMS could be compiled by common used compiler (e.g. MSVC 2010+, GCC 4.6+, and Intel C++ 12.0+) as 32-bit or 64-bit programs and run on any mainstream OS (e.g. Windows, Linux, and macOS).

SEIMS contains several module categories, include Hydrology, Erosion, Nutrient, Plant Growth, BMP Management, etc. Algorithms are integrated from SWAT, LISEM, WetSpa Extension, DHSVM, CASC2D, etc.

SEIMS is still being developing and any constructive feedback (issues or push requests) will be welcome and appreciated.

Selected peer-reviewed papers

Watershed modeling framework

• Zhu, L.-J., Liu, J., Qin, C.-Z., Zhu, A-X., 2019. A modular and parallelized watershed modeling framework. Environmental Modelling & Software 122, 104526. doi:10.1016/j.envsoft.2019.104526
• Liu, J., Zhu, A-X., Qin, C.-Z., Wu, H., Jiang, J., 2016. A two-level parallelization method for distributed hydrological models. Environmental Modelling & Software 80, 175-184.
• Liu, J., Zhu, A-X., Liu, Y., Zhu, T., Qin, C.-Z., 2014. A layered approach to parallel computing for spatially distributed hydrological modeling. Environmental Modelling & Software 51, 221-227.
• Liu, J., Zhu, A-X., Qin, C.-Z., 2013. Estimation of theoretical maximum speedup ratio for parallel computing of grid-based distributed hydrological models. Computers & Geosciences 60, 58–62.

BMPs scenario analysis

• Zhu, L.-J., Qin, C.-Z., Zhu, A-X., Liu, J., Wu, H., 2019. Effects of different spatial configuration units for the spatial optimization of watershed best management practice scenarios. Water, 11(2), 262.
• Qin, C.-Z., Gao, H.-R., Zhu, L.-J., Zhu, A-X., Liu, J.-Z., Wu, H., 2018. Spatial optimization of watershed best management practices based on slope position units. Journal of Soil and Water Conservation 73(5), 504-517.
• Wu, H., Zhu, A-X., Liu, J., Liu, Y., Jiang, J., 2018. Best Management Practices Optimization at Watershed Scale: Incorporating Spatial Topology among Fields. Water Resource Management 32, 155–177.

Support

SEIMS is an open source software. Support is provided through the Github issues and Email of present developers.

• SEIMS issues: https://github.com/lreis2415/SEIMS/issues
• Emails of present developers:
  • Dr. Liang-Jun Zhu ([email protected])
  • Asso. Prof. Junzhi Liu ([email protected])