New Generation of SMODERP2D Soil Erosion Model Landa, Jebek, Kavka, - - PowerPoint PPT Presentation

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New Generation of SMODERP2D Soil Erosion Model Landa, Jebek, Kavka, - - PowerPoint PPT Presentation

Dec 14, 2023 1.18k likes •1.34k views

New Generation of SMODERP2D Soil Erosion Model Landa, Jebek, Kavka, Peek HyGIS a P 2019 1 Introduction Runoff-soil erosion physically-based distributed episodic model Calculation and prediction processes at agricultural

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SLIDE 1

New Generation of SMODERP2D Soil Erosion Model

Landa, Jeřábek, Kavka, Pešek

HyGIS a ŽP 2019

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SLIDE 2

Introduction

  • Runoff-soil erosion physically-based distributed episodic model
  • Calculation and prediction processes at agricultural areas and small watersheds
  • History overview

○ Long-term running project driven by the Department of Landscape Water Conservation at the Czech Technical University in Prague ○ At the beginning developed as a surface runoff simulated by profile model (1D) ○ Later redesigned using spatially distributed method → SMODERP2D

  • Ongoing development on GitHub https://github.com/storm-fsv-cvut/smoderp2d

○ Open source, GNU GPL licence

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SLIDE 3

SMODERP2D Model

  • GIS based model
  • Cell by cell mass balance information
  • Kinematic wave approach for sheet flow
  • Explicit solution of time discretization
  • Rill development implemented in the model

Model structure:

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CPU parallelization strategy (planned)

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SLIDE 4

SMODERP2D Model

  • Rill development implemented in the model
  • Rills approximated with rectangular cross section

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SLIDE 5

Ongoing development

  • Clear separation of Data Preparation and

Model Computation packages

  • Complete refactoring, esp. Data Preparation

package

  • Data preparation (GIS-related part) can be

provided by various software packages (ArcGIS 10.x/Pro, GRASS GIS, QGIS)

  • Python 3 support introduced
  • Model computation parallelization

experiments (ongoing, experimental)

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SLIDE 6

Ongoing development | GIS providers

Toolbox for ArcGIS 10.x / Pro

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SLIDE 7

Ongoing development | GIS providers

Addons for GRASS GIS 7.7+

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SLIDE 8

Ongoing development | GIS providers

Plugin for QGIS 3.4+

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SLIDE 9

Ongoing development - parallelization experiments

  • To reduce the computation time
  • For both CPU and GPU
  • Mathematical operations rewritten to TensorFlow (2.0) or NumPy

○ Graph-based computations (independent math operations run in parallel)

  • Loop-based computations rewritten to matrix-based ones
  • Still under development (!)

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SLIDE 10

Results of experimental parallelized branch

  • Test data: 197 MB

○ Test with RAM 15 GB

■ Single CPU (AMD Ryzen 7 1700 Eight Core Processor, 1373 MHz, cache size 512 KB): 12 809 s ■ GPU (GeForce GTX 1060 3GB, clock 33 MHz, virtual memory 3016 MiB): 7 560 s ○

Tests with RAM 251 GB (JRC)

■ Single CPU (Intel Xeon CPU E5-2630 v4 @ 2.20 GHz, 2423 MHz, cache size 25600 KB): 10 637 s ■ GPUs (4x GeForce GTX 1080 Ti, clock 33 MHz, virtual memory 11178 MiB): 10 583 s

  • Test data: 62 KB

○ Test with RAM 15 GB

■ Single CPU (AMD Ryzen 7 1700 Eight Core Processor, 1373 MHz, cache size 512 KB): 0.2 s ■ GPU (GeForce GTX 1060 3GB, clock 33 MHz, virtual memory 3016 MiB): 4.0 s ○

Tests with RAM 251 GB (JRC)

■ Single CPU (Intel Xeon CPU E5-2630 v4 @ 2.20 GHz, 2423 MHz, cache size 25600 KB): 2.8 s ■ GPUs (4x GeForce GTX 1080 Ti, clock 33 MHz, virtual memory 11178 MiB): 0.2 s

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Conclusion

  • Ongoing development

○ Release planned for Q1/2020

  • Join us on GitHub

○ Report issues

Thanks for attention!

The research has been supported by the research grants TJ01000270, QK1910029, and internal CTU grant SGS17/173/OHK1/T3/11.

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